Global Business:
Concepts, Methodologies, Tools and Applications Information Resources Management Association USA
Senior Editorial Director: Director of Book Publications: Editorial Director: Acquisitions Editor: Development Editor: Production Editor: Content Systems Analyst: Assistant Production Editor: Typesetters: Print Coordinator: Cover Design:
Kristin Klinger Julia Mosemann Lindsay Johnston Erika Carter Chris Wozniak Sean Woznicki Devvin Earnest Deanna Zombro Michael Brehm, Keith Glazewski, Natalie Pronio, Jennifer Roamanchak, Milan Vracarich, Jr.
Jamie Snavely Nick Newcomer
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Global business : concepts, methodologies, tools and applications / Information Resources Management Association, editor. p. cm. Includes bibliographical references and index. Summary: "This multi-volume reference examines critical issues and emerging trends in global business, with topics ranging from managing new information technology in global business operations to ethics and communication strategies"--Provided by publisher. ISBN 978-1-60960-587-2 (hardcover) -- ISBN 978-1-60960-588-9 (ebook) 1. International business enterprises. 2. Electronic commerce. I. Information Resources Management Association. HD62.4.G5355 2011 658'.049--dc22 2011016269 British Cataloguing in Publication Data A Cataloguing in Publication record for this book is available from the British Library. All work contributed to this book set is original material. The views expressed in this book are those of the authors, but not necessarily of the publisher.
Editor-in-Chief
Mehdi Khosrow-Pour, DBA Editor-in-Chief Contemporary Research in Information Science and Technology, Book Series
Associate Editors Steve Clarke University of Hull, UK Murray E. Jennex San Diego State University, USA Annie Becker Florida Institute of Technology USA Ari-Veikko Anttiroiko University of Tampere, Finland
Editorial Advisory Board Sherif Kamel American University in Cairo, Egypt In Lee Western Illinois University, USA Jerzy Kisielnicki Warsaw University, Poland Keng Siau University of Nebraska-Lincoln, USA Amar Gupta Arizona University, USA Craig van Slyke University of Central Florida, USA John Wang Montclair State University, USA Vishanth Weerakkody Brunel University, UK
Additional Research Collections found in the “Contemporary Research in Information Science and Technology” Book Series Data Mining and Warehousing: Concepts, Methodologies, Tools, and Applications John Wang, Montclair University, USA • 6-volume set • ISBN 978-1-60566-056-1 Electronic Business: Concepts, Methodologies, Tools, and Applications In Lee, Western Illinois University • 4-volume set • ISBN 978-1-59904-943-4 Electronic Commerce: Concepts, Methodologies, Tools, and Applications S. Ann Becker, Florida Institute of Technology, USA • 4-volume set • ISBN 978-1-59904-943-4 Electronic Government: Concepts, Methodologies, Tools, and Applications Ari-Veikko Anttiroiko, University of Tampere, Finland • 6-volume set • ISBN 978-1-59904-947-2 Knowledge Management: Concepts, Methodologies, Tools, and Applications Murray E. Jennex, San Diego State University, USA • 6-volume set • ISBN 978-1-59904-933-5 Information Communication Technologies: Concepts, Methodologies, Tools, and Applications Craig Van Slyke, University of Central Florida, USA • 6-volume set • ISBN 978-1-59904-949-6 Intelligent Information Technologies: Concepts, Methodologies, Tools, and Applications Vijayan Sugumaran, Oakland University, USA • 4-volume set • ISBN 978-1-59904-941-0 Information Security and Ethics: Concepts, Methodologies, Tools, and Applications Hamid Nemati, The University of North Carolina at Greensboro, USA • 6-volume set • ISBN 978-1-59904-937-3 Medical Informatics: Concepts, Methodologies, Tools, and Applications Joseph Tan, Wayne State University, USA • 4-volume set • ISBN 978-1-60566-050-9 Mobile Computing: Concepts, Methodologies, Tools, and Applications David Taniar, Monash University, Australia • 6-volume set • ISBN 978-1-60566-054-7 Multimedia Technologies: Concepts, Methodologies, Tools, and Applications Syed Mahbubur Rahman, Minnesota State University, Mankato, USA • 3-volume set • ISBN 978-1-60566-054-7 Virtual Technologies: Concepts, Methodologies, Tools, and Applications Jerzy Kisielnicki, Warsaw University, Poland • 3-volume set • ISBN 978-1-59904-955-7
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List of Contributors
Acosta, Pedro Soto \ University of Murcia, Spain .......................................................................... 1615 Adekola, O. D. \ Babcock University, Nigeria . ............................................................................... 1438 Adeniji, Anthonia Adenike \ Covenant University, Nigeria ........................................................... 1868 Aggestam, Lena \ University of Skövde, Sweden .............................................................................. 206 Ahmed, Nazim U. \ Ball State University, USA .............................................................................. 1662 Ahonen, Aki \ OP Bank Group Central Cooperative, Finland ......................................................... 911 Al Rabea, Adnan I. \ Al Balqa Applied University, Jordan ............................................................ 2360 Alas, Ruth \ Estonian Business School, Estonia . ............................................................................ 1044 Alawneh, Ali \ Philadelphia University, Jordan .............................................................................. 1055 AlBulushi, Ahlam Abdullah \ Sultanate of Oman .......................................................................... 1087 Al-Gharbi, Khamis \ Sultan Qaboos University, Sultanate of Oman ............................................. 1087 Alqatawna, Ja’far \ Sheffield Hallam University, UK .................................................................... 2102 Al-Refai, Hasan \ Philadelphia University, Jordan . ....................................................................... 1055 Amjad, Urooj \ London School of Economics, UK ......................................................................... 2034 Anthopoulos, Leonidas G. \ Hellenic Ministry of Foreign Affairs, Greece . .................................... 294 Arjonilla-Domínguez, Sixto Jesús \ Freescale Semiconductor, Inc., Spain ....................................... 39 Assaf, Wael \ Scuola Superiore ISUFI - University of Salento, Italy .............................................. 1375 Athanasiadou, Christina \ Ernst & Young, Greece .......................................................................... 888 Averweg, Udo Richard \ eThekwini Municipality and University of KwaZulu-Natal, South Africa .......................................................................................................................................... 1858 Babatope, Ihuoma \ Delta State University, Nigeria ...................................................................... 2420 Bachani, Jyoti \ University of Redlands, USA ................................................................................... 150 Badr, Youakim \ INSA-Lyon, France . ............................................................................................... 670 Baek, John Y. \ Center for Advancement of Informal Science Education, USA . .............................. 529 Baker, Valerie \ University of Wollongong, Australia ..................................................................... 1788 Baker, Paul M.A. \ Georgia Institute of Technology, USA .............................................................. 2112 Bakke, John Willy \ Telenor Research and Innovation, Norway .................................................... 1948 Bandara, Arosha \ The Open University, UK . .................................................................................. 750 Batiha, Khaldoun \ Philadelphia University, Jordan . .................................................................... 1055 Baumeister, Alexander \ Saarland University, Germany . .................................................... 1588, 1644 Beaudry, Anne \ Concordia University, Canada ............................................................................. 1338 Beck, Phil \ Southwest Airlines, USA ............................................................................................... 1445 Berkin, Esin Ertemsir \ Yildiz Technical University, Turkey .......................................................... 1633 Biggert, Timothy \ IBM Global Business Services, USA .................................................................. 311 Biggiero, Lucio \ University of L’Aquila, Italy ................................................................................ 2525
Birchall, David W. \ Henley Business School, UK .......................................................................... 1396 Blumberg, Baruch S. \ Fox Chase Cancer Center, USA . ............................................................... 1201 Bocarnea, Mihai C. \ Regent University, USA ................................................................................ 1562 Borgman (Hans), H.P. \ University of Leiden, The Netherlands .................................................... 2493 Braun, Patrice \ University of Ballarat, Australia .......................................................................... 1978 Bricout, John C. \ University of Central Florida, USA . ................................................................. 2112 Btoush, Mohammad Hjouj \ Sheffield Hallam University, UK . .................................................... 2102 Burakova-Lorgnier, Marina \ ECE-INSEEC Research Laboratory, University of Montesquieu Bordeaux 4, France .................................................................................................................... 1896 Calo, Seraphin B. \ IBM Research, USA ........................................................................................... 750 Campos, Eduardo Bueno \ University of Madrid, Spain ................................................................. 418 Capó-Vicedo, Josep \ Universitat Politècnica de València, Spain .................................................. 1475 Carayon, Pascale \ University of Wisconsin-Madison, USA ........................................................... 1879 Casado-Lumbreras, Cristina \ Universidad Complutense, Madrid, Spain ..................................... 627 Caswell, Nathan S. \ Janus Consulting, USA .................................................................................. 2275 Chamakiotis, Petros \ University of Bath, UK ................................................................................ 1688 Chan, Cliff E. L. \ Mitsubishi Electric, Singapore .......................................................................... 1023 Chang, Yuan-Chieh \ National Tsing Hua University, Taiwan ....................................................... 1796 Chen, Ye-Sho \ Louisiana State University, USA . ....................................................................... 47, 809 Chen, Te Fu \ Graduate Institute of Central Asia, Chin Yung University, Taiwan & Lunghwa University of Science and Technology, Taiwan ................................................................ 1109, 2202 Chi, Hui-Ru \ National Changhua University of Education, Taiwan . ............................................ 1796 Chugh, Ritesh \ CQUniversity Melbourne, Australia ..................................................................... 2135 Claver-Cortés, Enrique \ University of Alicante, Spain ................................................................... 929 Colomo-Palacios, Ricardo \ Universidad Carlos III de Madrid, Spain ......................... 403, 627, 1615 Coltman, Tim \ University of Wollongong, Australia . .................................................................... 1788 Cox, Sharon \ Birmingham City University, UK ............................................................................... 732 Craven, Robert \ Imperial College, UK ............................................................................................ 750 Croteau, Anne-Marie \ Concordia University, Canada . ................................................................ 1338 Dai, Jie \ Huazhong University of Science and Technology, China ................................................. 1149 Datta, B. \ Indian Institute of Technology, India .............................................................................. 2331 Davies, John \ Victoria University of Wellington, New Zealand ..................................................... 2044 De, S. K. \ Indian Institute of Technology, India .............................................................................. 2331 de Juana-Espinosa, Susana \ University of Alicante, Spain ............................................................. 967 De Maggio, Marco \ University of Salento, Italy ............................................................................ 2380 Dekker, Ronald \ Delft University of Technology, The Netherlands & ReflecT at Tilburg University, The Netherlands ....................................................................................................... 1603 Del Vecchio, Pasquale \ University of Salento, Italy ....................................................................... 2380 Dong, Dong \ Hebei Normal University, China ................................................................................... 83 Drost, Adam W. \ eCareerFit.com, USA ......................................................................................... 2087 Duin, Heiko \ BIBA Bremer Institut für Produktion und Logistik GmbH, Germany ......................... 254 Durbin, Teresa \ San Diego Gas and Electric, USA . ........................................................................ 718 Dyehouse, Melissa A. \ Purdue University, USA ............................................................................... 529 Egyedi, Tineke M. \ Delft University of Technology, The Netherlands . ........................................... 105 Eisenhauer, Markus \ Fraunhofer FIT, Germany . ........................................................................... 569 El Emary, Ibrahiem M. M. \ King Abdulaziz University, Kingdom of Saudi Arabia . ................... 2360 Elia, Gianluca \ Scuola Superiore ISUFI - University of Salento, Italy ................................ 1375, 2380
Expósito-Langa, Manuel \ Universitat Politècnica de València, Spain ......................................... 1475 Eze, Uchenna Cyril \ Multimedia University, Malaysia ................................................................. 1178 Fables, Wylci \ IndaSea, Inc., USA .................................................................................................. 1933 Fagbe, T. \ ATT Safety Technologies, Nigeria .................................................................................. 1438 Faithorn, Lisa \ NASA Ames Research Center, USA ....................................................................... 1201 Fayyoumi, Ayham \ Scuola Superiore ISUFI - University of Salento, Italy ................................... 1375 Fengel, Janina \ University of Applied Sciences Darmstadt, Germany ............................................ 373 Ferlander, Sara \ Södertörn University, Sweden ............................................................................. 1904 Fernandes, Cristina \ PhD student at University of Beira Interior, Portugal ................................ 1765 Fernández-Sánchez, José Antonio \ University of Alicante, Spain . ................................................ 967 Ferreira, João J. \ University of Beira Interior, Portugal ............................................................... 1765 Fink, Lior \ Ben-Gurion University of the Negev, Israel ..................................................................... 28 Floren, Alexander \ Saarland University, Germany ....................................................................... 1588 Florkowski, Gary W. \ Katz Graduate School of Business, USA . .................................................... 976 Foster, Jonathan \ University of Sheffield, UK . .............................................................................. 1570 Fragidis, Garyfallos \ Technological Educational Institute of Serres, Greece ............................... 2473 Francesca, Grippa \ University of Salento, Italy ............................................................................ 2398 Frost, Eric \ San Diego State University, USA .................................................................................. 718 Gadman, Leslie \ London South Bank University, UK .................................................................... 1522 Galanaki, Eleanna \ Athens University of Economics and Business, Greece ................................... 948 Galván, Ramón Sanguino \ University of Extremadura, Spain . ...................................................... 183 García-Crespo, Ángel \ Universidad Carlos III de Madrid, Spain . ............................... 403, 627, 1615 Gayialis, Sotiris P. \ National Technical University of Athens, Greece . ........................................... 888 Gemoets, Leopoldo \ University of Texas at El Paso, USA . ............................................................. 229 Giambona, Genoveffa (Jeni) \ University of Reading, UK ............................................................ 1396 Gianluca, Elia \ University of Salento, Italy . .................................................................................. 2398 Gibbs, Jennifer L. \ Rutgers University, USA ................................................................................. 1413 Gibson, Lucy W. \ eCareerFit.com & Resource Assoiciates,, USA . ............................................... 2087 Given, Lisa M. \ University of Alberta, Canada . .............................................................................. 468 Gómez-Berbís, Juan Miguel \ Universidad Carlos III de Madrid, Spain ................................ 403, 627 Goossenaerts, Jan \ Eindhoven University of Technology, The Netherlands .................................. 2229 Goswami, Ranjit \ Indian Institute of Technology, India ................................................................ 2331 Grippa, Francesca \ University of Salento, Italy ............................................................................ 2380 Grisoni, Louise \ Bristol Business School, UK . .............................................................................. 1249 Gruber, Harald \ European Investment Bank, Luxembourg ........................................................... 2352 Gürol, Yonca \ Yildiz Technical Unversity, Turkey .......................................................................... 1633 Guiderdoni-Jourdain, Karine \ The Institute of Labour Economics and Industrial Sociology (LEST); Université de la Méditerranee, France ........................................................................ 2073 Gulliver, S. R. \ University of Reading, UK . ..................................................................................... 135 Gupta, Surendra M. \ Northeastern University, Boston, USA . ........................................................ 357 Gupta, Pramila \ CQUniversity Melbourne, Australia ................................................................... 2135 Haghirian, Parissa \ Sophia University, Japan ............................................................................... 1536 Halas, Helena \ SETCCE, Slovenia ................................................................................................... 192 Hall, Laura Lunstrum \ University of Texas at El Paso, USA ......................................................... 229 Haller, Armin \ National University of Ireland - Galway, Ireland .................................................... 782 Häsel, Matthias \ University of Duisburg-Essen, Germany .............................................................. 512 Hassall, Kim \ University of Melbourne, Australia ........................................................................... 643
Hernández-López, Adrián \ Universidad Carlos III de Madrid, Spain ......................................... 1615 Herremans, Irene M. \ University of Calgary, Canada .................................................................. 2433 Hollensen, Svend \ University of Southern Denmark, Denmark ..................................................... 1838 Holm, Justin \ Concordia University, Canada ................................................................................ 1338 Holt, Duncan \ RAYTHEON, Australia . .......................................................................................... 1961 Hongsranagon, Prathurng \ Chulalongkorn University, Thailand ................................................ 2512 Hoonakker, Peter \ University of Wisconsin-Madison, USA . ......................................................... 1879 Hua, Grace \ Louisiana State University, USA .................................................................................. 809 Huang, Liusheng \ University of Science & Technology of China, China & CityU-USTC Advanced Research Institute, China ............................................................................................................. 487 Huerta-Carvajal, María Isabel \ Universidad de las Americas-Puebla, Mexico ............................ 842 Hurley-Hanson, Amy E. \ Chapman University, USA ...................................................................... 619 Ifinedo, Princely \ University of Jyväskylä, Finland & Cape Breton University, Canada ............................................................................................................................. 1170, 1217 Ignatiadis, Ioannis \ Kingston University, UK ................................................................................ 2473 Ilg, Markus \ Vorarlberg University of Applied Sciences, Austria .................................................. 1644 Imafidon, Tongo Constantine \ Covenant University, Nigeria . ..................................................... 1508 Isaac, Robert G. \ University of Calgary, Canada .......................................................................... 2433 Jackson, Pamela \ Fayetteville State University, USA .................................................................... 1134 Järvinen, Raija \ National Consumer Research Centre, Finland ..................................................... 911 Jennex, Murray E. \ San Diego State University, USA . ................................................................... 718 Jentsch, Marc \ Fraunhofer FIT, Germany ....................................................................................... 569 Jiang, James \ University of Central Florida, USA ......................................................................... 1445 Jin, Hai \ Huazhong University of Science and Technology, China ................................................ 1149 Jones, Joanna \ University of Wales Newport, UK . .......................................................................... 984 Judge, Robert \ San Diego State University, USA . ........................................................................... 718 Julsrud, Tom Erik \ Telenor Research and Innovation, Norway .................................................... 1948 Juntunen, Arla \ Department of Marketing and Management Helsinki School of Economics, Finland & Finland’s Government Ministry of the Interior, Police Department, Finland ................. 820, 956 Justis, Bob \ Louisiana State University, USA ................................................................................... 809 Kalfakakou, Glykeria \ Aristotle University of Thessaloniki, Greece . .......................................... 1458 Kamath, Manjunath \ Oklahoma State University, USA . .............................................................. 2275 Kamau, Caroline \ Southampton Solent University, UK . ............................................................... 1707 Kanellis, Panagiotis \ National and Kapodistrian University of Athens, Greece ............................. 741 Karakostas, Bill \ City University, UK .............................................................................................. 593 Karat, John \ IBM Research, USA . ................................................................................................... 750 Karat, Clare-Marie \ IBM Research, USA . ...................................................................................... 750 Kardaras, Dimitris K. \ Athens University of Economics and Business, Greece ............................. 593 Katriou, Stamatia-Ann \ ALTEC S.A., Greece ............................................................................... 2473 Keesey, Christopher \ Ohio University, USA .................................................................................... 121 Kettunen, Juha \ Turku University of Applied Sciences, Finland ........................................... 611, 1281 Kim, Young Hoon \ Rutgers University, USA ................................................................................. 1413 Kipp, Alexander \ High Performance Computing Center Stuttgart, Germany . ............................. 1306 Kivistö-Rahnasto, Jouni \ Tampere University of Technology, Finland . ......................................... 911 Klein, Gary \ University of Colorado in Colorado Springs, USA ................................................... 1445 Kleinknecht, Alfred \ Delft University of Technology, The Netherlands ........................................ 1603 Klobučar, Tomaž \ Jožef Stefan Institute & SETCCE, Slovenia ....................................................... 192
Knebel, Uta \ Technische Universitaet Muenchen, Germany .......................................................... 1267 Kobb, Ryan \ IBM Global Business Services, USA ........................................................................... 311 Kollmann, Tobias \ University of Duisburg-Essen, Germany . ......................................................... 512 Kotinurmi, Paavo \ Helsinki University of Technology, Finland . .................................................... 782 Koumpis, Adamantios \ ALTEC S.A., Greece ................................................................................ 2473 Kovac, Jure \ Faculty of Organizational Sciences & University of Maribor, Slovenia . ................. 1750 Krcmar, Helmut \ Technische Universitaet Muenchen, Germany .................................................. 1267 Kung, Hsiang-Jui \ Georgia Southern University, USA . .................................................................... 67 Kwak, N. K. \ Saint Louis University, USA ....................................................................................... 344 Kwan Tan, Albert Wee \ National University of Singapore, Singapore ........................................... 271 Kyritsis, M. \ Brunel University, UK ................................................................................................. 135 Lagraña, Fernando A.A. \ Webster University Geneva, Switzerland & Grenoble École de Management, France ................................................................................................................. 1999 Land, Frank \ London School of Economics, UK ........................................................................... 2034 Landaeta, Reinaldo Plaz \ University of Madrid, Spain .................................................................. 418 Law, Wai K. \ University of Guam, Guam . ..................................................................................... 1924 Lawless, Désirée S. \ Woodward, USA . ............................................................................................... 67 Lawless, William F. \ Paine College, USA .......................................................................................... 67 Lee, Sun Kyong \ Rutgers University, USA ..................................................................................... 1413 Lee, Chang Won \ Jinju National University, Korea ........................................................................ 344 Leimeister, Jan Marco \ Kassel University, Germany .................................................................... 1267 Lenart, Gregor \ University of Maribor, Slovenia ............................................................................ 995 Lesh, Richard A. \ Indiana University, USA ..................................................................................... 529 Leung, Ying Tat \ IBM Almaden Research Center, USA ................................................................. 2275 Li, Xueping \ University of Tennessee, Knoxville, USA . ................................................................... 691 Li, Pengtao \ California State University, Stanislaus, USA ............................................................. 2244 Li, Qing \ City University of Hong Kong, China & CityU-USTC Advanced Research Institute, China ............................................................................................................................................ 487 Lin, Angela \ University of Sheffield, UK ........................................................................................ 1570 Liu, Chuanlan \ Louisiana State University, USA . ............................................................................. 47 Liu, An \ University of Science & Technology of China, China & City University of Hong Kong, China & CityU-USTC Advanced Research Institute, China ........................................................ 487 lo Storto, Corrado \ Universitá di Napoli Federico II, Italy ............................................................ 863 Lobo, Jorge \ IBM Research, USA . ................................................................................................... 750 López, Francisco J. \ Macon State College, USA ............................................................................. 229 López, Ana Villar \ Universitat Jaume I, Spain ................................................................................ 434 Lounsbury, John W. \ University of Tennessee at Knoxville and eCareerFit.com, USA . .............. 2087 Lukosch, Stephan \ Delft University of Technology, The Netherlands ............................................. 661 Luna-Reyes, Luis Felipe \ Universidad de las Americas-Puebla, Mexico ....................................... 842 Luo, Yaqin \ Huazhong University of Science and Technology, China ........................................... 1149 Lupton, Natalie \ Central Washington University, USA . .................................................................. 549 Lupu, Emil \ Imperial College, UK ................................................................................................... 750 Ma, Jiefei \ Imperial College, UK . .................................................................................................... 750 Maamar, Zakaria \ Zayed University, UAE ...................................................................................... 670 Mahmood, M. Adam \ University of Texas at El Paso, USA ............................................................ 229 Manassian, Armond \ American University of Beirut, Lebanon .................................................... 2433
Manikavasagam, Sivagnanasundaram \ NITT-National Institute of Technology Tiruchirappalli, India ........................................................................................................................................... 1094 Marques, Elon \ University of Dallas, USA ...................................................................................... 651 Marques, Carla S. \ University of Trás-os-Montes e Alto Douro, Portugal ................................... 1765 Martakos, Drakoulis \ National and Kapodistrian University of Athens, Greece . .......................... 741 Martín, Fernando Paniagua \ Universidad Carlos III de Madrid, Spain ...................................... 1615 McGuire, Kerry \ University of Wisconsin-Madison, USA ............................................................. 1879 Medina-Garrido, José Aurelio \ Cadiz University, Spain .................................................................. 39 Mehri, Darius \ University of California - Berkeley, USA .............................................................. 1157 Mendes, Júlio da Costa \ University of Algarve, Portugal ............................................................... 446 Mohamed, Mirghani S. \ New York Institute of Technology, Bahrain ............................................ 2457 Mohamed, Mona A. \ New York Institute of Technology, Bahrain . ................................................ 2457 Molnar, Darin R. \ CEO, eXcolo Research Group, USA ................................................................ 1675 Montagno, Ray \ Ball State University, USA .................................................................................. 1662 Moody, Janette \ The Citadel, USA ................................................................................................. 1991 Moon, Nathan W. \ Georgia Institute of Technology, USA ............................................................. 2112 Morar, S. \ Consultant, UK ................................................................................................................ 135 Moreno, Carlos Merino \ University of Madrid, Spain .................................................................... 418 Mulej, Matjaz \ University of Maribor, Slovenia ............................................................................ 2257 Munde, Gail \ East Carolina University, USA . ............................................................................... 2060 Murphy, Lyndon \ University of Wales Newport, UK . ..................................................................... 984 Narayanan, V. K. \ Drexel University, USA ...................................................................................... 286 Narendra, Nanjangud C. \ IBM Research India, India .................................................................... 670 Natale, Peter J. \ Regent University, USA ....................................................................................... 1562 Natarajan, Thamaraiselvan \ NITT-National Institute of Technology Tiruchirappalli, India ....... 1094 Navarro, Montserrat Boronat \ Universitat Jaume I, Spain . .......................................................... 434 Nazari, Jamal A. \ Mount Royal College & University of Calgary, Canada .................................. 2433 Nedelko, Zlatko \ University of Maribor, Slovenia ......................................................................... 2257 Nissen, Mark E. \ Naval Postgraduate School, USA ...................................................................... 1494 Nitse, Philip S. \ Idaho State University, USA ................................................................................. 1933 Nolas, Sevasti-Melissa \ London School of Economics, UK ........................................................... 2034 Obuh, Alex Ozoemelem \ Delta State University, Nigeria ............................................................. 2420 Oikonomitsios, Stylianos \ CIA, Consultant, Greece . ...................................................................... 888 Oiry, Ewan \ The Institute of Labour Economics and Industrial Sociology (LEST); Université de la Méditerranee, France . ...................................................................................................... 2073 Olivas-Luján, Miguel R. \ Clarion University of Pennsylvania, USA & Tecnológico de Monterrey, México .......................................................................................................................................... 976 Oren, Eyal \ Vrije Universiteit Amsterdam, The Netherlands . .......................................................... 782 Osorio, Diana Benito \ Universidad Rey Juan Carlos–Madrid, Spain ........................................... 1577 Özdemir, Erkan \ Uludag University, Turkey .................................................................................. 2019 Palacios, Tomás M. Banegil \ University of Extremadura, Spain . ................................................... 183 Panayiotou, Nikolaos A. \ National Technical University of Athens, Greece ................................... 888 Panayotopoulou, Leda \ Athens University of Economics and Business, Greece ............................ 948 Panteli, Niki \ University of Bath, UK ............................................................................................. 1688 Park, Jore \ IndaSea, Inc., USA ....................................................................................................... 1933 Parker, Kevin R. \ Idaho State University, USA ............................................................................. 1933 Pimpa, Nattavud \ RMIT University, Australia . ............................................................................. 2352
Pochampally, Kishore K. \ Southern New Hampshire University, Manchester, USA ...................... 357 Popplewell, Keith \ Coventry University, UK ................................................................................. 2229 Possel-Dölken, Frank \ RWTH Aachen University, Germany . ....................................................... 2229 Potocan, Vojko \ University of Maribor, Slovenia ........................................................................... 2257 Powell, Loreen Marie \ Bloomsburg University of Pennsylvania, USA ........................................... 777 Powell, Steven R. \ California State Polytechnic University, USA ................................................. 1231 Prause, Christian R. \ Fraunhofer FIT, Germany ............................................................................ 569 Premchaiswadi, Wichian \ Siam University, Thailand ..................................................................... 699 Pucihar, Andreja \ University of Maribor, Slovenia ......................................................................... 995 Qi, Li \ Huazhong University of Science and Technology, China .................................................... 1149 Quaddus, Mohammad \ Curtin University, Australia .................................................................... 1548 Quan, Jing \ Perdue School of Business, USA . ................................................................................... 56 Quer-Ramón, Diego \ University of Alicante, Spain ......................................................................... 929 Rachan, Wilfred \ University of Leiden, The Netherlands .............................................................. 2493 Rahim, Md Mahbubur \ Monash University, Australia ................................................................. 1548 Raisinghani, Mahesh \ Texas Women’s University, USA . ................................................................. 651 Rajagopal \ Monterrey Institute of Technology and Higher Education, ITESM, Mexico . .................... 1 Rajah, Saraswathy R. Aravinda \ NITT-National Institute of Technology Tiruchirappalli, India ........................................................................................................................................... 1094 Ramakrishna, Hindupur \ University of Redlands, USA ................................................................. 150 Rao, Pramila \ Marymount University, USA ..................................................................................... 635 Rathi, Dinesh \ University of Alberta, Canada . ................................................................................ 468 Rawlinson, David \ Central Washington University, USA ................................................................ 549 Richardson, Robert \ Mental Health Associates, USA ................................................................... 1522 Rimbau-Gilabert, Eva \ Open University of Catalonia (UOC), Spain .......................................... 1298 Robbins, Stephanie S. \ University of North Carolina at Charlotte, USA ...................................... 1134 Ruano-Mayoral, Marcos \ Universidad Carlos III de Madrid, Spain . ............................................ 403 Russo, Alessandra \ Imperial College, UK ....................................................................................... 750 Sahut, Jean-Michel \ Amiens School of Management, France ......................................................... 499 Salonen, Jarno \ VTT Technical Research Centre of Finland, Finland . ........................................... 911 Sarkar, Avijit \ University of Redlands, USA .................................................................................... 150 Schubert, Lutz \ High Performance Computing Center Stuttgart, Germany ................................. 1306 Schümmer, Till \ FernUniversität in Hagen, Germany . ................................................................... 661 Scott, Craig R. \ Rutgers University, USA ....................................................................................... 1413 Semolic, Brane \ Project & Technology Management Institute & Faculty of Logistics, University of Maribor, Slovenia ................................................................................................. 1750 Shaqrah, Amin Ahmad \ Alzaytoonah University of Jordan, Jordan . ........................................... 1071 Sharma, Sushil \ Ball State University, USA ................................................................................... 1662 Siddiqi, Jawed \ Sheffield Hallam University, UK .......................................................................... 2102 Silburn, Nicholas L.J. \ Henley Business School, UK .................................................................... 1396 Singh, Mohini \ RMIT University, Australia . .................................................................................. 1548 Sloman, Morris \ Imperial College, UK . .......................................................................................... 750 Smith-Robbins, Sarah \ Indiana University, USA ............................................................................ 121 Söderström, Eva \ University of Skövde, Sweden ............................................................................. 206 Sofge, Donald A. \ Naval Research Laboratory, USA ......................................................................... 67 Stamati, Teta \ National and Kapodistrian University of Athens, Greece ........................................ 741 Stamati, Konstantina \ National and Kapodistrian University of Athens, Greece . ......................... 741
Steel, Robert P. \ University of Michigan-Dearborn, USA ............................................................. 2087 Strang, Kenneth David \ APPC International Market Research, USA & Unviersity of Central Queensland, Australia ............................................................................................ 1023, 1350, 2298 Studham, R. Scott \ Oak Ridge National Laboratory, USA ............................................................ 2087 Stylianou, Antonis C. \ University of North Carolina at Charlotte, USA ....................................... 1134 Sun, Zhaohao \ University of Ballarat, Australia . .............................................................................. 83 Suryavanishi, Kumal \ IBM Global Business Services, USA ........................................................... 311 Swatman, Paula \ University of South Australia, Australia ............................................................ 1961 Swayne, Huw \ University of Glamorgan, UK .................................................................................. 984 Sweeney, Edward \ Dublin Institute of Technology, Ireland ........................................................... 1820 Taurino, Cesare \ Scuola Superiore ISUFI - University of Salento, Italy ....................................... 1375 Thoben, Klaus-Dieter \ BIBA Bremer Institut für Produktion und Logistik GmbH, Germany ........ 254 Thomas, Brychan \ University of Glamorgan, UK ........................................................................... 984 Timms, Duncan \ University of Stirling, Scotland .......................................................................... 1904 Tolias, Evangelos \ ALTEC S.A., Greece ......................................................................................... 2473 Tomás-Miquel, José V. \ Universitat Politècnica de València, Spain ............................................. 1475 Tung, Huilien \ Auburn University, USA ............................................................................................. 67 Valdés-Conca, Jorge \ University of Alicante, Spain ........................................................................ 967 Wagner, Claudia-Maria \ Dublin Institute of Technology, Ireland ................................................ 1820 Wallis, Steven E. \ Institute for Social Innovation, USA & Foundation for the Advancement of Social Theory, USA .................................................................................................................... 2177 Wang, Fen \ Central Washington University, USA ............................................................................ 549 Wang, Eric T.G. \ National Central University, Taiwan ................................................................. 1445 Ward, Andrew C. \ University of Minnesota, USA ......................................................................... 2112 Wenyin, Liu \ City University of Hong Kong, China & CityU-USTC Advanced Research Institute, China ............................................................................................................................................ 487 Wilkins, Linda \ RMIT University, Australia .................................................................................. 1961 Williams, James G. \ University of Pittsburgh, USA ........................................................................ 699 Wittkower, D. E. \ Coastal Carolina University, USA .................................................................... 2157 Wolff, R. Ayşen \ Haliç University, Turkey . .................................................................................... 1633 Worden, Daniel \ RuleSmith Corporation, Canada ........................................................................ 1732 Woszczynski, Amy B. \ Kennesaw State University, USA . ............................................................. 1991 Wulff, Vlad Stefan \ University of Southern Denmark, Denmark .................................................. 1838 Yearwood, John \ University of Ballarat, Australia ............................................................................ 83 Yu, Pei-Ju \ Chunghua Institution for Economic Research, Taiwan ............................................... 1796 Zapounidis, Konstantinos C. \ Aristotle University of Thessaloniki, Greece ................................ 1458 Zaragoza-Sáez, Patrocinio \ University of Alicante, Spain .............................................................. 929 Zeng, Qingfeng \ Shanghai University of Finance and Economics, China ........................................ 47 Zhang, Jilong \ RMIT University, Australia .................................................................................... 2554 Zhang, Xingguo \ Aging and Disability Service Administration, USA ............................................. 549 Zhao, Fang \ Royal Melbourne Institute of Technology, Australia . ................................................ 1290 Zhou, Haibo \ Erasmus University Rotterdam, The Netherlands . .................................................. 1603
Contents
Volume I Section I. Fundamental Concepts and Theories This section serves as a foundation for this exhaustive reference tool by addressing crucial theories essential to the understanding of global business. Chapters found within these pages provide an excellent framework in which to position global business within the field of information science and technology. Insight regarding the critical incorporation of global measures into global business is addressed, while crucial stumbling blocks of this field are explored. With a little over 10 chapters comprising this foundational section, the reader can learn and chose from a compendium of expert research on the elemental theories underscoring the global business discipline. Chapter 1.1. Marketing Strategy, Technology and Modes of Entry in Global Retailing......................... 1 Rajagopal, Monterrey Institute of Technology and Higher Education, ITESM, Mexico Chapter 1.2. The Business Value of E-Collaboration: A Conceptual Framework................................. 28 Lior Fink, Ben-Gurion University of the Negev, Israel Chapter 1.3. Virtual Corporations.......................................................................................................... 39 Sixto Jesús Arjonilla-Domínguez, Freescale Semiconductor, Inc., Spain José Aurelio Medina-Garrido, Cadiz University, Spain Chapter 1.4. E-Business Strategy in Franchising................................................................................... 47 Ye-Sho Chen, Louisiana State University, USA Chuanlan Liu, Louisiana State University, USA Qingfeng Zeng, Shanghai University of Finance and Economics, China Chapter 1.5. E-Business Strategy and Firm Performance...................................................................... 56 Jing Quan, Perdue School of Business, USA
Chapter 1.6. Conservation of Information and e-Business Success and Challenges: A Case Study.......................................................................................................................................... 67 Huilien Tung, Auburn University, USA Hsiang-Jui Kung, Georgia Southern University, USA Désirée S. Lawless, Woodward, USA Donald A. Sofge, Naval Research Laboratory, USA William F. Lawless, Paine College, USA Chapter 1.7. Demand Driven Web Services.......................................................................................... 83 Zhaohao Sun, University of Ballarat, Australia Dong Dong, Hebei Normal University, China John Yearwood, University of Ballarat, Australia Chapter 1.8. Between Supply and Demand: Coping with the Impact of Standards Change............... 105 Tineke M. Egyedi, Delft University of Technology, The Netherlands Chapter 1.9. Engagement, Immersion, and Learning Cultures: Project Planning and Decision Making for Virtual World Training Programs...................................................................... 121 Christopher Keesey, Ohio University, USA Sarah Smith-Robbins, Indiana University, USA Chapter 1.10. Learning Space in Virtual Environments: Understanding the Factors Influencing Training Time................................................................................................................... 135 M. Kyritsis, Brunel University, UK S. R. Gulliver, University of Reading, UK S. Morar, Consultant, UK Chapter 1.11. Business Analytics Success: A Conceptual Framework and an Application to Virtual Organizing........................................................................................................ 150 Hindupur Ramakrishna, University of Redlands, USA Avijit Sarkar, University of Redlands, USA Jyoti Bachani, University of Redlands, USA Chapter 1.12. An Overview of International Intellectual Capital (IC) Models and Applicable Guidelines.......................................................................................................................... 183 Tomás M. Bañegil Palacios, University of Extremadura, Spain Ramón Sanguino Galván, University of Extremadura, Spain Chapter 1.13. Business Models and Organizational Processes Changes............................................. 192 Helena Halas, SETCCE, Slovenia Tomaž Klobučar, Jožef Stefan Institute & SETCCE, Slovenia Chapter 1.14. Guidelines for Preparing Organizations in Developing Countries for Standards-Based B2B.......................................................................................................................... 206 Lena Aggestam, University of Skövde, Sweden Eva Söderström, University of Skövde, Sweden
Section II. Development and Design Methodologies This section provides in-depth coverage of conceptual architecture frameworks to provide the reader with a comprehensive understanding of the emerging technological developments within the field of global business. Research fundamentals imperative to the understanding of developmental processes within information/knowledge management are offered. From broad examinations to specific discussions on electronic tools, the research found within this section spans the discipline while offering detailed, specific discussions. From basic designs to abstract development, these chapters serve to expand the reaches of development and design technologies within the global business community. This section includes more than 15 contributions from researchers throughout the world on the topic of global business. Chapter 2.1. Building Business Value in E-Commerce Enabled Organizations: An Empirical Study.............................................................................................................................. 229 M. Adam Mahmood, University of Texas at El Paso, USA Leopoldo Gemoets, University of Texas at El Paso, USA Laura Lunstrum Hall, University of Texas at El Paso, USA Francisco J. López, Macon State College, USA Chapter 2.2. Enhancing the Preparedness of SMEs for E-Business Opportunities by Collaborative Networks....................................................................................................................... 254 Heiko Duin, BIBA Bremer Institut für Produktion und Logistik GmbH, Germany Klaus-Dieter Thoben, BIBA Bremer Institut für Produktion und Logistik GmbH, Germany Chapter 2.3. An Information Technology Planning Framework for an Industry Cluster.................... 271 Albert Wee Kwan Tan, National University of Singapore, Singapore Chapter 2.4. Linking Information Technology, Knowledge Management, and Strategic Experimentation.................................................................................................................... 286 V. K. Narayanan, Drexel University, USA Chapter 2.5. Collaborative Enterprise Architecture for Municipal Environments.............................. 294 Leonidas G. Anthopoulos, Hellenic Ministry of Foreign Affairs, Greece Chapter 2.6. Using Enterprise Architecture to Transform Service Delivery: The U.S. Federal Government’s Human Resources Line of Business................................................................ 311 Timothy Biggert, IBM Global Business Services, USA Kumal Suryavanishi, IBM Global Business Services, USA Ryan Kobb, IBM Global Business Services, USA Chapter 2.7. An Application of Multi-Criteria Decision-Making Model to Strategic Outsourcing for Effective Supply-Chain Linkages.............................................................................. 344 N. K. Kwak, Saint Louis University, USA Chang Won Lee, Jinju National University, Korea
Chapter 2.8. Reverse Supply Chain Design: A Neural Network Approach......................................... 357 Kishore K. Pochampally, Southern New Hampshire University, Manchester, USA Surendra M. Gupta, Northeastern University, Boston, USA Chapter 2.9. Semantic Interoperability Enablement in E-Business Modeling.................................... 373 Janina Fengel, University of Applied Sciences Darmstadt, Germany Chapter 2.10. Semantic Competence Pull: A Semantics-Based Architecture for Filling Competency Gaps in Organizations..................................................................................................... 403 Ricardo Colomo-Palacios, Universidad Carlos III de Madrid, Spain Marcos Ruano-Mayoral, Universidad Carlos III de Madrid, Spain Juan Miguel Gómez-Berbís, Universidad Carlos III de Madrid, Spain Ángel García-Crespo, Universidad Carlos III de Madrid, Spain Chapter 2.11. Model on Knowledge-Governance: Collaboration Focus and Communities of Practice...................................................................................................................... 418 Eduardo Bueno Campos, University of Madrid, Spain Carlos Merino Moreno, University of Madrid, Spain Reinaldo Plaz Landaeta, University of Madrid, Spain Chapter 2.12. Knowledge Integration through Inter-Organizational Virtual Organizations................ 434 Montserrat Boronat Navarro, Universitat Jaume I, Spain Ana Villar López, Universitat Jaume I, Spain Chapter 2.13. The Development of Knowledge and Information Networks in Tourism Destinations........................................................................................................................... 446 Júlio da Costa Mendes, University of Algarve, Portugal Chapter 2.14. Designing Digital Marketplaces for Competitive Advantage....................................... 468 Dinesh Rathi, University of Alberta, Canada Lisa M. Given, University of Alberta, Canada Chapter 2.15. Business Models for Insurance of Business Web Services........................................... 487 Liu Wenyin, City University of Hong Kong, China & CityU-USTC Advanced Research Institute, China An Liu, University of Science & Technology of China, China & City University of Hong Kong, China & CityU-USTC Advanced Research Institute, China Qing Li, City University of Hong Kong, China & CityU-USTC Advanced Research Institute, China Liusheng Huang, University of Science & Technology of China, China & CityU-USTC Advanced Research Institute, China Chapter 2.16. Business Model of Internet Banks................................................................................ 499 Jean-Michel Sahut, Amiens School of Management, France
Chapter 2.17. A Reverse Auction-Based E-Business Model for B2C Service Markets...................... 512 Tobias Kollmann, University of Duisburg-Essen, Germany Matthias Häsel, University of Duisburg-Essen, Germany Chapter 2.18. Multi-Tier Design Assessment in the Development of Complex Organizational Systems....................................................................................................................... 529 Melissa A. Dyehouse, Purdue University, USA John Y. Baek, Center for Advancement of Informal Science Education, USA Richard A. Lesh, Indiana University, USA Chapter 2.19. EBDMSS: A Web-Based Decision Making Support System for Strategic E-Business Management...................................................................................................................... 549 Fen Wang, Central Washington University, USA Natalie Lupton, Central Washington University, USA David Rawlinson, Central Washington University, USA Xingguo Zhang, Aging and Disability Service Administration, USA Section III. Tools and Technologies This section presents an extensive coverage of various tools and technologies available in the field of global business that practitioners and academicians alike can utilize to develop different techniques. These chapters enlighten readers about fundamental research on the many methods used to facilitate and enhance the integration of this worldwide industry by exploring the usage of such tools as supply chain design, IT strategy, and new business models, all increasingly pertinent research areas. It is through these rigorously researched chapters that the reader is provided with countless examples of the up-and-coming tools and technologies emerging from the field of global business. With more than 20 chapters, this section offers a broad treatment of some of the many tools and technologies within the global business community. Chapter 3.1. MICA: A Mobile Support System for Warehouse Workers............................................ 569 Christian R. Prause, Fraunhofer FIT, Germany Marc Jentsch, Fraunhofer FIT, Germany Markus Eisenhauer, Fraunhofer FIT, Germany Chapter 3.2. Fuzzy Modelling for Integrated Strategic Planning for Information Systems and Business Process Design............................................................................................................... 593 Dimitris K. Kardaras, Athens University of Economics and Business, Greece Bill Karakostas, City University, UK Chapter 3.3. Human Resources in the Balanced Scorecard System.................................................... 611 Juha Kettunen, Turku University of Applied Sciences, Finland Chapter 3.4. The Role of HRIS in Crisis Response Planning.............................................................. 619 Amy E. Hurley-Hanson, Chapman University, USA
Chapter 3.5. Concepts, Technology, and Applications in E-Mentoring............................................... 627 Ricardo Colomo-Palacios, Universidad de Carlos III, Spain Juan Miguel Gómez-Berbís, Universidad de Carlos III, Spain Angel Garcia-Crespo, Universidad de Carlos III, Spain Cristina Casado-Lumbreras, Universidad Complutense, Spain Chapter 3.6. E-Recruitment in Emerging Economies.......................................................................... 635 Pramila Rao, Marymount University, USA
Volume II Chapter 3.7. E-Logistics: The Slowly Evolving Platform Underpinning E-Business......................... 643 Kim Hassall, University of Melbourne, Australia Chapter 3.8. E-Business Perspectives through Social Networks......................................................... 651 Mahesh Raisinghani, Texas Women’s University, USA Elon Marques, University of Dallas, USA Chapter 3.9. Designing E-Business Applications with Patterns for ComputerMediated Interaction............................................................................................................................ 661 Stephan Lukosch, Delft University of Technology, The Netherlands Till Schümmer, FernUniversität in Hagen, Germany Chapter 3.10. Business Artifacts for E-Business Interoperability....................................................... 670 Youakim Badr, INSA-Lyon, France Nanjangud C. Narendra, IBM Research India, India Zakaria Maamar, Zayed University, UAE Chapter 3.11. Adaptive Web Presence and Evolution through Web Log Analysis.............................. 691 Xueping Li, University of Tennessee, USA Chapter 3.12. On-Line Credit Card Payment Processing and Fraud Prevention for E-Business........ 699 James G. Williams, University of Pittsburgh, USA Wichian Premchaiswadi, Siam University, Thailand Chapter 3.13. Achieving Electric Restoration Logistical Efficiencies During Critical Infrastructure Crisis Response: A Knowledge Management Analysis................................................ 718 Teresa Durbin, San Diego Gas and Electric, USA Murray E. Jennex, San Diego State University, USA Eric Frost, San Diego State University, USA Robert Judge, San Diego State University, USA Chapter 3.14. Assessing the Impact of Mobile Technologies on Work-Life Balance......................... 732 Sharon Cox, Birmingham City University, UK
Chapter 3.15. Migration of Legacy Information Systems................................................................... 741 Teta Stamati, National and Kapodistrian University of Athens, Greece Panagiotis Kanellis, National and Kapodistrian University of Athens, Greece Konstantina Stamati, National and Kapodistrian University of Athens, Greece Drakoulis Martakos, National and Kapodistrian University of Athens, Greece Chapter 3.16. Policy Technologies for Security Management in Coalition Networks........................ 750 Seraphin B. Calo, IBM Research, USA Clare-Marie Karat, IBM Research, USA John Karat, IBM Research, USA Jorge Lobo, IBM Research, USA Robert Craven, Imperial College, UK Emil Lupu, Imperial College, UK Jiefei Ma, Imperial College, UK Alessandra Russo, Imperial College, UK Morris Sloman, Imperial College, UK Arosha Bandara, The Open University, UK Chapter 3.17. Teleworker’s Security Risks Minimized with Informal Online Information Technology Communities of Practice.................................................................................................. 777 Loreen Marie Powell, Bloomsburg University of Pennsylvania, USA Chapter 3.18. Ontologically Enhanced RosettaNet B2B Integration.................................................. 782 Paavo Kotinurmi, Helsinki University of Technology, Finland Armin Haller, National University of Ireland - Galway, Ireland Eyal Oren, Vrije Universiteit Amsterdam, The Netherlands Chapter 3.19. Data Mining in Franchising........................................................................................... 809 Ye-Sho Chen, Louisiana State University, USA Grace Hua, Louisiana State University, USA Bob Justis, Louisiana State University, USA Chapter 3.20. Developing a Corporate Memory as a Competitive Advantage in the ICT Sector....... 820 Arla Juntunen, Helsinki School of Economics, Finland Chapter 3.21. City Boosterism through Internet Marketing: An Institutional Perspective.................. 842 María Isabel Huerta-Carvajal, Universidad de las Americas-Puebla, Mexico Luis Felipe Luna-Reyes, Universidad de las Americas-Puebla, Mexico Chapter 3.22. Learning Organizations or Organizations for Learning? How Small Firms can Learn from Planned and Random Technical Problem-Solving: Implications for Technical Education........ 863 Corrado lo Storto, Universitá di Napoli Federico II, Italy
Section IV. Utilization and Application This section discusses a variety of applications and opportunities available that can be considered by practitioners in developing viable and effective global business programs and processes. This section includes over 25 chapters that review numerous business aspects, such as IT diffusion, e-human resource management, and e-commerce development. Also explored in this section is the use of organizational learning during operational change in business. Contributions included in this section provide excellent coverage of today’s business community and how research into global business is impacting the social fabric of our present-day global village. Chapter 4.1. Risk Assessment in Virtual Enterprise Networks: A Process-Driven Internal Audit Approach.................................................................................................................................... 888 Nikolaos A. Panayiotou, National Technical University of Athens, Greece Stylianos Oikonomitsios, CIA, Consultant, Greece Christina Athanasiadou, Ernst & Young, Greece Sotiris P. Gayialis, National Technical University of Athens, Greece Chapter 4.2. eInsurance: Developing Customer-Firendly Electronic Insurance Services from the Novel Project Perspective..................................................................................................... 911 Aki Ahonen, OP Bank Group Central Cooperative, Finland Jarno Salonen, VTT Technical Research Centre of Finland, Finland Raija Järvinen, National Consumer Research Centre, Finland Jouni Kivistö-Rahnasto, Tampere University of Technology, Finland Chapter 4.3. A Qualitative Study of Knowledge Management: The Multinational Firm Point of View....................................................................................................................................... 929 Patrocinio Zaragoza-Sáez, University of Alicante, Spain Enrique Claver-Cortés, University of Alicante, Spain Diego Quer-Ramón, University of Alicante, Spain Chapter 4.4. Adoption and Success of E-HRM in European Firms..................................................... 948 Eleanna Galanaki, Athens University of Economics and Business, Greece Leda Panayotopoulou, Athens University of Economics and Business, Greece Chapter 4.5. A Case Study of a Data Warehouse in the Finnish Police............................................... 956 Arla Juntunen, Helsinki School of Economics, Finland & Finland’s Government Ministry of the Interior, Finland Chapter 4.6. Exploring the Relation between the Use of HRIS and their Implementation in Spanish Firms...................................................................................................................................... 967 José Antonio Fernández-Sánchez, University of Alicante, Spain Susana de Juana-Espinosa, University of Alicante, Spain Jorge Valdés-Conca, University of Alicante, Spain
Chapter 4.7. The Diffusion of HRITs Across English- Speaking Countries........................................ 976 Miguel R. Olivas-Luján, Clarion University of Pennsylvania, USA & Tecnológico de Monterrey, México Gary W. Florkowski, Katz Graduate School of Business, USA Chapter 4.8. The ‘Knock-on’ Effect of E-Business upon Graphic Design SMEs in South Wales.......................................................................................................................................... 984 Lyndon Murphy, University of Wales Newport, UK Joanna Jones, University of Wales Newport, UK Huw Swayne, University of Glamorgan, UK Brychan Thomas, University of Glamorgan, UK Chapter 4.9. “eSME Slovenia”: Initiative and Action Plan for the Accelerated Introduction of E-Business in SMEs........................................................................................................................ 995 Andreja Pucihar, University of Maribor, Slovenia Gregor Lenart, University of Maribor, Slovenia Chapter 4.10. Simulating E-Business Innovation Process Improvement with Virtual Teams Across Europe and Asia..................................................................................................................... 1023 Kenneth D. Strang, APPC International Market Research, USA & University of Central Queensland, Australia Cliff E. L. Chan, Mitsubishi Electric, Singapore Chapter 4.11. Organizational Learning During Changes in Estonian Organization.......................... 1044 Ruth Alas, Estonian Business School, Estonia Chapter 4.12. E-Business Adoption by Jordanian Banks: An Exploratory Study of the Key Factors and Performance Indicators................................................................................................... 1055 Ali Alawneh, Philadelphia University, Jordan Hasan Al-Refai, Philadelphia University, Jordan Khaldoun Batiha, Philadelphia University, Jordan Chapter 4.13. The Influence of Internet Security on E-Business Competence in Jordan: An Empirical Analysis....................................................................................................................... 1071 Amin Ahmad Shaqrah, Alzaytoonah University of Jordan, Jordan Chapter 4.14. Internet Adoption from Omani Organizations’ Perspective: Motivations and Reservations............................................................................................................ 1087 Khamis Al-Gharbi, Sultan Qaboos University, Sultanate of Oman Ahlam Abdullah AlBulushi, Sultanate of Oman Chapter 4.15. Snapshot of Personnel Productivity Assessment in Indian IT Industry...................... 1094 Thamaraiselvan Natarajan, NITT-National Institute of Technology Tiruchirappalli, India Saraswathy R. Aravinda Rajah, NITT-National Institute of Technology Tiruchirappalli, India Sivagnanasundaram Manikavasagam, NITT-National Institute of Technology Tiruchirappalli, India
Chapter 4.16. The Critical Success Factors and Integrated Model for Implementing E-Business in Taiwan’s SMEs........................................................................................................... 1109 Te Fu Chen, Graduate Institute of Central Asia, Chin Yung University, Taiwan Chapter 4.17. E-Commerce Development in China: An Exploration of Perceptions and Attitudes................................................................................................................... 1134 Antonis C. Stylianou, University of North Carolina at Charlotte, USA Stephanie S. Robbins, University of North Carolina at Charlotte, USA Pamela Jackson, Fayetteville State University, USA Chapter 4.18. Dynamic Maintenance in ChinaGrid Support Platform.............................................. 1149 Hai Jin, Huazhong University of Science and Technology, China Li Qi, Huazhong University of Science and Technology, China Jie Dai, Huazhong University of Science and Technology, China Yaqin Luo, Huazhong University of Science and Technology, China Chapter 4.19. Engineering Design at a Toyota Company: Knowledge Management and the Innovative Process................................................................................................................. 1157 Darius Mehri, University of California - Berkeley, USA Chapter 4.20. The Internet and SMEs in Sub-Saharan African Countries: An Analysis in Nigeria....................................................................................................................... 1170 Princely Ifinedo, University of Jyväskylä, Finland Chapter 4.21. E-Business and Nigerian Financial Firms Development: A Review of Key Determinants.............................................................................................................................. 1178 Uchenna Cyril Eze, Multimedia University, Malaysia Chapter 4.22. Lessons Learned from the NASA Astrobiology Institute............................................ 1201 Lisa Faithorn, NASA Ames Research Center, USA Baruch S. Blumberg, Fox Chase Cancer Center, USA Chapter 4.23. Influencing Factors and the Acceptance of Internet and E-Business Technologies in Maritime Canada’s SMEs: An Analysis.................................................................. 1217 Princely Ifinedo, Cape Breton University, Canada Chapter 4.24. An Analysis of the Latin American Wireless Telecommunications Market Portfolios of Telefonica and America Movil...................................................................................... 1231 Steven R. Powell, California State Polytechnic University, USA Chapter 4.25. Exploring Organizational Learning and Knowledge Exchange through Poetry......... 1249 Louise Grisoni, Bristol Business School, UK
Chapter 4.26. Hybrid Value Creation in the Sports Industry: The Case of a Mobile Sports Companion as IT-Supported Product-Servce-Bundle........................................................................ 1267 Jan Marco Leimeister, Kassel University, Germany Uta Knebel, Technische Universitaet Muenchen, Germany Helmut Krcmar, Technische Universitaet Muenchen, Germany Chapter 4.27. Management Information System in Higher Education.............................................. 1281 Juha Kettunen, Turku University of Applied Sciences, Finland
Volume III Section V. Organizational and Social Implications This section includes a wide range of research pertaining to the social and organizational impact of global business around the world. Chapters introducing this section critically analyze interoperability, collaboration, synergy and interpersonal communication/knowledge sharing. Additional chapters included in this section look at trust and tension in telework practices, which has been recognized as one of the main causes of the collapse of a large number of dot-com companies. With 20 chapters the discussions presented in this section offer research into the integration of global global business as well as implementation of ethical considerations for all organizations. Chapter 5.1. Business Relationships and Organizational Structures in E-Business.......................... 1290 Fang Zhao, Royal Melbourne Institute of Technology, Australia Chapter 5.2. Exploring the Link between Flexible Work and Organizational Performance............. 1298 Eva Rimbau-Gilabert, Open University of Catalonia (UOC), Spain Chapter 5.3. E-Business Interoperability and Collaboration............................................................. 1306 Alexander Kipp, High Performance Computing Center Stuttgart, Germany Lutz Schubert, High Performance Computing Center Stuttgart, Germany Chapter 5.4. Assessing Relational E-Strategy Supporting Business Relationships........................... 1338 Anne-Marie Croteau, Concordia University, Canada Anne Beaudry, Concordia University, Canada Justin Holm, Concordia University, Canada Chapter 5.5. Collaborative Synergy and Leadership in E-Business.................................................. 1350 Kenneth David Strang, Central Queensland University, Australia Chapter 5.6. Collaborative Learning Experiences in Teaching of E-Business Management............ 1375 Wael Assaf, Scuola Superiore ISUFI - University of Salento, Italy Gianluca Elia, Scuola Superiore ISUFI - University of Salento, Italy Ayham Fayyoumi, Scuola Superiore ISUFI - University of Salento, Italy Cesare Taurino, Scuola Superiore ISUFI - University of Salento, Italy
Chapter 5.7. Trust, Virtual Teams, and Grid Technology.................................................................. 1396 Genoveffa (Jeni) Giambona, University of Reading, UK Nicholas L.J. Silburn, Henley Business School, UK David W. Birchall, Henley Business School, UK Chapter 5.8. Examining Tensions in Telework Policies.................................................................... 1413 Jennifer L. Gibbs, Rutgers University, USA Craig R. Scott, Rutgers University, USA Young Hoon Kim, Rutgers University, USA Sun Kyong Lee, Rutgers University, USA Chapter 5.9. Workplace Safety and Personnel Well-Being: The Impact of Information Technology..................................................................................................................... 1438 T. Fagbe, ATT Safety Technologies, Nigeria O. D. Adekola, Babcock University, Nigeria Chapter 5.10. The Impact of Missing Skills on Learning and Project Performance......................... 1445 James Jiang, University of Central Florida, USA Gary Klein, University of Colorado in Colorado Springs, USA Phil Beck, Southwest Airlines, USA Eric T.G. Wang, National Central University, Taiwan Chapter 5.11. Recruiting, Selecting and Motivating Human Resources: Methodological Analysis and Case Studies Applications.................................................................. 1458 Konstantinos C. Zapounidis, Aristotle University of Thessaloniki, Greece Glykeria Kalfakakou, Aristotle University of Thessaloniki, Greece Chapter 5.12. Knowledge Management in SMEs Clusters................................................................ 1475 Josep Capó-Vicedo, Universitat Politècnica de València, Spain José V. Tomás-Miquel, Universitat Politècnica de València, Spain Manuel Expósito-Langa, Universitat Politècnica de València, Spain Chapter 5.13. Visualizing Knowledge Networks and Flows to Enhance Organizational Metacognition in Virtual Organizations.................................................................... 1494 Mark E. Nissen, Naval Postgraduate School, USA Chapter 5.14. The Multicultural Organization: A Histroric Organizational Theory for Gaining Competitiveness in Global Business Environment............................................ 1508 Tongo Constantine Imafidon, Covenant University, Nigeria Chapter 5.15. Multinational Intellect: The Synergistic Power of Cross Cultural Knowledge Networks.......................................................................................................... 1522 Leslie Gadman, London South Bank University, UK Robert Richardson, Mental Health Associates, USA
Chapter 5.16. Knowledge Transfer within Multinational Corporations: An Intercultural Challenge................................................................................................................. 1536 Parissa Haghirian, Sophia University, Japan Chapter 5.17. Understanding the Use of Business-to-Employee (B2E) Portals in an Australian University through the Employee Lens: A Quantitative Approach.................................. 1548 Md Mahbubur Rahim, Monash University, Australia Mohammad Quaddus, Curtin University, Australia Mohini Singh, RMIT University, Australia Chapter 5.18. Media Channel Preferences of Mobile Communities................................................. 1562 Peter J. Natale, Regent University, USA Mihai C. Bocarnea, Regent University, USA Chapter 5.19. Consumer Information Sharing................................................................................... 1570 Jonathan Foster, University of Sheffield, UK Angela Lin, University of Sheffield, UK Chapter 5.20. The Benefits of Home-Based Working’s Flexibility................................................... 1577 Diana Benito Osorio, Universidad Rey Juan Carlos–Madrid, Spain Section VI. Managerial Impact This section presents contemporary coverage of the social implications of global business, more specifically related to the corporate and managerial utilization of strategy and resource planning. Core ideas such as training and continuing education of human resources in modern organizations are discussed throughout these chapters. Issues, such as a conceptual model to show how managers evaluate internal (relative advantage and compatibility of adopting an innovation) and external (competitive pressure and partner conflict) determinants that affect the intention to adopt technological innovations in global business, are discussed. Equally as crucial, chapters within this section discuss how low-cost Internet commercialization has led to much more widespread adoption of inter-organizational information systems. Also in this section is a focus on finding a solution to deal with Internet empowered customers and to learn how to apply technologies demanded in the new digital economy. Chapter 6.1. Optimizing the Configuration of Development Teams Using EVA: The Case of Ongoing Project Adjustments Facing Personnel Restrictions....................................... 1588 Alexander Baumeister, Saarland University, Germany Alexander Floren, Saarland University, Germany Chapter 6.2. The Impact of Labour Flexibility and HRM on Innovation.......................................... 1603 Haibo Zhou, Erasmus University Rotterdam, The Netherlands Ronald Dekker, Delft University of Technology, The Netherlands & ReflecT at Tilburg University, The Netherlands Alfred Kleinknecht, Delft University of Technology, The Netherlands
Chapter 6.3. Personnel Performance Management in IT eSourcing Environments.......................... 1615 Adrián Hernández-López, Universidad Carlos III de Madrid, Spain Ricardo Colomo-Palacios, Universidad Carlos III de Madrid, Spain Ángel García-Crespo, Universidad Carlos III de Madrid, Spain Fernando Paniagua Martín, Universidad Carlos III de Madrid, Spain Pedro Soto Acosta, University of Murcia, Spain Chapter 6.4. E-HRM in Turkey: A Case Study.................................................................................. 1633 Yonca Gürol, Yildiz Technical Unversity, Turkey R. Ayşen Wolff, Haliç University, Turkey Esin Ertemsir Berkin, Yildiz Technical University, Turkey Chapter 6.5. Performance Management in Software Engineering.................................................... 1644 Markus Ilg, Vorarlberg University of Applied Sciences, Austria Alexander Baumeister, Saarland University, Germany Chapter 6.6. Strategy and Structure in a Virtual Organization.......................................................... 1662 Nazim Ahmed, Ball State University, USA Ray Montagno, Ball State University, USA Sushil Sharma, Ball State University, USA Chapter 6.7. Assessment Strategies for Servant Leadership Practice and Training in the Virtual Organization........................................................................................................................... 1675 Darin R. Molnar, eXcolo Research Group, USA Chapter 6.8. E-Leadership Styles for Global Virtual Teams.............................................................. 1688 Petros Chamakiotis, University of Bath, UK Niki Panteli, University of Bath, UK Chapter 6.9. Strategising Impression Management in Corporations: Cultural Knowledge as Capital........................................................................................................................ 1707 Caroline Kamau, Southampton Solent University, UK Chapter 6.10. Agile Alignment of Enterprise Execution Capabilities with Strategy......................... 1732 Daniel Worden, RuleSmith Corporation, Canada Chapter 6.11. Governance of Virtual Networks: Case of Living and Virtual Laboratories............... 1750 Brane Semolic, University of Maribor, Slovenia Jure Kovac, University of Maribor, Slovenia Chapter 6.12. Decision-Making for Location of New Knowledge Intensive Businesses on ICT Sector: Portuguese Evidences..................................................................................................... 1765 João J. Ferreira, University of Beira Interior, Portugal Carla S. Marques, University of Trás-os-Montes e Alto Douro, Portugal Cristina Fernandes, University of Beira Interior, Portugal
Chapter 6.13. Executive Judgement in E-Business Strategy............................................................. 1788 Valerie Baker, University of Wollongong, Australia Tim Coltman, University of Wollongong, Australia Chapter 6.14. Prioritizing Corporate R&D Capabilities: The Intellectual Capital Perspective......... 1796 Yuan-Chieh Chang, National Tsing Hua University, Taiwan Pei-Ju Yu, Chunghua Institution for Economic Research, Taiwan Hui-Ru Chi, National Changhua University of Education, Taiwan Chapter 6.15. E-Business in Supply Chain Management.................................................................. 1820 Claudia-Maria Wagner, Dublin Institute of Technology, Ireland Edward Sweeney, Dublin Institute of Technology, Ireland Chapter 6.16. Global Account Management (GAM): Creating Companywide and Worldwide Relationships to Global Customers................................................................................. 1838 Svend Hollensen, University of Southern Denmark, Denmark Vlad Stefan Wulff, University of Southern Denmark, Denmark Chapter 6.17. An Overview of Executive Information Systems (EIS) Research in South Africa....................................................................................................................................... 1858 Udo Richard Averweg, eThekwini Municipality and University of KwaZulu-Natal, South Africa Chapter 6.18. Managerial Succession and E-Business...................................................................... 1868 Anthonia Adenike Adeniji, Covenant University, Nigeria Section VII. Critical Issues This section contains 21 chapters addressing issues such as business as a social institution, social capital theory, advancing women in the workplace through technology, management theory, digital divide, and copyright in business, to name a few. Within the chapters, the reader is presented with an in-depth analysis of the most current and relevant issues within this growing field of study. Issues, such as the current state of cultural integration of the workplace, are discussed. Crucial questions are addressed and alternatives offered, such as the divergence between the expected and realized degrees of innovation in business to business management. Rounding out this section is a look at scientific and technological revolutions, and their implications on different institutions and enterprises. Chapter 7.1. Sociotechnical Issues of Tele-ICU Technology............................................................ 1879 Peter Hoonakker, University of Wisconsin-Madison, USA Kerry McGuire, University of Wisconsin-Madison, USA Pascale Carayon, University of Wisconsin-Madison, USA Chapter 7.2. Contributions of Social Capital Theory to HRM.......................................................... 1896 Marina Burakova-Lorgnier, ECE-INSEEC Research Laboratory, University of Montesquieu Bordeaux 4, France
Chapter 7.3. Social Capital and Third Places through the Internet: Lessons from a Disadvantaged Swedish Community................................................................................................. 1904 Duncan Timms, University of Stirling, Scotland Sara Ferlander, Södertörn University, Sweden Chapter 7.4. Cross-Cultural Challenges for Information Resources Management........................... 1924 Wai K. Law, University of Guam, Guam
Volume IV Chapter 7.5. The Role of Culture in Business Intelligence................................................................ 1933 Jore Park, IndaSea, Inc., USA Wylci Fables, IndaSea, Inc., USA Kevin R. Parker, Idaho State University, USA Philip S. Nitse, Idaho State University, USA Chapter 7.6. Contested Terrain: Place, Work and Organizational Identities...................................... 1948 John Willy Bakke, Telenor Research and Innovation, Norway Tom Erik Julsrud, Telenor Research and Innovation, Norway Chapter 7.7. Evolutionary Diffusion Theory..................................................................................... 1961 Linda Wilkins, RMIT University, Australia Paula Swatman, University of South Australia, Australia Duncan Holt, RAYTHEON, Australia Chapter 7.8. Advancing Women in the Digital Economy: eLearning Opportunities for Meta-Competency Skilling................................................................................................................ 1978 Patrice Braun, University of Ballarat, Australia Chapter 7.9. Interventions and Solutions in Gender and IT.............................................................. 1991 Amy B. Woszczynski, Kennesaw State University, USA Janette Moody, The Citadel, USA Chapter 7.10. Ethical Issues Arising from the Usage of Electronic Communications in the Workplace................................................................................................................................ 1999 Fernando A.A. Lagraña, Webster University Geneva, Switzerland & Grenoble École de Management, France Chapter 7.11. Ethics in E-Marketing: A Marketing Mix Perspective................................................ 2019 Erkan Özdemir, Uludag University, Turkey Chapter 7.12. Accountability and Ethics in Knowledge Management.............................................. 2034 Frank Land, London School of Economics, UK Urooj Amjad, London School of Economics, UK Sevasti-Melissa Nolas, London School of Economics, UK
Chapter 7.13. Management Theory: A Systems Perspective on Understanding Management Practice and Management Behavior............................................................................ 2044 John Davies, Victoria University of Wellington, New Zealand Chapter 7.14. Global Issues in Human Resource Management and Their Significance to Information Organizations and Information Professionals............................................................ 2060 Gail Munde, East Carolina University, USA Chapter 7.15. Does User Centered Design, Coherent with Global Corporate Strategy, Encourage Development of Human Resource Intranet Use?............................................................ 2073 Karine Guiderdoni-Jourdain, Université de la Méditerranee, France Ewan Oiry, Université de la Méditerranee, France Chapter 7.16. Holland’s Vocational Theory and Personality Traits of Information Technology Professionals.................................................................................................................. 2087 John W. Lounsbury, University of Tennessee at Knoxville and eCareerFit.com, USA R. Scott Studham, Oak Ridge National Laboratory, USA Robert P. Steel, University of Michigan-Dearborn, USA Lucy W. Gibson, eCareerFit.com & Resource Assoiciates, USA Adam W. Drost, eCareerFit.com, USA Chapter 7.17. Do Insecure Systems Increase Global Digital Divide?............................................... 2102 Jawed Siddiqi, Sheffield Hallam University, UK Ja’far Alqatawna, Sheffield Hallam University, UK Mohammad Hjouj Btoush, Sheffield Hallam University, UK Chapter 7.18. Teleworking and the “Disability Divide”.................................................................... 2112 John C. Bricout, University of Central Florida, USA Paul M.A. Baker, Georgia Institute of Technology, USA Andrew C. Ward, University of Minnesota, USA Nathan W. Moon, Georgia Institute of Technology, USA Chapter 7.19. A Unified View of Enablers, Barriers, and Readiness of Small to Medium Enterprises for E-Business Adoption................................................................................................. 2135 Ritesh Chugh, CQUniversity Melbourne, Australia Pramila Gupta, CQUniversity Melbourne, Australia Chapter 7.20. Against Strong Copyright in E-Business..................................................................... 2157 D. E. Wittkower, Coastal Carolina University, USA Chapter 7.21. The Structure of Theory and the Structure of Scientific Revolutions: What Constitutes an Advance in Theory?.......................................................................................... 2177 Steven E. Wallis, Institute for Social Innovation, USA & Foundation for the Advancement of Social Theory, USA
Section VIII. Emerging Trends This section highlights research potential within the field of global business while exploring uncharted areas of study for the advancement of the discipline. Introducing this section are chapters that set the stage for future research directions and topical suggestions for continued debate. Discussions assessing the potential of new technologies for user authentication (verification of the user’s identity) on the basis of a practical test and an analysis of trust are offered. Another debate which currently finds itself at the forefront of research is the potential development and application of a ‘Social Network Scorecard’ (SNS) managerial tool to monitor social interchanges and relationships within and across organizations in order to assess the effectiveness of knowledge networks. Found in these chapters, concluding this exhaustive multi-volume set are areas of emerging trends and suggestions for future research within this ever- and rapidly expanding discipline. Chapter 8.1. Emerging Business Models: Value Drivers in E-Business 2.0 and towards Enterprise 2.0..................................................................................................................................... 2202 Te Fu Chen, Lunghwa University of Science and Technology, Taiwan Chapter 8.2. Vision, Trends, Gaps and a Broad Roadmap for Future Engineering........................... 2229 Jan Goossenaerts, Eindhoven University of Technology, The Netherlands Frank Possel-Dölken, RWTH Aachen University, Germany Keith Popplewell, Coventry University, UK Chapter 8.3. Emerging Trends of E-Business.................................................................................... 2244 Pengtao Li, California State University, Stanislaus, USA Chapter 8.4. What is New with Organization of E-Business: Organizational Viewpoint of the Relationships in E-Business.................................................................................................... 2257 Vojko Potocan, University of Maribor, Slovenia Zlatko Nedelko, University of Maribor, Slovenia Matjaz Mulej, University of Maribor, Slovenia Chapter 8.5. New Profession Development: The Case for the Business Process Engineer.............. 2275 Ying Tat Leung, IBM Almaden Research Center, USA Nathan S. Caswell, Janus Consulting, USA Manjunath Kamath, Oklahoma State University, USA Chapter 8.6. Articulating Tacit Knowledge in Multinational E-Collaboration on New Product Designs................................................................................................................................. 2298 Kenneth David Strang, APPC IM Research, USA & University of Central Queensland, Australia Chapter 8.7. Study on E-Business Adoption from Stakeholders’ Perspectives in Indian Firms....... 2331 Ranjit Goswami, Indian Institute of Technology, India S. K. De, Indian Institute of Technology, India B. Datta, Indian Institute of Technology, India
Chapter 8.8. The Global Telecommunications Industry Facing the IP Revolution: Technological and Regulatory Challenges......................................................................................... 2352 Harald Gruber, European Investment Bank, Luxembourg Chapter 8.9. Optimizing and Managing Digital Telecommunication Systems Using Data Mining and Knowledge Discovery Approaches................................................................................ 2360 Adnan I. Al Rabea, Al Balqa Applied University, Jordan Ibrahiem M. M. El Emary, King Abdulaziz University, Kingdom of Saudi Arabia Chapter 8.10. An ICT-Based Network of Competence Centres for Developing Intellectual Capital in the Mediterranean Area..................................................................................................... 2380 Marco De Maggio, University of Salento, Italy Pasquale Del Vecchio, University of Salento, Italy Gianluca Elia, University of Salento, Italy Francesca Grippa, University of Salento, Italy Chapter 8.11. Recognizing Innovation through Social Network Analysis: The Case of the Virtual eBMS Project............................................................................................... 2398 Grippa Francesca, University of Salento, Italy Elia Gianluca, University of Salento, Italy Chapter 8.12. Organizational Password Policy.................................................................................. 2420 Alex Ozoemelem Obuh, Delta State University, Nigeria Ihuoma Babatope, Delta State University, Nigeria Chapter 8.13. National Intellectual Capital Stocks and Organizational Cultures: A Comparison of Lebanon and Iran................................................................................................... 2433 Jamal A. Nazari, Mount Royal College & University of Calgary, Canada Irene M. Herremans, University of Calgary, Canada Armond Manassian, American University of Beirut, Lebanon Robert G. Isaac, University of Calgary, Canada Chapter 8.14. The Role of ICTs and the Management of Multinational Intellectual Capital............ 2457 Mirghani S. Mohamed, New York Institute of Technology, Bahrain Mona A. Mohamed, New York Institute of Technology, Bahrain Chapter 8.15. An Approach to Efficient Waste Management for SMEs via RBVOs........................ 2473 Stamatia-Ann Katriou, ALTEC S.A., Greece Ioannis Ignatiadis, Kingston University, UK Garyfallos Fragidis, Technological Educational Institute of Serres, Greece Evangelos Tolias, ALTEC S.A., Greece Adamantios Koumpis, ALTEC S.A., Greece Chapter 8.16. Supply Chain Risk Management Driven by Action Learning..................................... 2493 H.P. Borgman (Hans), University of Leiden, The Netherlands Wilfred Rachan, University of Leiden, The Netherlands
Chapter 8.17. Tailor-Made Distance Education as a Retention Strategy: The “Learning at the Workplace” Program in Thailand.................................................................... 2512 Prathurng Hongsranagon, Chulalongkorn University, Thailand Chapter 8.18. Knowledge Redundancy, Environmental Shocks, and Agents’ Opportunism............ 2525 Lucio Biggiero, University of L’Aquila, Italy Chapter 8.19. Embracing Guanxi: The Literature Review................................................................ 2554 Jilong Zhang, RMIT University, Australia Nattavud Pimpa, RMIT University, Australia
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Preface
The world is always expanding with people, ideas, and technology. Global business looks to capitalize on the successes of modern society and the range of products and services people look for around the world. As people and cultures change, so do the products and services they look for. In addition to producing and marketing new products for consumers, businesses create jobs and spur local growth in infrastructure. As change goes, so do the industries surrounding it; businesses must be ready to adapt to new technologies, products, and consumers. That is why Information Science Reference is pleased to offer this four-volume reference collection that will empower students, researchers, and academicians with a strong understanding of critical issues within global business by providing both extensive and detailed perspectives on cutting-edge theories and developments. This reference serves as a single, comprehensive reference source on conceptual, methodological, technical, and managerial issues, as well as providing insight into emerging trends and future opportunities within the discipline. Global Business: Concepts, Methodologies, Tools and Applications is organized into eight distinct sections that provide comprehensive coverage of important topics. The sections are: (1) Fundamental Concepts and Theories, (2) Development and Design Methodologies, (3) Tools and Technologies, (4) Utilization and Application, (5) Organizational and Social Implications, (6) Managerial Impact, (7) Critical Issues, and (8) Emerging Trends. The following paragraphs provide a summary of what to expect from this invaluable reference tool. Section 1, Fundamental Concepts and Theories, serves as a foundation for this extensive reference tool by laying the groundwork within the subject matter, and addressing crucial theories essential to the understanding of global business. The book opens with Marketing Strategy, Technology and Modes of Entry in Global Retailing by Rajagopal, breaking down how new businesses can enter their respective markets with proper strategy and best practices in place to allow substantive growth. The section also contains Engagement, Immersion, and Learning Cultures by Christopher Keesey, offering a guide to avoiding common pitfalls while suggesting a plan for maximum training benefit in virtual world implementations. Another among the vital chapter selections is An Overview of International Intellectual Capital (IC) Models and Applicable Guidelines by Tomas M. Banegil Palacios and Ramon Sanguino Galvan, moving out of the fundamental concepts and into some critical theory on intellectual capital management. Section 2, Development and Design Methodologies, presents in-depth coverage of the conceptual design and architecture of global business, focusing on aspects such as IT strategy, supply chain management, knowledge governance, and business models. Designing and implementing effective processes and strategies are the focus of such chapters as Collaborative Enterprise Architecture for Municipal Environments by Leonidas G. Anthopoulos, or Linking Information Technology, Knowledge Manage-
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ment, and Strategic Experimentation by V. K. Narayanan. The section also contains such revolutionary methodological suggestions as those found in A Reverse Auction-Based E-Business Model for B2C Service Markets by Tobias Kollmann. For those in strategic planning departments of their businesses, this section provides a vital reference of the latest research in the design and development of planning and growth of your business. Section 3, Tools and Technologies, shows how new devices and models can be implemented into the growth of global business. This comprehensive section includes such chapters as On-Line Credit Card Payment Processing and Fraud Prevention for e-Business by Wichian Premchaiswadi and James G. Williams, breaking down security measures involved in account payment and credit card processing, and Achieving Electric Restoration Logistical Efficiencies During Critical Infrastructure Crisis Response by Murray E. Jennex, Robert Judge, Eric Frost, and Teresa Durbin, an important look into crisis management and the role business infrastructure (especially within the energy sector) must play in the process. Another fantastic chapter in section 3 is Learning Organizations or Organizations for Learning? How Small Firms can Learn from Planned and Random Technical Problem-Solving by Corrado lo Storto, detailing knowledge management and learning strategies for keeping employees informed and sharp in critical thinking. The section contains a diverse selection of the latest strategies, tools, and technologies that businesses have begun to adopt around the globe. Section 4, Utilization and Application, describes how various strategies and technologies in global business have been utilized and offers insight on important lessons for their continued use and evolution. This section is filled with case studies and research from leading industry members around the world, including selections such as The ‘Knock-on’ Effect of E-Business upon Graphic Design SMEs in South Wales by Lyndon Murphy, Joanna Jones, Huw Swayne, and Brychan Thomas; Lessons Learned from the NASA Astrobiology Institute by Lisa Faithorn and Baruch S. Blumberg; and even as diverse as Exploring Organizational Learning and Knowledge Exchange through Poetry by Louise Grisoni. Section 4 has the broadest range of topics, the largest volume of chapters, and contains works from authors from over a dozen countries. Section 5, Organizational and Social Implications, discusses the human impact on global business, and how people influence the decision making and directions that companies take, with topics including human resource management, synergy, information transfer, and many more. The section includes chapters such as Trust, Virtual Teams, and Grid Technology by Genoveffa Giambona, Nicholas L.J. Silburn, and David W. Birchall, detailing the importance of employee trust and security measures in place in networked technologies within a business. Another representative chapter is The Multicultural Organization by Tongo Constantine Imafidon, part of a group of chapters on culture in business. Closing out section five is The Benefits of Home-Based Working’s Flexibility by Diana Benito Osorio, which, as the title suggests, compiles benefits of home business and strategies for growth in small and home businesses. Section 6, Managerial Impact, presents focused coverage of global business as it relates to managerial improvements and considerations in the workplace. In Assessment Strategies for Servant Leadership Practice in the Virtual Organization, Darin R. Molnar writes about “servant leadership,” a method gaining popularity in recent decades as a management technique, and its integration into virtual organizations. Prioritizing Corporate R&D Capabilities by Hui-Ru Chi, Pei-Ju Yu, and Yuan-Chieh Chang offers strategies and lessons learnt about the importance of research and development, with surveys from managers of different industries relaying their findings. An always vital topic in management is succession, and Managerial Succession and E-Business by Anthonia Adenike Adeniji closes out section 6.
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Section 7, Critical Issues, addresses vital issues related to global business, including ethics, security, digital divide, intellectual capital, the role of culture and gender, and business as social enterprise. The section has a broad range of critical, theoretical, and analytical topics, and closes out with two fascinating chapters: Against Strong Copyright in E-Business by D. E. Wittkower and The Structure of Theory and the Structure of Scientific Revolutions by Steven E. Wallis. These two chapters take sometimes marginalized or ignored topics and show their vital relevance to global business as ways of understanding how such things as intellectual property or organizational (r)evolution can inhibit or shape growth. Section 8, Emerging Trends, highlights areas for future research within the field of global business, while exploring new avenues for the advancement of the discipline. This section holds chapters such as The Global Telecommunications Industry Facing the IP Revolution by Harald Gruber, discussing how Internet Protocols are changing, and what businesses inside and outside the telecommunications industry must do to adapt and grow. Another emerging topic is covered in Organizational Password Policy by Alex Ozoemelem Obuh and Ihuoma Sandra Babatope, wherein the authors discuss the importance of keeping strict security measures such as password protection within businesses. As technology expands, and knowledge management grows into distance learning and cultural integration, chapters such as Tailor-Made Distance Education as a Retention Strategy: The “Learning at the Workplace” Program in Thailand by Prathurng Hongsranagon become vital resources for managers of global businesses. Although the primary organization of the contents in this multi-volume work is based on its eight sections, offering a progression of coverage of the important concepts, methodologies, technologies, applications, social issues, and emerging trends, the reader can also identify specific contents by utilizing the extensive indexing system listed at the end of each volume. Furthermore to ensure that the scholar, researcher, and educator have access to the entire contents of this multi volume set as well as additional coverage that could not be included in the print version of this publication, the publisher will provide unlimited multi-user electronic access to the online aggregated database of this collection for the life of the edition, free of charge when a library purchases a print copy. This aggregated database provides far more contents than what can be included in the print version, in addition to continual updates. This unlimited access, coupled with the continuous updates to the database ensures that the most current research is accessible to knowledge seekers. As a comprehensive collection of research on the latest findings related to multinational and multicultural enterprises, Global Business: Concepts, Methodologies, Tools and Applications, provides researchers, administrators, and all audiences with a complete understanding of the development of applications and concepts in global business. Given the vast number of issues concerning usage, failure, success, policies, strategies, and applications of global business in organizations, Global Business: Concepts, Methodologies, Tools and Applications addresses the demand for a resource that encompasses the most pertinent research in global business development, deployment, and impact.
Section I
Fundamental Concepts and Theories
This section serves as a foundation for this exhaustive reference tool by addressing crucial theories essential to the understanding of global business. Chapters found within these pages provide an excellent framework in which to position global business within the field of information science and technology. Insight regarding the critical incorporation of global measures into global business is addressed, while crucial stumbling blocks of this field are explored. With a little over 10 chapters comprising this foundational section, the reader can learn and chose from a compendium of expert research on the elemental theories underscoring the global business discipline.
1
Chapter 1.1
Marketing Strategy, Technology and Modes of Entry in Global Retailing Rajagopal Monterrey Institute of Technology and Higher Education, ITESM, Mexico
A firm, which would like to involve itself in the international business, may look for its entry into international marketing in many possible ways including exporting, licensing, franchising, or as a production firm with multi-national plant locations. However, at any level of market entry the managerial trade-off lies between extent of risk and operational control. The low intensity modes of entry minimize risk e.g. contracting with a local distributor requires no investment in the destination country market as the local distributors may own offices, distribution facilities, sales personnel, or marketing campaigns. Under the
normal arrangement, whereby the distributor takes title to the goods or purchases them as they leave the production facility of the international company, there is not even a credit risk, assuming that the distributor has offered a letter of credit from his bank. At the same time such arrangement to enter a destination country may minimize control along with the risk factor. In many cases, lowintensity modes of market participation cut off the international firm with information network while operational controls can only be obtained through higher-intensity modes of market participation, involving investments in local executives, distribution, and marketing programs.
DOI: 10.4018/978-1-60960-587-2.ch101
Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
Marketing Strategy, Technology and Modes of Entry in Global Retailing
Breakfast cereal, a relatively new introduction to the Bulgarian market, is the fastest growing sector in the Bulgarian bakery products market. According to a research study (Euromonitor, 2006), ready-to-eat breakfast cereals grew by 90 percent in value terms during 2000-2005 and the market grew by approximately 14 percent just in 2005. Despite this impressive growth, cereal consumption in Bulgaria is low compared to other countries, which illustrates the immaturity of the market and its potential for the future. Besides the “novelty” of breakfast cereals, a key reason for the success of breakfast cereals in Bulgaria is their healthy image, which manufacturers have carefully created by illustrating that their products are part of a balanced diet. Although the concept of health and wellness is growing in popularity in Bulgaria, consumers still need additional education on the subject. The foreign cereal manufacturing companies like Nestle, Kraft, Kellogg and General Mills etc. have therefore invested heavily in radio and television advertising to promote a healthy image for their products and attract health conscious consumers. These companies have also set up demonstrations in supermarkets that are designed to educate consumers on the health benefits of breakfast cereals. By using samples and other promotional materials, manufacturers have tried to inspire trials and eventually repeat purchases of their products. These campaigns mainly targeted the bigger cities, where consumers are generally more willing to try new products. The entry of foreign brands in the breakfast cereals in Bulgaria is further moved ahead by the fast expansion of supermarkets and the development of this distribution channel over the next several years will play a crucial role in making breakfast cereals more widely available (Euromonitor, 2006). Many companies begin their internationalization opportunistically through a variety of arrangements that may be described as “piggybacking,” because they all involve taking advantage of a channel to an international market rather than se-
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lecting the country-market in a more conventional manner. Piggybacking is an interesting development. The method means that organizations with little exporting skill may use the services of one that has. Another form is the consolidation of orders by a number of companies in order to take advantage of bulk buying. Normally these would be geographically adjacent or able to be served, say, on an air route. The fertilizer manufacturers of Zimbabwe, for example, could piggyback with the South Africans who both import potassium from outside their respective countries. Such practices may be noticed as American breakfast cereal products like Post from the owners of the leading US brand, which entered in the Mexican market via their subsidiary Kraft rather than direct from USA, thus leading to the rather bizarre situation of packs of breakfast cereals with English language packaging covered with stickers in Spanish. The most common form of piggybacking is to internationalize by serving a customer who is more international than the vendor firm. Thus, a customer requests an order, delivery, or service in more than one country, and the supplier starts selling internationally in order to retain the customer and increases its penetration of the account. This is particularly common in the case of businessto-business companies and technology-oriented start-ups (Arnold, 2003). The innovative concept of market entry strategy is based on moving with consumer space which indicates that foreign firms enter the destination market by developing adequate consumer awareness on the products and services prior to launch. This strategy is followed largely by the fast moving consumer goods manufacturing companies and such practice is termed as go-to-market strategy. Go-to-market planning enables the firm to achieve higher margins, accelerated revenue growth and increased customer satisfaction through existing sales channels. An effective go-to-market strategy aligns products & services, processes, and partners with customers and markets to deliver brand promise, the desired customer experience, and tangible value. Go-to-
Marketing Strategy, Technology and Modes of Entry in Global Retailing
market strategy services help technology suppliers overcome market challenges. Anti-ageing products are driving growth in Hong Kong’s skin care market, on the back of increasing consumer interest in premium products and the development of consumer-focused cosmetics retailing. Consumer interest in premium products has been spurred, in part, by recent media reports on the safety of chemicals present in some skin care products. Catching on to this consumer trend, manufacturers have been introducing more premium anti-ageing products containing rare ingredients, and products benefiting from more advanced technology, to the market. This has generated greater consumer interest in premium quality products and has provided a further boost to the market. Guerlain, for example, is expected to launch a new skin care cream in 2006, which is based on a rare orchid extract and is expected to retail for more than US$350. Further, a recent entrant to Hong Kong’s skin care market, Sulwhasoo which is a premium herbal based brand from Amore Pacific of Korea that draws on Oriental medicine by using a unique compound of five herbs to deliver a range of products targeted at women over 35. The value driver of growth in the anti-ageing products market in Hong Kong is the trend towards concept stores and beauty boutiques, which are retail outlets designed to emphasize the experiential aspects of premium cosmetic products. Developed to attract new customers and gain their loyalty in Hong Kong’s increasingly competitive market, these brandspecific beauty salons and spas, not only engage in a highly personalized product sales process, but also provide make-up and skin care services. Since 2004, major players, such as Kose, L’Oréal, H2O and cult brand Aesop, have set up concept stores around the city, in the hopes of developing a loyal customer base (Hofmann, 2006). Such retail strategy where concept of the product is delivered with practical experience on it establishes the goto-market strategy on consumer space.
Some firms who are aggressive have clearly defined plans and strategy, including product, price, promotion, and distribution and research elements. Passiveness versus aggressiveness depends on the motivation to export. In countries like Tanzania and Zambia, which have embarked on structural adjustment programs, organizations are being encouraged to export, motivated by foreign exchange earnings potential, saturated domestic markets, growth and expansion objectives, and the need to repay debts incurred by the borrowings to finance the programs. The type of export response is dependent on how the pressures are perceived by the decision maker. The degree of involvement in foreign operations depends on “endogenous versus exogenous” motivating factors, that is, whether the motivations were a result of active or aggressive behavior based on the firm’s internal situation (endogenous) or a result of reactive environmental(exogenous) changes (Piercy, 1982). There is certainly no single strategy that fits all firms, products and markets. The competitive strategy for an established firm to start a new venture and launch a new product must be shaped by the characteristics of the firm, the market, and other environmental factors. Market entry through expansion of the company draws many challenges to firms considering new business options. Capitalizing on overseas markets often opens doors to new levels of top and bottom line growth. Moreover, introducing a new product or service into a new market is an even bigger strategic challenge. A Successful Entry strategy may conceptualize and implement well structured entry processes to drive future growth, explore diversified stream of revenues and augment profit margins. It also addresses new competitors, customers, partners, suppliers and other market dynamics. However, there are five major modes which a foreign firm may apply to enter in the international markets. These modes of entry include exporting, contractual agreement, joint venture, strategic alliance and wholly owned subsidiaries.
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Marketing Strategy, Technology and Modes of Entry in Global Retailing
EXPORTING A firm may organize indirect export through the intermediaries or export agents of the parent country. On the contrary, in direct exporting foreign markets are reached by exporters through agents located outside their parent markets. Exporting is a low risk-low investment strategy wherein a company may minimize the risk of dealing internationally by exporting domestically manufactured products either by minimal response to inquiries or by systematic development of demand in foreign markets. Exporting activity requires small capital for quick start. Exporting is also a good way to gain international experience. A major part of the overseas involvement of large firms is through export trade managed by the various channels involved in the process. The channels involved in direct and indirect exporting are listed in Table 1. Some companies, which occasionally carry out export activities typically, use the services of the broker. Brokers are the middlemen who bring buyers and sellers in contact for a negotiated commission or brokerage. They are just the trade facilitators and do not take the ownership of the product. These brokers operate in international markets independently and do not belong to any firm. The manufacturer’s export agent (MEA) may be an exclusive agent engaged by the firm to offer services as desired by the firm. The MEA’s are vested with the right to take marketing decisions on behalf of the firm, arrange negotiations Table 1. Export Channels Indirect Exporting
Direct Exporting
Broker
Representative
Manufacturer’s Export Agent
Merchant Middlemen
Combination Export Manager
Company Sales Manager
Group Export Forum
Own Distribution Network
Domestic Middlemen Company Based Managers
4
and trade agreements and the delivery of the consignment to the buyer. The Combination Export Manager (CEM) provides services over and above the broker and the MEA by way of taking over the entire export operations of a firm on a commission basis. The export operations involve a variety of activities like identifying the country, markets, analyzing consumer behavior, product designing, technological improvements, competitive pricing, distribution, promotion, negotiations with the governments of countries, public relations and collecting marketing information. The group export forums are associations of exporters who collectively manage to export activities. These forums are recognized by the government of the parent country and provide admissible concessions on export activities like licensing, taxes and duties infrastructure, etc. Middlemen who have base in the parent country of the exporting firm also function as one of the channels for indirect exports. The company based managers are the salaried personnel of the exporting firm and possess the responsibility of total export management. In direct exporting activities, the firm appoints its own export representatives for conducting the export operations in the respective markets or countries. The Merchant Middlemen are a type of intermediary based in foreign markets that buy products on their own and resell these to the identified countries functioning with substantial operational managers. They may also take up export activities without involving any indirect channel. Such offices may also be networked as an effective distribution channel for a region in order to cater to identify countries thereof. Li & Fung, Hong Kong’s largest export trading company, has been an innovator in supply-chain management. It performs the higher-value-added tasks such as design and quality control in Hong Kong, and outsources the lower-value-added tasks to the best possible locations around the world. To produce a garment, for example, the
Marketing Strategy, Technology and Modes of Entry in Global Retailing
company might purchase yarn from Korea that will be woven and dyed in Taiwan, then shipped to Thailand for final assembly, where it will be matched with zippers from a Japanese company. The corporate philosophy of Li & Fung envisages that for every order, the goal is to customize the value chain to meet the customer’s specific needs. The organizational approaches that keep the company towards growth in profits and size largely set around small customer-focused units, competitive incentives and compensation structure and it’s leaning towards of venture capital strategy as a vehicle for business development (Fung and Margaretta, 1998). The company operates in partnership with customers to cater to their needs of competitive pricing, quality, on-time delivery, as well as ethical sourcing. The company manages the logistics of producing and exporting private label consumer goods across many producers and countries1. The firms choosing to enter the international markets through exporting activities may choose to engage the goods listed under open general license which does not involve heavy documentation process. However the goods that are not controlled, regulated or prohibited by other government departments need to be reported to customs prior to export by means of export declaration. On the contrary regardless of their value, export of all goods that are controlled, regulated, or prohibited need to be supported by valid permits, licenses, or certificates required by the government departments or agencies that regulate the export of these goods. A firm also opts for direct exporting as a platform to enter into the destination country. This approach is the most ambitious and difficult as the exporting firm handles every aspect of the exporting process independently from market research and planning to foreign distribution and collections. Consequently, a significant commitment of management time and attention is required to achieve good results. However, this approach
may lead to maximum profits, higher control and long-term growth.
CONTRACTUAL AGREEMENT There are several types of contractual agreements including patent licensing agreement, turnkey operation, co-production agreement, management contract, and licensing. The patent licensing agreement is based on either a fixed fee or a royalty-based agreement and delivering managerial training on manufacturing and quality control process. The plant construction, personnel training, and initial production runs on a fixed-fee or cost-plus arrangement are be covered under turn-key operation agreement. The co-production agreement was one of the popular practices among the Soviet-bloc countries, where plants were built and then paid for with part of the output. In the Middle East, the management contract requires that an MNC provide key personnel to operate the foreign enterprise for a fee until local people acquire the ability to manage the business independently.
LICENSING This is one of the common tools of franchising a firm to set quality and operational control standards. In the past, multinational companies used licensing for many reasons. One of the major reasons may be towards the use of a trade mark of the company. Licensing may be understood as one of the varieties of contractual agreements whereby a multinational firm makes available intangible assets such as patents, trade secrets, know-how, trademarks, and company name to foreign companies in return for royalties or other forms of payment. Transfer of these assets is usually accompanied by technical services to ensure their proper use. It also helps in regulating the import and export operations of firms in
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Marketing Strategy, Technology and Modes of Entry in Global Retailing
such countries or regions where trade restrictions prohibit the movement of products. Some of the advantages of licensing are as follows: •
• •
•
•
•
•
•
•
Licensing is a quick and easy entry tool with little capital investment in the foreign markets Some countries offer licensing as the only means of tapping the market. Licensing is also considered to be an effective tool for life extension of products during their stage of maturity in order of their life cycle. Licensing is a good alternative to start foreign production and marketing activity in a destination country which has economic inflation, shortages of skilled-labor, increasing domestic and foreign governmental regulation and restriction, and severe international competition. In the licensing arrangement periodic royalties are guaranteed, whereas shared income from investment fluctuates and stays risky. The company which has strong domestic base can benefit through licensing arrangement in developing customized products without expensive research. Licensing provides an alternative when exports are no longer profitable because of intense competition. Licensing can reduce transportation costs and help promoting exports in non-competitive markets. One of the major advantages of licensing is the immunity over stringent political intervention as expropriation.
On the contrary, the economic liberalization policy envisages the de-licensing of goods and services (notified) for mutual business growth. Under contract manufacturing, a firm gets its products manufactured by an independent local firm as per the agreement. Such export mecha-
6
nism is chosen by the firms typically where the marketing potential seems to be low with tariff walls that are too high. Assembling involves the import of raw material and mechanical parts for manufacturing any product. Such an operation is usually labor intensive, despite high capital investment in business. This mode of entry into international marketing would be advantageous in countries which do not impose heavy import duties and which encourage free exports. Assembling firms take the benefit of low wage rates by shifting labor intensive operations to the foreign market that results in a lower final price of the product. Largely, local laws of a country play a big role in the decision-making for setting up an assembling unit in foreign country. Procter & Gamble offered most of its exceptional growth through continuous innovation and building global research facilities. The company lagged behind in achieving its growth objectives by spending greater and greater amounts on research and development for smaller and smaller payoffs during 2000. This situation revolutionized the strategic management process of the company to dispense with the company’s age-old invent it ourselves approach and reorient to innovation following connect and develop model. Now, the company collaborates with suppliers, competitors, scientists, entrepreneurs, and others, systematically scouring the world for proven technologies, packages, and products that P&G can improve, scale up, and market, either on its own or in partnership with other companies. Connect and develop approach, brought P&G an increase of about 60 percent productivity through research and development. In the past two years, P&G launched many new products for which some aspect of development came from outside the company (Hustom and Sakkab, 2006). Among most successful connect-and-develop products of the company include Oil of Olay, Tide, Crest dental products and Mr. Clean Magic Eraser. The success of this strategy further revealed in
Marketing Strategy, Technology and Modes of Entry in Global Retailing
launching a unique portfolio in the US Market. The company that revolutionized the laundry industry with the launch of Tide(R) in 1946 has begun offering an on-premise laundry (OPL) and daily cleaners program to hotels in select markets across the United States. Marketed under the P&G Pro Line(TM) brand name, the Lodging Program aims to leverage reputation of the company as a leader in home and commercial cleaning products to help hotel housekeeping staffs discover how the company’s top- performing brands maximize productivity and increase guest satisfaction. The program is built around popular householdname laundry brands including Tide, Downy(R), and Clorox(R) Bleach, as well as daily cleaners including Spic and Span(R) 3-in-1 Disinfecting All-Purpose Spray and Glass Cleaner and Comet(R) Disinfecting Bathroom Cleaner. The Lodging Program presents an alternative to the housekeeping departments of lodging establishments (Proctor and Gamble, 2005). Technology licensing is a contractual arrangement in which the licensor’s patents, trademarks, service marks, copyrights, trade secrets, or other intellectual property may be sold or made available to a licensee for compensation that is negotiated in advance between the parties. A technology licensing agreement usually enables a firm to enter a foreign market quickly, and poses fewer financial and legal risks than owning and operating a foreign manufacturing facility or participating in an overseas joint venture. In considering the licensing of technology, it is important to remember that foreign licensees may attempt to use the licensed technology to manufacture products in direct competition with the licensor or its other licensees.
FRANCHISING Franchising is not a business itself, but a way of doing business. It is essentially a marketing
concept introducing an innovative method of manufacturing and distributing goods and services. Franchising is a business relationship in which the franchisor (the owner of the business providing the product or service) assigns to independent entrepreneur (the franchisee) the legal right to manufacture, market and distribute the franchisor’s goods or service using the brand name for an agreed period of time. The International Franchise Association defines franchising as a continuing relationship in which the franchisor provides a licensed privilege to do business, plus assistance in organizing training, merchandising and management in return for a consideration from the franchisee. Franchising has become popular because it allows a much greater degree of control over the marketing efforts in the foreign country. In franchising, product lines and customer service are standardized, two important features from a marketing perspective though cultural differences might require adaptation. Franchising can offer people looking at self-employment a greater chance of success than starting their own businesses, but it is a path that many people are not aware is open to them. A franchisor’s main ongoing commitment to his franchisees is to provide support. A support program should be well defined prior to joining a given franchise group and is likely to cover areas such as staff issues, marketing and system compliance. There are four possible models of franchising as discussed below: •
•
•
Manufacturer-Retailer: Where the retailer as franchisee sells the franchisor’s product directly to the public. (e.g. Automobile dealerships). Manufacturer-Wholesaler: Where the franchisee under license manufactures and distributes the franchisor’s product (e.g. Soft drink bottling arrangements). Wholesaler-Retailer: Where the retailer as franchisee purchases products for retail sale from a franchisor wholesaler. (e.g.
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Marketing Strategy, Technology and Modes of Entry in Global Retailing
•
Hardware equipments and automotive product stores) Retailer-Retailer: Where the franchisor markets a service, or a product, under a common name and standardized system, through a network of franchisees.
The first two categories cited above are often referred to as product and trade name franchises. These include arrangements in which franchisees are granted the right to distribute a manufacturer’s product within a specified territory or at a specific location, generally with the use of the manufacturer’s identifying name or trademark, in exchange for fees or royalties. The business format franchise, however, differs from product and trade name franchises through the use of a format, or a comprehensive system for the conduct of the business, including such elements as business planning, management system, location, appearance and image, and quality of goods. Papa John’s has recently expanded its business in Edinburgh and Glasgow (UK). Its new-look stores compete with more established names like Pizza Hut and Domino’s Pizza. The competition in the fast food market is fierce and challenging for potential franchisees. Papa John’s operates a comprehensive marketing and public relation campaign for all stores. Launch events typically include a ‘grand opening’ day with entertainment, free pizzas and visits from local dignitaries. It also runs national marketing campaigns and special offers, backed up by a marketing team to help franchisees promote their stores at a local level. Franchisees can expect to pay extra for those services. The prospective franchisees need to undergo three stages interview process which include an initial telephone interview to ascertain suitability and solvency of applicants, an informal meeting and presentation of factual details including an outline of potential working hours and staffing requirements and a more formal gathering to discuss site positioning and
8
to release paperwork, including a legal/franchise agreement and a business plan template to present to the bank. The company has proposed a 5 percent royalty fee on the store’s weekly net sales figures, and a 4 percent marketing fee is also charged on its weekly net sales2. •
•
•
•
•
•
•
The franchisor provides detailed consultation and training in operating the business as well as choosing locations for the business The franchisee benefits from operating under the established brand image and reputation of the franchisor The franchisees usually need less capital than they would if they were setting up a business independently because the franchisors, through their pilot operations and buying power, will have eliminated unnecessary expenses. The franchisor helps the franchisee obtain occupation rights to the trading location, comply with planning (zoning) laws, prepare plans for layouts, plans ergonomics and refurbishment, and provide general assistance in calculating the correct level and mix of stock for the opening launch of the business. The franchisee taps into the bulk purchasing power and negotiating capacity made available by the franchisor by reason of the size of the franchised network. The franchisee has access to use of the franchisor’s patents, trade marks, copyrights, trade secrets, and any secret processes or formulae. The franchisee has the benefit of the franchisor’s continuous research and development programs, which are designed to improve the business and keep it up-to-date and competitive.
Marketing Strategy, Technology and Modes of Entry in Global Retailing
One of the drawbacks of franchising is the need for careful and continuous quality control. Such close supervision of the various aspects of distant operations requires well-developed global management systems and labor-intensive monitoring. Inevitably, the relationship between the franchisor and franchisee must involve the imposition of controls. These controls will regulate the quality of the service or products to be provided or sold by the franchisee to the consumer. As the effective managerial skills are required, international franchising has become successful largely among those enterprises which have long experience with franchising at home before venturing out in international markets.
JOINT VENTURES A joint venture involves partnership between two or more business firms interested in pooling their resources and expertise to achieve a common goal. The risks and rewards of the enterprise are also shared. The reasons for forming a joint venture may include business expansion, development of new products or moving into new markets, particularly overseas. The joint venture may offer more resources, increased capacity of production, enhanced technical expertise and established markets and distribution channels. Entry into an international market would be possible either as a wholly owned subsidiary of any firm or as a joint venture. Joint ventures provide the best partnerlike manner of obtaining foreign trade income the firm chooses to begin a business relationship with a firm in the host country. These two partners could agree upon a contract setting out the terms and conditions of how this will work. Alternatively, joint ventures may be set up as a separate joint venture business, possibly a new company. A joint venture company can be a very flexible option wherein partners own substantial resources in the company, and agree on a managing strategy. Firms of any size can use joint
ventures to strengthen long-term relationships or to collaborate on short-term projects. A successful joint venture can offer: • • • •
Access to new markets and distribution networks Increase in production capacity Risk sharing and control process policies among business partners Working with specialized staff and technology
However, partnering in business may also be complex. It may consume time and effort to build the right relationship while operational problems may grow with the following ideological and functional discrepancies: •
•
•
•
The objectives of the venture are not clear and communicated among the partnering firms There exists an imbalance in levels of expertise, investment or assets set into the venture by the different business partners Coordination problems of cross- cultural issues and management styles affecting the functional integration and workplace co-operation Lack of sufficient leadership and support in the early stages
Success in a joint venture depends on thorough research and analysis of aims and objectives. This should be followed up with effective communication of the business plan to everyone involved. International joint ventures are used in a wide variety of manufacturing, mining, and service industries and frequently involve technology licensing. The company looking for a joint venture invites foreign firms by issuing by a regional or global invitation to share stock ownership in the new unit. However, the control of the unit will rest with the companies accepting either a minority or a majority position. Largely, multi-national
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Marketing Strategy, Technology and Modes of Entry in Global Retailing
companies prefer wholly owned subsidiaries for effective control. A major potential drawback of joint ventures, especially in countries that limit foreign companies to minority participation, is the loss of effective managerial control. This can result in reduced profits, increased operating costs, inferior product quality, exposure to product liability, and environmental litigation and fines. When firms decide to create a joint venture, the terms and conditions need to set out in a written agreement. This will help prevent any misunderstandings once the joint venture is up and running. A written agreement should cover: • • •
• • • •
• •
•
The structure of the joint venture The objectives of the joint venture Financial contributions, liabilities, distribution of profit, and other matters related to corporate finance and accounts Protocol on transfer assets or employees in or out of the joint venture Ownership of intellectual property created by the joint venture Management and control of operational issues Responsibilities, tasks and processes to be followed in production and operations activities Protocol on managing liabilities, sharing of profits and losses Policy and process of disputes settlement between the partnering firms in the joint venture, and Exit policies to being the joint venture to an end and cause and effect management at post-closure.
Ranbaxy Laboratories Limited (Ranbaxy) has raised its equity stake in Nihon Pharmaceutical Industry Co., Ltd. (NPI), a Joint Venture between Ranbaxy and Nippon Chemiphar Co. Ltd. (NC), from the present 10% to 50%. With this enhancement, NPI will become a 50:50 Joint Venture
10
between Ranbaxy and NC. Ranbaxy and NC have signed the agreement on November 11, 2005. The increasing financial stakes of Ranbaxy in the shareholding of the joint venture reinforces the Company’s strong commitment to the Japanese market. Further, the new structure recognizes the equal commitment of both partners and their intent to grow the generics business in Japan, in a collaborative manner. Ranbaxy and NPI have had a successful relationship. This logical move by Ranbaxy to enhance its stake flows from the increased comfort level of both partners and take the business to higher levels of performance. The 50:50 JV exemplifies the synergy and the strengths, which the respective companies bring to the Joint Venture. In Japanese ethical pharmaceutical industry, NC is one of the first companies to recognize the importance of generics and to make the generic business a pillar of the company’s business. NC intends to be a leading company in Japan’s generics market. Both partners have a complementary role to play. NC provides the regulatory know how and in-depth knowledge of the Japanese market, while Ranbaxy brings to the table, its diversified and rich generics product pipeline along with its astute understanding of the global generics business3. Smaller firms often want to access a larger partner’s resources such as a strong distribution network, specialist employees, and financial resources. The larger company might benefit from working with a more flexible, innovative partner or simply from access to new products or intellectual property (IP). Joint ventures offer mutual advantages for domestic and foreign firms to operate in a global competitive business environment sharing both capital and risk and by making use of mutual technical potentials. Japanese companies, for example, prefer entering into joint ventures with American firms as such arrangements help them to ensure against possible trade barriers. American firms, on the other hand like to venture with Japanese firms to explore product innovation
Marketing Strategy, Technology and Modes of Entry in Global Retailing
at low-cost Japanese manufacturing technology, and make pace to enter a wide Asian market. The joint venture in this ways helps both the international firms to utilize established channels and to outperform potentially tough competitors in respective countries. House Foods and Takeda Pharmaceutical have signed a joint venture agreement on their beverage and food businesses. Under the terms of the agreement, the two companies will establish a new company, House Wellness Foods Corporation, with a capital of 100 million yen ($840,000), on April 2006. House Foods will have a 66% stake in the new company while Takeda Pharmaceutical will retain the remaining 34%. After the initial 18-month joint venture period, the new company will become a wholly owned House Foods subsidiary (Tsukioka, 2006). A joint venture serves as a center of resource appropriation and making a foreign firm’s entry into a new terrain easier than other modes. It should not be viewed as a handy vehicle to reap money without effort, interest, or additional resources. In view of the above benefits, the joint ventures stand as a popular mode to seek entry in a foreign country.
STRATEGIC ALLIANCE A strategic alliance for international marketing is developed by pooling resources directly in collaboration. This strategy is more advantageous than joint venture. In this process the business partners bring together the specific skills of production, marketing and control in order to maximize their profit and have a major stake in the international business scenario. Many organizations have come to rely on alliances with key players in the marketplace as strategic ventures for maintaining a competitive advantage. These key relationships can help foster organizational learning, thus giving an edge over the competition. This serves as a primary motivation for alliance formation. A new trend of collaborative strategy in international business has gained popularity based on strategic
alliance through which leading firms, particularly in high-tech industries gain mutual benefit. Strategic alliances are partial merger, but have comprehensive impact on the performance of the firm. They involve mutual dependence and shared decision making between two or more separate firms. Strategic alliances differ from joint ventures as they encompass selected activities within time limits. Strategic goals pursued through strategic alliances are product exchange or supply alliances, learning alliances in research and development and market positioning alliances (Schoenmakers and ╯Duysters, 2006). There are some important types of alliance that can be set-up for optimizing the business. They are: • • • •
Technology based alliances Production based alliances Distribution based alliances Resource based alliances
One way for a firm to enter into a foreign market is to create a strategic alliance. A global strategic alliance is an agreement among two or more independent firms to cooperate for the purpose of achieving common goals such as a competitive advantage or customer value creation. Strategic partnerships may emerge in many forms including research and development consortium, co-production alliance, co-marketing partnerships, cross-licensing and cross-equity arrangements. Such alliances do not result in formation of a separate corporate entity but equity joint ventures form new strategic allies as legal entities to do specified business. The emergence of strategic alliances in Canada and other industrialized countries are related to economies of scale or scope, resource pooling, and risk and cost sharing among alliance partners. They include globalization of the world economy, systemic technological change, and the growing acceptance of the view that competition, by itself, does not necessarily ensure optimum, innovation-led growth. While international alliances provide firms with strategic flexibility, enabling
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Marketing Strategy, Technology and Modes of Entry in Global Retailing
them to respond to changing market conditions, they can also be effective paths for achieving global scale in enterprise operations along with mergers and acquisitions and green field investment. The driving forces behind international strategic alliances include cost economizing in production and research and development, strengthening market presence, and accessing intangible assets (NamHoon and Kentaro, 2005). In the recent trends of globalization, the practice of entering the international market through such alliances seems to be gearing up along with political support from developing countries. However, the companies having a larger share in the international market still reserve the right to entertain or not, any such alliances. Strategic alliances offer many advantages in business, of which some significant ones are as indicated below: •
• •
•
•
The organizational efficiency will be improved with the flexibility and informality in strategic alliances Alliances developed strategically offer access to new markets and technologies The risk and expenses are shared among the allies reducing the impact of risk on the participating members The alliance would help the partners build their independent brand and manage retailing of goods and services Alliances can take various forms, from simple research and development deals to heavy budget projects.
Strategic alliances are especially useful for seeking entry into emerging markets. Foreign firms in emerging markets seek to optimize the market performance in global economy and strategic alliances appear to be the obvious solution for mutual benefit. Given this pattern of benefit, the strategic alliances of US and European manufacturing firms account for over half of the market entries into Latin America and Asia.
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ING is one of the largest financial services companies among the prominent global firms, offering banking, insurance and asset management in over 50 countries. It has spread over its business to 60 million private, corporate and institutional clients in 60 countries with a workforce of over 115,000 people as in 2003. ING was founded in 1991 by a merger between Nationale-Nederlanden and NMB Postbank Group to become the first bancassurer of Netherlands. During the past 15 years ING has become multinational with very diverse international activities. The company holds insurance operations and asset-management activities in the Americas. It is well-established in the United States with retirement services, annuities and life insurances and has leading positions in non-life insurance in Canada and Mexico. Furthermore, the company is active in Chile, Brazil and Peru. The operating profits for the company in Americas have been increasing in €1310 million in 2003 to €1669 in 2004 before tax. In 2004, ING successfully repositioned itself in the wholesale banking market. The insurance business of the company in the Netherlands introduced a far-reaching plan to improve its customer service, with positive results so far. The business lines of the company further sharpened their focus on profitable top line growth, managing costs and risks and showing good bottom-line results. These four pillars are all equally important to generate above-average returns for shareholders. ING has diversified business activities in developing markets which offer a broad range of services in the fields of banking, insurance and asset management and has made its identity obvious in Asia/Pacific, Latin America and Central Europe amidst the competing local and multinational companies. In Latin America, ING is the largest insurer in Mexico and has important businesses in Chile and Brazil (Rajagopal, 2005). The convergence of business practices of the partnering firms often emerges as a major challenge to perform the alliance task as in interna-
Marketing Strategy, Technology and Modes of Entry in Global Retailing
tional business arena partnering firms belong to different socio-cultural environments. Alliance managers must make difficult decisions about when to partner and with whom, as well as how to structure and manage the partnership. Managers who can leverage information and knowledge across each stage of the alliance process will find that a knowledge-based approach is critical to the success of any partnership. In U.S.-Japanese alliances in the past, for example, Japanese companies saw these partnerships as a way to learn from their partner, while their U.S. counterparts used these alliances as a substitute for more competitive skills, ultimately resulting in an erosion of their own internal skills. Therefore, with companies that look on alliances as a way of learning from their partners, practices that enable knowledge sharing, creation, dissemination and internalization become critical (Parise Salvatore╯and╯Sasson, 2002). Cisco Systems and Polycom Inc. have a strategic agreement for joint development, licensing, and sales of Internet protocol (IP) telephony solutions. The objective of the alliance is to deliver enhanced IP telephones to enterprise customers; this agreement combines Polycom’s leadership in audio conferencing technologies and Cisco’s industry-leading expertise in IP networking and IP telephony. Based on this agreement, Polycom and Cisco have brought a Voice over IP (VoIP) conference phone to market that provides customers with industry-leading group conferencing capabilities within the Cisco IP Telephony environment4.
WHOLLY-OWNED SUBSIDIARIES The multi-national companies also plan to enter into a new international market establishing themselves in overseas markets by direct investment in a manufacturing or assembly subsidiary company. In view of the frequently changing economic, social and political conditions globally, these wholly-owned subsidiaries are highly risk averse. A wholly owned subsidiary in manufacturing can
involve investment in a new manufacturing or assembly plant or the acquisition of an existing plant (such as Coca-Cola Company purchases local bottling plants in developing countries). The presence of actual manufacturing operations helps support marketing activities. As manufacturing is established abroad through direct investment, parts and components are often exported from the home country. Besides manufacturing subsidiaries, establishing a sales subsidiary requires relatively low levels of capital investment which leads to low risk. HP Financial Services has emerged in 2002 as the parent company Hewlett Packard’s (HP) new leasing and financial services subsidiary. HP Financial Services (HPFS) is designed to enhance the worldwide sales efforts of the parent company by delivering a broad range of financial services and asset management capabilities that can positively impact the customer and partner relationships and shareowner value of the parent company . The HPFS represents approximately 4 percent of total revenue of parent company. This new subsidiary brings a centralized business model for the financial services offered to customers as part of a total HP solution5. Cadbury has played an excellent strategic move by acquiring Green & Black’s (G&B), organic food products, which has been leading with 90 percent market share in organic chocolates. In the global marketplace for organic products, the organic chocolate market in United Kingdom was worth £24 million in 2004 and growing on an average by a phenomenal 30% each year since 2002. With this acquisition G &B has enabled Cadbury to enter both the organic and premium chocolate markets, which are growing faster than chocolate confectionery overall, with a well-established brand that already enjoys significantly wider distribution than many other organic products. G & B is the fastest growing chocolate confectionery brand in the UK and will also benefit from Cadbury’s strong presence in impulse channels such as newsagents, where distribution of their products
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Marketing Strategy, Technology and Modes of Entry in Global Retailing
is still relatively weak. Nonetheless the company’s sales have more than quadrupled between 2001 and 2004 thanks to a combination of other factors, including good distribution across various channels from foodservice to supermarkets, the premium image of the brand and the company’s fair trade policies (Benkouider, 2005). The parent ventures, which are managed by wholly-owned subsidiaries, are more successful than shared management ventures, where both companies-parent and subsidiary-contribute on operational strategies. Problems often arise in shared situations because managers of international ventures have communication problems and different attitudes regarding time, job performance and the desirability of change (Killing, 1982). Firms become multinational companies by setting up manufacturing or marketing subsidiaries overseas and transferring knowledge, which embodies its advantage, from one country to another. That is, knowledge flows from headquarters to overseas subsidiaries. Venturing is serious business, requiring skill, patience, and entrepreneurial flair. Most new ventures involve entering unfamiliar markets, employing unfamiliar technology, and implementing an unfamiliar organizational structure. An approach of particular promise is the new-style joint venture, in which a small company with vigor, flexibility, and advanced technology joins forces with a large company with capital, marketing strength, and distribution channels (Rajagopal, 2006). In order to determine the fit between the parent company and its subsidiaries, corporate strategists should evaluate the operational areas which includes the critical success factors of the business, the parenting opportunities in the business, organizational attributes of the parent company, and the financial results (Campbell et al, 1995).
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DEVELOPING ENTRY PLAN An international marketing plan is prepared considering various factors that determine marketing functions across various countries. However, the marketing plan primarily needs to be designed considering the principal business components as stated below: • • • •
•
Commitment on decisions taken by the marketing firm Selection of country or cluster of countries (trade region) Mode of entry in the market Appropriate marketing strategy in tune to the marketing environment of the identified country or region. Building effective marketing organization
The selection of a country is a critical exercise that involves the examination of all the above variables besides undertaking the demand analysis and financial estimates. The commitment of the firm to its trading decisions in the selected country, cost-benefit ratio study, and market operational methods largely determine the mode of entry of the firm into the international marketing avenue. The marketing strategy needs to be evolved assessing the objectives of the firm in the local markets in order to acquire differential advantage. Once the marketing-mix is critically analyzed, an implementation strategy can be formulated by the marketing firm. However, to ensure effective implementation of marketing policies, the marketing organization needs to be strengthened first. The decentralized organizational structure at regional levels (like Central Asia, South-East Asia, Middle-East, Far-East, etc.) would be appropriate for a marketing firm when planning for international marketing in more than one country. Such an organizational set-up would facilitate monitoring of demand, supply, price trend and political interventions more comprehensively. The centralized set-up would be of greater cost
Marketing Strategy, Technology and Modes of Entry in Global Retailing
but less effective in exercising the marketing implementation and control measures. A two stage selection process is required for the firm in identifying the product, market and services for international marketing. In this process, first, potential international markets need to be explored. Secondly, comparison of the domestic market of the firm with those abroad needs to be carried out in order to ensure that marketing at the international level has cooperative advantages over the domestic market (Rajagopal, 2004). Identifying a marketing region is always better than restricting to an individual country for the purpose of cost effective distribution networking. In addition, the tariff walls at the border countries need to be studied carefully. The firm involved in the international marketing should also make efforts to develop export markets in the initial stage. This would help in product specialization. International business firms have found that exporting is cheaper than manufacturing in overseas markets. There still remain some basic issues to be examined by the firm engaged in international marketing. These are: • • • • • • • • • •
Size and growth Marketing potential of a country or region Similarities in host countries Free trade area, customs, common market Economic and political unions Appropriate economies of scale in managing business Accessibility, infrastructure and its cost Possibilities of decentralizing business activities Geographical boundaries of the markets Long run market segmentation
Exporting firms should understand that the export operations are subordinate to the domestic market policies and that the policy of the business firm to market the surplus home produce in the international market, would largely be determined by the opportunities offered by the host country
or regional markets. However, the considerations on —(i) the firm’s extent of awareness on varying requirements of consumers (ii) market response to the design and packaging of the product (iii) the impact of the pre-launch promotion among the focus groups and (iv) the size of the market which influences the adaptation process of goods and services at the international markets level. Roche is a pharmaceutical research, technology and market-driven company, whose unique portfolio of products and services creates superior value for the customers. The products of the company are delivered through its affiliates located all over the world. Affiliates or regional representations are direct link to the customers and local markets of the company. Roche Diagnostics integrates its own know-how with that of selected partners from a wide range of specialized areas. With this objective in mind, Roche Diagnostic’s strategic alliances and collaborative partnerships are aimed at combining potential with an innovative and ambitious approach. Best known examples of successful and long lasting partnerships are the global alliances with Hitachi (since 1978) for clinical chemistry and immunoassay systems, with Sysmex (since 1998) for hematology systems and with Stago (since 1973) in selected countries for coagulation systems. Roche Centralized Diagnostics (formerly Roche Laboratory Systems) directs its products and services at private labs, laboratory associations and central hospital laboratories, offering high-performance analysis systems to measure hundreds of different parameters in clinical specimens as well as programs to optimize lab processes, from sample down to result management. In cooperation with its partners Hitachi, Sysmex and Stago, Roche Centralized Diagnostics offers a full line of solutions for laboratories of all workloads. Roche Centralized Diagnostics’ ultimate goal is to improve patients’ health through the application of modern laboratory diagnostics as an integrated part of health management systems. In another alliance Roche-
15
Marketing Strategy, Technology and Modes of Entry in Global Retailing
Syntex Mexico is engaged in selling the diagnostic reagents and equipments to the government and private clinics. The company also provides the diagnostic equipments to these health institutions and hospitals on lease. The business environment of the diagnostic market in Mexico is highly competitive and distributor oriented. The laboratory diagnostics supplier base in Mexico is confined to the selected suppliers dominating 80% of the total market (Rajagopal, 2003). The firms preparing for international marketing should also keep track of the international subsidies provided to the developing countries. A strong political and economic information system would help the firms in preparing international marketing plans more effectively. The synthesis of these inputs for planning is essential in pursuing global strategies. Thus integration of this information with the border-country profiles is a pre-requisite for sound plans. The selection of a market place at international level is a critical process and is required to be filtered at many intermediate levels to select the core business country.
CONTROL MANAGEMENT A control feedback system is one of the core components of international marketing management and it serves to assess performance. Monitoring is one of the tools to measure the degree of the success of international marketing and needs to be incorporated in the plan itself. The marketing plans need to specify the periodicity of the control exercises and its prime objective. The monitoring calendar for international marketing firms may be designed keeping the following checks in mind: • • •
16
Budgetary control Plan implementation Performance of marketing functions (11Ps) which include product, price, place, promotion, packaging, pace, people, per-
• •
formance, psychodynamics, posture and proliferation Periodical appraisals of marketing information Social, cultural and political changes
The overall objective of these checks and controls is to determine the achievement of targeted results on time. These points need to be administered from the corporate office of the business firm in a centralized manner in order to enable effective planning and execution process. The standardization of marketing-mix is usually centralized to ensure the quality of all the components of the mix across the markets in the operational region. Besides, it is important to provide a common business language across markets which would help in understanding local markets more analytically. The checks need to be exercised at different levels of the marketing plan execution and to build-up a strong communication and information system. A consolidated document of the target group index (TGI) may be an appropriate tool for information processing and analysis. The variables which need to be covered in the TGI include consumer goods, industrial goods, services, spatial and temporal trend of demand and price, distribution patterns, marketing budgets, response to advertising, communication services and the like. International marketing research needs to be conducted on specific issues of interest and inferences may be tagged along with the Monitoring and Evaluation (M&E) process. Nevertheless, M&E should be conducted periodically as a tool of control.
EXIT POLICY It is essential that the firm entering into the international market needs to analyze the level of profitability, asset-production ratio, production costs, sales projections, and the risk factors in the short and long run. Further, it is very important that the firm should make all possible arrangements for
Marketing Strategy, Technology and Modes of Entry in Global Retailing
a smooth ejection from the international business in case of an unavoidable loss to property, brand or functional markets. The firm usually faces exit barriers after entry. A firm will be reluctant to commit on non-recoverable investments that have been made, people hired, contracts signed if there is likelihood of a forced exit. Another consideration for the marketer is the potential loss of goodwill accompanying withdrawal from an important and visible market. The French automaker Peugeot probably lost a great deal of brand equity and money in the U.S. market before finally exiting in 1992. The specific exit reasons for international firms to leave the operational stream are listed below: • • • • • • •
Shut down of specific operations Labor scarcity and high wage rates Market speculation and its impact Employees’ demand, labor problems and threats Changing government regulations International trade policies Total mismanagement
Hence, exiting strategy should also be carefully designed together with the approaches for entering the international market. Enough capital cushions are to be built or insured against risks in the world markets and against abrupt exits. In the era of global marketing, the company needs sufficient resources and capability to nurture and sustain its products and brands, thus surmounting exit barriers by never having to face them.
bearing on possessing the relative market share and growth of the business organization. The strategies are the directional statements and need to be converted into the step-by-step plan of action for effective plan implementation. The strategic directions have four options that can be expressed by 4As - arena, advantage, access and activities. The arena may be defined as serving the targeted market segment through an appropriate scale of operations and scope of activities to be performed for competitive advantage. The advantages in the process consist of positioning the products theme that differentiates the business from competitors. The access may be referred to the communication and distribution channels used to reach the market in the uncertain business conditions. These activities are interdependent and are affected by the change in any of the factors. The arena of the market largely dictates the customers to be served by the company, the competitors to by-passes and the key success factors to be considered upon. Each market has distinctive profile of key success factors developed by the attributes of the market. The recent development of corporate strategies shows that many multi-national companies are considering their choice of the market arena based on the following factors: •
•
There is an increasing trend of market fragmentation. New segments with specific needs are emerging and are being served by the specialist competitors by offering tailor made goods and services. The traditional market boundaries are disappearing as a consequence of the rush of substitutes emerging due to the technological growth. The transformation of existing self-contained regional and national markets into global markets.
MARKET UNCERTAINTIES AND ENTRY DECISIONS
•
In turbulent markets the competitive strategy provides the conceptual magnitude that integrates various functional activities and marketing programs for sustaining the competitive threats. The effective competitive strategies have a direct
In the above discussed situations the challenge for the corporate sector management may be observed as to find the right balance of global
17
Marketing Strategy, Technology and Modes of Entry in Global Retailing
reach and standardization of the activities versus the traditional strategies or local adaptation. The companies need to find out the competitive advantages within the chosen arena of business. The core issue associated with the competitive advantage is positioning of the theme that sets a business apart from the rivals in the way that is meaningful to target the customers. It is necessary for the companies to move aggressively against the competitors to retain their market territories and build a strong defense. Thus Kodak asserted itself in the film market against the strategies of Fuji in American market. The supply gluts also put pressure on advantages. The markets for the pharmaceuticals, electronics and automobiles suffer chronic global overcapacity to the extent of 15-40 percent. Such problem situation demands the companies to develop the strategies of competitive advantage to hold the key success factors and become the market leader. Such strategies are required as there are too many firms competing and the customers may back integrate by their marketing requirement rather than buying them. This situation reduces the volume of market demand relative to supply and the customers may sell their excess capacity on competition with their one-time supplier. The need for the competitively advantageous strategies may further be justified as a large number of firms are increasingly productive in reference to the rapid diffusion of the technologies. The customers’ bargaining power also works out to be an instrument to either broaden or narrow the differences between the competitors. The companies that use intermediaries are often encountered with balancing the power of distribution and delivery of services. In consumer markets the retail trade is forcing major concessions on the multi-national brands. Such strategies hold the access to the retail network through a long chain of channels. Conventionally the choice of appropriate scale in business and scope thereof were guided by the concepts of the bigger is better and umbrella control of activities. In the current era of globalization the decentralization of activities and
18
production sharing have become more effective tools in marketing. The profit centre approach (PCA), control circles and total quality management practices has endorsed the success of small integrated units operating in a well defined market. In view to promote the PCA concepts and maintain the control circles, the large companies are increasingly creating the autonomous, small and entrepreneurial units to find responsive solutions to the customer problems in the well defined market niches (Webster, 1989). Corporate structures are changing in order to accommodate the concept of PCA and control circles and are exploring for the long term advantages by way of heavy investment to develop the core competencies. BMW, Honda, and Toyota, among other companies, begin with a strong brand that imparts sales momentum to each model. Brands that are weak—because their products have acquired a reputation for shoddy workmanship, their designs are not evocative, or their models bear little relationship to one another—cannot pursue this top-down approach. But a company stands a good chance of selling more cars and, step by step, of rehabilitating the brand if managers take pains to match each model to the consumer segments most likely to be interested in it, identify and overcome the obstacles that keep browsers from becoming purchasers, and emphasize both the functional and the process and relationship benefits of the model in question. BMW Direct is an initiative of BMW (GB) to help selected company car fleet buyers streamline their service for employees. BMW Direct is a web based fully personalized, car configuration and ordering system for the purchase of new BMWs. This highly efficient rules based web application delivers a level of information previously unavailable outside of a showroom. The BMW Direct solution provides users with the ability to view details on all eligible cars online and then go on to configure them against a full menu of accessories. BMW Direct is truly ‘CRM’ compliant, providing two-way communication via
Marketing Strategy, Technology and Modes of Entry in Global Retailing
automated alerts and e-mails and incorporating a Contact Centre to ensure immediate access to trained product advisors. Users can track online the status of their individual orders whether by web, phone, fax or email. The call centre functionality includes phone and e-campaign generation, customer enquiry handling and profiling to customized promotions (Rajagopal, 2003a). Post-sales support is delivered using a thin client solution, (using Citrix) to BMWs contact centre in Croydon and order management centre in Bracknell in UK. The technological changes are the main impetus behind new market opportunities. The extent of such change may be explained from super technologies to the appropriate and intermediate technologies. The strategic choices have wide ranging ripple effects through the organization that determine the key success factors and growth performance. Some companies would be making right strategic choices by improving the implementation process of competitive advantages. These companies are guided by the shared strategic vision and are driven by the responsive attitude towards the market requirements. They emphasize the continuous strive to satisfy the customers. A strategic vision in managing markets may be understood as the guiding theme that explains the nature of business and the future projections thereof. These projections or business intentions depend on the collective analysis of the environment that determines the need for the new developments or diversifications. The vision should be commissioned on a concrete understanding of the business and the ability to foresee the impact of market forces on the growth of business. The vision will motivate the organization for collaborative business planning and implementation. The powerful visions are also the statements of intent that create on obsession with winning thorough out the organization (Day, 1990). The business strategy broadly incorporates the following dimensions:
• • • •
Customer needs Consumer segments Technology and resources Activities in the value added chain
The strategic thrust has a significant magnitude and direction in sailing the business though the turbulent situation. The factors associated with the competitive advantage and business investments uphold the strategic thrust to achieve the business objectives though the positive channel efforts. The competitive advantage may be assessed in reference to the superior customer value and lowest delivered cost. Such combination of the strategies may be termed as competitive superiority that explains cost effective delivery strategy to enhance the customer value. An overall edge is gained by performing most of the activities at a lower cost than competitors. This would enable the company to optimize its cost of delivery of the new products and simultaneously enhance the value of customer value to up-hold the strategic thrust of the company. Canon delivers innovative digital business solutions to ensure that its customers achieve and maintain the information edge. The increasingly competitive global marketplace, and the fact that the organizations must store, process and share immense volumes of information with both speed and accuracy have been the key areas of the company to penetrate in the territorial gateways like Mexico for Latin American market. The company functions with four key areas in Mexican market that include marketing, logistics, sales and services operations. The marketing activities of the company consist of planning and budgeting, pricing, forecasting, purchases, marketing research and developing promotional strategies. The company is also engaged in developing attractive media –mix and advertising campaigns and launches the loyalty programs for its major brands. The virtual shopping network is also a
19
Marketing Strategy, Technology and Modes of Entry in Global Retailing
major part of the marketing functions performed by the company in the country. The company feels that the loyal, ongoing customers are the backbone of every business and in the prevailing highly competitive environment, these shoppers cannot be ignored or else they may be won over by competitors. The consumers might have bought such products many times in their life or some might have purchased at least once in life time. There is no single way to segment a market. The most important factors influencing a consumer’s involvement level are their perceived risks. The purchase of any product involves a certain amount of risk, which may include product failure, financial, operational, social, personal and psychological. The repeat customers are more apt to buy a full range of merchandise, not merely items that are under promotional programs. This means that the dealers and retailers of the company can reach profit margin goals. The logistics functions of the company is largely international trade oriented as the Canon Mexico is a part of Canon USA and many products of the company are acquired from its USA counterpart as inbound logistics. The import process has been one of the major activities of the company in Mexico. The logistics of the company further involves the key activities of transport, inventory management and developing appropriate overseas trade and information strategies (Rajagopal, 2003b). There are major types of strategies catalogued and given various names by different authors. Often these strategies and tactics are so bold and innovative that they “change the rules of the game.” Leaders are increasingly being advised to seek that objective in planning and executing their strategies. The pace of change today is dizzying with new technological breakthroughs occurring at shorter intervals and global competition putting the heat on. Mergers and acquisitions change the competitive landscape unexpectedly, and strategic alliances develop even among the companies that
20
were, or still are, competitors. The concept of “Hyper-competition explains the highly aggressive form of competition that characterizes hi-tech industries today. Hyper-competition is said to be increasingly making its way into other industries as well. They speak in terms of surprise, speed and mobility, terms suggestive of the military approach. Not that aggressive action is new in business so much so as the level, intent and severity of business “combat” have changed dramatically. It is necessary to build the strategic business mindset to outwit the competitors and gain competitive advantages over the segmented markets. The following factors need to be considered for achieving the strategic business leadership: •
•
•
• • •
• •
• •
A clear sense of desired outcomes before acting. Develop a plan capable of delivering outcomes that will add significant value to a state of affairs. Explore possibilities outwards to capture the larger context, to see how the pieces fit together. Adaptive to realities and flexible in choice of tactics. Recognize that once action begins the “game board” is fluid offering both new threats and new opportunities.╯ Wherever possible, attempt to achieve multiple objectives through singular actions. Plan a couple of steps ahead of competition. Anticipate the actions of business rival and strategically rehearse next responses should those contingencies arise. Core discipline to observe the market moves and rival reactions. Capitalize on business crises or behavioural change in the markets in order to turn them to advantage. Stay future-focused. Plan the business strategy implementation in both sequential and parallel direction to accomplish goals and sustain the impact thereof.
Marketing Strategy, Technology and Modes of Entry in Global Retailing
•
• • •
• • • • • •
• •
•
Develop negotiations with the business intermediaries on win-win platform at an acceptable cost. Supplement actions with those of others (allies, partners, joint ventures.)╯ Be patient, with a good sense of timing. Be able to scrap or alter plans when information indicates actions are not attaining their intended results. Develop alternate strategies for contingencies Use speed and surprise to gain advantage. Form alliances with opponents of his opponents in business. Learn the strengths and weaknesses of rivals. Be aggressive in pursuing goals, cordon the moves and ready to take on to the next. Assure that everyone in the company knows one’s role and is equipped with the resources to contribute. Monitor activities in the operating environment. Use “what if” speculation to stretch thinking in the direction of opportunities and possibilities. Study the logic of the opponent’s tactics with an eye toward determining what their ultimate end purposes may be.
These are some tested aspects of thinking employed by leaders to gain and hold strategic advantage. They can serve as a checklist when responsibilities include thinking strategically. Customers want more of everything they value. If they value low cost they want it lower. If they value convenience they want it easier and faster. If they look for state of the art they want it first and want to push the envelope. If they need expert advice they want more time and dedicated effort and investment. By raising the level of value that customers can expect from everyone, leading companies are driving the market and driving their competitors out of business, or at least into
a malaise of mediocrity. Here are a few options for managerial consideration: •
•
• •
•
•
•
•
•
Alter the industry structure to change the basis of competition. Reconfigure the value chain - retailers become wholesalers and suppliers, insurers takeover brokerages, banks move into insurance, etc. Improve the position of the business within the industry by way of acquisitions and market share. Alter the playing field to achieve an enhanced scale of operations and competitive positioning.╯ Innovate and create new opportunities new products, services, and markets. Employ barriers to entry in terms of significant capital investment, proprietary technology, or in the magnitude of resources required to compete effectively. Increase the dependence of customers for products and services in terms of the total value for customers or higher costs of switching to alternates. Change and enhance supplier relationships to obtain cost and quality improvements, reduced cycle times, and integrated processes. Change the basis of competition by creating a service relationship and differentiation. Move away from price to service, software, and customer relationships.╯ Centralize into high volume, low cost, automated, ‘focused factories’, to achieve the lowest cost operations in support of customer value. Decentralize into custom, low volume, flexible factories, quick to market, responsive, and able to customize products to specific customer requirements.
Controls may be considered as checkpoints used to verify performance progress by comparison with some standard in a given competitive environment. Generally the business standards
21
Marketing Strategy, Technology and Modes of Entry in Global Retailing
are established by top management in the planning process. The control and analysis process need to be revised with the growing size of the firm and its business operations. Controls must go along with the expansion process and tight control should ensure consistency in product and marketing performance. Since multinational companies typically have several foreign subsidiaries in different parts of the world, a good control system is important to ensure that these subsidiaries move together toward a common goal, spelled out by the corporate strategic plan to meet any market uncertainties. These issues need to be considered in anticipation by the international firms while deciding the entry strategies in foreign markets.
DRIVERS OF GLOBALIZATION There are over 200 countries in the world and it is difficult for the marketer to determine a critical path of success across the countries or regions. Exceptionally, couple of companies like Fuji, Kodak and Coca-cola that have spread their business in over 100 countries developed gradually. The characteristics of the global market place are diverse and international marketing approaches are different. The companies need to adapt a strong rationale for grouping the countries into segments. The multinational and the global corporation are different as the former operates in a number of countries and carries adjustment in the production and marketing practices in each country at a highly relative costs (Levitt, 1998). The global corporation operates with the stanch loyalty at relatively low costs with standardization. Coca-cola and Pepsi-Cola companies have standardized their products globally according to the regional and ethnic preferences of consumers. The most effective world competitors integrate quality and trust attributes into their cost structure. Such companies compete on the basis of appropriate value of price, quality, trust and delivery systems. These values are considered by
22
the companies in reference to the product design, function and changing consumer preferences like fashion. The multi-national corporations know a lot about the business environment in a country, put their efforts on adapting to the given environment and sets gradual penetration process in the country. On the contrary, the global corporations recognize the absolute need to be competitive and drive through the lower prices by standardizing its marketing operations. The global corporations treat the world as composed of a few networked and standardized markets than many independent and customized markets. There are five major categories of drivers that propel companies towards globalization. These drivers include market, competition, cost, technology and government. Of these, the market driver has been considered as one of the strongest forces that push the process of global marketing. The major driver of change for General Motors today is the same as for most companies; it’s globalization. Advances in technology and communication are making the ‘small world’ a reality, and the world will only get smaller and smaller in coming years…This trend towards global integration should be- viewed as an opportunity—not a problem. -John F. Smith, Jr., CEO of General Motors The market drivers comprise the needs of common customers, global customers, global channels and transferable marketing. The common customers needs become a compelling factor for the multinational companies when customers of the different countries have the same needs in a product category. The free trade and unrestricted travel has created homogenous groups of customers across the countries in reference to specific industries. However, some markets that typically deal with the culture bound products like food and beverages, apparel and entertainment strongly resist the shift towards globalization and remain multi-domestic serving to the different customer
Marketing Strategy, Technology and Modes of Entry in Global Retailing
preferences and differentiated products across the countries. On the contrary the global customers need the same products or services in many countries like the case of Kodak films or Hilton Hotels. The global channels, distribution and logistics companies offer seamless transport, storage and delivery services. The companies can expand internationally provided the channel infrastructure is met with the distribution needs of the company. Hence their integrated networks thrive to bring the multinational companies close to the global distributors, retail stores like super markets and departmental stores in order to generate systems effect. Transferable marketing is applied to the same marketing ideas on brand names, packaging, advertising and other components of marketingmix in the different countries. Nike’s campaign anchoring the basketball champion Michael Jordan pulled-up the brand in many countries. This is how the good ideas of multinationals get leveraged world over. The competitive drivers support the companies for matching their strategies appropriately with their moves in the market. The existence of many global competitors indicates that an industry is mature for international business operations. The global competitors operate on cost advantages over the local competitors. The emergence of strong global competitors has served to develop the market infrastructure for the local companies and also help in transfer of technological skills enabling the domestic company to explore the scope of expansion. The competitive efforts put pressure on companies to globalize their marketing activities to derive optimum performance by interpreting appropriately the competitor signals. When Kodak backed out from sponsoring the 1984 Los Angeles Olympics, the Fuji Film entered into the sponsorship issue immediately at the prescribed price and was one of the official sponsors of the Olympics. By the time Kodak reconsidered to participate in this international event, the time overran. However, for the Olympics of 1988 and
ABC-TV Kodak become sport program sponsor (Finnerty, 2000). The cost drivers are largely based on the scale of economies that involve the cost of production functions in large and complex industries, cost of outsourcing, diffusion and adaptation of technology, tariffs and taxes and costs associated with the basic and advanced marketing functions. The macro economic factors of the neighboring countries also govern the cost drivers. When a new automobile plant is set-up, it aims at designing, manufacturing or assembling and delivering a particular model by penetrating into the neighboring markets to gain the advantages of economies of scale. The automobile plant of Toyota at Kentucky manufacture the Camry model for catering to the markets of NAFTA group of countries. The high market share multi-domestic companies derive gains from spreading their production activities across multiple product lines or diversified business lines to achieve advantage through the scope of economies. The manufacturing and marketing activities of Proctor and Gamble, Unilever, Colgate-Palmolive may illustrate this global attribute that is explained by the cost drivers. The other cost drivers include global sourcing advantages, low global communications and automation processes. The location of strategic resources to the production plants, cost differences across the countries and transport costs are also some important considerations of the cost drivers. The lowering of trade barriers made globalization of markets and production a theoretical possibility, and technological change has made it a tangible reality. Since the end of World War II, the world has seen major advances in communications, information processing, and transportation technology including, most recently, the explosive emergence of the Internet and World Wide Web. The technology drivers play a significant role in global business. Global expansion of the multinational companies has been highly stimulated by the technological advancements in the designing,
23
Marketing Strategy, Technology and Modes of Entry in Global Retailing
manufacturing and marketing of consumer and industrial products. The services were also improved by many technological breakthroughs. The internet revolution has triggered the e-commerce as open access channel with a strong driving force for the global business in the consumer and industry segments. Improved transport and communication now makes it possible to be in continuous contact with producers anywhere in the world. This makes it easier for companies to split production of a single good over any distance. Storage and preservation techniques have revolutionized the food industry for example, so that the idea of seasonal vegetables is no longer relevant today as anything can be exported all year round from anywhere. In addition, the IT revolution has made the movement of investment capital around the globe an almost immediate process ensuring that financing opportunities across the developed and developing world have both expanded and become more flexible. However, non-economic drivers of global integration, from travel to telephone traffic maintained their forward momentum, making the world more integrated at the end of 2002 than ever before. Technological upgrading, in the form of introduction of new machinery and improvement of technological capabilities, provides a firm with the means to be successful in competition. In the process of introducing better technologies, new lower-cost methods become available, which allow the firm to increase labor productivity, i.e., the efficiency with which it converts resources into value. Firms will adopt these newer methods of production if they are more profitable than the older ones. The ability of a firm to take advantage of technical progress is also enhanced if the firm improves its entrepreneurial and technological capabilities through two competitiveness strategies, namely (i)╯learning and adaptation, and (ii)╯innovation. The latter is a process of searching for, finding, developing, imitating, adapting, and adopting new products, new processes, and new organizational arrangements. Because rivals
24
do not stand still, the firm’s capacity to develop these capabilities, as well as its ability to compete, depends on the firm’s maintaining a steady pace of innovation (Asian Development Bank, 2003). Containerization has revolutionized the transportation business, significantly lowering the costs of shipping goods over long distances. Before the advent of containerization, moving goods from one mode of transport to another was very labor intensive, lengthy, and costly. It could take days to unload a ship and reload goods onto trucks and trains. The efficiency gains associated with containerization, transportation costs have plummeted, making it much more economical to ship goods around the world, thereby helping to drive the globalization of markets and production. The government drivers for the globalization include diplomatic trade relations, customs unions or common markets. The government drivers add favorable trade policies, foreign investment regulations, bilateral or regional trade treaties and common market regulations. The introduction of global standard norms like ISO certifications by the respective countries may be one of the effective measures to promote the globalization through uniform quality perspectives. In the past the government barriers to foreign market entry protected the domestic markets and made the global marketing an uphill task. WTO has been instrumental in promoting government drivers for improving trade in the developing countries. At the Fourth World Trade Organization Ministerial Meeting held in Doha in November 2001, Ministers launched a comprehensive set of multilateral trade negotiations and a work program. This mandate is sometimes referred to as the Doha Development Agenda, reflecting a shared desire to ensure that the trading system is relevant and responsive to the needs of developing countries. Among the areas covered by the negotiations or the work program are market access in manufactures, agriculture and services, certain rules (including anti-dumping, subsidies and countervailing mea-
Marketing Strategy, Technology and Modes of Entry in Global Retailing
sures, and regional arrangements), trade and environment, trade-related intellectual property rights, the relationship between trade and investment, the interaction between trade and competition policy, transparency in government procurement, trade facilitation, and dispute settlement. Developing countries were particularly instrumental in putting certain issues on the agenda, including trade and technology transfer, trade, debt and finance, small economies, implementation issues (mostly pending from the Uruguay Round) and special and differential treatment. Between 1990 and 2001, South-South trade grew faster than world trade with the share of intra-developing country trade in world merchandise exports rising from 6.5 per cent to 10.6 per cent. Over this period, developing country economies grew much faster than those of the developed and transition countries. The liberalization of the trade and investment regimes of a large number of these countries has played a significant role in this expansion. Much of this expansion in South-South trade took place in developing Asia (which accounts for more than two-thirds of intra-developing country trade). Manufactures, in particular office and telecom equipment, played a leading role in the growth of intra-developing country trade. This strong performance can be attributed in part to open trade and investment policies in the major developing economies of Asia. Trade liberalization in Asia took various forms in the 1990s: some of it was undertaken on a unilateral basis, some arose from multilateral efforts (World Trade Organization, 2003). Integrating a worldwide strategy involves five key dimensions: selecting markets for their global strategic importance; standardizing products; locating value-adding activities in a global network; using uniform marketing techniques; and integrating competitive moves across countries. Industry globalization drivers that are defined as the industry conditions that determine industry globalization potential and organization and management
factors largely determine the use of global strategy. Such drivers have the strongest influence in global trade. The application of global strategy in industries with high globalization potential improves business performance. The global companies constantly search for opportunities to achieve the benefits of globalization; take a zero-based view of existing activities; flout conventional wisdom and established practices; systematically analyze industry, strategy, and organizational linkages; and make multiple reinforcing changes in strategy and organization. They assume that strategy should be global unless proven otherwise, and they think globally and act locally. Besides, the five drivers discussed above, there exists other reasons to market products and services globally. The major factors that influence the drivers of globalization may be illustrated as under: • • • • • • •
Market Saturation Trade Deficit Foreign Competition Emergence of New Markets Globalization of Markets Opportunities via Foreign Aid Programs Other Reasons
The most evident reason to drive the companies go global is the market potential in the developing countries that constitute as major players in the world market. The companies such as Nintendo, Disney and the Japanese Motorcycle industries (Honda, Kawasaki, Suzuki etc.) have been greatly benefited from exploiting the markets of the developing countries and reassuring their growth in the world market to harness the promising market potential. The emerging scope of spatial diversification has also been one of the drivers for enhancing the global business utilizing the additional production capacity at the economies of scale and low-cost outsourcing. The production sharing of Volvo industries in India (Bangalore) where the company manufacture engines for its
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heavy transport vehicles may be cited as one of the examples. The thrust of Japanese motorcycle industry in the US markets is aided significantly by its low-cost position. The saturation of the demand for the products and services of a company in domestic market may also be an effective driver to globalization wherein the company looks for building the value for its brand across the boundaries. When a product that is near to the end of its life cycle in the domestic market while beginning to generate growth abroad. Dickson Poon’s export of high brand value luxury goods from America to the Far-east may be cited as an example of gaining advantage of general rise in the conspicuous consumption that is regarded as a sign of prosperity. Sometimes the cross-culture attributes of overseas markets that become the source of new product ideation, also may be considered as one of the potential drivers for globalization of business and explore the strategic alliances with prominent regional or multinational brands thereof. The tested market entry approaches may be implemented in the emerging markets such as South-east Asia as shown by the Revlon in cosmetics though risk of international currency prevails, legal issues and business protocols. However the most difficult task for the global companies to develop products with a universal appeal as illustrated by Gillette with its fragrances. On the contrary Lego is facing hardship in the Far-east markets to popularize its concept of do it yourself (DIY) for creative learning against the head-on competition of video games industries attracting the same segment of buyers (age group 5- 14).
REFERENCES Arnold, D. (2003). The Mirage of Global Marketing: How Globalizing Companies can Succeed as Markets Localize. Financial Times Prentice Hall, Upper Saddle River, NJ, (pp. 24-65).
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Asian Development Bank (2003). Drivers of change: Globalization, technology and competition. section III, competitiveness in developing Asia, Asian development Outlook. Benkouider, C. (2005). Going Organic: Cadbury Acquires Green and Black’s. Euromonitor, 20 May (Online edition). Campbell, A., Goold, M., & Alexander, M. (1995). Corporate Strategy-The Quest for Parenting Advantage. Harvard Business Review, 73(2), 120–132. Day, G. S. (1990). Market Driven Strategy: Process for Creating Value. New York: The Free Press, (pp. 10-18). Euromonitor (2006). Breakfast Cereals Boom in Bulgaria. Euromonitor online. January. Finnerty, T. C. (2000). Kodak Vs. Fuji – The Battle for Global Market Share, Institute of Global Business Strategy. Lubin School of Business, Pace University, New York, (pp. 1-23). Fung, V., & Magretta, V. (1998). Fast Global and Entrepreneurial: Supply Chain ManagementHong Kong Style. Harvard Business Review, 76(5), 103–114. Hofmann, O. (2006). Anti-ageing Skin Cream Booms in Hong Kong. Euromonitor, May (online edition). Hustom, L., & Sakkab, N. (2006). Connect and Develop: Inside Proctor and Gamble’s New Model for Innovation. Harvard Business Review, 84(3), 58–66. Killing, P. J. (1982). How to make a Global Joint Venture Work. Harvard Business Review, 60(3), 120–127. Levitt, T. (1998). The globalization of markets. In M. W. Taylor & G. L. John (Ed.), International and Global Marketing-Concept and Cases. Irwin McGraw Hill, Boston, (pp. 13-23, 1998).
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Nam-Hoon, K., & Kentaro, S. (2005). International Strategic Alliances: Their Role in Industrial Globalization. OECD, STI Working Paper # 2000/5. Parise, S., & Sasson, L. (2002). Leveraging Knowledge Management across Strategic Alliances. IBM Institute for Business Value Study, Cambridge, Massachusetts. USA. Piercy, N. (1981). Company Internationalization: Active and Reactive Exporting. European Journal of Marketing, 15(3), 26–40. doi:10.1108/ EUM0000000004876 Proctor & Gamble. (2005). P & G Launches Loading Program in Selected US Markets. Corporate web site, News, November 14, 2005. Rajagopal (2003). Sales Force Re-organization for Maintaining Profitable Growth: A Case of Roche Diagnostics Mexico (A), Discussion case, ITESM, Mexico City Campus, (pp. 1-19). Rajagopal (2003a). Building Customer Loyalty through Relationship Networking: A Case of BMW Mexico. Discussion Case, ITESM, Mexico City Campus, (pp. 1-16). Rajagopal (2003b). Striving with Competition in Global Imaging Market: Canon in Mexican Business Environment ITESM, Mexico City Campus, (pp. 1-22). Rajagopal (2004). Conceptual Analysis of Brand Architecture and Relationships within Product Category. Journal of Brand Management, 11(3), 233-247. Rajagopal (2005). Virtual Sales Offices for Insurance Services in Mexico: A Case of ING Comercial America, Discussion Case, ITESM, Mexico, (pp. 1-21).
Schoenmakers, W., & Duysters, G. (2006). Learning in Strategic Technological Alliances. Technology Analysis and Strategic Management, 18(2), 245–264. doi:10.1080/09537320600624162 Tsukioka, A. (2006). Joint venture agreement on food and beverages. Japan Corporate News Network, Feb. 27, 2006. Webster, F. E., Jr. (1989). It’s 1990- Do you know where your marketing is? Mass Marketing Science Institute, Cambridge MA. World Trade Organization. (2003). World Trade Report, Executive Summary, WTO, Geneva, (pp. 14-15).
ENDNOTES 1
2
3
4
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Corporate website, Li & Fung http://www. lifung.com For details on the case study please see Case Study:Papa John’s, New Business.Com http://www.newbusiness.co.uk/cgi-bin/ showArticle.pl?id=3562 Ranbaxy Laboratorios Ltd.: Ranbaxy Consolidates Relationship with Japan JV Partner Nippon Chemiphar, Rainbaxy Press Release, November 11, 2005 http://www.ranbaxy. com/newsroom For details see Polycom Corporate Website: Information on strategic ally partners, http:// www.polycom.com Hewlett Packard Development Company: HP Financial Services as Wholly Owned Subsidiary, News Release, Corporate Office, Aug 13, 2002 http://www.hp.com/hpinfo/ newsroom/press/2002/020813a.html
Rajagopal (2006). Innovation and Business Growth through Corporate Venturing in Latin America: Analysis of Strategic Fit. Management Decision, 44(5), 703-718. This work was previously published in Information Communication Technologies and Globalization of Retailing Applications, edited by Dr. Rajagopal, pp. 278-315, copyright 2009 by Information Science Reference (an imprint of IGI Global). 27
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Chapter 1.2
The Business Value of E-Collaboration: A Conceptual Framework Lior Fink Ben-Gurion University of the Negev, Israel
INTRODUCTION This article presents a conceptual framework of the business value of e-collaboration. In the past decade, firms have increasingly implemented collaborative technologies to support business activities, and investments in collaborative technologies have taken an increasing share of firms’ e-business investments. Presumably, such investments have been motivated by the notion that the implementation of collaborative technologies has business value. While research has repeatedly demonstrated the individual- and group-level DOI: 10.4018/978-1-60960-587-2.ch102
impacts of collaborative technologies, it has rarely addressed their impacts at the organizational level and demonstrated their business value. In this article, I draw on three strategic management frameworks – the resource-based view of the firm, the knowledge-based view of the firm, and the dynamic capabilities perspective – to describe how specialized knowledge assets can be integrated through collaborative processes to create and sustain a competitive advantage. I then use this conceptualization as a platform for defining the organizational roles of collaborative technologies and the potential impact of each role on organizational performance. The main objective of this article is to provide a conceptual framework for
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The Business Value of E-Collaboration
researchers and practitioners who are interested in investigating and understanding the organizational impacts of collaborative technologies.
BACKGROUND Resource- and KnowledgeBased Views of the Firm The resource-based view of the firm (Barney, 1991) argues that heterogeneity and immobility of firm resources can provide a basis for superior competitive performance. Firm resources that are strategically valuable and heterogeneously distributed enable firms to outperform the competition. However, such a competitive advantage cannot be sustained if competitors can acquire strategically equivalent resources to implement the same valuable strategy. Therefore, for a firm to sustain its competitive advantage, its valuable and rare resources should not be open to imitation or substitution. The knowledge-based view of the firm (Grant, 1996; Kogut & Zander, 1996; Nonaka, 1991) extends the resource-based view by defining organizational knowledge as a valuable subset of firm resources. The knowledge-based view perceives a firm as a knowledge-creating entity; it argues that the capability to create and utilize knowledge is the most valuable source of the firm’s sustainable competitive advantage (Nonaka, Toyama, & Nagata, 2000). Specialized, firm-specific knowledge resources are those that are valuable, scarce, and difficult to imitate, transfer, or substitute. By using such resources, a firm could gain an advantage in its markets that competitors would find difficult to overcome. Applying Grant’s (1996) view of coordination mechanisms, e-collaboration is conceptualized here as a group coordination mechanism. Kock, Davison, Wazlawick, and Ocker (2001) define e-collaboration as “collaboration among individuals engaged in a common task using electronic
technologies” (p. 1). This definition encompasses different types of systems, ranging from computermediated communication (CMC), through group decision support systems (GDSS), to Web-based collaboration tools (Kock & Nosek, 2005). Nonetheless, researchers agree that e-collaboration tools are vehicles for information and knowledge sharing that transcends traditional limitations of time and space. Therefore, compared with traditional coordination mechanisms, e-collaboration is a group coordination mechanism with wider capabilities because it enables and facilitates the work of virtual groups, giving firms extra degrees of freedom in establishing and managing knowledge-sharing mechanisms.
Dynamic Capabilities Perspective The dynamic capabilities perspective (Teece, Pisano, & Shuen, 1997) is an extension of the resource-based view to dynamic markets. It has evolved to account for the deficiencies of the resource-based view in explaining how firm resources are developed and renewed in response to shifts in the business environment. The resourcebased view identifies a subset of resources as a potential source of competitive advantage. However, this is a static view of the relationship between firm resources and competitive advantage. When change occurs in the business environment, firm resources should evolve to enable new and innovative forms of competitive advantage. By adopting a process approach, the dynamic capabilities perspective argues that dynamic capabilities are the process mechanisms responsible for the continuous development of resources in the face of rapidly evolving strategic needs. By viewing specialized, firm-specific knowledge resources as a strategic asset and ecollaboration processes as a dynamic capability, I propose that e-collaboration is a potential source of competitive advantage, because of its ability to foster organizational change and innovation. In rapidly changing business environments,
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knowledge assets that have enabled superior competitiveness can quickly lose their strategic relevance, calling for the fast identification and utilization of novel, possibly tacit and distributed knowledge bases to maintain a favorable market position. In these situations, e-collaboration can provide a unique mechanism for the persistent identification, organization, integration, and utilization of knowledge assets. By creating webs of collaborations among various business segments, firms are able to generate new and synergistic resource combinations (Eisenhardt & Galunic, 2000). The dynamic capability of e-collaboration enables the frequent introduction of organizational innovations, which, in turn, can provide a source of sustained competitive advantage.
ORGANIZATIONAL ROLES OF E-COLLABORATION Teece et al. (1997) describe organizational processes as having three roles: coordination/ integration (a static concept), learning (a dynamic concept), and reconfiguration (a transformational concept). Building upon this framework, I describe coordination, learning, and innovation as the three organizational roles of e-collaboration.
COORDINATION The primary functional role of e-collaboration is to facilitate coordination among individuals, groups, and organizations. Malone and Crowston (1994), who define coordination as “managing dependencies between activities” (p. 90), describe communication and group decision making as two processes that are important in almost all instances of coordination. Collaborative technologies are typically designed to facilitate communication and decision making and therefore enable firms to manage dependencies between activities more efficiently and effectively, whether those dependencies are intra- or inter-organizational. The
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ability of collaborative technologies to enhance coordination among organizations is frequently discussed in the context of interorganizational systems (e.g., Chi & Holsapple, 2005). Bafoutsou and Mentzas (2002) demonstrate that all categories of electronic tools for communication and collaboration address some of the coordination problems created by recent organizational trends, such as decentralization and outsourcing.
Learning E-collaboration may serve as a mechanism for facilitating learning by boosting knowledge creation and sharing processes. Kogut and Zander (1996) view firms as organizations that represent social knowledge of coordination and learning. Collaborative technologies can enable individuals to arrive at new insights by providing an extended field for interaction among members of an organization (Alavi & Leidner, 2001). The use of collaborative technologies improves the three aspects of knowledge management – knowledge creation, knowledge discovery, and knowledge transfer (Paul, 2006). Leidner, Alavi, and Kayworth (2006) describe two fundamental approaches to knowledge management: the process approach and the practice approach. The process approach attempts to codify organizational knowledge through formalized processes. In contrast, the practice approach attempts to build social environments necessary to facilitate the sharing of tacit knowledge. According to Leidner et al., both approaches involve the use of collaborative technologies – either to enhance the quality and speed of knowledge creation and distribution or to facilitate conversations and transfer of tacit knowledge.
Innovation Knowledge can provide a firm with a competitive advantage, because it is through this knowledge that the firm is able to introduce innovation in
The Business Value of E-Collaboration
processes, products, and services (Nonaka et al., 2000). Nonaka (1991) describes the “knowledgecreating company” as a company “whose sole business is continuous innovation” (p. 96). Collaborative technologies play a significant role in creating business innovation (Eden & Ackermann, 2001). Wheeler (2002) proposes the net-enabled business innovation cycle (NEBIC) as an applied dynamic capabilities theory for understanding how pervasive digital networks can enable growth through business innovation. The role of collaboration in fostering business innovation is also demonstrated in absorptive capacity research. Cohen and Levinthal (1990) show that a firm’s absorptive capacity – its ability to recognize, assimilate, and apply new information based on prior related knowledge – is critical to its innovative capabilities. E-collaboration as a platform for interaction and learning creates opportunities for integrating new external knowledge into existing knowledge assets. Figure 1 graphically presents the process through which e-collaboration creates a competitive advantage.
ORGANIZATIONAL PERFORMANCE IMPACTS OF E-COLLABORATION In a comprehensive review of the literature on IT and organizational performance, Melville, Kraemer, and Gurbaxani (2004) highlight the
existence of two formulations of performance, efficiency and effectiveness. The former, designated efficiency impacts, adopts an internal process perspective using such metrics as cost reduction and productivity enhancement. The latter, designated competitive impacts, focuses on the attainment of organizational objectives in relation to the external environment. I propose that e-collaboration roles are associated with both efficiency and competitive impacts. However, the particular roles differ in their impacts on organizational performance – coordination leads primarily to efficiency impacts, whereas learning and innovation are more strongly associated with competitive impacts. One of the most fundamental performance impacts attributed to IT is the reduction of coordination costs. Efficiency impacts also result from better coordination with the external business environment. Collaborative supply chain management (SCM) systems, which strengthen coordination among partners in a supply chain, offer inventory, process, and product cost reductions, while lowering the total cost of system ownership (McLaren, Head, & Yuan, 2002). Coordination-based efficiency impacts are apparent at the organizational and interorganizational levels, but also at lower levels. Huang and Newell (2003) empirically demonstrate that the level of coordination positively affects integration efficiency in the context of cross-functional project teams. In conclusion,
Figure 1. How e-collaboration creates a competitive advantage
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implementing collaborative technologies for the purpose of enhancing coordination, at different organizational levels, can deliver a wide range of organizational efficiency impacts. Conversely, organizational learning has the potential to generate both efficiency and competitive impacts, depending on its objectives and level. Electronic links enhance lower and higher levels of learning (Scott, 2000). At the lower level, collaborative technologies are used to integrate explicit knowledge for the purpose of reducing process and product costs, shortening cycle times, improving productivity, enhancing quality, and streamlining business processes. At the higher level, collaborative technologies are used to facilitate strategic planning, strengthening the ability of firms to identify opportunities and threats in the business environment, to understand their strengths and weaknesses, to formulate an organizational vision, and to develop creative solutions to organizational problems. By identifying, integrating, and utilizing organizational sources of tacit knowledge, a firm can outperform the competition and gain a competitive advantage. However, at the higher level, the competitive impacts of learning are not direct but rather mediated through innovation. There is a causal relationship between organizational learning capabilities, process and product innovation, and competitive advantage (Adams & Lamont, 2003). While collaborative technologies may be viewed as commodity resources that are susceptible to imitation, a firm’s ability to exploit their potential in facilitating its learning and innovation capabilities is critical in gaining IT-based competitiveness. The strategic importance of learning comes from implying path-dependency and specificity in organizational transformations preventing imitability, which is crucial for competitive advantage (Andreu & Ciborra, 1996). In recent years, it seems that continuous business innovation has repeatedly been identified, more than any other organizational capability, as a potential source of competitive advantage in contemporary business environments (e.g., Sawhney, Wolcott, & Arroniz, 2006).
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A CONTINGENCY PERSPECTIVE OF E-COLLABORATION In this section, I draw on contingency theory to integrate the conceptualizations developed thus far in this article into a process view of e-collaboration at the organizational level. Contingency theory, one of the most dominant theories in the study of organizational design and performance, is based on the assumption that there is no one best way to organize, and that any one way of organizing is not equally effective under all conditions (Galbraith, 1973). Central to this theory is the proposition that the structure and process of an organization must fit its context, if it is to be effective (Drazin & Van de Ven, 1985). The contingency approach to information systems research suggests that the better the fit between contingency variables and the design and use of IT, the better the IT performance and the organizational performance (Weill & Olson, 1989). The view developed here focuses on the business environment, specifically on the extent to which it is dynamic, as the primary contingency variable determining the preferred mode of ecollaboration. The business environment has been conceptualized as one of the key constructs for understanding organizational behavior and performance (Prescott, 1986). One of its important characteristics is the rate of change in products, processes, and organizational factors. The rate of change in the business environment has been found to be a moderator of the relationship between IT use and organizational performance (Guimaraes, Cook, & Natarajan, 2002). I propose that firms can implement collaborative technologies in two different modes, operational and strategic. The former is more valuable when a firm’s business environment is static, whereas the latter is more valuable when the business environment is dynamic.
The Business Value of E-Collaboration
Operational Mode of E-Collaboration Firms can implement collaborative technologies to improve their efficiency of scale and scope by building upon their ability to facilitate organizational coordination. Such an IT investment is more lucrative for firms that operate in less dynamic business environments and aim at gaining efficiency advantages in their markets. When market conditions are relatively stable, market entry barriers are high, new technologies are developed along an evolutionary path, and business models are established and steady, then a firm may pursue market advantages that are based on superior cost and time-to-market positions. To gain IT-based efficiency advantages, the firm can implement collaborative technologies that emphasize the coordination role of e-collaboration. The use of asynchronous communication tools, such as Wikis, Blogs, and RSS, may enable better exchange of information and explicit knowledge, improved coordination, and, eventually, cost and cycle time reductions. The primary purpose of such tools is to provide an efficient platform for information sharing; valuable information is easily captured, stored, presented, and disseminated. Such an information sharing mechanism facilitates rehearsability (the medium enables the rehearsal or fine tuning of messages prior to sending them) and reprocessability (messages can be reexamined or reprocessed within a communication event) (Dennis & Valacich, 1999). Rehearsability and reprocessability improve information clarity, accuracy, and completeness, which are crucial given the high cost associated with inaccuracies and misunderstandings when coordination and efficiency are the objectives.
Strategic Mode of E-Collaboration Firms can also use collaborative technologies to gain competitive advantages by capitalizing on their ability to facilitate organizational learning and innovation. Such an IT investment is more
lucrative for firms that operate in high-velocity markets and repeatedly seek to exploit opportunities and neutralize threats in their external environments. When market conditions are dynamic, market entry barriers are low, new technologies are developed along a revolutionary path, and business opportunities are proliferating, then a firm has to continuously find new organizational sources of competitiveness. To gain an IT-based competitive advantage, the firm can implement collaborative technologies that emphasize the role of e-collaboration in enabling learning and innovation processes. The use of synchronous collaboration tools, such as instant messaging and Web conferencing, may support the crossorganizational identification and integration of tacit knowledge, enhance learning processes, and generate opportunities for innovation. Such tools are designed to facilitate communication, expression, and collective thinking, significantly beyond those enabled by traditional technologies. The tools improve feedback immediacy (the medium enables rapid bidirectional communication), symbol variety (the variety of ways in which information can be communicated), and parallelism (the number of simultaneous conversations that can exist effectively) (Dennis & Valacich, 1999). In dynamic business environments, the interactiveness and richness of communication channels are crucial to the creative thinking of individuals and to their ability to learn and innovate.
Transitioning between Modes of E-Collaboration Another dynamic aspect that the framework should account for is the need to transition from one mode of e-collaboration to another because of a dramatic change in the level of environmental turbulence. A good example is the recent financial crisis that negatively affected the stability of many relatively static markets. Firms having to transition between e-collaboration modes need to transform the organizational role of e-collaboration from
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The Business Value of E-Collaboration
coordination to learning and innovation, or vice versa. Because the framework suggests that different roles are associated with different tools, these firms also need to transform their portfolio of collaboration tools. Thus, such a transition represents a combined technical-managerial effort. It requires financial resources to acquire new tools, and managerial resources to implement these tools and motivate employees to use them to enhance valuable organizational capabilities. While the technical effort should precede the managerial effort, the latter is undoubtedly more demanding and uncertain than the former. Firms that are able to meet this challenge are better positioned to create business value from e-collaboration. Figure 2 graphically summarizes the conceptual framework developed in this article.
FUTURE RESEARCH DIRECTIONS The conceptual framework presented in this article draws on contingency theory to argue that the extent to which the business environment is dynamic is an important determinant of the selection and implementation of collaborative technologies. This contingency approach to e-collaboration can be used in future research to explore the influence of other environmental characteristics on the
business value of e-collaboration. Such studies on environmental characteristics can considerably advance the e-collaboration literature because of its emphasis on the moderating effects of media and task characteristics. The conceptual framework depicted in Figure 2, which identifies the modes, roles, and impacts of e-collaboration, may serve as a theoretical starting point for such studies. Furthermore, the proposed framework can promote empirical research on the business value of e-collaboration. The conceptualizations developed in this article may be used straightforwardly to formulate research hypotheses about relationships among collaboration tools, roles, organizational impacts, and environmental characteristics. For example, empirical research may investigate whether synchronous collaboration tools are associated with collaboration-based learning and innovation, resulting in competitive impacts, and whether those relationships are more significant in dynamic business environments than in static environments.
CONCLUSION While there is an increasingly growing body of research that explores the organizational implementation of collaborative technologies, a
Figure 2. A conceptual framework of the business value of e-collaboration
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The Business Value of E-Collaboration
significant part of that research typically focuses on the context of the individual or the group. As a result, studies that use an organizational lens to explore e-collaboration are lacking. In this article, I propose a conceptual framework of the business value of e-collaboration. A view of e-collaboration as having three organizational roles – coordination, learning, and innovation – associated with either efficiency impacts (operational mode) or competitive impacts (strategic mode) offers valuable practical guidelines and, at the same time, advances theory development. The next conceptual step should be to link this organizational view to previous, more established views of e-collaboration, which focus on processes that individuals or groups undergo.
REFERENCES Adams, G. L., & Lamont, B. T. (2003). Knowledge management systems and developing sustainable competitive advantage. Journal of Knowledge Management, 7(2), 142–154. doi:10.1108/13673270310477342 Alavi, M., & Leidner, D. E. (2001). Knowledge management and knowledge management systems: Conceptual foundations and research issues. MIS Quarterly, 25(1), 107–136. doi:10.2307/3250961 Andreu, R., & Ciborra, C. (1996). Organizational learning and core capabilities development: The role of IT. The Journal of Strategic Information Systems, 5(2), 111–127. doi:10.1016/S09638687(96)80039-4 Bafoutsou, G., & Mentzas, G. (2002). Review and functional classification of collaborative systems. International Journal of Information Management, 22(4), 281–305. doi:10.1016/ S0268-4012(02)00013-0
Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. doi:10.1177/014920639101700108 Chi, L., & Holsapple, C. W. (2005). Understanding computer-mediated interorganizational collaboration: A model and framework. Journal of Knowledge Management, 9(1), 53–75. doi:10.1108/13673270510582965 Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128–152. doi:10.2307/2393553 Dennis, A. R., & Valacich, J. S. (1999). Rethinking media richness: Towards a theory of media synchronicity. In R. H. Sprague (Ed.), 32nd Hawaii International Conference on System Sciences (pp. 1-10). Los Alamitos, CA: IEEE Computer Society Press. Drazin, R., & Van de Ven, A. H. (1985). Alternative forms of fit in contingency theory. Administrative Science Quarterly, 30(4), 514–539. doi:10.2307/2392695 Eden, C., & Ackermann, F. (2001). Group decision and negotiation in strategy making. Group Decision and Negotiation, 10(2), 119–140. doi:10.1023/A:1008710816126 Eisenhardt, K. M., & Galunic, D. C. (2000). Coevolving: At last, a way to make synergies work. Harvard Business Review, 78(1), 91–101. Galbraith, J. (1973). Designing complex organizations. Reading, MA: Addison-Wesley. Grant, R. M. (1996). Toward a knowledgebased theory of the firm. Strategic Management Journal, 17, 109–122. doi:10.1002/ (SICI)1097-0266(199602)17:23.0.CO;2-P
35
The Business Value of E-Collaboration
Guimaraes, T., Cook, D., & Natarajan, N. (2002). Exploring the importance of business clockspeed as a moderator for determinants of supplier network performance. Decision Sciences, 33(4), 629–644. doi:10.1111/j.1540-5915.2002.tb01659.x
Nonaka, I., Toyama, R., & Nagata, A. (2000). A firm as a knowledge-creating entity: A new perspective on the theory of the firm. Industrial and Corporate Change, 9(1), 1–20. doi:10.1093/ icc/9.1.1
Huang, J. C., & Newell, S. (2003). Knowledge integration processes and dynamics within the context of cross-functional projects. International Journal of Project Management, 21(3), 167–176. doi:10.1016/S0263-7863(02)00091-1
Paul, D. L. (2006). Collaborative activities in virtual settings: A knowledge management perspective of telemedicine. Journal of Management Information Systems, 22(4), 143–176. doi:10.2753/MIS0742-1222220406
Kock, N., Davison, R., Wazlawick, R., & Ocker, R. (2001). E-collaboration: A look at past research and future challenges. Journal of Systems and Information Technology, 5(1), 1–9.
Prescott, J. E. (1986). Environments as moderators of the relationship between strategy and performance. Academy of Management Journal, 29(2), 329–346. doi:10.2307/256191
Kock, N., & Nosek, J. (2005). Expanding the boundaries of e-collaboration. IEEE Transactions on Professional Communication, 48(1), 1–9. doi:10.1109/TPC.2004.843272
Sawhney, M., Wolcott, R. C., & Arroniz, I. (2006). The 12 different ways for companies to innovate. MIT Sloan Management Review, 47(3), 75–81.
Kogut, B., & Zander, U. (1996). What do firms do? Coordination, identity, and learning. Organization Science, 7(5), 502–518. doi:10.1287/orsc.7.5.502
Scott, J. E. (2000). Facilitating interorganizational learning with information technology. Journal of Management Information Systems, 17(2), 81–113.
Leidner, D., Alavi, M., & Kayworth, T. (2006). The role of culture in knowledge management: A case study of two global firms. International Journal of e-Collaboration, 2(1), 17–40.
Teece, D. J., Pisano, G., & Shuen,A. (1997). Dynamic capabilities and strategic management. Strategic ManagementJournal,18(7),509–533.doi:10.1002/ (SICI)1097-0266(199708)18:73.0.CO;2-Z
Malone, T. W., & Crowston, K. (1994). The interdisciplinary study of coordination. ACM Computing Surveys, 26(1), 87–119. doi:10.1145/174666.174668
Weill, P., & Olson, M. H. (1989). An assessment of the contingency theory of management information systems. Journal of Management Information Systems, 6(1), 59–85.
McLaren, T., Head, M., & Yuan, Y. (2002). Supply chain collaboration alternatives: Understanding the expected costs and benefits. Internet Research, 12(4), 348–364. doi:10.1108/10662240210438416
Wheeler, B. C. (2002). NEBIC: A dynamic capabilities theory for assessing net-enablement. Information Systems Research, 13(2), 125–146. doi:10.1287/isre.13.2.125.89
Melville, N., Kraemer, K., & Gurbaxani, V. (2004). Information technology and organizational performance: An integrative model of IT business value. MIS Quarterly, 28(2), 283–322. Nonaka, I. (1991). The knowledge-creating company. Harvard Business Review, 69(6), 96–104.
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ADDITIONAL READING Barua, A., Konana, P., Whinston, A. B., & Yin, F. (2004). An empirical investigation of net-enabled business value. MIS Quarterly, 28(4), 585–620.
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Bharadwaj, A. S. (2000). A resource-based perspective on information technology capability and firm performance: An empirical investigation. MIS Quarterly, 24(1), 169–196. doi:10.2307/3250983 Bhatt, G. D., & Grover, V. (2005). Types of information technology capabilities and their role in competitive advantage: An empirical study. Journal of Management Information Systems, 22(2), 253–277. Brews, P. J., & Tucci, C. L. (2004). Exploring the structural effects of internetworking. Strategic Management Journal, 25(5), 429–451. doi:10.1002/smj.386 Daft, R. L., & Lengel, R. H. (1986). Organizational information requirements, media richness and structural design. Management Science, 32(5), 554–571. doi:10.1287/mnsc.32.5.554 Dedrick, J., Gurbaxani, V., & Kraemer, K. L. (2003). Information technology and economic performance: A critical review of the empirical evidence. ACM Computing Surveys, 35(1), 1–28. doi:10.1145/641865.641866 El Sawy, O. A., & Pavlou, P. A. (2008). IT-enabled business capabilities for turbulent environments. MIS Quarterly Executive, 7(3), 139–150. Fink, L., & Neumann, S. (2009). Exploring the perceived business value of the flexibility enabled by information technology infrastructure. Information & Management, 46(2), 90–99. doi:10.1016/j.im.2008.11.007 Ginsberg, A., & Venkatraman, N. (1985). Contingency perspectives of organizational strategy: A critical review of the empirical research. Academy of Management Review, 10(3), 421–434. doi:10.2307/258125 Goh, A. L. S. (2005). Harnessing knowledge for innovation: An integrated management framework. Journal of Knowledge Management, 9(4), 6–18. doi:10.1108/13673270510610297
Kearns, G. S., & Lederer, A. L. (2003). A resourcebased view of strategic IT alignment: How knowledge sharing creates competitive advantage. Decision Sciences, 34(1), 1–29. doi:10.1111/15405915.02289 Kock, N. (Ed.). (2007). Encyclopedia of e-collaboration. Hershey, PA: Information Science Reference. Kohli, R., & Grover, V. (2008). Business value of IT: An essay on expanding research directions to keep up with the times. Journal of the Association for Information Systems, 9(1), 23–39. Li, M., & Ye, L. R. (1999). Information technology and firm performance: Linking with environmental, strategic and managerial contexts. Information & Management, 35(1), 43–51. doi:10.1016/ S0378-7206(98)00075-5 Malhotra, Y. (2000). Knowledge management and new organization forms: A framework for business model innovation. Information Resources Management Journal, 13(1), 5–14. Nonaka, I., & Takeuchi, H. (1995). The knowledgecreating company: How Japanese companies create the dynamics of innovation. New York, NY: Oxford University Press. Oh, W., & Pinsonneault, A. (2007). On the assessment of the strategic value of information technologies: Conceptual and analytical approaches. MIS Quarterly, 31(2), 239–265. Peteraf, M. A. (1993). The cornerstones of competitive advantage: A resource-based view. Strategic Management Journal, 14(3), 179–191. doi:10.1002/smj.4250140303 Porter, M. E. (2001). Strategy and the Internet. Harvard Business Review, 79(3), 63–78. Powell, W. W., Koput, K. W., & Smith-Doerr, L. (1996). Interorganizational collaboration and the locus of innovation: Networks of learning in biotechnology. Administrative Science Quarterly, 41(1), 116–145. doi:10.2307/2393988 37
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Ravichandran, T., & Lertwongsatien, C. (2005). Effect of information systems resources and capabilities on firm performance: A resource-based perspective. Journal of Management Information Systems, 21(4), 237–276. Sambamurthy, V., Bharadwaj, A., & Grover, V. (2003). Shaping agility through digital options: Reconceptualizing the role of information technology in contemporary firms. MIS Quarterly, 27(2), 237–263. Santhanam, R., & Hartono, E. (2003). Issues in linking information technology capability to firm performance. MIS Quarterly, 27(1), 125–153. Soh, C., & Markus, M. L. (1995). How IT creates business value: A process theory synthesis. In J. I. DeGross, G. Ariav, C. Beath, R. Hoyer & C. Kemerer (Eds.), 16th International Conference on Information Systems (pp. 29-41). Atlanta, GA: Association for Information Systems. Teece, D. J. (2007). Explicating dynamic capabilities: The nature and microfoundations of (sustainable) enterprise performance. Strategic Management Journal, 28(13), 1319–1350. doi:10.1002/smj.640 Teo, T. S. H., & Pian, Y. (2003). A contingency perspective on Internet adoption and competitive advantage. European Journal of Information Systems, 12(2), 78–92. doi:10.1057/palgrave. ejis.3000448 Tippins, M. J., & Sohi, R. S. (2003). IT competency and firm performance: Is organizational learning a missing link? Strategic Management Journal, 24(8), 745–761. doi:10.1002/smj.337
Wade, M., & Hulland, J. (2004). The resourcebased view and information systems research: Review, extension, and suggestions for future research. MIS Quarterly, 28(1), 107–142. Zahra, S. A., & George, G. (2002). The net-enabled business innovation cycle and the evolution of dynamic capabilities. Information Systems Research, 13(2), 147–150. doi:10.1287/isre.13.2.147.90 Zigurs, I., & Buckland, B. K. (1998). A theory of task/technology fit and group support systems effectiveness. MIS Quarterly, 22(3), 313–334. doi:10.2307/249668
KEY TERMS AND DEFINITIONS Business Value: The contribution of a firm resource to business performance. Competitive Advantage: The ability of a firm to systematically achieve above-normal performance. Contingency Theory: A theoretical view that considers the fit between a firm’s structure and process and its context as critical to organizational effectiveness. Dynamic Capability: A theoretical view that attributes competitive advantage to a firm’s ability to reconfigure and redeploy its resource base to address rapidly changing environments. E-Collaboration: Cooperation among individuals using electronic technologies. Organizational Learning: The ability within an organization to improve performance based on experience. Resource-Based View: A theoretical view that attributes competitive advantage to a subset of firm resources.
This work was previously published in Encyclopedia of E-Business Development and Management in the Global Economy, edited by In Lee, pp. 144-154, copyright 2010 by Business Science Reference (an imprint of IGI Global).
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Chapter 1.3
Virtual Corporations Sixto Jesús Arjonilla-Domínguez Freescale Semiconductor, Inc., Spain José Aurelio Medina-Garrido Cadiz University, Spain
INTRODUCTION At the end of the 20th century, many authors tried to predict what new structures companies would be likely to adopt in the 21st century. Now, in the 21st century a clear tendency is emerging: the virtual organization (Agrawal & Hurriyet, 2004; Alsop, 2003; Bekkers, 2003; Camarinha-Matos & Afsarmanesh, 2005; Heneman & Greenberger, 2002; Lee, Cheung, Lau, & Choy, 2003; Talukder, 2003; Vakola & Wilson, 2004). This type of organization offers the most promising response to an increasingly complex business reality. In this respect, current organization theory is beginning to change its focus to new, flexible, and virtual organizational forms.
This article is organized as follows: The background section defines different concepts of virtual organization. The first model equates the virtual corporation to a temporary network of firms that quickly comes together to exploit temporary market opportunities. The second model focuses on the manufacture of virtual products by means of stable and trusting relationships with suppliers and customers. The third model of virtual corporation tries to turn the fixed workforce costs into variable costs. The third section points out the shared characteristics of this type of organization and the role of the manufacturing function, information and information technology, the network structure, and a new type of worker. The final sections discuss future trends and our conclusions.
DOI: 10.4018/978-1-60960-587-2.ch103
Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
Virtual Corporations
BACKGROUND The term virtual corporation was coined by Jan Hopland, an executive at Digital Equipment Corporation at the end of the 1980s, to describe firms that can marshal more resources than they actually possess by means of both internal and external collaborations (Fitzpatrick & Burke, 2001; Weisenfeld, Fisscher, Pearson, & Brockhoff, 2001). The term can be traced to the computing concept of virtual memory, which describes how a computer can behave as if it had much more processing power than it really has. The expression virtual corporation has been used in the literature to refer to concepts ranging from simply using teleworking and outsourcing intensively (Buhman, 2003; Coates, 2005; Matthews, 2004) to the wholesale restructuring of the firm. However, three approaches predominate in the literature: (1) virtual corporation as a temporary network of firms that rapidly forms to exploit temporary opportunities appearing in the market (Alsop, 2003; Beckett, 2003; Chalmeta & Grangel, 2003); (2) virtual corporation as a firm that produces virtual products, and which develops strong and stable links with its suppliers and customers (Biondi, Bonfatti, Monari, Giannini, & Monti, 2003; Lee et al., 2003; Mo & Zhou, 2003); and (3) a final model which considers that the virtual firm is an organization whose costs are essentially variable, only being generated when the firm is sure that it will recover them by selling the product or service (Matthews, 2004; Talukder, 2003). The virtual corporation can also be defined by what it is not. The virtual corporation is not a takeover or merger between firms, nor is it a temporary employment agency, nor a “hollow” firm seeking to cut costs by closing down factories in one country and opening them up again in another one with lower labor costs.
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CHARACTERISTICS OF VIRTUAL CORPORATIONS As we mentioned in the previous section, there are three different perspectives of the concept of virtual corporation. Among the characteristics shared by these three models of virtual corporation, we would stress: excellence, technology, trust, opportunism, and absence of borders: •
•
•
•
•
Excellence: Since each member contributes its core competencies (Mo & Zhou, 2003), it is possible to create an organization with the best of each of them, so that every process of the virtual corporation can be the best in its class, something that no one firm could achieve on its own. Technology: Information technology— and more specifically, communications networks—will facilitate the transfer of knowledge and technologies between firms and will allow firms and workers to work together (Helling, Blim, & O’Regan, 2005; Heneman & Greenberger, 2002; Im, Yates, & Orlikowski, 2005; Kovacs & Paganelli, 2003). Trust: This type of relationship makes firms more dependent on others, and hence requires a much greater trust than would normally be the case between firms that are just partners (Camarinha-Matos & Afsarmanesh, 2003; Clases, Bachmann, & Wehner, 2003; Gallie & Guichard, 2005). Opportunism: In the first and third model, firms will come together to exploit a very specific market opportunity, disbanding as soon as the opportunity disappears. In the second model, the opportunity to form a virtual corporation is brief. Once a firm adopts a virtual corporation structure, other firms have less chance of doing the same. Absence of Organizational Borders: The close cooperative ties established between competitors, suppliers, and customers will
Virtual Corporations
make it difficult to see where one firm ends and another begins (Lee et al., 2003). This organizational structure shares the knowledge and resources needed to carry out the work to be done, regardless of which firm owns or manages them. In virtual corporations the role of the manufacturing function also changes (Martinez, Fouletier, Park, & Favrel, 2001). This type of organizational structure seeks to generate high-quality products and services rapidly in response to the demand (Offodile & Abdel-Malek, 2002; Weisenfeld et al., 2001). Generating virtual products, also known as mass-customized products (Biondi et al., 2003), requires both the customers’ participation in their conception and design and the firms’ implementation of time-based strategies. This implies combining the customers and suppliers in a type of highly efficient network (Lee et al., 2003), which will require information systems that support relationships at all levels (Hsieh, Lin, & Chiu 2002). Companies will focus on one, maybe two, or three core competencies, all else will be outsourced (Buhman, 2003; Erickson, 2004; Mo & Zhou, 2003; Porter, 2000). Time is regarded as a component that, like any other, can be improved by means of intelligent planning and the use of technology (Hao, Shen, & Wang, 2005; Lee et al., 2003). Mass customization of products combines the effects of lean manufacturing processes (Guisinger & Ghorashi, 2004), zero-inventory production methods, or just-in-time, and total quality management processes. These management processes make it possible to produce the great variety of products that could once only be made by craft manufacturing, but often at a lower cost than mass production, and with excellent quality. Moreover, incorporating the new information technology into the manufacturing processes has given rise to flexible manufacturing systems (FMS) and computer-integrated manufacturing (CIM) (Presley, Sarkis, Barnett, & Liles, 2001).
Such systems help manufacturers to achieve many of the objectives of the virtual corporation, such as shorter production cycles, a smaller and more qualified labor force, smaller batches, flexibility, a better short-term response, and long-term adaptability. In virtual corporations, the role of information and information technology is also important (Aerts, Szirbik, & Goossenaerts, 2002; Alsop, 2003; Gallie & Guichard, 2005; Heneman & Greenberger, 2002; Joukhadar & Binstock, 2000; Khalil & Wang, 2002; Kovacs & Paganelli, 2003; Stowell, 2005; Xu, Wei, & Fan, 2002). This role becomes clear in the three models described previously. The virtual corporation understood as a network of firms is also an information system where there is an exchange of the data generated by the activities or processes (internal and external) that it carries out. The success of the virtual corporation will depend on its capacity to acquire, distribute, store, analyze, and integrate this massive flow of information through its organizational elements, supported by information technology. The model of virtual corporation defined as a generator of virtual products is characterized by the customers’ intense participation in the creation of the products, and by the high information component of the latter. This growing information component of products is evident in the mass customization of products that the virtual corporation is applying. On the other hand, the virtual corporation is organized as a network organization structure. Firms have gone from competing against each other to cooperating. This cooperation was initially based on more or less temporary alliances, and subsequently on connections of variable geometry. This new organizational structure of variable geometry, or dynamic network structure, considers that the main components of firms can be assembled and reassembled again and again to adapt to the changing environmental conditions (Aerts et al., 2002; Huang, Gou, Liu, Li, & Xie, 2002). This network structure is accepted by all
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Virtual Corporations
of the authors (Camarinha-Matos & Afsarmanesh, 2003, 2005; Weisenfeld et al., 2001), although they refer to it using different analogies and names. Where there is consensus is in the idea that the dynamic network is the most flexible organizational form known. Its main characteristics are: (1) disaggregation of the firm’s functions (design and development, manufacturing, marketing, and distribution), now carried out by independent organizations in a network; (2) existence of internal and external agents, responsible for linking the business functions of different firms (Aerts et al., 2002; Zarour, Boufaida, Seinturier, & Estraillier, 2005); (3) existence of market mechanisms for coordinating the functions, rather than plans and controls (Biggs, 2000); and (4) existence of freely accessible information systems for verifying each member’s contribution (Zarour et al., 2005), rather than the slow processes of mutual trust building. The virtual corporation is founded on a new type of worker. This organizational structure is based on the management of processes, demanding a flexible number of versatile and autonomous human resources. Thus, a radical change in corporate culture is required for the concept of virtual corporation to work. This culture will be reflected throughout the entire organization, requiring new management skills (Heneman & Greenberger, 2002; Khalil & Wang, 2002)—focusing on how to lead “persons” and manage “relationships” (Beranek & Martz, 2005)—and a new type of worker. With regards to human resource management, the emphasis is on retaining highly qualified workers in this type of organization (Erickson, 2004), and there is significant rotation of workers between the different functions and divisions of the firm. These workers turn the firm into a learning organization. Agile Web Inc. is an example of virtual corporation. It is made up of 20 successful small and medium-sized manufacturing enterprises in north-eastern Pennsylvania. The aim of this project was that small firms could become more
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competitive, more productive, and provide a greater value-added service to their customers by working together in new ways to provide totally integrated solutions. This virtual corporation has the ability to knit companies together in the right configuration to achieve each task with speed and efficiency. Agile Web Inc. acts as a single point of contact that directs all the aspects of multi-phase design and production projects, ever changing to meet the customer’s needs and anticipating them. The member companies are able to communicate by e-mail and electronic data interchange (EDI) to ensure a quick response. Agile Web Inc. offers a totally integrated chain of suppliers with high flexibility by a sharing of needed information rather than within a traditional hierarchical structure. The company’s mission is to provide customers with solutions at the lowest possible price, with the fastest delivery time and highest technical performance. This example of virtual corporation illustrates the above mentioned roles of the manufacturing function, information, and information technology, and the network structure.
FUTURE TRENDS It will be many years before we see the first real virtual corporation. There is no empirical evidence that fully supports this theoretical model, but there is growing interest in the model in the literature, as well as among firms. This model never gained widespread acceptance because the technology needed to integrate companies with their suppliers and customers did not exist. Now, the technology exists and companies are beginning to revisit the virtual corporation concept (Joukhadar & Binstock, 2000). Thus, for example Hector Ruiz (personal communication, January 24, 1997), after being named executive president of Motorola’s semiconductor sector, wrote in an internal memo that organizations like his were becoming increasingly virtual. This trend is recognized by the Electronics Manufacturing Service Industry
Virtual Corporations
(EMSI), which detects a shift towards the virtual corporation in companies as important as Apple, Cisco, Bay Networks, and HP. From the academic perspective, important lines of research are opening up. On the one hand, researchers could investigate which of the three models of virtual corporation described previously is most likely to be adopted by firms in the future. Another line of research would be to design an approach integrating the three models. Finally, it would be interesting to analyze the virtual corporation model from the perspective of the most consolidated theories of the firm (transaction cost economics, institutional theory, agency theory, options theory, population ecology theory, resource-based view of the firm, network theory, sociological theory, etc.). Analyzing the virtual corporation phenomenon with each of these theories would allow us to increase understanding of the phenomenon, its impact on firms and society, and future trends.
CONCLUSION The new knowledge-based economy requires flexibility, new organizational structures, and managerial processes—based more on information than on hierarchy. Firms need to encourage self-learning, adapt to and exploit rapid technological change, and use their core competencies to differentiate themselves from their competitors. The characteristics described previously are reflected in the different models of virtual corporation discussed in this article. The first model equates the virtual corporation to a temporary network of firms that quickly comes together to exploit temporary market opportunities, using the best resources and capabilities of each firm. The second model focuses on the manufacture of virtual products—which vary according to customer needs—by means of stable and trusting relationships with suppliers and customers. The third model of virtual corporation tries to turn the
fixed workforce costs into variable costs, which are only incurred when the market demands the product or service. This article outlines both the basic characteristics that define the virtual corporation—excellence, technology, trust, opportunism, and absence of borders—and other elements that, while they are not exclusive to virtual corporations, must always be present to make them possible. This is the case of the set of technologies making up the so-called lean manufacturing, of information and information technology, of the new type of worker, and of the organizational structures of variable geometry or dynamic networks. Nevertheless, all authors coincide in noting that we have not yet seen the pure virtual corporation defined in the theoretical literature. At present it remains just an important trend towards which many firms are gradually orienting their management and organizational structure.
REFERENCES Aerts, A. T. M., Szirbik, N. B., & Goossenaerts, J. B. M. (2002). A flexible, agent-based ICT architecture for virtual enterprises. Computers in Industry, 49(3), 311–327. .doi:10.1016/S01663615(02)00096-9 Agrawal, R. K., & Hurriyet, H. (2004). The advent of manufacturing technology and its implications for the development of the value chain. International Journal of Physical Distribution & Logistics Management, 34(3/4), 319–336. .doi:10.1108/09600030410533619 Alsop, S. (2003). I’ve seen the real future of tech and it is virtual. Fortune, 147(7), 390. Beckett, R. C. (2003). Determining the anatomy of business systems for a virtual enterprise. Computers in Industry, 51(2), 127. .doi:10.1016/ S0166-3615(03)00032-0
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Bekkers, V. (2003). E-government and the emergence of virtual organizations in the public sector. Information Polity, 8(3/4), 89–101. Beranek, P. M., & Martz, B. (2005). Making virtual teams more effective: improving relational links. Team Performance Management, 11(5/6), 200–213. .doi:10.1108/13527590510617774 Biggs, M. (2000, September). Tomorrow’s workforce. InfoWorld: CTO FirstMover, S59-S61. Biondi, D., Bonfatti, F., Monari, P. D., Giannini, F., & Monti, M. (2003). A product manager supporting a new co-design methodology for SMEs. International Journal of Computer Applications in Technology, 18(1/4), 174–188. Buhman, C. H. (2003). Oncoming wave of collaboration. Industrial Engineer, 35(8), 43. Camarinha-Matos, L. M., & Afsarmanesh, H. (2003). Elements of a base VE infrastructure. Computers in Industry, 51(2), 139. .doi:10.1016/ S0166-3615(03)00033-2 Camarinha-Matos, L. M., & Afsarmanesh, H. (2005). Collaborative networks: A new scientific discipline. Journal of Intelligent Manufacturing, 16(4-5), 439–452. .doi:10.1007/s10845-0051656-3 Chalmeta, R., & Grangel, R. (2003). ARDIN extension for virtual enterprise integration. Journal of Systems and Software, 67(3), 141. .doi:10.1016/ S0164-1212(02)00125-5 Clases, C., Bachmann, R., & Wehner, T. (2003). Studying trust in virtual organizations. International Studies of Management & Organization, 33(3), 7–27. Coates, J. (2005). At 14 technology trends. Research Technology Management, 48(5), 7–9. Erickson, K. (2004). The tangible presence of virtual agribusiness. Agri Marketing, 42(8), 20–22.
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Fitzpatrick, W. M., & Burke, D. R. (2001). Virtual venturing and entry barriers: Redefining the strategic landscape. S.A.M. Advanced Management Journal, 66(4), 22–30. Gallie, E. P., & Guichard, R. (2005). Do collaboratories mean the end of face-to-face interactions? An evidence from the ISEE project. Economics of Innovation and New Technology, 14(6), 517–532. .doi:10.1080/1043859042000304052 Guisinger, A., & Ghorashi, B. (2004). Agile manufacturing practices in the specialty chemical industry: An overview of the trends and results of a specific case study. International Journal of Operations & Production Management, 24(5/6), 625–635. .doi:10.1108/01443570410538140 Hao, Q., Shen, W., & Wang, L. (2005). Towards a cooperative distributed manufacturing management framework. Computers in Industry, 56(1), 71–84. .doi:10.1016/j.compind.2004.08.010 Helling, K., Blim, M., & O’Regan, B. (2005).An appraisal of virtual networks in the environmental sector. Management of Environmental Quality, 16(4), 327–337. .doi:10.1108/14777830510601208 Heneman, R. L., & Greenberger, D. B. (2002). Human Resource Management in Virtual Organizations. Greenwich, CT: Information Age. Hsieh, Y., Lin, N., & Chiu, H. (2002). Virtual factory and relationship marketing—A case study of a Taiwan semiconductor manufacturing company. International Journal of Information Management, 22(2), 109–126. .doi:10.1016/ S0268-4012(01)00049-4 Huang, B., Gou, H., Liu, W., Li, Y., & Xie, M. (2002). A framework for virtual enterprise control with the holonic manufacturing paradigm. Computers in Industry, 49(3), 299–310. .doi:10.1016/ S0166-3615(02)00098-2
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Im, H. G., Yates, J., & Orlikowski, W. (2005). Temporal coordination through communication: Using genres in a virtual start-up organization. Information Technology & People, 18(2), 89–119. .doi:10.1108/09593840510601496 Joukhadar, K., & Binstock, A. (2000). Virtual enterprise comes of age. Information Week, 811, 141. Khalil, O., & Wang, S. (2002). Information technology enabled meta-management for virtual organizations. International Journal of Production Economics, 75(1-2), 127–134. .doi:10.1016/ S0925-5273(01)00186-4 Kovacs, G. L., & Paganelli, P. (2003). A planning and management infrastructure for large, complex, distributed projects—Beyond ERP and SCM. Computers in Industry, 51(2), 165. .doi:10.1016/ S0166-3615(03)00034-4 Lee, W. B., Cheung, C. F., Lau, H. C. W., & Choy, K. L. (2003). Development of a Web-based enterprise collaborative platform for networked enterprises. Business Process Management Journal, 9(1), 46–59. .doi:10.1108/14637150310461396 Martinez, M. T., Fouletier, P., Park, K. H., & Favrel, J. (2001). Virtual enterprise—Organisation, evolution and control. International Journal of Production Economics, 74(1-3), 225–238. .doi:10.1016/S0925-5273(01)00129-3 Matthews, J. (2004). The rise of the virtual company. Supply Management, 9(15), 32–33. Mo, J. P. T., & Zhou, M. (2003). Tools and methods for managing intangible assets of virtual enterprise. Computers in Industry, 51(2), 197. .doi:10.1016/ S0166-3615(03)00036-8 Offodile, O. F., & Abdel-Malek, L. L. (2002). The virtual manufacturing paradigm: The impact of IT/ IS outsourcing on manufacturing strategy. International Journal of Production Economics, 75(1-2), 147–159. .doi:10.1016/S0925-5273(01)00188-8
Porter, A. M. (2000). The virtual corporation: Where is it? Purchasing, 128(4), 40–48. Presley, A., Sarkis, J., Barnett, W., & Liles, D. (2001). Engineering the virtual enterprise: An architecture-driven modeling approach. International Journal of Flexible Manufacturing Systems, 13(2), 145. .doi:10.1023/A:1011131417956 Stowell, C. (2005). Real-time collaboration with flair. Communique Newsletter, 42(3), 40–42. Talukder, M. I. (2003). The perception of professionals and management personnel on the virtual organization. Journal of Computer Information Systems, 43(3), 92–99. Vakola, M., & Wilson, I. E. (2004). The challenge of virtual organisation: Critical success factors in dealing with constant change. Team Performance Management, 10(5/6), 112–120. .doi:10.1108/13527590410556836 Weisenfeld, U., Fisscher, O., Pearson, A., & Brockhoff, K. (2001). Managing technology as a virtual enterprise. R & D Management, 31(3), 323–334. .doi:10.1111/1467-9310.00220 Xu, W., Wei, Y., & Fan, Y. (2002). Virtual enterprise and its intelligence management. Computers & Industrial Engineering, 42(2-4), 199–205. .doi:10.1016/S0360-8352(02)00053-0 Zarour, N., Boufaida, M., Seinturier, L., & Estraillier, P. (2005). Supporting virtual enterprise systems using agent coordination. Knowledge and Information Systems, 8(3), 330. .doi:10.1007/ s10115-004-0183-4
KEY TERMS AND DEFINITIONS Information Component of Products: All that the buyer needs to know to obtain and use the product, and hence achieve the desired result (information about product characteristics, instructions for use, and maintenance).
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Knowledge-Based Economy: An economy characterized by the recognition of knowledge as a source of competitiveness; the increasing importance of science, research, technology, and innovation in knowledge creation; and the use of computers and the Internet to generate, share, and apply knowledge. Lean Manufacturing: “A philosophy of production that emphasizes the minimization of the amount of all the resources (including time) used in the various activities of the enterprise” (APICS Dictionary). Strategic Network: Agreements by which firms establish a web of close, stable relationships to provide products and services in a coordinated and flexible way. Teleworking: Professional activity that takes place in a firm and that is independent of the firm’s physical location. The person who does this work at a distance—the teleworker—keeps in contact with the firm using information technology.
Variable Cost Virtual Corporation: These firms turn fixed personnel costs into variable costs. They make use of freelance teleworkers, who can be called in or sent home at the employer’s convenience, and outsourcing (Coates, 2005). Variable Geometry Structure: Dynamic network of firms whose main components can be assembled and reassembled again and again to adapt to the complex and changing environmental conditions. Virtual Corporation as Temporary Network: Set of firms that come together quickly to exploit temporary opportunities appearing in the market, using each firm’s best resources and capabilities. Virtual Corporation That Manufactures Virtual Products: Stable and trusting relationships with suppliers and customers to manufacture products that adapt to each customer’s changing needs. Virtual Product: A product that adapts to the customer’s changing needs.
This work was previously published in Encyclopedia of Information Science and Technology, Second Edition, edited by Mehdi Khosrow-Pour, pp. 3992-3996, copyright 2009 by Information Science Reference (an imprint of IGI Global).
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Chapter 1.4
E-Business Strategy in Franchising Ye-Sho Chen Louisiana State University, USA Chuanlan Liu Louisiana State University, USA Qingfeng Zeng Shanghai University of Finance and Economics, China
INTRODUCTION Franchising as a global growth strategy is gaining its popularity (Justis and Judd, 2002; Thomas and Seid, 2000; Chen and Justis, 2006). For example, the U.S. Commercial Service estimated that China, having over 2,600 brands with 200,000 franchised retail stores in over 80 sectors, is now the largest franchise market in the world (U.S. Commercial Service, 2008). The popularity of franchising continues to increase, as we witness an emergence of a new e-business model, Netchising, which is the combination power of the Internet for global demand-and-supply processes and the DOI: 10.4018/978-1-60960-587-2.ch104
international franchising arrangement for local responsiveness (Chen, Justis, and Yang, 2004; Chen, Chen, and Wu, 2006). For example, Entrepreneur magazine – well known for its Franchise 500 listing – in 2001 included Tech Businesses into its Franchise Zone that contains Internet Businesses, Tech Training, and Miscellaneous Tech Businesses. At the time of this writing, 45 companies are on its list. In his best seller, Business @ the Speed of Thought, Bill Gates (1999) wrote: “Information Technology and business are becoming inextricably interwoven. I don’t think anybody can talk meaningfully about one without talking about the other.” (p. 6) Gates’ point is quite true when one talks about e-business strategy in franchising. Thus, to see how e-business can be
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E-Business Strategy in Franchising
“meaningfully” used in franchising, one needs to know how franchising really works.
FRANCHISING: BUILDING THE FRANCHISOR/FRANCHISEE RELATIONSHIP Franchising is “a business opportunity by which the owner (producer or distributor) of a service or a trademarked product grants exclusive rights to an individual for the local distribution and/or sale of the service or product, and in return receives a payment or royalty and conformance to quality standards. The individual or business granting the business rights is called the franchisor, and the individual or business granted the right to operate in accordance with the chosen method to produce or sell the product or service is called the franchisee.” (Justis and Judd, 2002, pp. 1-3) Developing a good relationship between the franchisor and the franchisee is the key for a successful franchise (Justis and Judd, 2002). Figure 1 describes how to build a good franchisor/franchisee relationship. The franchisor needs to learn continuously for the growth of the franchise. The learning process is developed through five stages (Justis and Judd, 2002): (1) Beginner – learning how to do it; (2) Novice – practicing doing it; (3) Advanced – do-
ing it; (4) Master – teaching others to do it; and (5) Professional – becoming the best that you can be. Once reaching the Advanced stage, most preceding struggles have been overcome. However, further challenges will arise as the franchise continues growing. This is especially true once the system reaches the “Professional” stage, where various unpredicted and intricate problems could arise. Bud Hadfield (1995), the founder of Kwik Kopy franchise and the International Center of Entrepreneurial Development, aptly stated: “The more the company grows, the more it will be tested.” (p. 156). To capture the learning process, a counter-clockwise round arrow surrounding the franchisor is used to depict the increasing intensity of learning as the franchisor continues to grow. The franchisee also goes through five stages of franchisee life cycle (Schreuder, Krige, and Parker, 2000): (1) Courting: both the franchisee and the franchisor are eager with the relationship; (2) “We”: the relationship starts to deteriorate, but the franchisee still values the relationship; (3) “Me”: the franchisee starts to question the franchisor that the success so far is purely of his/her own work; (4) Rebel: the franchisee starts to challenge the franchisor; and (5) Renewal: the franchisee realizes the “win-win” solution is to continue working with the franchisor to grow the system. Similar to the franchisor, a counter-clockwise
Figure 1. Understanding how the franchisor/franchisee relationship works
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round arrow surrounding the franchisee is used in Figure 1 to depict the increasing intensity as the franchisee continues growing. As the franchisee progresses through the life cycle, the good relationship gradually develops an influencing process (Justis and Vincent, 2001), depicted in Figure 1 with a bi-directional arrow. By going through the processes of learning and influencing, both the franchisor and the franchisee gain the progressive working knowledge of relationship management with the consumers and suppliers. The franchisor, the franchisee, the consumers, and the suppliers in Figure 1 are surrounded with dashed lines, indicating that there is no limit to the learning process.
E-BUSINESS STRATEGY IN FRANCHISE RELATIONSHIP MANAGEMNET With the advancement of Internet technology, franchise companies are adapting e-business strategies for perfecting the franchisor/franchisee
relationship to grow their franchises globally. Figure 2 is a visual depiction of deploying ebusiness strategy in franchising. This community of franchise companies, consumers, and suppliers can be virtually connected for relationship management as follows: •
•
•
Intra-enterprise collaboration through Intranet, enabling the franchisor to build up relationships with the board of directors, multi-unit franchisees, new franchisees, prospective franchisees, franchisor management and employees; Collaboration with consumers through Internet, enabling the franchisor and the franchisees to build up relationships with customers, prospective customers, investors, competitors, media, blogs, advocacy groups, and government; Collaboration with suppliers through Extranet, enabling the franchisor and the franchisees to build up relationships with members and affiliates of international franchise association, law firms, co-brand-
Figure 2. E-Business strategy in franchise relationship management
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E-Business Strategy in Franchising
ing partners, goods distributors, real estate agents, information systems consultants, accounting firms, and marketing agents.
HARNESSING THE E-BUSINESS STRATEGY AROUND THE CUSTOMER SERVICE LIFE CYCLE Table 1 shows a customer-service-life-cycle (CSLC) (Ives and Mason, 1990) e-business strategy in franchising (Chen, Chong, and Justis, 2002) for relationship management depicted in Figure 2. Here we define the franchisee as the customer of the franchisor and the franchisee’s customer as the customer’s customer of the franchisor. The stages of CSLC are based on two well-known franchising books by Justis and Judd (2002) and Thomas and Seid (2000). There are four major components in the ebusiness strategy: 1. Benchmarking the Requirements and Acquisition stages. The CSLC model shown in Table 1 is a comprehensive guide for a franchise to develop its web site, especially at the stages of Requirements and Acquisition. The model may be used to compare a franchise’s e-business strategy with its competitors. As the industry progresses, best practices based on the CSLC model will evolve and become a standard for benchmarking and websites enhancements. 2. Helping the franchisees serve their customers in the Ownership stage without the Internet encroachment. There is a rich collection of studies in e-business in franchising (Chen, Chong, and Justis, 2002) showing how the Internet can help the franchisees serve their customers in the Ownership stage, including “Marketing & Promoting the Franchise Products/Services” and “Managing the Franchise System”.
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3. Cultivating the Ownership and Renewal/ Retirement stages with effective knowledge management. As mentioned earlier, the greatest challenge in the Ownership stage is to build up the relationship between the franchisor and franchisee. To cultivate the Ownership stage so that “Professional” franchisee can advance to the Renewal stage instead of retiring, Chen, Chong, and Justis (2000) suggest building an Intranet-based Franchising Knowledge Repository. The Repository provides a framework based on which a franchise system may transform into a learning organization. 4. Partnering with the “disruptive technology” providers to enhance the CSLC stages. Innovative entrepreneurs will reengineer their franchise businesses around the CSLC model shown in Table 1. Their ability to track, analyze, and leverage the buying behaviors of their customers in the CSLC sub-stages is their real competitive advantage. For example, Statability.com is a “visionary Web-based Reporting” portal for the hospitality industry. In terms of the CSLC model, Statability.com is a focused business which reengineers around the sub-stages of Ownership. Its “disruptive technology” of reporting is adopted by many franchises in the hospitality industry. As discussed earlier, partnering with those “disruptive technology” providers will make the franchise system more competitive.
ALIGNING THE CSLC-BASED E-BUSINESS STRATEGY WITH APPLICATION SERVICE PROVIDERS Although Internet technology can help deploy the franchise’s e-business strategy, the immediate question is: at what cost? Because of the need for e-business processes to monitor the linkage of internal information technologies with external
Renewal or Retirement
Ownership
Acquisition
Requirements
CSLC
Becoming a Professional Multiunit Franchisee or Retiring from the Franchise System
Building the Relationship between the Franchisor and the Franchisee
Cultivating the franchisor/franchisee relationship with effective knowledge management tools (Chen, Chong, Justis, 2000a,b; Chen, Hammerstein, and Justis, 2002; Chen, Seidman, and Justis, 2005), e.g., basic communications support, distance learning, and centralized franchise applications such as employee recruitment and online ordering
Partnering with suppliers to enhance the various stages of CSLC continuously (Chen, Justis, and Wu, 2006), e.g., a franchise system may need to partner with banks to deliver good services at the stage of “Financing the Franchise Business”. Aligning the Internet and Intranet Strategy with reputable Application Service Providers (ASP) having focused businesses reengineering around the stages of CSLC (Chen, Ford, Justis, and Chong, 2001). For example, Statability.com is a “visionary Web-based Reporting” portal for the hospitality industry. It has the focused business reengineering around the stage of “Managing the Franchise System”. Its focused service is being respected by franchise companies in the hospitality industry, as is evidenced from the ever-increasing list of its client base, including Hilton and Marriott.
Transforming the organizational structure and corporate culture to fit the e-business operation pushed by the Intranet systems (Zeng, Chen, and Huang, 2008), e.g., designing an environment for more team work opportunities and establishing e-learning environment for the employees
Managing the Franchise System
Extranet Strategy
Intranet Strategy
Helping the franchisees make sales and serve their customers with proper policies dealing with the Internet encroachment issues
Using the web site as the friendly customer relationship management tool to address customer concerns at various stages (Chen, Chong, and Justis, 2002), e.g., providing useful on financing and showing how the franchise system may help finance the franchise investment Benchmarking and enhancing the web site continuously (Chen, Chong, and Justis, 2002; Chen, Justis, and Chong, 2008), e.g., identifying frequently the best practices of web deign in the industry and improving the web site accordingly
Internet Strategy
Marketing & Promoting the Franchise Products or Services
Signing the Contract
Financing the Franchise Business
Preparing Business Plan
Making the Choice
Obtaining Franchisee Prospectus
Investigating Franchise Opportunities
Understanding How Franchising Works
Sub-stages
Table 1. The customer-service-life-cycle (CSLC) e-business strategy in franchising
E-Business Strategy in Franchising
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processing and services, the e-business investment could be very expensive and complicated. Many franchise companies, especially small ones, find it financially difficult to invest in the e-business technologies; however, a new type of service in e-business called Application Service Providers (ASP) promises to make e-business more economical and affordable to the franchise systems. The concept of subscribing information technologies through ASPs has special appeal in the franchising industry because an ASP can duplicate success for other similar franchises quickly and inexpensively (Chen, Ford, Justis, and Chong, 2001). When aligning the CSLC-based e-business strategy with ASPs, a franchise company should focus on (Chen, Ford, Justis, and Chong, 2001): 1. Develop an overall vision of the applications, including software and hardware, needed for the company. 2. Determine what applications and the specific services, e.g., to be available 24 hours a day and 7 days a week with 99.999% of reliability, you want an ASP to host, which have to be clearly defined in the Service Level Agreement. 3. Evaluate ASP providers, i.e., vendors who provide the applications services, using flexibility and trust relationship as the two primary factors.
FUTURE TRENDS: AN ATTENTIONBASED FRAMEWORK FOR THE FRANCHISEE TRAINING The third industrial revolution, combining information technology with globalization, produces an environment where everyone is facing the problem of information overload. Simon (1971) spoke for us all when he said that ‘a wealth of information creates a poverty of attention.” (p.41) Getting the franchisee’s attention on training in an information rich world is a major challenge. Ocasio (1997) pro-
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posed an attention-based theory of the firm, which allows the firm to shield off irrelevant information and gain access to information relevant to what the firm focuses on. According to Ocasio (1997), attention is defined to “encompass the noticing, encoding, interpreting, and focusing of time and effort by organizational decision-makers on both (a) issues: the available repertoire of categories for making sense of the environment: problems, opportunities, and threats; and (b) answers: the available repertoire of action alternatives: proposals, routines, projects, programs, and procedures.” (p.188) Ocasio (1997) further classifies attention into three principles: (1) focus of attention, what decision makers do primarily depends on the selective issues and answers they focus attention on; (2) situated attention, what decision makers focus on and do depends primarily on the particular contextual environment they are located in; and (3) structural distribution of attention, how decision makers attend to the particular contextual environment they are in depends on how the firm’s attention structure (including rules, resources, and relationships) channels and distributes various issues, answers, and decision makers into specific communications and procedures. In the context of franchising, what do focus of attention, situated attention, and attention structures look like? How does a franchise design an attention-based training program for the franchisees? We propose an attention-based framework in Table 2 for the franchisee training. Such a framework has two dimensions. The first dimension is the franchisee life cycle, consisting of Beginner in the Courting Phase, Novice in the “We”-Phase, Advanced in the “Me”-Phase, Master in the Rebel Phase (since the rebel ones tend to be those who know the system well and are capable of influencing others to follow them), and Professional in the Renewal Phase. It is vital for relationship building to understand which stage the franchisee is situated and allocate appropriate resources at different touch-points to help them perform their focuses of attention. The second
E-Business Strategy in Franchising
dimension is the demand-and-supply value networks (Chen, Justis, and Wu, 2006), the attention structures of the franchise, consisting of customers, franchisee outlet, franchisor headquarters, suppliers and partners, and franchise community. The main body of the framework is the focus of attention of the franchise of different levels.
CONCLUSION Franchising has been popular as a growth strategy for businesses; it is even more so in today’s global and e-commerce world (Chen, Chen, and Wu, 2005). The essence of franchising lies in managing the good relationship between the franchisor and the franchisee. In this paper we showed e-business strategy plays an important role in growing and nurturing such a good relationship. Specifically, we discussed: (1) managing the franchisor/franchisee relationship through the
Table 2. An attention-based framework for the franchisee training
Franchisee Life Cycle
Situated Attention: Relationship Touch-points
Attention Structures: Demand & Supply Value Networks Customers
Franchisee Outlet
Franchisor Headquarters
Suppliers & Partners
Franchise Community
Beginner in the Courting Phase: Beginner Guide
Focus of Attention: Learning how to become a franchisee €€€• Understanding how franchising works €€€• Investigating franchise opportunities €€€• Obtaining franchisee prospectus €€€• Making the choice €€€• Preparing business plan €€€• Financing the franchised business €€€• Signing the contract
Novice in the “We”-Phase: Practicing
Focus of Attention: Practicing how to do activities such as: €€€• How to get training and services from the headquarters €€€• How to find a good site €€€• How to find suppliers €€€• How to work with the franchisor €€€• How to work with fellow franchisees
Advanced in the “Me”-Phase: Doing
Focus of Attention: Doing activities such as: €€€• How to acquire and keep customers €€€• How to hire, train, and fire employees €€€• How to manage inventory €€€• How to manage the back office operations
Master in the Rebel Phase: Teaching Others
Focus of Attention: Teaching others how to do activities such as: €€€• How to teach others €€€• How to work as team €€€• How to do the bulleted processes above for Beginner, Novice, and Advanced franchisees
Professional in the Renewal Stage: Creative Learning and Innovation
Focus of Attention: Becoming the best he/she can be by: • Learning to creatively improve activities such as: €€€• How to cut the cost of the operations €€€• How to increase the profit of the operations €€€• How to acquire other franchises and brands • Looking for opportunities for innovation such as: €€€• Are there any new growth opportunities we can create based on our intangible assets of demand & supply value chains? How do we avoid the loss of this new venture? €€€• Are there any partnership opportunities with our customers and suppliers so that their customers could become ours and vice versa. €€€• What are the major concerns in the communities and how can we help to deal with them and build a good media relationship also?
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CSLC approach, where organizational learning is believed to be the key to building the good relationship; (2) harnessing the e-business strategy around the CSLC approach, where four major components are discussed: benchmarking the requirements and acquisition stages, helping the franchisees serve their customers in the ownership stage and avoiding Internet encroachment, cultivating the ownership and renewal/retirement stages with effective knowledge management, and partnering with the “disruptive technology” providers to enhance the CSLC stages continuously; and (3) aligning the CSLC-based e-business strategy with application service providers, where trust relationship is the major issue.
REFERENCES Chen, Y., Chen, G., & Wu, S. (2006). A Simonian Approach to E-business Research: A Study in Netchising. In Advanced Topics in E-Business Research: E-Business Innovation and Process Management, Vol. 1. Chen, Y., Chong, P., & Justis, R. T. (2000a). Information Technology Solutions to Increase Franchise Efficiency and Productivity. In Proceedings of the 2000 Franchise China Conference and Exhibition, Beijing (November 6-7), Guangzhou (November 9-10), and Shanghai (November 1314), China. Chen, Y., Chong, P., & Justis, R. T. (2000b). Franchising Knowledge Repository: A Structure for learning Organizations. In Proceedings of the 14th Annual International Society of Franchising Conference, San Diego, California, February 19-20. Chen, Y., Chong, P., & Justis, R. T. (2002). EBusiness Strategy in Franchising: A CustomerService-Life-Cycle Approach. In Proceedings of the 16th Annual International Society of Franchising Conference, Orlando, Florida, February 8-10.
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Chen, Y., Ford, C., Justis, R. T., & Chong, P. (2001). Application Service Providers (ASP) in Franchising: Opportunities and Issues. In Proceedings of the 15th Annual International Society of Franchising Conference, Las Vegas, Nevada, February 24-25. Chen, Y., Hammerstein, S., & Justis, R. T. (2002). Knowledge, learning, and capabilities in franchise organizations. In Proceedings of the 3rd European Conference on Organizational Knowledge, Learning, and Capabilities, Athens, Greece, April 5-6. Chen, Y., Justis, R., & Wu, S. (2006). Value networks in franchise organizations: A study in the senior care industry. In Proceedings of the 20th Annual International Society of Franchising Conference, Palm Springs, California, February 24-26. Chen, Y., & Justis, R. T. (2006). Chinese Franchise Brands Going Globalization. In 1st Annual China Franchise International Summit, International Franchise Academy, Zhuhai, China, November 9-11. Chen, Y., Justis, R. T., & Chong, P. P. (2008). Data mining in franchise organizations. In J. Wang (Ed.), Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications (pp. 2722-2733). Chen, Y., Justis, R. T., & Yang, H. L. (2004). Global E-Business, International Franchising, and Theory of Netchising: A Research Alliance of East and West. In Proceedings of the 18th Annual International Society of Franchising Conference, Las Vegas, Nevada, March 5-7. Chen, Y., Seidman, W., & Justis, R. T. (2005). Strategy and docility in franchise organizations. In the Proceedings of 19th Annual International Society of Franchising Conference, London, UK, May 20-22. Gates, B. (1999). Business @ the Speed of Thought: Succeeding in the Digital Economy. Clayton, Australia: Warner Books.
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Hadfield, B. (1995). Wealth Within Reach. St. Paul, MN: Cypress Publishing. Ives, B., & Mason, R. O. (1990). Can Information Technology Revitalize Your Customer Service? Academy of Management Executive, 4(4), 52–69. Justis, R. T., & Judd, R. J. (2002). Franchising. Cincinnati, OH: DAME Publishing. Justis, R. T., & Vincent, W. S. (2001). Achieving Wealth Through Franchising. Avon, MA: Adams Media Corporation. Ocasio, W. (1997). Towards an attentionbased view of the firm. Strategic Management Journal, 18, 187. doi:10.1002/ (SICI)1097-0266(199707)18:1+3.3.CO;2-B Schreuder, A. N., Krige, L., & Parker, E. (2000). The Franchisee Lifecycle Concept – A New Paradigm in Managing the Franchisee-Franchisor Relationship. In Proceedings of the 14th annual International Society of Franchising Conference, San Diego, California, February 19-20. Simon, H. A. (1971). Designing organizations for an information rich world. In M. Greeberger (Ed.), Computers, Communications, and the Public Interest (pp. 38-52). Baltimore, MD: The Johns Hopkins Press. Thomas, D., & Seid, M. (2000). Franchising for Dummies. Boston: IDG Books. U.S. Commercial Service. (2008 April). China Franchising Industry. Beijing, China: The JLJ Group.
Zeng, Q., Chen, W., & Huang, L. (2008). E-Business Transformation: An Analysis Framework Based on Critical Organizational Dimensions. Journal of Tsinghua Science and Technology, 13(3), 408–413. doi:10.1016/S10070214(08)70065-8
KEY TERMS AND DEFINITIONS Customer Service Life Cycle: Serving customers based on a process of four stages: Requirements, Acquisition, Ownership, and Retirement. Many companies are using the approach to harness the Internet to serve the customers. Franchising: A business opportunity based on granting the business rights and collecting royalties in return. Franchisor: The individual or business who grants the business rights. Franchisee: The individual or business who receives the business rights and pay the royalties for using the rights. Franchisor/Franchisee Learning Process: The stages of learning, including Beginner, Novice, Advanced, Master, and Professional. Franchisee Life Cycle: The stages a franchisee goes through in the franchise system: Courting, “We”, “Me”, Rebel, Renewal. Franchisor/Franchisee Relationship Management: The vital factor for the success of a franchise, including: Knowledge, Attitude, Motivation, Individual Behavior, and Group Behavior.
This work was previously published in Encyclopedia of E-Business Development and Management in the Global Economy, edited by In Lee, pp. 316-324, copyright 2010 by Business Science Reference (an imprint of IGI Global).
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Chapter 1.5
E-Business Strategy and Firm Performance Jing Quan Perdue School of Business, USA
ABSTRACT Electronic business (e-business) has been popularly lauded as “new economy.” As a result, firms are prompted to invest heavily in e-business related activities such as supplier/procurement and online exchanges. Whether the investments have actually paid off for the firms remain largely unknown. Using the data on the top 100 e-business leaders compiled by InternetWeek, this chapter compares the leaders with their comparable counterparts in terms of profitability and cost in both short-run and long-run. The authors find that while the leaders have superior performance based on most DOI: 10.4018/978-1-60960-587-2.ch105
of the profitability measurements, such superiority is not observed when cost measurements are used. Based on the findings, this chapter offers managerial implications accordingly.
INTRODUCTION The rapid expansion of e-business we witnessed in the late 1990s was nothing short of a spectacle. It seemed that almost everyone was talking about it, and every firm was eager to invest in it, hoping to take away a slice of the pie. Andy Grove, Chairman of Intel Corp, stated in 1998: “Within 5 years, all companies will be internet companies or they would not be companies.” (Intel, 2000).
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E-Business Strategy and Firm Performance
Merely mentioning of the “e” word could mean multi-million dollars. The case at hand was Zapata Corp, a fish oil processing company, co-founded by former US President George H. W. Bush. The company announced on December 23, 1998 that it would transform itself into an internet portal to compete with Yahoo!, Lycos and alike. Immediately following the announcement, Zapata’s stock price skyrocketed nearly 100% from 7.19 to 14.25 with trading volume at more than 2,000% higher than normal, according to Yahoo! Finance. Academic researchers rushed in and concluded that “a new economy was born.” The potential benefits of e-business are well documented by academic researchers and practitioners alike (InternetWeek 2000/2001; Phan, 2003). Organizations that integrate e-business applications, such as shared online database and internet-based reporting in their business processes, can lead to reduced cost, increased efficiency and profitability, and better customer relationship management. Perhaps, one of the most significant contributions of e-business applications is its abilities to directly bring sellers and buyers together with little middleman’s interventions. Although the advantages of e-business exist in theory, little empirical work has been done to confirm them. Some study actually showed an inconclusive link between e-business and sustainable development (Digital Europe, 2003, p.1): Our survey showed no conclusive evidence for companies that use a lot of e-business actually performing better than other companies on sustainable development, simply by virtue of their e-business use. There may be a relationship here - which could become more obvious as e-business applications are more fully integrated into companies’ operations - but more research would be needed to prove a link. Answering this call, researchers have attempted to build theoretical frameworks to pinpoint how e-business creates value. Using the technology-
organization-environment (TOE) framework Zhu, Kraemer, Xu, and Dedrick (2004) found that technology readiness, firm size, global scope, financial resources, competition intensity, and regulatory environment may affect e-business value creation. Amit and Zott (2001) integrated several theoretical perspectives on entrepreneurship and strategic management to identify four interdependent dimensions: efficiency, complementarities, lock-in, and novelty as sources of value creation. Despite the recent advancement of research in this area, the fundamental question regarding e-business remains unanswered, i.e., whether ebusiness creates value. This paper attempts to fill this vacuum by establishing a theoretical foundation to evaluating the linkage between e-business investments and firm performance in terms of profitability and cost savings. Confirmation or disconfirmation of the effectiveness of firms’ investments in e-business will contribute to the knowledge accumulation in this area. It can also provide an insight for future investments. We begin the paper by presenting our research framework grounded in the resource-based view (Barney, 1986; Barney, 1991; Conner, 1991; Rumelt, 1984). Resource-based view argues that firm-specific skills and resources that are rare and difficult to imitate or substitute are the main drivers of firm performance. We show how e-business initiatives create unique skills and resources for firms. Then we formulate our hypotheses, discuss the data set and methodology, and present estimation results. Finally, we provide discussion of the results and suggestions for future research.
RESEARCH FRAMEWORK: THE RESOURCE-BASED VIEW Broadly speaking, e-business value is a subset of the business value of IT. The business value of IT investments in general has been long debated, which led to the birth of the famous term “productivity paradox.” Some studies provide posi-
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tive support for the business value of computer investments (Brynjolfsson 1993; Brynjolfsson and Hitt 1996; Hitt and Brynjolfsson 1996; Bharadwaj 2000; Stratopoulos and Dehning 2000). On the other hand, Strassmann (1997) argues that IT investments have no discernible effects on firm profitability measured in return on assets (ROA), return on equity (ROE), and economic value added (EVA). In an attempt to explain the inconclusiveness, some researchers propose several theoretical models that examine the entire process needed for IT investments to make an impact on business value (Lucas 1993; Markus and Soh 1993). One of the dominate views is the resource-based view (RBV). Based on this view, IT investment itself does not provide any sustainable value because competitors can easily duplicate the investment by purchasing the same hardware and software. Rather, competitive advantages are derived from the manner in which firms deploy IT to generate a unique set of resources and skills that are difficult to duplicate (Clemons 1986, 1991; Clemons and Row 1991; Mata et al. 1995). This type of resources is firm specific, rare, imperfectly imitable, and not strategically substitutable by others create competitive advantages for firms (Barney, 1991). Grant (1991) extends the RBV by linking resources to organizational capabilities. Firms generate organizational capabilities by optimally assembling their resources. When these capacities are embedded in organizational processes, it makes firms deploy resources more effectively and efficiently than its competitors. In turn, competitive advantages are created. Adopting this RBV, one can see that IT investments themselves do not necessarily generate sustained value because competitors can easily duplicate the action by investing in the same or equivalent hardware and software. In order to achieve competitive advantages of IT investments, firms must leverage their investments (resources) to create unique capacities that impact their overall effectiveness.
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E-BUSINESS AND COMPETITIVE ADVANTAGE Information systems researchers have classified key IT-based resources into three categories: (1) the physical IT infrastructure (the tangible resources); (2) the technical and managerial IT skills (the human resources); and (3) the intangible resources such as knowledge base, customer relations, and synergy (Bharadwaj, 2000; Grant, 1995). To be successful, e-business based firms need to invest in a new type of IT infrastructure that can provide real time responses 24/7 to customer inquiries. Some emerging infrastructures include XML, server farms, and dynamic storage. In addition, to protect the infrastructures and ensure the integrity of information, firms need to heavily invest in security. All these require IT and management staff to possess necessary skills for managing the new working environment. This allows the firms to acquire unique, rare and firm specific technical and managerial skills. With the infrastructure and management skills in place, the firms can manage their knowledge base better and create synergies between different working units. In the process, they can become truly customer oriented. Therefore, from the resource-based perspective, e-business initiatives help firms to obtain competitive advantage in the marketplace. In this paper, we measure competitive advantage in terms of either higher profit or lower cost. As a result, we propose the following hypotheses: H1:The average profit ratios of the e-business leader firms are higher than those of the non-leaders. H2:The average cost ratios of the e-business leader firms are lower than those of the non-leaders.
METHODOLOGY We adopt the “matched sample comparison group” method, which has been extensively used in previ-
E-Business Strategy and Firm Performance
ous research (Bharadwaj, 2000, Stratopoulos and Dehning 2000). In this methodology, there are two samples: the first sample is a treatment group and the second is a carefully selected control group that is matched to the treatment group by size and type. Then the levels of interest variables of these two samples are compared. In our case, the treatment group consists of the firms identified by the industry as e-business leaders while the control group consists of the matched firms in terms of size and type.
Dataset In 2000 and 2001 InternetWeek published a special issue InternetWeek 100, in which 100 e-business leaders were identified for their effectiveness in using internet to achieve tangible business benefits (InternetWeek, 2000/2001). They were evaluated based on their e-business participation in customer-oriented activities, supplier/procurement activities, electronic marketplace, integration of front- and back-end systems, revenue growth, and cost cutting efforts. In order to obtain a consistent sample, we restricted the selection of the companies that were identified as leaders in both years. In addition, firms must have complete financial data on Compustat for the period of 1999 to 2002. This process led to 46 companies in the treatment sample. For the control sample, we first specified that a matching firm must be in the same industry as the leader based on the 4-digit primary Standard Industrial Classification (SIC) code. Second, the average sales of the matching firm must be within 70% to 130% of the leader firm’s. When there were multiple matches, the firm with five-year average sales closest to that of the leader firm was selected. If a match couldn’t be identified in this fashion, then the 4-digit SIC matching rule was relaxed to three- or two-digit SIC. This procedure has been used by previous studies such as Bharadwaj (2000) and Barber and Lyon (1996). Firms in both groups are listed in the Appendix.
Table 1 provides the descriptive statistics for the two groups. The t-test does not reveal any systematical differences between them in terms of size measures such as sales, total assets and number of employees. Two categories of variables are collected for both treatment and control samples to test the aforementioned two hypotheses related to profit and cost. Five profit ratios include return on assets (ROA), return on sales (ROS), operating income to assets (OI/A), operating income to sales (OI/S), and operating income to employee (OI/E). Three cost ratios are total operating expenses to sales (OEXP/S), cost of goods sold to sales (COGS/S), and selling and general administrative expenses to sales (SG&A/S). Total operating expenses are defined as the sum of COGS and SG&A. The rational for those variables can be found in Bharadwaj (2000).
Statistical Tests and Outliers Our primary interest is to test the hypotheses that the mean levels of operational performance variables of e-business leaders are better than those of non-leader firms. Traditional standard t-test would be used for this purpose. However, since the distributions of financial ratios, such as the variables defined above, tend to be nonnormal, skewed and fat tailed, non-parametric test is preferred (Bharadwaj, 2000; Stratopoulos and Dehning, 2000). In this paper, we use the Wilcoxon signed rank test. Another characteristic of financial data is that there are a significant number of outliers. As a data treatment, we followed a methodology suggested by Stratopoulos and Dehning (2000) by removing those data points that fall more than 1.5 times the interquartile range above the third quartile or below the first,.
59
E-Business Strategy and Firm Performance
Table 1. Descriptive statistics 1999
E-Business Leaders
Control Sample
Mean
Mean
Median
Difference of Means Median
T
Sales (billion $)
20.84
11.27
18.56
10.28
1.326
Assets (billion $)
45.61
16.54
35.72
12.74
1.103
Number of Employees
82348
45504
120931
54450
-0.859
Median
T
2000
E-Business Leaders
Control Sample
Mean
Mean
Median
Difference of Means
Sales (billion $)
23.05
12.26
20.78
11.42
1.207
Assets (billion $)
57.17
20.49
41.96
13.02
1.474
Number of Employees
89888
44000
121425
46546
-0.900
2001 Sales (billion $)
E-Business Leaders
Control Sample
Mean
Median
Mean
Median
T
Difference of Means
21.69
12.81
20.72
11.33
0.531
Assets (billion $)
56.52
20.25
44.80
13.71
1.115
Number of Employees
85435
46800
121199
62175
-1.175
2002 Sales (billion $)
E-Business Leaders
Control Sample
Mean
Median
Mean
Median
T
Difference of Means
21.66
11.92
20.38
11.45
0.605
Assets (billion $)
59.08
19.50
48.47
13.79
0.922
Number of Employees
83961
47480
101336
44323
-1.315
RESULTS AND DISCUSSION Table 2 provides the one-sided Wilcoxon signed rank results for the aforementioned profitability related variables between e-business leaders and control sample from 1999 and 2002. E-business leaders performed better in terms of all measures but one (OIE) in 1999, the year before they were identified as e-business leaders. This indicates that financial performance was one of the considerations for their selections. Most of the advantages were maintained in 2000, except for ROA, while the leaders now performed better based on the OIE measurement. In 2001, however, there were no significant differences between the leaders and matched firms in all financial variables. In the last year of our sample, e-business leaders performed better than the control sample in terms of three out of 5 financial ratios. Based on the discussion
60
above, we can conclude that overall our hypothesis #1 is partially supported. Table 3 provides the one-sided Wilcoxon signed rank test results for the aforementioned cost related variables between the e-business leaders and the control sample from 1999 and 2002. Throughout all these years there were no significant differences between the leaders and the matched firms. This finding is largely consistent with other studies such as Bharadwaj (2000), and Mitra and Chaya (1996). Based on the results, we conclude that our hypothesis #2 is not supported.
CONCLUSION As businesses rushed to invest in the “new” economy, pressured by either the thinking of a
E-Business Strategy and Firm Performance
Table 2. E-business and profitability 1999 Mean ROAleaders ROAcontrol ROSleaders ROScontrol OIAleaders OIAcontrol OISleaders OIS-control OIEleaders OIE-control
Median
5.145
4.508
3.876
2.726
0.076
0.067
0.051
0.045
0.112
0.092
0.085
0.068
0.136
0.121
0.104
0.089
0.033
0.025
0.027
0.018
2000 Pr>Z 0.06c
0.01
a
0.02
b
0.01
b
0.18
Mean
Median
5.327
3.810
4.067
3.457
0.066
0.070
0.052
0.049
0.097
0.089
0.067
0.064
0.132
0.121
0.095
0.085
0.042
0.032
0.024
0.016
2001 Pr>Z 0.31
0.04
b
0.02
b
0.01
a
0.01a
Mean
Median
2.789
1.659
1.452
1.513
0.052
0.043
0.020
0.032
0.076
0.064
0.059
0.049
0.088
0.079
0.092
0.068
0.028
0.023
0.023
0.011
2002 Pr>Z 0.22
0.10
c
0.12
0.32
0.21
Mean
Median
3.126
2.892
1.384
2.031
0.029
0.032
0.021
0.032
0.068
0.069
0.045
0.046
0.096
0.104
0.074
0.069
0.027
0.021
0.021
0.014
Pr>Z 0.02b
0.49
0.02b
0.05b
0.33
Notes: a 1% level, b 5% level, c 10% level ROA - return on assets; ROS – return on sales; OIA – operating income to assets; OIS – operating income to sales; OIE – operating income to employees.
Table 3. E-business and cost 1999 Mean COG/Sleaders COG/S-control SGA/Sleaders SGA/S-control OPEXP/Sleaders OPEXP/Scontrol
Median
0.650
0.699
0.653
0.669
0.230
0.228
0.237
0.214
1.086
0.788
1.223
1.301
2000 Pr>Z 0.49
0.37
0.13
Mean
Median
0.638
0.683
0.644
0.650
0.236
0.233
0.236
0.238
1.227
0.952
1.175
1.234
2001 Pr>Z 0.42
0.49
0.33
Mean
Median
0.690
0.708
0.670
0.683
0.245
0.232
0.243
0.237
1.208
0.956
1.229
1.316
2002 Pr>Z 0.80
0.59
0.25
Mean
Median
0.656
0.659
0.679
0.683
0.240
0.224
0.254
0.230
1.263
1.238
0.909
1.315
Pr>Z 0.46
0.32
0.22
Notes: COG/S – cost of goods sold to sales; SGA/S – selling and general administration expense to sales; OPEXP/S – operating expenses to sales.
61
E-Business Strategy and Firm Performance
paradigm swift or peers during the internet boom, the payoff of such investments was not as important as making the move or taking action. Now that the bubble has burst, companies are forced to focus once again to justifying their IT investment decisions. This study aims to provide an assessment whether the investments made in e-business during the boom period had actually paid off in terms of profitability and cost in both short- and long-runs. Using the e-business leaders identified by InternetWeek, we created a control sample that matched the leaders based on industry type and size. The performances, measured in profit and cost, of these two groups were compared using the Wilcoxon signed rank non-parameter test. The results indicate that in terms of profitability e-business leaders performed better than the control sample in the long-run but the superior performance fluctuated in the short-run. In terms of cost, there were no significant differences between the leaders and the control sample in both the short- and long-runs. The combination of leaders’ higher profitability than and the same cost measures as the firms in the control sample is consistent with the observation by Bharadwaj (2000, p187) that “IT leaders do not necessarily have a cost focus, but tend to exploit IT for generating superior revenues.” Based on the findings in this study, we suggest that management should be very clear about the time horizon of the e-business, or IT in general, investments. The findings of this study demonstrate that the consistent superior financial performances of the e-business leaders are only observed in the long-run. In reality, management often fails to see the long-run benefits from new IT investments due to the cost concerns of new IT in the short-run. Dehning et al. (2005) suggest that management should take a long-term view because IT might allow a firm to form relationships with its customers and suppliers and reduce variability in cash flows and earning. The combined effect of such interactions between the other variables may
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easily make up for the temporary increase in cost and decline in competitive advantage. This type of research using a third party ranking suffers a few limitations, such as causality, indirectness of measurements, inherent biases of leader firms, the selection of the control sample, as suggested by Bharadwaj (2000) and Stratopoulos and Dehning (2000). Those limitations may serve as the directions for future research. Santhanam and Hartono (2003) suggest a different way of selecting the control sample. Instead of choosing a single benchmark firm for each e-business leader, one can consider all the firms in that industry for comparison. They argue that this method is more consistent with the procedure of selecting leaders, robust and general. Future research can consider adopting this approach of sample selection. Another logical follow-up study would be to extend the period beyond 2002 to examine the impact of e-business investment in the long term.
REFERENCES Amit, R., & Zott, C. (2001). Value creation in e-business. Strategic Management Journal, 22, 493–520. doi:10.1002/smj.187 Barber, B. M., & Lyon, J. D. (1996). Detecting abnormal operating performance: the empirical power and specification of test statistics. Journal of Financial Economics, 41, 359–399. doi:10.1016/0304-405X(96)84701-5 Barney, J. B. (1986). Strategic factor markets: expectations, luck, and business strategy. Management Science, 32, 1231–1241. doi:10.1287/ mnsc.32.10.1231 Barney, J. B. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17, 99–120. doi:10.1177/014920639101700108
E-Business Strategy and Firm Performance
Barua, A., & Kriebel, C.H. & Mukhopadhyay. (1995). Information technologies and business value: an empirical investigation. Information Systems Research, 6(1), 3–23. doi:10.1287/isre.6.1.3 Bharadwaj, A. S. (2000). A resourced-based perspective on information technology capability and firm performance: an empirical investigation. MIS Quarterly, 24(1), 169–196. doi:10.2307/3250983 Brynjolfsson, E. (1993). The productivity paradox of information technology. Communications of the ACM, 36(12), 67–77. doi:10.1145/163298.163309 Brynjolfsson, E., & Hitt, L. (1996). Paradox lost? Firm-level evidence on the return to information systems spending. Management Science, 42(4), 541–558. doi:10.1287/mnsc.42.4.541 Clemons, E. K. (1986). Information systems for sustainable competitive advantage. Information & Management, 11(3), 131–136. doi:10.1016/03787206(86)90010-8 Clemons, E. K. (1991). Corporate strategy for information technology: a resource-based approach. Computer, 24(11), 23–32. doi:10.1109/2.116848 Clemons, E. K., & Row, M. C. (1991). Sustaining IT advantage: the role of structural differences. MIS Quarterly, 15(3), 275–294. doi:10.2307/249639 Conner, K. R. (1991). A historical comparison of the resource-based theory and five schools of thought within industrial organization economics: do I have a new theory of the firm? Journal of Management, 17(1), 121–154. doi:10.1177/014920639101700109 Dehning, B., Richardson, V. J., & Stratopoulos, T. (2005). Information technology investments and firm value. Information & Management, 42(7), 989–1008. doi:10.1016/j.im.2004.11.003 Digital Europe (2003). Is ebusiness good business? Survey key findings, May, DEESD IST2000-28606
Grant, R. M. (1991). The resource-based theory of competitive advantage. California Management Review, 33(3), 114–135. Grant, R. M. (1995). Contemporary Strategy Analysis. Oxford, UK: Blackwell Publishers, Inc. Hitt, L. M., & Brynjofsson, E. (1996). Productivity, business profitability, and consumer surplus: three different measures of information technology value. MIS Quarterly, 20(2), 121–142. doi:10.2307/249475 Intel (2000). Retrieved January 23, 2004 from http://www.intel.com/ebusiness/estrategies/ enabling/ InternetWeek. (2000). InternetWeek 100, Special Issue, June 8. http://internetweek.cmp. com/100/100-00.htm. Retrieved on February 18, 2004. InternetWeek. (2001), InternetWeek 100, Special Issue, June 11. http://internetweek.cmp. com/100/100-01.htm. Retrieved on February 18, 2004. Lucas, H. C. (1993). The business value of information technology: a historical perspective and thoughts for future research, in strategic information technology management: perspectives on organizational growth and competitive advantage. In R. Banker, R. Kauffman, and M.A. Mahmood (Eds.), Strategic Information Technology Management: Perspectives on Organizational Growth and Competitive Advantage. Hershey, PA: Idea Group Publishing. Markus, M. L., & Soh, C. (1993). Banking on information technology: converting it spending into firm performance. In R. Banker, R. Kauffman, and M.A. Mahmood (Eds.), Strategic Information Technology Management: Perspectives on Organizational Growth and Competitive Advantage. Hershey, PA: Idea Group Publishing.
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Mata, F. J., Fuerst, W. L., & Barney, J. B. (1995). Information technology and sustained competitive advantage: a resource-based analysis. MIS Quarterly, 19(4), 487–505. doi:10.2307/249630 Mitra, S., & Chaya, A. K. (1996). Analyzing cost effectiveness of organizations: the impact of information technology spending. Journal of Management Information Systems, 13(2), 29–57. Phan, D. D. (2003). E-business development for competitive advantages: a case study. Information & Management, 40(6), 581–590. doi:10.1016/ S0378-7206(02)00089-7 Rumelt, R. P. (1984). Toward a strategic theory of the firm. In R. Lamb (Ed.), Competitive strategic management (pp. 556-570). Englewood Cliffs, NJ: Prentice-Hall.
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Santhanam, R., & Hartono, E. (2003). Issues in linking information technology capability to firm performance. MIS Quarterly, 27(1), 125–153. Strassmann, P.A. (1997, September 15) Computers have yet to make companies more productive. ComputerWorld. Stratopoulos, T., & Dehning, B. (2000). Does successful investment in information technology solve the productivity paradox? Information & Management, 38(2), 103–117. doi:10.1016/ S0378-7206(00)00058-6 Zhu, K., Kraemer, K. L., Xu, S., & Dedrick, J. (2004). Information technology payoff in e-business environment: an international perspective on value creation of e-business in the financial service industry. Journal of Management Information Systems, 21(1), 17–54.
E-Business Strategy and Firm Performance
APPENDIX Table 4. E-business leader firms and matched sample E-Business Leaders
SIC
Control Sample
SIC
ANHEUSER-BUSCH COS INC
2082
KIRIN BREWERY LTD -ADR
2082
MILLER (HERMAN) INC
2520
HON INDUSTRIES
2522
KIMBERLY-CLARK CORP
2621
3M CO
2670
KNIGHT-RIDDER INC
2711
AMERICAN GREETINGS -CL A
2771
AIR PRODUCTS & CHEMICALS INC
2810
ROHM & HAAS CO
2821
DU PONT (E I) DE NEMOURS
2820
BAYER A G -SPON ADR
2800
DOW CHEMICAL
2821
AVENTIS SA -ADR
2834
EASTMAN CHEMICAL CO
2821
PRAXAIR INC
2810
BRISTOL MYERS SQUIBB
2834
ABBOTT LABORATORIES
2834
AVON PRODUCTS
2844
LAUDER ESTEE COS INC -CL A
2844
PPG INDUSTRIES INC
2851
COLGATE-PALMOLIVE CO
2844
GILLETTE CO
3420
CROWN HOLDINGS INC
3411
CISCO SYSTEMS INC
3576
SUN MICROSYSTEMS INC
3571
EMERSON ELECTRIC CO
3600
ELECTROLUX AB -ADR
3630
AMERICAN PWR CNVRSION
3620
ALTERA CORP
3674
WHIRLPOOL CORP
3630
KYOCERA CORP -ADR
3663
NORTEL NETWORKS CORP
3661
ERICSSON (L M) TEL -ADR
3663
INTEL CORP
3674
MOTOROLA INC
3663
DAIMLERCHRYSLER AG
3711
FORD MOTOR CO
3711
RAYTHEON CO
3812
NORTHROP GRUMMAN CORP
3812
CSX CORP
4011
NORFOLK SOUTHERN CORP
4011
UNION PACIFIC CORP
4011
BURLINGTON NORTHERN SANTA FE
4011
UNITED PARCEL SERVICE INC
4210
UNITED STATES POSTAL SERVICE
4210
CONSOLIDATED FREIGHTWAYS CP
4213
YELLOW CORP
4213
ALASKA AIR GROUP INC
4512
AMERICA WEST HLDG CP -CL B
4512
AMR CORP/DE
4512
BRITISH AIRWAYS PLC -ADR
4512
DELTA AIR LINES INC
4512
NORTHWEST AIRLINES CORP
4512
AT&T CORP
4813
DEUTSCHE TELEKOM AG -SP ADR
4813
COX COMMUNICATIONS -CL A
4841
BRITISH SKY BRDCSTG GP -ADR
4833
ARROW ELECTRONICS INC
5065
GENUINE PARTS CO
5013
AVNET INC
5065
TECH DATA CORP
5045
PENNEY (J C) CO
5311
TARGET CORP
5331
SEARS ROEBUCK & CO
5311
KMART HOLDING CORP
5331
OFFICE DEPOT INC
5940
TOYS R US INC
5945
STAPLES INC
5940
RITE AID CORP
5912
J P MORGAN CHASE & CO
6020
CITICORP
6020
MELLON FINANCIAL CORP
6020
BANCO COMERCIAL PORTGE -ADR
6020
continues on following page 65
E-Business Strategy and Firm Performance
Table 4. continued E-Business Leaders
SIC
Control Sample
SIC
SCHWAB (CHARLES) CORP
6211
BEAR STEARNS COMPANIES INC
6211
HARTFORD FINL SVCS GRP INC
6331
MILLEA HOLDINGS INC -ADR
6331
HILTON HOTELS CORP
7011
STARWOOD HOTELS&RESORTS WLD
7011
MARRIOTT INTL INC
7011
INTERCONTINENTAL HOTELS -ADR
7011
INTL BUSINESS MACHINES CORP
7370
FUJITSU LTD -SPON ADR
7373
COMPUTER ASSOCIATES INTL INC
7372
KELLY SERVICES INC -CL A
7363
MICROSOFT CORP
7372
ADECCO S A -SPON ADR
7363
GENERAL ELECTRIC CO
9997
SIEMENS A G -SPON ADR
9997
This work was previously published in Technological Advancement in Developed and Developing Countries: Discoveries in Global Information Management, edited by M. Gordon Hunter and Felix B. Tan, pp. 389-399, copyright 2010 by Information Science Reference (an imprint of IGI Global).
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Chapter 1.6
Conservation of Information and e-Business Success and Challenges: A Case Study Huilien Tung Auburn University, USA Hsiang-Jui Kung Georgia Southern University, USA Désirée S. Lawless Woodward, USA Donald A. Sofge Naval Research Laboratory, USA William F. Lawless Paine College, USA
ABSTRACT Guided by the authors’ theory of the (COI), which holds that the transformation pairs of information uncertainty between time and frequency remain DOI: 10.4018/978-1-60960-587-2.ch106
constant (or alternately uncertainty for geospatial position and spatial frequency), they describe a case study on an international corporation based in Taiwan to demonstrate COI factors associated with the challenges and successes in the adoptions of e-business by the firm and by small and medium size enterprises in general.
Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
Conservation of Information and e-Business Success and Challenges
BACKGROUND e-Business is business exchanges on the Internet which utilize information and communication technologies to support business activities and processes. Beside regular selling and buying transactions, web-based customer service and collaboration with business partners are central components of e-Business. Web applications are the glue joining Information Technology (IT) infrastructure with the business processes that e-Business services deliver to constituents. Reviewing web applications over the past ten years, scholars agree that more features are offered every year, producing more complexity as web design methods and technologies advance (Kung, Tung & Case, 2007). However, a Standish Group (2002) survey on web applications development shows that 84 percent of development projects do not meet business needs, 56 percent do not have the required functionality, 79 percent are behind schedule, and 63 percent are over budget. These challenges are especially hard on small to medium sized businesses. We will use theory and a case study to discuss the challenges and successes that e-Business organizations face from ever evolving technologies, different e-business process requirements, different e-platforms, and different e-infrastructures.
THEORY We review the state of interdependence theory and the evidence in support of it. This section engages in mathematical modeling. Whenever possible, we will summarize the results to minimize the need by readers for mathematics to better understand the material. In fact, the conclusion to draw is that understanding is a byproduct of a strongly independent worldview; an interdependent worldview, should one exist, precludes the existence of a “single understanding” or “situational analysis”. Instead, the conclusion is that in an interdependent
68
world, single perspectives or worldviews reflect human and cultural tradeoffs coupled to a residual, irreducible level of uncertainty. A single perspective in isolation is static, but two together, existing in a state of interdependence (ι), can produce a potent dynamic. What follows is our approach to a theory of ι. In sum, dynamics are the result of competitive behaviors represented by the existence of two mutually incommensurable view points (Republicans and Democrats; conservatives and liberals; market economists and socialists; etc.). These polar opposite views serve many key but seldomly appreciated functions in society: Under conflict, we learn better (Dietz et al., 2003); we make better political decisions (e.g., Coleman, 2003); and we make better economic decisions (Hayek, 1944). But how can this conflict be modeled? And what relationship can be established to winning and losing across social, political or market landscapes? A Hilbert Space (HS) is an abstract space defined so that vector positions and angles permit the calculations of distance, reflection, rotation and geospatial measurements, or subspaces with local convergences where these measurements can occur. That would allow real-time determinations of the situated, shared situational awareness in localizing the center of a target organization, σx-COG, to represent the shared uncertainty in social-psychological-geospatial terms, and σk to similarly represent the spatial frequencies of an organization’s patterns displayed across physical space (e.g., the mapping of social-psychological or organizational spaces to physical networks). It would establish an “oscillation” between two socio-psycho-geospatial operators A and B such that [A,B] = AB - BA =iC ≠ [B,A].
(1)
This type of an oscillation defines a social-psychological decision space within an organization. It is called an “oscillator” because decision-making
Conservation of Information and e-Business Success and Challenges
occurs during rapid-fire turn-taking sessions driven by big self-interests that “rotate” attention for the topic under discussion in the minds of listeners or deciders first in one valence direction (e.g., “endorsing” a proposition) followed by the opposite (e.g., “rejecting” a proposition) to produce a “rocking” or back and forth process, like an organizational or social-psychological harmonic oscillator (SPHO) within an organization, or like the merger and acquisition (M&A) negotiations between a hostile predator organization and its prey target. But these oscillations may not occur in the minds of the agents who are driving the discussion (e.g., oscillation occurs in the minds of neutral jury members as first a prosecutor’s case is presented to them followed by a defense attorney’s case, but specifically not in the partisan minds of the prosecutor or defense attorney, unless they are seeking a compromise; or not in the minds of a predator organization competing for its prey M&A target organization but more likely in the observers more neutral to the M&A process yet who are not neutral to making a profit; in Lawless et al., 2009). A democratic space could be defined as a space where decisions characterized by SPHOs are made by majority rule (e.g., jury, political, or faculty decisions); the lack of an SPHO identifies decisions made by minority (consensus) or authoritarian rules (e.g., decisions where countervailing views are suppressed, as in common to military, authoritarian government or CEO business decisions; Lawless et al., 2007). The key to building the abstract representations necessary to construct an SPHO may be to locate opposing clusters of the shared interpretations of concepts geospatially across physical space or via a socio-psychological network anchored or mapped to physical network space. SPHOs should generalize to entertainment or stories. Similar to a decision process involving drivers and neutrals, we propose that a story or stage production, as found by Hasson and his colleagues (2004) in their study of inter-subjectivity among viewers
of a Clint Eastwood movie, engages and holds an audience’s attention with this rocking process. SPHO rocking produces fluctuations that produce information characteristic of an organization’s stability response. This insight suggests that the reverse engineering of terrorist organizations may be possible (Lawless et al., 2007). The operators A and B are community interaction matrices that locate social objects interdependently,ι, in social space (shared conceptual space) that are in turn separately anchored (embedded or situated) in geospatial or physical space. ι states are non-separable and non-classical; disturbances collapse ι states into classical information states. Two agents, one as an web-based firm’s President and the second as the Chief Technology Officer (CTO), meet in the President’s office, the choice of seating location reflecting the relative social power of the President over the subordinate CTO, but the CTO holding a skill set required by the organization that permits the two to negotiate while both are aware of their different functions and relative social ranks in the organization (Ambrose, 2001), generating bistable social perspectives that reflect the separate social constituencies that drive compromises (Wood et al., 2009); e.g., in contrast to the gridlock in the Department of Energy’s (DOE) Hanford cleanup driven by its consensus-ruled Citizens Advisory Board (CAB) where compromises can be easily blocked, compromises made by the majorityruled DOE Savannah River Site (SRS) CAB have accelerated environmental remediation at SRS (Lawless et al., 2008). Per Bohr (1955), complementarity actors and observers and incommensurable cultures generate conjugate or bistable information couples that he and Heisenberg (1958) suggested paralleled the uncertainty principle at the atomic level. We have built a model to test their speculation and to extend it to role conflicts (Lawless et al., 2009). But even for mundane social interactions, Carley (2002) concluded that humans became social to reduce uncertainty. Thus, the information avail-
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Conservation of Information and e-Business Success and Challenges
able to any human is incomplete, producing uncertainty. More importantly, this uncertainty has a minimum irreducibility that promotes the existence of tradeoffs between any two factors in an interaction (uncertainty in worldviews, stories or business models, ∆WV, and their execution, ∆v; uncertainty in centers of gravity ∆xCOG and spatial frequencies, ∆k; and uncertainty in energy, ∆E, and time, ∆t). The uncertainty in these oscillations can be reformulated1 to establish that Fourier pairs, consisting of standard deviations, are equal to: σAσ B> ½
(2)
Equation (2) indicates that as variance in factor A broadens, variance in factor B narrows. To summarize, a model of interdependence in the interaction or organizations must be able to: 1. Reflect orthogonal perspectives (i.e., Nash equilibriums; cf. Luce & Raiffa, 1967); e.g., between prosecutors and defense attorneys (Busemeyer & Trueblood, 2009); between actions and observations or between multiple cultures (Bohr, 1955); between USAF combat fighter jet pilots and book-knowledge of air combat maneuvering (Lawless et al., 2000); between game-theory preferences and actual choices made during games (Kelley, 1992); and to capture the discrepancy between the views of managers and the decisions made by their organizations (Bloom et al., 2007). 2. Allow rotation vectors as a function of the direction of rotation. Permit measurements between vectors and rotations. 3. Enable a mathematics of interdependent (ι) bistability where measurements disturb or collapse the ι states that occur during socialpsychological interactions in physical space. 4. Test the proposition that information in organizational interactions can be modeled by the conservation of information.
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What we have accomplished above is to model social rotations as part of an SPHO. What we have not done to this point is to link SPHO with winners and losers in society, politics, or the market place. However, the existence of an SPHO should it be established would alone signify the value of stability to organizations and social systems. An SPHO allows us to study organizations as they search for stability (mergers; in Lawless et al., 2009). We will do this next with a case study.
CASE STUDY MiTAC Inc. was founded in 1974 as the original member of MiTAC-SYNNEX Group. The group now consists of more than 40 companies from different fields such as electronic gases & chemicals, design and manufacturing of IT and mobile communication devices, system integration and Internet technology, as well as distribution and fulfillment. MiTAC-SYNNEX Group has been trying to form a unique group, called the “NDimensional Network Organization”2, a tight network (i.e., reduced uncertainty) of different specialized units interlinked to achieve common goals. They define the N-Dimensional Network Organization as one organization that combines a problem-solving group domain of knowledge, group synergy, e-Centric skills and growth. The original core business of MiTAC Inc. was the personal computer (PC) market. In 1974, MITAC introduced the INTEL microprocessor system to Taiwan and the first super-minicomputer (Perkin-Elmer, 32-bit) and then moved on to model system integration. Later, it developed the first commercial Chinese terminal, a computerized taxation system and the first auction system in Taiwan. In the 1980s, MiTAC launched the first Chinese terminal named Ha-Tun, developed the first multi-processor system in Taiwan, established the Traffic Surveillance system for the National Chungshan freeway and got involved in different systems such as population, land, military and
Conservation of Information and e-Business Success and Challenges
police administration. In the 1990s, it entered the communication, network and education fields, produced industrial computers, built the island-wide united Credit Card Center networking system, and expanded into mainland China. Aiming at becoming a trend leader, MiTAC has been moving toward the field of Internet service by providing e-commerce web services in the 2000s. From 2000 to the present, it also developed a Self-service Counter System (SCS) for financial markets, constructed a Taipei Easy Card system using Smart Card technology, teamed up with Thales and Fubon Back to play a major part with the Taiwan High-Speed Consortium, and become the first company in Taiwan to attain a CMMI Maturity Level 3 appraisal for Systems Engineering and Software Engineering.3 MiTAC expanded from commercial computer production and system integration to IT distribution. It is now the largest IT system integration provider in Taiwan. As stated on its website, its goal is “to incorporate advanced technology and management knowledge, providing customers with comprehensive, dynamic solutions to improve productivity and working efficiency to better compete in the marketplace.” 4 MiTAC Inc. has accomplished a number of system integration projects. Their clients include governmental organizations, militaries, financial institutes, and private enterprises. In response to the “Digital Taiwan Plan” authorized by the Taiwan government, the wide-range of its clients demonstrates MiTAC’s managing concept of “eGovernment, e-Industry, and e-Society”. We list major projects from all three of these areas.
E-GOVERNMENT MiTAC has developed various information systems for different Taiwan government branches that illustrate its versatility.
•
•
•
•
•
•
Integrated Tax System (ITS): ITS is a full-scale operation service for the outsourcing program of Taiwan’s Internal Revenue Service. It is a dual-phased, cross platform system that provides data exchange through Internet and Gateways using different platforms. Integrated Taxation Administration Information System (M-ITAIS): The M-ITAIS includes taxpayer registration, tax return filing and processing, auditing, compliance, billing collection management, enforcement audit selection, and other related services. MiTAC is responsible to operate, maintain and continuously upgrade the Taxation Administration Information System. We discuss this project in more detail below as a “success” eBusiness project that MiTAC has implemented. Integrated Land Administration Information system: Taiwan land administration computerization project and its maintenance. Healthcare field: Mainframe system upgrade and database integration, and computerization for 369 villages and towns for the Bureau of National Health Insurance. Government field: The Office Automation computerization systems for the Taiwanese Presidential Palace, the National Security Office, the Executive Yuan, the Legislative Yuan, and the Judicial Yuan. Military field: Tactical Communication System and Logistics Information Management System for the Taiwanese Air Force; military real estate control system; Coast Guard Administration Information System and Vessel Satellite Monitoring System; Military Police Integrated Information System; Advanced Air Defense System (AADS) for the Taiwanese Air Force; Multiple Integrated Laser Engagement System (MILES) for the
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Conservation of Information and e-Business Success and Challenges
Taiwanese Army; and Command Control Communication Computer Intelligence Surveillance and Reconnaissance for Taiwanese tri-services.
• •
E-BUSINESS •
Silo and Mill Automatic control System:5 These Automatic control system are to increase operation performance for warehouse businesses. A complete silo automation management and control system changes the traditional storage and delivery of agriculture products process and lowers operational cost (reduce personnel and time) while increasing production. It manages the intake, shipping and delivery process under a precise product flow monitor model. Consisting of a front end control system and management system, it is mainly a chain-reaction control system run from a computer programmed controller and other equipment, including field conveying equipment control and management system controls.
E-SOCIETY •
MiTAC has built Silo automatic control systems for Taichung and Kaohsiung harbor (Far-Eastern Silo) and a mill automatic control system for LienHua Fu-Kung flour factory, Great Wall enterprise Co., and Great Wall Chuang-hua. • •
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Credit Card Operation Management System. Banking Everybody Information System: The purpose for establishing this system is to assist not only the decisionmaking for the executive and operation mangers, but also expand the system to permit all clients to be able to get their own internal or external banking information.
Logistics, Finance and Stocks Management System. Bank Foreign Exchange System: MiTAC Bank Foreign Exchange System has 4 major functions: Outward Remittance, Inward Remittance, Inter-bank Transfer and Foreign Deposits on a common platform. This platform serves to form a foundation for all foreign exchange transactions.
• • •
Integrated Highway Surveillance control System: A highway surveillance system was assigned to provide the public with a more convenient and safer driving environment by monitoring traffic and car accidents. The system should also generate revenue for the government. There are three sub-systems in the MiTAC Integrated Highway Surveillance System (MIHSS): Traffic Control System (MIHSS-100), Toll Collection System (MIHSS-200) and Operation Management System (MIHSS-300). MiTAC has developed and installed the Taiwan Chungshan Highway’s first stage traffic control system, toll counting system, and central computer system for the second Northern Highway northern section control center and tunnel control center. The Traffic Control System uses surveillance equipment to collect instant traffic information and send it back to the control center. The central computer then makes the best assessment and decision based on operational models and policies. The Operation Management System mainly provides strategic and management support. Cab Driving Simulation System. Hog Auction Management System. Automatic Fare Collection System (AFC): With the experience of designing
Conservation of Information and e-Business Success and Challenges
and installing automatic control systems, MiTAC moved to serve the rapid-transportation field. It has completed numerous projects involving system design and implementation of Highway, Railway, Mass Rapid Transit, and High Speed Rail automation. Its specialties are manifested by the Automatic Fare Collection systems. The AFC that MiTAC assigned and implemented is successful due to its ability to handle operations on a grand project scale, to provide real time traffic information and control, and to generate sufficient revenue to operate the system. MiTAC has completed Taipei’s EasyCard System AFC, Taiwan High Speed Rail System AFC, and the Electronic Toll Collection System in recent years for Taiwan as it constructed a rapid transit network to serve its public. Taipei EasyCard System is a multi-operator and multimodal system. Since its operation, it has issued over 7 million cards with transactions recorded at around 3 million per day. Taiwan’s High Speed Rail System serves over 300,000 passengers per day and is designed for future interoperability with Taipei’s EasyCard system.
Challenge: e-Government Project E-government may be described as the general use of information and communication technology and the specific use of e-commerce to carry out government operations. It includes providing citizens and organizations with more convenient access to government information and services, and with delivering government agency services to citizens, business partners and suppliers or other government agencies (UN & ASPA, 2002). Taiwan government authorities have been promoting a “Digital Taiwan” plan. MiTAC has finished some major projects under this umbrella. MiTAC has developed significant e-Government projects which include a full-scale integrated
Tax system, Integrated Taxation Administration Information System, Integrated Land Administration Information system, Healthcare field system, and other government and military systems. We discuss the project MiTAC did for Taiwan’s Patent Office, the TiPOnet, to describe the challenges for government as it moves into the eBusiness world to better serve its people; there are also challenges that a medium-size IT company faces as it develops an e-system for government authorities in this territory unfamiliar to both the government and the company.
TIPONET The challenges that digital technologies pose for national and international regulation of intellectual property rights are receiving considerable attention these days from many governments such as the United States, Taiwan and China. In September 1995 the United States issued its White Paper on Intellectual Property and the National Information Infrastructure (Samuelson, 1996). To promote efiling and international harmonization with other countries, the TIPOnet project was proposed in early 2002 by MiTAC to Taiwan’s Patent Office to integrate information technology under business processes re-engineering (BPR) to create an IT-activated, paperless and online infrastructure. The TIPOnet project was designed to enhance administrative efficiency and service quality as well as to increase the competitiveness of domestic industries. On January 6, 2003, the Executive Yuan agreed to incorporate the TIPOnet project into the “Digital Taiwan Plan” for “Challenge 2008—National Development Plans”,6 Taiwan’s plan to develop a Knowledge-based economy in Taiwan formulated by the Council for Economic Planning and Development. TIPO awarded the TIPOnet development project, valued at over $26 million (NT$ 894 million), to MiTAC in January 2003. TIPOnet is a five-year development project. Table 1 shows the
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Conservation of Information and e-Business Success and Challenges
Table 1. TIPOnet total cost breakdown (in NT$ million) 7 2003
2004
2005
2006
2007
Total
Hardware
*
59.7
52.3
47.6
47.5
207.1
Operation
*
3.8
4.8
8.3
12.6
29.5
Maintenance
*
*
7.1
13.4
19.1
39.7
Application Development
53.0
168.8
187.7
183.3
25.0
617.8
Grand Total
53.0
232.2
251.9
252.7
104.2
894.1
*There were no costs associated with Hardware, Operation and Maintenance in the first stage of system design.
total cost breakdown of the TIPOnet project. The total hardware cost is about $6 million (NT$207 million), operation $0.88 million, maintenance $1.2 million, and application development $18 million. Table 2 shows the software cost breakdown in employee-months. The total application development required over twenty-nine hundred employee-months, over four hundred employeemonths for project management, over eight hundred employee-months for operations, and over one hundred employee-months for training. MiTAC Inc. has since developed other largescale e-government development projects in Taiwan. But intellectual property systems are a brand new area for MiTAC. In order to reduce the risk to MiTAC with the TIPOnet development project, MiTAC teamed up with IBM and Reed Technology and Information Service Inc. (RTIS). IBM has been involved in the development of patent and trademark application system for the United States Patent and Trademark Office (USPTO). RTIS has been working with USPTO for over thirty years in publishing the USPTO
Gazette and in converting paper-based patents to electronic documents. In February 2001, the Chief Information Office (CIO) consortium provided guidance for FEA (federal enterprise architecture) to the United States federal government (CIO Council, 2001). The FEA is a collection of reference models that defines a common taxonomy and ontology for describing IT resources. It includes the Performance Reference Model (PRM), the Business Reference Model (BRM), the Service Component Reference Model (SRM), the Data Reference Model (DRM) and the Technical Reference Model (TRM). The purpose of the FEA framework is to identify opportunities to simplify processes and unify work across agencies and within the lines of business for the federal government. The TIPOnet enterprise architecture (EA) framework adopted a simplified view of the relationships among FEA reference models. The TIPOnet enterprise architecture (EA) framework represents the TIPOnet EA in three fundamental tiers or layers (i.e., business, services, and technical), all of which are intersected
Table 2. Software cost breakdown (in employee-months) 2004
2005
2006
2007
Total
Application Development
879
919
902
239
2,939
Project Management
128
119
167
15
429
Operation
102
204
240
312
858
Training
20
40
40
5
105
Grand Total
1,129
1,282
1,349
571
4,331
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Conservation of Information and e-Business Success and Challenges
by three critical architectural dimensions (i.e., information and data, operational, and security and privacy). This means that the three basic perspectives of the TIPOnet EA (the business view, the services view, and the technical view) must always be considered in the context of three pervasive sets of considerations: information and data flows; operational objectives and measures; and security and privacy controls. Since it is a service-oriented system, TIPOnet utilized SRM to plan and map services that the system offers. The SRM defines seven major services: portal, e-filing, e-examining, e-search, e-publishing, knowledge management (KM), and management information system (MIS). TIPOnet set out to launch an e-filing system on 26 August 2008 for patents and trade marks.8 To encourage applicants to use online instead of paper filings, from the time when it was first launched, the application fee was reduced by approximately EUR 13 per document (about 16%) for patents and EUR 6.5 (about 10%) for trademarks. Now some of the applications for patents are free. Since the launching of this new electronic filing service, the response from all types of users has been positive. The e-filing service has been utilized by individuals, agents and companies alike, with many of the first-time applicants becoming long-term users.
CHALLENGES Although TIPOnet was finished on time, it did not follow the original project time-line allotted for each component/phase of its project life cycle. This project is not listed as one of MiTAC’s “most successful” cases because it suffered project creep, delay of certain phases, and the project life-cycle was not completed in a timely and cost-effective way. Due to the nature of the project and the customer, there was no room for negotiation in the budget or for time increases. MiTAC had to come up with alternative solutions for these problems. MiTAC faced two major challenges:
step in a new and unfamiliar field to design a system, and try to follow a yet-to-mature model. First, and as the first intellectual property project MiTAC had taken on, TIPOnet’s startup had not been easy. It took MiTAC two years to do the requirements analysis to meet business (TIPO) needs and to design the system to have all the required functionalities. This caused a major delay in the beginning (requirement analysis and design phase) of the project. And the learning curve for this project was steep. Unlike the financial market that MiTAC was familiar with and also has had many models to follow, the procedure of applying and processing patents and trademarks had to be uniquely defined, mapped and implemented. Then the second major challenge revealed itself. MiTAC was asked to adopt the FEA framework. Adopting this framework meant that MiTAC inherited both its advantages and disadvantages. One of the weaknesses in the FEA framework is that it does not contain a detailed description sufficient to generate specification documents for each cell of an FEA-F Matrix (Leist & Zellner, 2006). There is no standard artifact description for some cells. Each organization has to define the meta model for each cell such as data, function, network, people, time and motivation. Such cells represent different areas of interest for each perspective. Therefore, the resulting framework is not a definite solution. Many studies compare the similarities and differences between different enterprise architecture frameworks, but few studies report the empirical implementation of FEA frameworks (Kim et al, 2005; Meneklis et al., 2005). These deficiencies made MiTAC’s work more difficult and farther steepened its learning curve. But by taking advantage of its strong background in software development, MiTAC gained time back by adding extra software developers to its team to help with the coding process during the development phase and to finish the project in time.
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Conservation of Information and e-Business Success and Challenges
SUCCESS: INTEGRATED TAXATION ADMINISTRATION INFORMATION SYSTEM (M-ITAIS) A good taxation system is the foundation of a government’s economic growth plan. Taiwan’s previously paper-based taxation system created many obstacles. From the public’s perspective, members of the public had to fill out different forms for different level units (federal, city, or local) and they had to go to each location, to get in line and either fill out a tax return or deal with several different tax issues. The process was time-consuming, error-prone and sometimes the paperwork got lost, causing many to repeat the process. From the official side, the lack of a standardized data format increased costs and time; officials were also overloaded with many different cases. To make matter worse, there was no central database for different tax units to share tax data. Taiwan’s government wanted a good taxation system to serve its people better and to stimulate economic growth. This could be better done by utilizing Information technology and the Web to reduce bottom-line costs, and thus to generate revenue that could be used for public development. During the past three decades, MiTAC won several projects to design and deploy the Integrated Taxation Administration Information System (MITAIS) in Taiwan for many government agencies. To “overhaul” the manual system, there were two major challenges/requirements for a TAIS: a common platform (to reduce uncertainty) and a “one stop” portal for both tax officials and citizens. With its strong background in information technology, web service and financial market experience, MiTAC designed ITAIS as a web-service system with a Service Oriented Architecture (SOA) to ensure interoperability across different government units.9 It consisted of three major parts of e-Business: G2C (Government to Consumer), G2B (Government to Business) and G2G (Government to Government). It was a prime model for
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e-Government to serve the public (consumers), to perform eBusiness functions (G2B), and to interoperate government units (G2G). M-ITAIS includes taxpayer registration, tax return filing and processing, auditing, compliance, billing collection management, enforcement audit selection, and other related functions. It has significant features such as the All-in-one Functional Center, transparency and accountability for all tax officials. It also simplifies service and the automation of administrative assessments. Mi-TAIS provides the government of Taiwan with an effective and cheaper way to collect taxes and at the same time to offer a better and faster service to its citizens. M-ITAIS has become both a benchmark model of a desired taxation system and MiTAC’s most famous successful project based on customer satisfaction, increased productivity, reduced operational costs, an efficient but complex system, and the revenue that it generates. The annual tax revenue collected is over 50 billion USD which has drawn international attention. Delegations from countries of Asia, Latin America and the USA have visited the Financial Data Center in Taiwan to observe its “best practices” model.
Success Factors of M-ITAIS 1. Understand the customer’s needs and goals for a project. This is critical for any system design. MiTAC has a strong background in the financial sector and it has been designing systems for different levels of organizations for about 30 years. Although it was a familiar field, MiTAC must still make sure it understands the needs for each office. However, the rotations that we described in the earlier section under theory tell us that beliefs and actions can be orthogonal; thus, we cannot rely on the average responses from customers but instead must consider the widest range of them and, more importantly, their actions. 2. Provide professional and specialized team and management. With extensive back-
Conservation of Information and e-Business Success and Challenges
grounds in all aspects of hardware, software, communication, networking, integrated testing, training, maintenance and consulting services, MiTAC was able to implement an e-Tax net which connects all levels of government units for data sharing and processing. 3. Provide the logistics necessary for operations. MiTAC has strong Supply Chain management and since it could draw knowledge, man-power from other companies in their Group on the supply chain, it was able to obtain adequate resources to finish its target project. 4. All-in-One service is the key success feature of M-ITAIA. The main purpose of setting up a ITAIS was to provide the government tax officials and citizens a central portal for their taxation needs. All-in-One services offer real-time data, standardized forms, accountability, and best of all, convenience. It saves time and cost. 5. Cross-platform design. Since the e-Tax net connects different levels of government tax units, it has to be able to perform on different platforms.
MITAC BETAS Many formulas exist for stock market beta, including with statistical regressions. Beta represents market volatility. We estimated beta with the
covariance of a target organization A against a standard, such as the S&P 500, divided by variance of the standard (see www.answers.com/ topic/beta-coefficient). In order for the data to be synchronized, we matched the dates of the available data for MITAC, the S&P 500 Index, the Goldman Sachs Taiwan Select 50 Index (TS 50), and the USA Today E-Business 25 Index. The time period chosen was from March 1, 2007 to May 21, 2009. MiTAC’s betas indicate that MiTAC is a very stable organization. Whether compared to the S&P 500 Index, the TS 50 Index, or the eBusiness 25 Index, MiTAC’s responses to market perturbations have been uniformly stable.
DISCUSSION From MiTAC’s various projects and our COI theory, we try to find the common competiveness/ success factors as listed below.
Innovation Since its founding in 1974, MiTAC has always tried to use the most current technology in order to position itself as a trend leader. It evolved from a PC and Software Development Company to a system integration enterprise that can provide a total solution for its customers. To be a trend leader, MiTAC has to be innovative in technology
Table 3. SD of MiTAC = 8.507 COVAR MiTAC
S&P 500
1942.277
Goldman Sachs Taiwan Select 50 (USD) Index
136.0038
USA TODAY E-BUSINESS 25 INDEX
155.3663
Beta 1 (S&P 500 and MiTAC)
.03
Beta 2 (TS 50 and MiTAC)
.30
Beta 3 (eBusiness 25 and MiTAC)
.39
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Conservation of Information and e-Business Success and Challenges
products, in management, and in services to its customers. Their (MiTAC-SYNNEX Group) 3V business model (Velocity, Visibility and Value), and their N-Dimension Network concept have helped MiTAC create a synergy that seamlessly unites its partners, customers, employees, and companies. MiTAC’s products and services have won awards from government, technology shows, and its customers almost every year, providing proof that it is an innovative firm. With so many successfully designed and implemented projects, such as the M-ITAIS we discussed above, MITAC has set a benchmark for financial markets.
Sophisticated Supply Chain Management and Integrated Designand-Manufacturing System Supply chains are the life-blood of all kinds of organizations. They are often the unseen forces without which an organization cannot function. A good supply chain will ensure that materials are available to begin production and that finished products are ready for delivery to the customer. A supply chain is best satisfied when the interrelated components expressed in a business plan, business objectives and profitability, and productivity extend through a planning horizon sufficient to schedule the labor, equipment, facilities, material, and finances required to accomplish the production plan. In that this plan affects many interdependent company functions, it integrates information from across the supply chain (e.g., marketing, manufacturing, engineering, finance, materials). There must be interaction across management and the other units (i.e., oscillation) of an organization. There must be units to provide real-time information on customer needs, even before customers or suppliers can articulate these needs. MiTAC’s approach, PLM (Product Lifecycle Management), is its way to address this particular part of its supply chain to reduce time and cost with precise production management. Combining the MiTAC-Synex group’s horizontal
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development strategy, MiTAC’s supply chain is completed with products Design & Manufacturing (manufacturing and Research & Development), Internet Technology & Mobile Solutions, and Distribution & Fulfillment. MiTAC’s different but interdependent functional units and other companies of the group in its supply chain communicate (oscillate back and forth) through the whole chain which enables it to identify and solve problems to provide the best and most effective service to its customers and follow its “all service in one” model. Since systems are developed by distinct groups with different points of view, only by reducing uncertainty and increasing the rate of information exchange is it possible to reach the “best” design.
Vertical and Horizontal Development Strategy MiTAC’s horizontal (i.e., supply chain) is completed from products to e-Commerce to take full advantages of its network. Its vertical chain consists of units from material (production) to system (integration and delivery).
Precise Management Unique business model and management concepts enable administrators to control all of the information relevant to an organization’s or government’s businesses. Management teams must continually strive for focus, alignment and synchronization among the interdependent functions of an organization to reduce its time and cost factors.
Great Customer Service/ Management MiTAC’s complete system life-cycle, integration, development, consultation and maintenance processes not only provide real-time information exchanges for its customers, but also help to keep its customers involved in system design and
Conservation of Information and e-Business Success and Challenges
development. This has increased customer satisfaction and has served to ensure that the systems it designs meet its customer’s needs. MiTAC is also involved in many government IT projects to build good relationships with government authorities that not only provide framework and regulations to follow but also a great resource for future projects.
e-Centric and Digitalization of its Operations are “MustHaves” in the Information Age Partnerships MiTAC partners with other companies for specialized functions when MiTAC cannot fulfill a customer’s needs or make its products sufficiently competitive. It has partnered with different companies, some very famous, with different specialties to build solutions for its customers. For example, MiTAC teamed up with HITACHI, MITSUBISHI and others for a transportation solution; with HP, IBM, Microsoft, Oracle and others for computer integration; with CORNING, CISCO, MOTOROLA and others for communication integration; and CISCO, SYMANTEC, and WATCHGUARD for security integration. MiTAC has also invested with Anjes, Sinfotek, and Onsys to build up a professional Internet service team and to team up with banks on various other projects.
LESSON LEARNED AND FUTURE TRENDS For an eBusiness to be successful, future systems must be functional across different platforms, able to provide real-time responses, and able to reduce computational time. For better management, evaluation and decision making, it is ideal to implement Web-based performance metrics to provide feedback, pinpoint the components that need improvement and reduce uncertainty. But like
most decisions made, states of interdependence can positively or adversely impact the resulting decision (Lawless et al., 2007). An organization has to involve the entire supply chain and its customers as early in the process as possible to avoid unnecessary costs. New product development should not be kept separate from the supply chain focus because not only the products (system) created but routing can adversely impact the finances of new products. Utilizing the most current information technology and Internet technology are also critical for eBusiness success. What we have done is to create a model of social rotations (i.e., SPHOs, Nash Equilibria; etc.). What we have not done is to link rotations with population effects from the fluctuations or perturbations caused by rotations (Nash equilibria). Once we do so, our model will become dynamic and predictive. We predict that these fluctuations will generate limit cycles, our next area of research.
CONCLUSION We have devised a theory of social rotations to model social, political and market conflict and competition. We used our ideas about rotation to study stability and to apply them to MiTAC, which we found to be one of the more successful international companies. We suspect that our theory of rotations and findings about MiTAC may well contradict the prevailing view of Nash Equilibria. In this prevailing view, set out by Luce and Raiffa (1969), where it was believed that cooperation can avoid the traps of Nash Equilibria, it was taken to its logical extreme by Axlerod (1984) who believed that Nash Equilibria led to the worst social welfare outcomes: “the pursuit of self-interest by each [participant] leads to a poor outcome for all” (Axlerod, 1984, p. 7; also p. 8) that can be avoided when sufficient punishment exists to discourage competition. Instead, we suspect when all is said and done, that competition is the mechanism by
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which a company like MiTACor a society can best learn, govern, defend, and feed itself.
ACKNOWLEDGMENT For the fifth author, this material is based upon work supported by, or in part by, the U. S. Army Research Laboratory and the U. S. Army Research Office under contract/grant number W911NF-10-1-0252.
REFERENCES
CIO (Chief Information Officer) Council. (2001). A Practical Guide to Federal Enterprise Architecture. Version 1.0. Retrieved June 30, 2006, http:// www.gao.gov/special.pubs/eaguide.pdf Cohen, L. (1995). Time-frequency analysis: theory and applications. Upper Saddle River, NJ: Prentice Hall Signal Processing Series. Coleman, J. J. (2003). The benefits of campaign financing. CATO Institute Briefing Papers.www. cato.org/pubs/briefs/bp-084es.html. Washington. Dietz, T., Ostrom, E., & Stern, P. C. (2003). The struggle to govern the commons. Science, 302, 1907. doi:10.1126/science.1091015
Ambrose, S. H. (2001). Paleolithic technology and human evolution. Science, 291, 1748–1753. doi:10.1126/science.1059487
Gershenfeld, N. (2000). The physics of information technology. Cambridge, MA: Cambridge University Press.
Axelrod, R. (1984). The evolution of cooperation. New York: Basic.
Hasson, U., Nir, Y., Levy, I., Fuhrmann, G., & Malach, R. (2004). Intersubject Synchronization of Cortical Activity During Natural Vision. Science, 303, 1634–1640. doi:10.1126/science.1089506
Bloom, N., Dorgan, S., Dowdy, J., & Van Reenen, J. (2007). Management practice and productivity. The Quarterly Journal of Economics, 122(4), 1351–1408. doi:10.1162/qjec.2007.122.4.1351 Bohr, N. (1955). Science and the unity of knowledge . In Leary, L. (Ed.), The unity of knowledge (pp. 44–62). New York: Doubleday. Busemeyer, J., & Trueblood, J. (2009). Comparison of quantum and Bayesian inference models. In P. Bruza, Sofge, D.A., Lawless, W.F., Van Rijsbergen, K., & Klusch, M. (eds). Quantum Interaction. Third International Symposium, QI2009. Berlin:Springer-Verlag. Carley, K. M. (2002). Simulating society: The tension between transparency and veridicality. Social Agents: ecology, exchange, and evolution. University of Chicago, Argonne National Laboratory.
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Hayek, F. A. (1944/1994). The road to serfdom. Chicago, UK: Routledge Press/University of Chicago Press. Heisenberg, W. (1958/1999). Language and reality in modern physics. Physics and philosophy. The revolution in modern science (pp. 167–186). New York: Prometheus Books. Kelley, H. H. (1992). Lewin, situations, and interdependence. The Journal of Social Issues, 47, 211–233. doi:10.1111/j.1540-4560.1991. tb00297.x Kim, J., Kim, Y., Kwon, J., Hong, S., Song, C., & Baik, D. (2005). An enter-p rise architecture framework based on a common information technology domain (EAFIT) for improving interoperability among heterogeneous information systems. Proceedings of the 2005 Third ACIS Int’l Conference on Software Engineering Research.
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Kung, H., Tung, H., & Case, T. (2007). Managing E-Government Application Evolution: A State Government Case. International Journal of Cases on Electronic Commerce, 3(2), 36–53. Lawless, W. F., Bergman, M., Louçã, J., Kriegel, N. N., & Feltovich, N. (2007). A quantum metric of organizational performance: Terrorism and counterterrorism. Computational & Mathematical Organization Theory, 13, 241–281. doi:10.1007/ s10588-006-9005-4 Lawless, W. F., Castelao, T., & Ballas, J. A. (2000). Virtual knowledge: Bistable reality and the solution of ill-defined problems. IEEE Systems Man, and Cybernetics, 30(1), 119–126. doi:10.1109/5326.827482 Lawless, W. F., Sofge, D. A., & Goranson, H. T. (2009). Conservation of Information: A New Approach To Organizing Human-Machine-Robotic Agents Under Uncertainty. In P. Bruza, Sofge, D.A., Lawless, W.F., Van Rijsbergen, K., & Klusch, M.(eds). Quantum Interaction. Third International Symposium, QI-2009. Berlin:SpringerVerlag. Lawless, W. F., Whitton, J., & Poppeliers, C. (2008). Case studies from the UK and US of stakeholder decision-making on radioactive waste management. Practice Periodical of Hazardous, Toxic, and Radioactive Waste Management, 12(2), 70–78. doi:10.1061/(ASCE)1090025X(2008)12:2(70) Leist, S., & Zellner, G. (2006). Evaluation of Current Architecture Frameworks. ACM Symposium on Applied Computing (pp. 1547-1553). Dijon, France: ACM. Luce, R. D., & Raiffa, H. (1967). Games and decision. New York: Wiley.
Meneklis, B., Kaliontzoglou, A., Douligeris, C., & Polemi, D. (2005). Engineering and Technology Aspects of an e-Government Architecture Based on Web Services, Proceedings of the Third European Conference on Web Services. OMB (Office of Management and Budget). (2006). FEA Practice Guidance. Retrieved June 30, 2006, http://www.whitehouse.gov/omb/egov/ documents/FEA_Practice_Guidance.pdf Rieffel, E. G. (2007). Certainty and uncertainty in quantum information processing. Quantum Interaction: AAAI Spring Symposium, Stanford University:AAAI Press. Samuelson, P. (1996). Intellectual Property Rights and the Global Information Economy. Communications of the ACM, 39(1), 23–28. doi:10.1145/234173.234176 Standish Group. (2001). Extreme chaos. Retrieved May 30, 2006, http://www.standishgroup.com/ sample_research/PDFpages/extreme_chaos.pdf UN & ASPA. (2002). Bench-marking e-government: A global perspective. Retrieved May 30, 2006, http://unpan1.un.org/intradoc/groups/ public/ documents/UN/UNPAN021547.pdf Wood, J., Tung, H.-L., Marshall-Bradley, T., Sofge, D. A., Grayson, J., & Lawless, W. F. (2009). Applying an Organizational Uncertainty Principle: Semantic Web-Based Metrics. In M. M. Cunha, Eva Oliveira, Antonio Tavares & Luis Ferreira (Eds.). Handbook of Research on Social Dimensions of Semantic Technologies and Web Services. Hershey, PA: IGI Global.
ENDNOTES 1
Given [A,B] = iC, and δA = A - , then [δA, δB] = iC; further, > ¼ , giving the Heisenberg uncertainty principle ∆A∆B >1/2 (for details, see
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2
3
4
5
Gershenfeld, 2000, p. 256). The uncertainty equation models the expected variance around the expectation value of the operators while the right hand side gives the expectation value of the commutator. In signal detection theory, the uncertainty principle becomes the Fourier pair σAσ B> ½ (see Cohen, 1995; Rieffel, 2007). http://www.msgroup.com.tw/index.htm Ndimension Organization = Domain knowledge + Synergy +e-Centric + Growth CMMI is a numeric scale used to “rate” the maturity of a software development process or team. There are five levels of maturity in CMMI: 1. performed, 2. managed, 3. defined, 4. Quantitatively Managed and 5. Optimizing. To achieve CMMI level three, a process that qualifies for CMMI level two is instituted as a corporate standard. Then it is tailored and applied to standard process to individual projects. http://tynerblain.com/ blog/2006/03/10/foundation-series-cmmilevels-explained/ http://www.mitac.com.tw/english/about. htm http://www.mitac.com.tw/english/project05.htm
6
7
8
9
Developed by the Council for Economic Planning and Development, Challenge 2008 –National Development Plan is combination of new policies and strategy to guide Taiwan’s IT development to meet the global IT challenge and move toward to eBusiness era. http://www.cepd.gov.tw/encontent/m1. aspx?sNo=0001451&ex=1&ic=0000069 1.00 TWD = 0.0308623 USD rate on September 27, 2009 http://www.xe.com/ucc/ convert.cgi?Amount=1&From=TWD&To =USD&image.x=55&image.y=11 http://tiponet.tipo.gov.tw/home/ In computing, service-oriented architecture (SOA) provides a set of principles of governing concepts used during phases of systems development and integration. Such an architecture will package functionality as interoperable services: software modules provided as a service can be integrated or used by several organizations, even if their respective client systems are substantially different. http://en.wikipedia.org/wiki/ Service-oriented_architecture
This work was previously published in E-Business Managerial Aspects, Solutions and Case Studies, edited by Maria Manuela Cruz-Cunha and João Varajão, pp. 254-269, copyright 2011 by Business Science Reference (an imprint of IGI Global).
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Chapter 1.7
Demand Driven Web Services Zhaohao Sun University of Ballarat, Australia Dong Dong Hebei Normal University, China John Yearwood University of Ballarat, Australia
ABSTRACT Web services are playing a pivotal role in ebusiness, service intelligence, and service science. Demand-driven web services are becoming important for web services and service computing. However, many fundamental issues are still ignored to some extent. For example, what is the demand theory for web services, what is a demand-driven architecture for web services and what is a demand-driven web service lifecycle remain open. This chapter addresses these issues by examining fundamentals for demand analysis in web services, and proposing a demand-driven architecture for web services. It also proposes a demand-driven web service lifecycle for the main DOI: 10.4018/978-1-60960-587-2.ch107
players in web services: Service providers, service requestors and service brokers, respectively. It then provides a unified perspective on demand-driven web service lifecycles. The proposed approaches will facilitate research and development of web services, e-services, service intelligence, service science and service computing.
INTRODUCTION Web services are Internet-based application components published using standard interface description languages and universally available via uniform communication protocols (ICWS, 2009). With the dramatic development of the Internet and the web in the past decade, web services have been flourishing in e-commerce,
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e-business, artificial intelligence (AI), and service computing. They have also offered a number of strategic advantages such as mobility, flexibility, interactivity and interchangeability in comparison with traditional services (Hoffman, 2003). The fundamental philosophy of web services is to meet the needs of users precisely and thereby increase market share and revenue (Rust & Kannan, 2003). Web services have helped users reduce the cost of information technology (IT) operations and allow them to closely focus on their own core competencies (Hoffman, 2003). At the same time, for business marketers, web services are very useful for improving interorganizational relationships and generating new revenue streams (Sun & Lau, 2007). Furthermore, web services can be considered a further development of e-business (Gottschalk, 2001), because they are service-focused business paradigms that use two-way dialogues to build customized service offerings, based on knowledge and experience about users to build strong customer relationships (Rust & Kannan, 2003). However, one of the intriguing aspects of web services is that any web service cannot avoid similar challenges encountered in traditional services such as how to meet the customer’s demands in order to attract more customers. Service-oriented architecture (SOA) is an important topic for service computing, service science and service intelligence (Singh & Huns, 2005). The special form of SOA in web services is Web service architectures. Web service architectures are the basis for engineering many activities in web services. Therefore, there are many web service architectures proposed in the web service community (Erl, 2006; Alonso, et al, 2004). Papazoglou (2003) proposes a hierarchical serviceoriented architecture (SOA) for web services. Burstein, et al. (2005) propose a semantic web services architecture. However, the existing web service architectures are mainly from the perspective of implementation (Benatallah, et al, 2006) rather than from a demand perspective. It seems that demand-driven web service architecture and
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corresponding web services have not yet received any attention, to our knowledge, although demand is a critical force for developing web services, just as demand is a driving factor for microeconomics. Demand is a fundamental concept of economics. Demand refers to “the quantities that people are or will be willing to buy at different prices during a given time period provided that other factors affecting these quantities remain the same” (Wilkinson, 2005, p. 75). The demand for a firm’s products determines its revenues and also enables the firm to plan its production (Wilkinson, 2005, p. 71). Then demand is a decisive factor for market. Demand theory is an important part in microeconomics and managerial economics (Wilkinson, 2005, pp. 73-120). Demand theory in managerial economics examines demand curves, demand equations, demand analysis, demand chain, impact factors on demand, demand estimation and so on. Demand analysis is a factor driving e-marketing and e-business strategy objectives (Chaffey, 2007, p. 344). Demand analysis assesses current and projected demand for e-commerce services amongst existing and potential customer segments (Chaffey, 2007, p. 344). Demand chain has drawn attention in the field of supply chain management and customer relationship management since the end of last century (Walters, 2006). The demand chain can be defined as “The complex web of business processes and activities that help firms understand, manage, and ultimately create consumer demand” (Rainbird, 2006). The following problems arise in web services: what is the demand of main service players in web services? what is the demand theory for web services? what is demand analysis? What is a demand chain in web services? what is the mathematical analysis of demand in web services? These problems remain open in web services. This chapter addresses these issues by providing a mathematical analysis for web services taking into account the demand of service players in web services. The web service lifecycle (WSLC) is a fundamental topic for web services and service
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computing. The web service lifecycle is also the basis for engineering and managing web services. However, the existing models for web service lifecycles have not paid sufficient attention to the main players in web services and the demand of the main players for web services. If the main players and their demands are ignored in web services, then the healthy development of web services might be problematic, because ignorance of demand in economy and business will lead to economic recession. Therefore, this chapter will address the above mentioned issues by examining fundamentals for demands in web services, and proposing a demand-driven architecture for web services. It also reviews the existing web service lifecycles and proposes a demand-driven web service lifecycle for the main players in web services: Service providers, service requestors and service brokers, respectively. The key ideas behind this chapter are that SOA is fundamental for service intelligence (SI) and service science (SS). Web services are an important application field of SI and SS. Web service architecture is a logical realization of SOA in web services. The demand of main players and their intelligent agents is a central part for web services. Mathematical analysis of demands in web services is a basis for developing demand analysis and demand theory of web services. A WSLC can be considered as a logical implementation of web service architecture. The demand-driven WSLCs are a logical realization of the WSLC. The proposed approach will facilitate the research and development of web services, e-services, service intelligence, service science and service computing. To this end, the remainder of this chapter is organized as follows. First of all, we review SOA, Web services architecture, web services life cycle and classify main players in web services. Then we analyse demands in web services mathematically, which leads to a new classification for ecommerce. We also examine demand relationships among service providers, brokers and requestors in web services and demand chain in web services.
Then we examine web service architectures and provide a demand-driven architecture for web services (DWSOA). We also examine web service lifecycles, propose the demand-driven web service lifecycle for the main players in web services respectively and then discuss the demand-driven web service lifecycles in a unified way. Finally we end the chapter with discussing some future research directions and providing some concluding remarks.
BACKGROUND Service-oriented architecture (SOA) has been extensively studied in the fields of web services and service-oriented computing (Atkinson, et al, 2004; Singh and Huns, 2005). SOA is a conceptual architecture for implementing e-business, e-services, leaving the networking, transport protocol, and security details to the specific implementation (Gisolfi, 2001). SOA consists of three principal participants: a service provider, a service requestor, and a service broker. These three SOA participants interact using three fundamental operations: publish, find and bind: Service providers publish services to one or more service brokers or discovery agencies (Ferris & Farrell, 2003; Burstein, et al, 2005). Service requestors find required services via a service broker or a discovery agency and bind to them (Gottschalk, et al, 2000; Ferris & Farrell, 2003). A concrete form of SOA in web services is web service architecture. A web service architecture is a conceptual architecture for implementing web services, which is free of concrete implementation of a web service system owing to its conceptual nature. There are a number of different web service architectures proposed in the web service community. For example, Gottschalk, et al. (2000) propose an IBM web service architecture. This might be the first web service architecture, which is then called a SOA (Gisolfi, 2001). In other words, the web service architecture is the same
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as SOA in web services. This can be considered as the simplest SOA. Kreger (2001) developed Gottschalk’s web service architecture proposed in 2000 by adding artifacts, which mainly consist of service and service description. He uses service registry to replace the service broker in the previous architecture to fulfil the role of discovery agencies (Ferris & Farrell, 2003). Kreger (2001) also provides a business perspective on service provider, requestor and registry. He considers the above-mentioned three fundamental operations: publish, find and bind as the interactions between service provider, service requestor, and service broker. Therefore, Kreger’s web service architecture is a further development of web service architectures or SOAs. Talia (2002) explores the open grid services architecture to fully integrate grids and web services, and defines grid as a geographically distributed computation platform composed of a set of heterogeneous machines that users can access via a single interfaces. Burstein, et al. (2005) propose a semantic web services architecture, and consider semantic web services as web services in which semantic web ontologies ascribe meanings to published service descriptions so that software systems representing prospective service clients can interpret and involve them. They also examine the main interactions of web services between service providers and service requestors: service discovery, engagement, and enactment. However, they have not paid much attention to the role of service broker in interactions of web services. They have not focuses on the activities of web services from a viewpoint of web services lifecycle either. Numerous techniques, approaches, methods have been proposed to facilitate or support the main stages of the entire web service lifecycle (Wu & Chang, 2005). A large number of web service lifecycles have also been proposed to improve web services with their applications. For example, Atkinson, et al. (2004) propose a process model for a typical service, which consists of resources, service logic, and a message-processing layer that
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deals with message of exchanges. In this model, messages arrive at the service and are acted on by the service logic, utilizing the service’s resources as required. This model can be considered as an anatomy of a service in SOA, because it only focuses on the processing of a service rather than the interactions of service providers, requestors and brokers. Kreger (2001) considers web services development lifecycle as the design, deployment, and runtime requirements for each of the players in web services: service registries, providers, and requestors. Each player has specific requirement for each phase of four phases in the development lifecycle: build, deploy, run and manage. Benatallah, et al. (2006) implement a modeldriven framework for web service development lifecycle in a prototype platform, Service Mosaic, to model, analyze, and manage service models including business protocols, and adaptors. This framework at least includes protocol definition, protocol analysis, and protocol data management, which are fundamental issues that affect the web service development lifecycle from an implementation perspective. However, they have focused on neither WSLC nor the interoperations or interactions of service providers, brokers and requestors from a demand perspective. Narendra and Orriens (2006) consider a web service lifecycle consisting of web service composition, execution, midstream adaptation, and re-execution. We will turn to web services life cycle once again later when we propose demand-driven web services lifecycle. Humans are one of the most important decisive forces for development of web services. From a viewpoint of multiagent systems (Weiss, 1999; Sun and Lau, 2007), various intelligent agents are also a decisive force for developing intelligent web services. However, few studies have paid sufficient attention to the main players in web services, to our knowledge. In the next section we will first examine main players in web services.
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MAIN PLAYERS IN WEB SERVICES This section will look at the players involved in web services and some corresponding architectures. There are mainly three players related to web services: web service requestors, web service brokers, and web service providers (Sun & Lau, 2007; Singh & Huhns, 2005), as shown in Figure 1. Web service requestors also denote web service users, buyers, customers, consumers, receivers, clients, and their intelligent agents. Web service brokers denote web service intermediaries, middle agents, registry (Kreger, 2001), discovery agency (Ferris & Farrell, 2003) and their intelligent agents (Burstein, et al, 2005). Web service providers (Kreger, 2001) denote web service owners, sellers, senders and their intelligent agents. Web service requestors, brokers, and providers are the most integral players in web services transactions (Deitel, et al, 2004, p. 52). Gisolfi (2001) mentioned these three players in the simple service oriented architecture (SOA) for web services. In this architecture, web service providers create web services and advertise them to potential web service requestors by registering the web services with web service brokers, or simply offers web services (Dustar & Schreiner, 2005). The web service provider needs to describe the web service in a standard format, and publish it in a central service registry. The service registry or broker contains additional information about the service provider, such as address and contact of the providing company, and technical details about the service. Web service providers may integrate
or compose existing services (Limthanmaphon & Zhang, 2003) using intelligent techniques. They may also register descriptions of services they offer, monitor and manage service execution (Dustar & Schreiner, 2005). Web service requestors retrieve the information from the registry and use the service description obtained to bind to and invoke the web service. Web service brokers maintain a registry of published web services and might introduce web service providers to web service requestors. They use universal description discovery integration (UDDI) to find the requested web services, because UDDI specifies a registry or “yellow pages” of services (Singh & Huhns, 2005, p. 20). They also provide a searchable repository of service descriptions where service providers publish their services, service requestors find services and obtain binding information for these services. This architecture is simple because it only includes three players (as mentioned above) and three basic operations for web services: publish, find and bind. In fact, some behaviors of web service agents are also fundamentally important in order to make web services successful. These fundamental behaviors at least include communication, interaction, collaboration, cooperation, coordination, negotiation, trust and deception (Singh & Huhns, 2005; Sun & Finnie, 2004; Burstein, et al, 2005). Papazoglou (2003) proposes an extended service-oriented architecture. The players involved in this architecture are more than that in the simple SOA, because it includes service provider,
Figure 1. Main players in web services
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service aggregator, service client, market maker, and service operator. A service aggregator is a service provider that consolidates services provided by other service providers into a distinct value-added service (Papazoglou, 2003). Service aggregators develop specifications and/or codes that permit the composite service to perform functions such as coordination, monitoring quality of service (QoS) (Burstein, et al, 2005) and composition. In our view, a service aggregator should be differentiated from a service provider. We can use web service recommender or web service composer to replace service aggregator, because recommendation and composition are most important activities in web services. The main task of web market makers is to establish an efficient service-oriented market in order to facilitate the business activities among service providers to service brokers and service requestors. In the traditional market, the service broker is working in the market, while the market maker makes the market operating. The web service operator is responsible for performing operation management functions such as operation, assurance and support (Papazoglou, 2003). From the viewpoint of multiagent systems (Weiss, 1999; Henderson-Sellers & Giorgini, 2005), there are still other players involved in web services, such as web service advisors, web service managers, web service composers, web service recommenders, web service consultants, and so on. Further, an activity of web services usually is implemented by a few intelligent agents within a multiagent web service system (Sun & Finnie, 2004). Therefore, more and more intelligent players or agents will be involved in web services with the development of automating activities of web services. Although some of these will be mentioned in the later sections, we mainly focus on service providers, brokers and requestors in what follows.
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MATHEMATICAL ANALYSIS OF DEMAND IN WEB SERVICES This section will analyze demands in web services from a mathematical perspective and then discuss the demand relationships in web services. Demand is an important concept in microeconomics. Jackson and Mclver (2004, p. 74) defines demand as “a schedule that shows the amounts of a product that consumers are willing and able to purchase at each specific price in a set of possible prices during some specified period of time”. The basic law of demand is “All else being constant, as price falls, the corresponding quantity demanded rises”. Alternatively, the higher the price is, the less corresponding quantity demanded. Demand analysis has drawn attention in ebusiness. Chaffey (2007) defines demand analysis as “assessment of the demand for e-commerce services among existing and potential customer segments” (p. 218). He then analyzes the factors that affect demand for e-commerce services (Chaffey, 2007, pp. 150-60.) and uses demand analysis to examine current projected customer use of each digital channel with different markets (Chaffey, 2007, p. 344). Demand, in particular “on-demand” (Dan, et al, 2004), has also drawn some attention in web services. For example, Burstein, et al. (2005) examine functional and architectural demands or requirements for service discovery, engagement and enactment in terms of the semantic web service architecture. However, in the above-mentioned discussion, it seems that the subject of the demand and its objective are ignored to some extent. For example, who demands what from where is usually unclear. It may not be critical for traditional economics and e-commerce. However, it is useful for web services to know who, what and where exactly for web services, which can be seen in the examination of web service lifecycle. Further there has not been a mathematical theory or analysis of demand in e-commerce and web services. In what follows, we examine the mathematical foundation
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of demand in order to fill this gap and then use it to develop demand-driven web services. We can analyze “demand” mathematically as follows. A man M demands something S provided by N. In other words, from a mathematical viewpoint, demand is a 3-ary relation that can be denoted as Demand (m, n, s). In the context of web services, we can explain Demand (m, n, s) as: a player m demands web service s provided by player n. For example, “service requestor r demands web service consultation c provided by service broker b” can be denoted as Demand (r, b, c). More generally, demand as a 3-ary relation can be denoted as: Let M, N, and S be a non-empty set respectively, M = {m1, m2,…, mI}, N = {n1, n2,…, nJ}, S = {s1, s2,…, SK}, then any subset D3 of M × N × S, D3 ⊆ M × N × S, is a demand relation. In web services, N and M can denotes all the service requestors and all the service providers or brokers respectively. S represents all the web services provided on the web. In business practice, this 3-ary demand relation is usually simplified as a binary relation D2 or a unary relation D1: For example, in B2C e-commerce, we only focus on: who demands what, that is, D2 ⊆ M ×S represents “customers m demands a good s,” where M denotes all the service requestors or all the service providers. Further, in B2C e-commerce, we usually do not care about “who demands what” but only care about “what that are demanded”, that is, D1 ⊆ S represents the good that is demanded. Therefore, from a demand’s perspective, there are three different types of e-commerce: D1 e-commerce, D2 e-commerce and D3 e-commerce. •
•
D1 e-commerce only focuses on the goods that are transacted. Such an e-commerce is usually used for statistical analysis. D2 e-commerce only focuses on the customer and the goods that are purchased by the customer or the seller, and that the goods that are sold. Therefore, D2 e-commerce corresponds to a B2C e-commerce.
•
D3 e-commerce focuses on all the service providers, requestors, and goods that are transacted. Therefore, D3 e-commerce is an organization that oversees the activities in web services or e-commerce.
In fact, taking into account the amount and payment associated with demand relation, we introduce demand functions respectively for D1 e-commerce, D2 e-commerce and D3 e-commerce. For example, let A and P be non-empty sets, then any function d1: S→A×P, d(s) = a∙p, is a demand function taking into account the amount A of demand and the corresponding price P per a unit demand. For example, in D1 e-commerce, a customer demands 100 textbooks on e-commerce, and the price is AUD$100.00 per textbook. Then, the corresponding demand function value is d1(book) = 100∙100 = 10000 where the customer and provider are technically ignored. This demand function represents the total price for the demanded 100 textbooks. Similarly, in D2 e-commerce, d2(David, book) = 100∙100 = 10000 represents that David demands 100 textbooks on e-commerce with the price of AUD$10000.00, where the providers are technically ignored. In D3 e-commerce, d3(David, book) = 100∙100 = 10000 represents that David demands 100 books on e-commerce provided by Amazon.com with the price of AUD$10000.00. This is a complete form for demand in a transactional web service. From the above discussion, we can see that there is an inclusion relationship among D1 ecommerce, D2 e-commerce and D3 e-commerce, as illustrated in Figure 2. In demand-driven web services, we need a 3-ary demand relation taking into account the main players in web services (see the previous section). This demand relation can be illustrated in Demand relations in Web services.
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Figure 2. Interrelationship among D1, D2, and D3 e-commerce
In D3 web services, demand is a 3-ary relation, that is, service requestors demands service brokers or providers to provide certain web services, and vice versa. However, what properties this 3-ary relation has in the context of web services remains open. Some stages in the web lifecycle may be absent since the demand disappears. There are also many situations resulting in demand cancellation. In Table 1, the first column consists of a service provider, a service requestor, and a service broker. The first row lists a service provider, a service requestor, and a service broker. WS activities in the top left cell denote all the web service activities (or operations) in all the cell (m, n), where m an n denote rows and columns respectively. This implies that cell (m, n) contains the web service activities that are demanded. For example, cell (1, 2) contains web service binding, discovery, negotiation, invocation, billing, contract, all of which are demanded by the web service provider
to the web requestor, where cell (2, 1) contains web service QoS, description, representation, identification, search, match, discovery, negotiation, invocation, contract, all of which are demanded by the web service requestor to the web service provider. Even if the web service requestor demands the web service provider to represent web services (web service representation), the web service provider might not represent web services by himself. Instead, he may demand others to do so. In this way, a web service demand chain is formed in web services. For example, the web service requestor demands service consultation from a service broker, while the service broker demands web service representation and publication from a service provider. The service provider demands the most powerful web service tools from the ICT developer to realize the web service representation and publication, as shown in Figure 3. The extended form of a web service demand chain is a web service demand network in web services, just as there are supply chain networks in e-commerce (Chaffey, 2007). It should be noted that supply chain management and demand chain management have been seriously studied in business, marketing and management (Chaffey, 2007, pp. 266-300; Rainbird, 2004; Walters, 2006), whereas demand chain and demand chain management have not drawn significant attention in e-business and e-com-
Table 1. Demand relations in web services WS activities
Provider
Requestor
Broker
Provider
N/A
Binding, discovery, negotiation, invocation, billing, contract
discovery, recommendation, invocation, billing, contract
Requestor
QoS, description, representation, identification, search, match, discovery, negotiation, invocation, contract
N/A
Finding, consultation, personalization, recommendation, adaptation, mediation negotiation,
Broker
Publication, management search, match, Discovery, billing, contract
invocation, billing, contract
N/A
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Figure 3. A demand chain in web services
merce, to our knowledge. This situation might be changed in web services, because service customers’ demands play a vital role in web services. What are the majority of customers’ demands as well as their expectation and propensity in web services? and how do demand chain and demand network as well as demand network management impact on web services? How can we integrate demand chain analysis with the proposed mathematical analysis of demand? These problems remain open. We will address them in another article, and will not look at them any more because they are beyond the scope of this chapter.
DWSOA: A DEMAND DRIVEN ARCHITECTURE FOR WEB SERVICES This section will review a few web service architectures and then provide a demand-driven architecture for web services. We have briefly mentioned different serviceoriented architectures (SOA) for web services in the section “Background”. In fact, web service architectures have been a research topic for engineering web services (Alonso, et al, 2004). There have been a large number of web service architectures proposed in the past years. For example, Wu and Chang (2005) provide a conceptual architecture of web services for service ecosystems. Garcia and de Toledo (2006) propose an extended web service architecture providing QoS management for
web services. However, the existing web service architectures are mainly from the perspective of developers rather than from a demand perspective. Based on the above demand analysis for web services, we can propose a demand-driven SOA for web services (DWSOA), as shown in Figure 4. Note that in Figure 4, x and z denote either WS providers, brokers or requestors, y denotes WS activities. In the DWSOA, WS (web service) providers demand WS discovery, recommendation, invocation, billing, and contract from WS brokers; WS brokers demand WS invocation, billing, contract from WS requestors; WS requestors demand WS finding, consultation, personalization, recommendation, adaptation, mediation, negotiation from WS brokers; and so on. From the viewpoint of previously mentioned demand relation in web services, the above-mentioned demand relations are 3-ary, and corresponds to 1. Demand (WS providers, WS brokers, WS activities) = {WS discovery, recommendation, invocation, billing, and contract}; 2. Demand (WS brokers, WS requestors, WS activities) = {WS invocation, billing, contract}; 3. Demand (WS requestors, WS brokers, WS activities) = {WS finding, consultation, personalization, recommendation, adaptation, mediation, negotiation};
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Figure 4. DWSOA: A demand-driven SOA for web services
and so on. It should be noted that there are inter-demands among the WS providers, brokers and requestors in the DWSOA, although the demands among them are not symmetric. In other words, the service requestor demands the service consultation from the service broker, whereas the service broker does not demand service consultation from the service requestor. We do not believe that all activities in the web services have been covered in the DSWOA. For example, WS engagement, enactment, and management (Burstein, et al, 2005) are not included in the DSWOA. The key idea behind it is that we expose the demand relationship among WS providers, brokers and requestors. This is the basis for demand-driven web service lifecycles, which will be discussed in later sections.
WEB SERVICE LIFECYCLE This section mainly reviews web service lifecycles and discusses the corresponding issues. From the perspective of computer science, the notion of lifecycle originated from software engineering (Pressman, 2001). It describes the life of a software product (development) from its conception, to its implementation, delivery,
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use, and maintenance (Pfleeger & Atlee, 2006). A traditional software development lifecycle mainly consists of seven phases: planning, requirements analysis, systems design, coding, testing, delivery and maintenance. Based on this, a web service lifecycle consists of the start of a web service, the end of web service and its evolutionary stages that transform the web service from the start to the end. There have been a large number of attempts to address web service lifecycle in the web service community, as discussed in the section “Background”. Further, Glatard, et al. (2008) examine a SOA enabling dynamic service grouping for optimizing distributed workflow execution. Leymann (2003) discusses a lifecycle of a web service based on explicit factory-based approach, in which a client uses a factory to create “an instance” of a particular kind of service. The client can then explicitly manage the destruction of such an instance, or it can be left to the grid environment. Sheth (2003) proposes a semantic web process lifecycle that consists of web service description (annotation), discovery, composition and execution or orchestration. Wu and Chang (2005) consider service discovery, service invocation and service composition as the whole lifecycle of web services. Zhang and Jeckle (2003) propose a lifecycle for web service solutions that consists of
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web service modeling, development, publishing, discovery, composition, collaboration, monitoring and analytical control from a perspective of web service developers. Kwon (2003) proposes a lifecycle of web services consisting of four fundamental steps: web service identification, creation, use and maintenance. Tsalgatidou and Pilioura (2002) propose a web service lifecycle that consists of two different layers: a basic layer and a value-added layer. The basic layer contains web service creation, description, publishing, discovery, invocation and unpublishing (Gottschalk, et al, 2000), all of these activities are necessary to be supported by every web service environment. The value-added layer contains the value-added activities of composition, security, brokering, reliability, billing, monitoring, transaction handling and contracting. These activities bring value-added functionality and better performance to any web service environment. They acknowledge that some of these activities take place at the web service requestor’s site, while others take place at the web service broker’s or provider’s site. They also explore technical challenges related to each activity in the web service lifecycle. However, they have not classified the proposed activities of stages in their lifecycle based on web service requestors, providers, and brokers in detail. Some organizations also propose their own web service lifecycle. For example, W3C proposes a service lifecycle for web service management, which is expressed as state transition diagrams (W3C, 2004). Sun Microsystems considers the lifecycle of web services consisting of four stages: design/ build, test, deploy/execute, and manage (Sun Microsystems, 2003), which can be considered a model for web service developers. Based on the above analysis, we can find that there are at least the following activities of web services that have been mentioned in the reviewed web service lifecycles, all of these can be classified into two categories: development-oriented web service activities and business-oriented web service activities.
•
•
Development-oriented web service activities: Web service modeling, representation, design/building, test, publishing, unpublishing, deployment, execution, re-execution, orchestration, collaboration, monitoring, analytical control, maintenance, and management, Business-oriented web service activities: Web service creation, identification, description (annotation), publishing, finding, discovery, use, invocation and binding (Gottschalk, et al, 2000), adaptation, composition, security, brokering, recommendation, reliability, billing, monitoring, transaction handling and contracting.
This classification does not produce a crisp mathematical partition, because, some activities such as web service representation, management, and creation can be considered in both kinds of web service activities. However, such a classification reflects the fact that some existing web service lifecycles are proposed from the implementation perspective of the web service developers (Burstein, et al, 2006), whereas other web service lifecycles are proposed from the perspective of business. Generally speaking, web service providers pay more attention to development-demanded web service activities than web service brokers and requestors, whereas web service brokers and requestors pay more attention to Business-demanded web service activities than web service providers. From a market perspective, web services mainly consist of three kinds of players: Service providers, service requestors and service brokers (Tang, et al, 2007). Different players require different web service lifecycles. Therefore, what is a web service lifecycle from the demand viewpoint of web service providers, brokers and requestors respectively? How many stages does a web service lifecycle consist of? These problems are interesting for examining demand-driven web services. Further, demand is an important factor for market and economy development (Chaffey,
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2007, p. 150). The decrease of demand is an implication for economic recession. Different players generally have different demands for web services, different demands have also different web service lifecycles. Therefore, what is the demand-driven web service lifecycle from the viewpoint of web service providers, brokers and requestors respectively? These issues still remain open in web services. The following sections will address these issues by examining the web service lifecycle from a demand viewpoint. It should be noted that everybody, whether an application user, developer, financier, businessman, or an e-commerce manager, has enjoyed or will enjoy some tangible benefits from web services (Guruge, 2004) such as searching information using Google and doing business online. At the same time, he or she demands more and more web services with the development of the Internet. Therefore, we do not examine the demand of everybody for web services, but the demand of the main players in web services in what follows, that is, we will look at demand-driven web service lifecycles for web service providers, requestors and brokers respectively.
A PROVIDER’S DEMAND DRIVEN WEB SERVICE LIFECYCLE In web services, a web service provider usually demands a web service requestor to commit some web service activities and also demands a web service broker to commit some web service activities. Therefore, based on the above demand analysis for web services, a provider’s demanddriven web service lifecycle mainly consists of web service finding, identification (Kwon, 2003), description/representation (Burstein, et al, 2005), creation (Kwon, 2003; Tang, et al, 2007), discovery, composition (Limthanmaphon & Zhang, 2003; Tang, et al, 2007; Burstein, et al, 2005), recommendation (Sun & Lau, 2007), negotiation (Hung, et al, 2004; Burstein, et al, 2005), invoca-
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tion (Burstein, et al, 2005), contracting, use and reuse (Kwon, 2003), execution or orchestration, management and monitoring (Dustar & Schreiner, 2005), maintenance (Kwon, 2003), billing and security (Tang, et al, 2007). Web service identification aims to identify appropriate services (Ladner, 2008). Web service invocation is to invoke the discovered web service interface. Web services are published to the intranet or the Internet repositories for potential users to locate (Tang, et al, 2007). Web service unpublishing is sometimes no longer available or needed, or it has to be updated to satisfy new requirements (Tang, et al, 2007) Web service composition primarily concerns requests of web service users that cannot be satisfied by any available web service (Bucchiarone & Gnesi, 2006; Narendra & Orriens, 2006). One form of simple web service composition is to combine a set of available web services to obtain a composite service that might be recommended to the users. In other words, web service composition is a process in which a single web service requested from a service requestor can be satisfied by an aggregation of different services provided by several independent web services providers. More strictly, web service composition refers to the process of creating customized or personalized services from existing services by a process of dynamic discovery, integration and execution of those services in order to satisfy user requirements (Wang, et al, 2008). Web service composition is a key challenge to manage collaboration among web services (Limthanmaphon & Zhang, 2003). It refers to intelligent techniques and efficient mechanisms of composing arbitrarily complex services from relatively simpler services available over the Internet. Service composition can be either performed by composing elementary or composite services. Composite services in turn are recursively defined as an aggregation of elementary and composite services (Dustdar & Schreiner, 2005).
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There are many techniques existing for web service composition. For example, Tang, et al (2007) propose an automatic web service composition method taking into account both services’ input/output type compatibility and behavioral constraint compatibility. Cheng, et al. (2006) use case-based reasoning (CBR) to support web service composition. Further, Dustdar and Schreiner (2005) discuss the urgent need for service composition and the required technologies to perform service composition as well as present several different composition strategies. Web service composition is becoming an important topic for service computing, because composing web services to meet the requirement of the web service requestor is the most important issue for web service providers and brokers.
REQUESTOR’S DEMAND DRIVEN WEB SERVICE LIFECYCLE In web services, a web service requestor usually demands a web service provider and a web service broker to commit some web service activities respectively. Therefore, based on the above demand analysis for web services, a requestor’s demand-driven web service lifecycle mainly consists of web service consultation, creation (Burstein, et al, 2005), representation, search (Ladner, 2008), matching (Ladner, 2008), finding, discovery (Tang, et al, 2007; Burstein, et al, 2005), identification (Burstein, et al, 2005), composition, mediation (Ladner, 2008; Burstein, et al, 2005), personalization, adaptation, negotiation (Gottschalk, et al, 2000), evaluation (Burstein, et al, 2005) and recommendation, QoS (Burstein, et al, 2005), invocation (Burstein, et al, 2005), contracting (Burstein, et al, 2005). Web service discovery is a process of finding the most appropriate web service needed by a web service requestor (Singh & Huhns, 2005; Burstein, et al, 2005). It identifies a new web service and detects an update to a previously discovered web
service (Ladner, 2008). Services may be searched, matched, and discovered by service requestors by specifying search criteria and then be invoked (Dustdar & Schreiner, 2005; Tang, et al, 2007). Service invocation is restricted to authorized users (Dustdar & Schreiner, 2005). There have been a variety of techniques and approaches developed for web service discovery. For example, OWL-S (an OWL-based Web service ontology of W3C) provides classes that describe what the service does, how to ask for the service, what happens when the service is carried out, and how the service can be accessed (Ladner, 2008). Web service mediation aims to mediate the request of web service from the web service requestor. Web service negotiation consists of a sequence of proposal exchanges between the two or more parties with the goal of establishing a formal contract to specify agreed terms on the web service (Yao, et al, 2006). Through negotiation, web service requestors can continuously customize their needs, and web service providers can tailor their offers. In particular, multiple web service providers can collaborate and coordinate with each other in order to satisfy a request that they can’t process alone. However, a web service requestor might not need to know how the web services are retrieved, discovered and composed internally. Therefore, search, matching, and composition might be less important for a web service requestor.
A BROKER’S DEMAND DRIVEN WEB SERVICE LIFECYCLE Brokering is the general act of mediating between requestors and providers in order to match service requestor’s needs and providers’ offerings. It is a more complicated activity than discovery (Tang, et al, 2007). A broker should enable universal serviceto-service interaction, negotiation, bidding and selection of the highest quality of service (QoS) (Singh & Huhns, 2005, pp. 345-346). Brokering
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is supported by HP web services platform as a HP web intelligent broker (Tsalgatidou & Pilioura, 2002). After discovering web service providers that can respond to a user’s service request, HP web services platform negotiates between them to weed out those that offer services outside the criteria of the request. In web services, a web service broker usually demands a web service provider and a web service requestor to undertake some web service activities respectively. Therefore, based on the above demand analysis for web services, a broker’s demand-driven web service lifecycle mainly consists of web service consultation, publication, search, matching (Burstein, et al, 2005), discovery, personalization, adaptation, composition, negotiation, recommendation, management, invocation, contracting and billing. We propose web service consultation as the start of the broker’s demand-driven web service lifecycle, because the web service requestor provides a request for a web service so that the web service broker begins to consultation. In order to provide a service consultation, the web service broker has to conduct web service search, by using a search tool/engine such as google.com and beidu.com. During the web service search, the web service broker uses any techniques of web service matching such as CBR (Sun & Finnie, 2004). After discovering a number of web services, the web service broker can select one of them to recommend it to the web service requestor. If the requestor accepts the recommended web service, then the web service can be considered as a web service use/reuse; that is, the existing web service has been reused by customers. Web service recommendation aims at helping web service requestors in selecting web services more suitable to their needs. Web service recommendation is a significant challenge for web service industry, in particular for web service brokers. Web service recommendation can be improved through optimization, analysis, forecasting, reasoning and simulation (Kwon, 2003).
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Recommender systems have been studied and developed in e-commerce, e-business and multiagent systems (Sun & Finnie, 2004). Sun and Lau has examined case based web service recommendation based on the analysis of customer experience and experience-based reasoning (Sun & Lau, 2007). However, how to integrate web service recommendation, composition and discovery in a unified way is still a big issue for web services. Different web service requestors have different preferences and expectations. Therefore, a web service broker has to personalize web services in order to meet the requirement of the web service requestor satisfactorily. It is necessary to compose web services based on the requirement of requestors in order to personalize the web service. At the same time, web service composition allows web service brokers to create a composite web service for requestors rapidly (Tang, et al, 2007). Billing concerns service brokers and service providers (Tang, et al, 2007). Service brokers create and manage taxonomies, register services and offer rapid lookup for services and companies. They might also offer value-added information for services, such as statistical information for the service usage and QoS data.
A UNIFIED PERSPECTIVE ON DEMAND DRIVEN WEB SERVICE LIFECYCLES Based on the above discussion, the stages involved in the demand-driven web service lifecycle for web service providers, requestors and brokers can be summarized in Figure 5. Some of the detailed activities have not been listed in the table because of space limitations. From Figure 5, we can intuitively find that service requestors and brokers are the dominant force for developing web services, which will be examined in more detail in another paper. In what follows, we discuss the above proposed demand-driven web service lifecycles from a unified perspective.
Demand Driven Web Services
Figure 5. Demand driven web service lifecycles: A unified perspective
Some activities in web services are common demands of the main players: service providers, brokers, and requestors. This means that they share some common web service activities. However, different players in web services demand the same activity in a different way. For example, the service provider demands “web services search” also means that s/he asks web services developers or her/his technology agents to provide efficient web services search function for his or her business. On the other hand, the service requestor demands “web services search” means that s/he requires a fast search function from the service provider or broker in order to obtain the most satisfactory web services as soon as possible. Finding, search and matching are not unique activities or operations related to web services, because they are also involved in database and case based reasoning (CBR). For example, Google uses search and matching to provide web services. In fact, search can be considered the most common demand for everyone who accesses the Internet or the web. Adaptation, retrieval, classification (Ladner, 2008), use/reuse (Kwon, 2003), retention or feedback are not unique activities related to web services either, because they are also stages of CBR cycle (Sun & Finnie, 2004). Web service invocation, binding, billing, contract (Tang, et al, 2007) can be considered as the common features
for any commercial activities. Therefore, we need not discuss each of them in detail in the context of web services. Based on the above discussion, the most important activities in web services can be web service discovery, composition and recommendation: The service requestors demand the service providers and brokers for web services discovery and recommendation; the service brokers demand the service providers for web services discovery and composition; the service providers demands up-to-date techniques and tools for web services discovery, composition and recommendation. In a more general sense, all the above-mentioned activities of web services can be considered as a demand from web services to all the stakeholders of web services. This demand asks web service developers to provide services with high QoS and advanced tools for all the activities of web services. Therefore, these services can be considered as meta-web services and we will examine the hierarchy of demands in web services in future work. It should be noted that the activities in web services should be classified in a hierarchical way (main services and subservices). For example, identification, finding, search and matching can be subactivities of web service discovery (Burstein, et al, 2005). Dan, et al. (2004) argues that the subactivities of web service contract consist of
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offering creation, customer order and negotiation, monitoring, billing and reporting. Burstein, et al. (2005) examines the subactivities of web service discovery, engagement, enactment and management. Then we can examine the hierarchical structure of activities or interoperations in web services assuming that publish, find, and bind are the fundamental activities of web services.
FUTURE RESEARCH DIRECTIONS Understanding the demand of stakeholders of web services is a critical factor for further development of web services. This chapter only focuses on demand-driven web services from a demand perspective of the main players in web services: service providers, brokers, and requestors. In fact, these demands from the web service providers, brokers, and requestors not only require to be met from themselves but also from more stakeholders of web services, in particular, the web service developers with the strong background of information communication technology (ICT). They will provide technological solution for the main activities of web service lifecycle such as web service description and discovery (Garcia & Toledo, 2006), composition (Papazoglou, et al, 2006), billing, contracting. For example, the engineering of web service composition and recommendation are a research direction (Papazoglou, et al, 2006). In future work, we will explore implementation issues for engineering of web service composition and recommendation. The proposed demand-driven web service lifecycles are still in a linear form. Providing other forms of demand-driven web service lifecycle is also a research direction. In future work, we will develop demand-driven models for web service lifecycle in a spiral and iterative way with corresponding diagrams, as done in software engineering. Applying intelligent techniques to web services and automating the process stages in the demand-
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driven web service lifecycle is another research direction (Petrie & Genesereth, 2003). In future work, we will integrate web service discovery, composition and recommendation using soft case based reasoning. Demand is an important concept in economics. However, there is less attention in web services. In future work, we will investigate the computing basis of demand and then improve the abovementioned web service lifecycle. For example, we will examine demand as a 4-ary relation (seller, buyer, service, price) from a mathematical and business viewpoint and propose a hierarchical structure for demand-driven e-commerce and demand-driven web services. We will also further analyse the demands between service players, and provide the related instruction/guidance for web service design and development in order to develop demand-driven framework for Web services.
CONCLUSION This chapter first looked at main players in web services, provided a mathematical analysis of demand in web services. It also examined the demand relationship among service providers, brokers and requestors in web services and the demand chain in web services. Then the chapter reviewed web service architectures and provided a demand-driven architecture for web services (DWSOA). It also reviewed web service lifecycles, proposed the demand-driven web service lifecycle for the main players in web services respectively and then discussed the demand-driven web service lifecycles in a unified way. The proposed approach in this chapter can facilitate the engineering and management of web services, and the research and development of web services, e-services, service intelligence and service science. In the future work, besides above-mentioned future research directions, we will develop demand-driven framework for Web services by extending Table 2 to include as many stages or activities of web services life
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cycle as possible. We will also use the proposed approaches to study business models further and try to apply them to Web services design.
ACKNOWLEDGMENT This research is partially supported by the Ministry of Education Hebei, China under a key research Grant No. ZH200815 and other research grants provided by the College of Mathematics and Information Science, Hebei Normal University, China.
REFERENCES
Chaffey, D. (2007). E-Business and E-Commerce Management (3rd ed.). Harlow, UK: Prentice Hall. Cheng, R., & Su, S. Yang, F., & Li, Y. (2006). Using case-based reasoning to support web service composition. In V.N. Alexandrov et al. (Eds.), ICCS 2006, Part IV (LNCS 3994, pp. pp. 87-94). Berlin, Heidelberg: Springer-Verlag. Dan, A., Kuebler, D., & Davis, D. (2004). Web services on demand: WSLA-driven automated management. IBM Systems Journal, 43(1), 136–158. doi:10.1147/sj.431.0136 Deitel, H. M., Deitel, P. J., DuWadt, B., & Trees, L. K. (2004). Web Services: A technical Introduction. Upper Saddle River, NJ: Prentice Hall.
W3C (2004). Web service management: Service life cycle. Retrieved December 26, 2008, from http://www.w3.org/TR/2004/NOTE-web servicelc-20040211/
Dustdar, S., & Schreiner, W. (2005). A survey on web services composition. International Journal Web and Grid Services, 1(1), 1–30. doi:10.1504/ IJWGS.2005.007545
Alonso, G., Casati, F., Kuno, H., & Machiraju, V. (2004). Web Services: Concepts, Architectures and Applications. Berlin: Springer-Verlag.
Erl, T. (2006). Service-Oriented Architecture (SOA): Concepts, Technology, and Design. Upper Saddle River, NJ: Prentice Hall.
Atkinson, M., DeRoure, D., Alistair Dunlop, A., et al. (2004). Web service grids: An evolutionary approach. UK e-Science Technical Report Series. Retrieved July 6, 2009 from http://www.nesc. ac.uk/technical_papers/ UKeS-2004-05.pdf
Ferris, C., & Farrell, J. (2003). What are web services? Communications of the ACM, 46(6), 31. doi:10.1145/777313.777335
Benatallah, B., Reza, H., & Nezhad, M. (2006, July/August). A model-driven framework for web services life-cycle management. IEEE Internet Computing, 55–63. doi:10.1109/MIC.2006.87 Bucchiarone, A., & Gnesi, S. (2006). A survey on services composition languages and models. In Proceedings of the International Workshop on Web Services – Modeling and Testing (Web serviceMaTe 2006), Palermo, Sicily, June 9 (pp.51-63). Burstien, M. (2005). A semantic Web services architecture. IEEE Internet Computing, 9(5), 72–81. doi:10.1109/MIC.2005.96
Garcia, D. Z. G., & de Toledo, M. B. F. (2006). A web service architecture providing QoS management. In Proceedings of the Fourth Latin American Web Congress (LA-Web ‘06) (pp. 189-198). Gisolfi, D. (2001). Web services architect: Part 1: An introduction to dynamic e-business. Retrieved July 8, 2009 from http://www.ibm.com/developerworks/webservices/library/ws-arc1 Glatard, T., Montagnat, J., Emsellem, D., & Lingrand, D. (2008). A service-oriented architecture enabling dynamic service grouping for optimizing distributed workflow execution. Future Generation Computer Systems, 24(7), 720–730. doi:10.1016/j.future.2008.02.011
99
Demand Driven Web Services
Gottschalk, K., et al. (2000). Web Services architecture overview. Retrieved July 15, 2009 from http://www.ibm.com/developerworks/webservices/library/w-ovr Guruge, A. (2004). Web Services: Theory and Practice. Amsterdam: Elsevier Inc. Henderson-Sellers, B., & Giorgini, P. (Eds.). (2005). Agent-Oriented Methodologies. Hershey, PA: Idea Group Publishing. Hoffman, K. D. (2003). Marketing + MIS = EServices. Communications of the ACM, 46(6), 53–55. doi:10.1145/777313.777340 Hung, P. C. K., Li, H., & Jeng, J. J. (2004). Web service negotiation: An overview of research issues. In Proc of 37th Hawaii Intl Conf on System Sciences (pp. 1-10). ICWS. (2009). http://conferences.computer.org/ icws/2009/. Jackson, J., & Mclver, R. (2004). Microeconomics (7th ed.). Australia: McGraw-Hill. Kreger, H. (2001). Web services conceptual architecture (WSCA 1.0), IBM Software Group. Retrieved March 28, 2009, from http://www. cs.uoi.gr/~zarras/mdw-ws/WebServicesConceptualArchitectu2.pdf Kwon, O. B. (2003). Meta web service: building web-based open decision support system based on web services. Expert Systems with Applications, 24, 375–389. doi:10.1016/S09574174(02)00187-2 Ladner, R. (2008). Soft computing techniques for web service brokering. Soft Computing, 12, 1089–1098. doi:10.1007/s00500-008-0277-0
100
Leymann, F. (2003). Web Services: Distributed Applications without Limits: An Outline. In Proceedings Database Systems for Business, Technology and Web BTW, Leipzig, Germany, Feb 26 – 28, 2003, Springer. Retrieved April 1, 2208, from http://doesen0.informatik.uni-leipzig. de/proceedings/paper/keynote-leymann.pdf Limthanmaphon, B., & Zhang, Y. (2003). Web service composition with case-based reasoning. In ACM Intl Conf Proc Series (Vol. 143), Proc. 14th Australasian Database Conf, Adelaide, Australia (pp. 201-208). Miller, G. (2005). NET vs. J2EE. Communications of the ACM, 48(7), 64–67. Narendra, N. C., & Orriens, B. (2006). Requirements-driven modeling of the web service execution and adaptation lifecycle. In S. Madria et al. (Eds.), ICDCIT (LNCS 4317, pp. 314-324). Papazoglou, M. P. (2003). Service -Oriented Computing: Concepts, Characteristics and Directions. In Proceedings of 4th Intl Conf on Web Information Systems Engineering (WISE2003) (pp. 3-12). Papazoglou, M.P., Traverso, P, Dustdar, S. & et al. (2006). Service-oriented computing research roadmap. Retrieved April 4, 2009, from http:drops. dagstuhl.de/opus/volltexte/2006/524/ Petrie, C., Genesereth, M., et al. (2003). Adding AI to web services. In L. van Elst, V. Dignum, & A. Abecker (Eds.), AMKM 2003 (LNAI 2926, pp. 322-338). Pfleeger, S. L., & Atlee, J. M. (2006). Software Engineering: Theory and Practice (3rd ed.). Beijing: Pearson Education, Inc. Pressman, R. S. (2001). Software Engineering: A Practitioner’s Approach (5th ed.). Boston: McGraw-Hill.
Demand Driven Web Services
Rainbird, M. (2004). Demand and supply chains: The value catalyst. International Journal of Physical Distribution & Logistics Management, 34(3/4), 230–250. doi:10.1108/09600030410533565
Tang, X. F., Jiang, C. J., Ding, Z. J., & Wang, C. (2007). A Petri net-based semantic web services automatic composition method. [in Chinese]. Journal of Software, 18(12), 2991–3000.
Rust, R. T., & Kannan, P. K. (2003). E-service: A new paradigm for business in the electronic environment. Communications of the ACM, 46(6), 37–42. doi:10.1145/777313.777336
Tsalgatidou, A., & Pilioura, T. (2002). An overview of standards and related technology in web services. Distributed and Parallel Databases, 12, 135–162. doi:10.1023/A:1016599017660
Schneider, G. P. (2003). Electronic Commerce (4th ed.). Boston, MA: Thomson Course Technology.
Wang, M., Cheung, W. K., Liu, J., Xie, X., & Lou, Z. (2006). E-service/process composition through multi-agent constraint management. In Intl Conf on Business Process Management (BPM 2006), Vienna, Austria (LNCS 4102, pp. 274-289).
Sheth, A. (2003). Semantic web process lifecycle: Role of semantics in annotation, discovery, composition and orchestration. Invited Talk, WWW 2003 Workshop on E-Services and the Semantic Web, Budapest, Hungary, May 20. Singh, M. P., & Huhns, M. N. (2005). Serviceoriented Computing: Semantics, Processes, and Agents. Chichester: John Wiley & Sons, Ltd. Sun, Z., & Finnie, G. (2004). Intelligent Techniques in E-Commerce: A Case-based Reasoning Perspective. Berlin, Heidelberg: Springer-Verlag. Sun, Z., & Finnie, G. (2005). A unified logical model for CBR-based e-commerce systems. International Journal of Intelligent Systems, 20(1), 29–46. doi:10.1002/int.20052 Sun, Z., & Lau, S. K. (2007). Customer experience management in e-services. In J. Lu, D. Ruan, & G> Zhang (Eds.), E-Service Intelligence: Methodologies, Technologies and Applications (pp. 365-388). Berlin, Heidelberg: Springer-Verlag. Sun Microsystems. (2003). Web services life cycle: Managing enterprise Web services, White Paper. Retrieved December 18, 2008, from http://www. sun.com/software Talia, D. (2002). The open grid services architecture: Where the grid meets the web. IEEE Internet Computing, 6(6), 67–71. doi:10.1109/ MIC.2002.1067739
Wang, M., Liu, J., Wang, H., Cheung, W. K., & Xie, X. (2008). On-demand e-supply chain integration: A multi-agent constraint-based approach. Expert Systems with Applications, 34(4), 2683–2692. doi:10.1016/j.eswa.2007.05.041 Waters, D. (2006). Demand chain effectivenesssupply chain efficiencies: A role for enterprise information management. Journal of Enterprise Information Management, 19(3), 246–261. doi:10.1108/17410390610658441 Weiss, G. (Ed.). (1999). Multiagent Systems: A modern approach to Distributed Artificial Intelligence. Cambridge, MA: MIT Press. Wiki (2009). Retrieved April 2, 2009, from http:// en.wikipedia.org/wiki/Demand_(economics). Wilkinson, N. (2005). Managerial Economics: A Problem-Solving Approach. Cambridge: Cambridge University Press. Wu, C., & Chang, E. (2005). A conceptual architecture of distributed web services for service ecosystems. In S. Dascalu (Ed.), 18th International Conf on Computer Applications in Industry and Engineering (CAINE 2005) (pp. 209-214).
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Yao, Y., Yang, F., & Su, S. (2006). Flexible decision making in web services negotiation. In J. Euzenat & J. Domingue (Eds.), AIMSA 2006 (LNAI 4183, pp. 108-117). Zhang, L. J., & Jeckle, M. (2003). The next big thing: Web services composition. In M. Jeckle & L.J. Zhang (Eds.), ICWS-Europe (LNCS 2853, pp. 1-10).
ADDITIONAL READING Bell, M. (2008). Service-Oriented Modeling (SOA): Service Analysis, Design, and Architecture. Chichester, UK: John Wiley and Sons Ltd. Breu, R. Breu1, M., Hafner, M., & Nowak, A. (2005). Web service engineering advancing a new software engineering discipline. In D. Lowe & M. Gaedke (Eds.), ICWE 2005 (LNCS 3579, pp. 8-18). Brown, A., Johnston, S., & Kelly, K. (2002). Using Service-Oriented Architecture and Component-based Development to Build Web Services. Retrieved 10 July 2009, from http://www. ibm.com/developerworks/rational/library/510. html#download Chen, L., & Tao, F. (2008). An intelligent recommender system for web resource discovery and selection . In Ruan, D., Hardeman, F., & van der Meer, K. (Eds.), Intelligent Decision and Policy Making Support Systems (pp. 113–140). Berlin, Heidelberg: Springer. doi:10.1007/978-3-54078308-4_7 Cheng, M.-Y., Tsai, H.-C., & Chiu, Y.-H. (2009). Fuzzy case-based reasoning for coping with construction disputes. Expert Systems with Applications, 36(2), 4106–4113. doi:10.1016/j. eswa.2008.03.025
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Cheng, R., & Su, S. Yang, F., & Li, Y. (2006). Using case-based reasoning to support web service composition. In V.N. Alexandrov et al. (eds.), ICCS 2006, Part IV (LNCS 3994, pp. 87-94). Berlin Heidelberg: Springer-Verlag. Chung, J. Y., Lin, K. J., & Mathieu, R. G. (2003). Web services computing: Advancing software interoperability. Computer, 36(10), 35–37. doi:10.1109/MC.2003.1236469 Costantini, S. (2008). Agents and Web Services. Retrieved April 04, 2009, from http://www. cs.nmsu.edu/ ~epontell/backbone/aug08/content/ Articles/sadri2/paper.pdf Han, W., Xingdong Shi, X., & Chen, R. (2008). Process-context aware matchmaking for web service composition. Journal of Network and Computer Applications, 31(4), 559–576. doi:10.1016/j. jnca.2007.11.008 Jeong, B., Cho, H., & Lee, C. (2009). On the functional quality of service (FQoS) to discover and compose interoperable web services. Expert Systems with Applications, 36(3), 5411–5418. doi:10.1016/j.eswa.2008.06.087 Küster, U., König-Ries, B., Stern, M., & Klein, M. (2007). DIANE: An integrated approach to automated service discovery, matchmaking and composition. In Intl Conf on World Wide Web (WWW2007), May 8–12, 2007, Alberta, Canada (pp. 1033-1041). Lau, R. Y. K. (2007). Towards a web services and intelligent agents-based negotiation system for B2B eCommerce. Electronic Commerce Research and Applications, 6(3), 260–273. doi:10.1016/j. elerap.2006.06.007 Lawler, J. P. (2007). Service-Oriented Architecture: SOA Strategy, Methodology, and Technology. Hoboken: Taylor & Francis Ltd. doi:10.1201/9781420045017
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Lu, J., Ruan, D., & Zhang, G. (Eds.). (2006). EService Intelligence. Berlin, Heidelberg: Springer Verlag. Madhusudan, T., & Uttamsingh, N. (2006). A declarative approach to composing web services in dynamic environments. Journal of Decision Support Systems, 41(2), 325–357. doi:10.1016/j. dss.2004.07.003 Park, C.-S., & Park, S. (2008). Efficient execution of composite Web services exchanging intensional data. Journal of Information Science, 178(2), 317–339. doi:10.1016/j.ins.2007.08.021 Psaila, G., & Wagner, R. R. (Eds.). (2008). ECommerce and Web Technologies: 9th International Conference, EC-Web 2008, Turin, Italy, September 3-4, 2008, Proceedings (LNCS). Berlin Heidelberg: Springer Verlag. Richter, M. M. (2009). The search for knowledge, contexts, and case-based reasoning. Engineering Applications of Artificial Intelligence, 22(1), 3–9. doi:10.1016/j.engappai.2008.04.021 Rust, R. T., & Kannan, P. K. (Eds.). (2002). EService: New Directions in Theory and Practice. Armonk, NY: M.E. Sharpe. Sahai, A., & Graupner, S. (2005). Web Services in the Enterprise: Concepts, Standards, Solutions, and Management (Network and Systems Management). New York: Springer. Song, R., Korba, L., & Yee, G. (Eds.). (2007). Trust in E-services: Technologies, Practices and Challenges. Hershey, PA: IGI Global. Talukder, A. K., & Yavagal, R. R. (2007). Mobile Computing: Technology, Applications and Service Creation. New York: McGraw-Hill Inc. Tatemura, J., & Hsiung, W. P. (2006). Web service decomposition: Edge computing architecture for cache-friendly e-commerce applications. Electronic Commerce Research and Applications, 5(1), 57–65. doi:10.1016/j.elerap.2005.08.001
Ting, I.-H., & Wu, H. J. (Eds.). (2009). Web Mining Applications in E-commerce and E-services. Berlin, Heidelberg: Springer Verlag. doi:10.1007/9783-540-88081-3 Web Services Activity. (n.d.). Retrieved April 3, 2009, from http://www.w3.org/2002/ws/arch/. Wooldridge, M. (2002). An Introduction to Multiagent Systems. Chichester, UK: John Wiley & Sons Ltd. Zhao, J. L., & Cheng, H. K. (2005). Web services and process management: a union of convenience or a new area of research? Journal of Decision Support Systems, 40(1), 1–8. doi:10.1016/j. dss.2004.04.002
KEY TERMS AND DEFINITIONS A Web Service Demand Chain: A chain linking players related to web services, similar to supply chain in e-commerce. For example, the web service requestor demands service consultation from service broker, while the service broker demands web service representation and publication from service provider. The service provider demands the most powerful web service tools from the ICT developer to realize the web service representation and publication. Demand Theory: A part of microeconomics. It examines demand curves, demand equations, demand analysis, demand chain, impact factors on demand, demand estimation and so on. Demand analysis assesses current and projected demand for e-commerce services amongst existing and potential customer segments. Intelligent System: A system that can imitate, automate some intelligent behaviors of human being. Expert systems and knowledge based systems are examples of intelligent systems. Currently intelligent systems is a discipline that studies the intelligent behaviors and their implementations as well as impacts on human society.
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Multiagent Systems: An intelligent system consisting of many intelligent agents. An intelligent agent can be considered as a counterpart of a human agent in intelligent systems. Service Computing: A research field about service science, science intelligence, service technology, service engineering, service management, and service applications. It is the most general representation form of studying service in computing discipline. Service computing and service-oriented computing are used interchangeably. Web Service Architecture: A Web service architecture is a high level description for web services, which is free of concrete implementation of a web service system. Web Service Discovery: The process of searching, matching a machine-processable description of a Web service. It aims to find appropriate web services that meet the requirement of the customers.
Web Service Lifecycle (WSLC): It consists of the start of a web service, the end of web service and its evolutionary stages that transform the web service from the start to the end. Many activities are included in a WSLC such as web service discovery, composition, recommendation and management. Web Services: Generally speaking, web services are all the services available on the Web or the Internet from a business perspective. The first web services were information sources (Schneider, 2003). From a technological perspective, web services are Internet-based application components published using standard interface description languages and universally available via uniform communication protocols. This definition is currently used in the web service community.
This work was previously published in Service Intelligence and Service Science: Evolutionary Technologies and Challenges, edited by Ho-fung Leung, Dickson K.W. Chiu and Patrick C.K. Hung, pp. 35-55, copyright 2011 by Information Science Reference (an imprint of IGI Global).
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Between Supply and Demand: Coping with the Impact of Standards Change Tineke M. Egyedi Delft University of Technology, The Netherlands
ABSTRACT There is a continuous pressure for improvement in e-business. Increasing technical possibilities, new forms of outsourcing, the ongoing integration of business processes, the expansion of value chains, the emergence of new markets and new players; they affect the infrastructure and underlying ICT standards. Contrary to the inherent stability one might expect from standards, maintenance of and change in standards are rule rather than exception. The benefit of standards change is sometimes obDOI: 10.4018/978-1-60960-587-2.ch108
vious. However, it can also pose severe problems (e.g. heavy switching costs and reduced market transparency). This chapter synthesizes research findings on standards change. A conceptual framework is developed to determine under which circumstances standards change is avoidable; if so, in what manner; and if not, which means exist to reduce the negative impact of change. While some change drivers are innovation-related, others stem from the standardization activity itself. They require distinct coping strategies: change control and quality control, respectively. Along these two lines, the chapter discusses strategies to cope with the impact of standards change.
Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
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1. INTRODUCTION For different reasons, change is inherent to e-business and to the ICT sector in general. First, the high rate of technology change has led to a shortening of technology and product life-cycles. The shorter life-cycles are accompanied by a higher rate of standards change and an accelerated standards process. Second, the world-wide diffusion of ICT systems has facilitated the globalization of business and production. The distributed production of goods and services, including outsourcing of research and development (R&D) services, has created an additional demand for ICT standards. This, in turn, challenges the standardization system. Next to the growing number of standards, the need to acquire consensus among a higher number of stakeholders with increasingly heterogeneous preferences is even more challenging. Even if consensus can be reached, the diversified context of those implementing ICT standards increases the likelihood of different implementations. Third, related to the aforementioned two trends is the deregulation of many industries, and the telecommunication sector, in particular. Publicly owned companies have been privatized and legal framework conditions have been substituted by self-regulatory schemes, which include standardization. In sum, the need to develop standards has increased while the stability of the surrounding conditions has decreased. Therefore, the rate of standards change promises to be particularly high. (Egyedi & Blind, 2008) Although standards change is systemic to the field of ICT (Blind, 2008; Egyedi & Heijnen, 2008) and is, as will be argued, not an unproblematic issue, until recently the topic has hardly been addressed. In order to draw attention to a number of studies that have recently been published, this chapter discusses and synthesizes their findings to determine the causes of standards change and how to deal with them. More specifically, the aim is to determine under which circumstances standards change is avoidable; if so, in what manner change
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can be avoided; and if not, which means exist to reduce the negative impact of change. The chapter is structured as follows. In order to explain the problems attached to standards change (section 4), section 2 first argues that stability is crucial to standards. Nevertheless, different kinds of change exist (section 3). Their causes are manifold. However, they seem to fall into two main categories: standardization-internal and external causes (section 5). The causes can be conceptualized and modeled with help of two complementary, theoretical angles: innovation and management (section 6). The heuristic model provides a stepping stone for identifying strategies to cope with standards change: avoiding unnecessary change, reducing its impact ex post, or dealing ex ante with future change in standards design (section 7). To conclude, the chapter’s main findings are re-analyzed in terms of supply- and demand-side drivers of standards change (section 8).
2. THE VALUE OF STANDARDS The term ‘standard’ is used in this chapter in two main senses, namely in the sense of committee standards and in the sense of de facto standards. A committee standard1 is a very specific type of agreement. It is a specification developed by a committee for repeated use, or “a document established by consensus (…), that provides, for common and repeated use, rules, guidelines or characteristics for activities or their results, aimed at the achievement of the optimum degree of order in a given context” (adapted from ISO/IEC, 2004, p. 8).2 This – adapted - definition covers the standards developed by formal standards bodies like the International Organization of Standardization (ISO) and from, for example, standards consortia (e.g. World Wide Web Consortium, W3C) and professional organizations (e.g. Institute of Electrical and Electronics Engineers, IEEE). The second sense in which the term ‘standard’ is often used, refers to de facto standards, that
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is, to specifications that underlie products and services with a significant market share, and to widely adopted practices. An example is the PDF specification of Acrobat Reader3. Initially these specifications were not meant to become standards, that is, to be referred and built to by third parties, but their wide use turns them into such standards. De facto standards, too, undergo changes (e.g. software updates). Standards make life easier because we can refer to them implicitly and explicitly, and thus reduce what economists term informational transaction costs (Kindleberger, 1983).4 Moreover, they create compatibility (i.e. interoperability). They allow products to work together and equipment parts to be replaced. In anonymous markets complementary products can be used together based on standard interfaces. As points of reference, standards coordinate technology development (Schmidt & Werle, 1998). They structure and coordinate the way markets develop. Standards-based clusters of economic activity emerge. An example is the product cluster for paper processing equipment like printers, copiers, and fax machines which is based on the common A-series of paper formats (ISO 216). There are many economic benefits to standards. As Table 1 indicates, standards facilitate trade and allow economies of scale. They increase economic efficiency.
3. CATEGORIES OF STANDARDS CHANGE To be of value, however, standards need to be stable – at least for a certain period of time. The problem is that often they are not. Standards are revised, extended, replaced, succeeded, withdrawn, re-instated, etc.. In short, they are dynamic. Standards dynamics refers to the changes to and interaction between standards, that is, to what happens to standards once they have been set (Egyedi & Blind, 2008). Although its meaning includes competition between standards and the friction between complementary standards, the emphasis in this chapter is on standards that change. There are four categories of standards change: implementation change, standard maintenance, standard succession, and formalization. •
• Table 1. Main functions of compatibility standards (Source: Blind, 2004, adapted) Function of standards
Effect on the market
Information
Reduce transaction costs Correct adverse selection5 Facilitate trade
Compatibility
Create network externalities6 Avoid lock-ins
Variety reduction
Allow economies of scale Build critical mass
•
Implementation change: a change introduced to the standard specification during its implementation in, for example, a product. When a standard is used, that is, implemented in a product, a service or a practice, it may undergo changes. The specification may only partly be implemented in order to suit the local situation (e.g. Timmermans & Berg, 1997); or it may be extended and implemented in a way that ties customers to a vendor. In such situations, where the implementation deviates from the standard, we speak of implementation change. Maintenance change or horizontal dynamics (Gauch, 2008): standards change that results from maintenance activities of standards bodies. It includes developing a new standard edition, a corrigendum, an amendment or a revision; merging standards, splitting them up, withdrawing a standard and re-instating it. Succession: the replacement of one standard by another one in an area of standardization. It includes what may retrospectively be seen to be a next generation standard.
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Where developed by the same committee, standard succession can be viewed as an extension to and special case of standard maintenance. However, different committees and even competing standards bodies may be involved in developing successors. Formalization or vertical dynamics (Gauch, 2008): the result of either ratifying a de facto standard in a standards consortium or a formal standards body (leading to a consortium standard or a formal standard, respectively), or by ratifying a consortium standard in a formal standards body. At stake is increased recognition and endorsement of the de facto or consortium standard.
is an extension of the standard’s life-cycle, as is formalization. Although Figure 1 does not specify sources of change, the category ‘implementation change’ already fore-shadows the importance of the interplay between, on the one hand, standards use, a significant factor on the demand-side of standardization, and, on the other hand, the standard setting, that is, the supply-side. Vendor experience with implementing and localizing standards, and end-user experience with implementations are highly relevant triggers for standards maintenance.
Each category can be plotted onto the standard’s life-cycle (see Figure 1). Figure 1 visualizes the relation between them. From the moment the standard specification has been defined, the cycle of standard maintenance starts. Feedback from implementers may be the reason to revise a standard (dotted arrow); while too many maintenance cycles may indicate that a more radical change is called for, i.e. a new standard. From the perspective of standards change, succession
Change is a double-edged sword. On the one hand, standards change may well be valued positively when it accompanies innovation in science and technology. For example, in the field of medicine new research might result in a changed reference value for medical treatment. It may mean a lower dose of medication and less side-effect for patients. In this case, standards change is a regular occurrence and standards maintenance is part of what Kuhn (1970) calls ‘normal problem
•
4. PROBLEMS OF STANDARDS CHANGE
Figure 1. Four categories of standards change: Implementation change, maintenance, succession and formalization in the extended life-cycle of a standard
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solving’. Some regulatory and policy areas highly depend on standards, and therefore need to find ways to cope with this kind of standards change. The European Union has decided not to include standards in regulation precisely because standards change so often. Re-drafting regulation would require too much time and effort. Therefore, a referential approach has been developed, which allows standards to evolve without affecting the regulatory framework. This referential approach, which was confirmed in 1985 as the New Approach, is still in place. On the other hand, where the need for a standard is expressed, inherently, the need for a certain degree of stability is implied. From this angle standards change poses a problem. While stable standards create transparency and reduce in formational transaction costs, changing them has the opposite effect; it decreases transparency and increases transaction costs. Standards change involves new costs (e.g. costs of updating the standard) and devaluates earlier investments (i.e. sunk cost). It diminishes self-evident interoperability because uncertainty may arise about the interoperability of products complying with different standard versions. To follow, we highlight two difficulties that may arise: the economic costs of switching to the revised standard, and the issue of who actually benefits from and who carries the burden of change. We close this section with two wellrecognized problems: the longevity of digital data and incompatibility between standard-compliant products.
4.1 Switching Costs The work of economists on switching between competing de facto standards (e.g. Farrell & Saloner, 1985) provides a useful theoretical underpinning for understanding the difficulty of switching to a new standard version. The costs involved in switching from one standard to another are called switching costs (e.g. vonWeizsacker,
1982). Literature informs us that whether or not a party switches standards depends in particular on the size of the installed base, the improvements offered by the competing standard, and how quick network externalities are expected to be realized. In addition to a likely need to depreciate earlier investments in terms of time, effort and money, new investments have to be made. If the sum of switching costs, for example, investments in new equipment and the costs of learning how to use a new technology, is assessed as being too high lock-in occurs (Farrell, 1990). Since similar switching costs are involved, thresholds for switching between competing standards also explain the hesitations which people have about switching to a new version of a standard or to a standard successor.
4.2 Who Bears the Costs A core question is who benefits and who bears the costs of standards change. Some parties stand to gain more than others. The stakes are not only distributed asymmetrically between those who develop and change standards (the developers), but also between developers, standard implementers (i.e. those who adopt standards in products, services, regulation, etc.), and those who buy the standard-compliant products and services or are affected by them (end-users such as consumers). Those who initiate the change are seldom the ones who bear its costs. In particular where lack of quality of an initial standard is the reason for a revision, the people responsible may not be the ones to pay (Sherif et al., 2007). As Jakobs puts it Users (…) are the ultimate sponsors of standardization (the costs of which are included in product prices). (…) Moreover, users will suffer most from inadequate standards that will leave them struggling with incompatibilities. (Jakobs, 2005, p. 5) Staying close to home, these last years Microsoft products have become de facto standards in
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both the home and the work environment. They have undergone many updates in response to software bugs and virus attacks, updates which users initially had to act upon (i.e. downloads). In addition, new software releases have kept many large organizations in an almost constant flux of IT projects, which usually not only involved the roll-out of software and adapted configurations but included renewal of the stock of personal computers (Egyedi, 2002). In short: here, as in many cases, not the producer but the consumer bears the costs of change.
4.3 Salient Problem Areas Next to the economic angle on the negative impact of change, there are a number of currently well-recognized problem areas in the field of ICT that illustrate the problematic side of standards change. Examples are, first, the increasingly urgent problem of sustainable digital data. Van der Meer (2008), for example, analyses the difficulty of maintaining access to archival digital data over time (i.e., longevity). The informational, legal, and cultural-historic value of archival data, “… are at risk as a result of standard dynamics”. In most cases changes to standards make it very difficult to retain access. A second example is that of standard-compliant, but incompatible IT products and services (Egyedi, 2008b). In particular implementation change leads to incompatibilities. Incompatible implementations may come about intentionally or unintentionally, for perfectly viable economic or functional reasons, or as part of an aggressive market strategy (embrace-and-extend). But whatever the reason, the consequences are the same. Implementation change undermines the open standards development setting and often results in needless market fragmentation.
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5. CAUSES OF CHANGE If change puts the value of standards at risk and can create serious problems, as the previous sections illustrate, then why do standards change? In order to know how to prevent, reduce and/or, retrospectively cope with the negative impact of standards change, insight is required in causes of standards change. The causes roughly fall into three complementary explanations, each with its own flow of reasoning: • • •
Standards change as part of innovation; Standards change as a market strategy; and Standards change as a learning phase in the standard’s life-cycle.
5.1 Innovation Standards change is endogenous to technology development (Egyedi, 1996). It is an intrinsic part of technology development and as such an unavoidable derivative of innovation. The pressure for change may stem from •
Evolving user requirements, that is, changes in the needs of consumers and organizations. Examples are the requirement for higher speed and more bandwidth in the case of wireless LAN (Jakobs, 2008); for more internet addresses in the case of IPv4 (Vrancken et al., 2008); or for extended facilities (Meer, 2008). In addition, standards use - and localization (Timmermans & Berg, 1997) leads to new problems which then also need to be addressed (Vrancken et al., 2008).
The expected importance of a new functionality is often enough reason to initiate standards change - although in practice the functionality may never be used (e.g. added proprietary standard features such as encryption in the WLAN case; Jakobs, 2008).
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•
•
The emergence of a new technical context. An example is the new possibilities which the web-based environment offered for using standardized mark-up languages (Egyedi & Loeffen, 2008). A new contextof-use sets different requirements. The identification of new application domains. Examples are the intended use of a mark-up language for company-external document exchange (business-to-business), while the focus used to be on managing complex, company-internal document flows (Egyedi & Loeffen, 2008); the expected use of IEEE 802.11 for imaging and voice transmission (IEEE 802.11a; Jakobs, 2008); and expansion of the Dublin Core to make it better suited for more types of digital objects, including software components and cultural heritage materials (Vander, Meer, 2008).
These developments lead to intensified standards maintenance as well as to more radical types of standards succession.
5.2 Market Strategy ICT companies typically use standardization as a competitive tool. A company policy on standards, including standard’s change, should therefore be part of their market strategy7. However, standards change can also be an outcome of market competition. Thus, in the case of wireless LAN competing technologies have led to different standard specifications (IEEE 802.11, 802.11a and 802.11b; Jakobs, 2008). Gauch’s study of changes in the area of DVD recordables illustrates how competition can even spur a standard’s race, and involve a high extent of change. He describes two largely stable, competing groups of companies tied together by patents and shared market interests. The two groups engage in R&D for increased speed and disc capacity to prolong revenue streams from their respective patents. This, in turn, leads
to a string of competing standards versions and initiatives to formalize them (horizontal and vertical dynamics; Gauch, 2008). Standards change is here an outcome of market competition as well as part of a market strategy. In the same vein implementation change can be a company strategy (e.g. embrace-and-extend strategy). A standard may be implemented with proprietary extensions or be otherwise ‘improved’ (as in the case of IEEE 802.11b+ implementations and Access Point that supports 128 bit link layer encryption; Jakobs, 2008); or, alternately, organizations may implement a standard prematurely and comply to a draft standard which is subsequently changed (Jakobs, 2008).
5.3 Standardization Factors Overall standards research ignores life-cycle issues of standardization and the relevance of maintenance therein. In addition to innovation- and market-related factors that give rise to standard updates and revisions, factors intrinsic to the activity of standardization occasion maintenance change. Factors are at work that are standardization-specific and stem from the context in which standards are developed, that is, the supply-side, and implemented, that is, the demand-side. There are four main sources of tension and change (Egyedi, 2008b). The source of change may lie in •
•
• •
A flaw or a weakness in the idea that underlies the standard (e.g. aim at a standard which is too comprehensive to be workable), How the standard process takes place (e.g. not involving an important category of standard users in its development), The standard specification itself (e.g. ambiguous terminology), and The way the standard is implemented (e.g. partial implementation due to cost-constraints).
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For example, a standard which is perceived as too complex for implementers may signal that the standard’s scope has been too wide (Thomas et al., 2008), but also that possibly too many compromises have clouded the standards process. Complex standards may only be partially implemented - as in the case of OSI standards (Egyedi, 2008b). Sometimes revisions are desired because experience with implementing a standard has uncovered ambiguities and omissions. Ambiguities may lead to different implementations and irreproducible outcomes as in the case of Z39.50 (Van der Meer, 2008). Table 2 summarizes a number of salient, standardization-related causes of incompatibility and assigns them to phases in the standards life-cycle. Table 2. Causes of incompatibility and their origin (source: Egyedi, 2008b) CAUSES OF INCOMPATIBILITY
PHASE C= conceptual idea SP= standard process S= standard spec IP=implem. process
Errors, ambiguities, inconsistencies
SP/S
Ambiguity of natural language
SP/S
Missing details, monopoly on tacit knowledge
S/IP
Ill-structured standards
S
Unclear how to handle options
S
Uncertain compatibility of non-binding recommendations
S
Complexity of comprehensive, ambitious standards
C
Too many options and parameters
SP/S/IP
‘Bugward compatibility’
C
Unclear official status of standard’s companion book
S
Single company pushing for standard; weak specs
SP
Overload of standards
C/IP
Deviation from and partial implementation of a standard
IP
Interference between standards
C/IP
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A number of factors influence the level of maintenance change. To note the most salient ones, the timing of standardization with respect to the technology life-cycle is influential (Egyedi & Sherif, 2008). It matters whether the technology to be standardized is mature (responsive standardization) or immature (anticipatory standardization). In the latter case experience with the technology comes after the standard and will sooner lead to revisions (Egyedi & Heijnen, 2008). Technical immaturity not only increases the likelihood of change. It also increases the scope of change. More radical changes to standards may be expected. Incidentally, the same applies to standards that switch development environment and are elaborated in a different standards setting – that is, a different committee or standard body. Such a switch also facilitates the adoption of more radical – and incompatible - changes to the original standard (e.g. XML; Egyedi & Loeffen, 2008). Lastly, although one might assume a direct relation between a low quality standards process, a dire need for maintenance and a high level of maintenance activity, this line of reasoning needs to be put into perspective: some standards bodies adopt a more elaborate and intensive maintenance policy, and are therefore more likely to show a higher number of revisions.
6. HEURISTIC MODEL The aforementioned findings point to two clusters of causes of standards change: the external causes of change typically also identified as causes of technology change in innovation literature (i.e. the innovation and market strategy angle), and the internal causes of change that are specific to the activity of standardization development and use. See Figure 2. With regard to the external causes, ICT standards are intrinsic to ICT. Where there is pressure to innovate in ICT, ICT standards will be subject to the same pressure for change. That is, the forces that lead to technology dynamics,
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Figure 2. External factors lead to technology change and therefore also to standards change. Internal factors in the settings of standard development and implementation may directly cause standards change.
such as regulatory change, market dynamics, and innovations in related technologies, also lead to changes in standards. In Figure 1 these forces are portrayed by the arrow ‘external causes of change’. The internal causes of standards change, which are standardization-specific and stem from the context in which standards are developed and implemented, are evident across all standards areas and directly affect standards. Institutional factors such as weaknesses in committee procedures fall within this explanatory category. The two sets of causes are analytically distinct but, as the figure indicates, not mutually independent: external factors such as a fiercely competitive market may well underlie internal causes of change such as ambiguity in the standard. That is, external causes may intensify internal causes of change. External pressures for technology change - and hence standards change – are difficult to withstand. Standards must follow technology innovation and remain up-to-date. Standards change is therefore unavoidable, and should therefore preferably be
well-orchestrated (i.e. change control). Where internal causes of change are concerned (Table 2), many of them are a consequence of the way the standards process has been managed and can be addressed (i.e. quality control). See Table 3. The distinction between avoidable internal causes and unavoidable external causes points to two different directions for systematically dealing with standards change: measures that focus on the quality of the standards process, and measures that mediate the impact of standards change. These two directions are explored in the following section.
7. COPING WITH THE IMPACT OF CHANGE Sometimes standards change has little impact. For example, the users of the Aachen Wireless LAN had few problems with the transition from IEEE 802.11b to IEEE 802.11g (Jakobs, 2008). However, in many cases revisions and extensions do
Table 3. Drivers for standards change and their implications (source: Egyedi & Sherif, 2008) Drivers for Change
External Causes
Internal Causes
Source of change
Co-evolution with technology
Standardization process
Characteristics of change
Inevitable
Consequence of a standardization management process (intentional or accidental)
Framework
Innovation
Management and business
Overall aim
Create up-to-date standard
Create a stable standard
Management objectives
Change control
Quality control
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create difficulties. For example, different standard versions may become competitors as in the case of the compatible short-term solution to IPv4 addressing problems (i.e. NAT) and the incompatible long-term solution (i.e. IPv6). Or, in the case of Z39.50, different standard implementations may lead to different query results. If a query result is later needed to account for an important decision and cannot be reproduced, this may have legal repercussions (Van der Meer, 2008). What means are there to cope with the adverse impact of standards dynamics? Literature analysis points to ad hoc and to systematic strategies, and strategies that try to prevent problems from occurring (ex ante) and those that try to deal with them ex post. See Table 4.
7.1 Ex Post Measures Standards change cannot be always be prevented. In such a situation, the main problem which implementers and end-users must deal with is market fragmentation and lack of interoperability between different standards versions, generations and implementations. The solution depends on the type of incompatibility concerned. In data communication, for example, bridges, multi-protocol stacks and routers are used to re-create interoperability between competing standards (Egyedi & Loeffen, 2008). More in general, in the field of ICT and consumer electronics multiprotocol implementations are made, that is, single devices in which competing standards are implemented (Gauch, 2008). In all these solutions producers and users of one standard still have access to the
market segment of the competing standard and its externalities. They reduce the consumer’s fear that the market will tip towards the competing standard leaving them with an obsolete technology. However, apart from the extra costs involved, Gauch argues that these solutions sustain market competition and fragmentation. Since they allow consumers to benefit from the externalities of both markets, there is no urgent need to integrate standards and markets (e.g. DVD recordables; Gauch, 2008). A similar phenomenon is at stake with the dual stack implementation of IPv4 and IPv6 (Vrancken et al., 2008). Although aimed to ease migration from IPv4 to IPv6, the dual stack lessens the need to migrate because it allows coexistence. Inefficiencies remain. Where the sustainability of digital data is concerned, there are a number of partial and temporary solutions (Van der Meer, 2008): data refreshment, migration and conversion, and the emulation of earlier data handling devices. The emulation option is required if there is no strategy to archive and update the data handling devices, as was the case with tools that could handle ODA/ ODIF (Van der Meer, 2008). Although crosswalks between a standard and its successor sometimes seem possible (e.g. from DC to DCQ; Van der Meer, 2008), the results of such efforts are likely to be ambiguous - as were the results of multiple efforts to re-establish compatibility between SGML and its successor XML (Egyedi & Loeffen, 2008). In principle these ex post measures temporarily resolve the adverse effects of standards dynamics. Moreover, in rapidly evolving fields of technology
Table 4. Strategies for coping with standards change Type of Solutions
Ad hoc
Systematic
Ex ante
-
Quality standards process Flexible, future-proof standard design
Ex post
Patchwork: converters, bridges, multi-protocol stacks, etc.
Downward compatibility
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‘temporariness’ need not always pose a problem. But they are usually costly and laborious, and are often unsatisfactory because they only solve part of the problem and do so inadequately.
7.2 Quality of the Standards Process Standardization-specific, internal causes of standards change can to large degree be avoided by improving the quality of the standards process (Sherif et al., 2007). Quality standards may sometimes take longer to develop but are more stable and therefore less disruptive for the market. Improving the quality of the process means intervening in the causes of dynamics. As indicated in Table 2, there are numerous examples of internal causes of standards change, causes that can be traced back to the scope of the standards project, the standards process, the standards specifica-
tion, and the implementation process. There are several options open to standards management for addressing these internal causes and intensifying quality control measures. A number of suggestions are made in Egyedi (2008b). See Table 5. Paying attention to the quality of the standards process will not always be able to prevent change. First of all, standards development is not a onesize-fits-all occurrence. Besides, there are design and participation dilemmas which by definition cannot be fully resolved. Learning and feedback is part of the process and will often lead to changes. Moreover, standards work is difficult to manage because there is no real hierarchy between the voluntary committee participants. It is difficult for the committee chair to manage – much more so than projects usually are (Sherif et al., 2007). Sometimes standards change is a by-product of the chosen standards strategy. Quick and dirty
Table 5. Recommendations Institutional measures towards reducing standard-based interoperability problems Drafting of standards €€€• provide institutional support for editors and rapporteurs on standards engineering €€€• involve technical editors €€€• use pseudo-code or formal languages in a focused way €€€• adopt a unified naming convention €€€• clarify the type of options involved €€€• specify how to deal with options (e.g. profiles) €€€• specify the consequences of (not) implementing options €€€• make explicit the rationale that underlies choices in the specification €€€• issue a reference guide with the standard €€€• organize wider scrutiny of the standard €€€• translate the standard to uncover ambiguities €€€• coordinate the interrelated processes of different standards bodies Pre-implementation €€€• validate standards before implementation in products (“walk throughs”) €€€• develop a reference implementation / pre-implementation €€€• develop a reference environment €€€• include standard conformance and interoperability testing €€€• organize interoperability events with different vendors (e.g. plug tests) €€€• organize dialogues between standard developers and implementers Post-implementation €€€• supply test suites €€€• improve consistent use and integrity of standards with e.g. compliance and interoperability conformance statements, compatibility logos, certification programs Standards policy €€€• prioritize implementability as a standard’s requirement €€€• reconsider the desired level of consensus across all areas
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standardization allows standardizers to make an early claim to market, but it also increases the likely need for improvements at a later stage.
7.3 Standards Design: Downward Compatible & Future-Proof Whereas high quality standards lessen the need for change, standards change is to a large degree unavoidable and even desirable where standards need to co-evolve with technology innovation. In many cases standards change actively contributes to the development of technologies and markets. In such situations, the only option is to intervene on the negative impact of standards change and design standards in way that causes the least upheaval. Two design strategies, each departing from a different point in time, would seem to be most promising: designing in downward compatibility and developing ‘future-proof’ standards (i.e., robust and flexible). Standards change can lead to technology disruption and fragmentation between the markets of the successor standard and its predecessor. Whether or not this will happen depends to a large degree on whether standard versions and successors are downward compatible and grafted. The incremental nature of most changes makes grafting8 a viable option and reduces the negative impact of change. In particular where the longevity of digital archival data is concerned, grafting would seem the most viable ex ante strategy (Van der Meer, 2008). Grafting also partly alleviates the problem that most standards are not stand-alone artifacts but part of a web of interrelated standards. To keep abreast with changes in the ‘core’ standard, related standards must be updated. Grafting lessens the pressure for change on related standards. However, it comes at a cost. Sometimes a less burdensome clean start is preferred, as the SGML- XML succession showed (Egyedi & Loeffen, 2008). ‘Downward compatibility or a clean start’ is one of the fundamental dilemmas in standards design.
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Backward compatibility is easier said than done (Thomas et al, 2008). The backward compatibility effort itself can become a source of problems. For example, when the STEP standard was introduced in the UK defense environment, end-users saw too few differences between the implemented versions. Moreover, compatibility between the versions was not fully achieved, which led to extra work and delays in the project (i.e. 1999, 2001, 2006 editions of AP224; Thomas et al). Furthermore, there is the problem of seeking backward compatibility with legacy systems that contain bugs - as in the case of AP224 with UNIX (Thomas et al., 2008) and CSS1 in Internet Explorer (Egyedi, 2008b). ‘Bugward compatibility’, as this is referred to, lays a burden on current and future interoperability with other systems. The second design angle relevant for coping with standards change is the development of ‘future-proof’ or robust ex ante standards. The need for robustness applies to sets of interrelated standards as well as individual standards. Where information architectures or otherwise composed systems are concerned, a modular and layered design approach to standardization is a well-tested and proven concept. In essence, the idea is here that modularity and layering allow one standard to evolve without affecting related standards. The archetypical example for layering is the Open Systems Interconnection reference framework for data communication (Tanenbaum, 1989). In respect to separate standards, standards must be flexible to be able to cater to uncertain future needs. What makes a standard flexible? Although there have been incidental studies exploring the characteristics of flexible system and product standards (Egyedi & Verwater-Lukszo, 2005), it is an area of research that deserves more systematic attention in the context of standards dynamics.
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8. CONCLUSION
ABBREVIATIONS
The occurrence of change in ICT standards is caused by an interplay of supply- and demandside factors. In this respect, e-business standards are no exception. On the demand-side, evolving user requirements, new technological possibilities, and new application domains create a pull for innovation-driven standards change; while experience gained with implementing standards in products and services and localizing standardcompliant systems make manifest the need to improve them. On the supply-side of setting standards, sources of change may play at any stage of the standards life-cycle (i.e., problems with the scope of the standard, the standards process, the specification, and the implementation process). In this chapter, these standardization-related factors, together with implementation feedback (a demand-side factor), have been categorized as internal causes of change. The resulting changes can partly be avoided by improving the standards process, that is, by improved quality control. However, standards change that is caused by external, demand-side factors, such as the emergence of new technological opportunities, is in the long run inevitable – and desirable where it supports innovation. To cope with the negative side of change such as switching costs and reduced transparency, change control is required. There are ad hoc as well as more systematic approaches to support change management. Some of them cope with change ex post and focus on repairing compatibility; while others try to prevent incompatibility by including change requirements in standards design. In particular in the latter area, that is, the area of developing ‘future-proof’, robust and flexible ex ante standards, much work still needs to be done to minimize the negative effects of standards change.
CSS: Cascading Style Sheets DC: Dublin Core DCQ: Dublin Core Qualifi ers DVD: Digital Versatile Disc ICT: Information and Communication Technology IEC: International Electrotechnical Commission IEEE: Institute of Electrical and Electronics Engineers IPv4: Internet Protocol version 4 IPv6: Internet Protocol version 6 ISO: International Standardization Organization IT: Information Technology LAN: Local Area Network NAT: Network Address Translation ODA: Open Document Architecture ODIF: Open Document Interchange Format OSI: Open Systems Interconnection R&D: Research and Development SGML: Standard Generalized Markup Language STEP: STandard for the Exchange of Product model data W3C: World Wide Web Consortium WLAN: Wireless Local Area Network XML: EXtensible Markup Language
ACKNOWLEDGMENT I sincerely thank the contributors to the NO-REST workpackage on standards dynamics (EU project), the Europeon Commission and Sun Microsystems for their valuable contributions and financial support and the two anonymous reviewers of this chapter for their constructive comments. This chapter is a strongly revised version of and extension to Egyedi (2008a).
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REFERENCES Blind, K. (2008). Factors influencing the lifetime of telecommunication and information technology standards In T. M. Egyedi & K. Blind (Eds.), The dynamics of standards (pp. 155-177). Cheltenham, UK: Edward Elgar. Egyedi, T. M. (1996). Shaping Standardisation: A Study of Standards Processes and Standards Policies in the Field of Telematic Services. Delft, the Netherlands: Delft University Press. Egyedi, T. M. (2002). Trendrapport Standaardisatie. Oplossingsrichtingen voor problemen van ITinteroperabiliteit. Delft: Ministerie van Verkeer en Waterstaat, Rijkswaterstaat/ Meetkundige Dienst. Egyedi, T. M. (2008a). Conclusion. In T. M. Egyedi & K. Blind (Eds.), The dynamics of standards (pp. 181-189). Cheltenham, UK: Edward Elgar. Egyedi, T. M. (2008b). An implementation perspective on sources of incompatibility and standards’ dynamics. In T. M. Egyedi & K. Blind (Eds.), The dynamics of standards (pp. 181-189). Cheltenham, UK: Edward Elgar. Egyedi, T. M., & Blind, K. (2008). Introduction. In T. M. Egyedi & K. Blind (Eds.), The dynamics of standards (pp. 1-12). Cheltenham, UK: Edward Elgar. Egyedi, T. M., & Heijnen, P. (2008). How stable are IT standards? In T. M. Egyedi & K. Blind (Eds.), The dynamics of standards (pp. 137-154). Cheltenham, UK: Edward Elgar. Egyedi, T. M., & Loeffen, A. (2008). Incompatible successors: The failure to graft XML onto SGML. In T. M. Egyedi & K. Blind (Eds.), The dynamics of standards (pp. 82-97). Cheltenham, UK: Edward Elgar.
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Egyedi, T. M., & Sherif, M. H. (2008). Standards’ Dynamics through an Innovation Lens: Next Generation Ethernet Networks. Paper presented at the Conference Name|. Retrieved Access Date|. from URL|. Egyedi, T. M., & Verwater-Lukszo, Z. (2005). Which standards’ characteristics increase system flexibility? Comparing ICT and Batch Processing Infrastructures. Technology in Society, 27(3), 347–362. doi:10.1016/j.techsoc.2005.04.007 Farrell, J. (1990). Economics of Standardization. In J. L. B. H. Schumny (Ed.), An Analysis of the Information Technology Standardization Process. Farrell, J., & Saloner, G. (1985). Standardization, Compatibility and Innovation. The Rand Journal of Economics, 16, 70–83. doi:10.2307/2555589 Gauch, S. (2008). + vs. –, Dynamics and effects of competing standards of recordable DVD media In T. M. Egyedi & K. Blind (Eds.), The dynamics of standards (pp. 47-67). Cheltenham, UK: Edward Elgar. ISO/IEC. (2004). ISO/IEC Directives, Part 2: Rules for the structure and drafting of International Standards. Geneva: ISO/IEC. Jakobs, K. (2005). The Role of the ‘Third Estate’ in ICT Standardisation. In S. Bolin (Ed.), The Standards Edge: Future Generation: The Bolin Group. Jakobs, K. (2008). The IEEE 802.11 WLAN installation at RWTH Aachen University: A case of voluntary vendor lock-in. In T. M. Egyedi & K. Blind (Eds.), The dynamics of standards (pp. 99-116). Cheltenham, UK: Edward Elgar. Jones, P., & Hudson, J. (1996). Standardization and the Cost of Assessing Quality. European Journal of Political Economy, 12, 355–361. doi:10.1016/0176-2680(95)00021-6
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Kindleberger, C. P. (1983). Standards as Public, Collective and Private Goods. Kyklos, 36, 377– 396. doi:10.1111/j.1467-6435.1983.tb02705.x Kuhn, T. S. (1970). The structure of scientific revolutions (2 ed.). Chicago: University of Chicago Press. Reddy, N. M. (1990). Product of Self-Regulation. A Paradox of Technology Policy. Technological Forecasting and Social Change, 38, 43–63. doi:10.1016/0040-1625(90)90017-P Schmidt, S. K., & Werle, R. (1998). Co-ordinating Technology. Studies in the International Standardization of Telecommunications. Cambridge, Mass: MIT Press. Sherif, M. H., Jakobs, K., & Egyedi, T. M. (2007). Standards of quality and quality of standards for Telecommunications and Information Technologies. In M. Hörlesberger, M. El_Nawawi & T. Khalil (Eds.), Challenges in the Management of New Technologies (pp. 427-447). Singapore: World Scientific Publishing Company.
v Weizsacker, C. C. (1982). Staatliche Regulierung - positive und normative Theorie. Schweizerische Zeitschrift fur Volkswirtschaft und Statistik, 2, 325–243. Vrancken, J., Kaart, M., & Soares, M. (2008). Internet addressing standards: A case study in standards dynamics driven by bottom-up adoption. In T. M. Egyedi & K. Blind (Eds.), The dynamics of standards (pp. 68-81). Cheltenham, UK: Edward Elgar.
ENDNOTES 1
2
3
4
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Tanenbaum, A. S. (1989). Computer Networks (2 ed.): Prentice-Hall. Thomas, J. W., Probets, S., Dawson, R., & King, T. (2008). A case study of the adoption and implementation of STEP. In T. M. Egyedi & K. Blind (Eds.), The dynamics of standards (pp. 117-134). Cheltenham, UK: Edward Elgar. Timmermans, S., & Berg, M. (1997). Standardization in Action: Achieving Local Universality through Medical Protocols. Social Studies of Science, 27(2), 273–305. doi:10.1177/030631297027002003 v Meer, K. d. (2008). The sustainability of digital data: Tension between the dynamics and longevity of standards. In T. M. Egyedi & K. Blind (Eds.), The dynamics of standards (pp. 15-27). Cheltenham, UK: Edward Elgar.
The term ‘open standards’ is avoided because it raises more questions than that it provides answers, and the term committee standard suffices for our purposes. For the interested reader we point to Krechmer (2006), who distinguishes different aspects of openness and angles (openness from the perspective of standard creators, implementers, and users). The phrase “and approved by a recognized body” was omitted from the definition in order to widen its applicability to other committee standards as well. In 2005 a PDF version became an ISO committee standard. Transaction costs are costs like the time and resources required to establish a common understanding. Standards reduce transaction costs of negotiation because “both parties to a deal mutually recognize what is being dealt in...” (Kindleberger, 1983, p. 395) Standards reduce transaction costs between producers and costumers by improving recognition of technical characteristics and avoidance of buyer dissatisfaction (Reddy, 1990). They reduce e.g. search costs since there is less need for customers to spend time and money evaluating products (Jones & Hudson, 1996). Adverse selection takes place if a supplier of inferior products gains market share through
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6
7
price competition because the supplier of high quality products has no means to signal the superior quality of its products to consumers. Quality standards support the latter in signaling activities, foster the co-existence of low and high quality market segments, and therefore minimize the likelihood that consumer selection is based on wrong assumptions. The term network externalities refers to the situation that every new user in the network increases the value of being connected to the network (Farrell & Saloner, 1985). Because company strategies on standardization are usually not made public, it is un-
8
certain whether company policies include a standards change paragraph. Since standards change has not yet been widely addressed, its business relevance may not have drawn their attention. The term grafting refers to the process of developing a standard (successor) based on another standard (predecessor) with the intention to improve the latter’s functionality and/or usefulness in other respects (e.g. ease or cost of implementation) while preserving compatibility and interoperability with its predecessor’s context of use (Egyedi & Loeffen, 2008, p.84)
This work was previously published in Information Communication Technology Standardization for E-Business Sectors: Integrating Supply and Demand Factors, edited by Kai Jakobs, pp. 171-186, copyright 2009 by Information Science Reference (an imprint of IGI Global).
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Chapter 1.9
Engagement, Immersion, and Learning Cultures:
Project Planning and Decision Making for Virtual World Training Programs Christopher Keesey Ohio University, USA Sarah Smith-Robbins Indiana University, USA
ABSTRACT The decision to use a virtual world for training and development is a potentially treacherous one. Legal issues, adoption barriers, a pedagogical design complexities often inhibit true engagement and adoption. Strategic planning is required for every step from the choice of a virtual world to instruction design and user adoption. In this chapter, Keesey and Smith-Robbins offer guide to avoiding common pitfalls while suggesting a plan for maximum
training benefit in virtual world implementations. Included are considerations about sound pedagogical practices, advice regarding the assessment of a corporate culture’s ability to engage in a virtual world, as well as recommendations for alleviating common fears and concerns. Special attention is paid to the complexities of virtual world cultures as they interact with organizational cultures. Finally, the authors offer a rubric to aid training designers evaluate whether a virtual world is the right choice for their organization through a series of question and adoption concerns.
DOI: 10.4018/978-1-60960-587-2.ch109
Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
Engagement, Immersion, and Learning Cultures
THE CHALLENGE OF VIRTUAL WORLD VENTURES The metaverse is littered with the corpses of failed corporate forays into developing virtual world presence. From late 2006 to the present, companies such as Coke, Reebok, Adidas and many others launched spectacular three-dimensional failures. These environments appeared to have little beyond a simple presence or conglomeration of slick modern structures, lacking adequate planning for how such a world could provide real Return on Investment (ROI) beyond an initial flurry of wild eyed journalists racing to be the first the report the official announcement of web 2.5, 3.0, 3.5 or whatever new marketing moniker had just been devised. Many of these industry players were guilty of the same offenses that were committed only 10 years ago during the height of the Internet bubble. Remember the rush of the wind generated by the stampede of anyone even capable of plopping a sub-par and sub-planned website onto the internet in 1997? Remember the subsequent bubble burst short years later following that wind of folly? Indeed, recent Gartner research statistics show that nine out of ten business ventures into virtual worlds will fail. Many virtual world naysayers are quick to utilize research data like this in support of a presupposed incompatibility between industry and virtual world technologies. Ultimately these failures were the result of one or a combination of missteps all leading down the same path of lack of proper research, knowledge, information and planning for proper implementation of a virtual world for adding value in the enterprise. Yet, regardless of the failure rates thus far by business in virtual worlds, Gartner Research also estimates that an over-riding majority of companies will utilize a virtual world within their enterprise by the year 2012. Therefore, the challenge for businesses today is to first identify if a virtual world can offer the kind of value add to justify the investment. Second, if it is determined
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that there are business functions/processes where a virtual world can increase efficiencies, shave costs, or provide value added, then the company must identify proper planning points to ensure that the initiative will not only succeed but also be continually supported by and provide support back into the enterprise.
THE BEST CORPORATE TRAINING PROGRAMS FOCUS ON THE END-USER Corporate training programs are one component of organizational management that could stand to benefit from properly planned utilization of virtual world technology. For example, one of the authors can remember back to 2001 and their first forced entry into a corporate LMS. Not only was completion of the training program required for retaining one’s job, but it was thought that the program would teach participants how to perform required job functions more effectively and efficiently. At the time, the whole experience was abdominally boring, merely consisting of pageturners and test-taking. That experience in 2001 was not designed for the learner. It was designed for the training managers and for human resources. While it did a great job of collecting data that could subsequently be utilized by trainers and managers, it did a horrible job of training this author or any other associate of the company because it wasn’t designed for the end-user or learner. Since that time, traditional corporate learning experiences across many companies have greatly improved, as training managers and corporate instructional designers conceived and implemented far more engaging, learner-center approaches to employee training. However, many of the early corporate builds in virtual worlds still lack the same consideration of the end-user. They seemed to have been implemented with little end-user focus at their mission core and in-such served no purpose, added no value, and ultimately ended up
Engagement, Immersion, and Learning Cultures
as visually pleasing ghost-towns. Imagine designing a feature-rich enterprise software application without first engaging in a host of ethnographic studies of your end-user or of how the potential software could add efficiency to their individual process and subsequent company process. Training initiatives deserve and are most often implemented following similar study of the user, in this case the learner. We study outputs and outcomes to identify training or knowledge gaps or processes where training could close said gaps and add efficiency and value. In the case of a virtual world training experience the scope of research should be even more complete. Ideally, study of the users would happen over multiple levels including training needs assessments and user/training interface study. Additionally, with existing virtual worlds that have existing cultures and norms an additional ethnographic study and intimate knowledge of the world within which you will be delivering the learning experience is critical.
VIRTUAL WORLDS AND CULTURAL SENSITIVITIES Simply from a cultural integration standpoint, moving an organization or a company into an existing virtual world platform has a few similarities to that of moving a company, organization or for that matter an individual into a foreign country. There is more to it than simply plopping structures, machines, processes and yourself into your new location and resuming operations as you did in other contexts. Rather, there are multiple layers to this cultural integration, all of which begin with doing a substantial amount of research just as you would before leaving for a foreign country. Additionally, you will have an entirely different set of cultural considerations depending on the mission of your virtual world presence, the public visibility, and the level of openness and outward faces.
Marketers learned some tough lessons early on about the perception of their brands during the early rush to enter Second Life. They quickly learned the difference in the perception of their brands within virtual world from the more traditional channels both online and offline. (http:// www.websitemagazine.com/content/blogs/posts/ articles/second_life_metaverse.aspx) Something as simple as a highway billboard or a webpage banner advertisement – items that are a part of the normal landscape in our online and offline everyday lives – are wildly out of place in a virtual world environment. They’re the equivalent of a real life elevator having a “Teleport” button. There are practical reasons for this. Virtual world users are not slow moving sightseers. They are flying and teleporting from place to place, hungry for interaction with other avatars. Buying is happening, but it is often for the sake of supplementing a social collaboration experience and not simply for the sake of buying something. (http:// www.kzero.co.uk/blog/?p=854) This is a different mode of consumption than that of an individual stuck in a traffic jam on their way home from work to watch television, in which case evoking thoughts of a bigger, better television via a billboard would be more fitting. When organizations attempt to employ virtual worlds in a manner that ignore these cultural sensitivities, the inhabitant community may respond. Indeed, transgressions against the unique ethnographic realities of these spaces has led to amusing stories of marketers having their billboards buried by virtual world residents under virtual forests or graffiti. The take away here is that regardless of your mission, an out-of-place, and non-relevant presence within the virtual world culture is quickly identified by residents and often rebelled against – either within the virtual world itself or in subsequent postings across other web 2.0 channels, such as blogs, Facebook or Twitter. Therefore, learning designers can themselves learn a great deal from the early forays by marketers into Second Life and other platforms. Substantial
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research and exploration of cultural intricacies during the definition of your project will greatly increase your chances of positively impacting both your organization and the world of which you will become a part. If you are utilizing a consumer focused platform such as Second Life or Active Worlds, don’t limit yourself to simply reading and exploring the greater environment. Explore the potential “settlement” location for your organization. Introduce yourself to your potential neighbors and acquaint yourself with their activities, goals and traffic. This advice is already understood within a real life context (for example, you probably do not want to move your fortune 500 or university training environment next door to a region of strip bars); the same rules apply in the metaverse. Furthermore, in devising a setting for your organization’s virtual presence, you can seek a location offering neighbors that may positively supplement the learner experience by providing greater occasion for extended community opportunities. For example, imagine locating your company’s supply chain orientation simulation next to a group of your suppliers in the same virtual environment; this could allow for collaboration and discussion that may improve the efficiencies of all those involved. This idea of community – which is not a new concept in learning circles – is one that must be greatly considered. In an ideal world, learning does not happen in a vacuum regardless of the medium of delivery. The question for those implementing a virtual worlds solution is how much of the community building opportunities of any particular virtual world culture will you leverage, what parts of that virtual world culture will be a benefit to your learning outcomes and what parts will be a hindrance. Further, in answering these questions, it is quite important to keep in mind the interactive nature of your company’s learning community: is it primarily asynchronous or synchronous?
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KNOWING AND BUILDING ON THE STRENGTHS OF VIRTUAL WORLDS Virtual Worlds are Social For example, let’s say your organization is currently sustaining learning communities across multiple time-zones via discussion threads, wikis or other shared documents. If you wanted to consider moving these activities into a virtual world, there would be a number of technological and community-based concerns to keep in mind. First, virtual world culture is at its most vigorous and vibrant when residents are being actively social. Virtual worlds, specifically those directed at the consumer such as Second Life or Active Worlds ARE social networking applications. Many virtual worlds have individual profiles, buddy lists, online status and a variety of other features to enable social activities. Further, they add the “world” element to social networking that allows for play amongst residents. Let’s not forget that while virtual worlds are not games, they are a distant cousin and were born with similar DNA. Play is an important part of collaboration and social interaction. Second, most virtual world residents are not in the world to read large swaths of text and will generally avoid reading large documents for a variety of reasons, one of the most important being related to readability and usability. Outside of the dialogue text from an active conversation, reading content or discussion threads is more preferable in a readable window as opposed to on the face of a three-dimensional structures. Therefore, if document sharing and collaboration are a large part of your training activities you will want to select a virtual world platform that is best suited for this purpose. Platforms such as QWAK and OLIVE by Forterra Systems Inc. are currently better suited to facilitate document collaboration naively or through third party plugins. Second Life is not strong with document collaboration and large quantities of text. However,
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Second Life, when teamed with your LMS can be quite effective.
add value for customers, employees, and organizations as a whole.
Virtual Worlds are Active
Considerations for the Synchronous Learning Community
Some very effective learning experiences can be delivered in the LMS with learners being sent out to participate in unique, value adding activities. These activities may include items such as self-paced games or process simulations to help explain simple global concepts, all of which can be built to supplement current outcomes addressed through your LMS. In turn, such activities may then drive more detailed discussion and application to your organization within the established learning community environment. Additionally, if your game or process simulation is not ripe with enterprise secrets, it may provide a great opportunity to involve the greater community of the virtual world in which your organization is based. Such opportunity will drive positive brand extension around the value that you have added to the community at large. Indeed, nothing will get blogged and Tweeted faster by virtual world residents than “I just had a great experience today.” Further, as experiences go, no experience is quite as popular to virtual world residents as the event. In fact, this element of virtual worlds is so popular that “Event Planning” is listed as one of six skills that Second Life residents publicize in their personal profiles. Entire companies are built and seeing profits from planning, organizing and delivering events for other companies within virtual worlds. Moreover, established real world companies can are also beginning to reap the cost benefits of virtual world meeting and conferences: IBM’s Academy of Technology recently saved $320,000 by holding an event in Second Life. The figure was reached by cutting $250,000 in travel costs and a further $150,000 inproductivity gains. (http://www.virtualworldsnews.com/2009/02/ ibm-saves-320000-with-second-life-meeting. html, n.d.) Bottom line: Events can substantially
Alternatively, if your organization’s learning communities are based from synchronous activities and collaboration (whether online or offline), you should plan an initial deployment that builds on your existing model and uses the strengths of the virtual world, namely the playfulness of the culture.
Virtual Worlds are Playful One interesting training example that has been fairly seamlessly moved from the synchronous classroom environment to the synchronous virtual world environment is the Six Sigma Catapult experience. Initially, the catapult experience was delivered around synchronous classroom discussions for identifying critical variables that will maximize the distance traveled by the loaded projectile.(http://www.pscoe.gov.sg/repository/ open/2/522/Training.htm, n.d.) The outcomes are then tied to greater six sigma concepts for improvement in product development. In this example, we see how virtual worlds can provide a wonderful framework where a playful activity fits and allows for distributed delivery. Subsequently, it can be argued that the exercise takes on an even more engaging tone as individuals launch their co-worker’s avatars hundreds of meters into the air to howling laughter, a feat that is not a healthy option for the real classroom.
Virtual Communities Carry Real Expectations Beyond the preparation for how your learning experience will fit your organizational culture and visa versa one of the greater considerations is preparing learners and instructors for how they
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will fit as individuals into the culture. Again, the similarities of preparing for travel and integration into the culture of a foreign country are loosely applicable. A good or bad experience traveling abroad can often be tied to the preparedness of the individual for the unique cultural norms of the culture within which they will be spending time. Poor preparation can leave the traveler feeling isolated, alone and out of place. However, proper planning can help travelers prepare mentally for confronting any cultural differences, allowing them to instead focus on more rewarding activities, such as collaboration with and learning from the people of the other culture. Just as when traveling abroad, instructors and learners must prepare for cultural expectations such as dress and language, both verbal and nonverbal. Though it may seem superficial to the new virtual world resident (“newbie”) to have to consider the appearance of their avatar, such a consideration is really no different than considering what to wear to a meeting in the real world; there is a cultural context in which appearance carries meaning. Avatars adorned in the stock clothing and hair who have taken no time to personalize their avatar will be subject to certain assumptions by other avatars, be they founded or not. Resident avatars will speak differently to those assumed to be newbies. They may even avoid such persons altogether if time is of the essence and an unsolicited training session in virtual world etiquette is not in the cards for the day. Is this really any different than entering a boardroom of upper-level executives for a strategy meeting in your jeans and tee-shirt having not washed or styled your hair that morning? Assumptions will be made, right or wrong.
Virtual World Etiquette Requires a New Skill Set Overall, virtual environments are hyper-friendly and are, at their core, social environments. Be
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prepared to for people to say “hi” and to address you by avatar name. Often new residents are taken aback by this and act as they might on the streets when approached by a stranger. These are two of many intricacies of living and working in the virtual world. The most successful organizations prepare their employees for the intricacies of virtual world collaboration through substantial cultural orientation experiences. One of the best examples of systematic preparation for most effective virtual world outcomes is implemented by World2Worlds, an event planning and coordination company that has worked with multiple organizations on virtual world roll-outs and virtual world events. World2Worlds habitually schedules a barrage of orientation meetings that first get new residents comfortable with often complex interface controls, then further hones their communication abilities, and then finally steers residents to options for avatar customization. All this is done to prevent cognitive overload when the user attends a virtual event, training session other experience, allowing him to focus on the intended target outcomes. It is highly encouraged that any company moving into virtual world delivery of training or other collaboration has a scheduled “train of adoption” where a group of experienced early adopters are leading trainers and subsequently, trainers are leading learners through the intricacies of becoming experienced residents. Much like traveling abroad, it is so much more enjoyable to initially walk the streets of a foreign environment with someone familiar with the landscape and cultural considerations to show you the ropes. To reiterate, each virtual world platform is a unique culture inhabited by equally unique residents. They have unique cultural mores that are partly driven by features and abilities given by the coding authority and partly as the outcome of residents developing certain collectively accepted rules that enhance the efficiency and enjoyment of life in that particular world. If this culture is the pallet or shell for a learning experience then
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lacking intimate knowledge of your shell will surely doom the experience to failure.
The ideas extolled above emphasize the key point that not all virtual worlds are created equally. Indeed, one virtual world platform could be of greater fit your needs than another. Though, sometimes the answer might be to use no virtual world at all. Be honest with yourself and don’t roll-out a platform just for the sake of rolling out a platform. As you survey your own corporate culture, the pedagogies utilized by your trainers, your security considerations, your budget and a host of other concerns, you will then want to match these factors with the most applicable virtual world platform for your unique requirements. First, take a realistic look at your organization’s culture and ask some simple questions:
technically-mediated initiatives, you might want to realistically consider whether a virtual world is a viable option. It is also worth noting that a team of young millennials can be as apprehensive to embrace and buy into a virtual world as any other group but for different reasons. It is not uncommon to hear a group of young students state, “It’s OK, but it’s not World of Warcraft.” Many millennial learners place much higher expectations on their 3D environments as many of them have spent far greater amounts of time in environments of similar aesthetics. Dr. Rod Riegel of Illinois State University embraced the expectations of millennial learners by completely delivering his undergraduate course in Social Foundations of Education within the popular massively multiplayer online roleplaying game Everquest II. This is truly an extreme example of embracing your culture of learners, but may nonetheless prelude an interesting and effective future trend.
Is your current technologically-mediated learning initiatives embraced and utilized?
What is your threshold for influence from the existing virtual world platform culture?
If you are offering a strong set of online training environments that are underutilized as is, what would a virtual world change? If buy-in is a problem for an already strong set of tools, odds are that a virtual world is not going to change things.
Second Life, the most popular of the consumer focused virtual worlds, does contain the settings to secure areas from outside avatars. Likewise, communication via voice and text can also be contained privately via groups. That said, these settings are only as good as locking the doors to a classroom with windows. The culture is right outside the window. At Ohio University, regardless of security settings in a particular area, students were still able to see and be distracted by a visit from the now infamous flying phalluses. Second Life is, at its core, a consumer application and as such has a wide and complex culture, as has been discussed. If your threshold of influence from the existing culture is low and the tools inside Second Life are not robust enough to tune out the cultural noise, there are platforms that have been designed specifically with industry in mind.
Is there a Virtual World Platform that Fits Your Organization?
Does your organization have the bandwidth to support on boarding employees to a virtual world training platform? If you are already struggling to support learners technically in existing LMS platforms or simulations, a virtual world is not going to make this job any easier and will most likely take far greater amounts of support time. Not all industries are ripe with teams of millennials who are ready and willing to ramp up quickly into a 3D environment. If your teams have already demonstrated apprehension and difficulty with more typical
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OLIVE by Forterra Sytems Inc. is one such tool. OLIVE is seeing wider adoption and was most recently adopted by Accenture and Affiliated Computer Services amongst others as the platform of choice. Protosphere is another platform to consider and was developed specifically with a focus on training and learning in mind. More recently Nortel launched their browser-embedded web. alive platform that is billed as “Network secured virtual world platform for collaboration, assisted E-Commerce and virtual learning & training applications.” These tools do however come with a higher initial price tag than Second Life, Active Worlds or other consumer focused virtual world applications. Another promising development that is currently in beta at the time of this chapter’s release is 3D integration into Lotus Sametime. The 3D capabilities would extend the current integration of IM, email, telephony and web conferences and add the capability for participants to quickly jump into a virtual world space should the immersive and persistent quality of virtual world collaboration be a desired form of collaboration for expanding on an idea. Lotus Sametime 3D would allow employees to quickly jump in and jump out of the virtual world around specific tasks or concepts, requiring very little in terms of integration into any existing virtual world culture. It also comes with a price tag and will still require you to have an existing virtual world environment in place. Lotus Sametime 3D has currently been tested with Second Life, Open Sim and Forterra. In terms of an achievable ramp-up for establishing and orienting your culture in a virtual world, Second Life still provides a wonderfully rich environment where organizations can affordably develop training tools and competencies for virtual world delivery. Organizations can take advantage of the openness of the community and relative ease of creating assets to transform content for real impact in a 3D environment. Then, once the virtual world solution achieves initially planned outcomes, greater adoption, greater funding and
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is holding more enterprise assets, it might be time to seek a more extensive and walled environment. What are your internal policies for securing the information you will have in your virtual world spaces? Some organizations may require a more secure option from the onset for any hope of buy-in from IT departments. Likewise, you might be training around sensitive enterprise information that would require more formidable security. Should a completely walled solution on local severs be required there are open source options that are becoming more and more viable for a contained and controlled virtual world solution. Three such solutions are Open Simulator,Project Wonderland and The Second Life Enterprise Beta. The most promising Open Simulator distribution is realXtend. The purported strength of the realXtend platform is its goal of global standardization and interconnectedness amongst virtual world platforms. Project Wonderland is a toolkit by Sun Microsystems that would enable your developers to create your own enterprise’s 3D virtual world. The Second Life Enterprise Beta enables a secure and flexible workspace behind an organization’s firewall. The key word related to both realXtend and Project Wonderland is “developers.” You will need people to develop and support any kind of platform that you plan to build on your own servers behind your firewall. Though this may seem like an obstacle at present, these kinds of self-contained solutions will become more and more attractive as these technologies advance and the value-add of virtual worlds for the enterprise are continually documented. The Second Life Enterprise Beta is more of an out-of-the-box solution for securing virtual collaboration. The Second Life documentation states that the installation and setup will take a network administrator thirty minutes. Eventually an architecture of an intra-virtual world and an inter-virtual world – and travel between the two
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– will more closely resemble the current intranet/ internet relationship. Meanwhile, platforms such as the consumer versions of Second Life or Active Worlds are viable environments for acclimating an organization to the unique culture of immersive virtual environments and offering an introduction to what does and does not work well. The key is to continually keep your feet wet and roll with the very rapid changes in the space, so that – as platforms continue to rapidly develop, change, merge, and become more interoperable and more ubiquitous – your organization is continually well footed to utilize the virtual world for increasing efficiencies where applicable. Another failure point that is currently more prevalent in the world of higher education is the sudden lack of pedagogical focus when crafting virtual world learning experiences. Where many of the early corporate failures were built around a marketing or customer communication function, most higher education initiatives where built around the hope of enhancing student learning experiences. Many educators made the mistake of throwing current e-learning or face-to-face learning experiences blindly into the virtual world without deciding which experiences or parts of experiences are more or less suitable for a virtual world. Each virtual world has strengths and weaknesses in light of human-computer interface, as well as in capability as an adequate delivery platform. Identifying these strengths and weaknesses is key to supporting learning outcomes with valuable activities that can drive inquiry and ultimate transfer. Indeed, there is only one thing worse than a page-turner: a page-turner delivered in a virtual world.
Examples of How Not to Employ a Virtual World Solution Considering such mistakes in application, as well as the defining characteristics of virtual worlds discussed earlier, we can identify some examples
of how your organization should not employ these environments.
Using Monologic or Inactive Pedagogy Listening to a talk head is boring no matter what the medium. We’ve all sat through lectures that were less than engaging. On the flip side, most of us have sat listening to engaging ideas wishing desperately that we would be allowed to contribute and have a conversation rather than merely listen passively. Using a virtual world for employee development, training, and community building requires a new approach to what “learning” looks like. We’ve all heard about the old “sage on the stage” model of learning and most of us have grim memories of experiences where we were expected to somehow magically absorb information presented to us in some flat, boring form. Learning in a virtual world not only gives us ways to go against the boring grain but may also occasionally make these old methods nearly impossible. Give a long lecture in Second Life, for example, and even the most intriguing speaker may look out on an audience of slumped avatars who are listening but not engaged. The virtual worlds we refer to in this chapter are largely constructed for facilitating social activities. They’re 3D social networks of people with similar interests. If training is to be successful in these spaces then it has to built around social practices. After all, we all learn better when we’re given the opportunity to discuss what we’re learning, mull it over, pull it apart, and bounce ideas off of peers. This can only happen when learning is social. It may be hard to imagine a class where everyone can talk at the same time, get up and fly around, or pan their avatar’s camera around to inspect another person or just to watch a sunset. This description might sound like a course that’s out of control but in fact it’s rather normal for people using virtual worlds. Rather than sitting in a virtual auditorium listening to a lecture (which is probably better done in Breeze or another teleconferenc-
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ing, webinar product), successful virtual learning allows participants to...well, participate! Passive learning just doesn’t cut it in a world where every user has the same ability to create content and to engage one another. Know that you may need to think way outside the box to make learning in a virtual world work in your institution. However, you can also be confident that, if you’re successful, you will have ditched all the elements of professional development that have given “training days” their horrible reputation.
Jumping in because Everyone Else is Doing It Adapting your training to fit within a social virtual world is no easy feat. The training, developing new courses and methods, engaging an internal community to make it work... these are not projects you want to take on if your reason for jumping into a virtual world is “other people are doing it.” Virtual worlds are a fairly hot topic. Over 5,000 educators subscribe to the Second Life mailing list but that doesn’t mean that every university or every CLO should jump in too. The PR blitz around companies experimenting in virtual worlds has almost completely passed as these spaces become more mainstream. Don’t let your CEO convince you that moving your training into a virtual world will be a good external marketing move. It won’t. Frankly, enough companies have already done it to render such a move no longer newsworthy. On the other hand, doing it really well might get you some exposure. But this still isn’t the best use of your time if your only goal is to get attention. There are certainly better ways to do it. We don’t mean to dissuade you from jumping in. It’s just that, if you’re to be really successful, you’ll need to have realistic goals that suit your needs, your people, and the tool you choose to use. Besides, it’s far too common that the brave soul willing to develop a new program is the one who gets the blame if it fails, even when other factors
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are to blame. Don’t let your marketing department turn you into a patsy for PR. Know that you have solid justification for adopting a new tool such as a virtual world. Be ready to justify it in detail and to define what success will be for the project.
THE FALL-OUT OF FAILED APPROACHES: HOW BEST TO INTRODUCE THE IDEA OF A VIRTUAL WORLD SOLUTION Ineffective introductions of virtual worlds as training spaces can have broad negative effects among a training population and in the organization in general. Such projects are still seen, unfortunately, as risky and experimental so their failure typically means that future efforts will meet increased resistance. But the negatives don’t end there. Once participants are convinced to give such a new approach to training a try, they’ve begun to invest trust in the trainer beyond simply being willing to learn. Often, the experience of becoming acclimated to a world such as Second Life involves a certain degree of vulnerability as participants learn through awkward circumstances such as flying into buildings or adjusting their avatar’s appearance. Once participants have committed to this kind of risk taking, a failure in the actual training experience itself can be destructive not only to that particular training effort but to future training efforts and to the relationship participants have with the trainer. Be as transparent as possible in introducing such a new approach. Including participants in the experimental nature of the training can help them to share the excitement and be more invested in the success of the program. It should also be noted that, in many cases, virtual world training efforts require a larger investment of time and money than recycling previously used approaches. And again, because using a virtual world is typically seen as risky rather than mainstream, the funds used to support such a project can easily be seen as a waste of money
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in a more negative way than “successful” but ineffective traditional methods. It’s important to explain to those who control budgets that an effort to develop virtual world training accomplishes many tasks at once, including training programs, introduction of new technology, research and development, and marketing efforts (for the attention that many organizations receive for using such a novel approach). Unfortunately, in many organizations, the outcomes of traditional approaches to training aren’t measured with the same standards that a new approach might be. Classroom lectures and self-paced slideshows are well understood and can be extremely ineffective but they are familiar. Therefore, while the outcomes of these approaches might be inferior to a well-run virtual training program, the failure of a more traditional approach usually doesn’t draw much attention. Fail at something new and you’ll have all eyes on you.
THE BIG QUESTION: ARE VIRTUAL WORLDS RIGHT FOR YOUR ORGANIZATION? So, if the risk is so high, why would anyone want to try his or her hand at developing virtual world training methods? How can you know beforehand that you’ve made the right choice when you choose to utilize virtual spaces for training? Have you adequately identified the need? You’ll need to if you’re to get good adoption. First, be sure you’ve adequately identified the training need and that you’ll get good adoption within the organization. Making a few asynchronous training modules available online requires little commitment. If no one takes advantage of them then there isn’t much lost. However, if you invest in developing an interactive training experience in a virtual space then you will have put in much more time and effort. Be sure that
you’ve selected a topic that has high interest in your organization. Make the decision to participate an easy one. Students taking the class should clearly understand that there are clear benefits to the program. You may even need to sweeten the deal by stressing that learning the virtual world’s tools may be beneficial after the training is over. Be sure it’s not just what you want to do but what’s best for the learners Next, ask yourself the tough question: Is using a virtual world what is best for my learners or is it just interesting to me? It’s easy as a trainer to be seduced by something that looks so different from the modes of delivery that you use every day (you can only make so many PowerPoints before you bore even yourself!). Using a virtual space can seem attractive merely for the novelty of them. It’s also seductive to think that mastering such a new approach might get you more approbations as a trainer. However, if an experimental approach is antithetical to the culture of your learners (technology novices for example), you’ll need to acknowledge that even though you may have a brilliant idea for training, it might not suit your audience. What haven’t you been able to accomplish in other tools; with other methods? As always, pedagogy should come before technology and learning goals should come before delivery method. Perhaps you’re trying to improve the results you get with another delivery method or accomplish a kind of training that you haven’t been able to deliver with the available tools. Regardless of the perceived need that drives you to consider virtual worlds for training, be sure that the time and effort are worth it and that there isn’t an easier to use tool that would allow you to deliver the training with a less steep learning curve. This will also help you make the case for a virtual world application. If you’re truly able to
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do something unique and compelling then gaining buy in should be much easier. Do you have adequate resources for ensuring long-term success? Finally, every corporate virtual world roll-out requires ongoing support in a variety of different domains depending on the over-riding mission of the virtual worlds strategy. For a roll-out focused on training function a business will want to vigilantly plan on having processes in place for initial support and training of users, technical support, internal evangelization and sales of the training efforts and ongoing content or learning experience creation, to name just a few. Virtual worlds, like most good web 2.0 applications, are successfully used and populated by users if the users perceive that “this is where the party is at.” If you don’t provide compelling reasons for your associates to come, learn, and share knowledge, the virtual world real estate will sit barren. If you actively work to populate your virtual world learning space with appropriate and dynamic learning activities and purposes for collaboration, you create motivated learners. There are also technology-related thresholds for adoption. We’ve worked with innumerable companies that are excited about using a virtual world until they realize that the standard issue computers in their office don’t have the processing power or graphics capabilities to even run the software. Is it worth it to replace the computers of everyone on the team? Perhaps your remote learners are on limited bandwidth and can’t get enough connection speed to adequately participate in the training. Is the program worth it to them to upgrade their internet connections or change locations? You may also need a team of people who can support the application and answer questions around the clock if you’re an international organization. Most virtual worlds platforms still have severely lacking customer service, so it you may require having an internal resource available
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to answer common questions or troubleshoot problems that participants encounter. Virtual communities take more than one evangelist to get started and stay in growth mode. Most successful projects have a project manager who is assisted by community managers – who help users and trouble shoot problems – as well as event planners – who work through the details of hosting an event and making sure that everyone can participate as expected. Additionally, you may also need to enlist subject matter experts who can help construct courses and experiences on desired topics. Such subject matter experts may be well versed in their topic area, but not in the virtual world platform, and thus may require significant training or support as well. It takes a village to create a community.
SO YOU’VE DECIDED; NOW WHAT? Virtual world applications require as much planning as traditional approaches if not more so. When you begin to draft your plan you’re doing more than just rationalizing the learning goals; you’re likely drafting a long term plan for a robust learning community which should be at least somewhat self-sustaining after a time. Knowing what this community will look like, how it will function, and why people should want to engage in it will go a long way toward success.
Spelling out the goals Ask yourself these questions: • • •
What is the desired outcome? How long will it take to achieve it? Is the outcome worth the time it will take?
If you hope to develop a long-lived presence in a virtual world, in which many programs will occur and an organizational community will form, it won’t happen overnight. Like any culture, it
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will have to develop over time and be nurtured and encouraged. You can’t, for example, build an island in Second Life and expect a community to form on its own. If your goal is to create a learning community you’ll need to host events, offer training, and provide incentives. It may take months for enough participants to adopt the tools to really see things happening. Can you wait this long? What are your metrics for success? How will you gather the information necessary to know that the community is growing as you’d expect?
Sharing the Plan and Getting Buy in A learning community requires, well, a community! Not just a few avid participants but many. To turn hesitant experimenters into excited evangelists may take significant effort and hand holding. You may want to schedule regular training and information sessions to invite people to become involved. Provide them with as much support as you can until they feel comfortable. Once they’re well acquainted, these first converts will become your first line of evangelists and make the process much more scalable, especially in a large organization. And bear in mind that people learn in different ways. You may need to make videos and handouts or offer one-on-one training. Be flexible and try to meet the needs of those willing to become involved.
Promise, Tool, Bargain: Spelling out the Plan Broad adoption may be a long time in the making and you may encounter snags along the way. This doesn’t mean that you should give up. Find out why the community fails to grow, or why participants fail to learn, and then be ready to try again. We find Clay Shirky’s model of the “Promise, Tool, and Bargain” from his book Here Comes Everybody very useful.
•
•
•
Promise: What users are told that they will get out of the project. This is the compelling “sell” that motivates participants to be willing to give it a try. Tool: The tool that will allow participants to accomplish what they need to accomplish in order to fulfill the Promise. Bargain: An explicit description of what users will have to do to gain what is promised.
First, you’ll need to acknowledge that everyone may not be as excited as you are. They’ll need to be motivated to participate. Be clear about the benefits of the community or program. Give them as many reasons as you can to say ‘yes.’ When we fail at creating compelling promises it usually means that we haven’t thought enough about the benefits to the users, that we haven’t anticipated and met their needs well enough. Keep in mind that groups of people in your organization may need different promises to compel them to become involved. Whatever you do, don’t present the project as being frivolous or just experimental. Don’t make excuses that will make it easy for participants to say no. Second, be sure that you understand the tool well enough to train others to use it and to solve common problems. Hesitant participants will need to feel that you’re in control of the space and can keep them safe and focused. If you, for example, choose a virtual world platform that is unstable and crashes often, then users will see that as an easy reason not to participate. Finally, be transparent and honest about what the participants will need to do to get the most benefit from the program. If being a passive, quiet user will leave them wondering why they’ve come, then be sure to tell them in advance that you’ll expect them to contribute in explicit ways. If you expect them to learn a bit on their own or to experiment with the tool, then tell them that and offer whatever support that they might need. If they fail to do so it will be easy for you to identify the
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points of failure that will need to be addressed in order to get the community rolling again. If they aren’t willing to fulfill their part of the bargain then you should go back to the promise and make it more compelling. Last, but not least, know that training in virtual worlds and building community is something that you’re never finished with. Like a garden, a community requires constant attention and nurturing. You’ll need ongoing programming and support to keep the project going and growing. This is no small task. Nonetheless, provided that it is given the proper consideration, preparation, and resources, a virtual world solution may offer an invaluable new opportunity for your training program.
REFERENCES http://www.kzero.co.uk/blog/?p=854, (n.d.). http://www.pscoe.gov.sg/repository/open/2/522/ Training.htm, (n.d.).
http://www.websitemagazine.com/content/blogs/ posts/articles/second_life_metaverse.aspx (n.d.). Shirky, C. (2008). Here Comes Everybody. New York: Penguin Press.
KEY TERMS AND DEFINITIONS Learning Community: A group of people who are actively engaged in cooperative learning whether formal or informal. Metaverse: Originally coined by Neal Stephenson in Snow Crash (1992), the term has come to be used as a description of al of virtual worlds and the reality and culture they represent. Pedagogy: The art and science of teaching. Return on Investment (ROI): A term commonly used in business to describe the quantifiable financial returns on a business effort. Virtual World: A synchronous, persistent network of people, represented by avatars, facilitated by computers.
http://www.virtualworldsnews.com/2009/02/ ibm-saves-320000-with-second-life-meeting. html, (n.d.).
This work was previously published in Virtual Environments for Corporate Education: Employee Learning and Solutions, edited by William Ritke-Jones, pp. 36-49, copyright 2010 by Business Science Reference (an imprint of IGI Global).
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Chapter 1.10
Learning Space in Virtual Environments: Understanding the Factors Influencing Training Time M. Kyritsis Brunel University, UK S. R. Gulliver University of Reading, UK S. Morar Consultant, UK
ABSTRACT Learning the spatial layout of an environment is essential in application domains including military and emergency personnel training. Traditionally, whilst learning space from a Virtual Environment (VE), identical training time was used for all users - a one size fits all approach to exposure / training time. This chapter, however, identifies both environmental and individual user differences that influence the training time required to ensure effective virtual environment spatial knowledge acquisition (SKA). We introduce the DOI: 10.4018/978-1-60960-587-2.ch110
problem of contradicting literature in the area of SKA, and discuss how the amount of exposure time given to a person during VE training is responsible for the feasibility of SKA. We then show how certain individual user differences, as well as environmental factors, impact on the required exposure time that a particular person needs within a specific VE. Individual factors discussed include: the importance of knowledge and experience; the importance of gender; the importance of aptitude and spatial orientation skills; and the importance of cognitive styles. Environmental factors discussed include: Size, Spatial layout complexity and landmark distribution. Since people are different, a one-size fits all
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approach to training time does not seem logical. The impact of this research domain is important to VE training in general, however within service and military domains ensuring appropriate spatial training is critical in order to ensure that disorientation does not occur in a life / death scenario.
INTRODUCTION The ability to ‘learn’ the environment before engaging in navigation is an area of interest for a variety of application domains (Egsegian et al., 1993, Foreman et al, 2003). Traditionally spatial training is accomplished by providing users with maps and briefings of an environment. These methods, however, only provide topological (survey) knowledge of the environment, which whilst being more flexible, pays little attention to the details of routes and landmarks (Thorndyke, 1980; Golledge, 1991). Procedural learning has a distinct advantage over survey knowledge, as can be seen in an experiments of Thorndyke and Hayes-Roth (1982) where participants with procedural knowledge of an environment, estimated route distances significantly better than participants who had acquired just survey knowledge. Navigation therefore relies heavily on previously acquired visual information, e.g. the process of re-orientation during navigation in a previously visited environments (Montello, 2005), which relies on previously seen “visual references” in order to adjust bearings during navigation. Maps and other traditional navigational equipment cannot provide the same level of supporting information. VE training, therefore, promises to provide procedural knowledge through exploration, and has caught the attention of a variety of researchers all attempting to discuss whether virtual training is more efficient than training through more traditional methods (Witmer et al., 1995; Goerger et al., 1998; Waller et al., 1998; Foreman et al., 2003). Learning in virtual environments relies on the ability of users to develop an understand-
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ing of space by creating a cognitive map of the environment (Asthmeir et al., 1993; Cobb and d’Cruz, 1994; Silverman and Spiker, 1997; Clark and Wong, 2000; Riva and Gamberini, 2000). Cognitive maps are mental representations of space that people develop in order to acquire an understanding of space, both virtual and real, through either procedural knowledge or survey knowledge (Thorndyke, 1980; Golledge, 1991; Witmer et al., 1995; Goerger et al., 1998). When learning in a procedural manner, cognitive maps are created through the act of navigation (Montello, 2005). Navigation itself is made up of two separate and very distinct processes. The first of these processes is locomotion, which is the movement of a person within an environment. The second process is way-finding, which is the planning of routes that a person undergoes when trying to get to a specific destination (Montello, 2005). It is understood that during self-directed locomotion (where the person is actively moving about in the environment solving problems - such as avoiding obstacles), there is a tendency to acquire more spatial knowledge (Feldman & Acredolo, 1979). Virtual environment training, however, provides self-directed locomotion without the possibility of a dangerous life-threatening situation, making it very suitable for emergency training. Research concerning spatial knowledge acquisition through VEs, have provided a variety of contradicting results. The findings, although conflicting, appear to be subject to a key influencing factor, ‘required exposure time’ (Witmer et al., 1996; Darken & Banker, 1998; Waller et al., 1998; Goerger et al., 1998; and Darken and Peterson, 2001). This factor is the exposure time that a user will spend learning the environment in order to achieve spatial knowledge acquisition.
THE IMPACT OF TRAINING TIME Witmer et al. (1996), Wilson et al. (1996), Waller et al. (1998), and Foreman et al. (2003) all con-
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ducted experiments in order to conclude whether spatial knowledge acquisition can be acquired from a VE representation of the real world. These experiments involved a group of participants navigating through virtual space and acquiring spatial knowledge, and then comparing the results to a group that learned the environment through conventional methods such as maps or photographs. These experiments concluded that a VE can be more beneficial than traditional training. However, this is only the case if a long exposure time is given to the users. Darken and Banker (1998) reported that experts perform better using conventional methods such as maps, while Goerger et al. (1998) reported that all participants had a greater success using conventional methods. Goerger et al. (1998) acknowledge, that with longer exposure times, virtual reality training may in fact be more beneficial, however, this is hard to determine since the exposure times that a user spent in each experiment differed. Waller et al (1998) allowed for two minutes, Darken and Banker allowed for a set 60 minute exposure, and Goerger et al. (1998) allowed for a set 30 minute exposure, yet they referred to this as a short exposure time. It was, therefore unclear how much exposure time is deemed as required, and if in fact various environmental attributes and individual user differences can affect the required exposure time. In an attempt to clarify this situation, Darken et al. (1999) and Koh et al. (1999) discussed why spatial knowledge acquisition research delivers contradictory results. They both made the argument that individual user differences are an extremely important factor in the development of cognitive maps, and that a one-size-fits all situation may not be possible when determining required exposure time. Darken et al. (1999) also examined how cognitive and biological differences affect a series of cognitive processes, which are critical to navigation. They stated that previous knowledge, aptitude, orientation ability, strategy, perceptual motoric and memorial knowledge, all influenced
the navigational skill of the user. According to Koh et al. (1999) and Waller et al. (2001) there is a need to identify these individual differences and to understand how they affect performance when acquiring spatial knowledge. Therefore, this chapter identifies and discusses commonly defined individual differences of users that affect navigation skills, and therefore the exposure time required to acquire spatial knowledge from a VE. Understanding how these individual differences affect navigational skill will help VE trainers understand the required exposure times necessary for a specific user to acquire spatial knowledge from a particular environment. Since people are different, a one-size fits all approach to training time does not seem logical. The individual differences of users that navigate through an environment is not the only factor that influences the required exposure time. Darken and Peterson (2001) reported that required exposure time is also environment dependent. They explained that some environments provide more cues than others and, therefore, that the exposure time needed alters according to relevant cues (Darken & Peterson, 2001). Darken and Peterson (2001) identified that, regardless of whether the training interface is supported with a map or whether other visual cues are used in combination with the environment, the structure of the environment itself contains factors that support user navigation, which can result in a smaller exposure time requirement. It may seem obvious that the size of an environment impacts the time required to navigate through it, however size is only one of many influencing factors that will be discussed in this chapter.
ENVIRONMENAL FACTORS AFFECTING EXPOSURE TIME Many of the factors that affect navigational complexity, which apply to the physical world are applicable in the virtual world (Darken & Banker,
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1998). Darken and Peterson (2001), broke down an environment into a space made up of building blocks or ‘landmarks’ that are connected by routes, which are interconnected to form nodes. These interconnected routes and nodes make up the spatial layout of the environment. Environments can be complex in nature and can therefore affect the exposure time required to acquire spatial knowledge (Darken & Peterson, 2001). Although we have used size as the example, size is only one of the factors that can influence navigation. Research indicates factors include complexity of the spatial layout and landmark information (Darken & Sibert, 1996; Witmer & Sadowski, 1998; Vinson, 1999; and Gouteux & Spelke, 2001). Studies by Goerger et al. (1998) and Gouteux and Spelke (2001), show that spatial layout complexity is an important component of cognitive development. Witmer et al. (1995), Witmer and Sadowski (1998) and Vinson (1999), claim that the number of landmarks and the frequency per square metre, as well as the graphical detail of these landmarks is important. Research also shows that navigational complexity influences various processes that directly affect navigation. These processes are identified by Stankiewicz and Kalia (2004) as: perception (input of cues and other environmental information at a given time during navigation); accessing the cognitive map (ability of each person to develop a cognitive map of the environment and then apply it to navigation); spatial updating (ability to navigate from different positions in the environment); decision making (logical process to reach a certain goal depending on current position and perception). Moreover, Stankiewicz and Kalia (2004) discuss how various environmental factors such as size influence these processes and make navigation more complex, i.e. how large size burdens perception due to a larger area being processed that requires a more complex cognitive map in spatial memory. Spatial updating takes longer since there are more places and objects to consider, and decision strategy is influenced as
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more decisions must be made to reach a certain goal (Stankiewicz and Kalia, 2004). The following sub-sections will discuss critical environmental factors that influence exposure time: size; spatial layout complexity; and landmark potential.
Size For the scope of this chapter, environmental size refers to the overall raw navigational space available to the user. The differentiation between largescale and small-scale environments, however is not clearly defined in literature. To Darken and Banker (1998) a large-scaled environment was described as being 1200*700 metres, which we can consider as being large when comparing it to other virtual spaces that represent a house or building, such as the one in Goerger et al. (1998). Obviously, without visual obstructions, size would not be a confounding factor, however in any nonflat featureless environment, as size increases so does the time taken too move (locomote) from one place to another in order to acquire spatial knowledge, which must then be transformed from visual working memory into long-term memory. What may not be so obvious is that navigational strategy is also affected. Butler et al. (1993) demonstrated that distance plays a significant role when navigating. They found that users will most frequently choose to navigate through shorter paths, even if those paths are more complex. Therefore, as size increases so does the amount of exposure time required by a person to acquire spatial knowledge from the environment. The question that seems to arise, however, is how much time is suitable for a specific size. For a large mountainous region, as used by Darken and Banker (1998), a 60 minute exposure time was considered as being ‘short’, however to our knowledge no justification for this exposure time was given. For a seven story building, as designed by Goerger et al. (1998), an exposure time of 30 minutes was also considered ‘short’,
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however again no justification for this exposure time was given. We have no indication at all, whether navigational complexity increases linearly as size increases when navigating through a virtual environment. If the relationship is not linear, then size becomes more and more critical to consider with respect to exposure time required for SKA.
Spatial Layout Complexity Spatial layout is the geometrical structure of an environment (Gouteux & Spelke, 2001). When trying to determine what makes a layout more complex, without involving size, spatial layout complexity is the number of objects, such as walls, that obstruct a user’s line of sight from reference points, i.e. visible landmarks. This is demonstrated in the work of Kalia and Stankiewicz (2007), who measured the spatial layout complexity in terms of corridors. They found that as the number of corridors in an environment increased, so did its complexity. In virtual environments the architecture of an environment is important to navigation, as demonstrated by Passini (1984), who discussed how Manhattan’s rectangular grid, with visual aids such as numbering of streets and avenues, makes navigation very simple. However, in some cases it is simply not possible to provide architectural simplification (e.g. in a natural mountainous region). Darken and Sibert (1996) explained that environments that do not provide any navigational aids, such as road signs, will be harder to navigate and will ultimately lead to a loss of awareness and disorientation. In an office building, one find signs that point towards different levels and not simply lead to dead ends, however a ‘natural environment’ has few restrictions and does not follow any architectural laws. In general, complex environments, both natural and man-made, tend to have a lot of visual obstructions to visual references. In mountainous regions, this may be
slopes, whilst in a cave or building it may be the walls that obstruct references.
Landmarks Lynch (1960), Vinson (1999) and Stankiewicz and Kalia (2004) identify that an environment is made up of a variety of landmarks that individuals use to navigate. Stankiewicz and Kalia (2004) broke down the term landmarks into two distinct types: structural landmarks and object landmarks. Structural landmarks are distinct geographical features of an environment that can be used for navigating (e.g. a T-junction), whilst object landmarks are objects in the environment that are independent of the structure (e.g. a statue). In general, landmarks differentiate between different parts of an environment (Weisman, 1981). Although it is rather difficult to understand and predict what landmarks a user will choose when navigating, there are theories. Stankiewicz and Kalia (2004) explained that different landmarks have various benefits for the user with landmark potential defined through the three properties that a landmark may possess. The first of these properties is persistence, which is whether the landmark is mobile. A parked car is not the best landmark as it has a high chance of moving by the time the user revisits the site. This can cause confusion as users often navigate initially using object landmarks rather than geographic structure (Newman et al., 2007). The second property is whether the landmark is perceptually salient (i.e. visible), and is determined by factors including landmark size and number of obstructions. The third and final property of a landmark is whether or not the landmark is informative. This is important as it informs an individual of their location. Stankiewicz and Kalia (2004) explain that for a landmark to be informative it must be distinctly different from other landmarks, in fact the reason why users have difficulty using landmarks such as statues (Ruddle et al., 1997) is because they cannot easily distinguish between
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the statues, unless they approach them for a closer inspection. If all three of these factors are satisfied then the landmark can be useful during landmark-based navigational updating, which, as we discussed before, is a process of reorientation that relies on landmarks. Stankiewicz and Kalia (2004) discovered that participants tend to learn structural landmarks better than object landmarks, and that when spatial knowledge acquisition does occur, the environment structure can be remembered by a user, even as far as a year later after the initial encounter. For example, most people will remember the layout of their first school, but few will remember the location of specific objects. Vinson (1999) deducted that the landmarks that are frequently available, and visible from various positions in the environment (i.e. paths), are useful in navigation. Frequent landmarks appear to increase navigational performance. For this to apply, however, landmarks must be unique. In natural environments, such as a forest, there is a large amount of non-unique landmarks, such as trees and rocks. These landmarks overpopulate the area, and cannot be used as reference points (which is a very important part of navigational updating), since one tree may not be distinctly different from another. However, man-made structures in a forest environment would stand out as distinct landmarks (Whittaker, 1996). Therefore, it is not just the frequency of landmarks readily available throughout the environment, but also the number of distinct landmarks available that can help a user orientate, decreasing navigational complexity. This information relates to the need for a landmark to be informative, as was suggested by Stankiewicz and Kalia (2004). The assumption is that for a virtual environment, landmark potential can be measured by the number of visible, non-dynamic (not moving) and distinct landmarks available to the environment as a whole, and the frequency of these landmarks per sector (for which a sector may be the maximum view available to the user: a room or a corridor).
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INDIVIDUAL DIFFERENCES IMPACTING USER NAVIGATION Individual differences have been considered for many years in Visuospatial research, which considers a very broad spectrum of research of understanding concerning images, space and spatial knowledge acquisition (Hegarty and Waller, 2005). This chapter considers the key individual user differences: gender, experience / knowledge, orientation skill, age, and cognitive styles. As suggested by Darken et al. (1999), each of these human attributes influence the navigational skills of the user when they navigate in a novel environment.
Gender Issues in Navigation There is evidence that gender plays a significant role in acquiring spatial knowledge from a VE. Waller et al. (1998) showed that females were particularly disorientated in a virtual maze, since they reported large bearing errors when drawing a retrospective maze map. Although women’s ability is more constrained when learning spatial characteristics of a virtual environment, their difficulty when navigating in the maze may be constrained by strategy rather than ability. Both Sandstrome et al. (1998) and Moffat et al. (1998) have provided explanations as to why male users navigate better in a maze. One of the deficiencies of a maze is that it relies heavily on geometrical navigation, rather than the use of landmark cues. Sandstrome et al. (1998) concluded that women rely heavily on the use of object landmarks for navigation, where men seem to use both structural landmarks and object landmarks. The difficulty that women may face when navigating through an environment with limited landmarks, suggests that the required exposure time required by women to acquire the spatial information is increased when environments lack well placed object landmarks. Accordingly, women have problems navigating environments that are complex by nature (such as a maze),
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however this does not mean that for other types of environments their navigation skills will suffer, or that if given enough exposure time their knowledge of the environment will not equal that of the men. This theory is backed by Vila et al. (2002), who indicate that as exposure time in the environment increases, the navigational differences between the genders decreases.
Knowledge and Experience of Environment and IT System Knowledge concerning the system, whether it is a desktop computer that allows for mouse and keyboard input, or if it an immersive device, can have a limiting effect due to an overload of mental tasks. This overload is described by Booth et al. (2000) and is explained to be a limitation to attention due to unfamiliar controls and interfaces. According to Booth et al (2000) this occurs mainly because there is an attention dividing of tasks, which are required to navigate and perceive the information seen on the screen. More effort is required to understand and interact with the interface, therefore not enough attention is given to creating cognitive maps of the environment. In compensation, a longer exposure time is required. More effort is also required if an environment is novel (i.e. if the user has never navigated through this type of architectural structure). In HCI, the difference during navigation between experts VS novices is critical for interface design (Dix et al., 1993; Eberts, 1994). Kuipers (1975), Brewer (2000) and Mania et al. (2005) explain how experience with a certain type of environment gives rise to certain structures in human knowledge memory. These structures are called schemas and are formed in human memory due to past experiences (Pelagatti et. al. 2009). Schemas consist of perceptual information and language comprehension, and are invoked when interacting with new information. The required exposure time to learn an environment depends on memory performance, which is in turn influenced by Schemas, which
are affected by the consistency of items in the environment, i.e. whether an item is likely to exist in such an environment (Brewer and Nakamura, 1984). Another theory is called the inconsistent effect and argues that inconsistent items positively influence memory (Lampinen et al., 2001). It is clear that schemas are highly relevant to landmark information and that a person with strong past experiences navigating through a certain type of environment will be more able to recognize key landmarks, and therefore create a cognitive map faster than a similar person with no experience navigating within such an environment. Knowledge of the environment was considered to be a variable in the experiment of Darken and Banker (1998), who only selected experienced mountaineers for their experiment. Darken and Banker (1998) reported, however, that the advanced mountaineers did not benefit from the 60 minute exposure time in the VE, yet did benefit from using a map. Interestingly, they did not, to the best of our knowledge, test user orientation skills. Instead, Darken and Banker (1998) used participants that have a large experience with navigating through real wilderness using cues and maps. This does not mean, however, that these participants were experienced with the VE system, or had a high aptitude and orientation skill.
Aptitude and Spatial Orientation Skills The most discussed individual user difference, in the area of spatial knowledge acquisition, is orientation skill. Most experiments testing for spatial knowledge acquisition attempt to keep orientation skill consistent amongst participants (Witmer et al., 1996; Goerger et al., 1998; and Waller et al., 1998). It is obvious that research considers spatial orientation skills as being a very influential attribute during a variety of areas involving human-computer interaction, such as browsing and other visual tasks (Gomez et al., 1986; Vicente et al., 1987; Stanney & Salvendy,
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1995). There is strong evidence that individuals have different orientation abilities, which are simply biological in nature (Smith & Millner, 1981; Maguire et al., 1996; Maguire et al., 1999; Maguire et al., 2000). Research points to the hippocampus area, which is placed in the centre of the brain, as being responsible for providing spatial memory. To measure spatial and spatial orientation, various spatial visualisation and orientation tests that can determine a person’s orientation skill, such as the Guilford-Zimmerman orientation survey (Guilford & Zimmerman, 1948). Other tests exist (such as spatial memory, and spatial scanning tests), but spatial orientation tests are thought to be more successful in determining a user’s ability to acquire spatial knowledge (Waller, 2001). Although the orientation skill of a user is often thought to be the most critical individual difference, there is actually no proof that it has the most impact on the required exposure time. Additional research is required to more fully investigate how orientation skill impacts spatial knowledge acquisition.
Age Differences in Navigation Age plays an important role in navigation due to an overall change in sensory abilities, as well as various knowledge and cognitive skills, which are developed through life (Cohen & Scheupfer, 1980; Mathews, 1992; Wilkniss et al., 1997; Pine et al., 2002). Hasher and Zacks (1979) suggest that spatial ability is an automatic process that does not demand cognitive abilities, and therefore should not be affected by age. According to Cohen and Scheupfer (1980), pre-adolescents navigate through a novel environment just as well as adults if the knowledge being acquired is through procedural means (i.e. direct exploration). Problem occur however when transferring survey knowledge to procedural knowledge, since the ability to navigate through the environment using abstract mental representations is only developed in later stages of adolescence (Mathews, 1992). Cohen and
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Scheupfer (1980) theorized that pre-adolescents are burdened when navigating through a novel environment using survey knowledge and abstract mental information (i.e. from a map). Pine et al. (2002) found that when navigating freely through a virtual city, adolescents reached as many goals and learned the environment as quickly as adults. Pine et al. (2002), however, also found that when asked to recall information, such as label points of interest on a map, adults significantly exceeded adolescents. Adults, therefore, have a better ability of transferring procedural to survey knowledge. As an adult reaches old age they suffer from various issues surrounding both their sensory and orientation skills. Salthouse et al. (1990) argues that as people get older, they find it increasingly hard to process new information, whilst trying to retrieve information from memory. According to Kirasic (2000), navigation becomes increasingly difficult as age increases due to declines in perceptual, cognitive and motor abilities. It seems that disorientation in spatial navigation becomes more and more frequent when a person exceeds the age of seventy, even if there is no sign of mental deterioration (Hunt and Waller, 1999). Research suggests that in terms of learning navigational space, older people find it increasingly hard to retrace routes and learn maps (Wilkniss et al., 1997), orientate with respect to other environmental objects (Aubrey & Dobbs, 1990), as well as make distance and direction judgments (Kirasic, 2000). One of the most difficult problems that older people face is the attention divide (Darroch et al., 2005). Because of this, the ability to acquire spatial knowledge through a virtual medium could be beneficial to older ages, since it would help them learn novel environments without the risk of facing physical tiredness.
Cognitive Styles The concept of people adopting different strategies in order to solve problems and make decisions was first presented by Allport (1937) who presented
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cognitive styles as a person’s preferred way of perceiving, remembering, thinking and problem solving. Since then research has looked into cognitive styles, and has referred to them as persistent strategies adapted by individuals when faced with problem solving tasks (Robertson, 1985). In more detail, cognitive styles affect perceiving, remembering, organizing, processing, thinking and problem solving (Liu & Ginther, 1999). Many different learning strategies are consistently adopted by a user in order to solve a problem. Messick (1976) identified as many as 19 different cognitive styles, and Smith (1984) identified 17. Schmeck (1988) grouped them using two distinctly different, but general, learning styles. The first is a more holist learning style, which is referred to as field-dependent and seems to emerge from activity in the right hemisphere of the brain. The second is a more analytical learning style that is referred to as field-independent and seems to emerge from activity in the left hemisphere of the brain. Field-dependent people are more passive when learning (Witkin et al.,1977), and prefer to learn information by focusing on the information as a whole - rather than breaking it down. Field-independent users are more active when learning new information and prefer to acquire information in a serial fashion by breaking it down (Pask, 1979). Goodenough (1976) and Witkin et al. (1977) stated that field-independent people sample more relevant cues to solve a problem, whilst field-dependent people sample more irrelevant cues to the current problem. In terms of landmarks, which are considered cues for navigation, field-independent users will benefit more from informative landmarks. This is also seen in research concerning ‘hypermedia navigation’ (Chen & Macredie, 2001), which indicates that field-dependent users were more efficient when they had to take a more holistic strategy, and navigate using a map of the overall system. In this research field-independent users benefited more from an analytical strategy, which included
a depth-search of the entire system (Ford and Chen, 2001).
RELATIONSHIP BETWEEN ENVIRONMENTAL AND INDIVIDUAL DIFFERENCES Since people are different, a one-size fits all approach to training time does not seem logical. By summarizing all we have discussed so far, and by closely examining the research presented in the previous sections, we show that certain individual user differences ‘react’ more strongly with specific environmental factors. The reaction between these properties critically influences the overall navigational complexity of the environment and therefore the required exposure time. Figure 1 illustrates the various interactions between the individual user differences and environmental factors, as discussed in this chapter. Figure 1 was developed by the authors in order to accommodate for the significance of various individual user differences during navigation when particular environmental properties are present. The top layer represents the environmental factors, the middle layer represents the individual user differences, and the bottom layer represents the cognitive categorization that these individual user differences belong to, as discussed by Darken et al. (1999). By closely examining Figure 1 we see that most individual user differences impact on all types of environments. The only exception seems to be gender and cognitive styles. This diagram is extracted from supporting literature and is therefore hypothetical in nature.
SUMMARY AND REVIEW OF BUSINESS IMPLICATIONS This chapter presents a variety of literature suggesting that spatial knowledge acquisition through VE navigation is feasible, but is influenced by the
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Figure 1. The stages of the information-processing model affected by environmental factors and individual user differences
exposure time given to a user to learn the environment. It was deducted through a comparison of previous studies, that individual cognitive and biological differences impact on the navigational skill of the user, and lead to higher exposure time requirements for spatial knowledge acquisition. These individual user differences affect various skills such as knowledge, aptitude, ability and strategy and have been identified as gender, age, orientation skills, knowledge / experience and cognitive styles. However, individual differences are not the only properties that affect exposure time requirements. Various structural factors of an environment render the environment more or less environmentally complex, and therefore influence the exposure time needed to acquire spatial knowledge as well (Darken and Peterson, 2001). These environmental factors are: size, spatial complexity, and landmark potential. From a business perspective the fact that i) VEs can be used acquiring spatial knowledge, and ii) that a one-size exposure duration is in appropriate, has significant implications. Much spatial knowledge training relates to real world space that is either under-development or potentially unsafe. In such cases on-site training of service, emergency and support staff is impossible, yet the result of badly trained staff has safety implication 144
in the case of an emergency or security breach. Imagine, in the case of a fire at a major sporting event (e.g. World cup or the Olympic Games), the international implications of emergency staff not knowing the layout of a stadium. What legal and political implications exist for government if it can be shown that the military had not provided soldiers with either appropriate training techniques (i.e. VEs) or VE exposure duration that later led to death. In such cases, learning using maps and briefings is restricted because of the individual user differences of the demographic groups involved. Training each and every member of staff in real-world space cannot practically be achieved, however the implication of badly trained staff has significant legal, political and ethic implications. What is the solution? Considerable research suggests that individual user differences impact exposure time for all types of environments, with two exceptions (i.e. gender and cognitive styles): gender is a critical factor only when navigation in low-landmark maze-like environments (see Figure 1); cognitive style impacts spatial knowledge acquisition with field-independent users acquiring spatial knowledge faster from complex environments, and field-dependent users having the advantage in large environments. Orientation skill and envi-
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ronmental knowledge impacts duration time in all environments, yet these individual differences are not easily trained and require significant periods of prolonged training (i.e. possibly years) before any noticeable improvement can be measured. Since significant periods of prolonged training is not possible to increase natural ability of service or military staff, relevant compensation (i.e. additional training within the specific space in question) must be given to cancel out low natural ability. As exposure of untrained staff to dangerous environments is not appropriate, use of spatial training within a VE is a good option for removing many of these safety concerns. Currently, however, there is no research, to the best of our knowledge that is able to quantify the impact of individual differences on exposure duration. Additional research is needed to facilitate VE designers in their understanding of how learning spatial knowledge for a VE impact different users, and what can be done with cue placement to maximize information acquisition, and limit frustration and disorientation. VE mapping, modeling and use in spatial training is of growing importance. It offers significant potential in the effective training of staff, yet a one-size fits all approach cannot be use justified. Only once individual use differences are quantified, can anyone effectively provide spatial training that is appropriate to the specific user.
REFERENCES Allport, G. W. (1937). Personality: A psychological interpretation. New York: Holt & Co. Asthmeir P. Feiger W. & Muller S. (1993), Virtual design: a generic VR system for Astur, R. S., Ortiz, M. L., & Sutherland, R. J. (1998). A characterization of performance by men and women in a virtual Morris water task: A large and reliable sex difference. Behavioural Brain Research, 93(12), 185–190. doi:10.1016/ S0166-4328(98)00019-9
Aubrey, J. B., & Dobbs, A. R. (1990). Age and sex differences in the mental realignment of maps. Experimental Aging Research, 16(3), 133–139. doi:10.1080/07340669008251540 Booth K. Fisher B. Page S. Ware C. & Widen S. (2000). Wayfinding in a virtual environment. Graphics Interface. Brewer, W. F. (2000). Bartlett’s concept of the schema and its impact on theories of knowledge representation in contemporary cognitive psychology. In Saito (Ed.), Bartlett, culture and cognition, 69-89, Psychology Press. Brewer, W. F., & Nakamura, G. V. (1984). The nature and functions of schemas. Handbook of social cognition, 1, 119160. Butler, D. L., Acquino, A. L., Hissong, A. A., & Scott, P. A. (1993). Wayfinding by Newcomers in a Complex Building. Human Factors, 35(1), 159173. Chen, S. Y., & Macredie, R. D. (2001). Cognitive styles and hypermedia navigation: Development of a learning model. Journal of the American Society for Information Science and Technology, 53(1), 315. doi:10.1002/1532-2890(2000)9999:99993.0.CO;2-2 Clark, S. A., & Wong, B. L. W. (2000). QTVR Support for Teaching Operative Procedures in Dentistry. People and Computer XIV. Usability or Else! Proceedings of HCL 2000, London. Cobb S.U.G. & D’Cruz, M. D. (1994) First UK national survey on industrial application of virtual reality. VR News, 3. Cohen, R., & Schuepfer, T. (1980). The representation of landmarks and routes. Child Development, 51, 1065–1071. doi:10.2307/1129545 Darken, R. P., Allard, T., & Achille, L. B. (1999). Spatial Orientation and Wayfinding in Large Scale Virtual Spaces II. Presence (Cambridge, Mass.), 8(6).
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Darken, R. P., & Banker, W. P. (1998). Navigating in Natural Environments: A Virtual Environment Training Transfer Study. Proceedings of VRAIS, 98, 12–19. Darken, R. P., & Peterson, B. (2001). Spatial Orientation, Wayfinding, and Representation . In Stanney, K. (Ed.), Handbook of Virtual Environment Technology. Stanney. Darken, R. P., & Sibert, J. L. (1996). Wayfinding strategies and behaviours in large virtual worlds. Proceedings of ACM CHI96, 142-149. Darroch, I. Goodman J. Brewster S. & Gray P. (2005) The Effect of Age and Font Size on Reading Text on Handheld Computers. Proceedings of IFIP INTERACT05: Human-Computer Interaction, pp. 253-266. Dix, A. Finlay J. Abowd G. & Beale R. (1993). Human computer interaction. New York: Prentice Hall. Doyle, S., Dodge, M., & Smith, A. (1998). The potential of web - based mapping and virtual reality technologies for modeling urban environments. Computers, Environment and Urban Systems, 22(2), 137–155. doi:10.1016/S01989715(98)00014-3 Eberts, R. E. (1994). User interface design. Englewood Cliffs, NJ: Prentice Hall. Egsegian, R., Pittman, K., Farmer, K., & Zobel, R. (1993). Practical applications of virtual reality to firefighter training. In Proceedings of the 1993 Simulations Multiconference on the International Emergency Management and Engineering Conference (pp. 155–160). San Diego, CA: Society of Computer Simulation Feldman, A., & Acredolo, L. P. (1979). The effect of active versus passive exploration on memory for spatial location in children. Child Development, 50, 698–704. doi:10.2307/1128935
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Ford, N., & Chen, S. Y. (2001). Matching/mismatching revisited: An empirical study of learning and teaching styles. British Journal of Educational Technology, 32(1), 5–22. doi:10.1111/14678535.00173 Foreman, N., Stanton, D., Wilson, P., & Duffy, H. (2003). Spatial Knowledge of a Real School Environment Acquired From Virtual or Physical Models by Able Bodied Children and Children With Physical Disabilities. Journal of Experimental Psychology, 9(2), 67–74. Gallistel, C. R. (1990). The organisation of learning. Cambridge M.A: The MIT Press. Goerger, S. Darken R. Boyd M. Gagnon T. Liles S. Sullivan J. & Lawson J.P (1998).Spatial Knowledge Acquisition from Maps and Virtual Environments in Complex Architectural Spaces. Proceedings of the 16th Applied Behavioral Sciences Symposium, 2223, April, U.S. Air Force Academy. Colorado Springs, 610. Golledge, R. G., Dougherty, V., & Bell, S. (1995). Acquiring Spatial Knowledge: Survey versus Route Based Knowledge. Unfamiliar Environments Reginald Annals of the Association of American Geographers, 85(1), 13158. Gomez, L. M. Egan D.E. & Bowers C. (1986). Learning to use a text editor: Some learner characteristics that predict success. HumanComputer Interaction, 2, 1–23. Goodenough, D. (1976). The role of individual differences in field dependence as a factor in learning and memory. Psychological Bulletin, 83, 675–694. doi:10.1037/0033-2909.83.4.675 Gouteux, S., & Spelke, E. (2001). Children’s use of geometry and landmarks to reorient in an open space. Cognition, 81, 119–148. doi:10.1016/ S0010-0277(01)00128-7
Learning Space in Virtual Environments
Guilford, J. P., & Zimmerman, W. S. (1948). The Guilford Zimmerman Aptitude Survey. The Journal of Applied Psychology, 32, 24–34. doi:10.1037/h0063610 Hasher, L., & Zacks, R. T. (1979). Automatic and effortful processes in memory. Journal of Experimental Psychology, 108, 356–388. Hegarty, M., & Waller, D. (2004). A dissociation between mental rotation and perspective-taking spatial abilities. Intelligence, 32, 175–191. doi:10.1016/j.intell.2003.12.001 Howes, A. Jones D. Payne S. & Ruddle R. (1999). Navigating Discontinuous Virtual Worlds. Workshop on Spatial cognition in real and virtual environments at the Max Planck Institute, Tuebingen. Hunt, E. & Waller, D. (1999). Orientation and wayfinding: A review. ONR Technical Report. industrial applications. Computer Graphics, 17, 671–677. Kirasic, K. C. (2000). Age differences in adults’ spatial abilities, learning environmental layout, and wayfinding behavior. Spatial Cognition and Computation, 2, 117–134. doi:10.1023/A:1011445624332 Koh, G., Wiegand, T. E., Garnett, R., Durlach, N., & Cunningham, B. S. (1999). Use of Virtual Environments for Acquiring Configurational Knowledge about Specific RealWorld Spaces. Preliminary Experiment, 8(6), 632–656. Kuipers, B. J. (1975). A frame for frames: Representing knowledge for recognition . In Bobrow, D. G., & Collins, A. (Eds.), Representation and understanding: Studies in cognitive science. New York: Academic Press. Lampinen, J., Copeland, S., & Neuschatz, J. (2001). Recollections of things schematic: rooms schemas revisited. Cognition, 27, 1211–1222.
Liu, Y., & Ginther, D. (1999). Cognitive Styles and Distance Education. Online Journal of Distance Learning Administration, 2(3). Lynch, K. (1960). The Image of the city. The MIT press. Maguire, E. A. (1999). Burgess N. & O’Keefe J. (1999) Human spatial navigation: cognitive maps, sexual dimorphism, and neural substrates. Current Opinion in Neurobiology, 9, 171–177. doi:10.1016/S0959-4388(99)80023-3 Maguire, E. A. Gadian D.G. Johnsrude I.S. Good C.D. Ashburner J. Frackowiak R.S.J. & Frith C.D. (2000). Navigation related structural change in the hippocampi of taxi drivers. Proceedings of the national academy of science (USA), 97(8) Maguire, E. A., Frackowiak, R. S. J., & Frith, C. D. (1996). Recalling Routes around London: Activation of the Right Hippocampus in Taxi Drivers. The Journal of Neuroscience, 17(18), 7103–7110. Mania K. Robinson A. & Brandt K.R. (2005). The effect of memory schemas on object recognition in virtual environments. Presence: Teleoperators and Virtual Environments archive, 14(5), 606 – 615 Mathews, M. H. (1992). Making Sense of Place: Children’s Understanding of Large Scale Environments. Hertfordshire, England: Harvester Wheatsheaf. Messick, S. (1976). Individuality in learning. San Francisco: Jossey-Bass. Moffat, S. D., Hampson, E., & Hatzipantelis, M. (1998). Navigation in a “virtual” maze: sex differences and correlation with psychometric measures of spatial ability in humans. Evolution and Human Behavior, 19, 73–78. doi:10.1016/ S1090-5138(97)00104-9
147
Learning Space in Virtual Environments
Montello, D. R. (2005) Navigation. In P. Shah & A. Miyake (Eds.), The Cambridge Handbook of Visuospatial Thinking. Cambridge University Press, 257-294. Newman, E. L., Caplan, J. B., Kirschen, P., Korolev, I. O., Sekuler, R., & Kahana, M. J. (2007). Learning your way around town: How virtual taxicab drivers learn to use both layout and landmark information. Cognition, 104, 231–253. doi:10.1016/j.cognition.2006.05.013 Pask, G. (1979). Final report of S.S.R.C. Research programme HR 2708. Richmond (Surrey): System Research Ltd. Passini, R. (1984). Wayfinding in Architecture. New York: Van Nostrand Reinhold Company Inc. Pelagatti, G., Negri, M., Belussi, A., & Migliorini, S. (2009). From the conceptual design of spatial constraints to their implementation in real systems. In Proceedings of the 17th ACM SIGSPATIAL international Conference on Advances in Geographic information Systems (Seattle, Washington, November 04 - 06, 2009). (GIS ‘09. ACM, pp 448-451)New York, NY. Pine, D. S., Grun, J., Maguire, E. A., Burgess, N., Zarahn, E., & Koda, V. (2002). Neurodevelopmental Aspects of Spatial Navigation: A Virtual Reality fMRI Study. NeuroImage, 15, 396–406. doi:10.1006/nimg.2001.0988 Riva, G., & Gambrini, L. (2000). Virtual reality in telemedicine. Telemedicine Journal, 6, 327–340. doi:10.1089/153056200750040183 Robertson, I. T. (1985). Human information processing strategies and style. Behaviour & Information Technology, 4(1), 19–29. doi:10.1080/01449298508901784 Rose, F. D., Attree, E. A., Brooks, B. M., Parslow, D. M., & Penn, P. R. (2000). Training in virtual environments: transfer to real world tasks and equivalence to real task training Authors. Ergonomics, 43(4), 494–511. doi:10.1080/001401300184378
148
Rose, F. D., & Foreman, N. P. (1999). Virtual reality. The Psychologist, 12, 551–554. Ruddle, R. A., Payne, S. J., & Jones, D. M. (1997). Navigating buildings in “desktop” virtual environments: Experimental investigations using extended navigational experience. Journal of Experimental Psychology. Applied, 3, 143–159. doi:10.1037/1076-898X.3.2.143 Salthouse, T., Donald, K., & Saults, S. (1990). Age, Self Assessed Health Status and Cognition. Journal of Gerontology, 45(4), 156–160. Salthouse T.A. (1992). Why do adult age differences increase with task complexity?, 28, 905–918. Sandstrome, N. J., Kaufman, J., & Huettel, S. A. (1998). Males and females use different distal cues in a virtual environment navigation task. Brain Research. Cognitive Brain Research, 6, 351–360. doi:10.1016/S0926-6410(98)00002-0 Schmeck, R. R. (1988). Learning strategies and learning styles. Plenum Press. Silverman, D. R., & Spiker, V. A. (1997), Ancient wisdom—future technology. Proceedings of the Human Factor and Ergonomics Society, 41st Annual Meeting. Albuquerque, New Mexico. Smith, M. L., & Milner, B. (1981). The role of the right hippocampus in the recall of spatial location. Neuropsychologia, 19, 781–793. doi:10.1016/0028-3932(81)90090-7 Smith, R. M. (1984). Learning how to learn. Milton Keynes: Open University. Stankiewicz, B. J., & Kalia, A. (2004). Acquisition and Retention of Structural versus Object Landmark Knowledge When Navigating through a Large Scale Space. Journal of Experimental Psychology. Human Perception and Performance, 33(2), 378–390. doi:10.1037/0096-1523.33.2.378
Learning Space in Virtual Environments
Stanney, K. M., Mourant, R. R., & Kennedy, R. S. (1998). Human Factors Issues in Virtual Environments: A Review of the Literature. Presence (Cambridge, Mass.), 7(4), 327–351. doi:10.1162/105474698565767 Stanney, K. M., & Salvendy, G. (1995). Information visualization; assisting low spatial individuals with information access tasks through the use of visual mediators. Ergonomics, 38(6), 1184–1198. doi:10.1080/00140139508925181 Thorndyke, P. (1980). Performance models for spatial and locational cognition (R2676ONR). Washington, D.C.: The Rand Corporation. Thorndyke, P., & Hayes-Roth, B. (1982). Differences in spatial knowledge acquired from maps and navigation. Cognitive Psychology, 14, 560–589. doi:10.1016/0010-0285(82)90019-6 Vicente, K. J., Hayes, B. C., & Williges, R. C. (1987). Assaying and isolating individual differences in searching a hierarchical file system. Human Factors, 29(3), 349–359. Vila, J. Beccue B. Anandikar S. (2002). The Gender Factor in Virtual Reality Navigation and Wayfinding. Proceedings of the 36th Hawaii International Conference on System Sciences (HICSS’03). Vinson, N. G. (1999) Design Guidelines for Landmarks to Support Navigation in Virtual Environments. Proceedings of CHI ‘99, Pittsburgh, PA. Waller, D., Hunt, E., & Knapp, D. (1998). The transfer of spatial knowledge in virtual environment training. Presence (Cambridge, Mass.), 7, 129–143. doi:10.1162/105474698565631 Waller, D., Knapp, D., & Hunt, E. (2001). Spatial Representations of Virtual Mazes: The Role of Visual Fidelity and Individual Differences. Human Factors . The Journal of the Human Factors and Ergonomics Society, 43(1), 147–158. doi:10.1518/001872001775992561
Weisman, J. (1981). Evaluating achitectural legibility: Way-finding in the built environment. Environment and Behavior, 13, 189–204. doi:10.1177/0013916581132004 Whitaker, L. A. (1996). Getting around in the natural world. Ergonomics in Design, 4, 3, 11–15. Wilkniss, S. M., Jones, M., Korel, D., Gold, P., & Manning, C. (1997). Agerelated differences in an ecologically based study of route learning. Psychology and Aging, 12(2), 372–375. doi:10.1037/0882-7974.12.2.372 Wilson, P. N., Foreman, N., & Tlauka, M. (1997). Transfer of spatial information from a virtual to a real environment. Human Factors, 39(4), 526–531. doi:10.1518/001872097778667988 Witkin, H. A., Moore, C. A., Goodenough, D. R., & Cox, P. W. (1977). Fielddependent and field independent cognitive styles and their educational implications. Review of Educational Research, 47, 1–64. Witmer B.G. Bailey J.H. & Knerr B.W. (1995), Training Dismounted Soldiers in Virtual Environments: Route Learning and Transfer. U.S. Army Research Institute for the Behavioral and Social Sciences Witmer, B. G., Bailey, J. H., Knerr, B. W., & Parsons, K. C. (1996). Virtual spaces and real world places: transfer of route knowledge. International Journal of Human-Computer Studies, 45(4), 413–428. doi:10.1006/ijhc.1996.0060 Witmer, B. G., & Sadowski, W. J. (1998). Nonvisually guided locomotion to a previously viewed target in real and virtual environments. (Special Section: Virtual environments: Models, Methodology, and Empirical Studies). Human Factors, 40, 478–485. doi:10.1518/001872098779591340
This work was previously published in Virtual Worlds and E-Commerce: Technologies and Applications for Building Customer Relationships, edited by Barbara Ciaramitaro, pp. 216-230, copyright 2011 by Business Science Reference (an imprint of IGI Global). 149
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Chapter 1.11
Business Analytics Success: A Conceptual Framework and an Application to Virtual Organizing Hindupur Ramakrishna University of Redlands, USA Avijit Sarkar University of Redlands, USA Jyoti Bachani University of Redlands, USA
ABSTRACT The chapter presents a conceptual framework that identifies technological and organizational factors that impact the success of business analytics (BA) use in organizations in general and virtual organizations in particular. The framework explores BA success through three business disciplines: decision sciences (DS), information systems (IS), and management. We believe that BA success comes from proper interaction between the three disciplines. Though the concept of BA has been around for a long time in business literature, its DOI: 10.4018/978-1-60960-587-2.ch111
full potential use has not been realized in organizations for a variety of reasons. The information and communication technologies (ICT) that have made virtual organizations, and flattening of the world possible have also created a better infrastructure/environment for use of BA by providing the capability to collect massive amounts of data and by providing easier-to-use analytic tools. Currently, BA is being touted as the next information technology (IT) capability that will generate considerable value including competitive advantage to businesses. In this chapter we present and discuss our framework, discuss its viability through existing examples of BA success, and finally apply the framework to a special emerg-
Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
Business Analytics Success
ing context in organizations, virtual organizing. Implications of this framework for identifying and filling research gaps in this area and implications for managers interested in exploring BA use in their organizations are presented.
INTRODUCTION Though the history of organizational/managerial decision-making is long, its movement from “decision-making as an art” to “decision-making as a science” is more recent. Parallel, and sometimes independent, developments in three fields have aided this evolution. Management theory focused on the typologies and processes of decisionmaking and the behavioral aspects (Henderson & Nutt, 1980; Kepner & Tregoe, 1965; Mintzberg et al, 1976; Simon, 1977; Tydeman et al, 1980)—the softer side. Decision Sciences (DS) as a field was formally defined in the early 1970s, and the field included the work done in management theory and extended it through the use of quantitative techniques—the harder side. Though quantitative techniques, mathematical and statistical, were available for use by organizations and managers, their use was not widespread due to the lack of availability and ease-of-use of the tools and data necessary for quantitative analysis. A parallel development in information systems (IS) that made the necessary tools and data available, and easier to use by most managers, made it possible for organizations to capture/collect/access massive amounts of data regarding the organizational processes and analyze them for decision-making through the use of quantitative analysis. Business analytics (BA)—the use of analytic techniques (driven by data and quantitative analysis) for organizational/managerial decision-making, a new term that has been coined recently—is a result of the parallel developments in the three disciplines, Management, DS, and IS. History of analytic techniques and data to improve organizational decision-making can be traced to
the 1960s to the development of the first decision support systems (DSS) (Power, 2001, 2002, and 20042004). Analytics has also been defined to be a subset of business intelligence (BI). BI includes both data access and reporting, and analytics. More formal definitions of BI and its essential components can be found in Negash and Gray (2003). The terms “data mining” and “business analytics” have also been used interchangeably in the literature (Kohavi, Rothleder, and Simoudis, 2002) to indicate the general process of investigation and subsequent analysis of data to identify the existence of new and meaningful trends. Relatively few formal definitions of BA exist in the literature. Davenport and Harris (2007) define analytics as “the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions.” Davenport & Harris further state that the “analytics may be input for human decisions or may drive fully automated decisions.” While data access and reporting help businesses understand “what happened,” and “what actions are needed,” analytics helps them to understand “why is this happening,” “what if these trends continue,” and perhaps forecast “what will happen next” (Davenport & Harris, 2007). Prior work related to the Management, IS, and DS aspects of BA is extensive in each area. Success in decision-making and problem-solving (including success of different phases) and its relation to different problem-solving methods and individual and group behavior has been studied extensively in the Management literature. Data collection, storage, and access issues have been addressed extensively in IS literature. Extensive work on building a variety of quantitative models exists in DS (sometimes also referred to as Management Science or Operations Research) literature. Some literature also exists that integrates two disciplines – for example, group decision support systems (GDSS) work that integrates Management and IS aspects of BA. Davenport’s (2006) work is the first attempt to link explicitly the three disciplines
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critical to BA success. Davenport identified three key attributes for organizations to be analytically competitive – (1) widespread use of modeling and optimization, (2) an enterprise approach, and (3) senior executive advocates. In the same work, the author argues that organizational success in BA can result if analytics-minded leaders actively recruit analytically competent people who are proficient in the use of technology and can decide “when to run the numbers.” Though some case-based evidence exists, Davenport’s (2006) work represents the only instance in the literature which hints that BA success results from an optimal blend of competence in several business disciplines. However the interrelationship between the disciplines towards the achievement of business analytics success has not been explicitly developed in his research. For BA to be used extensively in organizations and for it to succeed in providing value to organizations, it is important to build and test a conceptual model of BA success – a model that links relevant DS, IS, and Management factors (the independent variable set) to BA success (the dependent variable set). We believe that BA success is derived not only from understanding factors in each discipline but also from a good understanding of the relevant intersections/interactions of the three aspects of BA (DS, IS, and Management). From our review of the literature, it is clear that BA use in organizations is currently limited. Some factors that may have contributed to this are (1) a lack of specialized skill in quantitative modeling both at an individual and organizational level, (2) limited/restrictive IT infrastructure, often with the lack of enterprise-wide support for IT initiatives necessary for BA implementation, and (3) lack of an organizational culture that can successfully engineer a company-wide shift in decision-making paradigm. In addition, there is a clear lack of metrics of BA success that may have prevented companies from linking measures of BA success to their strategic goals or establish a connection between BA-related activities under-
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taken and financial outcomes achieved (Ittner and Larcker, 2003). Further, failures of BA initiatives in organizations have not been documented in the academic literature. Overall it is fair to say that BA success and the factors/actions that lead to it are not well understood. The primary objective of this chapter is to develop and present a framework for BA success. We argue that BA success lies at the intersection of three disciplines (1) decision sciences, (2) information systems, and (3) management. Though a considerable body of literature, and some case-based evidence, exists in different business disciplines as it pertains to BA, prior work has mostly been discipline-specific and not well integrated. We are building our framework based mostly on prior research in the three distinct business disciplines—three different components that are needed for BA success in organizations: (a) basic quantitative modeling and analysis needs with respect to data, tools, models, and interfaces, (b) IT infrastructure needs toward the support and successful implementation of BA technologies, and (c) top-down commitment to make analytics central to strategy coupled with an organizational culture that supports and rewards skillful use of data-driven analysis for the purpose of organizational decision-making. Clearly a oneto-one correspondence between each previous component (a), (b), and (c) and broader business domains of DS, IS, and Management, respectively, is intuitively apparent. If we take one or more of the disciplines/components away, BA success will be compromised. Data and models are key to quantitative analysis. But without adequate IT support, it is not possible to store large-scale data and run computationally intensive algorithms that provide modeling horsepower. An enterprise with access to data, models, and IT infrastructure will not be “BA successful,” however, in the absence of top-level commitment for measuring, testing, and evaluating quantitative evidence for decisionmaking purposes.
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Another unique contribution of this work is the application of our framework to virtual organizing. This application is cognizant of the fact that decision-making in businesses today is increasingly distributed in time and space. The increased use of group-based problem-solving (Davenport, 2006) and virtual teams (Jessup and Valacich, 2007) poses challenges and provides opportunities in each discipline that is a part of our BA success framework. We apply our model to virtual environments and explore several benefits of virtualization and also identify challenges which result due to the ability to span time and space. The chapter is organized as follows: (1) we present some discussion/review of literature on BA and in the three disciplines as they relate to BA, (2) we present our framework, its development, description of the framework, and its application/implications for research and practice, (3) we present the application of the framework to virtual organizing and justification for the application, and (4) we present some conclusions.
RELATED RESEARCH/ DEVELOPMENTS In order to develop a conceptual framework for BA success it is important first to understand developments in BA and related fields in the past few decades. In this section, we explore the developments in BA use in organizations and developments in the three fields/disciplines that are believed to have an impact on BA success: management, DS, and IS.
Business Analytics As we have noted earlier, Davenport and Harris (2007) state that business analytics is a subset of BI. They define BI as “a set of technologies and processes that use data to understand and analyze business performance.” According to Davenport and Harris, BI includes (1) data access and report-
ing, and (2) analytics. While data access and reporting includes tools such as standard reports, ad hoc reports, queries, and alerts, analytics includes tools such as optimization, predictive modeling, forecasting, and statistical analysis. Davenport & Harris suggest that the degree of intelligence increases as analytics complements data access and reporting. The terms “data mining” and “business analytics” have also been used interchangeably in the literature (Kohavi, Rothleder, & Simoudis, 2002) to indicate the general process of investigation and subsequent analysis of data to identify the existence of new and meaningful trends. Like Davenport, Kohavi et al. identify data collection, storage, and processing as issues pertinent to analytics and state that mined data is used extensively by business organizations that employ analytics for everyday operations. Over the last few years groundbreaking analytics-based systems such as online reservations (at American Airlines), predictive maintenance (at Otis Elevator), and revenue management systems (at Marriott International to determine the optimal price of guest rooms) have become more and more common. The fact that analytics can be applied to many business processes to add value and gain competitive advantage has been demonstrated by organizations like Amazon.com, Harrah’s, Capital One, and the Boston Red Sox, which have dominated their respective domains by employing analytics for key strategic decisionmaking purposes. Davenport and Harris (2007) have identified analytical competitors in a variety of industries, including consumer products, telecommunications, financial services, pharmaceuticals, transport, retail, hospitality and entertainment, airlines, and e-commerce. The same work also mentions the use of analytics by various levels of government – national, state, and local, for crime prevention, predictive modeling of contagious diseases, resource (gas, oil, minerals, etc.) optimization, and fraud detection. In fact sales, marketing, supply chain
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optimization, and fraud detection are several areas identified by Kohavi et al (2002) that routinely use business analytics. The same authors have mentioned that organizations in financial, retail, manufacturing, utilities, and telecommunications sectors increasingly want their field personnel to have access to BA information through wireless devices. Apte et al. (2002) state that industries that have derived benefits from data mining include insurance, direct mail marketing, telecommunications, retail, and healthcare. A summary of several successful BA applications is tabulated in Table 1. Each specifically describes the nature of the application, and tools, techniques, methodologies, or paradigms employed by the respective organization, and BA success measures used. A detailed list of several other business functions with scope for application of business analytics, description of the exact nature of usage of analytics (for example in capacity planning, demand-supply matching, location analysis, reducing inventory and preventing stock-outs, etc. toward the effective management of supply chains), and corresponding examples from industry can be found in Davenport (2006). Davenport and Harris (2007) provide the only instances when organizations have not been particularly successful in spite of adopting BA. These organizations are both prominent players in the US aviation industry – United Airlines and American Airlines. Davenport and Harris postulate that two factors have prevented these airlines from succeeding with their analytical strategies – (a) their analytics support an obsolete business model, far superior versions of which have been adopted by their competitors, and (b) other airlines too have adopted BA since airline industry data has become more readily available from associations and external providers. The BA literature is replete with examples of BA success. Several such examples are tabulated earlier in Table 1. In some instances, analogous metrics of BA success have been used. For ex-
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ample, market share at Harrah’s, earnings per share and return on equity at Capital One, market capitalization at Progressive have been used as surrogates for revenue. Negash and Gray state that ROI analysis is frequently necessary for BI projects and list statistics related to ROI figures for given levels of investment. Davenport and Harris (2007) contains similar statistics. Sports teams have often used number of games /titles won or reduction in player injuries as metrics of analytics success. Revenue increase (or cost reduction) is a commonly used (and intuitive) metric of BA success; however, our research did not yield any consistent metrics of business analytics success across industries in different sectors. Davenport et al. (2001) introduced a model for building analytic capability in organizations. The authors discussed the contextual factors in the model (a particular business strategy, a particular set of skills and experiences, a particular set of culture and organizational structure, and a particular set of technology and data capabilities) and also constructed a decision tree for implementing analytical capability. The authors also presented a framework that identifies and articulates the primary success factors which are required to develop broad organizational capabilities for transforming electronic data into knowledge and then into business results. Luecke (2006) cites several characteristics shared by organizations that routinely make good decisions. These include but are not restricted to employees who recognize behavioral traps that lead to bad decisions, decision-makers who understand their roles and possess skills their roles require, development of a number of feasible decision alternatives, availability of an array of decision-making tools and processes, and overall people who are dedicated to improving decision quality. Along similar lines, Davenport (2006) outlines the characteristics and practices at analytics-driven organizations and describes some of the very substantial changes that other organizations must undertake to compete on
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Table 1. Examples of successful BA applications in industry Example #
Organization (Reference)
Specific BA Application
Methodology/Paradigm Employed
BA success measures
1
Capital One (Davenport, 2006; Davenport and Harris, 2007)
Maximized the likelihood that (a) potential customers will sign up for credit cards, and (b) they will actually pay back Capital One once they sign up.
Simulates more than 30,000 scenarios each year with different interest rates, incentives, direct mail advertising, and several other variables of interest
Customer retention has increased by 87% and the cost of acquiring a new account has decreased by 83% over a period of time.
2
Netflix (Davenport and Harris, 2007)
Endeavored to match buying patterns with customer behavior; also in deciding what to pay for the distribution rights of DVDs.
Hired mathematicians who developed algorithms and subsequently computer codes to “define clusters of movies, connect customer movie rankings to the clusters, evaluate thousands of ratings per second, and factor in current Website behavior – all to ensure a personalized Webpage for each visiting customer”.
Has grown from $5 million in revenues in 1999 to $1 billion in 2006.
3
Progressive (Davenport, 2006; Davenport and Harris, 2007)
Profitably insured high risk customers, a constituent that competitors would otherwise ignore blindly assuming that these customers are “loss-making”.
Closely analyzed data to categorize customers into several narrow clusters, each characterized by age, college education, previous accident history, credit scores, etc. in order to rank them as high versus low risk, and then employed regression analysis to identify factors that closely define losses a particular cluster of customers produces.
Market capitalization doubled during the 2003-2007 period to $23 billion.
4
Marriott International (Davenport, 2006)
Established an analytical system for optimal pricing of guest rooms, conference facilities, and catering.
Pioneered the concept of revenue management, in which an analytical model computes and maximizes actual revenues as a percentage of optimal rates that could have been charged to customers; also developed a system to optimize offerings such as price discounts to frequent customers.
Actual revenues when computed as a percentage of optimal rates increased from 83% to 91%; annual profit increased by $86 million in 2004.
5
Harrah’s Entertainment (Davenport and Harris, 2007)
Developed the ability to use realtime data to make decisions on their business processes right down to individual machines where their patrons are gaming.
This is achieved by changing the odds based on the behavior of patrons that are analyzed as soon as they use the Harrah’s card. The incentives required to bring these patrons into the casino and to keep them playing can be manipulated based on exact data collected from their card usage.
Increased market share from 36% to 43% between 1998 and 2004.
6
Proctor and Gamble (Camm et al, 1997)
Successfully redesigned North American supply chain by integrating production, sourcing, and distribution functions.
A group of about 100 analysts from several organizational functions such as operations, supply chain, sales, marketing, etc. worked in tandem. For example, sales and marketing analysts supplied data on opportunities for growth in existing markets to analysts who design supply and distribution networks.
Reduced number of North American plants by almost 20% thereby saving over $200 million in pretax costs per year in the mid 1990s.
continues on following page
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Table 1. conitinued Example #
Organization (Reference)
Specific BA Application
Methodology/Paradigm Employed
BA success measures
7
Sears, Roebuck and Company (Weigel and Cao, 1999)
Tremendously improved their technician dispatching and home-delivery business.
Employing an analytically powerful vehicle routing and scheduling system within a geographic information systems (GIS) based framework to run its delivery and home service fleets more efficiently.
Achieved $9 million in onetime savings and over $42 million in annual savings; were able to consolidate vehicle dispatch facilities by more than 50%.
8
Deere and Company (Davenport and Harris, 2007)
Attempted to reduce inventory and complexity by eliminating product configurations that were difficult to produce and sell.
Worked with academic collaborators and successfully optimized configurations of products on two product lines.
Profits on the two lines increased by 15% due to 3050% reduction in the number of product configurations.
analytics turf. These changes include a top-down commitment to make analytics central to strategy, abundant use of complex data and statistical analysis, significant investment in technology, and executives’ unswerving commitment to change the way employees think, work, and are treated. Davenport (2006) further outlines four factors in defining analytical competition. These are (a) distinctive capability, (b) enterprise-wide analytics, (c) senior management commitment, and (d) large scale ambition. Davenport and Harris (2007) add that it would be a “huge mistake” to call analytics a happy marriage between analytical tools and information technology (IT). The authors argue that “human and organizational aspects” of analytics distinguish the successful exponents of BA in various industries. The hint that BA success stems from an optimal blend of (i) distinctive analyticsfriendly management style with (ii) analytical tools, and (iii) IT is unmistakable. However the fact that (i), (ii), and (iii) each represent one key business discipline has not been explicitly stated in any existing literature. Moreover the current literature also lacks a conceptual framework of BA success. In summary, though BA is a newly defined field, it is clear that research in BA-related fields such as DSS, BI, data mining, etc. have been around for many decades. There have been many successful
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(and some unsuccessful) applications reported in the literature. The applications have been in diverse organizational functions and in diverse industries. In addition, we can speculate that there must have been many unreported BA failures. As the field is fairly new, academic research that assists in developing a good understanding of factors that contribute to BA success (or failure) are scarce (Negash & Gray, 2003), and the evidence from most existing research is anecdotal. While the exact metrics of business analytics success can be industry specific, our review of the literature reveals that understanding of factors and/or disciplines, which combine to generate BA success, is limited. Several examples of BA applications in industry have been documented, and frameworks for classifying organizations competing on analytical turf exist. However, a good understanding of what contributes to BA success, as well as metrics of BA success, is fuzzy and almost non-existent in the literature.
Management Factors for BA Success The field of management has explored managerial/organizational decision-making, one of the core activities of management as identified by Mintzberg (1973), from multiple perspectives. They include: (1) the idea of rational decision-
Business Analytics Success
making that first originated in neo-classical economic theories, (2) the concept of bounded rationality and decision-making as “satisficing” as opposed to optimizing, (3) the garbage can model of decision-making. Management literature has also dealt with many aspects of managerial decision-making. The behavioral theory of the firm focused research on the managerial behaviors and their impact on organizations (Cyert & March, 1992). The pros and cons of individual versus group decision-making and the phenomenon of groupthink have been identified (Janis, 1972). The individual biases in decision-making (Kahneman et al, 1982) and the importance of framing the decisions have been studied. The importance of politics was highlighted by Allison and Zelikow’s (1999) study of the Cuban Missile Crisis and the different ways decisions were made in that situation. The roles of other organizational factors, (e.g. technology or organizational structure) on managerial decisions have also been investigated (Lawrence and Lorsch, 1967; Scott, 2003; Thompson, 1967, 2003; Woodward 1975). The behaviorists have questioned the standard rational model of economics, and bounded rationality is now widely accepted as an alternative assumption for explaining managerial behaviors (Simon 1997). In the meantime, progress in the fields of IS and DS led to better tools, techniques, models, and computational power to allow managers to be increasingly scientific and rational in their decision-making. Evolutionary economics and the theory of the firm were becoming the basis for newer management theories. Together, these changes led to the present situation, when we consider that it is imperative to take a joint look across management, DS and IS, in order to really understand the impact of managerial decisionmaking on organizational success. Firms with managers who know how to deploy IS resources well were better positioned toward (hard) evidence-based decision-making (Ayers, 2007). Thus, IS offered competitive advantage to these firms. According to the resource-based
view of the firm, organizations achieve competitive advantage by securing inimitable and scarce resources (Barney, 1991). With increasing automation and affordable technology, IS is available to all firms as a resource, but only a handful are able to deploy it in a manner that creates competitive advantage. The differentiation comes from having managers who know how to play their decisional role well and are allowed to do so by the organizational context in which they operate. By choosing to focus on the important decisions and knowing the appropriate information to gather and process to inform these decisions, the managers can use IS to build the unique capability that can provide a competitive advantage to their firms. One way to classify organizational decisionmaking contexts is by the organizational and analytic complexity, from simple to complex. Figure 1 presents a 2x2 matrix that shows four possible different decision-making contexts (Bachani, 2005). Analytically complex decisions are those that have a lot of uncertainty in factors that influence the outcome of the decision. An example of an analytically complex decision is when a firm needs to build a new factory at a substantial cost. There are several uncertainties in this decision, such as predicting demand for the product, predicting the competitor’s investment in capacity, forecasting future prices for the product, and so on. Organizationally complex decisions require many people from different parts of the organization to be involved in the process since the choice will impact what they all do. For example, consider managers who are deciding on the features for the new version of a product. There may not be too many changes to the product’s core features, but any change requires coordinated effort that means involving different parts of the organization, from taking into account the voice of customers by consulting the customer service department, the input from the distributors by consulting the sales division of the company, the cost of the new features by getting estimates from the accounting department, the compatibility and production
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Figure 1. Business analytics adoption matrix
capabilities by consulting the operations department, and so on. When a business process is analytically and organizationally simple, there is no need for any investment in developing systems or competencies for handling these situations. Managers make the decisions promptly. If the business process is analytically complex but organizationally simple, then a specific tool to handle the nature of the analytical complexity should be deployed. These include specially designed models like forecasting models, risk analysis models, capacity planning systems, inventory management systems or other tools and techniques that address the special kind of analytical complexity associated with the business process and problem at hand. In the third case, if the business process is analytically simple but organizationally complex, then the best way to address it is through people-related methods – including facilitative leadership, training, redesigning organizational systems and structures to make communication easier, linking people across the various parts of the organization using ICTs, and so on. In the fourth situation where the business process is complex analytically as well as organizationally, there is a real need and potential for BA to make the biggest difference. It
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is in this situation that managers must make the investment in developing the BA capability. Having the right tools and techniques to deal with the analytical complexity as well as having the structures and systems that allow a better handling of organizational complexity will lead to the best outcomes for handling the business processes most efficiently. In summary, there has been an evolution in managerial/organizational decision-making from an art to a science. This has been made possible with parallel evolutions in IS and DS that have made the tools and data available for scientific (hard evidence-based) decision-making. In addition, characteristics of certain decision-making contexts dictate whether BA will lead to success. Managers should develop BA capabilities for those contexts to maximize benefits. With increased managerial acceptance of analytical techniques for decision-making, it appears the time may be ripe for BA to succeed.
Information Systems Factors for BA Success One necessary condition for BA success is the appropriate IT that supports the data, quantity,
Business Analytics Success
quality and availability, and analysis tools needs, availability and ease-of-use. Evolution in IT has made it possible for organizations to have access to massive amounts of useful data, internal as well as external, for BA use. With computerized record-keeping, organizations can access reports about customer demand, in different time periods, order size and content, customers quantities in different locations, segments of the market, account receivables, detailed inventory, and other such information that was much harder to track or consolidate without technology. The cost of data storage over this same time period has decreased at an exponential rate, thus making it possible for organizations to store more data that may be useful. There is also a trend toward sharing massive amounts of data with external entities, like Nielsen, that aggregate data from several sources to make it available to any organization that wishes to purchase it. In addition, massive amounts of demographic and related data are available from sources such as the U.S. Census Bureau. Organizations are also able to collect and store transaction data more easily due to the availability and development of standard, off-the-shelf enterprise-wide software packages that address specific business needs, e.g. enterprise resource planning (ERP) systems, customer relationship management (CRM) systems, and supply chain management (SCM) systems. When these systems are well implemented, they force users to input good quality data and assist in maintaining good data integrity. The evolution of data management technology from file management systems (of the 1960s and 1970s) to database management systems (DBMS) to data warehouses and data marts has created easier access to well integrated data with good integrity. In a related development, IT tools that assist organizations in analyzing the data have also become easier to access and use. The evolution has taken us from custom built packages for specific analysis and specific organizational decision con-
texts to standard off-the-shelf analysis packages and tool kits included as part of database packages. This has resulted in analysis tools that are better integrated with data sources and with interfaces that are easier to use. Another development in BA tools, BA capability as a Web service (as opposed to a product), has made it possible for organizations to benefit from BA without the need for an upfront investment in BA tools implementation. Business Analytics Online (BAO), a service offered by the Environmental Systems Research Institute (ESRI) of Redlands, CA, is an example of this development. Thus, IT evolution has made it easier for organizations to succeed in their BA efforts as they pertain to data and IT tools for analysis. This, in essence, has provided a necessary condition for BA success. However, BA success for any organization initially depends on the extent to which the organization has capitalized on the IT evolution in the areas discussed. For example, there are many organizations in the process of implementing enterprise-wide systems and data warehouses and data marts. As a consequence, BA success for these organizations will be limited due to data access issues. Though some organizations have good data access and, hence, a potential for BA success, many other organizations encounter data access issues. Even with the available data, the use could be limited. In a recent study by Davenport et al (2001), the authors found that less than 10% of the firms that had ERP data could cite examples of the data use for BA. They also found that few retail businesses that collect scanner data use much of that data for BA. In summary, it is clear that there are many IS-related factors that are critical for BA success. Evolution in a variety of (information) technologies has made it possible for organizations to access massive amounts of good quality data for BA success. Analysis tools have evolved from stand-alone tools with limited capability into highly sophisticated ones integrated with tools
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for data access. These developments enhance the possibility of BA success.
Decision Sciences Factors for BA Success One key factor that is critical for BA success is the use of the right quantitative analysis. This involves the application of sophisticated models, algorithms, and heuristics to solve complex business problems in various domains such as capacity planning, demand-supply matching, location planning and analysis, scheduling, and supply chain and logistics optimization. With the evolution of algorithms and computing machinery, prohibitively expensive computation times are a thing of the past. Davenport and Harris (2007) list combinatorial optimization, constraint analysis, Monte Carlo simulation, multiple regression analysis, risk analysis, price optimization, etc. as some analytical applications for various business processes. It is pertinent to mention here that all these applications belong to the broader domain of DS. Most DS models are amenable to the performance of sensitivity analysis that allows a decision-maker to simulate various alternative scenarios. Simulation models (Conchran, Mackulak, and Savory, 1995; Hwarng, 2001; Nance and Sargent, 2002) are widely used for industrial problem-solving and analysis. In several instances, sub-problems of complex industrial problems can be formulated as network optimization models. In several instances, however, a well-established model cannot be forced to fit into an actual industrial problem due to associated problem complexities. In such cases, it usually takes a substantial amount of imagination and modeling skill on the part of the management scientist, teamwork, and communication to transform a particular “real-life” industrial problem description to a well-defined problem which can then be solved using analytical tools or techniques, special purpose algorithms or heuristics, or by the use of software. The importance of creativity in
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modeling and MS overall has been highlighted in Evans (1991, 1992, 1993a, 1993b) and Tsoukas and Papoulias (1996). Hillier and Lieberman (2005) state that it is almost impossible for a single individual to be an expert in all aspects of MS. Therefore, for a full-fledged DS study, a group comprised of individuals with diverse skills and backgrounds must collaborate. Clearly virtualization can play a key role in fostering teamwork and communication among modeling associates, especially when individuals can span space and time. Another important characteristic of DS is the search for an optimal solution, loosely defined as the best solution under the given circumstances. When the search for optimal solutions often becomes prohibitively expensive (in terms of computation time) because industrial problems are simply too complex (too many variables, and/or too many constraints/relationships), heuristic approaches are employed which provide a “near-to” optimal solution. It is pertinent to mention here that top-level management, keeping in mind broader organizational targets and objectives, often decides the optimality gap. With recent advances in computing hardware and software, however, the search for an optimal solution has become faster. Bixby (2002) contains an account on how computation times of various test problems have improved over the last decade, and how the notion of “large” problem instances has evolved over the years. Bixby reports that several test problems were solved in computation times that were 52 times faster when using newer versions of the same commercial solver. The author further adds that a model that might have taken a year to solve could be solved in less than 30 seconds by 2002 due to an increase of several orders of magnitude of computing speed and algorithmic power. DS problems have always been amenable to spreadsheet modeling. Bodily (1986) suggests the use of spreadsheets to solve DS problems in 1986. Since then, spreadsheets and MS have both evolved to the extent that DS practitioners
Business Analytics Success
are solving problems in many functional areas using spreadsheets. Leon, Przasnyski, and Seal (1996) report that some areas of DS such as linear programming, simulation, project management, and forecasting use spreadsheet modeling more than some other areas such as network models and queuing. Dhebar (1993) states that systematic spreadsheet development and documentation of logic are critical in any quantitative analysis and sounds a note of caution related to the accuracy of spreadsheet models. A key step in the quantitative analysis of a problem through the development of a model is the availability and preparation of data required by the model. Data is often referred to as “uncontrollable inputs” and must be specified before analysts can feed the data to a model, specify a solution methodology and obtain meaningful outputs (often decisions). Many quantitative analysts believe that problem definition and development of a model essentially means problem solution and that data collection and preparation are trivial steps in the overall analysis framework. Nothing can be further from the truth, and the importance of data in relation to business analytics cannot be overstated. Often a large database is required to support a quantitative model, and information systems experts may become involved with the data preparation step. There are several other key modeling issues as well. One pertains to the ease of use or flexibility. The models developed in a business analytics framework must have the ability to access data from many different sources such as databases, spreadsheets, or the Internet, giving the user the flexibility to choose the most efficient and convenient way to incorporate data into the model. Another pertains to the issues of interfaces that should be straightforward and intuitive enough such that users can begin building models within minutes of installation; yet the modeling interfaces must possess depth of features to handle the most difficult problem scenarios. The scalability of models —in other words, their ability to handle
and analyze huge volumes of data—is another pertinent issue. To that end, data mining is one of the most general approaches utilized to reduce data in order to explore, analyze and understand it. Several goals that are uniquely addressed by data mining have been identified in Fayyad and Uthurusamy (2002) and include scaling analysis to large databases and scaling to higher-dimensional data and models. In summary, it is clear that many diverse factors related to DS are critical to BA success. The specific factors that will have an impact on BA success are context specific, organizational as well as decision-making. A summary (that presents the current context of BA) of BA-related evolution in the field is presented in Table 2.
FRAMEWORK FOR BA SUCCESS Development The framework for BA success has been developed over the past year. The authors began with a broad survey of existing literature in the field of business analytics in order to better understand this emerging area and the phenomena. Academic articles related to theory and practice in the area as well as trade press reports on the companies adopting and using business analytics were collected and studied. Early on in the process it was clear that the theory and academic research in the area was lagging behind practice. The cases and stories about the various companies’ experiences with adopting business analytics were not described or explained adequately with any theories from the existing literature (For a list of examples of successful BA applications in businesses, please see Table 1). Initially, we derived a list of factors/variables related to BA success from the case material. Next the authors attempted a categorization of these variables, and during the process it was clear that the variables could be classified into three broad categories:
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Table 2. BA-related evolution Evolution of the developments in management, IS, and DS that relate to BA
Current status of BA
The gap
Management €€€€€• Progress from rational decision-making to boundedly rational models of managerial decisions. €€€€€• Management awareness of analytical and computational tools and techniques that can assist decisionmaking. Going beyond IT as a support function to ICTs as a source of sustainable competitive advantage. €€€€€• Better understanding of the impact of technology on organizational structure, culture and form. €€€€€• Organizational boundaries becoming blurred with rise of ICTs and virtualization of many teams and outsourcing of many functions. IS €€€€€• Data management technologies —file management systems to DBMS to data warehouses and data marts €€€€€• Increased availability of external data integrated from many different sources €€€€€• Enterprise-wide systems that integrate & standardize organizational data €€€€€• Better understanding of factors related to IT implementation success €€€€€• Computing speed – Ability to actually solve very large and complex problems within reasonable time has increased tremendously due to (i) advances in computing machinery (hardware and software), and (ii) algorithmic improvements. DS €€€€€• Evolution in modeling tools – For example, evolution in simulation from FORTRAN-based programming to visual interactive modeling using icons, graphical depictions of scenarios, and actual pictures of system elements. €€€€€• Advances in analysis methodologies – For example variance reduction techniques, and extensive input data analysis. €€€€€• Algorithmic improvements – For example, the dual simplex algorithm with steepest edge can help solve complex optimization problems much faster. €€€€€• Popularity of spreadsheets has increased – due to their user friendliness, interactive nature, ability to support what-if analysis, and built-in presentation features. €€€€€• Paradigm shift in industry – decision-making based on hard numbers as more and more data has become available.
Managerial acceptance of technology as being central to business success, not just a support function. Extensive availability of analysis tools Potential for extensive data availability Success in BA use by early adopters
Lack of a good understanding of factors, organizational/managerial, IT, and MS, that lead to BA success.
managerial/organizational, information systems (IS), and decision sciences (DS). Once it was clear to us that these factors had not been identified in the BA literature because these were traditionally studied in three separate disciplines, we returned to do a more in-depth literature review by searching for articles in each
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What is possible Widespread BA use and success in organizations.
of these three disciplines. We used keywords related to the business analytics success factors. For example, we searched articles on modeling, decision-making, data integrity, decision support systems, data mining, business intelligence, etc. Though we could develop a more exhaustive list of factors that could impact BA success, it
Business Analytics Success
Figure 2. Model of business analytics success in organizations
became clear that the interactions between the factors (within and among disciplines) played a critical role. We have presented this idea in a simple model in Figure 2. To operationalize the model into a useable framework for BA success, we developed a list of factors/variables under each of the three disciplines. The framework consists of the dependent variable set (i.e., BA success factors/variables), the three sets of independent variables (i.e., managerial/organizational, IS, and DS variables), and the relationships between the variables (i.e., relationships between independent variables, the interactions, and relationships between dependent and independent variable sets). In the remainder of this section, we present this framework. First, we present our conceptualization of BA success (the dependent variable for our framework). Second, we present the disciplinespecific factors with justification for including each of them. We then explore some interactions, both two-way and three-way, between the three sets of discipline-specific factors that have been discussed in some case studies of successful BA applications. Finally, we conclude this section by presenting the application (or implications) of the framework to managers and researchers.
Components Motivation for any initiative that requires some expenditure (classified either as cost or investment) in an organization usually comes from survival, efficiency, or effectiveness. An initiative with the main motivation as survival usually deals with an organizational capability/need that is necessary just to stay in business. For example, an ATM network for a bank is the cost of doing business (i.e., cost of survival). Efficiency is a measure of output/input – i.e., the efficiency increases as more output is produced with the same level of input. Effectiveness, on the other hand, is a measure of market relevancy of the business. Defined differently, efficiency is “doing the thing right” and effectiveness is “doing the right thing.” Success of an initiative is a measure of how well the (survival, efficiency, or effectiveness) objectives are met. Success of BA initiatives can also be measured in this way. Methodologies/procedures for justifying initiatives vary depending on the context. Some common approaches are net present value (NPV), internal rate of return (IRR), return on investment (ROI), and total cost of ownership (TCO). On the cost side of the computations, there could be one-time or recurring costs or fixed and variable costs. On the benefits side there could be one-time
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and/or recurring benefits from an initiative. These concepts can also be applied to BA initiatives. Our analysis of some successful BA applications (as listed in Table 1) yields the following success measures that have been used: customer retention rate, cost of customer acquisition, reduction in cost of operations, growth in market capitalization, revenue growth, growth in market share, and growth in profit. The first three measures are clearly efficiency measures. It is important to note that efficiency is necessary but not a sufficient condition for continued success. For example, the customer retention rate may not be good if the kind of customers a business is retaining is not value producing. Efficiency combined with effectiveness is a desirable condition always. The last three measures are clearly effectiveness measures. The fourth measure listed is most likely an effectiveness measure. Measures like the one listed are very appropriate for the BA success framework we have developed. These form the dependent variables set for our framework. The independent variables for the framework of BA success are categorized into three disciplines: management, IS, and DS. Most of the variables in each category were either derived from the literature discussed in the previous section (“related developments” section) or from the reported case studies of successful BA applications in organizations (as listed in Table 1). As BA as a field is fairly new, academic research is sparse. Hence some variables were derived through conceptual reasoning. Many of the factors/variables we have listed, in Tables 3A through 3C, can be assigned values on a Likert-type scale (an ordinal scale) or can be explicitly quantified. For example, factors such as level of availability of models and tools (C1 and C2) can be rated on an ordinal scale, while factors such as the amount of per capita investment in modeling infrastructure (factor C3) and percentage of employees with advanced degrees in computational areas (factor C10) can be unequivocally measured. We will discuss managerial
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implications of such factor definitions later in this section under implications for practitioners. It is also important to note that the objective of this work is neither to build an exhaustive list of factors that is critical to BA success, nor to study relative importance of the factors with respect to each other. (We discuss these issues later in this section under implications for researchers.) Hence the factors are not ranked in Table 3A -3C in order of importance. Let’s examine each set of variables. Management factors (or variables) that are critical to BA success in organizations are listed in Table 3A. In tracing the history of business analytics and its predecessors, the computerized modeling-based decision systems, we see that rapid rise and changes in technology have forced management to look at these tools and techniques rather differently today than they did even a decade or two ago. The most important change in management factors responsible for BA success has been this shift in managerial attitude towards evidence, data and analysis-based decisionmaking (A1, A10, A11). While the economicsbased assumption of a rational economic agent was being challenged and replaced with the assumption of a boundedly rational economic agent who satisfices instead of optimizing every economic decision, the progress in technology was offering more sophisticated tools to allow individuals to make more rational choices in their business decisions. Once the senior managers were engaged with the technology and started to see it as central to success of their organizations, they began to hire, train and promote other managers who were computer/modeling savvy (A3, A4 and A5). The acceptance of rational decisions based on data and analysis using models began to spread across the different hierarchical levels within the organization. Many cases mentioned how CEO or top management commitment was crucial to BA success because they drove all the other decisions within the organizations and could influence attitudes towards BA across the organization. They con-
Business Analytics Success
Table 3. Factors/Variables—Management
Source
A1
Level of commitment of senior management to analytics and fact/data driven organizational decision-making—Rational Decision-making
Neo-classical economics.
A2
Level of flexibility in localized decision-making (for example, do regional managers have the ability to override system recommendations)—Organizational Structure and Culuture
Chandler 1962
A3
Level of comfort with models/modeling (mathematical, statistical, etc.) in the organization—Organizational capability
Barney 1991, Teece et al 1997
A4
Per capita investment in training employees to enhance their skills with models/ modeling—Organizational resources
Barney 1991
A5
Level of ability of managers to implement analytical decisions
Mintzberg 1973, Cohen et al 1972
A6
Level of teamwork, communications and partnering skills of employees—Organizational capability
Barney 1991, Janis 1972
A7
Extent of end-user compliance with (and acceptance of) analytical decisions
A8
Level of rewards for employees who support the analytics focus/mission and to insure data integrity (in data input for BA use)
A9
Level of investment in tools, techniques and employees in order to build Business Analytics capability
Teece et al 1997
A10
Level of politics in organizational decision-making and trade-offs in individual versus group decisions
Allison & Zelikow, 1999
A11
Level of bounded rationality and satisficing mentality in organizational decisions
Cyert & March 1992, Kahnemann et al 1982
Factors/Variables—Information Systems (IS)
Source
B1
Level of availability of internal data
Davenport & Harris, 2007; Davenport et al, 2001; Ferguson et al, 2005; Vesset & McDonough, 2007
B2
Level of availability of external data
Davenport & Harris, 2007; Ferguson et al, 2005
B3
Level of access of internal data
Corstjens & Merrihue, 2003
B4
Level of access of external data
B5
Level of quality of internal data
Davenport & Harris, 2007; Davenport et al, 2001
B6
Level of quality of external data
Davenport & Harris, 2007
B7
Level of integration of internal data (from numerous sources)
Corstjens & Merrihue, 2003
B8
Level of integration of internal & external data
B9
Level of availability of tools for analysis
B10
Level of ease-of-use of analysis tools
B11
Level of integration of data (internal & external) with analysis tools
B12
Level of computing power available for BA use
B13
Amount of per capita investment in computer hardware
C1
Ferguson et al, 2005; Kohavi et al, 2002 Davenport & Harris, 2007
Factors/Variables—Decision Sciences (DS)
Source
Level of availability of analytical models (such as scheduling, inventory management, forecasting, vehicle routing, site location, spatial analysis, etc.)
Labe et al. (1999)
continues on following page
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Table 3. continued C2
Level of availability of analytical problem-solving tools such as statistical software, simulation packages, decision analysis software, mathematical programming software, etc.
Labe et al. (1999)
C3
Amount of investment in modeling infrastructure (could be human resources investment or investment in tools/software, etc.) per capita.
Davenport (2006), Davenport & Harris, 2007
C4
Level of use of MS-Excel in the organization.
Leon et al. (1996), Dhebar (1993)
C5
Level of ease of use of models.
Bodily (1986), Weigel and Cao (1999)
C6
Level of ease of use of tools.
Bodily (1986), Weigel and Cao (1999)
C7
Extent of data compatibility of existing models/tools (for example, whether a mathematical programming software can read data from spreadsheets, databases, or data stored as text, and can also write output results to spreadsheets and databases).
Weigel and Cao (1999)
C8
Level of integration between different modeling tools (for example, whether a statistical sub-routine can be called upon from within a simulation package).
Weigel and Cao (1999)
C9
Given size and scale of organizational problems, what is the likelihood that models and tools will solve problems efficiently?
Bixby (2002)
C10
Percentage of employees with advanced degrees (graduate and beyond) in disciplines such as operations research, computer science, mathematics, and statistics (this is a metric of technical expertise, more specifically statistical modeling and analytical problem-solving skills, and also creativity in modeling).
Davenport, 2006, Davenport & Harris, 2007, Davenport et al. (2001), Cochran et al. (1995)
Example #
Organization
Table 3A factors
Table 3B factors
Table 3C factors
1
Capital One
A1
B1, B2, B8
C10
2
Netflix
A1
B1
C3
3
Progressive
B1, B2, B8, B4
C2
4
Marriott
A1, A2
B1
C1
5
Harrah’s
A1, A5, A8
B1
C10
6
Proctor and Gamble
A1, A6
B2
C1, C8, C10
7
Sears, Roebuck, and Co.
A4, A5, A7, A8
B1, B2, B8, B12, B13
C1, C5, C8
8
Burlington Motor Carriers
A7, A8
B5, B6
C1
9
Merrill Lynch
A6
B7, B8
C10
trolled the resources and made investments in technology, training, rewards and teamwork that were needed to set the organization up to succeed in adoption of BA (A6, A7, A8, A9). These changes added up to a change in organizational culture in some places, and there was also a corresponding shift in formal structure (A2, A8 and A10) with more decentralized decisions, better teamwork and changed organizational politics.
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Information systems factors (or variables) that are critical to BA success in organizations are listed in Table 3B. The variables are in the following categories: data, tools, and computing power. Variables B1 and B2 address the availability of internal and external data for BA applications. Availability, the collection and storage or purchase of data, is the necessary condition for BA success. However, access to these data by anyone interested in using it for a BA application is more important
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for BA success. Access many times could be restricted by turf battles in an organization or by a lack of IT support for proper access. Variables B3 and B4 address this. In addition, it is also important to have data that is of good quality, and this can either be ensured by managing internal data collection and storage well or through quality assurance from the vendor supplying the external data. This issue is addressed by variables B5 and B6. For many BA applications it is necessary to have data from a variety of sources (both internal and external) that are well integrated. It is always likely that these integration efforts will lead to discovery of inconsistencies in data from different sources. Variables B7 and B8 address these issues. It is intuitively obvious that well integrated good quality data be available and easily accessible to end-users for their BA applications. Any one of the issues—access, availability, data quality, and/ or integration—could dampen the spirit of the end-user if not addressed properly. Mathematical and statistical tools that are used to perform analysis on the data play a critical role in the success of BA applications. For the end-user, who may not be very sophisticated in quantitative analysis or IT, the availability of the right tools for analysis and the ease-of-use of those tools play an important role in the actual use of the BA application. Variables B9 and B10 address these. In addition, for most users, it is also important to have a seamless integration of data with the tools they are using for their BA applications. Variable B11 addresses this issue. Most BA applications use massive amounts of data and fairly sophisticated mathematical/ statistical analysis. This requires a good level of computing power available to the end-users so as to perform the analysis in a timely manner. Variables B12 and B13 address these. Table 3C includes several DS factors that are critical to BA success. While the relevance of the factors is intuitively understood, the following discussion attempts to justify the importance of the factors relative to BA success by grounding them
in literature and/or (justifying their importance as illustrated by) business applications. Well-defined, easy-to-use, canned models exist in DS for many BA applications. From an end-user’s perspective it is important to have a good set of canned models readily available in order to increase the likelihood of applying those models to potential BA situations. Similarly, it is also important to have readily available, easy-touse tools (statistical and mathematical) available in order to increase the likelihood of use. These are captured in variables C1 and C2. Factor C3 is intuitively understood. The importance of investment in modeling and human resources (factor C3) infrastructure has been highlighted repeatedly by Davenport (2006) and Davenport and Harris (2007). Bodily (1986) reports that practitioners were adopting spreadsheets (factor C4) as a decision-making tool because (a) of their ease-of-use (factors C5 and C6) in data input, solution and report generation, (b) spreadsheets provide a natural interface for model building (factor C1), and (c) their ability to perform whatif analysis. The pervasive use of spreadsheets in modeling and problem-solving (in varying degrees) is documented by Leon et al. (1996). Dhebar (1993) has identified systematic spreadsheet development as one of the ingredients of a sound quantitative analysis methodology. Ease of use of tools and models (factors C5 and C6) can also impact implementation and user compliance (factors A5 and A7 in Table 3A), both critically important to the success of BA. Such issues have been discussed by Weigel and Cao (1999) and Powell et al. (2002). Complex business problems often require the integration of tools and models (factor C8). Very often business analysts/data modelers are hamstrung by the incompatibility of tools/models to data stored in specific storage formats. Seamless data communication between tools/models and data storage interfaces (factor C7) can also help facilitate the validation and implementation of complex customized models. The DS literature is
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replete with such examples. In one such instance, Weigel and Cao (1999) describe the integration of vehicle routing models within a GIS framework in Sears’ Enhanced Home Delivery System, which allows Sears to develop efficient solutions for constrained routing problems in extremely dense street networks. Solution efficiency (in terms of optimality gap and computation time) is a function of the efficacy of available models and tools (factor C9) (Bixby, 2002) and computing horsepower (factor B13 in Table 3B). Finally, Willemain (1994, 1995), and Powell and Baker (2007) identify technical skills and craft skills as key characteristics of good modelers (in relation to factor C10). In a survey conducted by Cochran, Mackulak, and Savory (1995), 21% of the practitioners identified lack of technical background as an obstacle to in-house quantitative (in this case, simulation) analysis. In fact, Davenport et al. (2001) identify regression, data mining, data presentation and report preparation as some of the statistical modeling and analytical skills desirable of business analysts. The importance of factor C10 is clearly established.
Interactions Between Components As stated earlier, our model is based on the premise that BA success hails from distinctive competencies in three broad business disciplines—management, IS, and decision sciences, and also as a result of the interaction between the disciplines. In the following discussion, we illustrate the use of IS in conjunction with decision-making tools and techniques, and aided by analytics-friendly management policies in organizations that have achieved a high level of BA success. More specifically we identify specific management, IS, and DS variables (listed earlier in Tables 3A, 3B, and 3C) and also study interactions between those variables in different organizational contexts. The purpose is to describe and validate our model using exemplars of several successful analytically competitive organizations. Note that while the
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following discussion pertains to the exemplars tabulated earlier in Table 1, we sometimes supplement our discussion with new examples. One key factor for BA success (identified in Table 3 sectionA) is the level of commitment of senior management to analytics and fact/datadriven organizational decision-making (item A1 in Table 3A). Capital One and Netflix (examples 1 and 2, respectively, in Table 1) are classic examples where the founder(s) had the vision to be analytically driven when the company was a startup. Capital One annually collects data of millions of customers pertaining to spending rates, timely installment payments, credit scores, and various other parameters, and integrates (item B8 in Table 3B) these internal data (item B1 in Table 3B) with external data (item B2 in Table 3B) pertaining to conditions of general economic prosperity. Using these disparate data from various sources, Capital One uses analytical models to calculate customers’ willingness to repay loans/balances, maximize customer retention, and minimize the cost of acquiring a new account. The organization also actively recruits analysts who possess a high level of analytical aptitude and the ability to use software applications proficiently (item C10 in Table 3C). This example clearly highlights several discipline-specific variables of consequence to Capital One and also interactions between all three disciplines that lead to BA success. The thrust in analytics at Netflix (example 2 in Table 1) comes from its founder (item A1 in Table 3A). The main objective of analytics at Netflix is to predict customer movie preferences. To that end, Netflix collects data about customers’ rental history and film ratings (item B1 in Table 3B) and has created an overall IS environment with analytics in mind. Moreover Netflix recruits mathematicians with programming experience (item C3 in Table 3C) to write code and devise algorithms to define clusters of movies and then connect customer preference (data) with the movie clusters (based upon customer data collected).
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Progressive (example 3 in Table 1) is a pioneer in the insurance industry in providing policies at competitive rates to “high-risk” customers. Progressive’s internal customer data (item B1 in Table 3B) captures a wide range of attributes such as customer’s age, level of education, credit scores, participation in high-risk activities (such as skydiving) and is integrated (item B8 in Table 3B) with widely available insurance industry external data (item B2 in Table 3B). It is pertinent to note here that pharmaceuticals and other such regulated industries are often hamstrung by the lack of availability and sometimes access to external industry data (item B4 in Table 3B). Progressive then employs regression analysis (item C2 in Table 3C) to determine customers with low credit scores who might actually be risk worthy and also identify those customer attributes that are better predictors of risk than other attributes. High-risk customers are a constituency that is typically neglected by Progressive’s competitors and hence provides competitive advantage. While this example illustrates the IS and DS factors/variables which are key to Progressive, and also illustrates their interaction, it is pertinent that senior management at Progressive chose analytics as a strategic focus (variable A1 in table 3A). An overall culture of analytics perpetrates the entire organization at Marriott (example 4 in Table 1) comprising its employees, regional property managers, vendors, and senior management (item A1 in Table 3A). The focus is on factbased decision-making, which is embedded in the corporate culture since Marriott’s inception. The concept of revenue management, more specifically the revenue opportunity model (item C1 in Table 3C), originated in the hotel part of Marriott’s business and now spans across its restaurants, catering services, and conference facilities. Flexibility in decision-making is a key at Marriott, where regional property managers have the ability to override system recommendations to account for localized events (item A2 in Table 3A). Internal customer data consists of attributes ranging from
the type of service a particular customer prefers to the frequency of visits. Using this data (item B1 in Table 3B), promotions are designed and marketed to online and traditional travel agencies and major corporate customers to help them make informed travel management decisions. While this clearly exemplifies superior management practices at Marriott, the role played by IS and DS towards BA success at Marriott is also immense. At Harrah’s (example 5 in Table 1), CEO Gary Loveman brought with him a customer analytics drive (like Netflix and Capital One) which was broadly distributed but centrally driven (item A1 in Table 3A). Harrah’s, like Marriott, focused on employing analytics at increasing customer loyalty, customer service, pricing, and promotions. The CEO made sure that individual casino property managers implemented (item A5 in Table 3A) the company’s marketing and customer service programs in a uniform fashion. However unlike Marriott, hotel managers are not allowed to override automated analytical decisions since evidence-based decisions outperform those made by individuals. Harrah’s also introduced a novel method to collect customer behavior data via loyalty cards which captured gaming preferences, spending rates, etc. all collected in real time. These internal data (item B1 in Table 3B) were extensively used for a variety of purposes, for example to locate slot machines and guide customers to slower parts of the casino with added incentives during peak business hours. The organizational culture underwent a paradigm shift from paternalism and tenure to one based upon meticulous numbers-driven performance evaluation and customer service (item A8 in Table 3A). Notice that new management impacted overall organizational culture at Harrah’s. However, a new culture of analytics, while necessary, was not sufficient. To that end, the CEO hired a group of statistical experts (item C10 in Table 3C) who designed and implemented quantitatively grounded loyalty programs and marketing campaigns and hence
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played a significant role at Harrah’s in achieving BA excellence. At Proctor and Gamble (P&G, example 6 in Table 1), the primary thrust for analysis comes from two vice-chairpersons (item A1 in Table 3A). P&G uses analytical software and databases to intensively analyze sales data obtained from external sources such as ACNielsen (item B2 in Table 3B) and accordingly designs promotions for its customers. Dozens of analytical professionals (items C10 in Table 3C) support various organizational functions such as operations, supply chain management, and marketing, and report directly to the CIO. During the mid-90s, P&G streamlined its North American product sourcing and distribution systems by successfully blending operations research models and techniques (item C1 in Table 3C) within a GIS framework (item C8 in Table 3C). The importance of teamwork (item A6 in Table 3A) vis-à-vis successful BA initiatives is also highlighted in this application in which over 500 P&G employees worked in approximately 30 teams to complete the supply-chain restructuring. The vehicle routing and scheduling system developed by Sears, Roebuck and Company (example 7 in Table 1) is a perfect example for our model where an optimal marriage between IS, DS, and management resulted in a tremendously successful BA application. To develop the system, internal customer data such as location of customers, type of service required, products to be delivered, delivery time windows, etc. (item B1 in Table 3B) available from mainframe based databases was integrated (item B8 in Table 3B) with commercially available external data such as street networks, congestion, etc. (items B2 in Table 3B) within a geographical information systems (GIS) framework. The problem was modeled as a vehicle routing problem with time windows (item C1 in Table 3C) within a GIS framework (to accurately estimate travel distances) thereby highlighting the integration of modeling tools and software (item C8 in Table 3C). Sears’ investment in hardware (item B13 in
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Table 3B) is apparent as the home delivery and routing systems developed are UNIX-based and operate on either a central server or distributed workstations. Their investment in developing computing horsepower (item B12 in Table 3B) is also apparent; vehicle routing problem instances with approximately two million street network arcs could be solved in less than 20 minutes of computing time. All the IS and DS investments would have proven futile if Sears employees were not trained (item A4 in Table 3A) by an outside firm to overcome difficulties associated with (1) shifting from text-driven terminals to mouse-based GUIs, a fundamental IT paradigm shift, and also (2) to overcome unfamiliarity problems with the various model input parameters (item C5 in Table 3C). Managers in charge of regional routing offices encountered implementation difficulties as technicians and truck drivers resented the online tracking by the systems. However the problem was overcome as field managers gained more confidence in the system and were able to communicate its benefits to truck drivers (end users in this case) and encouraged them to follow the routes the automated systems suggested (items A5, A7, A8 in table 3A). On a related note, but in a different context, Burlington Motor Carriers encountered user compliance (item A7 in Table 3A) problems while assigning drivers to its fleet of 1200 trucks (Powell, Marar, Gelfand, and Bowers, 2002). Fleet planners who were used to doing things in a different way complained vaguely about difficulties encountered in using the assignment model. To overcome these behavioral hazards, management implemented a system that monitored individual user compliance, which was then correlated with monthly bonuses (item A8 in Table 3A). As a result, user compliance rose by 20% over a five-month period. However the organization was still plagued by problems of imperfect, sometimes incomplete, data - clearly data quality issues (items B5 and B6 in Table 3B), and also end-user compliance issues (item A7 in Table 3A) where drivers often devi-
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ated from routes suggested by planners, costing Burlington several thousand dollars in recruiting and training new drivers. Interestingly, some of the key traits of the management science group at Merrill Lynch are technical expertise (item C10 in Table 3C), objectivity, communication skills, proactivity, teamwork (item A6 in Table 3A), integration of various data (items B7 and B8 in Table 3B), data integrity, careful attention to implementation issues (item A5 in Table 3A), and focus on goals of the firm rather than goals of the department. (Labe et al, 1999). Notice that all of these are crucial and relevant for BA success in organizations. Through the examples described earlier, we have attempted to highlight key management, IS and DS factors/variables and explicitly identify interactions between those factors/variables (and disciplines themselves) that have led to BA success in a cross-section of very large organizations. It is pertinent to note that if organizations choose to outsource certain BA specific tasks such as modeling, IT infrastructure development and support, advanced communication technologies can still ensure BA success. In a later section of this chapter, we discuss virtualization and as a special case BA implementation in virtualized settings. In summary, the discipline-specific (management, IS, and DS) variables/factors that interacted in each of the previous examples to ensure BA success have been tabulated in Table 3D. Admittedly the examples did not illustrate the relevance of each and every factor/variable listed in Tables 3A, 3B, and 3C (we have justified each variable in an earlier section). Also the objective of this chapter is not to construct an exhaustive set of variables/factors that lead to BA success and hence that particular task is outlined as a future research direction. Moreover, it is pertinent to observe here that there are too many possible interactions, twoway as well as three-way, between the three sets of factors (listed in Tables 3A, 3B, 3C). Table 3D tabulates only a sample of these interactions, and the previous discussion substantiates them with
the aid of concrete examples found in a variety of industrial settings. Further, we note that the management, IS, DS variables/factors, and interactions between those discipline-specific factors which lead to BA success are purely contextual, almost industry specific. The interactions that cause casinos to attract more customers in gaming may not necessarily be identical to the interactions that help major retailers deliver products/ services to customers more efficiently. Finally we recognize that BA success is clearly a function of the strength of the discipline-specific factors and their interactions. This work has not attempted to evaluate the strength of the various factors and their interactions vis-à-vis BA success.
Framework Use: Practice In the previous discussion, we described the conceptualization and development of the BA success framework. Discipline-specific factors were tabulated, and factor interactions were illustrated using exemplars from the literature. In this section, we outline the procedure to use the framework in practice and also discuss implications for researchers. The framework presented will be useful to practicing managers to evaluate whether a new BA application contemplated by their organization is likely to succeed and/or to assess what needs to be done by the organization to make the initiative succeed. To illustrate the usage of our framework, let us consider a Sears-like scenario where a business manager of a major retailer is attempting to streamline product/service delivery and technician dispatching and routing functions. Let us assume that the Sears-specific success factors (listed in Table 3D) apply in this case, too. The business manager can assign ratings to all these factors on an ordinal scale. For example, factors such as A4 and A5 (management), B1 and B2 (IS), and C1 and C8 (DS) are assigned the highest ratings, factors such as A7 (management), B8, and B13 (IS), and C8 (DS) are assigned medium
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ratings, and the remaining factors A8 and B12 are assigned low ratings. Such a scenario will encourage a practitioner to invest in BA to meet the specified objective. It also helps to highlight the weaker factors, and corrective strengthening measures can be initiated to maximize chances of BA success. Admittedly, such a paradigm to use the BA success framework is simplistic. Also, developing consistent ordinal scales for all factors is a challenging task. Finally, one immediate drawback of this approach is the fact that all factors are considered equally important. To that end, in order to refine usage of the framework, practitioners can also assign weights to the factors which are organizationally or contextually more important. This can facilitate the development of a factor rating approach, a technique that is widely used in personal as well as professional decision-making. Its application in a BA context is outlined as follows: 1. Determine which management, IS, and DS factors are relevant. 2. Assign a weight to each factor which indicates its relative importance. Whether to assign weights on a discipline-specific basis or irrespective of the discipline a factor belongs to is an open-ended question. 3. Decide a common ordinal scale for all factors (e.g. 0 to 100) and set a minimum acceptable threshold score for each factor, if necessary. 4. Multiply each factor’s weight by its score and sum the results to develop a composite score. 5. If the composite score is above a threshold (to be decided organizationally), the chances of BA initiative success are maximized, ceteris paribus. Clearly both approaches described for evaluating potential for BA success are somewhat simplistic. While the second approach refines the first one, several issues such as assigning
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weights to factors and developing thresholds (for individual factors and also a composite threshold) are distinctly tricky. Some sensitivity analysis can be performed to identify factors that are clearly critical to BA success.
Framework Use: Research The conceptual framework of BA success developed in this work is based on the premise that BA success results not only from the individual factors but also from the interactions between three broad disciplines – management, IS, and DS. More specifically, BA success results due to the interactions between several discipline-specific factors which were earlier listed in Tables 3A, 3B, and 3C. The concept of BA success has not been formally defined until now, and the framework presented in this chapter is a novel beginner in that regard. Researchers can further consolidate several aspects of the framework, and some are outlined below. 1. The factors in the tables are illustrative in nature; as a result each discipline-specific table can be populated further. The factors listed are either conceptual or their genesis lies in the literature (case examples from industry). Today BA is a growing phenomenon that is increasingly used in a variety of industrial sectors including retail, healthcare, financial institutions, manufacturing, petroleum, and also by government at various levels for several purposes, including homeland security. A thorough review of the literature for applications in each of these areas will yield several more discipline-specific factors that will consolidate the factor tables, and perhaps help to identify factors that are industry- or domain-specific. 2. Most of the factors listed in the tables are universal in relation to BA success. For example, senior management commitment, availability, access, and quality of internal
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data, and investment in quantitatively proficient analysts are all factors that are critical to BA success irrespective of industry sector, for-profit or government, and any such criterion. However, factors such as availability and perhaps access to external data (for highly regulated industries such as pharmaceutical) and level of organizational politics are arguably industry-specific. It would be worthwhile to categorize the management, IS, and DS discipline-specific factors as either universal or industry-specific. This will certainly aid researchers and practitioners understand the relevance of the factors more in depth. Moreover it can be conjectured that small and medium-sized enterprises (SMEs) are often constrained in relation to several of the factors already listed, for example access to industry-wide external data. Hence classifying the factors with respect to size of organizations is another interesting avenue for future research. 3. As mentioned earlier, the factors listed in the tables have not been ranked in importance. It can be argued that senior management buy-in would perhaps be one of the most important management-specific factors, while employing analysts with advanced computational proficiency would be a key DS factor. Ranking the factors within disciplines (and then perhaps across disciplines) would be valuable. This will help researchers and practitioners alike understand the importance of specific factors and aid in predicting the chances of success of BA initiatives. 4. As the factor tables are consolidated, the scope of interactions increases polynomially. Previous discussion in this section (summarized in Table 3D) has highlighted several such interactions in successful BA applications. Clearly the interactions identified in the exemplars are by no means exhaustive, and more such interactions can be identi-
fied by thorough literature reviews and by conducting industry surveys. 5. Analogous to ranking the individual factors, studying the strength of factor interactions is also valuable. For example, a review of the interactions in Table 3D reveals that interaction between factor A1 (senior management commitment) and factors B1 and B2 (availability of internal and external data) is commonly reported to have contributed to BA success. Such an interaction can hence be defined as a strong interaction. Identifying such interactions and developing an allied framework to measure the strength of the interactions (followed by rank ordering them) will supplement the existing literature and would also be meaningful to managers on the threshold of BA initiatives. We have attempted to outline possible research implications of this work. Clearly research into BA issues such as understanding of BA success – the contributing factors and their interactions is still at a nascent stage, and our framework can be considered part of a growing body of literature. In the following section, we apply our framework to a special case —that of virtual organizations—and discuss how the framework can be adapted for virtual organizing.
VIRTUAL ORGANIZING: APPLICATION OF FRAMEWORK Continued developments in information and communication technologies (ICT) have made it possible to distribute organizational processes/ work spatially and temporally. This phenomenon is often called virtual organizing, and the organizations that use this extensively are called virtual organizations. We witness this through the revolution of the global marketplace for outsourcing of information and knowledge work (Friedman, 2007). One such process or knowledge work that
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can be distributed is organizational/managerial decision-making. Decision-making using analytics, i.e., business analytics, is by extension a good candidate for virtual organizing. The costs and benefits of outsourcing/offshoring knowledge work also apply to virtualizing BA work in organizations. The opportunities and challenges are also similar. In this section we will first present a discussion on virtual organizing (and virtual organizations) and a discussion of the relationship between virtual organizing and BA. We will then discuss how the framework for BA success (presented in the previous section) can be applied to virtual BA work.
Emerging Organizations and Virtualization Extensive availability of reasonably cost-efficient ICT to facilitate collaboration between entities separated spatially and temporally has made it possible for organizations or organizational work/ processes to become somewhat virtual. Though virtualization was possible before the widespread availability of the Internet platform, it became less expensive and easier to develop and use since the development of the World Wide Web. Research on the move towards this virtualization in organizations has been discussed under virtual organizations (Bleecker, 1994; Chesbrough & Teece, 1996; Coyle & Schnarr, 1995; Davidow & Malone, 1992; Dutton, 1999; Fulk & DeSanctis, 1995; Goldman, Nagel, & Preiss, 1995; Hedberg, Dahlgren, Hansson, & Olve, 1997) as a form of organizational structure or under virtual organizing (Negroponte, 1995; Quinn, Anderson, & Finkelstein, 1996; Venkataraman & Henderson, 1998) as an organizational characteristic. However, the essence of virtualization appears to be similar between the two views. According to DeSanctis and Monge (1999), virtualization in organizations implies the following: “(a) highly dynamic processes, (b) contractual relationships among entities, (c) edgeless,
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permeable boundaries, and (d) reconfigurable structures.” A few of the other researchers who have contributed to the development of the concept of virtual organizations are Galbraith (1995), who presented the concept of “company without walls;” Clancy (1994) and Barner (1996), who discussed the concept of “employees who are physically dispersed from one another;” Coyle and Schnarr (1995), who discussed “organizations replete with external ties;” Grenier and Metes (1995) and Lipnack and Stamps (1997), who described virtual organizations consisting of “teams that are assembled and disassembled according to need;” and Bleecker (1994), Grenier and Metes (1995), and Hedberg et al (1997), who discussed the concept of “people working together, regardless of location or who owns them.” . The degree of virtualization varies among organizations depending on their needs. For example, Cisco has developed a virtual relationship with its suppliers that results in their suppliers shipping 70% of the customers’ orders directly without Cisco receiving them at their locations. What aspects of an organization’s processes are virtualized depend on an organization’s need. In the case of Cisco, manufacturing and shipping are highly virtualized and R&D is not as virtualized. The degree of virtualization of any organization is also dynamic. For example, Amazon.com had a vision to be a total virtual organization, i.e., an organization that does not take possession of any of the items it sells. Through the use of ICT, Amazon.com was designed to be an intermediary between the buyers and sellers. However, as the business slowly took shape it became clear that 100% virtualization will not work and Amazon. com had to become partly non-virtual by building warehouses and taking possessions of goods. On the other hand, half.com (now a part of eBay) started out as 100 percent virtual and has stayed that way. Another example of a company that is 100 percent virtual is threadless.com. Virtualization in organizations opens up some opportunities and also results in some challenges as
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they pertain to BA. The availability of somewhat inexpensive global talent leads to better success in BA analytics. It is also possible to divide BA work in organizations to suit local conditions and still derive the benefits of BA. On the other hand the challenges posed through the use of communication technologies and differences in cultures of virtual participants in BA work could pose significant challenges to BA success in organizations. Early work related to virtualization of organizational work and BA has focused on decisionmaking and problem-solving through the use of ICT, the group decision support systems (GDSS) (Armstrong, 1994; Chidambaram & Tung, 2005; DeSanctis & Gallupe, 1987; Fjermestad & Hiltz, 1998; Hiltz, Johnson, & Turoff, 1986; Rao & Jarvenpaa, 1991). The work has focused on the role of technologies, task characteristics, and group dynamics/behavior on the success of problemsolving in a virtualized context. Though the role of appropriate ICT in the success of virtualized BA work is important, we contend that success is also dependent on choosing the right aspects of BA work to virtualize, including the consideration of different phases of problem-solving (see Simon, 1977), the consideration of knowledge transfer needs between members separated by space and time, and on the nature of the BA work that is virtualized (whether it is autonomous where there is very little need for dynamic interactions between members or systemic where dynamic interactions are absolutely necessary). As BA as a concept is fairly recent, very little research exists in the area. However, there is some research related to the issues we have identified for success of virtualized BA work. Chesbrough and Teece (1996) report that (1) virtualization and incentive to take risks are positively related, (2) virtualization and the ability to settle conflicts and coordinate activities are negatively related, and (3) BA work that can be autonomous is more likely to succeed in a virtualized context. In addition,
they also point out the need to consider the type of knowledge transfer (tacit or explicit) needed for success of virtualized BA work. Majchrzak, Malhotra, and John (2005) report that lack of face-to-face cues creates challenges in developing collaborative know-how and that these challenges can be overcome by communicating not just content, but also context. Schmidt, Montoya-Weiss, and Massey (2001) report from their research that virtual teams are the most effective compared to other types of teams in making decisions. Technological factors make it possible for organizations to virtualize BA work. The availability of global talent pools to better address certain aspects of BA work makes it more beneficial for organizations to virtualize the work. However, much more research is necessary to develop a better understanding of the success of virtualized BA work.
Application of the Framework to Virtual BA Work The framework for BA success presented has three sets of independent variables (one set each in management, IS, and DS disciplines) and a set of dependent variables (i.e., measures of BA success – these would usually be context specific for any organization/application). When we apply this framework to virtual settings it is very important to redefine these sets to suit the virtual context. It is possible some of the variables in the four sets could be the same for the new context and some could be different (some eliminated and some added). For example, the typical dependent variable set (as derived from successful BA applications and presented in the previous section) could be customer retention rate, reduction in cost of operations, revenue growth, growth in market share, etc. In a virtual BA setting an additional success measure could be how well organizational intellectual capital has been utilized. In independent variable sets, it is possible that we may need to add the following
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variables: extent of team members’ comfort in working across spatial and temporal boundaries (an addition to variables listed in Table 3A), level of access of internal/external data across spatial and temporal boundaries (variables B1 and B2 modified from Table 3B set or an addition to the existing set), level of availability of analytical models (variable C1 in table 3C) that could be modified to reflect an added set of dimensions, temporal and spatial, etc. Some of the BA work that could be straightforward in a one-location setting could pose a challenge for virtualized settings. Some aspects of the work such as problem definition and preliminary model building would involve considerable interactions between team members, and some activities such as model validation and solving may need lot less interactions. Thus it is important for organizations considering virtual BA work to break down the work to smaller parts and identify the best candidates for distributed work. The following process (modified from the previous section titled “Framework Use: Practice”) could be used by organizations considering virtual BA work: 1. Identify which variables arerelevant as success measures for the application (i.e., identify and specify the dependent variable set). 2. Identify which variables from Tables 3A – 3C are relevant to the virtual BA context, make any changes to the specification of variables, and add any new variables to address the changed context (i.e., identify and specify independent variable set). 3. Assign weights in both sets of variables to indicate their importance to the context. 4. Identify variable interactions (within and among discipline-specific sets) that are believed to have a significant impact on the dependent variables set (i.e., success measures).
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5. Assign weights to the interactions identified in the previous set. 6. Assign values to the variable sets (on an ordinal scale). 7. Use a composite score approach or judgment in deciding whether the BA application is likely to succeed in the virtual context. The process is intentionally simplistic as this is the first attempt at using the new framework developed. As more research validating the framework becomes available and more and more organizations use this approach it is likely that more sophisticated processes for evaluating success will emerge.
CONCLUSION This chapter presents a framework for business analytics success. BA is a novel data-driven quantitative analysis-based capability available to organizations. It is being increasingly used in diverse industry sectors such as retail, insurance, telecommunications, healthcare, financial services, sports and entertainment, manufacturing, and several others. Anecdotal evidence reported in the literature points to cost savings of millions of dollars and increased revenues and profits. Academic research in BA is lagging behind practice and is limited. It is mostly built on the basis of reports on successful business applications in the business and trade press. The limited literature, practitioner accounts, and documentation of BA usage have simply alluded to the fact that datafueled developments in information systems, large scale quantitative analysis, and senior management buy-in have acted as catalysts in successful BA applications in organizations. However, what constitutes BA success is not very well documented and what specific factors result in BA success are not well laid out. The interactions between these factors, if any, are mostly not considered. The framework for BA success that is presented in this
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chapter is the first attempt, to our knowledge, to address this gap in BA research. We consolidate the existing knowledge from reports of BA success in different applications. We review BA-related academic literature that discusses and explains what BA is and how companies are using it to become successful. We integrate the two aspects, accounts of practitioner-based experiences and the current academic thinking to develop a comprehensive framework. This framework offers a definition of BA success, identifies the various factors that have led to BA success in different situations. This chapter goes further to ground this framework in academic theoretical traditions by classifying and grounding these BA success factors under the academic literatures where these have been studied previously. This theoretical grounding reveals how practice has evolved with no regard to our disciplinary boundaries, and how managers have used whatever it takes to achieve business success. The chapter thus makes a call for interdisciplinary research in the area of BA success. We believe that one of the novelties of this research is its inter-disciplinary nature. The framework developed proposes that BA success comes from an optimal blend of factors in three key business disciplines – management, information systems (IS), and decision sciences (DS). We consider both the technological and organizational factors which contribute to and impact BA success. Three tables with details of factors by each of the three disciplines have been explicitly identified (see tables 3A, B and C for management, DS and IS-related factors for BA success). We take this one step further by making the first attempt to define these factors as measurable variables. By using the existing cases of successful BA applications, we demonstrate how BA success results from careful consideration of individual variables and also the critical interactions between these variables. The interactions between the various factors are also explicitly spelled out to the extent that we could make these
connections based on the examples of BA success that we analyzed. In addition to the list of factors important for BA success and their interactions, we lay out a roadmap for managers on how to use this framework to guide their own efforts at implementing BA in their organizations. While the press offers examples of tremendous savings and competitive advantages to be gained from implementing BA in organizations, urging managers to jump on this bandwagon, we actually take a more reasoned approach. We lay out a way to help managers decide if adopting BA is the right solution for their organization or not. In certain business situations, the more appropriate tools may be pure decision models or organizational interventions. BA is not a solution to all problems but is suitable for a subset of specific situations characterized by both organizational and analytical complexity. Once managers decide to adopt BA, they can also use this chapter as a starting point to review all the factors to be considered for BA success and the interactions between these factors. For the academics interested in this area, we draw out the implications of this work. Starting with a call for more inter-disciplinary research, we also have made a call for other researchers to build on this framework further. Since this is the first comprehensive attempt to consolidate the state-of-the-art research and practice in this emerging area, we feel that other researchers have an opportunity to develop further, refine, and validate the framework that has been presented here. The final and perhaps the most crucial contribution of this chapter is to show both academics and managers how to use this framework by discussing in detail one specific application. Virtual organizations are becoming increasingly common. Virtualization offers contemporary challenges for both managers and researchers, and in discussing how to apply our BA success framework in this context, we demonstrate the utility of this work. By walking through an in-depth application in a virtually organized context, a relatively novel
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phenomenon that allows organizations to distribute work spatially and temporally, we show how BA works in a manner that is most likely to yield successful outcomes. While BA applications are proliferating, BA as a research domain is sparsely populated. This work can hence be considered to be one of the first attempts at truly understanding BA success. Practitioner implications of such understanding followed by successful employment and use of BA can be potentially enormous. Clearly a lot more can be achieved given the nascent stage of BA research. The framework can be further consolidated by identifying newer factors, understanding newer interactions, and by classifying the factors so that organizations in various industry domains can explore the use of BA and derive the most value (and perhaps develop competitive advantage) through its extensive adoption and usage.
REFERENCES
Barner, R. (1996). The new millennium workplace: Seven changes that will challenge managers and workers. The Futurist, 30, 14–18. Barney, J. B. (1991). Firm resources and sustained competitive advantage . Journal of Management, 17, 99–120. doi:10.1177/014920639101700108 Bixby, R. E. (2002). Solving real-world linear programs: A decade and more of progress. Operations Research, 50(1), 3–15. doi:10.1287/ opre.50.1.3.17780 Bleecker, S. E. (1994). The virtual organization. The Futurist, 28(2), 9–14. Bodily, S. (1986). Spreadsheet modeling as a stepping stone. Interfaces, 16(5), 34–52. doi:10.1287/ inte.16.5.34 Camm, J. D., Chorman, T. E., Dill, F. A., Evans, J. R., Sweeney, D., & Wegryn, G. W. (1997). Blending OR/MS, judgment, and GIS: Restructuring P&G’s supply chain. Interfaces, 27(1), 128–142. doi:10.1287/inte.27.1.128
Allison, G. T., & Zelikow, P. (1999). Essence of decision: Explaining the Cuban missile crisis. New York: Addison-Wesley Longman.
Chandler, A. D. (1962). Strategy and structure: Chapters in the history of the industrial enterprise. Cambridge, MA: MIT Press.
Apte, C., Liu, B., Pednault, E. P. D., & Smyth, P. (2002). Business applications of data mining. Communications of the ACM, 45(8), 49–53. doi:10.1145/545151.545178
Chesbrough, H. W., & Teece, D. J. (1996). When is virtual virtuous? Harvard Business Review, (January-February): 65–71.
Armstrong, M. P. (1994). Requirements for the development of GIS-based group decision support systems. Journal of the American Society for Information Science American Society for Information Science, 45(9), 669–677. doi:10.1002/(SICI)10974571(199410)45:93.0.CO;2-P Ayers, I. (2007). Super crunchers. New York: Bantam Books. Bachani, J. (2005). Building decision quality in organizations. California Journal of Operations Management, 3(1), 12–16.
178
Chidambaram, L., & Tung, L. L. (2005). Is out of sight, out of mind? An empirical study of social loafing in technology-supported groups. Information Systems Research, 16(2), 149–168. doi:10.1287/isre.1050.0051 Clancy, T. (1994). The latest word from thoughtful executives - the virtual corporation, telecommuting and the concept of team. The Academy of Management Executive, 8(2), 8–10.
Business Analytics Success
Cochran, J. K., Mackulak, G. T., & Savory, P. A. (1995). Simulation project characteristics in industrial settings. Interfaces, 25(4), 104–113. doi:10.1287/inte.25.4.104 Cohen, M. D., March, J. G., & Olsen, J. P. (1972). A garbage can model of organizational choice. Administrative Science Quarterly, 17(1), 1–25. doi:10.2307/2392088
Dutton, W. H. (1999). The virtual organization: Tele-access in business and industry. In G. DeSanctis and J. Fulk (Eds), Shaping organizational form: Communication, connection, and community. Newbury Park, CA: Sage. Evans, J. R. (1991). Creativity in OR/MS: Creative thinking, a basis for OR/MS problem solving. Interfaces, 21(5), 12–15. doi:10.1287/inte.21.5.12
Corstjens, M., & Merrihue, J. (2003). Optimal marketing. Harvard Business Review, (October): 114–121.
Evans, J. R. (1992). Creativity in OR/MS: Improving problem solving through creative thinking. Interfaces, 22(2), 87–91. doi:10.1287/inte.22.2.87
Coyle, J., & Schnarr, N. (1995). The soft-side challenges of the “virtual corporation.” . Human Resource Planning, 18, 41–42.
Evans, J. R. (1993a). Creativity in OR/MS: The multiple dimensions of creativity. Interfaces, 23(2), 80–83. doi:10.1287/inte.23.2.80
Cyert, R. M., & March, J. G. (1992). A behavioural theory of the firm. Cambridge, MA: Blackwell.
Evans, J. R. (1993b). Creativity in OR/MS: Overcoming barriers to creativity. Interfaces, 23(6), 101–106. doi:10.1287/inte.23.6.101
Davenport, T. (2006). Competing on Analytics. Harvard Business Review, 84(1), 99–107. Davenport, T., & Harris, J. (2007). Competing on Analytics. Boston: Harvard Business School Press. Davenport, T., Harris, J., De Long, D., & Jacobson, A. (2001). Data to knowledge to results: Building an analytic capability. California Management Review, 43(2), 117–138. Davidow, W. H., & Malone, M. S. (1992). The virtual corporation. New York: Harper Business. DeSanctis, G., & Gallupe, R. B. (1987). A foundation for the study of group decision support systems. Management Science, 33(5), 589–609. doi:10.1287/mnsc.33.5.589 DeSanctis, G., & Monge, P. (1999). Communication processes for virtual organizations. Organization Science, 10(6), 693–703. doi:10.1287/ orsc.10.6.693 Dhebar, A. (1993). Managing the quality of quantitative analysis. MIT Sloan Management Review, Winter, 69-75.
Fayyad, U., & Uthurusamy, R. (2002). Evolving data mining into solutions for insights. Communications of the ACM, 45(8), 28–31. doi:10.1145/545151.545174 Ferguson, G., Mathur, S., & Shah, B. (2005). Evolving from information to insight. MIT Sloan Management Review, Winter, 51-58. Fjermestad, J., & Hiltz, S. T. (1998). An assessment of group decision support systems experimental research: Methodology and results. Journal of Management Information Systems, 15(3), 7–149. Friedman, T. (2007). The world is flat. New York: Farrar, Straus and Giroux. Fulk, J., & DeSanctis, G. (1995). Electronic communication and changing organizational forms. Organization Science, 6(4), 337–349. doi:10.1287/orsc.6.4.337 Galbraith, J. R. (1995). Designing organizations. San Francisco: Jossey-Bass.
179
Business Analytics Success
Goldman, S. L., Nagel, R. N., & Preiss, K. (1995). Agile competitors and virtual organizations: strategies for enriching the customer. New York: Van Nostrand Reinhold. Grenier, R., & Metes, G. (1995). Going virtual: Moving your organization into the 21st century. Upper Saddle River, NJ: Prentice Hall. Hedberg, B., Dahlgren, G., Hansson, J., & Olve, N.-G. (1997). Virtual organizations and beyond: Discover imaginary systems. New York: Wiley. Henderson, J. C., & Nutt, P. (1980). The influence of decision style on decision making behavior. Management Science, 26(4), 371–386. doi:10.1287/mnsc.26.4.371 Hillier, F. S., & Lieberman, G. J. (2005). Introduction to operations research. New York: McGraw Hill. Hiltz, S. R., Johnson, K., & Turoff, M. (1986). Experiments in group decision-making: Communication process and outcome in face-toface versus computerized conferences. Human Communication Research, 13(2), 225–252. doi:10.1111/j.1468-2958.1986.tb00104.x Hwarng, H. B. (2001). A modern simulation course for business students. Interfaces, 31(3), 66–75. doi:10.1287/inte.31.3.66.9631 Ittner, C. D., & Larcker, D. F. (2003). Coming up short. Harvard Business Review, (November): 88–95. Janis, I. L. (1972). Victims of groupthink: a psychological study of foreign-policy decisions and fiascoes. Boston: Houghton Mifflin.
Kepner, C., & Tregoe, B. (1965). The rational manager. New York: McGraw-Hill. Kohavi, R., Rothleder, N., & Simoudis, E. (2002). Emerging trends in business analytics. Communications of the ACM, 45(8), 45–48. doi:10.1145/545151.545177 Labe, R., Nigam, R., & Spence, S. (1999). Management science at Merrill Lynch Private Client Group. Interfaces, 29(2), 1–14. doi:10.1287/ inte.29.2.1 Lawrence, P. R., & Lorsch, J. (1967). Organization and Environment. Cambridge, MA: Harvard University Press. Leon, L., Przasnyski, Z., & Seal, K. C. (1996). Spreadsheets and OR/MS models: An enduser perspective. Interfaces, 26(2), 92–104. doi:10.1287/inte.26.2.92 Lipnack, J., & Stamps, J. (1997). Virtual teams: Reaching across space, time and organizations with technology. New York: John Wiley. Luecke, R. (2006). Make better decisions. Harvard Management Update, 11(4), 3–5. Majchrzak, A., Malhotra, A., & John, R. (2005). Perceived individual collaboration know-how development through information technologyenabled contextualization: Evidence from distributed teams. Information Systems Research, 16(1), 9–27. doi:10.1287/isre.1050.0044 Mintzberg, H. (1973). The nature of managerial work. Englewood Cliffs, NJ: Prentice-Hall.
Jessup, L., & Valacich, J. (2007). Information systems today. Upper Saddle River, NJ: Prentice-Hall.
Mintzberg, H., Raisinghani, D., & Theoret, A. (1976). The structure of “unstructured” decision processes. Administrative Science Quarterly, 21, 246–275. doi:10.2307/2392045
Kahneman, D., Slovic, P., & Tversky, A. (1982). Judgment under uncertainty: Heuristics and biases. Cambridge, MA: Cambridge University Press.
Nance, R. E., & Sargent, R. G. (2002). Perspectives on the evolution of simulation. Operations Research, 50(1), 161–172. doi:10.1287/ opre.50.1.161.17790
180
Business Analytics Success
Negash, S., & Gray, P. (2003). Business intelligence. In Proceedings of Ninth Americas Conference on Information Systems.
Scott, W. R. (2003). Organizations: Rational, natural, and open systems (5th ed.). Upper Saddle River, NJ: Prentice Hall.
Negroponte, N. (1995). Being digital. New York: Knopf.
Simon, H. A. (1977). The new science of management decision. New York, NY: Harper & Row.
Powell, S. G., & Baker, K. R. (2007). Management science: The art of modeling with spreadsheets. New York: Wiley.
Simon, H. A. (1997). Models of bounded rationality. Cambridge, MA: MIT Press.
Powell, W. B., Marar, A., Gelfand, J., & Bowers, S. (2002). Implementing real-time optimization models: A case application from the motor carrier industry. Operations Research, 50(4), 571–581. doi:10.1287/opre.50.4.571.2852 Power, D. J. (2001). Supporting decision-makers: An expanded framework. In A. Harriger (Ed.), Informing Science Conference, Krakow, Poland, 431-436. Power, D. J. (2002). Decision support systems: Concepts and resources for managers. Westport, CT: Greenwood/Quorum. Power, D. J. (2004). Decision support systems: From the past to the future. In Proceedings of the 2004 Americas Conference on Information Systems, New York, NY, 2025-2031. Quinn, J. B., Anderson, P., & Finkelstein, S. (1996). Managing professional intellect: Making the most of the best. Harvard Business Review, 74(2), 71–80. Rao, V. S., & Jarvenpaa, S. L. (1991). Computer support of groups: Theory-based models for SDSS research. Management Science, 37(10), 1347–1362. doi:10.1287/mnsc.37.10.1347 Schmidt, J. B., Montoya-Weiss, M. M., & Massey, A. P. (2001). New product development decision-making effectiveness: Comparing individuals, face-to-face teams, and virtual teams. Decision Sciences, 32(4), 1–26. doi:10.1111/j.1540-5915.2001.tb00973.x
Teece, D. J., Pisano, G., & Shuen,A. (1997). Dynamic capabilities and strategic management. Strategic ManagementJournal,18(7),509–533.doi:10.1002/ (SICI)1097-0266(199708)18:73.0.CO;2-Z Thompson, J. D. (1967, (2003). Organizations in Action: Social Science Bases of Administrative Theory. New Brunswick, NJ: Transaction Publishers. Tsoukas, H., & Papoulias, D. B. (1996). Creativity in OR/MS: From technique to epistemology. Interfaces, 26(2), 73–79. doi:10.1287/inte.26.2.73 Tydeman, J., Lipinski, H., & Sprang, S. (1980). An interactive computer-based approach to aid group problem formulation. Technological Forecasting and Social Change, 16, 311–320. doi:10.1016/0040-1625(80)90039-6 Venkatraman, N., & Henderson, J. C. (1998). Real strategies for virtual organizing. Sloan Management Review, (Fall): 33–48. Vesset, D., & McDonough, B. (2007). The next wave of business analytics. DM Review, Weigel, D., & Cao, B. (1999). Applying GIS and OR techniques to solve Sears technician-dispatching and home-delivery problems. Interfaces, 29(1), 112–130. doi:10.1287/inte.29.1.112 Willemain, T. R. (1994). Insights on modeling from a dozen exerts. Operations Research, 42, 213–222. doi:10.1287/opre.42.2.213
181
Business Analytics Success
Willemain, T. R. (1995). Model Formulation: What experts think about and when. Operations Research, 43(6), 916–932. doi:10.1287/ opre.43.6.916
Woodward, J. (1975). Management and Technology. London: HMSO.
This work was previously published in Connectivity and Knowledge Management in Virtual Organizations: Networking and Developing Interactive Communications, edited by Cesar Camison, Daniel Palacios, Fernando Garrigos and Carlos Devece, pp. 222-254, copyright 2009 by Information Science Reference (an imprint of IGI Global).
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Chapter 1.12
An Overview of International Intellectual Capital (IC) Models and Applicable Guidelines Tomás M. Bañegil Palacios University of Extremadura, Spain Ramón Sanguino Galván University of Extremadura, Spain
ABSTRACT
INTRODUCTION
In line with the increasing importance of the intangible economy within the last few years, a higher number of models have been published. In this sense, the authors main original contribution when measuring Intellectual Capital is related to comparing and assessing the different existent Guidelines, unlike previous published papers. The purpose of this chapter is to present and compare some of the most recent and significant contributions from researchers to the field of the measurement and management of intangibles.
Intangible assets comprise one of the principal factors in the current and future success of organizations. The multidisciplinary character of this work is demonstrated by the fact that an increasing number of specialists, such as sociologists, psychologists, economists, philosophers, intellectuals and professionals, are working in these questions. At the same time, attention has been drawn to the growing importance of the intangible Economy by the publication of a growing number of models. Nevertheless, we have observed that there are no generally accepted models for measuring Intellectual Capital in organizations. In recent years,
DOI: 10.4018/978-1-60960-587-2.ch112
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An Overview of International Intellectual Capital (IC) Models and Applicable Guidelines
several have been proposed, with a number of similar aspects, but differing with regard to their complexity and adaptability. Knowledge Management is a very recent management tool, which, although it has been greatly discussed in the business world, still does not have a significant number of organizations with a formally implanted management program. The results of different studies carried out by consultants, university researchers and innovative companies have materialized in different guidelines for classifying, measuring and reporting on intangibles. Nevertheless, considerable confusion still exists between the concepts used, the practices recommended and the final Intellectual Capital Reports obtained. All these studies follow the line of introducing supplementary information, external to the company’s financial condition, basically a new “information layer” using “narrative reports”. The concept of “value reporting” effectively follows the line of complementing the traditional annual statement of accounts (balance sheet, profit and loss account and management report) with information on intangible assets and non-financial indicators. Our main objectives in this research consist on • •
Performing a comparative study among well-known IC models and Presenting most significant international guidelines which contributed to develop such models.
BACKGROUND In an effort to find instruments capable of “capturing” the real value of a company, many academics and professionals have started to develop models and measurements to quantify and visualize intangibles, directing their attention in particular to a new type of report called Intellectual Capi-
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tal Reports (also known as Intellectual Capital Statement). Considering the different studies and analyses that have been carried out in the past decade and taking into account the lack of an adequate business practice, launching generalised models for the implementation of Knowledge Management systems and the Measurement and Management of Intangibles in the business world (Intellectual Capital) seems premature. According to the MERITUM Project (2002), there isn’t actually an internationally accepted frame of reference for the identification, measurement and diffusion of information on intangibles that determine the value of organisations, instera just some isolated efforts in different parts of the world. In the light of this fact, it would appear opportune to dedicate effort to the development of general guidelines that would make it easier for companies to identify, measure and follow-up their intangibles. The International Community should ensure that the process of elaboration and diffusion of intangible assets produces homogeneous and comparable reports and that, as a result, these be useful for estimating future profits, the risk associated with investments, etc. In the moment we are at, we can consider that the fairly complex task of acquisition, production, use, diffusion and measurement of knowledge is essential. According to Carter (1996), although various attempts have been made to measure knowledge, both at a microeconomic and a macroeconomic level, there is still a long way to go. The inclusion, in their annual accounts, of capital sums invested in intangible elements decreases the results announced by companies. This is the reason why certain professional sectors (managers, analysts, consultants,…) are reticent to invest in intangibles, even though they affirm that they contribute to the creation of value. In recent years, different associations and companies have made great advances in the identification, measurement, management and diffusion of
An Overview of International Intellectual Capital (IC) Models and Applicable Guidelines
their intangibles; even if the criteria adopted for this process have been, in the majority of cases, heterogeneous and, as a consequence, the results obtained difficult to compare and/or verify. For all the foregoing, we understand that it is necessary to have a commonly accepted international frame of reference, which provides companies with a basis for the identification and measurement of their intangibles. These Guidelines will not constitute a proposal for the modification of accounting rules. According to the OECD (1999), changes in accounting rules may be necessary in the future but, for the moment, all the efforts concentrated on the measurement and publication of information, should be subject to testing and applied voluntarily. As it turns out, in the depths of the OECD a certain consensus has been established that, little by little, steps should be taken in the development of voluntary Guidelines to measure, report on and manage intangibles. The European Commission has also commenced a process, similar to the preceding, based on the idea that the key to future competitiveness and wellbeing lies in increasing the knowledge base shared by European citizens. In this regard, Chaminade and Johanson (2002) have summarised the conclusions of the conference held by the European Commission in Växjö in March 2001, in the following way: •
•
There still does not exist a commonly accepted conceptual frame of reference to understand, measure and report on intangibles. This means that the coordination and “fertilization” of initiatives between countries from different parts of Europe is very complex (and due to the growing importance of intangibles, the need for a useful, understandable and commonly accepted conceptual framework -or Guideline- seems urgent). The policies of government agencies, the initiatives of the European Union, as well as the possibility of incorporating organi-
•
sations from different sectors, is the crucial starting point to initiate a Project and for the acceptation and diffusion of the methodologies. Although there is no consensus over how to structure the important questions and that it is not possible to develop a serious and adequate empirical study without the necessary (financial) support, this does not mean that there is not a real interest in the question of intangibles in the business world.
Nevertheless, and despite all the reasons already expressed, there are countries that have not developed their own Guidelines (or have not participated as members of the research team of a European project).
Intellectual Capital Models Next we will make an overview of the main inputs in the last years, in theorist and practical ways. Following Table 1 and having in mind the temporal evolution, we can say that there are three different steps: •
•
In the first step, which refers from the first works until 1998, the investigations were centered in making definitions, classifications, establishing the different components of the Intellectual Capital and develop methodologies in a theorist way which have to be then empirically refuted. It is develop an important and diverse conceptual frame with some consensus relating to Intellectual Capital components2. In this step we highlight the pioneer models of Kaplan and Norton, Edvinsson and Malone, Sveiby and Bontis.3 In the second step, which comes from 1999 until 2001, the investigators are dedicated, mainly, to make a review of the existent literature with comparison models, establish-
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An Overview of International Intellectual Capital (IC) Models and Applicable Guidelines
Table 1. Relevant investigations in Intellectual Capital Definition and Classification Kaplan and Norton (1992)
Literature Revision
Empirical Study
Indicators
Petrash (1996)
X X
Edvinsson (1997)
X X
Edvinsson and Malone (1997)
X
Ross et al (1997)
X
Sveiby (1998)
X X
X
X
Cañibano et al (1999)
X
Bornemann et al (1999)
X
Backhuijs et al (1999)
X
X
X
Westphalen (1999)
X
Andriessen et al (1999)
X
Hoogedoorn et al (1999)
X
X
X
X
Guthrie et al (1999) Petty and Guthrie (2000)
X
Bontis et al (2000)
X
Mouritsen et al (2001)
X
Viedma (2001)
X
Ordóñez (2002)
X
Seetharaman et al (2002)
Measurements
X
Brooking (1996)
Bontis (1998)
Macro Conceptual Development
X X
Bueno et al (2003)
X
X
X
X X X
X
X
X
X
X
Serrano et al (2003) Marr et al (2003)
X
X
X X
X
X
Source: Own work1
•
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ing synergies and differences. Also, empiric studies are made which try to validated the before established models proving the relations between the Intellectual Capital and the value creation in a company. Finally, the publications from 2002 until today reflect a new step in which the models are being improved and adapted to the reality of the organizations, in which they are starting to be implemented (financial entities, services companies, insurance companies, knowledge intensive enterprises, public administration, etc.)
The Guidelines We shall specifically seek to justify the need for general guidelines that provide an adequate reference framework for companies and organization’s interested in developing systems of Knowledge Management and the Measurement of Intellectual Capital. To this end, a comparative analysis of the most rigorous efforts developed in recent years has been carried out. Considering the different studies and analyses that have been carried out in the past decade and taking into account the lack of an adequate busi-
An Overview of International Intellectual Capital (IC) Models and Applicable Guidelines
ness practice, launching generalized models for the implementation of Knowledge Management systems and the Measurement and Management of Intangibles in the business world (Intellectual Capital) seems premature. There isn’t actually an internationally accepted frame of reference for the identification, measurement and diffusion of information on intangibles that determine the value of organizations, instead just some isolated efforts in different parts of the world. In the light of this fact, it would appear opportune to dedicate effort to the development of general guidelines that would make it easier for companies to identify, measure and follow-up their intangibles.
Comparisons Between European Guidelines Due to the growth of the Intangible Economy, a growing number of Guidelines, Recommendations, and similar documents dealing with reporting on intangibles and the state of Intellectual Capital have been published in recent years. There has even been an element of competition between them (Del Bello, 2002). Guimón (2002) agrees that this type of document (Guidelines) consists of a series of recommendations, directed towards company directors, on how to manage and report on Intellectual Capital. At a business level, empirical studies show that innovative companies are more financially robust and generate more employment. The key to the continuity of a company is the successful management of its Intellectual Capital.
1. Presentation of the Guidelines The comparative study of the various Guidelines, to which we have been referring, will concentrate on the most important European ones, those with prestige both in the scientific world as well as in professional and business sectors.
The first Guideline is one of the main results of the MERITUM Project (Measuring Intangibles to Understand and Improve Innovation Management). “Guidelines for the Management and Diffusion of Information on Intangibles (Intellectual Capital Report)”, is the final document published in January 2002, which gathers up the principal conclusions of the three-year study. The second Guideline we analyzed is the result of close cooperation between researchers, companies, organizations, consultancies and official organisms in Denmark. It was financed by the Danish Agency for Trade and Industry (from now on Guidelines DATI4). The third Guideline is the principal outcome of NORDIKA (Nordic Project for measuring Intellectual Capital), an Intellectual Capital project initiated by the Nordic Industrial Fund, in collaboration with a Commission set up by the countries involved and a Round Table or Expert Panel formed by professional and business associations in the Nordic countries (Finland, Iceland, Norway, Sweden and Denmark). The analysis was carried out on two levels. Firstly, a study was made of the manner in which the Guidelines were developed and the end result of the research. The following elements were considered (Bañegil and Sanguino, 2007): 1. Terminology employed 2. Conceptual framework adopted 3. Objectives sought in the development of the Guidelines 4. Research methodology The second level of the analysis related to the recommendations incorporated into each Guideline for the elaboration of Intellectual Capital Reports by companies, taking into account the following aspects: 1. Practices used in its development (Who is going to carry it out?)
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2. Procedures for implementation (How is it going to be carried out?) 3. Recommendations for the structure of the proposed Intellectual Capital Report (What will the result be?) 4. Character of the proposed Indicators (What instruments will be used for measuring?) 5. Users of the Intellectual Capital Report (To whom is it directed?)
2. Methodology of the investigation Evidently, the use of different methodologies in the development of the Guidelines will have a clear impact on the final results. The MERITUM Project can be considered the most ambitious because it includes various countries. It describes how to prepare an Intellectual Capital Report and also proposes a model for managing intangibles. As it was developed by a wide range of geographically dispersed researchers there were difficulties in arriving at a consensus. The best practices of approximately eighty European companies were analysed and the conclusions validated by a group of experts using a Delphi analysis. The Intellectual Capital Report is, therefore, presented as the logical conclusion of the process of managing intangibles.
The DATI researchers (university professors, members of government and consultants, amongst others) worked much more closely with companies; the majority of which already had experience in managing intangibles and were guided and supervised by the DATI team in the development of Intellectual Capital Reports. On the other hand, the NORDIKA Guidelines are supported by a thorough conceptual revision of the different models in existence, as well as numerous examples and comparisons of companies. The final document is arrived at through a detailed study of the best practices currently employed in the Nordic countries. In table 2 the principal differences and similarities in the first part of the comparative analysis are set out. Reference is made to the final document produced by the studies, the Guideline.
FUTURE TRENDS For all the foregoing, we understand that it is necessary to have a commonly accepted international frame of reference, which provides companies with a basis for the identification and measurement of their intangibles. These guidelines will not constitute a proposal for the modification of accounting rules.
Table 2. Summary of the first level of the analysis Terminology and Conceptual Framework
Objectives
Methodology
MERITUM
“Intellectual Capital Report” There is no definition of knowledge
Points of connection between resources and critical activities are suggested
Developed by a wide range of researchers from six countries using the DELPHI methodology
DATI
“Intellectual Capital Statement” Knowledge in action
Communication tool that involves clients, employees and other users in the process
Works very closely with companies. Prepares reports on these same companies
NORDIKA
“Intellectual Capital Report” Knowledge as a flow not stock
Tool to manage knowledge and other intangibles
Revision of examples, establishment of comparisons and best practice.
Source: own work
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Table 3. Comparative elements in the established recommendations MERITUM
DATI
NORDIKA
Practices used and implementations procedures
Designation of tasks to different subjects in three well defined phases
Directors should commence the process, which will have four phases.
More subjects involved and the organisation must get ready for that
Structure
The most clear: includes vision, resources, activities and indicators
Semi-closed structure, including Auditor’s Report on Intellectual Capital
Doesn’t propose any particular structure
Indicators
Doesn’t establish any, they are specific to each company
Must be strictly related to actions
Lacks a fixed scheme, they should be developed with strategic purposes
Users
Internal (fundamentally directors) and external
Stakeholders
Principally internal, also external
Source: own work
According to the OECD (1999), changes in accounting rules may be necessary in the future but, for the moment, all the efforts concentrated on the measurement and publication of information, should be subject to testing and applied voluntarily. As it turns out, in the depths of the OECD a certain consensus has been established that, little by little, steps should be taken in the development of voluntary guidelines to measure, report on and manage intangibles.
CONCLUSION We have to emphasise that, despite not finding significant differences between the Guidelines analysed, the similarities are still far from configuring a single Conceptual Framework offering comparability and homogeneity for carrying out Intellectual Capital Reports. An effort at benchmarking and cooperation between the researchers of the Guidelines studied, in order to complete the actualisations that are contemplated, would be an excellent starting point for exploiting synergies and achieving a wide consensus in different basic aspects of the measurement of intangibles in general and Intellectual Capital in particular.
So that researchers, consultants, politicians and professionals who work in the field of intangibles can achieve the necessary and desired degree of comparability, governments should promote the development of a commonly accepted Guideline. For this purpose, the identification of best practice in the existing Guidelines, should be the starting point of any initiatives that seek to harmonise the measurement practices for intangibles. Nevertheless, there are forces pushing in the opposite direction. In some countries that are in an early stage of research, and which do not have an established theoretical framework, the main problems to be overcome are: resistance to change and groups that promote certain approximations (research groups, business and professional associations, government, etc). In addition, companies demand freedom and flexibility when they then decide how to handle and report on intangibles and therefore oppose specific regulations and obligations. The final purpose of our efforts seeks to enfazise the fact that those specific guidelines should be internationally accepted. This would allow further empirical studies on those businesses that decide to implement them, particularly and mainly at a sectorial level. In this sense, those indicators used for this purpose should be adjusted to the specific characteristics of each sector.
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Fortunately, various Spanish sectors have been recently mobilizing to set common standards in order to elaborate homogeneous Intellectual Capital Reports. The Banking and Electrical sectors are examples of entities leading this new tendency.
REFERENCES Bañegil, T., & Sanguino, R. (2007). Intangible measurement guidelines: a comparative study in Europe. Journal of Intellectual Capital, 8(2), 192–204. doi:10.1108/14691930710742790 Brennan, N., & Connell, B. (2000). Intellectual Capital; current issues and policy implications. Journal of Intellectual Capital, 1(3), 206–240. doi:10.1108/14691930010350792 Carter, A. (1996). Measuring the performance of a Knowledge-based Economy. OCDE Report Employment and Growth in the Knowledge-based Economy, Paris, OECD. Chaminade, C. (2002). Can guidelines for Intellectual Capital reporting be considered without addressing cultural differences? An explorative paper. In Proceedings The Transparent Enterprise. The value of intangibles. Madrid: Autonomous University of Madrid. Danish Agency for Trade and Industry –DATI. (2000). A guideline for Intellectual Capital Statements. A Key to Knowledge Management. Retrieved June 1, 2009, from http://en.vtu.dk/ publications/2001/a-guideline-for-intellectualcapital-statements/a-guideline-for-intellectualcapital-statements-a-key-to-knowledge-management DATI. (2003). Intellectual Capital Statements – The New Guideline. Retrieved June 1, 2009, from http://www.pnbukh.dk/site/10186.htm
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Del Bello, A. (2002). A regulatory competition? A critical comparison of the existant guidelines and recommendations on ic statements and intangibles reports. In Proceedings The Transparent Enterprise. The value of intangibles. Madrid: Autonomous University of Madrid. Guimón, J. (2002). Guidelines for intellectual capital management and reporting. Comparing the MERITUM and the Danish approaches. In Proceedings The Transparent Enterprise, The value of intangibles. Madrid: Autonomous University of Madrid MERITUM. (2002). Guidelines for managing and reporting on intangibles. Intellectual Capital Report, Ed. Fundación Airtel Móvil. Retrieved June 1, 2009, from http://www.pnbukh.com/site/ files/pdf_filer/MERITUM_Guidelines.pdf. Nordic Industrial Fund. (2001). Intellectual capital. Managing and reporting. A Report from the Nordika Project. Retrieved June 1, 2009, from http://www.nordicinnovation.net/_img/ nordika_report_-_final1.pdf Nordic Industrial Fund. (2002). Nordika – Frame Market Survey. Norway: Author. OCDE. (1999). International Symposium on Measuring and Reporting Intellectual Capital: Experience, Issues and Prospects. Amsterdam: Author. Retrieved June 1, 2009, from www. oecd.org/dsti/sti/industri/indcomp/act/Ams-conf/ symposium.htm
ENDNOTES 1
2
Related to it we can read the article published by Brennan and Connell (2000). Its structure is defined having in mind three capitals: Human Capital, Structural Capital and Relational Capital (or Client Capital).
An Overview of International Intellectual Capital (IC) Models and Applicable Guidelines
3
4
The Kaplan and Norton model can not be considered specifically as a Intellectual Capital Model but, seen that it has been the first which exceeds the only financial vision, we think we must incorporate it to this study. This guideline is base on empirical research as well as a thorough research in this field,
lead by the Copenhagen Business School and the Aarhus School of Business, in cooperation with the consulting enterprise Arthur Andersen in Denmark. Additionally, more than a hundred Danish companies have finalized their intellectual capital reports based on these guidelines.
This work was previously published in Strategic Intellectual Capital Management in Multinational Organizations: Sustainability and Successful Implications, edited by Kevin O’Sullivan, pp. 136-143, copyright 2010 by Business Science Reference (an imprint of IGI Global).
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Chapter 1.13
Business Models and Organizational Processes Changes Helena Halas SETCCE, Slovenia Tomaž Klobučar Jožef Stefan Institute & SETCCE, Slovenia
ABSTRACT This chapter explores the influence of pervasive computing on companies and their businesses, with the main stress on business models. The role of business models for companies is presented. Introduction to pervasive computing and a survey of existing e-business models classifications are used as a base for our research. The main characteristics of today’s business models are discussed and a method for evaluating business models characteristics is proposed. We concentrate on characteristics of pervasive computing and their DOI: 10.4018/978-1-60960-587-2.ch113
influence on companies’ business processes and business models. The present and future business characteristics and business models are briefly compared, and future research directions on pervasive computing and business models are presented.
INTRODUCTION The future is bringing us more and more challenges, and changes have become an ordinary part of our everyday lives. The same is true for business. Companies constantly face novelties, and it is important that they know how to tackle
Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
Business Models and Organizational Processes Changes
the new circumstances and how to adjust their business. One of the biggest shifts was caused by appearance of internet, which interconnected the world in many aspects and fundamentally transformed the way companies conduct business. Internet technologies enabled communication and cooperation on different levels between whichever interested parties around the world. As a result of further development of information-communication technologies (ICT), we are approaching the next major change that will affect companies, i.e. appearance of pervasive computing. Pervasive computing is already a fact, although its final form and impact are still not known in detail. However, researchers and practitioners agree that its influence on business will be significant and it will dramatically change business models. Therefore, it is important for companies to become aware of it and to start thinking about what effect pervasive computing and pervasive technologies will have on their businesses. The appearance of pervasive computing needs to be seen as an opportunity for companies to improve their business processes and business as a whole, and not as an (un)necessary evil. New technologies allow companies to improve their business processes, adjust business models, start doing business in a new way, or start completely new business. A question arises here, which of the existing business models will be appropriate for the future environment of pervasive computing and in which way the development of business models will go or what new business models we can expect. It is necessary to investigate which characteristics of pervasive computing will mainly affect future business and which common characteristics of future business models could be exposed. The main objective of the chapter is to examine how pervasive computing affects the way a company organizes its business and how existing business models fit in the environment of pervasive computing. Our work on this topic discusses existing business models that are appropriate for the era of pervasive computing and necessary changes.
We also identify some general characteristics for the future business models. Next, we discuss the means of collaboration between incorporated participants and relations with customers and how will they change with appearance of pervasive technologies. Business models for setting up and operating seamlessly integrated infrastructure are also discussed. The chapter is organized as follows. First, we present the concept of pervasive computing and basics about business processes and business models. In the next step, we concentrate on characteristics of today’s systems and present some existing e-business models taxonomies. At the end of this section, we try to summarize common characteristics of today’s business models. After that, we focus on pervasive computing and the changes caused by appearance of pervasive technologies, and their impact on companies and their business processes. Adequacy of existing business models for pervasive computing environments is investigated and a view on the future business models is presented. Future research directions are given at the end.
PERVASIVE COMPUTING “The most profound technologies are those that disappear. They weave themselves into fabric of everyday life until they are indistinguishable from it.” (Weiser, 1991). Although Mark Weiser proposed this concept under the term ubiquitous computing almost 20 years ago, only recently pervasive computing really has started to affect organizations and their businesses. In the last few years, technology improvement of the networks, connectivity and devices capability have moved borders of possible and facilitated wider use of pervasive computing. Pervasive computing refers to presence of advanced communication and computing technologies everywhere around us in a way they are invisibly embedded in everyday objects and
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people are mostly unaware of their presence. The computing environment is thus available everywhere and is into everything. In the literature, we find several terms for this concept, e.g. pervasive computing, ubiquitous computing and ambient intelligence. Pervasive and ubiquitous computing are usually used almost as synonyms, while ambient intelligence emphasizes more the system infrastructure’s autonomic learning capability and interaction mechanisms for users in particular social contexts (Roussos, Marsh, & Maglavera, 2005). Pervasive and ambient intelligence technologies offer people support and opportunities to make their lives simpler. However, on the other hand they also introduce new security and privacy problems. Embedding informationcommunication technology components into every object immediately raises scruples about privacy, as objects can be tracked everywhere and all the time, and consecutively so do people, who wear or carry them. Pervasive computing environments require seamless communication infrastructure, intelligent intuitive user interfaces and low-power devices, which are sensitive, adaptive, and responsive to human needs. If we focus on ICT technologies, the main attributes of pervasive computing environments and pervasive systems are miniaturization, embedding, networking, ubiquity, and context awareness (Federal Office for Information Security, 2006). Miniaturized ICT components, embedded into everyday objects transform them into smart objects and integrate them into a virtual world. The invisible components are everywhere around us (ubiquity) and connected together in networks, where mobility and ad-hoc networking are important characteristics. Pervasive computing environments have abilities to recognize users and their context (context awareness). Context typically includes, for example, user and devices identity and location, the facts such as proximity, time, or history, network and environment characteristics, or social situation of the user. Personalization services en-
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able pervasive computing environments adjust to the needs of individual users.Technologies that make pervasive computing possible start to become mature. They include: • • •
• •
Communication technology (e.g. 802.11, Bluetooth, UMTS), Identification technology (e.g. RFID tags, visual barcodes), Localisation technology (e.g. satellite supported, such as GPS, cellular-supported, such as GSM, or indoor localisation systems), Sensor and actuator networks and technology, Intelligent user (friendly) interfaces.
With their integration, pervasive environments can be established, and objects and processes in the real world can be linked up with the digital world of information systems without human intervention.
INTRODUCTION TO BUSINESS MODELS In this section we briefly present some business elements that will help us better understand business of a company and impact of changes. Changes are today something ordinarily on the market and their dynamics is increasing. It is on the companies not to resist changes but to accept them as new opportunity for the success. New technology is one of the main factors that bring changes. Business in a company is tightly connected with business processes. A business process is a series of logically connected tasks, which perform with the purpose to reach defined goal (Davenport, Short, 1990). It is about logically connected tasks, procedures, activities, whose result is some planed product or service. As a process, we can define every activity in a company or out of it. However, it is reasonable to consider and define only those
Business Models and Organizational Processes Changes
processes that contribute to the additional value of final products or services (Kovačič, & Bosilij Vukšič, 2005). Therefore, changes in the company bring changes in its business processes. Malone and Weill (2003) define a business model as a description of activities that a company performs to generate revenue or other benefits, and the relationships, information, and product flows a company has with its customers, suppliers, and complementors. Osterwalder, Pigneur and Tucci (2005) define it more precisely, namely as a conceptual tool that contains a big set of elements and their relationships and allows expressing the business logic of a specific firm. It is a description of the value a company offers to one or several segments of customers and of the architecture of the firm and its network of partners for creating, marketing, and delivering this value and relationship capital, to generate profitable and sustainable revenue streams. Generally, a business model is description of company’s business processes and their interconnections. For a company it is essential to have good knowledge of its business and activities. A business model is a great help for expressing the business logic of a company. In the present time of rapid changes, it is reasonable to have this picture always in front of our eyes to be capable to react quickly when the need or opportunity appears.
to electronic business. The fundamental innovations were not just using new technologies, but using technologies to enable new business models (Malone & Weill, 2003). But it is important to be aware that electronic commerce over the internet may run as a complement to traditional business or represent a whole new line of business (Timmers, 1998). At the moment, e-business still plays mainly a role in supporting the basic business, not driving the business. Business models are often viewed from different perspectives and they depend on the field of interest. Because of this there is no unified method to classify acquired knowledge about business models, and approaches often overlay or sometimes even conflict. Osterwalder, Lagha and Pigneur (2002), for example, established that three aspects on business models could be found in the literature: revenue/product aspect, business actor/network aspect and market aspect. In the literature we can find several proposals for business model taxonomies that try to categorize business models into different classes based on various criteria. A survey of some approaches is listed below: •
PRESENT: BUSINESS MODELS The progress in information and communication technology has changed conditions in economics and significantly affected the way companies conduct their business today. With support of ICT companies can easily cooperate or make business with business partners from everywhere.
Today’s Business Models Important changes in business occurred already with expansion of internet, when world moved
•
Timmers (1998) distinguished the following generic models: e-shop, e-procurement, e-auctions, e-malls, 3rd party marketplace, virtual communities, value chain service provider, value chain integrators, collaboration platforms, information brokerage, trust and other third-party services. Bambury (1998): ◦⊦ Translated real-world business models: mail-order model, advertisingbased model, subscription model, free trial model, direct marketing model, real estate model, incentive scheme model, B2B, combinations of the above models; ◦⊦ Native internet business models: library model, freeware model, information barter model, digital products
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•
•
•
•
•
•
•
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and digital delivery model, access provision model, website hosting and other models. Hartman, Sifonis and Kador (1999) identified five extended business models: e-business storefront, infomediary, trust intermediary, e-business enabler, and infrastructure providers/communities of commerce. Viehland (1999) proposed three business models: virtual retailing, distributed storefronts, buyer-led pricing. Linder and Cantrell (2000) differentiated business models according to price model, convenience model, commodity-plus model, experience model, channel model, intermediary model, trust model, innovation model. Tappscott, Ticoll & Lowi (2000) distinguished five value networks: agora, aggregation, value chain, alliance, and distributive network. Applegate (2001) classified models in four categories: ◦⊦ Focused distributor models: retailer, marketplace, aggregator, infomediary, exchange, ◦⊦ Portal models: horizontal portals, vertical portals, affinity portals, ◦⊦ Producer models: manufacturer, service provider, educator, advisor, information and news services, custom supplier, ◦⊦ Infrastructure provider models: infrastructure portals. Weil and Vitale (2002) provided eight atomic e-business models that could be combined in multiple ways: direct to customer, full service provider, whole enterprise, intermediaries, shared infrastructure, virtual community, value net integrator, content provider. Laudon and Traver (2003) categorized business models according to e-commerce sector (B2C, B2B, and C2C). They identi-
•
•
•
fied seven B2C business models: portal, etailer, content provider, transaction broker, market creator, service provider, and community provider. Osterwalder, Pigneur and Tucci (2005) identified nine building blocks for business models: value proposition, target customer, distribution channel, relationship, value configuration, core competency, partner network, cost structure, revenue model. Lai, Weill, & Malone (2006) explained sixteen possible models regarding to what types of rights are being sold (creator, distributor, landlord, broker) and what types of assets are involved (physical, financial, intangible, human), but some of them are not brought into use: entrepreneur, manufacturer, inventor, human creator, financial trader, wholesaler/ retailer, IP trader, human distributor, financial landlord, physical landlord, intellectual landlord, contractor, financial broker, physical broker, IP broker, HR broker. Rappa (2007) defines forty models in nine basic categories, which are in practice often used in combination: ◦⊦ Brokerage model (marketplace exchange, buy/sell fulfilment, demand collection system, auction broker, transaction broker, distributor, search agent, virtual marketplace), ◦⊦ Advertising model (portal, classifieds, user registration, query-based paid placement, contextual advertising, context-target advertising, intromercials, ultramercials), ◦⊦ Infomediary model (advertising networks, audience measurement services, incentive marketing, metamediary), ◦⊦ Merchant model (virtual merchant, catalogue merchant, click and mortar, bit vendor),
Business Models and Organizational Processes Changes
◦⊦
◦⊦ ◦⊦
◦⊦
◦⊦
Manufacturer model (direct) (purchase, lease, license, brand integrated content), Affiliate model (banner exchange, pay-per-click, revenue sharing), Community model (open source, open content, public broadcasting, social networking services), Subscription model (context services, Person-to-person networking services, trust services, internet services providers). Utility model (metered usage, metered subscription).
Lambert (2006) says that in general two basic classification schemes are recognized: special and general. General classification schemes could serve to multiple purposes, special to very specific ones. He also claims that all existing classification schemes in literature are special. They are designed to suit particular views or needs of a researcher and cannot be used for multiple purposes. The need for a general classification scheme for business models has been widely recognized. Lambert (2006) believes that proper general business model typology could be achieved if a large number of business model variables are considered simultaneously, which can only be done objectively using statistical analysis, in particular cluster analysis.
Common Characteristics of E-Business Models Many business models exist and countless combinations are possible and also applied in practice (Jansen, Steenbakkers, & Jägers, 2007). As mentioned before they are often viewed from different perspectives and there is no unified method to classify them. Therefore, we do not concentrate here on specific business models, but try to establish some common characteristics of today’s business models.
Today, a prefix “e” is actually unavoidable. Internet has significantly changed business and the way business is conducted, which resulted also in emergence of new business models for digital environment. Settlement of inter-organizational networks is indispensable as it is impossible to implement these models without the networks. Focus has been put on CRM (customer relationship management), SCM (supply chain management) and ERP (enterprise resource planning) with maximum support of internet technology. Expansion of internet has enabled new markets to emerge online. Electronic marketplace or e-marketplace is a trading community of buyers and suppliers, and makes buying and selling easier for both parties by reducing the number of needed interactions and automation of some processes. To improve business processes business models need to assure improved communication across the supply chain, good collaboration between partners to improve CRM and product development, and optimisation of partnership relations (BuyIT, 2002). In an increasingly dynamic and uncertain business environment it is essential that business models can be easily modified (by business model designers) (Petrovic, Kittl, & Teksten, 2001). Based on a synthesis of existing business model literature Osterwalder (2004) proposed nine business model elements that can be evaluated when characterizing business models: • • •
• • • • •
Value proposition (product or service innovation) Target customer (communities) Distribution channels (the right quantities of the right products or services available at the right place, at the right time) Relationship management (customer integration, personalization) Value configuration (value chain, value shop, value network) Capabilities (management and business) Partnerships (cooperation, competition) Cost structure (low-cost leadership)
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•
Revenue model (sale, registry, subscription, advertisement, transaction, commission)
FUTURE: BUSINESS MODELS Now, it is still hard to estimate which existing e-business models will be appropriate for the pervasive computing environment. Pervasive computing technology is not necessarily going to completely change companies’ business models, but in some cases just improve existing business processes. As the number of business models is getting larger and the new models constantly appear we will rather investigate which characteristics of business models will prevail in the future. Therefore, in this section, we first discuss expected influence of pervasive computing on companies’ business in general and some expected characteristics of the future new business models. Then we present some business models for the environment of pervasive computing.
Impact of Pervasive Computing on Business Processes New technologies can influence business in two ways: by improving business processes or changing business models. Changing business model means that a company runs existing business in a new way, starts new business, or complements existing business. According to the BSI’s pervasive computing study (Federal Office for Information Security, 2006) the main drivers or motivations behind pervasive computing are: • • • •
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Economic incentives of offering new products and services Economic incentives of reducing costs Increasing personal comfort and user friendliness Increasing energy efficiency and materials use efficiency
In this respect, pervasive computing appears to be nothing special comparing to other new technologies. The main difference is in a way how that is achieved. The question is what pervasive computing could do in this direction and what its contribution is. Bohn, Coroamă, Langheinrich, Mattern, and Rohs (2004) claim that two important pervasive technologies form the core of new economic processes and applications: the ability to track real-world entities, and the introspections capabilities of smart objects. Tracking objects in realtime allows for more efficient business processes, while objects that can monitor their own status via embedded sensors allow for a range of innovative business models. Automatic identification, localization and sensor technology can inform us about the current product state, location and presence of other products in its neighbourhood (Strassner, & Schoch, 2002). Focusing on tracking goods, different aspects can be established: SCM, production, CRM, etc. Already the swing of internet influenced business processes considerably, but media breaks and consecutively information delays are still causing processes inefficiencies. With new technologies the breaks between real and virtual world could be avoided and problems with inefficiencies solved. More accurate and continuous tracking of goods within supply chain would prevent losses and mislays of goods and reduce stock quantity as product planning could be improved. Tracking products in time of production would help to detect mistakes shortly after their appearance. “Smart” objects would be able to accept their own decisions on the basis of all available data. New technologies affect companies in such a way that business processes can be more automated and independent of the people and their decisions, what leads to self-management. Thus chances for human errors are reduced or totally eliminated as in the final phase supply chain can be conducted in a fully automated way. Those benefits would impact efficiency improvement and cost reduc-
Business Models and Organizational Processes Changes
tion in various business processes of a company. With today’s technology many improvements could already be realized, but the question of cost justification remains. The optimisation of individual processes has effect on operational efficiency (speeds up processes), availability of goods, product quality and flexibility of process management. Even more important for companies is which novelties the new technology will bring.
Pervasive Computing Business Models Pervasive computing technology will affect companies and their businesses with complete integration of the real and virtual world. Companies will be able to collect more useful data (more accurate, more diverse, more frequent...) and to get real time information. Automation will be on higher level. With full data collection a usage based pricing business model will be useful and efficient to a greater extent. The companies will face the following changes: •
• •
Transforming business model from selling services at a fixed price to usage-based pricing Selling services instead of selling products Selling product related services beside products
Fleisch (2004) believes that pervasive computing technologies will primarily be used in controlling intensive processes. Expected changes can be divided into two classes: •
•
Improvement of existing business processes (faster, more accurate, reliable and cost efficient), where a company changes the way it manages resources (how), but does not change its business model (what) New business model, when company does not ask how to improve existing business
processes but investigates which new services it could be offered to its customers In addition, new ways of collaboration or improved collaboration between different parts of a value chain arise. Pervasive computing is changing the way business and customers are able to access each other. With pervasive computing technologies, the scope of CRM will expand significantly. Location of the customer will become the location of the business, products will be possible to track and communicate with after they are sold, and sold products will be at the same time the best representatives of a company (Gerschman, 2002). Services are in the centre of most pervasive computing opportunities because new technologies and infrastructure enable companies to follow the customer’s needs and truly deliver individualised services anywhere and anytime. It is expected that in pervasive computing the services value will grow significantly. Product lifecycle is connected with many activities and each of them could be an opportunity for the company. Products could be linked with services that extend their functionalities. In addition, services that are not directly connected to a product represent an opportunity. In this way, companies could differ from their competitors and retain customers or even gain new ones. Harbor Research (2005) explains that to understand pervasive business models we must see individual opportunities as elements of an overall business opportunity that can be solo or team opportunity. Further, they define two business models within each category. Four types of business models were established: •
•
Embedded innovator - It allows traditional standalone services to be embedded directly into the product. Solutionist - It provides many or all of the services around the total lifecycle of a product.
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•
•
Aggregator - It integrates the sales and service of the product, as well as the interaction with the customer. Synergist - It is a contributor and a participant in alliance web where no single company “owns” the aggregator function.
Nagumo (2002) identified the following major innovative business models for the era of pervasive computing: •
•
•
“Concierge” business models - The author described them as “very attentive services provided when needed” that support the everyday life of people in a non-intrusive manner. “Knowledge asset management” business models - It enables companies to gather the knowledge available on the network and make the best use of it to develop advanced and efficient services. “Wide-area measurement” business models - It refers to gathering data to resolve public issues.
Bohn et al. (2005) proposed the following innovative business models: • • •
Real-time shopping - People could buy anything from anywhere. Pay-per-weigh - It refers to pay-per-use instead of buying products. No risk, no premium - Also called pay-perrisk, where price of an offer depends on risk involved.
Tracking customers’ possibility will allow price discrimination or dynamic pricing, although question appears when if at all this kind of pricing brings profit. Potential user reaction to price discrimination should also be taken into account before its introduction.
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Willis (2003) presented pervasive business models in respect of participated players: business, consumer, employee, machine, where he foresaw also relation between two machines (M2M business). In pervasive computing environment, business models will be of great significance. Researches still focus mainly on pervasive computing technology and business models classification. More research should be dedicated to analysis of appropriateness of existing business models and to methodologies for developing new business models for the pervasive computing environment. To develop a suitable business model in pervasive computing environment, a logical and systematic development method reflecting the characteristics of pervasive computing is needed (Leem, Jeon, Choi, & Shin, 2005). Table 1 shows a summary of essential characteristics of the present business and business models and expected trend for the future business and business models that will be possible in pervasive computing environment.
CONCLUSION Future is constantly bringing changes. Some of them can be foreseen, others surprise us. Pervasive computing is something certain in the near future, but we cannot foresee exactly in what shape and size it will develop. It is important for companies to be aware of its current situation and to be prepared to take advantage of the opportunity when it appears. Moreover, pervasive computing will surely bring new opportunities for companies. Although many researchers and practitioners have devoted their effort to the domain of business models, there are still many issues to be clarified. There is no unified method to classify acquired knowledge about business models and therefore it cannot be used in such extent and so effectively as it could be. As business models present one of the possibilities for differentiation
Business Models and Organizational Processes Changes
Table 1. Present and future business and business models
BUSINESS MODELS
BUSINESS
PRESENT
FUTURE
Unclear mass of data
On-time information
Partial integration of virtual and real world
Full integration of virtual and real world
Technology as a support to people
People support to technology?
People make decisions
Devices, machines… make decisions
People – machine communication
Machine – machine communication
Partial automation of business processes
Full automation of business processes
Quickly responding business
Real-time business
Customers search products
Products find customers
Easily adaptable business models
Self-configurative business models
Selling services at a fixed price
Usage-based pricing
Selling services at a fixed price
Risk-based pricing
Selling products
Selling services
Selling products
Selling products and related services
Single price
Dynamic pricing
Regular shopping, internet shopping
Real-time-shopping
from competitors and in this way a potential for competitive advantage, the business model domain needs to be researched further, especially in the new circumstances.
FUTURE RESEARCH DIRECTIONS Business models are for a company one of the possibilities for differentiation from competitors and thus a potential for competitive advantage. In order to use the acquired findings more effectively as a base for further research and faster advancement of the business models domain the unified method for classifying existing knowledge about business models in general would be helpful. This would also enable more successful implementation in practice. In further research particular e-business models taxonomy should be selected and examined. Its characteristics should be established and more precisely analysed. Adequacy of the analyzed business models for environment of pervasive computing should be evaluated. The
evaluation of business models characteristics can be performed by the method proposed in the paper. Pervasive computing characteristics in connection with business models should be further discussed in more detail, as well as comparison between present and future business models. Economic issues of pervasive computing infrastructure as one of the fundamental factors for realization of pervasive computing and connected businesses needs to be further investigated. The literature is concerned mostly with needed technology for establishment of pervasive infrastructure. One of the important questions is who will fund the infrastructure costs required to support pervasive computing everywhere and how the use of the infrastructure will be charged. Research should concentrate also on business models appropriate for setting up and operating seamlessly integrated infrastructure.
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REFERENCES Applegate, L. M. (2001). E-Business models: Making sense of the Internet business landscape. In: G. Dickson, W. Gary and G. DeSanctis (Eds.), Information Technology and the Future Enterprise: New Models for Managers. Upper Saddle River, N.J.: Prentice Hall. Bambury, P. (1998). A taxonomy of Internet commerce. First Monday, 3(10). Bohn, J., Coroamă, V., Langheinrich, M., Mattern, F., & Rohs, M. (2005). Social, economic, and ethical implications of ambient intelligence and ubiquitous computing. In: W. Weber,J. Rabaey & E. Aarts (Eds.), Ambient Intelligence, 5-29. Berlin Heidelberg, Germany: Springer. BuyIT (2002). Supplier adoption: Getting ready for E-Business. Section 2: The E-Business Models. BuyIT Best Practice Network. Davenport, T. H., & Short, J. E. (1990). The new industrial engineering: Information technology and business process redesign. Sloan Management Review, (Summer): 11–27. Federal Office for Information Security. (2006). Pervasive computing: Trends and impacts. Bonn, Germany: BSI. Fleisch, E. (2004). Business impact of pervasive technologies: Opportunities and risks. Human and Ecological Risk Assessment, 10(5), 817–829. doi:10.1080/10807030490513838 Gerschman, A. (2002). Ubiquitos commerce – Always on, always aware, always pro-active. IEEE Computer Society, 37-38. Harbor research. (2005). Growth opportunities and business models for the Pervasive Internet. Boston and San Francisco, USA: A Harbor White paper. Hartman, A., Sifonis, J., & Kador, J. (Eds.). (2000). Neat Ready: Strategies for success in the E-Economy. New York: McGraw-Hill.
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Jansen, W., Steenbakkers, W., & Jägers, H. (Eds.). (2007). New business models for the knowledge economy. Hampshire, England: Gower Publishing Limited. Kovačič, A., & Bosilj Vukšić, V. (Eds.). (2005). Management poslovnih procesov: Prenova in informatizacija poslovanja. Ljubljana: GV Založba. Lai, R., Weill, P., & Malone, T. (2006). Do Business Models Matter? SEEIT, MIT Sloan School of Management. Retrieved August 3, 2007, from http://seeit.mit.edu/publications.asp Lambert, S. (2006, June). A business model research schema. Proceedings of the 19th Bled eConference, Bled, Slovenia. Laudon, K., & Traver, C. (Eds.). (2003). ECommerce: Business, technology, society (2nd ed.). Boston: Addison-Wesley. Leem, C. S., Jeon, N. J., Choi, J. H., & Shin, H. G. (2005). A business model (BM) development methodology in ubiquitous computing environments. In: O. Gervasi et al. (Eds), Computational Science and Its Applications – ICCSA 2005, Singapore International Conference: Proceedings, Part 4, (pp. 86-95). Berlin Heidelberg, Germany: Springer. Linder, J., & Cantrell, S. (2000). Carved in water: Changing business models fluidly. A Working Paper from the Accenture Institute for Strategic Change. Retrieved October 12, 2007, from http:// sirnet.metamatrix.se/material/SIRNET_bakgrundsmaterial/business_model_0012.pdf Malone, T., & Weill, P. (2003). Changes in Business Models. SEEIT, MIT Sloan School of Management.Retrieved August 3, 2007, from http:// seeit.mit.edu/publications.asp Nagumo, T. (2002). Innovative business models in the era of ubiquitous networks. NRI Papers, 49. Nomura Research Institute.
Business Models and Organizational Processes Changes
Osterwalder, A. (2004). The business model ontology: A proposition in a design science approach. PhD Dissertation. Switzerland: University of Lausanne. Osterwalder, A., Lagha, S. B., & Pigneur, Y. (2002, July). An ontology for developing E-Business models. Proceedings of IFIP DSIAge’2002. Osterwalder, A., Pigneur, Y., & Tucci, C.L. (2005). Clarifying Business models: Origins, present, and future of the concept. CAIS, 15, 751-775. Parliamentary Office of Science and Technology. (2006). Pervasive computing (POST note No. 263). London: The Parliamentary Office of Science and Technology. Retrieved July 14, 2007, from http://www.parliament.uk/documents/ upload/postpn263.pdf Petrovic, O., Kittl, C., & Teksten, R. D. (2001). Developing business models for E-Business. International Conference on Electronic Commerce 2001, Vienna. Rappa, M. (2007). Business models on the Web. Managing the digital enterprise. Retrieved August 3, 2007, from http://digitalenterprise.org/models/ models.html Roussos, G., Marsh, A. J., & Maglavera, S. (2005). Enabling Pervasive Computing with Smart Phones. IEEE Pervasive Computing / IEEE Computer Society [and] IEEE Communications Society, 4(2), 20–27. doi:10.1109/MPRV.2005.30 Strassner, M., & Schoch, T. (2002). Today’s impact of ubiquitous computing on business processes. In: F. Mattern, M. Naghshineh (Eds.), Short Paper Proceedings, International Conference on Pervasive Computing, Pervasive 2002 (pp. 62-74). Zürich. Tapscott, D., Ticoll, D., & Lowi, A. (Eds.). (2000). Digital capital - harnessing the power of business Webs. Boston: Harvard Business School Press.
Timmers, P. (1998). Business Models for Electronic Markets. Electronic Markets, 8(2), 3–8. doi:10.1080/10196789800000016 Viehland, D. W. (1999). New business models for electronic commerce. Proceedings of the 17th Annual International Conference of the Association of Management/International [San Diego: California.]. Association Management, 17(2), 141–143. Weill, P., & Vitale, M. R. (Eds.). (2001). Place to space: Migrating to E-Business Models. Boston: Harvard Business School Press. Weiser, M. (1991). The Computer for the 21st Century. Scientific American, (Sept): 94–100. Willis, T. (2003). Pervasive Computing. 18th annual ACM SIGPLAN Conference on OOPSLA, Workshop Pervasive Computing Going beyond Internet for small screens.
ADDITIONAL READING Acquisti, A. (2005). Ubiquitous Computing, Customer Tracking, and Price Discrimination. In: G. Roussos (Ed.), Ubiquitous and Pervasive Commerce: New Frontiers for Electronic Business (pp. 115-132). New York, USA: Springer. Acquisti, A., & Varian, H. R. (2005). Conditioning Prices on Purchase History. Marketing Science, 24(3), 367–381. doi:10.1287/mksc.1040.0103 Akella, K., & Yamashita, A. (1999). Application Framework for e-business: Pervasive computing. IBM. Retrieved June 27, 2007, from http:// www.ibm.com/developerworks/library/wa-pvc/ index.html Albee, J., Kuchal, M., & Jaiswal, R. (2003). Pervasive computing: e-business anywhere, anytime. IBM. Retrieved June 27, 2007, from http://www.ibm.com/developerworks/wireless/ library/wi-pvcapps/
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Business Models and Organizational Processes Changes
Amor, D. (2001). Pervasive Computing: The Next Chapter on the Internet. Prentice Hall PTR. Retrieved June 27, 2007, from http://www.informit. com/articles/article.aspx?p=165227&rl=1 Chalmers, D., et al. (2006). Ubiquitous Computing: Experience, Design and Science. Retrieved July 2, 2007, from http://www-dse.doc.ic.ac.uk/ Projects/UbiNet/GC/index.html
Hoare, T., & Milner, R. (Eds.). (2004). Grand Challenges in Computing: Research. Swindon: The British Computer Society. ISTAG. (2003). Ambient Intelligence: from vision to reality. For participation – in society & business. Draft report. Brussels: IST Advisory Group, European Commission.
Fano, A., & Gershman, A. (2002). The Future of Business Services in the Age of Ubiquitous Computing. Communications of the ACM, 45(12), 83–87. doi:10.1145/585597.585620
Jazayeri, M. (2002, September). On the Way to Pervasive Computing. Brazilian Symposium on Software Engineering. Retrieved November 16, 2007, from http://www.infosys.tuwien.ac.at/Staff/ mj/papers/pervasive.pdf
Fleisch, E. (2001). Business Perspectives on Ubiquitous Computing. M-Lab Working Paper, No. 4, Ver. 1.0. Retrieved November 11, 2007, from http://www.m-lab.ch/
Kyoung, J., Jeong-In, J., & Jeong Mu, J. (2006). A Payment & Receipt Business Model in UCommerce Environment. ACM International Conference Proceeding Series, Vol. 156, 319–324.
Fleisch, E., & Tellkamp, C. (2005). The Business Value of Ubiquitous Computing Technologies. In: G. Roussos (Ed.), Ubiquitous and Pervasive Commerce: New Frontiers for Electronic Business (pp. 115-132). New York, USA: Springer.
Lambert, S. (2006). Do We Need “Real” Taxonomy for e-Business Models? School of Commerce Research Paper Series: 06-6. ISSN: 1441-3906. Retrieved August 31, 2007, from http://www.socsci. flinders.edu.au/business/research/papers/06-6.pdf
Gershman, A., & Fano, A. (2005). Ubiquitous Services: Extending Customer Relationship Management. In: G. Roussos (Ed.), Ubiquitous and Pervasive Commerce: New Frontiers for Electronic Business. New York, USA: Springer.
Lee, D. L. (2002). Technological and Business Challenges in Pervasive Computing. SAINT, Proceedings of the 2002 Symposium on Applications and the Internet (pp. 41-42).
Haas, M., Koeszegi, S., & Noester, M. (2007). Current practice and structural patterns in virtual organizations – a qualitative analysis of 30 cases. The Electronic Journal for Virtual Organizations and Networks, 8. Retrieved November 27, 2007, from http://www.virtual-collaboration.org/projects/264/Issues/eJOV%20Vol8/eJOV8_4_Haas_ Current%20practice%20and%20structural%20 patterns.pdf Hertel, G., Geister, S., & Konradt, U. (2005). Managing virtual teams: A review of current empirical research. Human Resource Management Review, 15, 69–95. doi:10.1016/j.hrmr.2005.01.002
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Ley, D. (2007). Emerging Technologies for Learning: Ubiquitous Computing. British Educational Communications and Technology Agency, 2, 64–79. Lyytinen, K., & Yoo, Y. (2002). Issues and Challenges in Ubiquitous Computing. Communications of the ACM, 45(12), 62–96. doi:10.1145/585597.585616 Malone, T. W., Weill, P., Lai, R. K., D’Urso, V. T., Herman, G., Apel, T. G., & Woerner, S. (2006). Do Some Business Models Perform Better than Others? MIT Sloan Research Paper No. 4615-06. Available at SSRN: http://ssrn.com/ abstract=920667.
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Martins, L. L., Gilson, L. L., & Maynard, M. T. (2004). Virtual Teams: What do we know and where do we go from here? Journal of Management, 30. Pateli, A. G., & Giaglis, G. M. (2003). A framework For Understanding and Analysing e-Business Models. Proceedings of the 16th Bled eCommerce Conference, Bled, Slovenia. Roussos, G. (Ed.). (2006). Ubiquitous Computing for Electronic Business. In: Ubiquitous and Pervasive Commerce: New Frontiers for Electronic Business (pp. 1-12). New York, USA: Springer. Roussos, G., Gershman, A., & Kourouthanassis, P. (2003). Ubiquitous Commerce, Ubicomp 2003 Adjunct Proceedings, Seattle, WA, 12-15 October. Saha, D., & Mukherjee, A. (2003). Pervasive Computing: A Paradigm for the 21st Century. IEEE Computer, 36(3), 25–31. Satyanarayanan, M. (2001). Pervasive Computing: Vision and Challenges. IEEE PCM, August, 10-17. Vasilakos, A., & Pedrycz, W. (Eds.). (2006). Ambient Intelligence, Wireless Networking and Ubiquitous Computing. Artech House, ISBN 1-58053-963-7. Verburga, R.M., & Bosch-Sijtsema, P.M. (2007). The limits of virtual work. The Electronic Journal for Virtual Organizations and Networks, 9. Special Issue “The Limits of Virtual Work”, July.
KEY TERMS AND DEFINITIONS Ambient Intelligence (AmI): A vision of the future information society where intelligent interfaces enable people and devices to interact with each other and with the environment. It resembles pervasive or ubiquitous computing, but it emphasizes the system infrastructure’s autonomic learning capability and interaction mechanisms for users in particular social contexts. Business Model (BM): Description of company’s business processes and their interconnections. Business Process (BP): Logically connected tasks, procedures, activities, whose result is some planed product or service. Business Process Management (BPM): Concept or method of managing changes in business process reengineering. Context Awareness: The ability to use any piece of context information to contribute to the environmental situation of an entity (person, place, object), thus rendering human-machine interaction more personalized and efficient. Electronic Business (E-Business): Any business process that relies on an automated information system E-Business Model: Business model that leans on support and possibilities of internet technologies. Pervasive Computing (Ubiquitous Computing): Presence of communication and computing technologies everywhere around us in a way they are invisibly embedded in everyday objects and people are mostly unaware of their presence. The omnipresence of computer power and associated sensors and controls in daily life.
This work was previously published in Risk Assessment and Management in Pervasive Computing: Operational, Legal, Ethical, and Financial Perspectives, edited by Varuna Godara, pp. 155-168, copyright 2009 by Information Science Reference (an imprint of IGI Global).
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Chapter 1.14
Guidelines for Preparing Organizations in Developing Countries for Standards-Based B2B Lena Aggestam University of Skövde, Sweden Eva Söderström University of Skövde, Sweden
ABSTRACT B2B development has been faster in the developed world comparing to developing countries. This chapter proposes a “tool” for managing CSF in B2B settings. The tool is in the form of guidelines, which are concrete and detailed, and which enable a more clear view of actions needed during the preparation stage of B2B projects. We argue that developing countries seldom have the
luxury of affording failure in new B2B ventures, but that they instead must learn from the mistakes already made by the developed countries. Thus, our proposed guidelines are based on an existing framework and experiences made in the developed countries. The guidelines are furthermore discussed with regard to the specific problems and conditions that developing countries face. Much work still remains, and problems still must be resolved. From a global perspective, this is important for all of us!
DOI: 10.4018/978-1-60960-587-2.ch114
Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
Guidelines for Preparing Organizations in Developing Countries for Standards-Based B2B
INTRODUCTION It is no secret that electronic business between organizations (B2B) is constantly picking up speed and adoption throughout the world. B2B can be defined as the use of Internet and Webtechnologies for conducting interorganizational business transactions (Teo and Ranganathan, 2004). So far, its development has been faster in the developed world than in developing countries (Hawk, 2004; García-Murillo, 2004; Uzoka and Seleka, 2006). In the former, B2B is adopted and used for competitive and collaborative reasons to a larger extent than in developing countries. In particular, the developing world often lacks the infrastructural, economic and socio-political framework to develop e-commerce in comparison to the developed countries (Uzoka and Seleka, 2006). Furthermore, power distance must be considered, since it indicates the ability for organizations to affect change in government. The higher the distance, the faster industry – including e-commerce – can grow (Sparks et al, 2007). Through the use of B2B, companies in developing countries can create and sustain competitive advantage, get access to new and better suppliers and customers, etc (Wood, 2004). Proper attention to specific conditions of these countries can prevent negative effects and slow e-business adoption (García-Murillo, 2004). However, a successful B2B development project requires proper management of different types of Critical Success Factors (CSF). CSF are: “the conditions that need to be met to assure success of the system” (Poon and Wagner, 2001, p.395). CSFs can be categorised as emerging from economic, technological or organizational issues (Ewusi-Mensah and Przasnyski, 1994). Planning considerations should focus on important organizational factors, because they influence the other factors. Circumstances in the developing countries also reveal the importance of trying to resolve organizational factors such as confidence and trust in order to establish a corporate culture where the benefits
of sharing are viewed as important and natural. Leaders initiate this process by imposing his/ her beliefs, values, and assumptions, but culture only arises when the assumptions of individuals lead to shared experiences (Schein, 2004). Thus, developing a culture is a long-term process, and the importance of planning and preparation is clear. Currently, the lack of means for dealing with CSF is accentuated by the fact that many B2B projects fail. Additionally, specific conditions in developing countries such as capacity of organizations to absorb, use, and adapt advances in science and technology must be studied (Salman, 2004). Organizations in developing countries must prepare themselves well to avoid pitfalls and achieve the full benefits of B2B. This is no different compared to developed countries. The difference is that developing countries lack suitable resources for such preparations, with regard to poverty, and inadequacy and instability of various resources in developing countries (Agoulu, 1997; Roy and Biswas, 2007; Purcell and Toland, 2004), together with low B2B maturity. There are barriers to e-commerce such as: low income levels, low literacy rates, lack of payment systems that support online transactions, and cultural resistance to online transaction-making (Ho et al, 2005). Our work contributes to better preparatory routines in organizations in developing countries. This chapter proposes a “tool” for managing CSF in B2B settings. The tool is in the form of guidelines, which are concrete and detailed, and which enable a more clear view of actions needed during the preparation stage of B2B projects. The guidelines can be used during the planning stage of B2B in order to prepare the organization for managing CSF in this context. They are built on experiences in developed countries, and will hence enable organizations in developing countries to avoid redoing the same mistakes. The specific conditions of developing countries are taken into consideration by specific referencing when each guideline is discussed in terms of how they help to alleviate problems. The target audience is B2B
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project managers, since they are in charge of making the B2B venture happen.
BACKGROUND Collaboration is a necessity to survive in the business world regardless of geographical location. Developing countries should strive in this direction. In order to set the scene for the guidelines, we first give some background information on B2B, developing countries, and a framework for managing CSF. The guidelines are developed from these areas.
B2B B2B is defined as the use of Internet and Webtechnologies for conducting inter-organizational business transactions (Teo and Ranganathan, 2004). This section will introduce B2B, and elaborate on an implementation model used as the basis for the work presented in this chapter.
Introduction to B2B To a great extent, B2B is conducted using standards to simplify cooperation (Ersala et al, 2002; Hasselbring, 2000; Ghiladi, 2003). Standards are guidelines for how to structure and manage communication and information sent between organizations (Söderström, 2004). They enable a common language between partners, as well as automation of relevant business processes. However, the associated technology is often complex and expensive, which in itself can be an obstacle for developing countries to enter into world-wide B2B. One reason is that the standards used are flexible and general, and hence difficult to implement (Jakobs et al, 2001). It takes time and resources. Standards should therefore be used with as many partners as possible to be a justifiable option. This requires some economies of scale for quality (Motwani et al, 1999), and is in itself
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is a problem for small organizations, which may not have that many partners. Adopting B2B is a strategic choice, and partner relationships must be carefully managed (Thompson and Ranganathan, 2004).
B2B Standards Implementation Model As a point of origin in our analyzis, we use a model of the B2B standards implementation process developed by Söderström (2004). The three main phases are: preparation, architectural and consolidation. Preparation concerns activities for planning and preparing projects and architectural work. Architectural work concerns making changes to processes and technology to incorporate the standard into the existing infrastructure. Finally, consolidation concerns launching the standard, as well as evaluating and maintaining the system and expanding its use. Our focus is the preparation phase, since careful planning and proper management features are best determined therein. Preparation includes four sub-steps (Figure 1): strategic planning, process analysis, partner alignment, and project planning. The order between the steps is not necessarily the same at all times, and some activities may be conducted parallel (double-headed arrows). In brief, the four steps contain: 1. Strategic planning: Standards and B2B must be part of the business strategy, in order to identify how they can help achieve the business plan (Ramsey, 1998), create new markets, redefine old ones and enable Figure 1. Detailing of the preparation phase
Guidelines for Preparing Organizations in Developing Countries for Standards-Based B2B
inter-operability (Bolin, 2004). The lack of strategic vision is a major barrier to justifying IT investments (Love and Irani, 2004). Top management commitment is a necessity (Premkumar et al, 1994). Stakeholders from different organizational levels must be involved early to achieve implementation success. 2. Process analysis: Business processes must be analyzed in order to identify, prioritise and orchestrate which processes to include (Söderström, 2004), which enables a deeper understanding of the organization and its processes (Kosanke and Nell, 1999). Hence, business processes help define project scope regarding which processes to support (Ersala et al, 2002), and how and which part(s) of the organization that will be affected. 3. Partner alignment: B2B partners must identify with whom to trade (Intel, 2003; Söderström, 2004). Partners may have different levels of maturity, and hence varying experience in standards use. Agreements include what, where, how, and scope (WebMethods, 2003). Common goals must be set, responsibilities, time span and resources established, and a commitment given by each partner, for example through Trading Partner Agreements (TPA). 4. Project planning: Details about required technology, infrastructure, and project conduction are determined (RosettaNet 2001; Söderström, 2004). Results from previous phases are utilised in planning, with implementation goals, milestones and resources. Planning is the key to implementing IT (Ramsey, 1998). Agreements between project participants are important to resolve open issues and prepare execution options. This model is the most detailed implementation model of its kind for B2B. It is based on an extensive literature survey, as well as on empirical
material from standards developers, standards users and creators of standards-based software.
Developing Countries One basic difficulty compared to developed countries is the vast population and degree of illiteracy in developing countries. The developed world consists of 20% of the world’s population of which 96% are literate, while 30% of the remaining population in the developing countries still are illiterate (Agoulu, 1997; Hawk, 2004). Developing countries also suffer from poverty, as well as inadequacy and instability of various resources (Agoulu, 1997; Roy and Biswas, 2007; Purcell and Toland, 2004). In a literate world, information is a basic resource that is spread with high speed. In a population where illiteracy is vast, traditional practices remain (Agoulu, 1997; Goodman, 1991). The lack of new technology and an appropriate good infrastructure for communication and information spreading in developing countries is also evident (Agoulu, 1997; Sadowsky, 1993; Singh and Gilchrist, 2002; Purcell and Toland, 2004; Tan et al, 2007). The consequences are effects on if and how e-business is regarded and practiced. Therefore, many developing countries still struggle with basic technology functions, while developed countries can use their infrastructure to address more advanced challenges (Singh and Gilchrist, 2002). Internet use is fairly evident in developed countries, but is far more uncommon in developing nations (Uzoka and Seleka, 2006). An ITU study (Ho et al, 2005) has shown that 11,8% of the world’s population has Internet access. It should be noted, however, that increased Internet use in developing countries does not automatically mean an increase in e-commerce adoption, even if this is the case in developed countries (Sparks et al, 2007). In the latter, e-commerce is more well spread and advanced (Hawk, 2004; García-Murillo, 2004; Uzoka and Seleka, 2006). One potential reason is that even though Internet
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use can be widespread, e-commerce activities are sometimes not as popular (see for example Meskaran & Ghazali on e-commerce in Iran). Empirical evidence also still lag behind theoretical developments (Kshetri, 2007). One contributing factor behind this may be that more basic needs such as food and clean water are of a more primary concern than investments in new technologies. Sharing information between companies and partners in B2B is essential. However, this requires a culture in which the benefits of sharing over protecting assets are important and natural. Such a culture does not exist to the same extent in developing countries compared to in developed ones (Jennex et al, 2004). Still, developing countries may have at least one advantage compared to developed countries, in that they do not have the broad availability of different mechanisms for delivering goods and services. This availability may reduce the benefits of electronic networks, Developing countries can hence get higher payoff faster (Sadowsky, 1993). Table 1 presents an overview of the problems mentioned concerning developing countries and e-business. Each problem has been given an identifier, which will be referenced when discussing the guidelines. Firstly, many people are not aware
of what information can do for them, and what they can use it for. Since information in developed countries is the “nerve” of society, this problem must be addressed. A related aspect is that oral culture still dominates these countries, making written communication something for the “elite”. Face-to-face commerce is also preferred in many countries, such as India. Incorporating electronic meetings and trading into traditional culture and traditions therefore faces great challenges. Neither should replace the other, but consideration must be taken to the conditions and culture of the specific countries. A proper infrastructure for conducting and reaching B2B benefits is essential. Infrastructure not only refers to technology, even if this is important, but also to financial infrastructure, and access to the adequate infrastructure. All perspectives are needed. It also places requirements on the knowledge and skills required for the population, both in terms of the people working with the B2B systems, and the customers that are to use them. It also concerns lack of management knowledge, which is needed for B2B success. The management level concerns company-internal management, as well as government/national management. In the latter, the legal system must
Table 1. Problems for developing countries related to e-business Problem
Reference
People are often unaware of the need for information, and do not exploit information as much as they could (A)
Agoulu, 1997
Oral culture dominates, written communication is “elitistic”, and commerce is preferred face-to-face (B)
Agoulu, 1997; Hawk, 2004; Mwangi, 2006; Kshetri, 2007
Lack of proper infrastructure, both technical, financial and access to (C)
Hawk, 2004; Sadowsky, 1993; Singh and Gilchrist, 2002; Purcell and Toland, 2004; Uzoka and Seleka, 2006; Kshetri, 2007; Sparks et al, 2007;
Lack of qualifications, in staff as well as customers (D)
Hawk, 2004; Sadowsky, 1993; Jennex et al, 2004; Singh and Gilchrist, 2002
Lack of an advanced legal system (E)
Hawk, 2004; Uzoka and Seleka, 2006; Mwangi, 2006; Kshetri, 2007; Sparks et al, 2007
Security and trust issues are not resolved (F)
Jennex et al, 2004; Uzoka and Seleka, 2006; Meskaran & Ghazali, 2007
Unsure quality in products, and unstable markets (G)
Motwani et al, 1999; Wood, 2004; Uzoka and Seleka, 2006
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be evolved to enable handling of new situations due to B2B. Trust is an essential aspect of collaborations, and an important part of the culture needed for successful B2B. Lack of trust and doubts about security are problems that all countries face. However, developing countries do not have as many mechanisms and cultural features in place as developed countries do. Meskaran and Ghazali (2007) claim most developing countries have a collectivistic culture, in which the level of trust is lower than for those countries in which individualistic culture dominates. An understanding of culture helps to develop more suitable strategies to improve trust. Lastly, several literature sources mention that the developed world has doubts concerning the quality of products and the stability of markets in developing countries. Some doubts may origin simply in inexperience in trading with these countries, others from different quality control systems, etc. These problems are not exclusive to, and may not be of the same dignity in all developing countries. Still, they must be addressed. Our work concerns how companies and organizations can better prepare themselves for standards-based B2B. Since developing countries are our centre of attention, we will return to discussing how our suggestions and guidelines help alleviating and/ or reduce these problems later on in the chapter.
users and let them understand what the project is about, how it is going to affect them etc. This contributes to trust, which must be encouraged in particular in developing countries.
The Framework for Managing Critical Success Factors
The System’s Boundary This factor concerns business borders, and not technical ones. Knowing what the system is and defining its boundary is a prerequisite for addressing all success factors and a performing a successful B2B implementation. The system’s boundary constrains what needs to be considered and what can be left outside (van Gigch, 1991). Identifying the boundary triggers an active discussion about what the actual system includes, which related systems and subsystems there are, etc. Related systems may also offer resources in exchange for something.
The framework is developed on a generic level in order to fit all kinds of information systems (IS) development. It is based on organizational success factors and should be used during planning to prepare an organization for a project. We choose this framework since B2B systems are IS, and since this framework, to the best of our knowledge, is the only one focusing on CSF from a preparation point of view. Furthermore, a cornerstone in the framework is to motivate the
Critical Success Factors The Framework Base CSFs are conditions that must be met to avoid failure. The analysis of the factors emerging from organizational issues shows four different CSF (Aggestam, 2004): • • • •
To learn from failed projects To define the system’s boundary, both for the whole system and for relevant subsystems To have a well defined and accepted objective that aligns with the business objectives To involve, motivate and prepare the “right” stakeholders.
The factor To learn from failed projects is a prerequisite whether an organisation is to better perform projects as for example a B2B. Thus, the framework does not explicit need to take this into consideration. Furthermore, for less developed countries it is important to avoid redoing the mistakes already made by the developed counterparts. The reminder of this chapter will elaborate on each of the three remaining CSF.
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The Stakeholders Organizational change is risky, but risk can be minimised by having the right kind of persons on your team (Champy 1997), and to identify important stakeholders and discover their requirements (Kotonya and Sommerville 1997). How well an IS will work in an enterprise depends on the user involvement in the development process (Cherry and Macredie, 1999; Pohl, 1998; Sutcliffe, Economou and Markis, 1999; Saiedian and Dale, 2000; Browne and Ramesh, 2002). The success of the involvement depends on how well people work and communicate (Saiedian and Dale 2000), and communication gaps do exist. According to Champy (1997) stakeholders across the organization have two needs during organizational change: Confidence in the management and knowledge about the meaning of the change. Commitment from the top is crucial if the project affects a large part of the organization (Milis and Mercken, 2002). Strong sponsorship is required even before a project is launched to it being initiated and seeded resources (Poon and Wagner, 2000), and confidence in the management is essential (Proccacino et al, 2001). The Objective A successful IS should meet common business objectives (Ewusi-Mensah and Przasnyski 1994, Milis and Mercken 2002). When the IS strategy reflects organizational objectives, supports business strategies, recognizes external forces and
reflects resource constraints, then the organization more likely uses IS strategically (Kearns and Leder 2000). Defining the goal is fundamental (Clavadetcher 1998) and organizational change must begin here (Champy, 1997). A comprehensive project definition gives a common vision, a cooperation base, terms of reference and prevents boundaries from extending beyond intended limits (Milis and Mercken 2002). An organization should be examined from different perspectives (Pun 2001) which in turn is a prerequisite for defining the goal. We use Bolman and Deal’s (1997) four complementary views/frames (Table 1), but complement them with a fifth frame – Neutral – in order to capture the neutral perspective of the organization in terms of mission (service or manufacture), business plan, size (both turnover and number of employees), ownership (private or public) and so on. The frames are summarised in Table 2. The Neutral frame can be thought of as a starting point for the other frames, because facts from this frame limits an organization and consequently organizational change, and it also limits and influences the other frames. Also the Structural frame focuses on explicit facts about the organization as e.g. rules and policies. The Human resource, Political and Symbolic frames, on the other hand, help to understand and gain knowledge about the organizational culture which is an important influence factors regarding if the B2B project will be a success or not.
Table 2. Overview of the four-frame model, adapted from Bolman and Deal (1997) Structural frame
Human resource frame
Political frame
Symbolic frame
Metaphor for organizations
Factory or machine
Family
Jungle
Carnival, temple, theatre
Central concepts
Rules, roles, goals, policies, technology, environment
Needs, skills, relationship
Power, conflict, competition, organizational politics
Culture, meaning, metaphor, ritual, ceremony, stories, heroes
Image of leadership
Social architecture
Empowerment
Advocacy
Inspiration
Basic leadership challenge
Attune structure to task, technology, environment
Align organizational and human needs
Develop agenda and power base
Create faith, beauty, meaning
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The way an objective will be defined and formulated depends on the level of inquiry at which it has been considered (van Gigch 1991, Beyer and Holtzblatt 1998, Leffingwell and Widrig 2000). Discussions about objectives, often only take place at the action level and/or what-to-do level, but according to van Gigch (1991) all three levels (why, what and how) are necessary. This is in accordance with Bubenko (1993) who claims that the HOW part should be linked to the WHY and WHAT parts. The framework based on the presented organizational factors is presented in next section. The Framework for Managing CSF We argue that preparation based on organizational factors is necessary to increase the chances of success when organizations in developing countries engage in B2B projects. To the best of our knowledge, no other framework takes this point of view. The framework, see Figure 2, stresses a flexible outset adaptable according to stakeholder type, and should be used in planning to prepare the organization for managing CSF in future activities. The framework should also be used iteratively on different levels of abstraction: first to the whole project (“the system”) and then to identified criti-
cal parts (“subsystems”). However, we will use a sequential order in this chapter for simplicity. The target organization should define the system’s boundary and relevant subsystems. Next, the objective must be defined, and relevant stakeholders identified. The objective should be analyzed and described from different complementary frames and at different levels of detail. It should always support the business objective, which requires IS- and business strategies to be clearly aligned. The goal descriptions can be thought of as a tool box aiming to be used in the motivation process. Relevant stakeholders should be motivated and prepared for future participation and involvement in the ISD process. User participation refers to user activities, while user involvement is more a subjective psychological state of individuals. Stakeholder groups are probably a mix of the two. Both motivation and preparation must thus be adapted to the various types of stakeholders. The motivation process should focus on stakeholder knowledge and confidence needs. They feel confident and motivated by a a description of the objective that is adapted to them and explained in a way that they understand how it will affect them and why the project is important. The
Figure 2. A framework to support the information systems development process
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most suitable stakeholder description should be chosen, which could mean more than one description. User participation and user involvement is a communication process. The preparation process should thus focus on educating stakeholders about concepts to make future communication easier and more effective. These processes aim to meet stakeholder needs about confidence and knowledge about changes. This will contribute to positive, motivated and prepared stakeholders, a prerequisite for user involvement and participation, and consequently for reaching user satisfaction with the system. Using the framework results in a clear, well defined and accepted objective, and in positive, motivated and prepared stakeholders which is critical for all types of projects, including a B2B-project.
MAPPING THE CSF FRAMEWORK TO THE B2B SETTING The mapping of the CSF framework to B2B originates from the descriptions of the implementation phases with the intention to identify matches between them and the framework. Since
the framework is based on organizational CSF and has a planning and preparion view, the main matches are found in the three sub-steps: strategic planning, process analysis, and partner alignment (see Table 3). The leftmost column presents the four implementation phases, the middle column includes a brief description of key points therein, and the rightmost column includes comments of in what way the framework can assist in preparing for B2B implementation planning. Starting with strategic planning, the two central issues are: the need for an updated business strategy, and the inclusion of relevant stakeholders. The strategy determines where the organization is heading and which operations matters, and the standards-based solution must be duly incorporated. The framework emphasizes the important why-perspective by stressing the necessity of clear and accepted goals. Commitment from top management is another central building block. This is where strategy is determined and operations are set towards meeting goals. The framework also emphasizes the identification of critical parts such as departments, partners, systems, work groups, processes etc. and their alignment between and to the goals. If the strategic perspective is not
Table 3. Relating B2B standards implementation preparation to Aggestam’s (2004) framework Description
Framework
Strategic planning
Phases
An updated business strategy is essential when implementing B2B standards. As many relevant stakeholder as possible should be involved early on.
It is essential to have a clear and accepted goal, supporting the why perspective. Strengthens the need to identify critical departments, partners, work groups, systems etc. Emphasises relations and alignment between goals, included stakeholders, and identified sub-systems.
Process analysis
Identifying what (parts of) business processes.
The goal and systems boundaries are tightly coupled, and presuppose one another. Contributes to identify important sub-systems/parts of the organization and enhance where to focus.
Partner alignment
The common goal needs to be agreed on and committed to. Responsibility and resource commitment must be agreed upon. To identify requirements placed on each partner
The goal and system boundaries need to be identified. Contributes to identify relevant issues to resolve between partners. Contributes to achieving well accepted goals.
Project planning
Make a detailed plan based on the results from the previous phases.
Is not explicitly managed within the framework, but results from previous phases can be utilized as a basis for project planning.
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clear, the strategy or what is included in the parts must be revised. Identifying critical parts and their relationships includes delimiting the IS by clearly identifying and stating systems boundaries, the whole system and critical sub systems, and to include relevant stakeholders in its preparation. In the implementation model, a crossfunctional/cross-organizational, implementation team is suggested which should co-operate for goal realisation and to conduct B2B implementation. In process analysis, the most essential point is to identify what to include in the B2B venture, in terms of processes, systems and organizational entities. Organizations should analyze their processes to define the scope of projects, and to identify processes that need support. The iterative element in the framework enhances identification of the focus by allowing each goal and subsystem to be “the system”, and use that to identify relevant subsystems in the form of processes, partners, work groups etc. Boundary identification is included in order to set clear goals and delimitations. The tight coupling between goals and boundaries mean that goal definition helps to define systems boundaries as well. The goals are agreed upon by involved stakeholders. In this process, another positive effect may also be a clarification of which partners and actors there are to include. Partner negotiations (or partner alignment) are essential to establish what to do, why, by whom, with what means, and when. Clear responsibilities make better ground for project success. Besides the mentioned focus on goals and system boundaries, using the framework contributes to identify issues that partners need to resolve as well as who has the main responsibility for doing so. Results are agreements on e.g. common and well accepted goals and work distribution, raising the likelihood of success. The project planning phase does not deal directly with the framework, but framework use aims for a more “correct” project planning. Previous phases form the basis for the activities in project
planning. In particular, preparations made in the three phases aim to facilitate and enable mutual agreements between all project participants. The framework does not deal with economic or technological issues, but on organizational ones. However, since organizational issues affect the other two, they are implicitly part of the framework. For example, it is important to know which business processes to include to be able to establish needed economic and technological resources. Our previous work has resulted in generic guidelines (Aggestam and Söderström, 2006). These will be developed into more concrete ones in the coming sections. The three most relevant phases of the B2B standards preparation stage, Strategic planning, Process analysis and Partner alignment, will be used as the main structure. Sub-sections are created for each main aim with a summarizing table. Each table provides the existing generic guideline to the left, and specific guidelines to the right. Problems in developing countries will be discussed. The identifier of each problem (Table 1) is referenced in the discussion.
CONCRETE GUIDELINES FOR STRATEGIC PLANNING Based on the mapping (Table 4) three aims can be identified explaining why the framework is useful in B2B standards implementation concerning strategic planning: • • •
To achieve clear and accepted goals in relation to an updated business strategy To identify critical parts as departments, stakeholders etc To explicitly define how these critical parts relate to one another and to the goals and the strategy.
For each of these aims, we will elaborate on a more generic level on what to do in order to reach them (Aggestam and Söderström, 2006).
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Table 4. Guidelines to achieve clear and accepted goals in relation to an updated business strategy Guidelines
Detailed guidelines
Discuss from different views how the goals of the standards implementation project are useful in helping the organization to achieve its general business goals (G-1)
The goals of B2B should be described from the following frames using a why-perspective: - Neutral: increase the number of standards-based B2B transactions with more partners, to increase the chances of reaching e-business benefits - Structural: identify and describe how the organization needs to change when implementing B2B, in terms of technology, rules, structure, management, etc., to ensure a suitable infrastructure - Symbolic: plan a launch event to contribute to incorporating B2B into the corporate culture - Political: describe how staff at different levels are affected by the changes, and how to achieve collaboration, to get everyone in the organization to work towards a common goal - Human resources: describe what competences that need to be developed to ensure sufficient knowledge on all organizational levels, to ensure that the benefits of B2B are reached
If necessary, review the existing strategy and reformulate the strategy to incorporate the use of standards as a strategic tool (G-2)
Incorporate text on (B2B) standards and their usefulness into the business strategy, to motivate management Define a process for how the strategy and standards perspective therein can be updated on a regular basis.
The generic guidelines are then concretized into more detailed ones, with a specific reference to developing countries and how help them alleviate their specific problems. It should be noted that strategic planning concerns work conducted internally in an organization.
To Achieve and Describe Goals in Relation to an Updated Business Strategy The guidelines are summarised in Table 3. When describing the goals of a B2B project in relation to an updated business strategy, different perspectives are needed. The framework for preparation (Figure 2) makes a clear contribution by emphasising the five frames. The B2B goals should be described in each frame including a whyperspective, as illustrated in Figure 2. Developing countries currently have a low e-business rate, and therefore benefit naturally from all frames since they contribute to creating a culture for sharing and conducting e-business. This takes time, and must be initiated early on. Developing countries may have the advantage of not having to battle already existing cultures. The detailed guidelines thereby address the problems A, B, C, D and F: They clarify the meaning of information, raise
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the competence level and make written communication accessible for more people, contribute to increase the willingness to share, contribute to creating a clear infrastructure on several levels, emphasise education, and by conducting B2B with known partner, they increase the likelihood of partners trusting the transactions made. It is also important to review and revise the existing business strategy to align it better with the B2B intents. The detailed guidelines thereby address the problems C and G by incorporating standards in the business strategy, the number of automated transactions can increase. Standards are then managed more systematically and transactions are consistent, which potentially raises their quality. Standards are made part of the corporate culture, contributing to the change of perspective.
To Identify Critical Parts where the Initial Anchoring Work should Start The first generic guideline in this aim concerns the identification of bottle-necks. These, such as the lack of competence regarding B2B standards, can be identified from the goal descriptions and systems boundaries. By comparing them with the general problems (Table 1), priorities can be made of the importance of the problems. The detailed
Guidelines for Preparing Organizations in Developing Countries for Standards-Based B2B
Table 5. Guidelines to identify critical parts where the initial work should start Guidelines
Detailed guidelines
Analyze the goal descriptions to discover potential “bottle-necks”, in terms of people, organizations or systems (G-3)
Identify where the bottle-necks are, both from general problems, and from the company’s specific conditions, to increase the chances of reaching the goals and to remove unnecessary obstacles Prioritise the problems based on their importance and consequences, to ensure that the limited resources are directed towards the most important actions
Plan explicit actions to ensure the inclusion and motivation of “bottle-necks” residing inside the organization (G-4)
Based on the priorities create an action list, a time plan and responsibility assignments, to ensure that actions are made in a reasonable timeframe, and to enable follow-up actions. An example is to plan education activities in, for example, Internet technology
Use the adapted goal descriptions in order to motivate critical stakeholders (G-5)
Use the goal descriptions in activities such as education, meetings, launch events, etc., to motivate relevant stakeholders on different organizational levels
guidelines (Table 5) thereby address the problem A: since it makes people aware of the meaning and importance of information. The problem priority list (what to do) can assist in the creation of an action list (how to do) for removing obstacles, which must be accompanied by a time plan and the assignment of responsibilities. The detailed guidelines thereby address the problems A, B and D since they contribute to raising the awareness of the importance of information and planning. For example, responsibilities must be assigned to ensure the completion of tasks. Furthermore, the staff competence level is raised, and the oral culture is affected in a longterm perspective. In all activities planned based on the priorities, the goals must be explained to the stakeholders in such a way so that they firstly, understand the project, and secondly, how the project affects them. This results in the stakeholders trusting the efforts and the management. The detailed guidelines thereby address the problems A and C since
they make the needs explicit, and give access to information and an infrastructure.
To Explicitly Define Relations Between Goals, the Strategy, Stakeholders, etc. The second and third aims are similar, since both concern why B2B is an important effort, and how things relate. While the second concerns bottlenecks, this aim concerns the relationships between goals, strategies and stakeholders. The generic guideline (Table 6) is focused on relationships, both in terms of identification and awareness. Written documents and oral meetings are needed in all situations. In developing countries, however, the oral tradition is – as mentioned – prevailing, and written communication is elitistic. By face-toface discussions, people can participate regardless of their reading skills, which contributes to trust and inclusion. The detailed guidelines thereby address the problems A, B and C: They show the importance
Table 6. Guidelines to explicitly define relations between critical parts Guidelines Use goal descriptions and discussion seminars to identify relations between goals and raise the awareness of the same (G-6)
Detailed guidelines The project leader reviews the goal descriptions and makes a draft describing goal relations, to provide a basis for discussion Organise at least one seminar with relevant stakeholders to model and discuss around the goals, to get a common view of goals, to find what goals affect what other goals and how, and to identify what stakeholders affect/are affected by the goals
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of written information as a point of origin, create an awareness of the importance of a common view and to share information to achieve this. However, discussions are grounded in the oral tradition and residing culture, which should increase the chance of identifying and anchoring goals. Furthermore, the guidelines provide a clear view of goal relations, which increases the chances of developing a good infrastructure that is accessible to the right users.
CONCRETE GUIDELINES FOR PROCESS ANALYSIS Based on the mapping (Table 2) three aims can be identified explaining why the framework is useful in B2B standards implementation concerning process analysis: • •
•
To have a clear view of the organization’s business processes To identify what business processes to include, and to motivate and prepare relevant stakeholders To identify what systems that support the business process
These aims are derived from the tight coupling needed between goal and system boundaries, and
from the identification of what processes and other sub-parts on which to focus. Similarly to the former section, we elaborate on a more generic level on what to do in order to reach the aims and concretize them into more detailed actions. It should be noted that process analysis concerns work conducted internally in an organization.
To have a Clear View of the Organization’s Business Processes In B2B standards implementation, different business processes are included, such as: procurement, order, invoice and payment (Söderström and Pettersson, 2003). To have a clear view of which these processes are, and which of them that are the most relevant for the future project is important. Guidance is provided by the results from the strategic planning phase in terms of e.g. bottle-necks. The initial step is to map the situation “today” (AS-IS), which is done by studying documents and existing models, talking to relevant people, observe the work, and then construct up-to-date models (see Table 7). These guidelines address the problems B and F: they use the oral culture to extract information and lay the foundation for a solid written documentation (Agoulu, 1997). They can also assist in removing prejudices and assumptions, and
Table 7. Guidelines to enhance a clear view of the business processes Guidelines
Detailed guidelines
Model the business processes according to the current situation (AS-IS) (G-7)
Study existing documents of for example work and process descriptions, to establish a basis for AS-IS process models Speak to different stakeholders on different levels, to obtain their view and a more up-to-date perspective on how the work actually is conducted If possible, participate in and observe the work done Use the results to create process models, preferably through joint discussions, to get a basis for discussion with relevant stakeholder groups
Model the business processes according to the desired future situation (TO-BE) (G-8)
Identify how the organization and work should be structured by originating from existing process models, identified bottle-necks, and documentation from strategic planning, to establish an up-to-date process view Develop new process models, preferably via discussions, to document the process view Anchor the models in all levels of the organization, to ensure commitment
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thereby increase the trust in co-workers and their ways of working. The results from the AS-IS-modeling should be mapped to the goal descriptions from strategic planning in order to identify the desired future (TO-BE). Here as well, a combination of written documentation and oral discussions should be used as a basis. Note that it is essential to disseminate the TO-BE models to everyone involved, for commitment purposes. The detailed guidelines thereby address the problems C and D: They contribute to increasing the modeling skills of the staff, and since they utilize a combination of oral and written information to disseminate information and ensure commitment. Discussions during development and anchoring of the models can be conducted orally, while the end product can be shared in a written format.
To Identify what Business Processes to Include, and to Motivate and Prepare Relevant Stakeholders From the identification of relevant processes, this aim is focused on which processes to include in the B2B venture (see Table 8). This is essential, by removing irrelevant or low-priority processes, and focusing on the right ones. In developed countries, many projects have failed because not proper attention has been paid to the right processes, i.e. on prioritized processes. Furthermore, most
organizations do not learn from their failures; but make the same mistakes over and over again (Ewusi-Mensah and Przasnyski, 1995, Lyytinen and Robey, 1999). This is one mistake developing countries can avoid by doing it right from the beginning. The detailed guidelines thereby address the problem G: they secure quality in a long-term perspective since the business processes and goals are audited and defined more clearly. Motivational actions of different kinds are also important to enable trust and a common purpose among the people involved in the prioritized processes. In terms of the framework, the symbolic perspective comes into play here, since it is not enough to simply distribute written information or just to inform. Some levels of emotions must be included. The detailed guidelines thereby address the problems A and B: They contribute to create awareness of the importance of information, and to creating a common culture with a focus on sharing information and data.
To Identify what Systems that Support the Business Process The guidelines is summarised in Table 9. Besides processes, it is also relevant to identify which systems that are critical, based on the priorities made. Do we need to make any IS/IT investments or do we have what we need? Are our systems in accordance with the strategy? If this work identifies
Table 8. Guidelines to identify what processes to include and to motivate and prepare relevant stakeholders Guidelines
Detailed guidelines
Identify, list and prioritise processes to include in B2B by pairing each goal description with the TO-BE process models (G-9)
Use goal descriptions and identify all processes mentioned therein, to obtain a goal perspective Map the results to the TO-BE models to ensure that the rights relations and processes have been identified Compare the matching results to the priority list, to ensure that efforts are made in the rights areas and in the right order
Take specific actions must to motivate the personnel involved in the selected processes to participate in the project (G-10)
Use the results and identify what staff to involve, to ensure that all relevant staff will be involved in the project Plan events to inform, discuss and commonly plan what to do next, to ensure that everyone feels involved, and to incorporate the project into the corporate culture
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Table 9. Guideline to identify supporting systems Guidelines Identify what IT systems that support the business processes and list relevant systems (G-11)
Detailed guidelines Use the revised list of processes and identify what parts of the organization that is affected, to ensure that the most critical processes are included Identify what IT-systems that are used in these organizational parts Discuss if the organizational parts that lack IT-support can be made more efficient by implementing systems
a need for investments, it is really important that this is aligned to all relevant strategies, including the IT/IS strategy. The activities needed are the same as for identifying and listing processes. In developing countries, the lack of a proper infrastructure, of for example a technical nature, is clear (Kshetri, 2007). This may seem to be a problem, but it can be an advantage. Since there are only a few legacy systems, little effort is needed to integrate new systems with old ones, and there is instead a chance for the companies to start fresh. It is hence possible to learn from mistakes and experiences in developed countries, and our guidelines are one way to do so. The detailed guideline thereby address the problem A, C and F: They provide greater opportunities in managing and using information, provide a more stringent and clear infrastructure to enable e-business, and the overview of the IT systems can be used to identify potential security problems.
CONCRETE GUIDELINES FOR PARTNER ALIGNMENT Based on the mapping (Table 2) three aims can be identified explaining why the framework is useful in B2B standards implementation concerning partner alignment: • • •
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To establish partner readiness To establish legal contracts To form cross-organizational teams
These aims are derived from the need to resolve important issues between partners, and preparing for a successful project. Similarly to the former sections, we elaborate on a more generic level on what to do in order to reach the aims and concretize them into more detailed actions. It should be noted that partner alignment concerns external work between organizations.
To Establish Partner Readiness Partner alignment is all activities involving more than one organization. Basically, it concerns a lot of rework, but this time with the external perspective in mind (see Table 10). Readiness refers to organizations’ awareness of what they become involved in, what human and technological resources it will require, as well as how much time it will demand. Common project goals should be established in joint meetings, where negotiations take place based on internally relevant goals. The detailed guidelines thereby address the problems A, B and D: They concern a better understanding and use of common documents, participating representatives enhance their respective knowledge, and face-to-face meetings are the basis for creating a sense of commonality and acceptance of the ways of working of others. Based on the common goals, the contributions of each partner in terms of resources, competences, activities, etc. must be clarified. Followingly, mutual agreements on responsibilities are necessary. The detailed guidelines thereby address the problem B: they contribute to strengthen the sense of commonality and the corporate culture
Guidelines for Preparing Organizations in Developing Countries for Standards-Based B2B
Table 10. Guidelines to establish partner readiness Guidelines
Detailed guidelines
Establish common B2B project goals in a meeting with all partners (G-12)
Discuss what goals the company has with B2B, and develop a dictionary of central concepts and definitions, to be well prepared for common discussions Negotiate on what common goals the B2B project should have based on the separate corporate goals, to establish common grounds
Identify what the project will require from each partner in terms of preparation and work (G-13)
Define what resources and competences that each partner should contribute to the project, what activities to perform and when, and what responsibility assignments to have, to ensure commitment and successful project completion
Establish readiness by matching requirements and internal preparations (G-14)
Based on the mutually established grounds, each partner should review and plan internal project preparations
of collaborating across borders. Lastly, requirements should be matched against conducted internal preparations, to establish what remains to be done to enable the external connection. Possible actions should be planned to address shortcomings. The detailed guidelines thereby address the problem B: they contribute to strengthen the corporate culture of collaborating across borders. Lastly, requirements should be matched against internal preparations, to establish what remains to be done to enable the external connection. Possible actions should be planned to address shortcomings. The detailed guidelines thereby address the problem B: they contribute to strengthen the corporate culture of collaborating across borders.
To Establish Legal Contracts All legal issues need to be resolved by involving legal expertise to draw up the contracts (see Table 11). If “skeleton agreements” exist within an industry, or if standards exist on either a national or an international level, these should be used. This issue highlights the need for a legal system nationwide that takes B2B collaborations into account.
The detailed guideline thereby addresses the problem E by ensuring a correct and legally valid collaboration effort.
To Form Cross-Organizational Teams In the case of cross-organizational teams, stakeholder identification helps facilitate the management of organizational relationships in standards implementation, and the joint teams enable orchestration of implementation activities (see Table 12). The previously developed priority list can facilitate the task. The partners should jointly establish what competences that are needed in the project, using the readiness assessments. If one or more such competences are missing, actions must be taken. The detailed guidelines thereby address the problem B: by maintaining the culture of meeting face-to-face, and by stimulating written culture through the documentation work. Based on the agreements on needed competences, a project team is established with representatives from each partner. The written agreement is crucial in this step, not the least to ensure that the legal agreements (contracts) with the
Table 11. Guideline to establish legal contacts Guideline Establish connections between legal expertises to draw up contracts (G-15)
Detailed guideline Use existing attorneys or legal connections to discuss the B2B project, to establish solid contracts and secure the conditions for the own company
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Table 12. Guidelines to form cross-organizational teams Guidelines
Detailed guidelines
Agree on the team structure and boundaries in terms of number of people, skills required, mandate, resource requirements, etc (G-16)
Document what competences that are needed to succeed with B2B based on the previous agreements, to establish a suitable project organization
Assign appropriate team members based on internal preparations in other phases (G-17)
Internally identify and assign suitable persons to the project, based on contracts and agreements, and create jointly a written agreement on the commitment of each partner, to ensure a successful project result
respective commitments are followed and obtained. The detailed guidelines thereby address the problem B by here as well maintaining the culture of meeting face-to-face, and by stimulating written culture through the documentation work.
CONCLUDING REMARKS Preparation is always important in organizational development projects. Developing countries seldom have the luxury to afford failure in new ventures like in business-to-business. Thus, they should have the possibility to learn from developed countries and hence not redo mistakes already committed by developed countries. By careful preparation, the risk of failure can be reduced, and our guidelines are one approach to use. They aim to prepare the organization from the perspective of CSF, and provide means for dealing with these in B2B. All organizations and nations must prepare themselves well to achieve B2B benefits and gains. Still, our guidelines can help developing countries in particular, since project managers (our target audience) can practically implement them because they: 1. Are based on actual experiences in developed countries 2. Have been developed from factors of critical importance
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3. Are technology-neutral and can hence be used in planning regardless of infrastructural platform used 4. Can be directly implemented in ongoing projects 5. Can be easily adjusted to all types of preparatory/planning projects in B2B 6. Can help organizations to achieve a longterm e-business perspective and increased maturity to perform B2B projects The guidelines are based on an existing framework for ISD, and are therefore in themselves also proof of that existing tools and methods for ISD can be useful in B2B development. The literature on developing countries also shows that the guidelines are suitable to the existing culture in these countries since issues such as the willingness to adopt Internet technologies (Kshetri, 2007), and the collectivistic culture which includes low trust levels, (Meskaran & Ghazali, 2007), can be Table 13. Problems in developing countries versus the guidelines Problem
Guidelines
A
G-1, G-3, G-4, G-5, G-6, G-10, G-11, G-12
B
G-1, G-4, G-6, G-7, G-10, G-12, G-13, G-14, G-16, G-17
C
G-1, G-2, G-5, G-6, G-8, G-11
D
G-1, G-4, G-8, G-12
E
G-15
F
G-1, G-7, G-11
G
G-2, G-9
Guidelines for Preparing Organizations in Developing Countries for Standards-Based B2B
addressed. This is necessary to get commitment to the B2B project, and in developing countries in particular in order to raise the maturity of written communication, and to resolve security and trust issues. In the guidelines, specific references have been made to problems (Table 1) that are particularly important or present in developing countries. Table summarize these references. All problems are addressed to some extent, showing fit of the guidelines to alleviate problems such as lack of proper infrastructure, qualifications and advanced legal systems. The latter (see e.g. Hawk, 2004) can, in a way, be used as an advantage, since developing countries can “start over” and create a suitable and updated legislation to begin with. We therefore argue that the proposed guidelines are one way to give developing countries a real chance to come closer to the developed countries in terms of B2B maturity and increased electronic business use. It should be noted that the guidelines proposed are not explicitly connected to processes, phases or steps in relation to time. The motivation is that firstly, they vary between projects, and secondly, they must be adaptable according to for example project and company size, and maturity level. As experience grows, the time required for each step is also likely to be reduced. Future work will need to address the weaknesses of our guidelines. These include firstly that they are focused on organizational aspects. Complementary methods and/or guidelines must therefore be developed to cover for example economical and technical aspects. Secondly, the guidelines lack elements for measuring the effects. In a long-term perspective this is a difficult issue to resolve. The Neutral frame does provide valuable contributions to measuring, and potential measuring points include the number of B2B transactions, changes in strategies, number of agreements, and B2B partners. The measuring should be performed before preparation as well as during and after the project, after for example 6 months, and after 1 year.
Finally, we can conclude that the proposed guidelines enable the developing countries to climb on the B2B maturity staircase, even though using the guidelines will not take them to the top. There is still work to be done and further problems to be solved. With the words of Becker (2007, p.233): “Under the right conditions, entrepreneurs in developing nations can launch locally viable Internet ventures with real value, but many developing nations also face very real constraints in harnessing the Internet economy.” In our global world, all countries irrespectively of financial status or literacy degree have a contribution to make on the “e-scene”. We hope our work will encourage others to address the issues of developing countries and their e-commerce/B2B adoption. Empirical evidence must be gathered, guidelines be tested, and efforts made to reduce the gap between the developed and developing worlds. From a global perspective, this is important for all of us!
REFERENCES Aggestam, L. (2004). A Framework for supporting the preparation of ISD. Proceedings of the Doctoral Consortium, held in conjunction with the Conference on Advanced Information Systems Engineering (CAiSE’04). Aggestam, L. & Söderström, E. (2006). Managing Critical Success Factors in a B2B Setting. IADIS International Journal on WWW/Internet, Vol.4, No.1, 96-110. Aguolu, I. (1997). Accessibility of information: a myth for developing countries? New Library World, 98(1132), 25–29. doi:10.1108/03074809710155587 Bastöe, P. Ö., & Dahl, K. (1996). Organisationsutveckling i offentlig verksamhet. Utbildningshuset Studentlitteratur.
223
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Becker, K. (2007), The impact of e-commerce and information technology in developing countries, In Krishnamurthy and Isaias (eds.), Proceedings of the IADIS International Conference e-Commerce, December 7-9, Algarve, Portugal, pp.230-235 Beyer, H., & Holtzblatt, K. (1998). Contextual Design Defining Customer-Centered Systems. Morgan Kaufman, Publishers Inc. Bolin, S. (2004). The Nature and Future of ICT Standardization. Retrieved June 21, 2004, from: http://www.sun.com/software/standards/natureandfuture_ICT.pdf Bolman, L. G., & Deal, T. E. (1997). Nya perspektiv på organisation och ledarskap. Andra upplagan, Lund, Studentlitteratur. Browne, G. J., & Ramesh, V. (2002). Improving information requirements determination: a cognitive perspective. Information & Management, 1–21. Bubenko, J. A., Jr. (1993). Extending the Scope of Information Modelling. 4:th International Workshop on the Deductive Approach of Inforamtion Systems and Databases, Lloret, Costa Brava,(Catalonia), Sept 20-22 1993. Departmentd de Llenguatges i Sistemes Informaticsn Universitat Politecnica de Catalunya, Report de Recerca LSI/93-25, Barcelona (http://www.dsv. su.se/~janis/jbpaper/library/bib.htm) Champy, J. A. (1997). Preparing for OC In Hesselbein, F., Goldsmith, M. & Beckhard, R. (1997). The Organiszation of the Future. Jossey-Bass, Publisher San Francisco, Cherry, C. & Macredie, R.D. (1999). The Importance of Context in Information System Design: An assessment of Participatory Design. Requirements Engineering, 4, 103–114. Clavadetcher, C. (1998). User involvement: key to success. IEEE SoftWare March/April.
224
Crick, F., & Koch, C. (2003). A framework for conscious. Nature Neuroscience, 6(2), 19–126. doi:10.1038/nn0203-119 Ersala, N., Yen, D., & Rajkumar, T. (2002). Enterprise Application Integration in the electronic commerce world. Computer Standards & Interfaces, 2189, 1–14. Ewusi-Mensah, K., & Przasnyski, Z. H. (1994). Factors contributing to the a bondonment of information systems development projects. Journal of Information Technology, 9, 185–201. doi:10.1057/ jit.1994.19 Ewusi-Mensah, K., & Przasnyski, Z. H. (1995). Learning from abandoned information systems development projects. Journal of Information Technology, 10, 3–14. doi:10.1057/jit.1995.2 Flamholtz, E. (1995). Managing Organisational Transitions: Implications for Corporate and Human Resource Management. European Management Journal, 13(1), 39–51. doi:10.1016/02632373(94)00056-D García-Murillo, M. (2004). Institutions and the Adoption of Electronic Commerce in Mexico. Electronic Commerce Research, 4, 201–219. doi:10.1023/B:ELEC.0000027980.16492.af Ghiladi, V. (2003). The Importance of International Standards for Globally Operating Businesses. International Journal of IT Standards & Standardization Research, Vol.1, No.1, Idea Group Publishing, 54-56. Goodman, S. (1991). Computing in a Less-Developed Country. Communications of the ACM, 34(12), 25–29. doi:10.1145/125319.125408 Hasselbring, W. (2000a). Information System Integration. Communications of the ACM, June, vol.43, no.6, 33-38. Hatch, M. J. (1997). Organisation Theory Modern, Symbolic, and Postmodern Perspectives. Oxford University, Press.
Guidelines for Preparing Organizations in Developing Countries for Standards-Based B2B
Hawk, S. (2004). A comparison of B2C ecommerce in developing countries. Electronic Commerce Research, 4, 181–199. doi:10.1023/ B:ELEC.0000027979.91972.36 Ho, S., Kauffman, R., & Liang, T.-P. (2005), A growth theory perspective on the international diffusion of e-commerce, In Proceedings of the International Conference on E-Commerce (ICEC’05), August 15-17, Xi’an, China, pp.57-65
Leffingwell, D., & Widrig, D. (2000). Managing Software Requirements A unified Approach. Addison, Weasley. Love, P., & Irani, Z. (2004). (in press). An exploratory study of information technology evaluation and benefits management practices of SMEs in the construction industry . Information & Management.
Intel (2003). Collaborative RosettaNet Implementation: Intel and Fujitsu streamline e-Business automation across the supply chain. Intel Information Technology White Paper, October.
Meskaran, F., & Ghazali, M. (2007), B2C in Iran: A case study to improve trust in developing countries, In Krishnamurthy and Isaias (eds.), Proceedings of the IADIS International Conference e-Commerce, December 7-9, Algarve, Portugal, pp.129-136
Jakobs, K., Procter, R., & Williams, R. (2001). The Making of Standards: Looking Inside the Work Groups. IEEE Communications Magazine, 2–7.
Milis, K. & Mercken, R. (2002). Success factors regarding the implementation of ICT investments projects. (Article in Press) Elsevier Science BV.
Jennex, M., Amoroso, D., & Adelakun, O. (2004). E-commerce infrastructure success factors for small companies in developing economies. Electronic Commerce Research, 4, 263–286. doi:10.1023/B:ELEC.0000027983.36409.d4
Motwani, J., Youssef, M., Kathawala, Y., & Futch, E. (1999). Supplier selection in developing countries: a model development. Integrated Manufacturing Systems, 10(3), 154–161. doi:10.1108/09576069910264411
Kearns, G. S., & Leder, A. L. (2000). The effect of strategic alignment on the use of IS-based resources for competitive advantage. The Journal of Strategic Information Systems, 9, 265–293. doi:10.1016/S0963-8687(00)00049-4
Mwangi, W. (2006). The Social Relations of eGovernment Diffusion in Developing Countries: The Case of Rwanda. Proceedings of the 2006 international conference on Digital government research, ACM International Conference Proceeding Series, vol.151, San Diego, USA, 199-208.
Kosanke, K., & Nell, J. (1999). Standardisation in ISO for enterprise engineering and integration. Computers in Industry, 40, 311–319. doi:10.1016/ S0166-3615(99)00034-2 Kotonya, G., & Sommerville, I. (1998). Requirements Engineering. ISBN 0-471-97208, WILEY. Kshetri, N. (2007). Barriers to e-commerce and competitive business models in developing countries: A case study . Electronic Commerce Research and Applications, 6, 443–452. doi:10.1016/j. elerap.2007.02.004
Pohl, K. (1998). Requirements engineering: An overview. CREWS Report Series CREWS-96-02. Poon, P., & Wagner, C. (2001). Critical success factors revisited: success and failure cases of information systems for senior executives. Decision Support Systems, 30, 393–418. doi:10.1016/ S0167-9236(00)00069-5 Premkumar, G., Ramamurthy, K. & Nilakanta, S. (1994). Implementation of Electronic Data Interchange: An Innovation Diffusion Perspective. Journal of Management Information Systems, Fall, Vol.11, No.2, 157-186.
225
Guidelines for Preparing Organizations in Developing Countries for Standards-Based B2B
Procaccino, D. J., Verner, J. M., Overnyer, S. P., & Darter, M. E. (2002). Case study: factors for early prediction of software development success. Information and Software Technology, 44, 53–62. doi:10.1016/S0950-5849(01)00217-8 Pun, K.-F. (2001). Cultural influences on total quality management adoption in Chinese enterprise: An empirical study. Total Quality Management, Vol.12 Issue 3, 323, 20p. Purcell, F., & Toland, J. (2004). Electronic Commerce for the South Pacific: A Review of E-Readiness. Electronic Commerce Research, 4, 241–262. doi:10.1023/B:ELEC.0000027982.96505.c6 Ramsey, J. (1998). Developing an IT Strategy. Computer Bits, 8 (8). Retrieved August, 1998 from http://www.computerbits.com. RosettaNet. (2001). Case Study: Arrow and UTEC replace EDI-based purchase order process with RosettaNet standards. Case study report. Retrived 20 February, 2004 from http://www.rosettanet. org/RosettaNet/Doc/0/D074294MUC4KJD8GF7HQL8RE67/Arrow_case_study.pdf. Roy, S., & Biswas, S. (2007). Collaborative ICT for Indian Business Clusters. Proceedings of the WWW 2007 Conference, May 8-12, Banff, Alberta, Canada, 1115-1116. Sadowsky, G. (1993). Network connectivity for developing countries. Communications of the ACM, 36(8), 42–47. doi:10.1145/163381.163388 Saiedian, H. & Dale, R. (2000). Requirements engineering: making the connection between the software developer and customer. Information and Software Technology 42), 419-428. Salman, A. (2004). Elusive challenges of e-change management in developing countries. Business Process Management Journal, 10(2), 140–157. doi:10.1108/14637150410530226
226
Schein, E. H. (2004). Organisational culture and Leadership (3rd edition). John Wiley & Sons, Inc. ISBN: 0-7879-6845-5. Singh, J., & Gilchrist, S. (2002). Three layers of the electronic commerce network: challenges for the developed and developing worlds. Info, 4(2), 31–41. doi:10.1108/14636690210435785 Söderström, E. (2004). B2B Standards Implementation: Issues and Solutions. PhD Thesis, Department of Computer and Systems Sciences, Stockholm University, Akademitryck, ISBN 917265-942-4. Söderström, E., & Pettersson, A. H. (2003). The Use of B2B Process Standards. Proceedings of the 15th International Conference on Advanced Information Systems Engineering Forum (CAiSE Forum 2003), 121-124. Sparks, R., Desai, N., Thirumurthy, P., & Kistenberg, C. (2007), An analysis of e-commerce adoption between developed and developing countries: A holistic model, In Krishnamurthy and Isaias (eds.), Proceedings of the IADIS International Conference e-Commerce, December 7-9, Algarve, Portugal, pp.11-18 Sutcliffe, A. G., Economou, A., & Markis, P. (1999). Tracing requirements problems in the requirements engineering process Requirements. Engineering, 4, 134–151. Tan, J., Tyler, K., & Manica, A. (2007). Business-to-business adoption of eCommerce in China. Information & Management, 44, 332–351. doi:10.1016/j.im.2007.04.001 Thompson, T., & Ranganathan, C. (2004). Adopters and non-adopters of business-to-business electronic commerce in Singapore. Information & Management, Vol.42. 89-102.
Guidelines for Preparing Organizations in Developing Countries for Standards-Based B2B
Uzoka, F.-M., & Seleka, G. (2006). B2C ECommerce Development in Africa: Case Study of Botswana. Proceedings of the Electronic Commerce conference (EC) Ann Arbor, Michigan, USA, 290-295. Van Gigch, J. P. (1991). System Design Modeling and Metamodeling. New York, Plenum Press.
WebMethods. (2003). GEAR 6 RosettaNet Implementation Guide: Project Planning Guide, Whitepaper. Wood, C. (2004). Marketing and e-commerce as tools of development in the Asia-Pacific region: a dual path. International Marketing Review, 21(3), 301–320. doi:10.1108/02651330410539639
This work was previously published in Emerging Markets and E-Commerce in Developing Economies, edited by Kamel Rouibah, Omar E. M. Khalil and Aboul Ella Hassanien, pp. 271-292, copyright 2009 by Information Science Reference (an imprint of IGI Global).
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Section II
Development and Design Methodologies
This section provides in-depth coverage of conceptual architecture frameworks to provide the reader with a comprehensive understanding of the emerging technological developments within the field of global business. Research fundamentals imperative to the understanding of developmental processes within information/knowledge management are offered. From broad examinations to specific discussions on electronic tools, the research found within this section spans the discipline while offering detailed, specific discussions. From basic designs to abstract development, these chapters serve to expand the reaches of development and design technologies within the global business community. This section includes more than 15 contributions from researchers throughout the world on the topic of global business.
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Chapter 2.1
Building Business Value in E-Commerce Enabled Organizations: An Empirical Study M. Adam Mahmood University of Texas at El Paso, USA Leopoldo Gemoets University of Texas at El Paso, USA Laura Lunstrum Hall University of Texas at El Paso, USA Francisco J. López Macon State College, USA
ABSTRACT This research attempts to identify critical ecommerce success factors essential for building business value within e-commerce enabled organizations. It is important to identify the critical success factors that organizations must pursue in order to facilitate a successful transformation from traditional brick-and-mortar organizations to click-and-brick business models. Diffusion DOI: 10.4018/978-1-60960-587-2.ch201
theory is used to demonstrate how these success factors create business value within an organization. The research model is fully grounded in information technology business value and productivity literature (e.g., Kauffman & Kriebel (1988), Mahmood, Gemoets, Hall, & Lopez (2008) Mahmood & Mann (1993), and Zhu (2004)). The manuscript utilizes an existing sample set consisting of a population of more than 550 company executives who are successfully implementing e-commerce strategies. The research examines constructs found in the literature and focuses on
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two importance dimensions of creating business value through e-commerce strategies: IT alignment to organizational strategies (ITOrS) and the quality and effectiveness of existing online systems (OnSQE). Critical success factors for e-commerce business success were found to include ITOrS (IT alignment to organizational strategies), IOrSA (Quality and effectiveness of online systems, OnSE (Online systems efficiency), and OnSQE (Online systems quality and effectiveness. The research produces empirical evidence that strategic decision making concerning implementation of e-commerce technologies and alignment with top management strategic planning is critical to the success of creating business value for e-commerce enabled organizations. The manuscript concludes with limitations of the research and implications for future research studies.
INTRODUCTION In today’s economic environment it is vital that organizations invest in resources that will build value throughout the entire organization. Implementation of e-commerce strategies have become a popular way of increasing business value. Social networking through popular mediums such as Facebook and MySpace, advanced mobile communication devices, and widespread accessibility has redefined e-commerce and has resulted in an explosion of increased opportunities for e-commerce enabled organizations. Many traditional brick-and-mortar companies have invested and continue to invest heavily in e-commerce technologies due to a huge increase in online opportunities. e-Marketer (June, 2008) reports: In 2007, 133.1 million individuals, nearly four-fifths of US Internet users, shopped online. By 2012, the total will be closer to 158.2 million, or 82.5% of Internet users. From 2007 to 2012, the number of new online shoppers in the US is expected to grow at a 3.5% average annual rate.
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Also in 2007, 110.7 million individuals, nearly two-thirds of US Internet users, made at least one online purchase. By 2012 the number of online buyers is expected to be 141 million, or 73.5% of Internet users. From 2007 to 2012, the number of new online buyers in the US will grow at a 5% average annual rate. (p.1) Forrester Research (2007) estimates that online sales will reach $204 billion this year and $335 billion by 2012. E-commerce currently accounts for 6 percent of all retail sales in the United States. Although forecasts for retailers are currently dismal it is believed that e-commerce retailers will fare better than their brick-and-mortar counterparts (e-Marketer, 2008). The information technology (IT) productivity and business value literature report performance and productivity gains for organizations that evolve to click-and-brick structures. There are many well known examples of click-and-brick organizations including Best Buy, Wal-Mart, Target, Walgreens, Sears, Cisco Systems, Dell Computers, and Boeing Corporation. These are excellent examples of large click-and-brick organizations that have achieved a significant economic benefit by using e-commerce technologies. Cisco, the single largest user of e-commerce in the world, attributes 90% of its 2000 sales to online sales. Also, 82% of its customer inquiries are handled online (McIlvaine, 2000) and 83% of questions concerning support are answered through. Cisco’s web based self service tools (“Customer Care,” 2001) handle 82% of customer inquiries and 83% of technical support requests online. Dell, ranked 49th in the Top 50 Internet properties logged 9.2 million first time visitors with sales of more than $1 million dollars in PC sales online, everyday. Dell Computer reported over 250% return on invested capital from its logistics and order fulfillment systems (Dell.com, November 2000). The importance of the present research stems from the fact that there is very little empirical evidence in the IT productivity and business value literature regarding the critical success factors
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from e-commerce business initiatives, especially for large click-and-brick companies (Brynjolfsson and Kahim, 2000). The fundamental objective of the present research is to define the success indicators of business value in e-commerce technology enabled organizations. The present research investigates firms that are successful in using e-commerce technology and determines the critical success factors responsible for building business value within the organizations.
THEORETICAL FOUNDATIONS Diffusion theory studies the adoption of innovations through (or as a function of) time and identifies and understands the factors that influence adoption behavior. Zhu (2004) assessed e-commerce payoffs indirectly via an interaction effect with IT infrastructure. He found a positive interaction effect between IT infrastructure and e-commerce capability. He also found that this relationship positively contributes to firm performance in terms of sales per employee, inventory turnover, and cost reduction. Clearly Zhu’s study did not look at the stand-alone impact of e-commerce technologies on a firm’s performance. In addition, Zhu used the resource-based theory to ground his research whereas we used Rogers’ (1983) diffusion theory to provide a foundation for our research. While it is true that price (reduction) is an important factor, our contention is that diffusion may be strong even if prices go up (so long as the benefit more than offsets the cost). Therefore, we propose the incorporation of the cost-benefit relation in diffusion models. A complete and thorough analysis would study these models using longitudinal data. Unfortunately, such data are not yet available. Thus this research requires two steps. The first consists of identifying the factors that result in e-commerce business success while the second step incorporates those factors into diffusion models. We are
unable to validate these models in the present research for the lack of longitudinal data. In the present research, we use cross-sectional data to analyze the relationship among the following factors that were selected based on a thorough literature review: a. Inter-organizational systems availability (IOrSA): extent to which e-commerce has helped in integrating the different systems and made workflow processes easier; b. Online systems efficiency (OnSE): availability of uniform operating and highly automated mechanisms using e-commerce technologies; c. IT Alignment to organizational strategies (ITOrS): an indication of how much support for Internet-enabled IT there is in the organization; d. online systems quality and effectiveness (OnSQE): measured in terms of e-commerce site design and availability; and, e. e-commerce business success (ECBS). Since the latter clearly indicates “benefits,” we propose (based on our findings in the present research) incorporating IOrSA, OnSE, ITOrS, and OnSQE in e-commerce diffusion models as indicators of the cost-benefit relationship. Later on, when historical data become available, we will build on the ideas of Gurbaxani and Mendelson (2001) and develop and test (i.e., curve-fit) the corresponding models. Even though it is not yet possible to conduct this research because of lack of data, this idea is an important contribution of the present research.
LITERATURE REVIEW As stated earlier, there is little or no empirical research in the area of e-commerce business value but some important related concepts that have been identified include business value; impact of e-commerce; and success and failure of e-commerce businesses. It is, however, possible to draw useful insights from the IT business value and other related literature. There are a number of studies on factors contributing to the success or failure of an IT system that can be compared to e-commerce success and failure. Thus, the IT
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business value literature provides background information and concrete theoretical support to ground our e-commerce success model. Next, a review of IT business value literature is provided below that suggests incorporation of five constructs in our analysis.
IT Alignment to Organizational Strategies (ITOrS) This construct measures the degree to which the strategies, goals, and objectives of a firm’s information technology are aligned to its parent organization’s strategies, goals, and objectives. When this occurs, top management support for IT initiatives appears to be stronger which, as suggested in previous research, seems to be a critical success factor for any IT project. This type of support takes various forms including appointing an executive level manager as the Chief Information/ Technology Officer and allowing IT to influence, through the adoption of email and other internet technologies, the way the company conducts business. Thus, indicators of alignment include the presence of an IT manager with executive authority; the level of support given by executives to e-commerce and other IT-related initiatives; and whether the organization has a learning and adaptive culture that allows innovations to take root in its functional environment. Segars and Grover (1998) evaluate the strategic impact of IT. They suggest that paying attention to aligning IT strategy with business strategy, understanding the systems processes, and the support of management and end-user groups are crucial to IT planning success. Barua, Kriebel, and Mukhopadhyay (1991) also analyze the strategic use and impact of IT implementation. Reich and Benbasat (2000) found that communication between IT and business executives, the level of connection between IT and business planning processes, and the extent of shared domain knowledge leads to better alignment of IT and business strategies in the short and long terms. Feeny and Ives (1990)
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also focus on sustained strategic advantage generated through IT applications. Teo and Ang (1999) identify top management commitment to the strategic use of IT, IS management business knowledge, and top management confidence in the IS department as critical success factors for an organization. Teo and King (1996, 1997) studied potential inhibitors and facilitators of development of successful IT applications with strategic value. They found that integration of business planning and IT planning results in IT being able to support business strategies more effectively. Kao and Decou (2003) focused on the importance of a strategy-based e-commerce planning model which included seven dimensions with strategy at the core. Clemons and Wang (2000) also provided strategies for electronic commerce initiatives. Shin (2001) also suggested the use of e-commerce for gaining organizational competitive advantage. Additionally, it is obvious that some companies have an explicit way of aligning IT to their organizational strategy. Wal-Mart, for example, has separate e-commerce headquarters in California to fulfill the company’s e-commerce business needs. The following research studies also identify other factors related to the success or value of IT. Teo and King (1997) address the importance of alignment of IT planning with business planning and determine that the business knowledge of the IT executive is the most significant factor in influencing the integration process. Dos Santos and Sussman (2000) indicate that IT investments fail to have an impact on some firms’ value because the companies fail to prepare or respond well to the structural changes of the firm caused by IT.
Inter-Organizational Systems Availability (IOrSA) IOrSA refers to the extent to which e-commerce has helped in integrating the different systems and made workflow processes easier between different organizations, thus creating e-commerce business value. E-commerce technologies such as
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extranets allow businesses to connect their suppliers, customers, and other business partners that result in competitive advantages. E-commerce adds value to a firm by introducing a new channel for buying, selling, and providing information to appropriate stake holders. Some of the readily apparent benefits are reduction in employee costs and communication costs. Hidden benefits include better relationships with upstream and downstream business partners because of a uniform and secure communication system. Dai and Kauffman (2002) point out that firms can conduct successful B2B transactions by creating inter-organizational systems. Barua, Konawa, Whinstone, and Yin (2001) indicate that the readiness of business partners to implement e-commerce technologies is critical to achieving business excellence and online systems efficiency. Bakes (1991) uses economic theory to understand why electronic marketplaces work and when they are of strategic value. Electronic marketplaces, according to Bakos (1991), improve inter-organizational coordination and reduce search costs. Bakos (1997) also points out that commodity and differentiated markets respond differently to the integration enabled by electronic marketplaces. Reduction in search costs, for example, occurs differently in these markets. In a subsequent paper, Bakos (1998) reinforces the points made in the first two by explaining that electronic marketplaces create more efficient and friction-free markets. Steinfield, Markus, and Wigand (2005) used the industry level of analysis to explore inter-organizational systems in the home mortgage industry. Kurnia and Johnston (2005) developed a case study of category management adoption in Australia to model inter-organizational system adoption. According to Benjamin and Scott (1988), one of the reasons for IT success is that it enables, through online databases and telecommunication networks, new forms of integration that result in better cost performance and increased data integration. Kickul and Gundry (2001) argue that maintaining better relationships and integrating
with suppliers is a crucial element of the company sustenance process. Johnston and Vitale (1988) suggested that, if carefully identified and used, inter-organizational systems give significant competitive advantages to organizations.
Online Systems Efficiency (OnSE) Automated, uniform operating mechanisms through e-commerce technologies that function in tandem with existing mechanisms normally result in better online systems efficiency and cost savings. Also, online customer service in terms of FAQ’s, chat rooms, and a link to call centers indicate high levels of online systems efficiency. Banker, Kauffman, and Morey (1990) distinguish between impacts of IT investment on competitive efficiency and on online systems efficiency. Mukhopadhyay and Kekre (1995) study an electronic data interchange system at Chrysler over a period of 10 years and observe that it has caused massive cost savings and has imparted system-wide discipline and integrative value to the company. In 2001, Molla and Licker (2001) extended the IS success model to E – commerce including the construct of system efficiency. Shao and Lin (2001, 2002) define technical efficiency as actual output versus expected output and find a positive correlation between investment in IT and technical efficiency improvement. Stratopoulos and Dehning (2000) show that firms making successful investments in IT are more successful at solving the productivity paradox than those that make failed or abortive investments in IT. Hitt and Brynjolfsson (1997) analyze the effects of IT on the internal firm organization and find that IT is associated with decentralization of authority, increased knowledge work, and decreased observability. Brynjolfsson and Hitt (1998) find that productivity payoffs from computerization are not automatic, but part of a series of productivity changes that eventually make financial sense. Barua, Konana, Whinston, and Yin (2001) show that the readiness of business partners to
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implement e-commerce technologies is critical to achieve business excellence and online systems efficiency. Lee and Barua (1999) find positive correlation between IT inputs and productivity. Tsay and Agrawal (2004) identified various sources of inefficiency in the effect of channel conflict on system efficiency including pricing changes, demand functions, and structural properties.
Online System Quality and Effectiveness (OnSQE) OnSQE has to do with aspects related to online presence effectiveness through the e-commerce site design and availability. Previous research has analyzed factors that make a website successful, which is associated to overall e-business success. E-commerce, via websites, has dramatically improved the interaction of companies with customers. The ability to offer products and services to customers worldwide on a 24/7 basis is a value-adding attribute of an e-business. Also, the website is a means that firms can use to influence customer’s perceptions of its business. Customers perceive website security and access time of the site as critical. This is a reason why firms try to improve users’ perceptions of security by making their website secure and aligning with recognizable internet security agencies and protocols. Other important factors include ease of use, quality of design, and value for the customer. Moon and Kim (2001) argue that the acceptance of the World Wide Web (WWW) is similar to the “perceived ease of use” (PEOU) component of the Technology Acceptance Model. Acceptance of a new technology is likely to vary depending on the kind of technology, the target users, and the context. Moon and Kim (2001) measure online presence effectiveness through the design and availability aspects of the e-commerce site. Gefen and Straub (2000) also argue that the PEOU plays an important role in the actual use and success of systems. A survey by Liu, Arnett, and Litecky (2000) indicates that the attractiveness, qual-
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ity of design, and information available on the e-commerce site are the most important factors influencing the purchase decision of a customer. Zhang, Von Dran, Small, and Barcellos (1999, 2000) use Herzberg’s hygiene-motivation theory to study how the general ‘hygiene’ or perceptual quality of a website affects users’ motivation to use the website. Applying the Kano model of quality to the design of web sites, Zhang and Von Dran (2001) study features that generate ‘delight’, ‘motivation,’ and ‘loyalty’ of website users. Lederer, Maupin, Sena, and Zhuang (2000) point out that the “ease of use” quality is very important for successful web sites. Keeney (1999) stresses the importance of identifying value propositions and developing an e-commerce value model for the customer. Cao, Zhang, and Seydel (2005) conducted an empirical study on web-site quality in a B2C environment and identified, using the IS success model, what constitutes the web site quality and effectiveness. Pather, Erwin, and Remenyi (2003) attempted to measure the effectiveness of e-commerce using a conceptual model. Rose and Straub (1999) identify excessive download time as one of the most serious technological impediments to e-commerce.
E-Commerce Business Success (ECBS) Performance, productivity, and perception are some factors that can be used to measure ECBS. Performance has been measured in the IT business value literature, in terms of financial ratios: return on investment (ROI), return on equity (ROE), return on sales (ROS), growth in revenue (GINR), and net income over invested capital (NIC). Cron and Sobol (1983) and Dos Santos, Peffers, and Mauer (1993) employed ROI. Barua, Kriebel, and Mukhopadhyay (1995); Hitt and Brynjolfsson (1994); and Strassman (1990) used NIC. Hitt and Brynjolfsson (1994) and Mahmood and Mann (1993) applied ROS. Woo and Willard (1983) used GINR. Dehning and Richardson
Building Business Value in E-Commerce Enabled Organizations
(2002) analyze the impact of IT through ROI, ROE, and ROS that can capture system success. Likewise, productivity has been assessed in terms of two ratios: sales to total assets (STA) and sales by employee (SE). Brynjolfsson and Hitt (1993) used a measure similar to STA, total sales. Strassman (1990) employed SE. Perception has been measured through company’s image, customer satisfaction, product service innovation, and the number of return customers. The first three create customer loyalty that results in return purchases. Loyalty is one of the most significant contributors to business profitability (Turban, King, Lee, Warkentin, and Chung (2002)). It can also reduce costs in the sense that it costs five to eight times more to acquire a new customer than to keep an existing one. A comprehensive review of the use of the Internet to foster customer loyalty is provided by Reichheld (2001). In spite of the fact that initial costs are high, continuous support for e-commerce strategy is essential for the success of e-commerce initiatives. Zott, Amit, and Donlevy (2000) study the most successful strategies among European firms to create e-business value. Peteraf (2000) looks at strategies that give competitive advantage to the firm from a resource-based perspective of the firm. Zhu (2004) focused on the firm level to develop a research framework which described the relationships between IT infrastructure and ecommerce capability. Barua et al. (2001) observe that e-business affects large and small companies differently. Smaller companies experience a quick impact because of immediate expanded geographic reach. Larger companies face more complexity and need to pay considerable attention to the drivers and need to establish an appropriate infrastructure before acceptable payback is received. Subramani and Walden (2001) analyze the impact of e-commerce investment on the value perceived by investors. They found a positive correlation between e-commerce initiatives announcements and higher value perceived by investors.
Dekleva (2000) identifies four environmental variables that affect e-businesses: building trust so consumers engage in e-commerce, establishing a legal framework for e-commerce operations, enhancing information systems infrastructure by improving technical resources, and maximizing the benefits provided by such systems via increased integration across systems. Amit and Zott (2001) identified four value creating components in e-commerce companies: efficiency, complimentarity, lock-in, and novelty. Lee and Clark (1997) analyze factors contributing to the successful implementation of electronic market systems. There are other factors that affect ECBS. These are similar to what occurs with IT investment (Mahmood et al., 2000, 2001) as such some of the relevant IT-related literature is also covered in this section. Melville, Kraemer, and Gurbaxani (2004) used an integrative model of IT business value to describe the relationship between information technology and organizational performance. Chan (2000) points out the need to take ‘soft’ factors into account when measuring the value of IT. Chircu and Kauffman (2000) consider hard (e.g., better financial performance and increase in sales) and soft (e.g., better market position and better supplier relationship) IT benefits. DeLone and McLean (1992) review existing research (180 articles) on MIS success and identify six IS success dimensions: system quality, information quality, use, user satisfaction, individual impact, and organizational impact. Davern and Kauffman (2000) differentiate the value realizable from IT into: a) potential value, in the areas of the organization that would have an impact that current systems fail to provide, and b) realizable value, which is the value that can be derived from the system considering the assets that exist in the firm. Kim and Peterson (2001) identify five factors that contribute to IS success from a developer’s perspective: management and user input, project management, characteristics of the project leader, methodology, and characteristics of
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Building Business Value in E-Commerce Enabled Organizations
the team members. Teo and Ang (2000) analyze how IT planning leads to IT success. Teo and Ang (2001) also study major existing problems during the IT planning process. Dos Santos, Peffers, and Mauer (1993) and Im, Dow, and Grover (2001) discuss the effects of IT investments on a firm’s value. Josefek and Kauffman (1997) analyze the potential profitability or success of innovative information systems. As explained earlier, this work is the first of two research steps in the analysis and development of theory on e-commerce technology enabled business value. The fundamental objective and contribution of the current (first step) exploratory research is to formulate and test a model for value creation in e-businesses. Thus, the model can function as a reference framework for strategic managers by offering guidelines for e-business initiatives. Also, the constructs developed in the model can serve as a foundation for further investigation of different e-commerce drivers and their relationships with business value measures. There may be additional environmental factors associated with successful e-commerce implementations. A further goal of this article is to establish theoretically grounded constructs, factors, and ideas that can be used for further research in this field and to enhance the present work. The importance of the research study stems from the fact that it is the first empirical study that directly addresses the business value of e-commerce technologies enabled business initiatives.
MODEL AND HYPOTHESES We used the five constructs that we identified in the IT business value/success literature to build a model that captures the drivers of e-business success and relationships among these drivers. The model appears in Figure 1. The model suggests the way IT alignment to organizational strategies (ITOrS), inter-organizational systems availability (IOrSA), online system
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Figure 1. E-commerce business value model
efficiency (OnSE), and online system quality and effectiveness (OnSQE) interact with each other and together affect e-commerce business success (ECBS). The model also helps one understand the tasks a brick-and-mortar company has to complete as well as the processes that it needs to undertake for it to be successful in an e-commerce initiative.
Hypotheses Hypothesis 1: This proposition examines the relationship between the degrees of IT alignment to organizational strategies (ITOrS) and Inter-organizational systems availability (IOrSA). ITOrS, as stated earlier, measures the degree to which the strategies, goals, and objectives of a firm’s information technology are aligned to its parent organization’s strategies, goals, and objectives. When this occurs, top management support for IT initiatives appears to be stronger, which appears to be a critical success factor for any IT project. Indicators of alignment include the presence of an IT manager with executive authority, the level of support given by executives to e-commerce initiatives, and whether the organization has a learning
Building Business Value in E-Commerce Enabled Organizations
and adaptive culture that allows innovations to take place in its functional environment. What influence might that have on the inter-organizational system availability? If indicators of alignment are present in the firm it should have a positive impact on the extent to which these indicators has helped in integrating the different systems and made workflow processes easier between different organizations. Barua, Konana, Whinston, and Yin (2001) indicate that the readiness of business partners to implement e-commerce technologies is critical to achieving business excellence and online systems efficiency. Thus the degree of IT alignment to organizational strategy will have a positive influence on workflow processes and integration of systems, creating e-commerce business value. Segars and Grover (1998) evaluate the strategic impact of IT. They suggest that paying attention to aligning IT strategy with business strategy, understanding the systems processes, and the support of management and end-user groups are crucial to IT planning success. These lead to the following hypothesis
alignment. Sanders and Premus (2002) classify firms into high-, medium-, and low-level users of IT depending on their level of IT sophistication. They cite efficiencies gained via IT in terms of automation as an enabler for managers to focus on strategic issues and competencies. Lederer, Mirchandani, and Sims (2001) investigate whether strategic advantage can be derived from the World Wide Web. They propose that the efficiencies created by web-enabled systems affect strategic alignment positively by improving customer relations. Banker, Kauffman, and Morey (1990) distinguish between impacts of IT investment on competitive efficiency and on online systems efficiency. Mukhopadhyay and Kekre (1995) study an electronic data interchange system at Chrysler over a period of 10 years and observe that it has caused massive cost savings and has imparted system-wide discipline and integrative value to the company. Shao and Lin (2001, 2002) define technical efficiency as actual output versus input. This leads to the following hypothesis:
H1: There is a positive correlation between high levels of IT alignment to organizational strategies (ITOrS) and high levels of interorganizational systems availability (IOrSA).
H2: There is a positive correlation between businesses with higher levels of IT alignment with organizational strategies (ITOrS) and a high level of online systems efficiency (OnSE).
Hypothesis 2: This proposition considers the relationship between the level of IT alignment to organizational strategies (ITOrS) and the likelihood of obtaining online system efficiency (OnSE). While ITOrS is measured in terms of top management support, existence of a top IT executive, and other similar factors. OnSE is measured by way of impact on productivity and efficiency measures. Online systems with impact on productivity and efficiency will garner more management support which in turns will ensure that these systems are more aligned toward organizational goals and strategies. Huselid and Becker (1997) propose the existence of synergies between implementing efficient systems and their strategic
Hypothesis 3: This hypothesis examines the relationship between ITOrS and online systems quality and effectiveness (OnSQE). The more the company’s IT is aligned to the organization’s strategies the more successful it will be at obtaining management support for creating higher quality and effective online presence. Also, since the online interface presents the so-called gateway to the company, top management is eager to portray an elegant interface reflecting a better image of the company. Kowtha and Choon (2001) mention how the sophistication of a firm’s website reflects the strategic priorities of the firm. They suggest that critical competencies in e-commerce have little to do with technology and more with managerial
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domain and priorities. They furthermore suggest that strategic commitment has substantive and high significant effects on website development. Peak and Guynes (2003, 2003-1) point out that aligning IT with organizational strategies improves information quality which results in improved quality of products and services. These lead to the following hypothesis H3: There is a positive correlation between businesses with higher level of IT alignment to organizational strategies (ITOrS) and online system quality and effectiveness (OnSQE) Hypothesis 4: This hypothesis examines the critical relationship between ITOrS and e-commerce business success (ECBS). Some studies mention top management commitment and involvement in IT projects as singularly important factors for success of IT systems. In fact, lack of their commitment and involvement is pointed out to be among the top ten problems that lead to failure of IT projects (Johnson, Boucher, Conners, and Robinson, 2001). Pollalis (2003) confirms that alignment of IT to organizational strategies leads to better performance of banks. Sun and Hong (2002) find wide support in the literature for a significant direct effect of strategic alignment on business performance in the field of manufacturing strategy. Burn and Szeto (1999) find that it is critically important to align business and IT planning. They point out that business success depends on the linkage of business strategy; IT strategy; organizational infrastructure and processes; and IT infrastructure and processes. They also argue that the role of IT management is to lead and maintain a close alignment between the IT function and business strategy. Brown (2003) suggests that developing appropriate strategic performance metrics for the IT human resource function creates a closer IT alignment with strategic objectives. These lead to the following hypothesis.
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H4: There is a positive correlation between businesses with higher level of IT alignment to organizational strategies (ITOrS)and ecommerce business success (ECBS). Hypothesis 5: This hypothesis examines the critical relationship between Inter-organizational systems availability (IOrSA) and E-commerce business success (ECBS). Dai and Kauffman (2002) point out that firms can conduct successful B2B transactions by creating inter-organizational systems. Barua, Konana, Whinston and Yin (2001) indicate that the readiness of business partners to implement e-commerce technologies is critical to achieving business excellence and online systems efficiency. According to Bakos (1991) electronic marketplaces improve inter-organizational coordination and reduce search costs. Bakos (1998) further explains that electronic marketplaces create more efficient, friction-free markets. According to Benjamin and Scott (1988) one of the reasons for IT success is that it enables, through online databases and telecommunication networks, new forms of integration that result in better cost performance and increased data integration. Kickul and Gundry (2001) argue that maintaining better relationships and integrating with suppliers is a crucial element of the company sustenance process. Johnston and Vitale (1988) defend that if carefully identified and used, inter-organizational systems give significant competitive advantages to organizations. Barua, Konana, Whinston, and Yin (2001) show that the readiness of business partners to implement e-commerce technologies is critical to achieve business excellence and online systems efficiency. Epstein (2000) says that integration of processes and systems directly translates into business success. Huang, Chen, and Frolick (2002) argue that introducing the web as a way of integrating data leads to better business value. Epstein (2000) says that integration of processes and systems directly translates into business success. Huang, Chen, and Frolick (2002) argue that introducing the web as a way of integrating data
Building Business Value in E-Commerce Enabled Organizations
leads to better business value. Dai and Kauffman (2002) point out that firms can conduct successful B2B transactions by creating inter-organizational systems. At least one empirical study mention efficiency benefits from the implementation of integrated inter-organizational systems. Mebane Packaging, for example, achieved better efficiency, and the chain of supermarkets Somerfield Stores improved its business efficiencies with its systems integration project (Thomas, 2003). These lead to the following hypothesis: H5: There is a positive correlation between businesses with higher level of Inter-organizational systems availability (IOrSA) and e-commerce business success (ECBS). Hypothesis 6: Firms with efficient e-commerce systems should be at a relatively better position to achieve better business success. Lederer, Mirchandani, and Sims (2001) point out that strategic advantage from the World Wide Web is created through increased efficiency of processes. Mukhopadhyay and Kekre (1995) study an electronic data interchange system at Chrysler over a period of 10 years and observe that it has caused massive cost savings and has imparted system-wide discipline and integrative value to the company. Stratopoulos and Dehning (2000) show that firms making successful investments in IT are more successful at solving the productivity paradox than those that make failed or abortive investments in IT. Hitt and Brynjolfsson (1997) analyze the effects of IT on the internal firm organization and find that IT is associated with decentralization of authority, increased knowledge work, and decreased observability. These lead to the following hypothesis. H6: There is a positive correlation between businesses with higher online systems efficiency (OnSE) and e-commerce business value (ECBS).
Hypothesis 7: This hypothesis purports that the quality and effectiveness of the website (online presence) drives e-commerce success. Zhu and Kraemer (2002) point out that better e-commerce capability serves to improve the effectiveness of investments on e-commerce initiatives through firm performance. Chaudhury, Mallick, and Rao (2001) mention that enhancement of website quality can improve business value. Huang, Chen, and Frolick (2002) say that evaluating web data quality is important to effectively determining the business value of online data. A survey by Liu, Arnett, and Litecky (2000) indicates that the attractiveness, quality of design, and information available on the e-commerce site are the most important factors influencing the purchase decision of a customer. Lederer, Maupin, Sena, and Zhuang (2000) point out that the “ease of use” quality is very important for successful web sites. Rose and Straub (1999) identify excessive download time as one of the most serious technological impediments to e-commerce. These lead to the following hypothesis. H7: There is a positive correlation between businesses that have a higher level of online system quality and effectiveness (OnSQE) and e-commerce business success.
Data Collection Based on the existing research literature, we designed a questionnaire (Appendix) to gather information on e-business success. It contains 31 items. The respondents were asked to answer each question on a seven-point Likert scale with values ranging from 1 (strongly disagree) to 7 (strongly agree). Each construct was measured using a series of items. ITOrS, for example, comprises five items: i) alignment of IT strategies with top management strategies, ii) whether IT is considered a part of the long term strategies, iii) whether IT executives have decision making roles, iv) IT structure features, and v) overall organizational
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learning environment. IOrSA was measured in terms of whether: i) the firm has an Internetenabled system to share information among upstream and downstream entities, ii) there is an effective automated order changing system, iii) data is automatically transmitted and processed, iv) it is possible to track inventory and purchasing continuously, v) there exists an online procurement system, and vi) internet expertise is an important selection criteria for suppliers/vendors. OnSE contains five items: i) degree of online business transactions, ii) availability of online customer service, iii) availability of a highly automated order tracking system, iv) possibility of resolving customer requests online, and v) availability of a system to monitor orders continuously. OnSQE is based on five e-commerce website features: i) security, ii) attractiveness, iii) navigability, iv) flexibility, and v) continuous availability of the website. Finally, ECBS is measured in terms of i) return on investment; ii) return on sales; iii) growth in revenue; iv) net income over invested capital; v) sales over total assets; vi) sales by employee; vii) company image; viii) customer satisfaction; ix) product /service innovation; and x) return of customers. The data used to test the hypothesized model comes from surveying 550 companies which have been identified as premier companies that have successfully implemented e-commerce technologies or strategies and have been able to create positive value either operationally or financially. These firms were listed in Information week 500 and Internet week 100, two premier computer magazines that survey innovative and successful uses of IT for competitive advantage. A copy of the instrument was mailed to IT executives of these companies. The respondents were allowed to reply via postal mail or answer the questionnaire online. In order to increase the response rate, we sent the instrument to local representatives (managers of the stores) of national chains (e.g., Target and Dillards). Also, we surveyed a group of Boeing executives attending an MBA-level e-
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commerce class. Individual identity and responses were masked to ensure confidentiality. We received 43 responses, seven of which were incomplete. Incomplete responses were not used for analyzing data. Forty one companies had more than 1 million in revenues. The other two companies did not provide revenue information. About 42% of the respondents were executive technology officers; 32% middle managers; and 26% store managers or associates. About 2% of the responses were from companies that engage in all three modes of business: Business to Business (B2B), Business to Consumer (B2C), and Consumer to Consumer (C2C). Overall, there were 60% in B2B, 72% in B2C, and 2% in C2C. About 44% were involved in both B2B and B2C. Around 14% were exclusively B2B and 23% exclusively B2C. The average number of employees of these firms was 98,000. Surveying took about 6 months during the summer and fall of 2002.
RESULTS Analysis In this section we report statistical results with respect to constructs validations; model fit; and hypotheses and paths analysis. The Partial Least Square (PLS) approach is typically suited for problems dealing with a small sample size and is often used for exploratory model testing and validation. We have, however, used an AMOS/ LISREL approach to analyze our structural equation model because it also yields similar results for a small sample size while offering more statistics (AMOS (Arbuckle, J.L., 1989). In the past, the AMOS/LISREL approach has been used for analyzing small data sets. Wold (1989), for example, used this approach to analyze a model based on a data set consisting of 10 cases and 27 variables.
Building Business Value in E-Commerce Enabled Organizations
Unidimensionality
measure convergent validity as a reliability test for the five constructs in the model. ITOrS, IOrSA, OnSE, OnSQE, and ECBS have reliability scores of 0.90, 0.76, 0.67, 0.81, and 0.93, respectively. Nunnally (1978) suggested a Cronbach alpha threshold level of 0.60 for exploratory research. All five constructs met this threshold level. More recently, Hair et al. (1998) suggested the threshold values of 0.60 for exploratory research and 0.80 for confirmatory research. Since the present research is an exploratory study, the aforementioned constructs are also reliable using the guidelines suggested by Hair et al. (1998).
To verify that all items loaded well in their assigned constructs, we used factor analysis to conduct unidimensionality tests with a reference norm of 0.40 as suggested by Mahmood and Sniezek (1989). Table 1 shows results of this test. With the exception of item #2, all remaining five items in construct IOrSA load satisfactorily (> 0.40). All items in OnSE load well (> 0.46). All 5 items in ITOrS load strongly (> 0.82) with the exception of item #3 which loads at 0.59. All five items in OnSQE load well (> 0.58). The 10 items or questions in ECBS, the terminal construct of the model, load well (> 0.59). The average variance extracted (from communalities from factor analysis) is 0.54, 0.42, 0.62, 0.37, and 0.57 for IOrSA, OnSE, ITOrS, OnSQE, and ECBS, respectively.
Validity Table 2 presents the correlations between constructs. Demonstrating divergent or discriminant validity requires that the constructs do not correlate highly with each other (Campbell and Fiske (1959)). As can be seen, almost all the correlations are below 0.50 which indicates that these constructs are valid independently. Note that IOrSA-OnSE, IOrSA-ITOrS, ITOrS-ECBS and OnSQE-ECBS involve some measure of overlap. It is not surprising that all constructs are correlated to some extent as the various processes contributing
Reliability Cronbach’s coefficient alpha, one of the most widely used reliability tests, was carried out to ensure that the items for each factor were internally related in the manner expected. Cronbach’s alpha is based on “internal consistency” of a test: the degree to which variables in the measurement set are homogeneous. We used the Cronbach alpha to
Table 1. Scale development Number of Items or questions
Construct IOrSA OnSE ITOrS OnSQE
ECBS
6 5 5 5
10
Mean 5.00 4.98 5.55 5.24
5.29
Standard Deviation 0.90 0.92 1.01 1.00
0.98
Cronbach Alpha
Variance Extracted
Factor Loadings
0.76
0.501, 0.148, 0.614, 0.763, 0.683, 0.648
0.54
0.67
0.584, 0.701, 0.545, 0.613, 0.459
0.42
0.90
0.861, 0.881, 0.592, 0.837, 0.884
0.62
0.81
0.748, 0.752, 0.890, 0.583, 0.677
0.37
0.93
0.767, 0.796, 0.807, 0.792, 0.751, 0.590, 0.794, 0.833, 0.880, 0.585
0.57
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Table 3. Average variance extracted (AVE)
Table 2. Correlations among constructs Construct
IOrSA
OnSE
ITOrS
OnSQE
IOrSA
1.000
OnSE
0.520
1.000
ITOrS
0.641
0.464
1.000
OnSQE
0.373
0.471
0.403
1.000
ECBS
0.498
0.467
0.609
0.558
ECBS
S1
IOrSA
1.000
to the success of an e-business can be expected to interweave and overlap among themselves. Since the aforementioned analysis does not provide unambiguous results on discriminant validity, we have decided to use a more rigorous factor-based procedure known as the average variance extracted (AVE) method proposed by Fornell and Larcker (1981) (see Tables 3 and 4). The formula for calculating the AVE is provided at the bottom of Table 3. Using this method, one may conclude that constructs are different if the AVE for a given set of constructs is greater than their shared variance. Table 4 provides a matrix of squared covariance of each construct with each other construct. The diagonal elements are replaced with the AVE for the column construct. If there is a discriminant validity among the constructs, then the diagonal element for a given construct (column) should be larger than any of the squared covariances in the column or row in which it is found. Using this benchmark, there is unequivocal evidence that all constructs included in the present study pass the test of discriminant validity.
Results AMOS results showed that the paths ITOrS →IOrSA, ITOrS → OnSE, ITOrS → OnSQE, and ITOrS → ECBS, and OnSQE → ECBS are significant, with coefficients 0.64 (significant at the.01 level), 0.46 (significant at the.05 level), 0.40 (significant at the.05 level), 0.39 (significant at the.05 level), and 0.34 (significant at the.05
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Construct 2.12
S2
AVE
3.88
0.35
OnSE
1.72
3.28
0.34
ITOrS
3.35
1.65
0.67
OnSQE
2.72
2.29
0.54
ECBS
5.85
4.15
0.59
S1 = Sum of squared factor loadings of the indicator variables on the factor representing the construct S2 = Quantity (1 – the squared loading) summed for all indicators AVE = S1/(S1 + S2)
Table 4. Squared covariance and AVE ITOrS
IOrSA
OnSE
OnSQE
ECBS
ITOrS
0.35
0.331
0.198
0.181
0.365
IOrSA
0.331
0.34
0.186
0.116
0.181
OnSE
0.198
0.186
0.67
0.212
0.182
OnSQE
0.181
0.116
0.212
0.54
0.318
ECBS
0.365
0.181
0.182
0.318
0.59
level), respectively. Paths IOrSA → ECBS and OnSE → ECBS, with regression weights of 0.09 and 0.09, respectively, were not significant. The model itself is significant at 0.034 with a chi-square value of 8.681 and 3 df (the chi-square value for SEM type of analyses should not be significant if there is a good model fit to the data) (see Figure 2). The chi-sq is, however, too sensitive to sample size (Bentler and Bonnett (1980)). Instead, for the present research, the chi- sq/df ratio is being used to test the model fit (see Table 5). This ratio is less than 5, the threshold suggested by Hayduck (1987) to move forward with further analyses. Given that the sample size for the present research is small, the comparative fit index (CFI) is first used to test fit between the model and the data. The CFI value for the proposed model is.90 which satisfies the standard suggested by Hu and Bentler (1999). To further test the model-to-data fitness, the goodness-of-fit index (GFI) is used. The value for GFI for the model is 0.91 which surpasses a conservative value on.90 recom-
Building Business Value in E-Commerce Enabled Organizations
Figure 2. Results of the hypothesized model
Table 5. Model fit statistics Model
Chi sq/ df
CFI
GFI
IFI
M1: Hypothesized Model
2.89
0.90
0.91
0.91
M2: Independent Model
6.61
0.00
0.49
0.00
mended by Kline (1998). The final index reported in the present analysis is the incremental fit index (IFI). The IFI value for the present model is 0.91. A value above.90 is an acceptable fit. Aforementioned results related to the proposed model in Figure 2 reveal a good fit of the model to the data.
DISCUSSION Our results confirm H1, that IT alignment to Organizational Strategies (ITOrS) and InterOrganizational System Availability (IOrSA) are critical success factors for building business
value in e-commerce enabled organizations. The results show that evidence of strong decision making power of a chief information officer, strong structure for technology and planning, strong alignment of short term and long term IT strategy with top management strategy, and a positive technology learning environment results in more sophisticated systems integration within the organization. These results are supported by Barua, Konana, Whinston, and Yin (2001) when they indicated that the readiness of business partners to implement e-commerce technologies is critical to achieving business excellence and online systems efficiency. Our results are also supported by Segars and Grover (1998) when they suggested that paying attention to aligning IT strategy with business strategy, understanding the systems processes, and the support of management and end-user groups are crucial to IT planning success. In the same way, strong ITOrs result in a high quantity or percentage of online business and highly automated systems. Our results confirm that higher ITOrS is a critical success factor for achieving online systems efficiency (OnSE) (H2). Our results, as such, support Huselid and Becker’s (1997) suggestion about the existence of synergies between implementing efficient systems and their strategic alignment. Results of the present research study also support Lederer, Mirchandani, and Sims’ (2001) assertion that the efficiencies created by web-enabled systems affect strategic alignment positively by improving customer relations. Our results are also in line with Mukhopadhyay and Kekre’s (1995) findings on EDI at Chrysler that suggest that the EDI system has caused massive cost savings and has imparted system-wide discipline and generated integrative value for the company. Our results confirm that ITOrS is a critical success factor for Online System Quality and Effectiveness (OnSQE) (H3). In other words, the more a company’s IT is aligned to its parent organization’s strategies the more successful it will
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be in obtaining management support for creating higher quality and effective online presence. These results are in line with what is suggested in the literature. Peak and Guynes (2003, 2003-1), for example, point out that aligning IT with organizational strategies improves information quality which resulted in improved quality of products and services. Kowtha and Choon (2001) mention how the sophistication of a firm’s website reflects the strategic priorities of the firm. They further suggest that strategic commitment has substantive and high significant effects on website development. The results of the present research support the critical relationship between IT alignment to organizational strategies and e-commerce business success (ECBS) (H4) by finding that this relationship is significant and positive. This is also in line with what is suggested in the literature. Pollalis (2003), for example, confirms that alignment of IT to organizational strategies leads to better performance of banks. Sun and Hong (2002) find support in the literature for a significant and direct effect of strategic alignment on business performance in the field of manufacturing strategy. Burn and Szeto (1999) find that this alignment is critically important for business success. Our results also support the critical relationship between quality and effectiveness of online systems (OnSQE) and e-commerce business success (H7). We are, therefore, able to agree with Zhu and Kraemer (2002) when they pointed out that better e-commerce capability serves to improve the effectiveness of investments on e-commerce initiatives through firm performance. We are also in a position to agree with Chaudhury, Mallick, and Rao (2001) when they mentioned that enhancement of website quality can improve business value. The same goes for the study by Huang, Chen, and Frolick (2002) when they stated that evaluating web data quality is important to effectively determining the business value of online data. Our results do not support the relationship between inter-organizational system availability
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(IOrSA) and ECBS (H5) as critical success factors. We are, therefore, unable to support Bakos’ (1991) assertion that electronic marketplaces create interorganizational coordination and reduce search costs and increase economic efficiencies. We are also unable to concur with Kickul and Gundry’s (2001) argument that maintaining better relationships and integrating with suppliers is a crucial element of the company sustenance process. We are also unable to agree with Johnston and Vitale’s (1988) contention that, if carefully identified and used, inter-organizational systems give significant competitive advantages to organizations. Our results also do not support the path between online system efficiency and e-commerce business success (H6). It is not known why this path is not significant. One would normally expect for firms with efficient e-commerce systems to be at a relatively better position to achieve better business success. We are, therefore, unable to support Hitt and Brynjolfsson’s (1997) findings with regard to IT’s association with decentralization of authority, increased knowledge work, and decreased observability. We are also unable to agree with Stratopoulos and Dehning (2000) when they stated that firms making successful investments in IT are more successful at solving the productivity paradox than those that make failed or abortive investments in IT.
CONCLUSION In summary, our results clearly identify IT alignment to organizational strategies (ITOrS) and online system quality and effectiveness (OnSQE) as critical success factors toward achieving ebusiness success (ECBS). Our results also suggest that ITOrS impacts inter-organizational system availability (IOrSA), online system efficiency (OnSE), quality and effectiveness of online systems (OnSQE), and e-commerce business success (ECBS). Our results also suggest that OnSQE is a critical success factor towards ECBS.
Building Business Value in E-Commerce Enabled Organizations
Our results showed that IOrSA and OnSE played no significant role towards e-business success. It is obvious, at least according to the present research, the quality and effectiveness of these systems are much more important than their availability and efficiency. These relationships need to be investigated further in future research studies.
Implications of the Research The present research has revealed critical success factors for building business value in e-commerce enabled organizations. The research reveals to practioners that it is crucial to develop strong IT planning strategies for the implementation of e-commerce technologies within organizations. Organizations must understand that the increase in business value of the organization depends on the quality and effectiveness of the systems design.
Limitations and Future Research Although critical success factors for building business value in e-commerce enabled organizations have been identified, further research should include a study determining the strength of the relationships between the constructs as well as their validity across varied e-commerce sectors. The scope of the study should also be expanded in order to include a larger sample size.
ACKNOWLEDGMENT Special acknowledgement to Ritesh Mariadas, University of Texas at El Paso
REFERENCES Amit, R., & Zott, C. (2001). Value creation in e-business. Strategic Management Journal, 22, 493–520. doi:10.1002/smj.187
Arbuckle, J. L. (1989). AMOS: Analysis of moment structures. The American Statistician, 43, 66–67. doi:10.2307/2685178 Bakos, J. Y. (1991). A strategic analysis of electronic marketplaces. MIS Quarterly, 15(3), 295–310. doi:10.2307/249641 Bakos, J. Y. (1991). Information Links and Electronic Marketplaces: Implications of Interorganizational Information Systems in Vertical Markets. Journal of Management Information Systems, 8(2), 1991. Bakos, J. Y. (1997). Reducing buyer search costs: Implications for electronic marketplaces. Management Science, 43(12), 1676–1692. doi:10.1287/ mnsc.43.12.1676 Bakos, J. Y. (1998). The Emerging Role of Electronic Marketplaces on the Internet. Communications of the ACM, 41(8), 35–42. doi:10.1145/280324.280330 Banker, R. D., Kauffman, R. J., & Morey, R. C. (1990). Measuring gains in operational efficiency from information technology: A study of the positran deployment at Hardee’s Inc. Journal of Management Information Systems, 7(2), 29–54. Barua, A., Konana, P., Whinston, A. B., & Yin, F. (2001). Driving e-business excellence. MIT Sloan Management Review, 43(1), 36–44. Barua, A., Konana, P., Whinston, A. B., & Yin, F. (2001a). Measures for e-business value assessment. IT Pro, 35-39. Barua, A., Kriebel, C. H., & Mukhopadhyay, T. (1991). An economic analysis of strategic information technology investments. MIS Quarterly, 15(3), 313–331. doi:10.2307/249643 Barua, A., Kriebel, C. H., & Mukhopadhyay, T. (1995). Information technologies and business value: An analytic and empirical investigation. Information Systems Research, 6(1), 3–23. doi:10.1287/isre.6.1.3
245
Building Business Value in E-Commerce Enabled Organizations
Benjamin, R. I., & Scott, M. S. S. (1988). Information technology, integration, and organizational change. Interfaces, 18(3), 86–98. doi:10.1287/ inte.18.3.86
Chaudhury, A., Mallick, D. N., & Rao, H. R. (2001). Web channels in e-commerce. Communications of the ACM, 44(1), 99–104. doi:10.1145/357489.357515
Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88(3), 588–606. doi:10.1037/0033-2909.88.3.588
Chircu, A. M., & Kauffman, R. J. (2000). Limits to value in electronic commerce-related IT investments. Journal of Management Information Systems, 17(2), 59–80.
Brown, C. V. (2003). Performance metrics for IT human resource alignment. Information Systems Management, 20(4), 36–42. doi:10.1201/1078/4 3647.20.4.20030901/77291.6
Clemons, E., & Wang, Y. (2000). Special Issue: Technology Strategy for Electronic Marketplaces. Journal of Management Information Systems, 17(2), 5–7.
Brynjolfsson, E., & Hitt, L. (1993). Is information technology spending productive? New evidence and new results. In Proceedings of the 14th Annual International Conference on Information Systems.
Cron, W., & Sobol, M. (1983). The relationship between computerisation and performance: a strategy for maximising the economic benefits of computerisation. Information & Management, 6, 171–181. doi:10.1016/0378-7206(83)90034-4
Brynjolfsson, E., & Hitt, L. (1998). Beyond the productivity paradox. Communications of the ACM, 41(8), 41–55. doi:10.1145/280324.280332 Brynjolfsson, E., & Kahim, B. (Eds.). (2000). Understanding the Digital Economy. Cambridge: MIT Press. Burn, J. M., & Szeto, C. (1999). A comparison on the views of business and IT management on success factors for strategic alignment. Information & Management, 37(4), 197–216. doi:10.1016/ S0378-7206(99)00048-8 Campbell, & Fiske (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81-105. Cao, M., Zhang, Q., & Seydel, J. (2005). B2C e-commerce web site quality: an empirical examination. Industrial Management & Data Systems, 105(5), 645–661. doi:10.1108/02635570510600000 Chan, Y. E. (2000). IT value: The great divide between qualitative and quantitative and individual and organizational measures. Journal of Management Information Systems, 16(4), 225–261.
246
Customer Care - Best Practices @ Cisco. (2001). Retrieved 2001, from http://www.cisco.com/warp/ public/779/ibs/solutions/customer/practices/ Dai, Q., & Kauffman, R. J. (2002). Business models for internet-based B2B electronic markets. International Journal of Electronic Commerce, 6(4), 41–72. Dai, Q., & Kauffman, R. J. (2002). B2B E-Commerce Revisited: Leading Perspectives on the Key Issues and Research Directions. Electronic Markets, 12(2). Davern, M. J., & Kauffman, R. J. (2000). Discovering potential and realizing value from information technology investments. Journal of Management Information Systems, 16(4), 121–143. Dehning, B., & Richardson, V. J. (2002). Returns on investments in information technology: A research synthesis. Journal of Information Systems, 16(1), 7–30. doi:10.2308/jis.2002.16.1.7 Dekleva, S. (2000). Electronic commerce: A halfempty glass. Communications of the Association for Information Systems, 3(18).
Building Business Value in E-Commerce Enabled Organizations
DeLone, W. H., & McLean, E. R. (1992). Information systems success: The quest for the dependent variable. Information Systems Research, 3(1), 60–95. doi:10.1287/isre.3.1.60 Dos Santos, B. L., Peffers, K., & Mauer, D. C. (1993). The impact of information technology investment announcements on the market value of the firm. Information Systems Research, 4(1), 1–23. doi:10.1287/isre.4.1.1 Dos Santos, B. L., & Sussman, L. (2000). Improving the return on IT investment: the productivity paradox. International Journal of Information Management, 20, 429–440. doi:10.1016/S02684012(00)00037-2 e-Marketer (June, 2008). June 2008: U.S. Retail E-Commerce. Retrieved 2008 from http://www. iab.net/insights_research/530422/1675/334589. Epstein, M. J. (2000). Organizing your business for the internet evolution. Strategic Finance, 82(1), 56–60. Feeny, D. F., & Ives, B. (1990). In search of sustainability: Reaping long-term advantage from investments in information technology. Journal of Management Information Systems, 7(1), 27–46. Fornell, C., & Larker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. JMR, Journal of Marketing Research, 18(1), 39–50. doi:10.2307/3151312 Gefen, D., & Straub, D. W. (2000). The relative importance of perceived ease of use in IS adoption: A study of e-commerce adoption. Journal of the Association for Information Systems, 1(8). Gurbaxani, V., & Mendelson, H. (2001). An Integrative Model of Information Systems Spending Growth. Information Systems Research, 1(1), 23–46. doi:10.1287/isre.1.1.23
Hair, J. F., Anderson, R. E., Tatham, R. L. T., & Black, W. C. (1998). Multivariate data analysis. Upper Saddle River, NJ: Prentice-Hall Inc. Hitt, L. M., & Brynjolfsson, E. (1994). The Three Faces of IT Value: Theory and Evidence. In Proceedings of the International Conference on Information Systems (pp. 263-277). Hitt, L. M., & Brynjolfsson, E. (1997). Information technology and internal firm organization: An exploratory analysis. Journal of Management Information Systems, 14(2), 81–101. Huang, Z., Chen, L., & Frolick, M. N. (2002). Integrating web-based data into a data warehouse. Information Systems Management, 19(1), 23–34. doi:10.1201/1078/43199.19.1.20020101/31473.4 Huselid, M. A., & Becker, B. E. (1997). The impact high performance work systems, implementation effectiveness, and alignment with strategy on shareholder wealth. Academy of Management Proceedings (pp. 144-148). Im, K. S., Dow, K. E., & Grover, V. (2001). Research report: A reexamination of IT investment and the market value of the firm - An event study methodology. Information Systems Research, 12(1), 103–117. doi:10.1287/isre.12.1.103.9718 Johnson, C. A., et al. (2003). US eCommerce Overview: 2003 - 2008. Cambridge, MA: Forrester Research, Inc. Johnson, J., Boucher, K., Connors, K., & Robinson, J. (2001). Collaboration: Development and Management Collaborating of Project Success. Software Magazine. Retrieved from http://www. softwaremag.com/archive/2001feb/CollaborativeMgt.html Johnson, J., Boucher, K. D., Conners, K., & Robinson, J. (2001). The Criteria for Success. Software Magazine, 21(1), s3–s11.
247
Building Business Value in E-Commerce Enabled Organizations
Johnston, H. R., & Vitale, M. R. (1988). Creating competitive advantage with interorganizational information systems. MIS Quarterly, 152–165. Josefek, R. A. Jr, & Kauffman, R. J. (1997). Dark pockets and decision support: The information technology value cycle in efficient markets. Electronic Markets, 7(3), 36–42. doi:10.1080/10196789700000036 Kao, D., & Decou, J. (2003). A strategy-based model for e-commerce planning. Industrial Management & Data Systems, 103(4), 238–252. doi:10.1108/02635570310470638 Kauffman, R. J., & Kriebel, C. H. (1988). Modeling and measuring the business value of information technologies. In P.A. Strassman, P. Berger, E.B. Swanson, C.H. Kriebel and R.J. Kauffman (Eds.), Measuring the Business value of Information Technologies. Washington, D.C.: ICIT Press. Keeney, R. L. (1999). The value of internet commerce to the customer. Management Science, 45(4), 533–542. doi:10.1287/mnsc.45.4.533 Kickul, J., & Gundry, L. K. (2001). Breaking through boundaries for organizational innovation: New managerial roles and practices in e-commerce firms. Journal of Management, 27, 347–361. doi:10.1016/S0149-2063(01)00095-2 Kim, C. S., & Peterson, D. K. (2001). Developers’ perceptions of information systems success factors. Journal of Computer Information Systems, 41(2), 29–36. Kline, R. B. (1998). Principles and Practice of Structural Equation Modeling. New York: Guilford Press. Kowtha, N. R., & Choon, T. W. I. (2001). Determinants of website development: a study of electronic commerce in Singapore. Information & Management, 39(3), 227–242. doi:10.1016/ S0378-7206(01)00092-1
248
Kraemer, K. L., & Dedrick, J. (2002). Strategic use of the Internet and e-commerce: Cisco Systems. The Journal of Strategic Information Systems, 11, 5–29. doi:10.1016/S0963-8687(01)00056-7 Kurnia, S., & Johnston, R. (2005). The Dynamic Interactional Model of Inter-Organizational System Adoption: The Case of Category Management Adoption in Australia, Asia Pacific. Management Review, 10(1). Lederer, A. L., Maupin, D. J., Sena, M. P., & Zhuang, Y. (2000). The technology acceptance model and the world wide web. Decision Support Systems, 28, 269–282. doi:10.1016/S01679236(00)00076-2 Lederer, A. L., Mirchandani, D. A., & Sims, K. (2001). The Search for Strategic Advantage from the World Wide Web. International Journal of Electronic Commerce, 5(4), 117–133. Lee, B., & Barua, A. (1999). An integrated assessment of productivity and efficiency impacts of information technology investments: Old data, new analysis and evidence. Journal of Productivity Analysis, 12, 21–43. doi:10.1023/A:1007898906629 Lee, H. G., & Clark, T. H. (1997). Market process reengineering through electronic market systems: Opportunities and challenges. Journal of Management Information Systems, 13(3), 113–136. Liu, C., Arnett, K. P., & Litecky, C. (2000). Design quality of websites for electronic commerce: fortune 1000 webmasters’ evaluations. Electronic Markets, 10(2), 120–129. doi:10.1080/10196780050138173 Mahajan, & Peterson, R. A. (1985). Models for Innovation Diffusion. SAGE Publications, Inc. Mahmood, M. A., Gemoets, L., Lopez, F., & Hall, L. (2008). Measuring E-Commerce Technology Enabled Business value: An Exploratory Research. International Journal of E-Business Research, 4(2), 48–68.
Building Business Value in E-Commerce Enabled Organizations
Mahmood, M. A., Hall, L., & Swanberg, D. (2001). Factors affecting information technology usage: A meta-analysis of the empirical literature. Journal of Organizational Computing and Electronic Commerce, 11(2), 107–130. doi:10.1207/ S15327744JOCE1102_02 Mahmood, M. A., & Mann, G. J. (1993). Measuring the organizational impact of information technology investment: An exploratory study. Journal of Management Information Systems, 10(1), 97–122. Mahmood, M. A., & Mann, G. J. (2000). Impacts of information technology investment on organizational performance. Journal of Management Information Systems, 17(1), 3–10. Mahmood, M. A., & Sniezek, J. A. (1989). Defining Decision Support Systems: An Empirical End-User Assessment. INFOR -- Canadian Journal of Operational Research and Information Processing, 27, 253-271. McIlvaine, B. (2000). John Chambers. Electronic Buyers’. News, 1242, 42. Melville, N., Kraemer, K., & Gurbaxani, V. (2004). Information Technology and Organizational Performance: An Integrative Model of IT Business value. MIS Quarterly, 23(2), 165–173. Molla, A., & Licker, P. S. (2001). E-Commerce Systems Success: An Attempt to Extend and Respecify the Delone and Maclean Model of IS Success. Journal of ECommerce Research, 2(4). Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a world-wide-web context. Information & Management, 38, 217–230. doi:10.1016/S03787206(00)00061-6 Mukhopadhyay, T., & Kekre, S. (1995). Business value of information technology: A study of electronic data interchange. MIS Quarterly, 19(2), 137–156. doi:10.2307/249685
Nunnally, J. C. (1978). Psychometric theory (2nd Ed.). New York: McGraw-Hill. Pather, S., Erwin, G., & Remenyi, D. (2003). Measuring e-Commerce effectiveness: a conceptual model. In J. Eloff, A. Engelbrecht, P. Kotzé, & M. Eloff (Eds.), Proceedings of the 2003 Annual Research Conference of the South African institute of Computer Scientists and information Technologists on Enablement Through Technology (September 17-19, 2003) (pp.143-152). ACM Press. Peak, D., & Guynes, C. S. (2003). The IT alignment planning process. Journal of Computer Information Systems, 44(1), 9–15. Peak, D., & Guynes, C. S. (2003). Improving information quality through IT alignment planning: a case study. Information Systems Management, 20(4), 22–29. doi:10.1201/1078/43647.20.4.200 30901/77289.4 Peteraf, M. A. (2000). The cornerstones of competitive advantage: A resource-based view. Strategic Management Journal, 14(3), 179–191. doi:10.1002/smj.4250140303 Pollalis, Y. A. (2003). Patterns of co-alignment in information-intensive organizations: business performance through integration strategies. International Journal of Information Management, 23(6), 469–492. doi:10.1016/S0268-4012(03)00063-X Reich, B. H., & Benbasat, I. (2000). Factors that influence the social dimensions of alignment between business and information technology objectives. MIS Quarterly, 24(1), 81–113. doi:10.2307/3250980 Reichheld, F. F. (2001). Lead for Loyalty. Harvard Business Review, 79(7), 76–84. Riggins, F. J., & Mukhopadhyay, T. (1994). Interdependent benefits from interorganizational systems: Opportunities for. Journal of Management Information Systems, 11(2), 37–57.
249
Building Business Value in E-Commerce Enabled Organizations
Rogers, E. M. (1983). Diffusion of innovations, New York: The Free Press.
Strassman, P. (1990). The Business value of Computers. The Economic Press.
Rose, G. M., & Straub, D. W. (1999). The Effect of Download Time on e-Commerce: The Download Time Brand Impact Model. In Proceedings of the Ninth Workshop on Information Technologies and Systems (pp. 167-172).
Stratopoulos, T., & Dehning, B. (2000). Does successful investment in information technology solve the productivity paradox? Information & Management, 38, 103–117. doi:10.1016/S03787206(00)00058-6
Sanders, N. R., & Premus, R. (2002). IT applications in supply chain organizations: a link between competitive priorities and organizational benefits. Journal of Business Logistics, 23(1), 65–83.
Subramani, M., & Walden, E. (2001). The impact of e-commerce announcements on the market value of firms. Information Systems Research, 12(2), 135–154. doi:10.1287/isre.12.2.135.9698
Segars, A. H., & Grover, V. (1998). Strategic information systems planning success: An investigation of the construct and its measurement. MIS Quarterly, (June): 139–163. doi:10.2307/249393
Sun, H., & Hong, C. (2002). The alignment between manufacturing and business strategies: its influence on business performance. Technovation, 22(11), 699–705. doi:10.1016/S01664972(01)00066-9
Shao, B. B. M., & Lin, W. T. (2001). Measuring the value of information technology in technical efficiency with stochastic production frontiers. Information and Software Technology, 43, 447–456. doi:10.1016/S0950-5849(01)00150-1 Shao, B. B. M., & Lin, W. T. (2002). Technical efficiency analysis of information technology investments: a two-stage empirical investigation. Information & Management, 39, 391–401. doi:10.1016/S0378-7206(01)00105-7 Shin, N. (2001). Strategies for competitive advantage in electronic commerce. Journal of Electronic Commerce Research, 2(4), 34–41. Siau, K. (2003). Interorganizational systems and competitive advantages - lessons from history. Journal of Computer Information Systems, 44(1), 33–39. Steinfield, C., Marcus, M. L., & Wigand, R. (2005). Exploring Interorganizational Systems at the Industry Level of Analysis: Evidence from the U.S. Home Mortgage Industry. Journal of Information Technology, 20(4). doi:10.1057/ palgrave.jit.2000051
250
Teo, T. S. H., & Ang, J. S. K. (1999). Critical success factors in the alignment of IS plans with business plans. International Journal of Information Management, 19, 173–185. doi:10.1016/ S0268-4012(99)00007-9 Teo, T. S. H., & Ang, J. S. K. (2000). How useful are strategic plans for information systems? Behaviour & Information Technology, 19(4), 275–282. doi:10.1080/01449290050086381 Teo, T. S. H., & Ang, J. S. K. (2001). An examination of major IS planning problems. International Journal of Information Management, 21, 457–470. doi:10.1016/S0268-4012(01)00036-6 Teo, T. S. H., & King, W. R. (1996). Assessing the impact of integrating business planning and IS planning. Information and Management, 30, 309-321. Teo, T. S. H., & King, W. R. (1997). Integration between business planning and information systems planning: An evolutionary-contingency perspective. Journal of Management Information Systems, 14(1), 185–214.
Building Business Value in E-Commerce Enabled Organizations
Thomas, D. (2003). Supermarket boosts efficiency tenfold by integrating systems. Computer Weekly, 2/20/2003, 12. Tsay, A., & Agrawal, N. (2004). Channel Conflict and Coordination in the E-Commerce Age. Production and Operations Management, 13(1), 93–110. Turban, E., King, D., Lee, J., Warkentin, M., & Chung, H. M. (2002). Electronic Commerce 2002: A Managerial Perspective. Upper Saddle River, NJ: Pearson Education. Wold, H. (1989). Introduction to the Second Generation of Multivariate Analysis. In H. Wold (Ed.), Theoretical Empiricism (pp. vii-xl). New York: Paragon House. Woo, C. Y., & Willard, G. E. (1983). Performance representation in business policy research: discussion and recommendation. Paper presented at the 23rd Annual National Meetings of the Academy of Management, Dallas. Zhang, P., & Von Dran, G. M. (2001). Expectations and rankings of website quality features: Results of two studies on user perceptions. In Proceedings of the 34th Hawaii International Conference on System Sciences, HICSS-34(7), 7019.
Zhang, P., Von Dran, G. M., Small, R. V., & Barcellos, S. (1999). Websites that Satisfy Users: A Theoretical Framework for Web User Interface Design and Evaluation. In Proceedings of the 32nd Hawaii International Conference on System Sciences, HICSS-32(2), 2016. Zhang, P., Von Dran, G. M., Small, R. V., & Barcellos, S. (2000). A Two-Factor Theory for Website Design. In Proceedings of the 33rd Hawaii International Conference on System Sciences, HICSS-33(6), 6026. Zhu, K. (2004). The Complementarity of Information Technology Infrastructure and E-Commerce Capability: A Resource Based Assessment of their Business value. Journal of Management Information Systems, 21(1), 187–202. Zhu, K., & Kraemer, K. L. (2002). e-Commerce metrics for net-enhanced organizations: Assessing the value of e-Commerce to firm performance in the manufacturing sector. Information Systems Research, 13(3), 275–295. doi:10.1287/ isre.13.3.275.82 Zott, C., Amit, R., & Donlevy, J. (2000). Strategies for value creation in e-commerce: Best practice in europe. European Management Journal, 18(5), 463–475. doi:10.1016/S0263-2373(00)00036-0
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APPENDIX Success Factors of Internet Enabled Business Questionnaire (On a Likert Scale with values ranging from 1, strongly disagree, to 7, strongly agree)
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IT Alignment to Organizational Strategies (ITOrS) 1. There is an alignment of information technology (IT) strategy and top management strategy 2. There is agreement within the company that information technology is part of long term strategy 3. The Chief Information Officer has significant decision-making power 4. There is a strong structure within the company for information technology planning and implementation 5. There is a positive environment for organizational learning associated with the use of new information technology Inter-Organizational Systems Availability (IOrSA) 6. An Internet-enabled uniform system of information sharing is available 7. An automatic change order system is available 8. The system permits highly automated transmitting and processing of data 9. Inventory and Purchase tracking systems are continuously monitored 10. The online procurement system is satisfactory 11. Internet expertise is a selection criteria for suppliers/vendors Online Systems Quality and Effectiveness (OnSQE) 12. The website used for purchasing and customer relations is highly secure 13. The website used for purchasing and customer relations is visually attractive 14. The website used for purchasing and customer relations is easily navigable 15. The website used for purchasing and customer relations offers personalized logons 16. The website used for purchasing and customer relations is consistently accessible without experiencing loading delays Online Systems Efficiency (OnSE) 17. There is a high quantity or percentage of online business 18. Online customer service is available 19. Customers requests are resolved online 20. Continuous monitoring of orders is available 21. A highly automated order tracking system is available E-commerce business success (ECBS) 22. Return on Investment has increased 23. Return on Sales has increased 24. Growth in Net Revenue has increased 25. Net Income over Invested Capital has increased 26. Sales over total assets has increased 27. Return on Sales per employee has increased 28. The organization has a positive company image
Building Business Value in E-Commerce Enabled Organizations
29. Customer satisfaction is high 30. The organization engages in product/service innovation 31. There are a large number of return customers Organizational Characteristics Company Name Location Primary products Circle all that applies. Does your business do…? Business to Business Business to Consumer Consumer to Consumer Annual sales (US $ billions) 0 division. (8)
Defuzzification Defuzzification is a technique to convert a fuzzy number into a crisp real number. There are several methods to serve this purpose. For example, the Centre-of-Area method (Tsaur et al., 2002) converts a fuzzy number P = (a, b, c) into a crisp real number Q where Q=
(c − a ) + (b − a ) +a 3
(9)
Defuzzification might become necessary in two situations: (i) When comparison between two or more fuzzy numbers is difficult to perform, and (ii) When a fuzzy number to be operated on has negative parameters (in other words, we make sure that upon performing an arithmetic operation on one or more TFNs, we get a TFN only; for example, squaring TFN (-1, 0, 1) using Equation 7 will lead to (1, 0, 1) that is not a TFN and so, we defuzzify (-1, 0, 1) before squaring it).
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Reverse Supply Chain Design
TOPSIS Method The basic concept of the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method (Triantaphyllou & Lin, 1996) is that the rating of the alternative selected as the best from a set of different alternatives, should have the shortest distance from the ideal solution and the farthest distance from the negative-ideal solution in a geometrical (i.e., Euclidean) sense. The TOPSIS method evaluates the following decision matrix, which refers to m alternatives that are evaluated in terms of n criteria (see Figure 5).where Ai is the ith alternative, Cj is the jth criterion, wj is the weight (importance value) assigned to the jth criterion, and zij is the rating (e.g., on a scale of 1-10, the higher the rating, the better it is) of the ith alternative in terms of the jth criterion.The following steps are performed: Step 1: Construct the normalized decision matrix. This step converts the various dimensional measures of performance into nondimensional attributes. An element rij of the normalized decision matrix R is calculated as follows: rij =
zij
∑ i =1 zij2
Figure 5.
362
m
(10)
Step 2: Construct the weighted normalized decision matrix. A set of weights W = (w1, w2, … wn) (such that ∑wj = 1), specified by the decisionmaker, is used in conjunction with the normalized decision matrix R to determine the weighted normalized matrix V defined by V = (vij) = (rijwj). Step 3: Determine the ideal and the negativeideal solutions. The ideal (A*) and the negativeideal (A-) solutions are defined as follows:
{
A* = max vij i
}
for i = 1, 2, 3, ....., m (11)
= {p1, p2, p3, ….., pn}
{
A− = min vij i
}
for i = 1, 2, 3, ....., m (12)
= {q1, q2, q3, …..., qn} With respect to each criterion, the decisionmaker desires to choose the alternative with the maximum rating (it is important to note that this choice varies with the way he or she awards ratings to the alternatives). Obviously, A* indicates the most preferable (ideal) solution. Similarly, A- indicates the least preferable (negative-ideal) solution.
Reverse Supply Chain Design
Step 4: Calculate the separation distances. In this step, the concept of the n-dimensional Euclidean distance is used to measure the separation distances of the rating of each alternative from the ideal solution and the negative-ideal solution. The corresponding formulae are Si * =
∑ (v
ij
− pj )2
for i = 1, 2, 3, ..., m
(13)
where Si* is the separation (in the Euclidean sense) of the rating of alternative i from the ideal solution, and Si − =
∑ (v
ij
− qj )2
for i = 1, 2, 3, ..., m
(14)
where Si- is the separation (in the Euclidean sense) of the rating of alternative i from the negativeideal solution. Step 5: Calculate the relative coefficient. The relative closeness coefficient for alternative Ai with respect to the ideal solution A* is defined as follows: Si − Ci* = Si * +Si −
(15)
Step 6: Rank the preference order. The best alternative can now be decided according to preference order of Ci*. It is the one with the rating that has the shortest distance to the ideal solution. The way the alternatives are processed in the previous steps reveals that if an alternative has the rating with the shortest distance to the ideal solution, then that rating is guaranteed to have the longest distance to the negative-ideal solution. That means, the higher the Ci*, the better the alternative.
Borda’s Choice Rule Borda (Hwang, 1987) proposed a rank-order method for group decision-making in which marks of m-1, m-2, ……., 1, 0 are assigned to the first ranked, second ranked, ……, last ranked alternative, for each decision maker (group, in our case). That means that a larger mark corresponds to more importance. Borda score (maximized consensus rating) for each alternative is then determined as the sum of the individual marks for that alternative. Then, the alternative with the highest Borda score is declared the winner. That means that the different decision makers unanimously choose the alternative that obtains the largest Borda score as the most preferred one. Besides the above techniques, some concepts of constructing and training a neural network are implemented in phase II of our approach. Introduction to those concepts is beyond the scope of this chapter. The reader is referred to any of the hundreds of introductory neural network books available in the literature.
EVALUATION OF EFFICIENCIES OF COLLECTION FACILITIES In this section, we present our four-phase approach to evaluate the efficiency of a collection facility of interest, through a numerical example. Phases I, II, III, and IV are presented.
Phase-I of the Approach We consider the following sets of criteria for the three groups, for evaluating the efficiency of a collection facility of interest:
Consumers •
Incentives from collection facility (IC) (higher incentives imply higher motivation to participate)
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•
• •
• •
Proximity to the residential area (PH) (higher proximity implies more motivation to participate) Proximity to roads (PR) (higher proximity implies more motivation to participate) Simplicity of the collection process (SP) (simpler process implies more motivation to participate) Employment opportunity (EO) (the more the better) Salary (SA) (the higher the better)
Local Government Officials •
•
Proximity to residential area (PH) (higher proximity implies greater collection and hence lower disposal) Proximity to roads (PR) (higher proximity implies greater collection and hence lower disposal)
Supply Chain Company Executives •
• • • •
•
•
364
Per capital income of the people in the residential area (PI) (the higher it is, the more the number of “resourceful” used products, and the less the people will care about the incentives from the collection facility) Space cost (SC) (the lower the better) Labor cost (LC) (the lower the better) Utilization of incentives from local government (UI) (the higher the better) Proximity to residential area (PH) (higher proximity implies greater collection and hence greater profit) Proximity to roads (PR) (higher proximity implies greater collection and hence greater profit) Incentives from local government (IG) (higher incentives from local government imply higher incentives to consumers)
Phase-II of the Approach Suppose that we have the linguistic ratings of 10 existing collection facilities, as given by an expert in each group described in phase I. Using the fuzzy set theory, these linguistic ratings are converted into TFNs (fuzzy ratings). Table 1 shows not only one of the many ways for conversion of linguistic ratings into TFNs but also the defuzzified ratings of the corresponding TFNs. Tables 2, 3, and 4 show the defuzzified overall rating of each existing collection facility, as well as its (collection facility’s) defuzzified rating with respect to each criterion, as evaluated by the consumers, the local government officials, and the supply chain company executives, respectively.
Table 1. Conversion table for ratings Linguistic rating
TFN
Defuzzified rating
Very Good (VG)
(7, 10, 10)
9
Good (G)
(5, 7, 10)
7.3
Fair (F)
(2, 5, 8)
5
Poor (P)
(1, 3, 5)
3
Very Poor (VP)
(0, 0, 3)
1
Table 2. Consumer ratings of existing collection facilities Collection Facility
IC
PH
PR
SP
EO
SA
Overall
C1
1
3
5
3
5
9
5
C2
9
1
3
5
7.3
9
7.3
C3
3
1
3
1
9
1
3
C4
3
9
1
7.3
1
7.3
5
C5
5
1
3
5
1
3
7.3
C6
9
3
7.3
3
5
7.3
3
C7
5
7.3
9
1
7.3
9
1
C8
1
5
1
5
3
1
9
C9
1
5
5
9
9
5
5
C10
5
9
5
3
9
3
1
Reverse Supply Chain Design
Table 3. Local government officials ratings of existing collection facilities Collection Facility
PH
PR
Overall
C1
1
3
5
C2
9
1
7.3
C3
3
1
3
C4
3
9
5
C5
5
1
7.3
C6
9
3
3
C7
5
7.3
1
C8
1
5
9
C9
1
5
5
C10
5
9
1
Table 4. Supply chain company executives’ratings of existing collection facilities Collection Facility
PI
SC
LC
UI
PH
PR
IG
Overall
C1
1
3
1
3
5
1
3
5
C2
9
1
3
7.3
3
5
7.3
7.3
C3
3
1
7.3
9
1
7.3
9
3
C4
3
9
5
1
5
3
1
5
C5
5
1
5
5
9
9
5
7.3
C6
9
3
9
5
3
9
3
3
C7
5
7.3
3
1
7.3
9
1
1
C8
1
5
1
3
1
3
5
9
C9
1
5
3
5
9
9
1
5
C10
5
9
1
3
5
7.3
7.3
1
sidered by the corresponding group. For example, Figure 6 shows the neural network constructed and trained for the group of consumers. After each neural network is trained, Equation 16 (Cha & Jung, 2003) is used to calculate the impacts of criteria considered by the corresponding group. Here, absolute value of Wvk is the impact of the vth input node upon kth output node, nV is the number of input nodes, nO is the number of output nodes (one, in our case), nH is the number of hidden nodes, Iij is the connection weight from the ith input node to the jth hidden node, and Ojk is the connection weight from the jth hidden node to the kth output node. Ivj ∑ nV Ojk j ∑ Iij i | Wvk |= nV nH Ivj O jk ∑ ∑ nV v j I ij ∑ i nH
(16)
Tables 5, 6, and 7 show the impacts of the criteria considered by the consumers, the local government officials, and the supply chain company executives, respectively. Figure 6. Neural network for consumers (Phase II)
A neural network is constructed and trained for each group, using the defuzzified ratings of the existing collection facilities with respect to criteria as input sets, and their (collection facilities) defuzzified overall ratings as corresponding outputs. In our example, there are 10 input-output pairs for each neural network because there are 10 existing collection facilities. Also, we consider three layers in each network, with 5 nodes in the hidden layer. The number of nodes in the output layer is one (for overall rating), and that in the input layer is the number of criteria con-
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Reverse Supply Chain Design
Table 5. Impacts of criteria of consumers Criterion
IC
PH
PR
SP
EO
SA
Impact
0.01
0.13
0.06
0.18
0.19
0.43
rating of collection facility, C12, with respect to criterion, PH (see Tables 8 and 10), is calculated using Equation 10 as follows: r22 =
Table 6. Impacts of criteria of local government officials Criterion
PH
PR
Impact
0.33
0.67
Table 7. Impacts of criteria of supply chain company executives Criterion
PI
SC
LC
UI
PH
PR
IG
Impact
0.24
0.09
0
0.18
0.25
0.1
0.13
Phase-III of the Approach Suppose that there are three collection facilities, C11, C12, and C13, of interest. We employ a fuzzy TOPSIS (Chu, 2002) approach that uses the weights obtained in phase-II, to calculate the overall ratings of the three collection facilities. The decision matrices formed by the consumers, the local government officials, and the supply chain company executives (with defuzzified ratings for C11, C12, and C13) in this example are shown in Tables 8, 9, and 10, respectively (we use Table 1 here too, to convert linguistic ratings given by each group into TFNs). Now, we are ready to perform the six steps in the TOPSIS for each group. The following steps show the implementation of the TOPSIS for the consumers, to evaluate C11, C12, and C13. Step 1: Construct the normalized decision matrix. Table 11 shows the normalized decision matrix formed by applying Equation 10 on each element of Table 8 (decision matrix formed by the consumers). For example, the normalized
366
1 92 + 12 + 32
= 0.105.
Step 2: Construct the weighted normalized decision matrix. Table 12 shows the weighted normalized decision matrix for the consumers. This is constructed using the impacts of the criteria listed in Table 5 and the normalized decision matrix in Table 11. For example, the weighted normalized rank of collection facility, C12, with respect to criterion, PH, that is, 0.014 (see Table 12), is calculated by multiplying the impact of PH, that is, 0.129 (see Table 5) with the normal-
Table 8. Decision matrix formed by consumers Collection Facility
IC
PH
PR
C11
3
9
1
7.33
SP
1
EO
7.33
SA
C12
5
1
3
5
1
3
C13
9
3
7.33
3
5
7.33
Table 9. Decision matrix formed for local government officials Collection Facility
PH
PR
C11
3
9
C12
5
1
C13
9
3
Table 10. Decision matrix formed by supply chain company executives Collection Facility
PI
SC
LC
UI
C11
5
1
5
5
C12
9
3
9
C13
5
7.33
3
PH
PR
IG
9
9
5
5
3
9
3
1
7.33
9
1
Reverse Supply Chain Design
Table 11. Normalized decision matrix formed by consumers for collection facilities Collection Facility
IC
PH
PR
SP
EO
SA
C11
0.278
0.943
0.125
0.783
0.192
0.679
C12
0.466
0.105
0.376
0.534
0.192
C13
0.839
0.314
0.918
0.320
0.962
Table 12. Weighted normalized decision matrix formed by consumers for collection facilities IC
PH
PR
SP
EO
SA
C11
0.004
0.122
0.007
0.140
0.036
0.294
0.278
C12
0.006
0.014
0.022
0.095
0.036
0.120
0.679
C13
0.011
0.041
0.053
0.057
0.181
0.294
ized rating of C12 with respect to PH, that is, 0.105 (see Table 11). Step 3: Determine the ideal and the negativedeal solution. Each column in the weighted normalized decision matrix shown in Table 12 has a maximum rating (found using Equation 11) and a minimum rating (found using Equation 12). They are the ideal and the negative-ideal solutions, respectively, for the corresponding criterion. For example (see Table 12), with respect to criterion, PH, the ideal solution (maximum rating) is 0.122, and the negative-ideal solution (minimum rating) is 0.014. Step 4: Calculate the separation distances. The separation distances (see Table 13) for each collection facility, are calculated using Equations 13 and 14. For example, the positive separation distance for collection facility, C12 (see Table 13), is calculated using Equation 13 that contains the weighted normalized ratings of C12 (see Table 12) and the ideal solutions (obtained in step 3) for the criteria. Step 5: Calculate the relative closeness coefficient. Using Equation 15, we calculate the relative closeness coefficient for each collection facility (see Table 14). For example, relative closeness coefficient (i.e., 0.137) for collection facility C12 (see Table 14) is the ratio of C12’s negative separation distance (i.e., 0.041) to the sum (i.e., 0.041 + 0.257 = 0.298) of its negative and positive separation distances (see Table 13). Step 6: Rank the preference order. Since the best alternative is the one with the highest relative closeness coefficient, the preference order for the
Collection Facility
Table 13. Separation distances calculated by consumers for collection facilities Collection Facility
S*
S-
C11
0.152
0.221
C12
0.257
0.041
C13
0.116
0.233
Table 14. Relative closeness coefficients calculated byconsumers for collection facilities Collection Facility
C*
C11
0.592
C12
0.137
C13
0.668
collection facilities is C13, C11, and C12 (that means, C13 is the best collection facility, as evaluated by the consumers). The TOPSIS is implemented for the local government officials and the supply chain company executives as well. The relative closeness coefficients of the collection facilities, as calculated by those two groups, are shown in Table 15.
Phase-IV of the Approach Table 16 shows the marks of the collection facilities as given using Borda’s choice rule (Hwang, 1987) for the consumers, the local government officials, and the supply chain company executives. Borda scores (maximized consensus rating) calculated for C11, C12, and C13 (viz., 5, 1, and 3,
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Reverse Supply Chain Design
Table 15. Relative closeness coefficients calculated by local government and supply chain company for collection facilities Collection Facility
Local govt.
Consumers •
Supply chain company
C11
0.754
0.619
C12
0.096
0.502
C13
0.354
0.415
•
•
Table 16. Marks and Borda scores of collection facilities Collection Facility
Consumers
Local government
Supply chain company
Borda score
C11
1
2
2
5
C12
0
0
1
1
C13
2
1
0
3
respectively) are also shown. For example, Borda score for C12 (i.e., 1) is calculated by summing the marks of C12 for the consumers, the local government officials, and the supply chain company executives (i.e., 0 + 0 + 1). Since C11 has the highest Borda score, it is the best of the lot.
EVALUATION OF EFFICIENCIES OF RECOVERY FACILITIES In this section, we present only the first phase of our approach to evaluate the efficiency of a recovery facility of interest because the remaining three phases are similar to the ones for a collection facility. We consider the following sets of criteria for the three groups, for evaluating the efficiency of a recovery facility of interest:
•
Proximity to surface water (PS) (lower proximity implies more suitability, that is, less hazardous) Proximity to residential area (PH) (lower proximity implies more suitability, that is, less hazardous) Employment opportunity (EO) (the more the better) Salary (the higher the better)
Local Government Officials •
•
Proximity to surface water (PS) (lower proximity implies more suitability, that is, less hazardous) Proximity to residential area (PH) (lower proximity implies more suitability, that is, less hazardous)
Supply Chain Company Executives • • • •
• • • •
Space cost (SC) (the lower the better) Labor cost (LC) (the lower the better) Proximity to roads (PR) (higher proximity implies easier transportation) Quality of reprocessed products (QO) – Quality of used-products (QI) (the higher the better) Throughput (TP) /Supply (SU) (the higher the better) Throughput (TP) * Disassembly time (DT) (the higher the better) Utilization of incentives from local government (UI) (the higher the better) Pollution control (PC) (the higher the better)
Unlike in a forward supply chain, components of incoming goods (used-products) of even the same type in a recovery facility are likely to be of varied quality (worn-out, low-performing, etc.). Though
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Reverse Supply Chain Design
the average quality of reprocessed goods (QO) is a criterion that can evaluate a recovery facility, it is not justified to use QO as an independent criterion for evaluation because QO depends on average quality of incoming products (QI). However, QI must not be taken as an independent criterion too because it cannot evaluate the recovery facility. So, the idea is to take the difference between QO and QI as a criterion for evaluation. The only driver to design a forward supply chain is the demand for new products and so if there is low demand for new products, there is practically no forward supply chain. However, this is not the case in some reverse supply chains where even if there is a low supply of used-products (SU), reverse supply chain must be administered due to the possible drivers like environmental regulations and asset recovery. In supply-driven cases like these, it is unfair to judge a recovery facility without considering SU for evaluation. Although throughput (TP) is a criterion that can evaluate a recovery facility, it is not justified to use TP as an independent criterion because TP depends on SU. However, SU must not be taken as an independent criterion too because it cannot evaluate the recovery facility. Furthermore, a low SU might lead to a low TP and a high SU might lead to a high TP. So, the idea is to take (TP)/(SU) as a criterion for evaluation. Thus, we compensate for the effect of a low TP by dividing TP with a possibly low SU, in order not to underestimate the facility under consideration. Similarly, we dampen the effect of a high TP by dividing TP with a possibly high SU, in order not to overestimate the facility under consideration. Average disassembly time (DT) is not exactly the inverse of TP because TP takes into account the whole reprocessing (disassembly plus recovery) time. Unlike in a forward supply chain, components of incoming goods (used-products) in a recovery facility are likely to be deformed or broken or different in number even for the same type of products. Hence, incoming products of the same type might have different reprocessing
times, unlike in a forward supply chain where manufacturing time and assembly time are predetermined and equal for products of the same type. Since TP of a recovery facility depends upon the DT, it is unfair to not consider DT for evaluation. However, DT must not be taken as an independent criterion because it cannot evaluate the recovery facility. Furthermore, a high DT might lead to a low TP and a low DT might lead to a high TP. So, the idea is to take (TP)*(DT) as a criterion for evaluation. Thus, we compensate for the effect of a low TP by multiplying TP with a possibly high DT, in order not to underestimate the facility under consideration. Similarly, we dampen the effect of a high TP by multiplying TP with a possibly low DT, in order not to overestimate the facility under consideration.
CONCLUSION In this chapter, a neural network approach to evaluate the efficiency of a facility (collection or recovery) of interest, which is being considered for inclusion in a reverse supply chain, using the available linguistic data of facilities (collection or recovery) that already exist in the supply chain, was proposed. The approach was carried out in four phases as follows: In phase I, criteria for evaluation of the facility of interest, by each group participating in the reverse supply chain, were identified. Then, in phase II, fuzzy ratings of existing facilities were used to construct a neural network that gives impacts of criteria identified for each group in phase I. Then, in phase III, using the impacts obtained in phase II, a fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) approach was employed to obtain the overall rating of the facility of interest, as calculated by each group. Finally, in phase IV, Borda’s choice rule was employed to calculate the maximized consensus (among the groups considered) rating of the facility of interest.
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FUTURE RESEARCH For their future research, the authors plan to propose quantitative models for the following additional issues faced by decision-makers in the area of reverse supply chain design: • •
• •
Selection of economical used products to reprocess in a reverse supply chain Optimization of transportation of goods (used and reprocessed) across a reverse supply chain Evaluation of marketing strategies for success of a reverse supply chain Selection of potential second-hand markets to sell reprocessed goods
ACKNOWLEDGMENT The authors are indebted to Dr. Sagar V. Kamarthi for letting them use his neural network software.
Hwang, C. L. (1987). Group decision making under multi-criteria: Methods and applications. New York: Springer-Verlag. Pochampally, K. K., & Gupta, S. M. (2003). A multi-phase mathematical programming approach to strategic planning of an efficient reverse supply chain network. In Proceedings of the IEEE International Symposium on the Electronics and the Environment (pp. 72-78). Pochampally, K. K., Gupta, S. M., & Cullinane, T. P. (2003). A fuzzy cost-benefit function to select economical used products for re-processing. In Proceedings of the SPIE International Conference on Environmentally Conscious Manufacturing (CD-ROM). Pochampally, K. K., Gupta, S. M., & Kamarthi, S. V. (2003). Evaluation of production facilities in a closed-loop supply chain: A fuzzy TOPSIS approach. In Proceedings of the SPIE International Conference on Environmentally Conscious Manufacturing (CD-ROM).
REFERENCES
Saaty, T. L. (1980). The analytic hierarchy process. New York: McGraw-Hill.
Cha, Y., & Jung, M. (2003). Satisfaction assessment of multi-objective schedules using neural fuzzy methodology. International Journal of Production Research, 41(8), 1831–1849. doi:10.1080/1352816031000074937
Talluri, S., & Baker, R. C. (2002). A multi-phase mathematical programming approach for effective supply chain design. European Journal of Operational Research, 141, 544–558. doi:10.1016/ S0377-2217(01)00277-6
Chu, T. C. (2002). Selecting plant location via a fuzzy TOPSIS approach. International Journal of Advanced Manufacturing Technology, 20, 859–864. doi:10.1007/s001700200227
Talluri, S., Baker, R. C., & Sarkis, J. (1999). A framework for designing efficient value chain networks. International Journal of Production Economics, 62, 133–144. doi:10.1016/S09255273(98)00225-4
Fleischmann, M. (2001). Quantititative models for reverse logistics: Lecture notes in economics and mathematical systems. Germany: Springer-Verlag. Gungor, A., & Gupta, S. M. (1999). Issues in environmentally conscious manufacturing and product recovery: A survey. Computers & Industrial Engineering, 36(4), 811–853. doi:10.1016/ S0360-8352(99)00167-9 370
Triantaphyllou, E., & Lin, C. (1996). Development and evaluation of five fuzzy multi-attribute decision-making methods. International Journal of Approximate Reasoning, 14, 281–310. doi:10.1016/0888-613X(95)00119-2
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Tsaur, S., Chang, T., & Yen, C. (2002). The evaluation of airline service quality by fuzzy MCDM. Tourism Management, 23, 107–115. doi:10.1016/ S0261-5177(01)00050-4
Beamon, M. B., & Fernandes, C. (2004). Supplychain network configuration for product recovery. Production Planning and Control, 15(3), 270–281. doi:10.1080/09537280410001697701
Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8, 338–353. doi:10.1016/S00199958(65)90241-X
Biehl, M., Prater, E., & Realff, M. J. (2007). Assessing performance and uncertainty in developing carpet reverse logistics systems. Computers & Industrial Engineering, 34, 443–463.
ADDITIONAL READING Readers interested in the area of reverse supply chain design are referred to the following additional articles. Alshamrani, A., Mathur, K., & Ballou, R. H. (2007). Reverse logistics: Simultaneous design of delivery routes and return strategies. Computers & Operations Research, 34, 595–619. doi:10.1016/j. cor.2005.03.015 Amini, M. M., Retzlaff-Roberts, D., & Bienstock, C. C. (2005). Designing a reverse logistics operation for short cycle time repair services. International Journal of Production Economics, 96(3), 367–380. doi:10.1016/j.ijpe.2004.05.010
Dowlatshahi, S. (2005). A strategic framework for the design and implementation of remanufacturing operations in reverse logistics. International Journal of Production Research, 43(16), 3455–3480. doi:10.1080/00207540500118118 Gautam, A. K., & Kumar, S. (2005). Strategic planning of recycling options by multi-objective programming in a GIS environment. Clean Technologies and Environmental Policy, 7(4), 306–316. doi:10.1007/s10098-005-0006-7 Hu, T., Sheu, J., & Huan, K. (2002). A reverse logistics cost minimization model for the treatment of hazardous wastes. Transportation Research Part E, Logistics and Transportation Review, 38, 457–473. doi:10.1016/S1366-5545(02)00020-0
Ammons, J. C., Realff, M. J., & Newton, D. J. (1999). Carpet recycling: Determining the reverse production system design. Polymer-Plastics Technology and Engineering, 38(3), 547–567. doi:10.1080/03602559909351599
Krikke, H., Bloemhof-Ruwaard, J., & Van Wassenhove, L. N. (2003). Concurrent product and closed-loop supply chain design with an application to refrigerators. International Journal of Production Research, 41(16), 3689–3719. doi:10.1080/0020754031000120087
Barros, A. I., Dekker, R., & Scholten, V. (1998). A two-level network for recycling sand: A case study. European Journal of Operational Research, 110, 199–214. doi:10.1016/S0377-2217(98)00093-9
Krikke, H., Leblanc, I., & van de Velde, S. (2004). Product modularity and the design of closed-loop supply chains. California Management Review, 46(2), 23–39.
Bautista, J., & Pereira, J. (2006). Modeling the problem of locating collection areas for urban waste management. An application to the metropolitan area of Barcelona. Omega, 34(6), 617–629. doi:10.1016/j.omega.2005.01.013
Krikke, H. R., Van harten, A., & Schuur, P. C. (1999). Business case: Reverse logistic network redesign for copiers. OR-Spektrum, 21(3), 381–409. doi:10.1007/s002910050095
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Kroon, L., & Vrijens, G. (1995). Returnable containers: An example of reverse logistics. International Journal of Physical Distribution and Logistics Management, 25(2), 56–68. doi:10.1108/09600039510083934
Ravi, V., Ravi, S., & Tiwari, M. K. (2005). Analyzing alternatives in reverse logistics for endof-life computers: ANP and balanced scorecard approach. Computers & Industrial Engineering, 48(2), 327–356. doi:10.1016/j.cie.2005.01.017
Lieckens, K., & Vandaele, N. (2007). Reverse logistics network design with stochastic lead times. Computers & Operations Research, 34, 395–416. doi:10.1016/j.cor.2005.03.006
Salema, M. I. G., Barbosa-Povoa, A. P., & Novais, A. Q. (2007). An optimization model for the design of a capacitated multi-product reverse logistics network with uncertainty. European Journal of Operational Research, 179, 1063–1077. doi:10.1016/j.ejor.2005.05.032
Lim, G. H., Kasumastuti, R. D., & Piplani, R. (2005). Designing a reverse supply chain network for product refurbishment. In Proceedings of the International Conference of Simulation and Modeling. Listes, O. (2007). A generic stochastic model for supply-and-return network design. Computers & Operations Research, 34(2), 417–442. doi:10.1016/j.cor.2005.03.007 Listes, O., & Dekker, R. (2005). A stochastic approach to a case study for a product recovery network design. European Journal of Operational Research, 160, 268–287. doi:10.1016/j. ejor.2001.12.001 Louwers, D., Kip, B. J., Peters, E., Souren, F., & Flapper, S. D. P. (1999). A facility location allocation model for reusing carpet materials. Computers & Industrial Engineering, 36(4), 855–869. doi:10.1016/S0360-8352(99)00168-0 Lu, Z., & Bostel, N. (2007). A facility location model for logistics system including reverse flows: The case of remanufacturing activities. Computers & Operations Research, 34, 299–323. doi:10.1016/j.cor.2005.03.002
Savaskan, R., & Van Wassenhove, L. N. (2006). Reverse channel design: The case of competing retailers. Management Science, 52(1), 1–14. doi:10.1287/mnsc.1050.0454 Savaskan, R. C., Bhattacharya, S., & Van Wassenhove, L. N. (2004). Closed-loop supply chain models with product remanufacturing. Management Science, 50(2), 239–252. doi:10.1287/ mnsc.1030.0186 Veerakamolmal, P., & Gupta, S. M. (1999). Analysis of design efficiency for the disassembly of modular electronic products. Journal of Electronics Manufacturing, 9(1), 79–95. doi:10.1142/ S0960313199000301 Wojanowski, R., Verter, V., & Boyaci, T. (2007). Retail-collection network design under depositrefund. Computers & Operations Research, 34(2), 324–345. doi:10.1016/j.cor.2005.03.003
This work was previously published in Web-Based Green Products Life Cycle Management Systems: Reverse Supply Chain Utilization, edited by Hsiao-Fan Wang, pp. 283-300, copyright 2009 by Information Science Reference (an imprint of IGI Global).
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Chapter 2.9
Semantic Interoperability Enablement in E-Business Modeling Janina Fengel University of Applied Sciences Darmstadt, Germany
ABSTRACT Businesses all over the world are faced with the challenge of having to flexibly react to change and to dynamically work with varying business partners. For establishing electronic business, the underlying processes and subsequent IT-support need to be described clearly. For doing so, conceptual modeling has become an indispensable means. Models describe interrelated business objects and activities, expressed in a certain modeling language with elements labeled in natural language.
If the decision for the labels is not dominated by rules, models are semantically heterogeneous, not only concerning their modeling language, but more importantly, concerning their domain language, making their comparison or integration a non-trivial task. For its alleviation Semantic-Web technologies are applied. Transforming legacy models of different types into ontologies allows for reusing and connecting the domain facts modeled. Here, the novel method of semantic model referencing developed for this task is used, and this chapter will show how it can provide the basis for semantic integration.
DOI: 10.4018/978-1-60960-587-2.ch209
Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
Semantic Interoperability Enablement in E-Business Modeling
INTRODUCTION One of the core tasks in business management is the design and continuous improvement of business processing according to changing needs and expectations and the allocation of all necessary resources (Schreyögg, 2008). The increasing speed of globalization demands from enterprises of all sizes to adequately adapt in an ever quickening pace to changing business conditions and varying market requirements (Scheer, & Nüttgens, 2000). The motivation mostly arises from increasing cost pressure and intensifying competition as well as new legal regulations, the need to follow standards or for incorporating new innovative technologies (Österle, 2007). Therefore, it is mandatory to engineer business in an agile manner for ongoing optimization or reengineering (Scheer, Nüttgens, & Zimmermann, 1995; Hammer, & Champy, 2006). Continuous shaping and reshaping of business processes and the supporting or even enabling IT is a critical success factor for a business’s competitiveness (Frank, 2004). In daily operation, businesses are faced with the challenge of having to dynamically work with varying business partners. Establishing business relationships does not only require strategic decisions, but also efforts in integrating the partners’ business processes and subsequent information exchange. Enterprises need to be able to couple their business processes without huge preparation efforts. The basis for designing and engineering ebusiness in enterprises and B2B-collaborations is their comprehensive correct description. For setting-up interactions in and between organizations, all applicable business processes need to be described clearly and in an unambiguous manner. Such descriptions are the basis for engineering and managing them as well as for optimization or integration purposes. Often, this is achieved through abstraction by means of conceptual models, in particular for describing the support by IT-systems (Frank, 1994; Scheer, 1996).
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Consequently, managing all required models in a comprehensive and consistent manner is the prerequisite for engineering integrated process execution. One of the major tasks is the integration of existing, actively used models. Business process models frequently have to be matched for the purpose of reuse or integration (Hepp, & Roman, 2007). They do not only have to be matched for the purpose of integration or reuse in intraorganizational settings, e.g., when implementing ERP-systems, optimizing business processes or in cases of business-IT-alignment as well as process and application integrations due to reorganizations, but even more so inter-organizationally at the time of company mergers and acquisitions, the realization of supply chain management and the set-up of B2B-collaborations. Unfortunately, in practice, process matching is frequently hindered, as models very often differ considerably not only syntactically, but mostly semantically (Pfeiffer, 2007). Semantic heterogeneity arises not only through the differences between the constructs of the various modeling languages chosen for building models, but also through the different ways in applying natural language for labeling the model elements, which is independent from the choice of the modeling language (Thomas, & Fellmann, 2007, p. 29). This observation holds true for models in general. In case no predefined domain vocabulary or rules for assigning labels to model elements are in place, terms are chosen individually on a case-by-casebasis. Therefore, as a result, models are often semantically heterogeneous concerning the domain language. Hence, a lot of models are semantically incompatible, especially when several modelers or decentralized teams are involved, as incoherent labeling leads to model mismatches (Hadar, & Soffer, 2006, p. 570). This is in particular the case in B2B-collaborations, where the models to be integrated originate from different independent sources. As a result, differing types of models and dissimilarly applied business terminology prevent direct automated business process inter-
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actions without prior manual preparation efforts for resolving discrepancies. For easing this task, we suggest to apply ontology engineering. We here report on our research and continue with presenting the foundations and related works, followed by a description of our method of semantic model referencing based on Semantic-Web technologies and show its application. Our method foresees the reengineering of existing models of different kinds and types into ontologies, thus enabling the use of ontology matching techniques for relating them semantically. The result is a terminological domain ontology derived bottom-up in an automated manner, capturing the authentic business language actually in use. The emergent ontology can be improved and further developed in a collaborative manner and be utilized for semantic integration in business modeling scenarios. At the end, we show possible future research directions and conclude with a brief discussion of our proposition.
BACKGROUND The usage of models for describing data, processes and organizations has become an indispensable means for implementing electronically supported business conduction and enterprise modeling provides enterprise-wide views of an organization as the basis for decision making (Uschold, King,
Moralee, & Zorgios, 1997). Basically, in this context, a model is an abstraction intended to reduce complexity (Mahr, 2009). Thereby, an object may be a model of something, i.e., a description of an as-is status or original, or it may be a model for something, i.e., a prescription of a to-be status (Stachowiak, 1983). Models represent reality by leaving out irrelevant aspects from or by adding extending attributes to the object to be described, as they serve a specific purpose (Stachowiak, 1973, pp. 139ff, 155ff). Creating models allows using something that is simpler, safer or cheaper than reality instead of reality (Rothenberg, 1989). In this, a model represents a system, as it offers a simplified image of it (Kurtev, Bézivin, Jouault, & Valduriez, 2006). Thereby, according to General System Theory, a system is a set of elements standing in interaction. Models are written in a certain language offering language constructs with a syntax providing the construction rules, a semantics defining the constructs’ meaning and a notation for visualization, which can be graphical (Krallmann, Frank, & Gronau, 2002, p. 85). A modeling language is defined by its meta model to which the model conforms. A meta model is a model describing models (Strahringer, 1998). Figure 1 illustrates the levels of modeling. A model describes the business theme of interest in general, e.g., the process of booking travel arrangements, expressed by means of the constructs provided by the modeling language, e.g.,
Figure 1. Levels in modeling
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EPC, and is realized in practice repeatedly, e.g., one as a travel booking with the ID 10-10-09/6745 for a certain customer at a specific date. In the object-oriented approach by the OMG called Model-Driven Architecture, meta-meta models are introduced on top of the meta-model level. Such models conform to themselves and are applicable for defining meta models, so that transformations between models can become feasible (OMG, 2003). Conceptualization denotes the abstraction of ideas into concepts and the relations between them (Mizoguchi, 2003). Thereby, the vocabulary for denoting the same concept can be different (Guarino, 1998). Conceptual modeling provides for models describing business objects and activities from a business-centric point-of-view independently from technical considerations and computational implementation specifications (OMG, 2003). Over the past decades, for conceptual modeling various different modeling languages have been developed, both from the field of academy and the industry, either being freely available as a standard or being proprietary to a certain modeling method, tool or company. These languages are focusing on specific aspects and facilitate the creation of unconnectedly usable models. They express and detail domain-specific expert knowledge, whereas languages such as the Unified Modeling Language (UML) are mainly used for software system engineering (OMG, 2009b); (OMG, 2009c). For describing business processes for example Petri Nets (Petri, 1962), Event-Driven Process Chains (EPC) (Keller, Nüttgens, & Scheer, 1992), activity diagrams in the UML, or more recently models in the Business Process Modeling Notation (BPMN) (OMG, 2009a) are popular. All these languages offer a graphic visualization and enable the description of sequences of activities. Although these business process modeling languages differ considerably in detail, the intended meanings of their basic concepts resemble each other, even if these similar notions are designated differently and comprise
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slightly different scope. The behavioural aspects described may be enhanced through the inclusion of resources such as business documents, business data or organizational agents. However, for modeling static business information in detail, the use of Entity-Relationship models (ERM) (Chen, 1976) and class diagrams of the UML have become common for describing conceptual database schemas. Depicting functional requirements of potential IT-system users can be done by means of use case or sequence models from the UML. The need for capturing inter-connections between the various existing models are tackled by approaches such as enterprise architecture, which provide special modeling languages for creating integrated enterprise models offering partial or overall views (Op’t Land, Proper, Waage, Cloo, & Steghuis, 2009; Lankhorst, 2009; Aier, Riege, & Winter, 2008; Ferstl, & Sinz, 2006, p. 185; Scheer, 2002). Figure 2 shows some example models, an EPC (adapted from Havey, 2005), an UML Activity Model (adapted from IBM, 2010) and a UML Class Model (adapted from Database Answers, 2010). Even though models may be created for the same subject theme, they are often unrelated and differ regarding the domain language used and are expressed in different modeling languages. The process models here describe a similar business operation, which is the booking of travel services, using different domain expressions as model element labels. Upon comparison differences in the domain language usage can be detected, e.g., “Request airline reservation” would correspond to “flight reservation” and “vehicle reservation” to “car reservation”. Before resolving these differences, a comparison of the flow of activities cannot be done. The class model describes a possible database design usable within the given scenario, also using differing labels. Linking one of the processes to the information required as in- and output to the information of the class model would need resolution of the labels’
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Figure 2. Example models
meanings, e.g., “vehicle” in the EPC to “car” in the activity model and “reservation” to “booking”. In practice, often differing unrelated nonaligned legacy models exist. There are efforts in matching models concentrating on the aspect of model language semantics based on migration or transformation from one modeling language into another (Murzek, & Kramler, 2007; Gehlert, 2007; Kensche, Quix, Chatti, & Jarke, 2007), matching models via their meta models (Kappel, Kramler, Kapsammer, Reiter, Retschitzegger, & Schwinger, 2005) or concentrating on managing models of the same kind (Melnik, Rahm, & Bernstein, 2003). The aspect of heterogeneously used domain language is not addressed in these approaches, instead the
model element labels are transferred and retained unchanged for further use. However, for consolidation models need to be compared regarding the intended meaning of their elements and their structure, whereas structural analysis cannot be performed until successful alignment of the domain language (Simon, & Mendling, 2007). The differences occurring there are similar to the ones found in knowledge modeling. In particular, variations can be found in the terminology applied, such as the choice of natural language and encoding or naming mismatches due to the occurrence of synonymy or homonymy, next to differences in granularity, scope or modeling style and the perspective and intended usage of a model (Klein, 2001; Kalfoglou, & Schorlemmer,
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2005, p.5). Especially, as seen also in the example above, naming conflicts hinder model integration (Becker, Rosemann, & Schütte, 1996; Thomas, & Fellmann, 2006). As a solution for preventing semantic differences concerning the domain language used in modeling, the use of agreed-upon sets of terms for creating labels for model elements has been suggested (Thomas, & Fellmann, 2007; Kugeler, & Rosemann, 1998). Such a set may be a business or domain model on the conceptual (Kugeler, & Rosemann, 1998) or business level (OMG, 2003, p. 2-5), a domain specific language (Pfeiffer, 2007; Kurtev et al., 2006) or more generally a domain ontology (Hepp et al., 2007; Saeki & Kaiya, 2006; Goméz-Pérez, Fernandéz-López, & Corcho, 2004) or more specific an enterprise ontology (Grüninger, Atefi, & Fox, 2000; Dietz, & Hoogervorst, 2008). These approaches assume the prior existence before modeling or a separate top-down development of such domain models. Present suggestions at integrating process models follow this notion by assuming the existence of a separately top-down developed domain ontology for providing mutual understanding of the element’s meaning (Weske, 2007; Becker, & Pfeiffer, 2008). Works in the field of semantic business process management foreseeing process model matching including the aspects of the domain language often rely on such a pre-defined business terminology (Hepp, Leymann, Domingue, Wahler, & Fensel, 2005; Brockmans, Ehrig, Koschmider, Oberweis, & Studer, 2006; Thomas, & Fellmann, 2007). This is combined with a semantic description of the business process modeling language for the purpose of automatedly supporting process modeling. However, the creation of a centrally defined, manually created, unified language model cannot solve the problem of semantic ambiguity completely. The development and maintenance of a shared standard is usually a very time-consuming and cost-intensive undertaking, since a group of experts needs to be installed for such a project.
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Usually, substantial work has to be done for determining the meaning of terms (d’Aquin, Motta, Sabou, Angeletou, Gridinoc, Lopez et al., 2008). Also, most of these tasks are repetitive, as changes over time need to be considered. The difficulty of the creation as well as the challenge of correctly elicitating the domain facts has been examined for the field of software engineering for the construction of domain models (Ambler, 2008) and formal domain specific (programming) languages (Hillairet, Bertrand, & Lafaye, 2008) as well as in knowledge engineering for ontology construction (d’Aquin et al., 2008; Hepp, 2007). Even the usage of public e-business standards cannot solve the problem, as the multitude of standards available and actively in use at the same time, moves the question of semantic interoperability only onto a higher level (Rebstock, Fengel, & Paulheim, 2008). So despite the development of e-business standards, the integration of business processes and business information is still a non-trivial issue, as business partners often use different e-business standards or their own individual language for describing their processes. Furthermore, the models to be integrated are actively is use and cannot easily be recreated or amended according to new guidelines or rules for business conduction with each specific partner. Nevertheless, for enabling integrated business process execution, managing and relating all required models is required, so that seamless electronic support of business usage scenarios such as the one mentioned above, is provided. Existing models need to be related to others for content clarification, while new models may have labels following newly defined specifications. For enabling meaningful comparisons of the sequence of activities described by business process models, resolving semantic discrepancies in the area of the domain language present is of the essence. Yet, models already represent domain knowledge in structured form. Furthermore, since conceptual models are an important source of information, automated support for retrieving the
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knowledge contained can increase the models’ usefulness (Becker, & Pfeiffer, 2007, p. 153). Employing semantic technologies for extracting this domain knowledge has been suggested. In the field of ontology engineering, the inclusion of ontology learning from unstructured resources such as texts (Cimiano, Hotho, Stumme, & Tane, 2004), matchmaking for ontology evolution (Castano, Ferrara, & Montanelli, 2006), and user participation (Braun, Schmidt, Walter, & Zacharias, 2008; Siorpaes & Hepp, 2007) have been proposed. Recently, automated derivation of a domain glossary from a specific model type has been suggested (Delfmann, Herwig, & Lis, 2009). Still, the realization of electronic business concerns all aspects of information processing. Similar to the areas subsumed by the notion of enterprise modeling, process, data and organization models together need to be considered. So far there are no propositions for solutions how to semantically coordinate business knowledge contained in models of different kinds and types for integrating the semantics of the modeling and the domain language together. We here suggest a new method for reengineering semi-structured and structured resources into ontologies for obtaining machine-processable semantic descriptions. It is a bottom-up approach by mining the models for the domain semantics contained achieving knowledge reuse without huge manual preparation efforts. Having presented the background and motivation of our work, we continue in the following chapter by introducing our novel approach. In that it is domain-semantics oriented, it addresses the challenge of semantic heterogeneity not only from a modeling language perspective. We are basing our solution on applying semantic technologies for integrating conceptual models concerning the domain language used for naming model elements. Next, we present the method developed, called semantic model referencing. We show the conceptual foundations and our approach at ontologizing models together with the supporting ontologies specifically developed for this business
challenge at hand. The semantic model integration is achieved based on leveraging semantic technologies, in particular ontology matching. The application of our method is shown by use of the example models presented above.
SEMANTIC REFERENCING The recent high acceptance and spread of the World Wide Web as an ubiquitous infrastructure for business conduction on a global level led to a quickly growing diffusion of electronic support for a variety of internal and external business conduction. With the advent of the Semantic Web and the technologies for its realization, also the possibilities for utilizing ontologies as a means to enabling semantic interoperability become more and more accepted. The idea of annotating information resources in the Web with meta data enables the representation of knowledge in structured, machine-processable form building on internet technologies, readable for humans as well as machines (Shadbolt, Berners-Lee, Hendler, & Hall, 2006). Thus, information processing can be automated. Since the manual collection and definition of knowledge to be shared may be tedious, we suggest to apply these information processing techniques for support. By reusing the wealth of domain knowledge hidden in existing data, business process or any other models, a knowledge model of the business terminology used can be established in a pragmatic bottom-up approach for resolving semantic heterogeneity in the area of the domain language present in business modeling. The idea is to extract and relate it, so that a comprehensive conceptual overview can be established. In turn, this can be used for improving and refining relations obtained in an integrative manner, combining automatic means with human input. Over time, the authentic semantics in use can become evident and be turned into a specific domain ontology generated in a bottom-up manner without initial ramp-up efforts.
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This is further usable for creating new models as well as for model matching.
Ontologies as Semantic Foundations Formalizing fact collections in well-defined semantics is the basis for interpreting the meaning of terms. Such representations are commonly referred to as ontologies (Goméz-Pérez et al., 2004, pp. 8ff). The notion of ontology emanates from philosophy. It denotes the science of being and the descriptions for the organization, designation and categorization of existence (Gruber, 1993). Ontology aims to explain the nature of the world. Carried over to computer science in the fields of artificial intelligence and information technologies, an ontology is understood as a semantic model and serves for specifying the knowledge about a certain universe of discourse in structured form (Allemang, & Hendler, 2008). One of the most popular definitions describes an ontology as an explicit specification of a conceptualization (Gruber, 1993). Hereby, this led to the formation of ontologies as a plural of what was originally used in philosophy solely as the singular ontology, since in many knowledge Figure 3. Extract from an example ontology
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domains several representations can coexist side by side (Hesse, 2005). An ontology captures the recognized and conceived in a knowledge domain for the purpose of representing and communicating the intended meaning of its concepts’ descriptions. A precise knowledge description is usually done in a logic-based language with well-defined semantics allowing for machine processing and logical deducting for the discovery of tacitly inherent knowledge (Uschold, & Gruninger, 2004). Often, a graphic visualization is done in the form of a semantic net, as shown in Figure 3, which shows an extract of an example ontology about travel (Knublauch, 2010). Basically, ontologies can be understood as collections of definitions of elements and their relationships. For the development, usually consensus is established between a group of modelers (Staab, Studer, Schnurr, & Sure, 2001). It is jointly decided which specific terms define a unique meaning within a commonly shared vocabulary and how these terms are related (Daconta, Obrst, & Smith, 2003, pp. 181ff). Thus, an ontology allows for sharing and reusing knowledge in an unambiguous manner serving as a model, as it provides a simplified abstract view of the
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world formally described by representational vocabulary for a shared domain of discourse (Gruber, 1993). In this it resembles a conceptual schema, similar to database schemas (Antoniou, Franconi, & van Harmelen, 2005). Its elements are classes or concepts representing a set of objects with common properties, instances representing the individual objects, relations and axioms, which are formalized statements or assertions, assumed to be true without having to be proved for modeling nondeductible knowledge. Thereby, ontologies can have different degrees of formality. The plainest form is the aggregation of facts as a semi-structured text. A first step towards formalization is the definition of a hierarchical structure. By adding predefined semantic relations, thesauri can be created. A formal semantics facilitates the definition of the intended meaning of the terms collected and their relations. The most powerful ontology forms are strictly formalized descriptions derived according to first-order logic, as this allows for quantified statements of objects and relations (Russell, & Norvig, 2003). Thereby, properties are defined by means of mathematical equations containing values of other properties or by logical statements defining disjoint or inverse classes or part-whole relations (Uschold, & Gruninger, 2004). Ontologies become more expressive with a higher degree of formality and thus increasing amount of meaning specified, so that ambiguity decreases (McGuiness, 2003; Uschold, & Grüninger, 1996). Accordingly, they can be distinguished regarding the extent of explication provided (Stuckenschmidt, & Harmelen, 2005). Lexicons and dictionaries are considered to be terminological ontologies, as they specify terms used in a domain (van Heijst, Schreiber, & Wielinga, 1997). Vocabularies, glossaries, thesauri, classifications and taxonomies are often called lightweight ontologies (Goméz-Pérez et al., 2004, pp. 8ff; Euzenat, & Shvaiko, 2007, pp. 29-30). They describe concepts with their relations and attributes and form a hierarchically structured network of relations. Data models are
less lightweight. They are also called information ontologies (van Heijst et al., 1997). Data models and formal ontologies which contain additional interlinking through relations of the concepts, stated as axioms and constraints in terms of predefined conditions, are called heavyweight ontologies (Goméz-Pérez et al., 2004, pp. 8ff; Euzenat, & Shvaiko, 2007, pp. 29-30). For the representation of Web-based ontologies, different languages exist, out of which the XML-based RDF Schema for basic lightweight ontologies or one of the dialects of the formal Web Ontology Language provided by the World Wide Web Consortium, called OWL, for more heavyweight ontologies are the most popular. In order to allow for automated processing, any model describing concepts needs to be formal, since formal ontologies can be reasoned upon (Blumauer, & Pellegrini, 2006). For this purpose, often the description logic based OWL DL is chosen for representing an ontology, because the more expressive OWL Full is not decidable (Smith, Welty, & McGuinness, 2004). Rules for inference can be defined based on the relationships contained in the ontology (Saeki, & Kaiya, 2006). Through inference new knowledge can be derived through logical deduction and the ontology evolves (Antoniou et al., 2005). Description-logic based languages are determinable, sufficiently expressive first-order-logic subsets. They provide welldefined formal semantics without variables in the formalism of predicates. Concepts, relations and individuals can be described independently of each other (de Bruijn, 2004). The use of these subsets solves the problem of non-determinability or semideterminability occurring when using inference engines with ontologies in first-order-logic-based languages. Languages are determinable if their characteristic function can be calculated fully or, at least, partly. A description-logic-based language consists of two parts. Figure 4 shows the modeling levels of an ontology in description logic in comparison to conceptual business models.
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Figure 4. Ontology and modeling levels
The TBox, the terminological box, defines the terminology of a domain’s concepts and with this all predicates and relations. The ABox, the assertional box, describes facts and assertions regarding the defining properties of entities and concept instances and their relations. This corresponds to the representation of the state of the modeled part of the real world. Thus, new concepts may be automatically classified into the hierarchy and instances may be automatically classified as well. Of central importance in description logic is the subsumption relation and complex general terms (Russell, & Norvig, 2003).
Types of Ontologies Aside from classifying ontologies according to their structural scope, they may also be distinguished by the task they are meant to fulfill
(Goméz-Pérez et al., 2004, pp. 47ff). Accordingly, some important ones can be identified. Table 1 shows examples. The terms contained in lower-level ontologies such as domain ontologies, can be linked to the notions given in top-level ontologies for the purpose of interlinking, thus specifying them. In this, domain ontologies specialize the terms of toplevel ontology. In the area of e-business, there are various standards available, for the most part in semistructured, machine-readable form. These knowledge representations at least define a common vocabulary and hold some relations between the terms, mostly subsumptions. Therefore, e-business standards can be understood as light-weight ontologies as well (Goméz-Pérez et al., 2004, p. 86). Presently, several standards and ontologies of various types exist, as presented in Table 2.
Table 1. Types of ontologies Ontology type
Scope
Examples
Knowledge representation ontologies
Primitives for knowledge formalization
Representation used in the context of the Semantic Web: RDF, RDF Schema, OWL
Top-level or upper-level ontologies
Knowledge about the world in general independent of a particular domain (space, matter, time, etc.)
Cyc (Cycorp, 2009), Suggested Upper Merged Ontology (SUMO) (IEEE, 2009), Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE) (Laboratory for Applied Ontology, 2009)
Lexical ontologies
Natural language
For English: WordNet (Princeton University, 2009)
Domain ontologies, task ontologies
Reusable vocabularies with their relations describing a specific domain or activity
E-Business, culture heritage, chemistry, biology or health and medicine
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Table 2. Overview of e-business ontologies E-Business Ontology type
Scope
Examples
Identification standards
Designations for business terms, participants, goods
ISBN, GLN, GTIN, EAN
Classification standards
Designations for master data formatting
UNSPSC (unspsc.org, 2009), eclass (eclass, 2005), catalog exchange formats
Transaction standards
Business document structures and document flow
UN/EDIFACT (UNECE, 2006), XCBL (xcbl.org, 2003), cXML (cxml.org).
Process standards
Business process structures
ebXML (OASIS), RosettaNet (GS1 US, 2009)
Enterprise ontologies
Knowledge about enterprises’ structure and operations
Enterprise Ontology (Uschold et al., 1997), TOVE Ontology (Fox, 1992), Enterprise Ontology (Dietz, 2006), FEA-RMO (GSA, 2005), SUPER ontologies (SUPER Integrated Project, 2009)
Product and service classifications are rather basic ontologies in the form of taxonomies with a lot of concepts (Omelayenko, 2001). Transaction standards focus on the automation of complex workflows in and between enterprises and contain many different document types (Omelayenko, 2001). Process-oriented standards provide standardization of complex workflows within and between businesses. An extensive overview is provided in (Rebstock et al., 2008). Overall, ebusiness standards, even if created for the same purpose or same domain, can differ considerably and it seems highly unlikely that one universal, globally accepted standard will become prevailing in the near future (Rebstock et al., 2008, p. 78). Enterprise ontologies are intended at defining terms and organizing knowledge about enterprises and their structure and operations, usable for engineering enterprises focusing on operations, transactions, organization, communication and coordination. All these types of ontologies have in common that they are vocabularies of particular domains with specifications of the meaning of terms and concepts (Uschold, & Gruninger, 2004). Thereby, their taxonomic structure describing generalization and specialization expressed as subclass relations can be understood as their backbone (Euzenat & Shvaiko, 2007, p. 99). As an approach for capturing semantics, the use of
ontologies is becoming popular, also in corporate settings (Uschold, & Grüninger, 1996). Ontologies present a means to accumulate and describe the knowledge of an enterprise in one single spot and facilitate the reconciliation of semantically heterogeneous information. Usually, the development of an ontology by an enterprise is motivated by the wish for enabling the structuring of its knowledge (Zelewski, 1999). Using ontologies within enterprises or B2B-collaboration networks facilitates capturing and sharing knowledge in an unambiguous manner to solve business tasks. The benefit lies in the support provided for semantic integration works within and across enterprise boundaries (de Bruijn, 2004). Thereby, for facilitating seamless processing, achieving mutual understanding about information is intended. Within information exchanges the information needs to be unambiguous and carry the same meaning for both the sender and the recipient, regardless whether they are humans or computers, so costly process interruptions can be avoided (Wigand, Picot, & Reichwald, 1997, pp. 60ff).
Relating Ontologies Expressing collections of concepts as ontologies allows rendering the semantics in machineprocessable form. This provides the basis for consolidating information from different sources.
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However, thereby the questions concerning semantic integration need to be faced, which is one of the major research challenges in this field (Stuckenschmidt, 2009, p. 73). Ontologies usually are developed independently of each other for different purposes, as described above, similar to conceptual business modeling. The existing e-business ontologies do not match and it seems unlikely that future ontologies, used either publicly or exclusively by an individual enterprise, will do so. Nevertheless, business interactions depend on interoperability on the semantic level (de Bruijn, 2004, pp. 2-3). Semantic interoperability denotes the enablement to share and reuse business knowledge upon integrating heterogeneous sources of information concerning their intended meaning, thus making this knowledge compatible. For extending the captured specialist knowledge or relating it to other domains, the ontologies have to be related. Thereby, identifying logical connections for fusing enables semantic integration (Uschold, & Menzel, 2005). Solutions for the challenges around semantic interoperability and integration have been suggested (Kalfoglou, Schorlemmer, Sheth, Staab, & Uschold, 2005; Alexiev & Breu, 2005; Stuckenschmidt & Harmelen, 2005; Noy, 2004). The techniques available are ontology matching and mapping. Converting non-ontological resources, such a models, and simple semantic models, such as company terminologies and e-business standards, into OWL DL allows for applying ontology matching technologies. These methods facilitate automated searches between the elements of one or more ontologies, which are related on the conceptual level and thus express semantic correspondence. Such relations may serve as semantic references between terms for the purpose of comparison and reconciliation. Thereby, the power of automated computing supports the process of having to compare labels manually and establish mappings. Ontology matching systems search for pairs of entities from different ontologies
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with the same intended meaning (Euzenat, Mocan, & Scharffe, 2008). The ontologies are reconciled for discovering semantic correspondences, which can be understood as mappings. Statements such as “A from Ontology X corresponds to B from Ontology Y” are functions describable as: mapping (e1)= {e2|e2∈O2}, e1∈O1
The correspondences found express equivalence or similarity. They can be stored for further usage (Euzenat et al., 2008). This is especially helpful, if the related ontologies are to be kept individually and not to be merged. Usually, existing models, terminologies and ontologies cannot be amended according to new demands once they have been created and are actively in use. The mappings found serve as means to a virtual integration and the aligned ontologies can remain in their original form and in usage in parallel without changes. The techniques available for matching ontologies can be distinguished in element- and structurebased techniques. Matching techniques on the element-level analyze ontology entities regardless of the relations they have with the other entities. Thereby, names or strings can be compared and linguistic resources can be included as background information. Edit-distance based methods, such as the Levenshtein distance, measure the distance between expressions by computing the number of edit operations required for achieving equality, whereas measures based on the Jaro metric compare the number and sequence of strings. Token-based methods perform such measuring on sets of strings (Cohen, Ravikumar, & Fienberg, 2003). In contrast, structure-based techniques include the information of the entities’ neighborhoods and analyze the structure of an ontology. Very often, structural analysis relies on hierarchical relations being present. Thereby, also non-trivial correspondences can be found. Comprehensive overviews can be found in (Euzenat, & Shvaiko, 2007; Kalfoglou & Schorlemmer, 2005).
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Basically, all matching systems have a similar approach, in that they process entities of two or more ontologies with the aid of some external information, preset parameters and, if available, supporting information (Euzenat, & Shvaiko, 2007). External information supporting the matching process can be dictionaries and top-level ontologies, linguistic ontologies or domain ontologies, such as e-business standards (Goméz-Pérez et al., 2004; Noy, 2004). The output consists of unidirectional mappings that can reflect non-symmetrical relating, mostly by listing related concepts in both ontologies in form of one-to-one mappings. An approach at generating more complex types of mappings including more than one entity from each ontology is presented in (Hu, & Qu, 2006). Furthermore, for achieving results of higher quality, there are different approaches for combining matching tools, since a combined approach can exploit more possibilities due to the diversity of the various methods utilized.
Ontologizing Models Reengineering non-ontological resources allows for employing previous intellectual achievements and reusing the wealth of domain knowledge contained in models of all kinds. In order to benefit from the possibilities for obtaining semantic relations through ontology matching techniques, existing models and terminologies in non-ontological form need to be transformed into ontologies. Converting non-ontological resources into OWL DL facilitates machine processability, as all model ontologies have the same expressivity and are represented in the same syntax and degree of formality. Furthermore, the use of OWL DL provides for reasoning as well.
Reengineering Terminologies Terminologies such as company glossaries and dictionaries as well as most of the e-business standards are semantic models in non-ontological
form. When they are available in XML or XSDformat, eXtensible Stylesheet Language Transformations (XSLT) can be developed. They serve for describing modification from one XML dialect into another, whereas here the target is OWL DL. Thereby, for each terminology transformation a different XSLT-sheet is required, as the models differ. Due to their diversity various criteria have to be considered for setting the approach usable for transforming their elements into ontology entities, i.e., classes, properties and applicable restrictions. So far, our research has revealed that no single commonly usable XSLT-sheet can be developed. However, in order to convert legacy semantic models without modifications in an automated manner, we combined and adapted the works of Klein, Fensel, van Harmelen, and Horrocks (2001), Bohring and Auer (2005) and García and Gil (2007) on a case-by-case basis. Thereby, a general approach could be established in that the core components called xsd:element are turned into owl:Class. Accordingly, classification categories and document structure fields are transformed into ontology classes related by subsumption. The resulting ontologies reflect the original models, also including any inconsistencies they may possess. For example, in product and service taxonomies a rather informal use of subclass relationships sometimes does not depict actual hierarchical, but instead mereologic relations describing part-whole-relationships (Hepp, & de Bruijn, 2007). However, our procedure allows for a fully automated transformation of huge amounts of information in a short time and preserves the original domain semantics as-is. If terminologies, on the other hand, are only available in an unstructured format, such as natural language in text documents or on webpages, ontology learning mechanisms may be employed for converting those descriptions to ontologies and extracting relevant terms.
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Reengineering Models Nowadays, modeling is mostly done with the help of modeling tools, thus the information is persistently electronically available and can be exported in an XML-based interchange format such as XML Metadata Interchange (XMI). Therefore, in principle transformations into OWL DL can be performed by means of XSLT. Unfortunately, even though XMI is an often used standard, our research showed that the exports differ profoundly, as each tool is creating its XMI-files in a different way. As a result, subject matter expertise is required for developing specific XSLT-sheets for each model type a modeling tool is supporting. Therefore, no universal basis, as it was possible for the reengineering of terminologies, could be established. Instead, individual transformation prescriptions are required for realizing a pragmatic attempt to convert models into ontologies. We have based this on the general considerations as shown here in the following. For creating a conceptual model of any kind, awareness of the modeling language specifics and of the applicable business terminology is Figure 5. Composition of a conceptual model
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required. This has been demonstrated for EPCs, but holds true for other models as well (Thomas, & Fellmann, 2006). Thereby, models contain input from two areas, as illustrated in Figure 5 for the composition of a business process model, here the EPC introduced already above. In that they are a composition of a set of model elements and model element labels, models possess two language spaces (Bézivin, Devedzic, Djuric, Favreau, Gasevic, & Jouault, 2006). The domain language designates the specific conceptual knowledge of a problem domain concerned in natural language, while the modeling language provides a means for sorting it (Fengel & Rebstock, 2009). Reversing the modeling process facilitates the decomposition of models. A model and its elements can be split into two separate models represented as ontologies, which together describe the model with its model type and name and the model elements with their model element types and labels. Thereby, the domain facts expressed in the natural domain language are separated from the type of element they are connected with. This type information resembles attaching provenance in-
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Figure 6. Meta models used for model decomposition
formation. For doing so, the idea of indexing the domain facts in a manner similar to indexing in librarianship in form of Topic Maps has been adopted (ISO/IEC, 2002). Figure 6 shows the meta models of thus decomposed models. The model ontology on the left hand side describes the domain knowledge in natural language as owl:Classes and the relations between them as properties with restrictions as needed. This model ontology imports the model type ontology. As a linking point they both contain a
concept called “domain entity”. For each modeling language a specific modeling language ontology can be developed in advance for continuous reuse. Such a Modeling Concept Ontology (MCO) contains the modeling concepts. They are associated by part-whole-relations, thus following the notion of strict meta modeling (Atkinson, & Kühne, 2002). This way the domain knowledge contained in the logical relations between model elements as the means for setting the specific models’ element order is preserved together with
Figure 7. Extract of a decomposed EPC
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the domain facts in the model ontology, not in the MCO. XSLT-sheets for transforming models exported in XMI have been developed accordingly for various modeling languages. Applying the decomposition to our EPC for example, returns a model ontology linked to its corresponding modeling concepts ontology, as shown in Figure 7 for an extract. In principle, for any type of model an MCO can be developed. All business process modeling languages provide the means for describing sequences of activities. They offer the idea of activities, either being called activities, tasks, functions or actions, which start and end with an event and are linked by flows. For the description of the behavioral aspect of processes, the flows can be tied to logical connectors for making decisions and showing alternative flow paths (Murzek, & Kramler, 2007). In detail the semantics of the modeling languages are not equivalent, so that models cannot be translated directly without loss of information (Kensche et al., 2007). However, the fundamental intensions of the concepts are comparable. The same observation can be made for models describing static business information. Conceptual data models can be represented as entity-relationship models, UML class models or directly as OWL-ontologies. Thereby, the entities of an ERM or classes of a class model correspond to the classes of an ontology, while the attributes and relationships correspond to the relations or properties in most ontology languages (Uschold, & Gruninger, 2004). Often, UML class models are even used for ontology modeling (Gašević, Djurić, Devedžić, & Damjanović, 2004; Brockmans, Volz, Eberhart, & Löffler, 2004). Research in the field of enterprise ontology is concentrating on defining common conceptualization for describing enterprise operations. In this, those ontologies can be used as a common ground for setting migration rules (Gehlert, 2007). The use of meta models for the purpose of migrating models is also being followed within the MDAapproach. Meta modeling for the purpose of in-
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tegrating models has been used for migrating conceptual models (Gehlert, 2007) and in the field of enterprise modeling (Müller, 1998) and for the development of the Unified Enterprise Modelling Language UEML (University of Bergen, 2009). In contrast, the approach presented here concentrates on elicitating the semantics of the domain language used for modeling. We transform the model name and model element labels into ontology classes with reference relations linking them to the modeling language semantics described in the separate modeling concept ontology. All labels are presently taken without further processing, so that not only terms, but complete expressions are transferred. Often, domain knowledge in the field of business processing lies in the combination of objects and the execution of activities, which is preserved this way. Basically, the suggested decomposition method abstracts from the statement a model intends to do and leaves the model as is for further active use. In order to be able to link the ontologies resulting from the conversion as described, the MCOs enable references between models of the same type. For further enabling also the referencing of models of the same kind, but different type as well as also models of different kind, we suggest to use the Unifying Modeling Concepts Ontology (UMCO), which we have developed specifically for this purpose. It provides a unifying model concept for each type of modeling concept with a similar intention. Input for its design has been found in the existing enterprise ontologies. For our purpose of integrating models, we have defined general modeling concepts and declared them equivalent to corresponding concepts in the various modeling languages for the purpose of integration. For example, an EPC is defined compliant with an UML activity model and a BPMN model, and these concepts are set to be equivalent to the UMCO concept called UMCO:Process; EPC_MCO:function in an EPC, UML_AM_MCO:action in an UML activity model and BPMN:task in a BPMN model are set
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Figure 8. Meta models with UMCO
equal to UMCO:Activity. Accordingly, all modeling concepts found in the various languages can be unified and related. The UMCO is extensible as needed for including further MCO-ontologies, which are rather small ontologies serving as bridge ontologies. The UMCO further extends the above depicted meta model, as shown in Figure 8. Developing MCOs not only for process models, but for data and organization models as well, allows connecting knowledge about resources used in process models, such as documents or participants etc., to the data models providing details about them. The conversion of models as suggested supplies lightweight individual ontologies. Each of them is a knowledge model of the concepts in use in a particular model and in principle all models can be processed in this manner.
Enabling Semantic Referencing Usually, the creation and ongoing care of a domain ontology is a major task. To ease this workload, we automate this step by reengineering the conceptual
domain knowledge contained in existing models as shown and relate it semantically for establishing semantic references between the model ontologies as an initial core of an emergent domain ontology. As an example for semantic model integration in the described manner, we develop the MODI (Model Integration) Framework as an application of our method for integrating models. Over the past years, extensive work has been done in developing ontology engineering tools and frameworks. Furthermore, we could draw on our experience gained from previous works in developing the ORBI Ontology Mediator used for reconciling e-business standards in the field of e-commerce (Rebstock et al., 2008). It was applied for realizing semantic synchronization between business partners during electronically supported multi-attribute negotiations (Fengel, Paulheim, & Rebstock, 2009). Building on these foundations, we are implementing our solution for facilitating the reconciliation of differing terminologies in non-ontological semantic models and conceptual models from the field of business
Figure 9. Process of semantic model referencing
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modeling as described above. Our framework is implemented in Java and can be accessed by a web service interface, so that it may be integrated with arbitrary applications. It consists of a core component, to which tools for mapping and reasoning can be variably connected by adapters. The focus of our work is on the realization of matching and establishing semantic references between models. Figure 9 depicts this process, which we call semantic model referencing. Having performed the model conversions as described above, ontology matching can be performed without merging any of the input model ontologies. Since the model ontologies obtained by transformation from process models do not contain hierarchical or mereologic relations, only element-based techniques return meaningful mappings. In the case of transformed ERM and class models as well as taxonomies, also structure-based techniques can be used, as here in most cases subsumption and aggregation associations return exploitable ontology structures. Since the domain facts are not transferred as instances of their individual model type, it is prevented that matchings return references between model element types. These links are provided without creating workload for the matchers through the introduction of the MCOs and the UMCO. Furthermore, avoiding such an undesired hierarchically structure focuses the matching efforts onto the domain language independently of the original modeling language used. The works for semantic referencing can be performed successively as needed. Results are obtainable from the beginning, especially after having included lexical background information for supporting the matching process from WordNet or also e-business standards. In principle, the ontologies of semantic terminology models and conceptual models as described can be matched with each other as well as with any other existing ontology as needed, e.g. an enterprise ontology. The mappings found as a result of matchings performed are preserved and stored in a
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reference repository. Additionally, user may add mappings manually. Collecting the semantic correspondences found creates persistent semantic interlinkages for further enhancement. The model ontologies as well as any other added ontologies are kept in their original form, whereas the references between them may be created, changed or deleted in the repository. As models are often big and rather complex, their transformation leads to large-scale ontologies. Using the matching tools and frameworks having become available over the past years, we found that only a few are capable of handling such large-scale ontologies. Presently the matching framework Malasco is used, which partitions ontologies for coping with the scalability problem for finding mappings (Fengel et al., 2009). For smaller ontologies, the further connected CROSI Matching System facilitates choices of various name and structure matchers for combination and parameter setting (Kalfoglou, Hu, Reynolds, & Shadbolt, 2005). Thus, an initial reference base is being established by means of automated tools. It serves as a starting point facilitating user-driven growth and quality improvement over time. Users can contribute to the reference collection by creating new references and adding new ontologies. At the time of using the resulting reference ontology, the automatically derived information is evaluated by its users. Usually, the results produced by matching tools are not perfect and require user input for quality enhancement. Even though the need for manual work is reduced, the mappings found are usually not perfect, but may be ambiguous or incorrect. For optimization and disambiguation usually human involvement is required (Zhdanova et al., 2004). Therefore our system facilitates user participation by enabling adding, editing and feedback provision. This way otherwise hidden knowledge is extracted, shared and made usable. Providing the possibility for community user participation in the process of disambiguation offers a wealth of specific background information concerning the domain
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context. Tapping into the users’ tacit knowledge in an implicit manner allows for exploiting existing knowledge and its combination with the automatically derived mappings without requiring tedious additional work. Capturing the implicit part of domain knowledge provides important subject matter expertise needed for resolving uncertainties and ambiguities. In this, technologies for collaboration and semantic technologies can complement each other (Gruber, 2007). The mappings found are stored as 5-tupels (Rebstock et al., 2008, p. 155-156): <e1,e2,R,c,a> whereby: • • •
•
e1 and e2 are the entities of the ontologies between which a relation is assumed, R is the type of semantic relation between the entities, e.g., equivalence or similarity, c is the confidence qualifying the relation, expressed as a numerical value between 1 and 0 being a fuzzy degree, a is a numerical value between 0 and 1 describing the degree of reputation and trust in the assumed relation.
The acceptance can be computed out of the users’ feedback, in the simplest form submitted directly by manual input or, alternatively, through transparent observation of a user’s choice in order not to impose additional workload. Each time an acceptance value is added, a relation is made more trustworthy and can become more precise and stable over time. With his selection decision, the user thus contributes to improving the quality of the respective reference. The referencing process is iterative and executed each time new references are added or existing references are used and rated by the users. Thus, the system can grow and improve over time. With an increasing number of models included, first tendencies towards commonly used terms can become obvious. An initial terminologi-
cal domain ontology emerges, consisting of the various independent model ontologies, which are linked through the references. The evolving reference repository can be queried for semantic references. Thereby, a user may request references for a specific term or directly compare two ontologies. Furthermore, also queries without specifying a source or destination ontology are possible. This provides for searching semantic correspondences for a term in question, returning references to all available ontologies, thus also showing the frequency of its occurrence. Alternatively, direct ontology comparisons are facilitated. The system searches the knowledge base like a dictionary, out of which machine-generated suggestions are extracted and presented to the users in form of a list of suitable references for selection. From this users can select a reference, or, when none of the suggestions is considered appropriate, create a new one. Alternatively, users may proceed without selecting from the list. Figure 10 shows the prototypically implemented suggestion list for a comparison of the two example business processes presented here. Aside from the standard user interface shown here for retrieving references and supplying feedback to the system, there is an additional interface for expert users for administration and data management options. The emerging ontology can be used at the time of creating new models searching for a suitable element label as well as and for explaining the intended meaning in existing models that need to be compared and related semantically. Figure 11 shows extracts of the related model ontologies of the example process models with some semantic correspondences verified by users. In addition, the emerging ontology is directly exploitable for further development by means of an ontology editor. Combining the model ontologies with our upper-level ontologies allows for searching for specific model types, e.g., searching for all EPCs available, as well as for models of all types of a certain kind, e.g., such as process
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Figure 10. List of suggested semantic references in MODI
Figure 11. Extracts of semantically integrated heterogeneous process models
models either being EPC or UML Activity Models, through utilizing the corresponding unifying concept, here UMCO:Process, for detailing the query. Alternatively, searches for UMCO:Activity shows all business operations. With the method described, not only models of the same kind can be matched and related. Instead, linking different models is possible as well with the help of a specific MCO, here one for UML Class Models. The class model as given in Figure 1 can then be linked at the occurrences
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of the notions of “customer” and “payment” to the correspondences in the given example EPC. Alternatively, an e-business standard or company glossary can be matched for comparing existing processes and product and service descriptions.
FUTURE RESEARCH DIRECTIONS The system developed and presented here has been implemented as a prototypical solution and is being
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evaluated. Its practical application has proven the conceptual strength and practical relevance of our approach. Still, a number of aspects remain to be researched for further improvement. Since the system is based on coupling existing tools for ontology matching and storing via adapters, evaluation concerning their efficiency and performance in different domains and with huge amounts of data is of interest. Research regarding the comparison and combination of mapping tools has been conducted. Thereby, scalability is one of the main technical issues. In its present experimental status we have used freely available tools for demonstration and evaluation purposes. Additionally, research on interoperability and coordination of the different tools is necessary, as this may help in finding more customizable solutions. Furthermore, potential parallel usage could be further examined, in particular questions as to how meaningful result combinations can be achieved, focusing on possibilities for calculating adaptively computed weighted result combinations and measuring their quality at run time. Presently, depending on the number of words contained in the concepts terms, name matching performs well only on smaller-sized terms, whereas term-frequency-based methods show better result for larger-sized terms, as they can often be found in the model element labels of process models. Our immediate next steps are the finalizing of the implementation works by adding user support in form of semantic net visualization and the extension to include knowledge processing of further types of models.
CONCLUSION We have shown here an approach using ontologies for achieving semantic interoperability of conceptual models describing e-business. A method for reusing existing models and relating the conceptual knowledge contained without huge manual efforts is developed. We have created a way for
reengineering non-ontological resources of different types and formats for meaningful relating with the help of supporting ontologies especially created for this purpose. The related models can be analyzed and compared regarding the intended meaning of their elements. The automatically produced results provide an ontology basis without initial manual laborintensive preparation and creation efforts. Through including user input, a possibility for overcoming the shortcomings of automated knowledge computing is presented, as human support is included for assessing and improving the quality of the mappings found by way of automated matching. The resulting reference collection provides support for the clarification of uncertainties and resolving of ambiguities in the domain language and allows for integrating models of any type. Our system works as a mediating medium and helps providing the grounds for concentrating on the actual questions of process integration and activity sequencing. With this example of putting ontology technologies to use, we can propose a method towards resolving real-world interoperability issues in electronic business. However, its adoption into everyday business requires more research to prove user acceptance and deal with user evaluation. Similar to social software systems, our system needs a critical mass of users in order to be useful. Since the collection of semantic references is envisioned to evolve and improve over time through user feedback, users actively adopting and engaging in sharing their knowledge are crucial to achieving this growth. It needs to be proven that the method and therefore our framework delivers sufficient benefits and is easy to use. In general, the objective when working with ontologies should to be to limit the amount of technical knowledge required of business users and to supply them with the most easy-to-use interface possible for easing the spread of this technology. The field of ontologies for electronic business is very lively, as can be seen from the huge
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number of terminologies and ontologies already available. However, analysis as well as ontology development requires expertise from knowledge engineers and domain experts alike. We found experience in modeling to be helpful for introducing the possibilities semantic technologies can offer. However, due the novelty in applying semantic technologies, using or developing own ontologies for business modeling purposes is not easily performed by domain experts. The introduction to the new technologies can be complicated due to the prototypical status of many freely available tools. Furthermore, so far, there are not many professional tools available offering interfaces for domain experts without a lot of knowledge engineering expertise. Overall, the idea of modeling ontologies for the Semantic Web and relating them has lead to new possibilities for realizing electronic business and enabling interoperability by semantically integrating these ontologies. Exploiting the World Wide Web and benefitting from it has become an accepted means for businesses. With our pragmatic approach of semantic model referencing and its implementation we hope to be able to contribute to propagating ontology usage in business modeling.
ACKNOWLEDGMENT These works have been supported by the by the German Federal Ministry of Education and Research (BMBF) under grant no. 1728X07 MODI.
REFERENCES Aier, S., Riege, C., & Winter, R. (2008). Unternehmensarchitektur – Literaturüberblick und Stand der Praxis. Wirtschaftsinformatik, (4): 297–304. Alexiev, V., & Breu, M. (2005). Information integration with ontologies: Experiences from an industrial showcase. Chichester, UK: Wiley.
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Allemang, D., & Hendler, J. A. (2008). Semantic Web for the working ontologist: Modeling in RDF, RDFS and OWL. Amsterdam: Morgan Kaufmann/ Elsevier. Ambler, S. W. (2008). The object primer: Agile model-driven development with UML 2.0. Cambridge: Cambridge Univ. Press. Antoniou, G., Franconi, E., & van Harmelen, F. (2005). Introduction to Semantic Web ontology languages. In N. Eisinger & J. Maluszynski (Eds.), Reasoning Web. (LNCS 3564). First International Summer School 2005, Msida, Malta, July 25-29, 2005, Revised Lectures, (pp. 1–21). Berlin, Heidelberg: Springer-Verlag GmbH. Atkinson, C., & Kühne, T. (2002). Profiles in a strict metamodeling framework. Science of Computer Programming, 44(1), 5–22. doi:10.1016/ S0167-6423(02)00029-1 Becker, J., & Pfeiffer, D. (2007). Automatic knowledge retrieval from conceptual models. In E. Proper, T. Halpin & J. Krogstie (Eds.), 12th International Workshop on Exploring Modeling Methods for Systems Analysis and Design (EMMSAD’07). held in conjunctiun with the 19th Conference on Advanced Information Systems (CAiSE’07), (pp. 153–162). CEUR Workshop Proceedings. Becker, J., & Pfeiffer, D. (2008). Solving the conflicts of distributed process modelling–towards an integrated approach. In W. Golden, T. Acton, K. Conboy, H. van der Heijden, & V. K. Tuunainen (Eds.), 16th European Conference on Information Systems (ECIS 2008), (pp. 1555–1568). Becker, J., Rosemann, M., & Schütte, R. (1996). Prozeßintegration zwischen Industrie- und Handelsunternehmen - eine inhaltlich-funktionale und methodische Analyse. Wirtschaftsinformatik, 39(3), 309–316.
Semantic Interoperability Enablement in E-Business Modeling
Bézivin, J., Devedzic, V., Djuric, D., Favreau, J.-M., Gasevic, D., & Jouault, F. (2006). An M3neutral infrastructure for bridging model engineering and ontology engineering. In Konstantas, D., Boudjlida, N., Bourrières, J.-P., & Léonard, M. (Eds.), Interoperability of enterprise software and applications (pp. 159–171). London: Springer. doi:10.1007/1-84628-152-0_15 Blumauer, A., & Pellegrini, T. (2006). Semantic Web und semantische Technologien: Zentrale Begriffe und Unterscheidungen. In Pellegrini, T., & Blumauer, A. (Eds.), Semantic Web Wege zur vernetzten Wissensgesellschaft (pp. 9–25). Berlin: Springer. Bohring, H., & Auer, S. (2005). Mapping XML to OWL ontologies. In K. P. Jantke, K.-P. Fähnrich, & W.S. Wittig (Eds.), Vol. P-72. LNI, Marktplatz Internet: von e-Learning bis e-Payment. 13. Leipziger Informatik-Tage, LIT 2005, Leipzig, (pp. 147–156). Bonn: Ges. für Informatik. Braun, S., Schmidt, A., Walter, A., & Zacharias, V. (2008). Using the ontology maturing process model for searching, managing and retrieving resources with semantic technologies. In R. Meersman & Z. Tari (Eds.), On the move to meaningful internet systems: OTM 2008. (LNCS 5332). OTM 2008 confederated international conferences, CoopIS, DOA, GADA, IS, and ODBASE 2008, Monterrey, Mexico, November 9 - 14, 2008, proceedings, part II, (pp. 1568–1578). Berlin: Springer. Brockmans, S., Ehrig, M., Koschmider, A., Oberweis, A., & Studer, R. (2006). Semantic alignment of business processes. In Y. Manolopoulos, J. Filipe, P. Constantopoulos & J. Cordeiro (Eds.), Proceedings of the Eighth International Conference on Enterprise Information Systems (ICEIS 2006). Information Systems Analysis and Specification. May 2006, Paphos, Cyprus (pp. 197–203). Setúbal: INSTICC.
Brockmans, S., Volz, R., Eberhart, A., & Löffler, P. (2004). Visual modeling of OWL DL ontologies using UML. In S. A. McIlraith (Ed.), Proceedings of The Semantic Web - ISWC 2004. Third International Semantic Web Conference, Hiroshima, Japan, November 7 - 11, 2004. (pp. 198–213). Berlin: Springer. Castano, S., Ferrara, A., & Montanelli, S. (2006). A matchmaking-based ontology evolution methodology. In M. Missikoff, A. De Nicola & F. D’Antonio (Eds.), Proceedings of the Open Interop Workshop on Enterprise Modelling and Ontologies for Interoperability, Co-located with CAiSE’06 Conference, June 2006, Luxembourg. CEUR Workshop Proceedings 200. Chen, P. P.-s. (1976). The entity-relationship model: Toward a unified view of data. ACM Transactions on Database Systems, 1(1), 9–36. doi:10.1145/320434.320440 Cimiano, P., Hotho, A., Stumme, G., & Tane, J. (2004). Conceptual knowledge processing with formal concept analysis and ontologies. In P.W. Eklund (Ed.), Proceedings of the Second International Conference on Formal Concept Analysis (ICFCA 04), Concept lattices. (pp. 189–207). Berlin: Springer. Cohen, W., Ravikumar, P., & Fienberg, S. (2003). A comparison of string distance metrics for name-matching tasks. In S. Kambhampati & C.A. Knoblock (Eds.), Proceedings of IJCAI-03 Workshop on Information Integration on the Web (IIWeb-03). (pp. 73-78). Retrieved from http:// www.isi.edu/info-agents/workshops/ijcai03/ papers/Cohen-p.pdf cxml.org. (2008). Commerce XML Resources. http://www.cxml.org/. Cycorp, I. (2009). The CYC knowledge base. Retrieved from http://www.cyc.com/cyc/technology/ whatiscyc_dir/whatsincyc
395
Semantic Interoperability Enablement in E-Business Modeling
d’Aquin, M., Motta, E., Sabou, M., Angeletou, S., Gridinoc, L., & Lopez, V. (2008). Toward a new generation of Semantic Web applications. IEEE Intelligent Systems, 23(3), 20–28. doi:10.1109/ MIS.2008.54 Daconta, M. C., Obrst, L. J., & Smith, K. T. (2003). The Semantic Web: A guide to the future of XML, web services, and Knowledge Management. Indianapolis: Wiley. Database Answers. (2010). Data models. Retrieved from http://databaseanswers.org/data_ models/index.htm. de Bruijn, J. (2004). Semantic information integration inside and across organizational boundaries. (Technical Report No. DERI-2004-05-04A). Innsbruck, Austria: Digital Enterprise Research Institute. Delfmann, P., Herwig, S., & Lis, L. (2009). Konfliktäre Bezeichnungen in Ereignisgesteuerten Prozessketten – Linguistische Analyse und Vorschlag eines Lösungsansatzes. In M. Nüttgens, F. J. Rump, J. Mendling & N. Gehrke (Eds.), EPK 2009 Geschäftsprozessmanagement mit Ereignisgesteuerten Prozessketten. 8. Workshop der Gesellschaft für Informatik e.V. (GI) und Treffen ihres Arbeitkreises Geschäftsprozessmanagement mit Ereignisgesteuerten Prozessketten (WI-EPK) November 2009, Berlin. Proceedings. (pp. 178–194). Bonn: Gesellschaft für Informatik. Dietz, J. L. G. (2006). Enterprise ontology: Theory and methodology. Berlin, Heidelberg: SpringerVerlag. doi:10.1007/3-540-33149-2 Dietz, J. L. G., & Hoogervorst, J. A. P. (2008). Enterprise ontology in enterprise engineering. In R.L. Wainwright & H.M. Haddad (Eds.), Proceedings of the 2008 ACM symposium on Applied computing, (pp. 572–579). New York: ACM. Eclass. (2005). The leading classification system. White paper.
396
Euzenat, J., Mocan, A., & Scharffe, F. (2008). Ontology alignments an ontology management perspective. In M. Hepp, P. Leenheer, A. Moor & Y. Sure (Eds.), Ontology management. Semantic Web, Semantic Web services, and business applications. (pp. 177–206). Boston: Springer Science+Business Media LLC. Euzenat, J., & Shvaiko, P. (2007). Ontology matching. Berlin: Springer. Fengel, J., Paulheim, H., & Rebstock, M. (2009). Semantic synchronization in B2B transactions. In Y. Kalfoglou (Ed.), Cases on semantic interoperability for Information Systems integration: Practices and applications. (pp. 210–234). Philadelphia: Information Science Reference, IGI Global. Fengel, J., & Rebstock, M. (2009). Model-based domain ontology engineering. In M. Hepp, K. Hinkelmann & N. Stojanovic (Eds.), ACM International Conference Proceeding Series. Proceedings of the 4th International Workshop on Semantic Business Process Management (SBPM2009). Held during European Semantic Web Conference (ESWC 2009), 01. Juni 2009, Heraklion, Kreta. New York: ACM Press. Ferstl, O. K., & Sinz, E. J. (2006). Grundlagen der Wirtschaftsinformatik (5ed.). München: Oldenbourg. Fox, M. S. (1992). The TOVE project: A commonsense model of the enterprise. In F. Belli (Ed.), Vol. 604. LNAI, Industrial and Engineering Applications of Artificial Intelligence and Expert Systems. Proceedings of 5th International Conference IEA/ AIE - 92 Paderborn, 1992. (pp. 25–34). Berlin, Heidelberg: Springer. Frank, U. (1994). Multiperspektivische Unternehmensmodellierung: Theoretischer Hintergrund und Entwurf einer objektorientierten Entwicklungsumgebung. Univ., Habil.-Schr.--Marburg, 1993. Berichte der Gesellschaft für Mathematik und Datenverarbeitung (Vol. 225). München, Wien: Oldenbourg.
Semantic Interoperability Enablement in E-Business Modeling
Frank, U. (2004). Informationstechnologie und Organisation. In G. Schreyögg & A.v. Werder (Eds.), Handwörterbuch Unternehmensführung und Organisation (HWO). (pp. 472–480). S.l.: Schäffer-Poeschel. GS1 US. (2009). About RosettaNet. Retrieved from http://www.rosettanet.org/AboutRosettaNet/ tabid/276/Default.aspx García, R., & Gil, R. (2007). Facilitating business interoperability from the Semantic Web. In W. Abramowicz (Ed.), Business Information Systems. (LNCS 4439). Proceedings of the 10th International Conference (BIS 2007), Poznan, 2007, (pp. 220–232). Berlin, Heidelberg: Springer. Gašević, D., Djurić, D., Devedžić, V., & Damjanović, V. (2004). Converting UML to OWL ontologies. In The thirteenth International World Wide Web Conference. Alternate track papers & posters, (pp. 488–489). New York: ACM. Gehlert, A. (2007). Migration fachkonzeptueller Modelle. Berlin: Logos-Verl. Goméz-Pérez, A., Fernandéz-López, M., & Corcho, O. (2004). Ontological engineering. London: Springer. Gruber, T. (1993). A translation approach to portable ontology specifications. Knowledge Acquisition, 5(2), 199–220. doi:10.1006/knac.1993.1008 Gruber, T. (2007). Collective knowledge systems: Where the social Web meets the Semantic Web. Web Semantics: Science. Services and Agents on the World Wide Web, 6(1), 4–13. Grüninger, M., Atefi, K., & Fox, M. A. (2000). Ontologies to support process integration in enterprise engineering. Computational & Mathematical Organization Theory, 6, 381–394. doi:10.1023/A:1009610430261 GSA. (2005). Federal Enterprise Architecture Reference Model Ontology (FEA-RMO). Retrieved from http://web-services.gov/fea-rmo.html
Guarino, N. (1998). Formal ontology and Information Systems. Proceedings of FOIS’98 Trento 1998. (pp. 3-15). Amsterdam: IOS Press. Hadar, I., & Soffer, P. (2006). Variations in conceptual modeling: Classification and ontological analysis. Journal of the AIS, 7(8), 568–592. Hammer, M., & Champy, J. (2006). Reengineering the corporation: A manifesto for business revolution. New York: Collins Business Essentials. Havey, M. (2005). Essential business process modeling. Sebastopol, CA: O’Reilly. Hepp, M. (2007). Possible ontologies: How reality constrains the development of relevant ontologies. IEEE Internet Computing, 11(1), 90–96. doi:10.1109/MIC.2007.20 Hepp, M., & de Bruijn, J. (2007). GenTax: A generic methodology for deriving OWL and RDF-S ontologies from hierarchical classifications, thesauri, and inconsistent taxonomies. In E. Franconi, M. Kifer & W. May (Eds.), The Semantic Web: Research and applications. Proceedings of the 4th European Semantic Web Conference (ESWC 2007), (LNCS 4519). (pp. 129–144). Innsbruck, 2007. Berlin, Heidelberg: Springer. Hepp, M., Leymann, F., Domingue, J., Wahler, A., & Fensel, D. (2005). Semantic business process management: A vision towards using Semantic Web services for business process management. In F.C.M. Lau, H. Lei, X. Meng & M. Wang (Eds.), Proceedings of the IEEE International Conference on e-Business Engineering. ICEBE 2005, October 2005, Beijing, China, (pp. 535–540). Los Alamitos, CA.: IEEE Computer Society. Hepp, M., & Roman, D. (2007). An ontology framework for Semantic business management. In A. Oberweis, C. Weinhardt & H. Gimpel (Eds.), eOrganisation. Service-, Prozess-, MarketEngineering. Bd. 1. 8. Internationale Tagung Wirtschaftsinformatik (WI 2007 (pp. 423–440). Karlsruhe: Univ.-Verl. Karlsruhe.
397
Semantic Interoperability Enablement in E-Business Modeling
Hesse, W. (2005). Ontologies in the software engineering process. In Lenz, R., Hasenkamp, U., Hasselbring, W., & Reichert, M. (Eds.), EAI 2005 - Enterprise Application Integration. Proceedings of 2. GI-/GMDS-Workshop, Marburg, 2005 (pp. 3–16). Berlin: GITO-Verl. Hillairet, G., Bertrand, F., & Lafaye, J. Y. (2008). Un processus dirigé par les modèles pour la création de bases de connaissance ontologiques. In Pantel, M., & Hassenforder, M. (Eds.), IDM 2008 Actes des 4 èmes journées sur l’Ingénierie Dirigée par les Modèles. June 2008. Mulhouse. Hu, W., & Qu, Y. (2006). Block matching for ontologies. In I. Cruz, et al. (Eds.), Proceedings of the 5th International Semantic Web Conference (ISWC 2006) (LNCS 4273). (pp. 300–313). Berlin: Springer. IBM. (2010). Business process management samples & tutorials-version 7.0. Retrieved from http://publib.boulder.ibm.com/bpcsamp/ IEEE. (2009). The Suggested Upper Merged Ontology (SUMO)-ontology portal. Retrieved from http://www.ontologyportal.org/ ISO/ IEC. (2002). ISO/IEC 13250 topic maps: Second Edition 19 May 2002 English. Retrieved from http://www1.y12.doe.gov/capabilities/sgml/sc34/ document/0322_files/iso13250-2nd-ed-v2.pdf Kalfoglou, Y., Hu, B., Reynolds, D., & Shadbolt, N. (2005). CROSI project final report. Technical Report. University of Southampton. Kalfoglou, Y., & Schorlemmer, M. (2005). Ontology mapping: The state of the art. In Kalfoglou, Y., Schorlemmer, M., Sheth, A., Staab, S., & Uschold, M. (Eds.), Dagstuhl Seminar Proceedings: No 04391. Dagstuhl, Germany: Semantic Interoperability and Integration.
398
Kalfoglou, Y., Schorlemmer, M., Sheth, A., Staab, S., & Uschold, M. (Eds.). (2005). Dagstuhl Seminar Proceedings: No 04391. Dagstuhl, Germany: Semantic Interoperability and Integration. Kappel, G., Kramler, G., Kapsammer, E., Reiter, T., Retschitzegger, W., & Schwinger, W. (2005). ModelCVS-a semantic infrastructure for modelbased tool integration. Technical Report. Vienna: University of Technology. Keller, G., Nüttgens, M., & Scheer, A. W. (1992). Semantische Prozeßmodellierung auf der Grundlage Ereignisgesteuerter Prozeßketten (EPK) (Veröffentlichungen des Instituts für Wirtschaftsinformatik No. 89). Saarbrücken: Universität des Saarlandes. Kensche, D., Quix, C., Chatti, M. A., & Jarke, M. (2007). GeRoMe: A Generic Role based Metamodel for model management. In Spaccapietra, S., Atzeni, P., Fages, F., Hacid, M.-S., Kifer, M., & Mylopoulos, J. (Eds.), Journal on Data Semantics VIII, (LNCS 4380) (pp. 82–117). Berlin, Heidelberg: Springer. doi:10.1007/978-3540-70664-9_4 Klein, M. (2001). Combining and relating ontologies: An analysis of problems and solutions. In A. Gómez Pérez, M. Gruninger, H. Stuckenschmidt & M. Uschold (Eds.), Proceedings of the IJCAI-01 Workshop on Ontologies and Information Sharing. in conjunction with the International Joint Conference on Artificial Intelligence, (pp. 53–62). CEUR Workshop Proceedings. Klein, M., Fensel, D., van Harmelen, F., & Horrocks, I. (2001). The relation between ontologies and XML schemas. Electronic Trans. on Artificial Intelligence, 6(4). Retrieved from http://www.ida. liu.se/ext/epa/cis/2001/004/paper.pdf Knublauch, H. (2010). A tutorial OWL ontology for a Semantic Web of tourism. Retrieved from http://protegewiki.stanford.edu/index.php/Protege_Ontology_Library#OWL_ontologies
Semantic Interoperability Enablement in E-Business Modeling
Krallmann, H., Frank, H., & Gronau, N. (2002). Systemanalyse im Unternehmen: Vorgehensmodelle, Modellierungsverfahren und Gestaltungsoptionen (4ed.). München: Oldenbourg. Kugeler, M., & Rosemann, M. (1998). Fachbegriffsmodellierung für betriebliche Informationssysteme und zur Unterstützung der Unternehmenskommunikation. Informationssystem Architekturen, 5(2), 8–15. Kurtev, I., Bézivin, J., Jouault, F., & Valduriez, P. (2006). Model-based DSL Frameworks. In OOPSLA ‘06: Companion to the 21st ACM SIGPLAN symposium on Object-oriented programming systems, languages, and applications (2006), Portland, (pp. 602–616). Laboratory for Applied Ontology. (2009). DOLCE: A descriptive ontology for linguistic and cognitive engineering. Retrieved from http:// www.loa-cnr.it/DOLCE.html Lankhorst, M. (2009). Enterprise architecture at work: Modelling, communication and analysis. Second Edition (2. Aufl.). The Enterprise Engineering Series. Berlin, Heidelberg: Springer. Mahr, B. (2009). Information Science and the logic of models. Software and System Modeling, 8(3), 365–383. doi:10.1007/s10270-009-0119-2 McGuiness, D. L. (2003). Ontologies come of age. In Fensel, D., Hendler, J., Lieberman, H., & Wahlster, W. (Eds.), Spinning the Semantic Web: Bringing the World Wide Web to its full potential (pp. 171–193). Cambridge: MIT Press. Melnik, S., Rahm, E., & Bernstein, P. A. (2003). Rondo: A programming platform for generic model management. In A.Y. Halevy (Ed.), Proceedings of the ACM SIGMOD International Conference on Management of Data. 2003, San Diego, (pp. 193–204). New York: ACM.
Mizoguchi, R. (2003). Tutorial on ontological engineering. New Generation Computing, 21(4), 365–384. doi:10.1007/BF03037311 Müller, W. (1998). Metamodellierung als Instrument der Verknüpfung von Unternehmensmodellen. Berlin: IPK. Murzek, M., & Kramler, G. (2007). The model morphing approach–horizontal transformations between business process models. In J. Nummenmaa & E. Söderström (Eds.), Proceedings of the 6th International Conference on Perspectives in Business Information Research - BIR’2007, (pp. 88–103). Tampere, Finland. Noy, N. (2004). Semantic integration: A survey of ontology-based approaches. SIGMOD Record, 33, 65–70. doi:10.1145/1041410.1041421 OASIS. (2010). The framework for eBusiness: White Paper. Retrieved from http://www.ebxml. org/ Omelayenko, B. (2001). Preliminary ontology modeling for B2B content integration. In A.M. Tjoa (Ed.), Proceedings of 12th International Workshop on Database and Expert Systems Applications. 2001, Munich, (pp. 7–13). Los Alamitos, CA: IEEE Computer Society. OMG. (2003). MDA guide version 1.0.1 12th June 2003. Retrieved from http://www.omg.org/docs/ omg/03-06-01.pdf OMG. (2009a). Business Process Modeling Notation (BPMN) Version 1.2, formal/2009-01-03. Retrieved from http://www.omg.org/docs/formal/09-01-03.pdf OMG. (2009b). OMG Unified Modeling Language (OMG UML), Infrastructure Version 2.2, formal/2009-02-04. Retrieved from http://www. omg.org/docs/formal/09-02-04.pdf
399
Semantic Interoperability Enablement in E-Business Modeling
OMG. (2009c). OMG Unified Modeling Language (OMG UML), Superstructure Version 2.2, formal/2009-02-02. Retrieved from http://www. omg.org/docs/formal/09-02-02.pdf Op’t Land, M., Proper, E., Waage, M., Cloo, J., & Steghuis, C. (2009). Enterprise architecture: Creating value by informed governance. The Enterprise Engineering Series. Berlin: Springer. Österle, H. (2007). Business engineering – Geschäftsmodelle transformieren. In Loos, P., & Krcmar, H. (Eds.), Springer-11775 /Dig. Serial]. Architekturen und Prozesse. Strukturen und Dynamik in Forschung und Unternehmen (pp. 71–84). Berlin, Heidelberg: Springer. Petri, C. A. (1962). Kommunikation mit Automaten (Schriften des IIM No. Nr. 2). Bonn: Institut für Instrumentelle Mathematik. Pfeiffer, D. (2007). Constructing comparable conceptual models with domain specific languages. In H. Österle, J. Schelp & R. Winter (Eds.), 15th European Conference on Information Systems (ECIS2007). Relevant rigour – Rigorous relevance. Princeton University. (2009). WordNet - About WordNet. Retrieved from http://wordnet.princeton.edu/ Rebstock, M., Fengel, J., & Paulheim, H. (2008). Ontologies-based business integration. Berlin, Heidelberg: Springer. Rothenberg, J. (1989). The nature of modeling. In Widman, L. E., Loparo, K. A., & Nielsen, N. R. (Eds.), Artificial intelligence, smulation, and modeling (pp. 75–92). New York: Wiley. Russell, S. J., & Norvig, P. (2003). Artificial intelligence: A modern approach (2nd ed.). Upper Saddle River, NJ: Prentice Hall.
400
Saeki, M., & Kaiya, H. (2006). On relationships among models, meta models and ontologies. In J. Gray, J.P. Tolvanen & J. Sprinkle (Eds.), Computer Science and Information System Reports, Technical Reports: TR-37. Proceedings of the 6th OOPSLA Workshop on Domain-Specific Modeling. Jyväskylä, Finland. Scheer, A. W. (1996). ARIS-House of Business Engineering: Von der Geschäftsprozeßmodellierung zur Workflow-gesteuerten Anwendung; vom Business Process Reengineering zum Continuous Process Improvement (Heft No. 133). Saarbrücken: Institut für Wirtschaftsinformatik (IWi). Scheer, A.-W. (2002). ARIS - vom Geschäftsprozess zum Anwendungssystem (4., durchges. Aufl.). Berlin: Springer. Scheer, A. W., & Nüttgens, M. (2000). ARIS architecture and reference models for business process management. In van Aalst, W. d. (Ed.), Business process management. Models, techniques, and empirical studies, (LNCS 1806) (pp. 376–389). Berlin: Springer. Scheer, A. W., Nüttgens, M., & Zimmermann, V. (1995). Rahmenkonzept für ein integriertes Geschäftsprozeßmanagement. Wirtschaftsinformatik, 37(5), 426–434. Schreyögg, G. (2008). Organisation: Grundlagen moderner Organisationsgestaltung; mit Fallstudien (4 ed.). Wiesbaden: Gabler. Shadbolt, N., Berners-Lee, T., & Hall, W. (2006). The Semantic Web revisited. IEEE Intelligent Systems, 21(3), 96–101. doi:10.1109/MIS.2006.62 Simon, C., & Mendling, J. (2007). Integration of conceptual process models by the example of event-driven process chains. In A. Oberweis, C. Weinhardt & H. Gimpel (Eds.), eOrganisation. Service-, Prozess-, Market-Engineering. Bd. 1. 8. Internationale Tagung Wirtschaftsinformatik (WI 2007). (pp. 677–694). Karlsruhe: Univ.-Verl. Karlsruhe.
Semantic Interoperability Enablement in E-Business Modeling
Siorpaes, K., & Hepp, M. (2007). myOntology: The marriage of ontology engineering and collective intelligence. In Proceedings of the ESWC 2007 Workshop Bridging the Gap between Semantic Web and Web 2.0. Smith, M. K., Welty, C., & McGuinness, D. L. (2004). OWL Web ontology language guide: W3C Recommendation 10 February 2004. Retrieved from http://www.w3.org/TR/owl-guide/ Staab, S., Studer, R., Schnurr, H. P., & Sure, Y. (2001). Knowledge processes and ontologies. IEEE Intelligent Systems, 16(1), 26–34. doi:10.1109/5254.912382 Stachowiak, H. (1973). Allgemeine Modelltheorie. Wien: Springer. Stachowiak, H. (1983). Erkenntnisstufen zum systemischen Neopragmatismus und zur allgemeinen Modelltheorie. In Stachowiak, H. (Ed.), Modelle - Konstruktion der Wirklichkeit (pp. 87–146). München: Fink. Strahringer, S. (1998). Ein sprachbasierter Metamodellbegriff und seine Verallgemeinerung durch das Konzept des Metaisierungsprinzips. In K. Pohl, A. Schürr & G. Vossen (Eds.), Vol. 9. CEUR Workshop Proceedings, Modellierung ‘98, Proceedings des GI-Workshops in Münster. Stuckenschmidt, H. (2009). Ontologien: Konzepte, Technologien und Anwendungen. Informatik im Fokus. Berlin, Heidelberg: Springer. Stuckenschmidt, H., & Harmelen, F. (2005). Information sharing on the Semantic Web. Springer-11645 /Dig. Serial]. Berlin, Heidelberg: Springer. SUPER Integrated Project. (2009). SUPER Ontologies. Retrieved from http://www.ip-super.org/ content/view/129/136/
Thomas, O., & Fellmann, M. (2006). Semantische Integration von Ontologien und Ereignisgesteuerten Prozessketten. In M. Nüttgens, F. J. Rump, & J. Mendling (Eds.), EPK 2006 - Geschäftsprozessmanagement mit Ereignisgesteuerten Prozessketten. Proceedings 5. GI-Workshop und –Arbeitskreistreffen, (pp. 7–23). Wien: CEURWS.org. Thomas, O., & Fellmann, M. (2007). Semantic business process management: Ontology-based process modeling using event-driven process chains. IBIS Interoperability in Business Information Systems, 2(1), 29–44. UNECE. (2006). UN/EDIFACT introduction and rules. University of Bergen. (2009). UEML. Retrieved December 29, 2009, from http://www.uemlwiki. org/ unspsc.org. (2009). UNSPSC homepage. Retrieved from http://www.unspsc.org/ Uschold, M., & Grüninger, M. (1996). Ontologies: Principles, methods, and applications. The Knowledge Engineering Review, 11(2), 93–155. doi:10.1017/S0269888900007797 Uschold, M., & Gruninger, M. (2004). Ontologies and semantics for seamless connectivity. SIGMOD Record, 33(4), 58–64. doi:10.1145/1041410.1041420 Uschold, M., King, M., Moralee, S., & Zorgios, Y. (1997). The enterprise ontology (Technical Report No. AIAI-TR-195). Artificial Intelligence Applications Institute (AIAI). Uschold, M., & Menzel, C. (2005). Achieving semantic interoperability using RDF and OWL: W3C Editor’s Draft 3 November 2005. Retrieved from http://www.w3.org/2001/sw/BestPractices/ OEP/SemInt/
401
Semantic Interoperability Enablement in E-Business Modeling
van Heijst, G., Schreiber, A. T., & Wielinga, B. J. (1997). Using explicit ontologies in KBS development. International Journal of HumanComputer Studies, 46(2-3), 183–292. doi:10.1006/ ijhc.1996.0090 Weske, M. (2007). Business process management: Concepts, languages, architectures. Berlin, Heidelberg: Springer. Wigand, R., Picot, A., & Reichwald, R. (1997). Information, organization and management: Expanding markets and corporate boundaries. Chichester, UK: Wiley. xcbl.org. (2003). About XCBL.http://www.xcbl. org/about.shtml Zelewski, S. (1999). Ontologien zur Strukturierung von Domänenwissen – Ein Annäherungsversuch aus betriebswirtschaftlicher Perspektive (Technical Report No. 3). Essen: University of GH Essen. Zhdanova, A. V., de Brujin, J., Zimmerman, K., & Sscharffe, F. (2004). Ontology alignment solution v2.0. (Esperonto project deliverable No. D1.4 V2.0). Retrieved from http://www.deri.at/ fileadmin/documents/deliverables/Esperonto/ Del1.4-V2.0-final.pdf
KEY TERMS AND DEFINITIONS
language with elements labeled in the natural language as applicable in the respective domain. In business its purpose is to describe business objects, business activities and events from a business-oriented point-of-view independent from technical and implementation specific details. Domain Semantics: Specific terminology in natural language, used in a certain domain. Electronic Business: Conduction of business supported by information technology. Mapping: Description of a semantic relation found as the result of ontology matching. Ontology: A semantic model capturing and describing knowledge for the purpose of understanding and sharing in an unambiguous manner. Ontologies may have different scopes and degrees of formality, depending on their purpose. A Webbased ontology is represented in an XML-based language. Ontology Matching: Process of reconciling two ontologies for searching for equivalences between the ontologies’ elements. Semantic Interoperability: Enablement to share and reuse business knowledge upon integrating heterogeneous sources of information concerning their intended meaning, thus making this knowledge compatible. Semantic Model Referencing: Method for semantically integrating heterogeneous models of different kinds and types concerning their modeling and domain languages.
Conceptual Model: An abstracted representation of reality, expressed in a certain modeling
This work was previously published in Electronic Business Interoperability: Concepts, Opportunities and Challenges, edited by Ejub Kajan, pp. 331-361, copyright 2011 by Business Science Reference (an imprint of IGI Global).
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Semantic Competence Pull:
A Semantics-Based Architecture for Filling Competency Gaps in Organizations Ricardo Colomo-Palacios Universidad Carlos III de Madrid, Spain Marcos Ruano-Mayoral Universidad Carlos III de Madrid, Spain Juan Miguel Gómez-Berbís Universidad Carlos III de Madrid, Spain Ángel García-Crespo Universidad Carlos III de Madrid, Spain
ABSTRACT Despite its considerable growth and development during the last decades, the software industry has had to endure several significant problems and drawbacks which have undoubtedly had negative effects. One of these aspects is the lack of alignment between the curricula offered by Universities and other kinds of education and training centres and the professional profiles demanded by companies and organizations. This problem defines DOI: 10.4018/978-1-60960-587-2.ch210
the objective of this work: to provide a set of mechanisms and a solution to allow companies to define and express their competency gaps and, at the same time, allow education centres to analyse those gaps and define the training plans to meet those needs.
INTRODUCTION The software industry has become one of the main streams of development all around the world. In
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Semantic Competence Pull
Spain, the information technology market generated a volume of 17,716 million € in 2006, which represents an increase of 7.8% with respect to the market volume in 2005 (MITC, 2007). The information services submarket experienced the highest rate of increase at 10.5%, representing 4 975 million €, and the software market sector volume was 1,600 million € (MITC, 2007). Traditionally, the information technology market demonstrated an insufficient number of practitioners due to the increasing demand for information technology professionals. Nowadays, demand continues to be relevant but it has experienced a deceleration accompanied by the appearance of market niches with unstable demand rates. Due to the scarce barriers to entry for practitioners (Joseph, 2005) work teams are formed by people from many different educational backgrounds and with diverse academic levels and training profiles (McConnell, 2003): bachelor and master graduates in Computer Science, graduates in other disciplines, licensed practitioners and undergraduate and unlicensed practitioners. During the 1990s, the demand for IT professionals exceeded the supply of qualified persons for several years (Koong, Liu & Liu, 2002). In 1999, there were 722,158 unfilled IT jobs in the United States. It was predicted that the shortage would grow to about 846,901 jobs by 2002 (Goodwin, 2000). While it is true that the economy has slowed down since the last quarter of 2000, many companies are still hiring persons with critical IT skills while other workers are being laid off (Armour, 2001; Gladwin, 2001). Additionally, the software industry has been characterized by a problem that was first identified at the beginning of the 1970s (Brooks, 1987). This problem is the inability to finish and deliver software products within the established time schedule, and not being able to remain within the planned budget, and was referred to as the ‘software crisis’ (Nauer, 1969). Latter analyses of the problem and the related literature have confirmed the clear difficulty in building software (Brooks, 1987) and have redefined the crisis as
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a breakdown or a chronic disease (Gibbs, 1994). Several key elements have been established to combat the effects of the crisis (Pressman, 2005): Project, Product, Development process and Personnel. Regarding the latter, human factors, considered by many authors as Peopleware (DeMarco, 1987), are proving as crucial aspects in the field of software development. Boehm (1981) points out that subsequent to the size of the product, personnel factors have the most important influence on the total effort necessary for the development of a software project, and that personnel characteristics and human resources related activities constitute the most relevant source of opportunities for improving software development (Boehm, 2000). On the same issue, some other authors state that inadequate competence verification of software engineers is one of the principal problems when it comes to carrying out any software development project (McConnell, 2003). In the information and communications technologies (ICT) field, software is a critical element. Failure rates associated with software projects are really high, and the personnel included in software development teams is one of the most decisive aspects for projects and their deficiencies (Pressman, 2005). The teams should be comprised of practitioners having heterogeneous education and experience (McConnell, 2003) and human resources management systems should be easily able to identify and assess the engineers’ professional training with the objective of improving the workforce’s competence level (Curtis, 2001).
Current Labour Market Situation This section presents both the current situation and the evolution of the labour market from the point of view of the demand for practitioners and their competency profiles. Historically, employment in the field of Information Technologies has been impacted by several crises such as the bankruptcy of dotcom companies, the delays in the adoption
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of new technologies and the worldwide economical crisis (Zamorano, 2003). These circumstances lead to a wave of dismissals and factory closures (Zamorano, 2003) and to an intense modification of the competences demanded in practitioners. The volume of the workforce required and the reorganization of labour markets define a constantly changing environment shifting towards an increase of the competency level. This consequently instigates a deceleration of the increase in salaries (Mallet, 1997), which forces the practitioners to improve their education and training. Historically, the professional environment in the Information Technologies labour market has been characterized by a strong lack of qualified practitioners (Casanovas, 2004). In 2003, according to AETIC (Asociación de Empresas de Electrónica, Tecnologías de la Información y Telecomunicaciones, Spanish Association of Electronics, Information Technologies and Telecommunications Companies), the ICT market grew 6%, up to a volume of 75,818╯million╯€. However, direct employment in the sector showed a recession of 4.1% and there was an 8,000 reduction in the number of jobs (Ruiz, 2004). In 2004 the ICT market grew 9% up to 82,535 million € (MITC, 2005); and direct employment displayed an increase, however, the growth was trivial. The contribution of the ICT sector to production in that year represented 11.811 million €, growing 4.7%. This indicates that the sector underwent a smaller growth compared to the overall activity in Spain, whose GDP was 6.6%. These figures, viewed in the international economic context, show that the ICT sector in Spain rather grows at a higher rate than the European average (2.8%), although at an inadequate pace for conformance with the convergence plans for the relevance of the sector in the European economy. An overview of the current situation of labour markets is provided by the RENTIC report (Fernández, 2002). This report shows the results obtained from an analysis of the job vacancies in ICT sector published in relevant Spanish newspa-
pers. The analysis was focused on the specific ICT knowledge profile required in the offers, as well as some other complementary requirements such as languages, degree, and behaviour competences. The study was carried out using 249 published job offers. Such a reduced data population does not allow a detailed analysis of its conclusions, but it should be noted that the relevance granted by the study to ‘personal competences’ is a reflection of the general (De Ansorena, 1996) or generic (González & Wagenaar, 2003) competences required. The report concludes that there is an evident interest on hiring personnel with both technical and general competences, and a requirement for education and training centres to meet companies’ requests. Lastly, the author remarks that there is an insufficient description of competences in the curriculums of candidates. Some of the conclusions provided by the RENTIC report show latent similarities with the analysis provided by the Bureau of Labor Statistics. This report discusses the tendency of hiring IT practitioners with strong technical, interpersonal and business skills in a labour market in which software engineering is projected to be one of the fastest-growing occupations from 2004 to 2014 (Bureau of Labor Statistics, 2006). This scene should result in very good opportunities for those college graduates with at least a bachelor’s degree in computer engineering or computer science. Another significant trend with implications in both the business and labour market is the two-way flow of foreign project contracts and software-skilled immigrants. On the one hand, firms may aim to cut costs by shifting operations to lower wage foreign countries with highly educated workers who have strong technical skills (Bureau of Labor Statistics, 2006). On the other hand, countries like India, where about 100,000 English-speaking software professionals graduate per year, can be a source of practitioners to compensate for the lack of qualified resources in developed countries.
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In short, the labour market situation for ICT, and particularly Software Engineering, situation is significantly changing. Additionally, this knowledge area shows an extremely rapid evolution: its knowledge doubles every three years, and competences have a mean lifetime of two and a half years (Ang, 2000). The proliferation of new areas will continue to grow from rapidly evolving technologies such as e-commerce, WWW applications, cyber security, mobile technologies, and wireless networks, among others (Bureau of Labor Statistics, 2006). The combination of these two facts forces practitioners to retrain almost constantly and, thus, organizations must implement mechanisms to measure the evolution of the competences of their personnel, and establish policies to allow the monitoring of the evolution of recently acquired competences.
Problem Statement In the previous sections, a labour market situation has been described which indicates a clear misalignment between the demand for qualified staff and supply of college graduates. Organizations require either the hiring of skilled practitioners, or the training of their personnel in order to comply with business changes, improve productivity or start new projects. Moreover, traditional education channels are slow and rarely specific; there is no connection between the organisation’s needs and the educational content, and if a connection exists, its effects are trivial (McConnell, 2003). The lack of specification with respect to defining and fulfilment of professional careers can hinder the adaptation of graduates’ professional competencies to the requests of labour markets. This circumstance is threatening countries’ prosperity (Career Space, 2001) and is forcing organizations to create and finance “Corporate Universities” (Casanovas, Colom, Morlán, Pont & Sancho, 2004). This not only delays the incorporation of professionals to development projects, but also implies an increase in costs for organizations.
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Considering this scenario, corporate universities are not the solution, since they combine the characteristics of both businesses and educational centres, and they are usually created and based upon non formal contacts between organizations. Moreover, according to the point of view of LifeLong learning, “enterprises need lifelong learning – that is, studies that one pursues during life and particularly during one’s working career. It includes basic education, further and continuous education, graduate and postgraduate studies, work/job-related and general studies, and a general interest in trying to understand the evolution of society and of work. Lifelong learning is a way to update and upgrade competence systematically; in fact, it is a form of “human recycling”, especially in situations where employees move from one job to another (Otala, 1994, pp. 13). The integration of the concepts of a pull strategy and LifeLong learning allows the creation of a solution to the problem described in this work, with which organizations will be able to fulfil their competency gaps. At the same time, it will allow professionals to follow a progressive development of their competences during their careers and adapt this development to specific market and emerging requirements as fast and precisely as possible.
PROPOSED SOLUTION This section presents a novel and promising architecture that applies and takes advantage of the best capabilities of semantics in the field of competence management. The objectives of the research and an overview of the architecture will be discussed.
Objectives Semantic Competence Pull has been defined as one main objective, which is comprised of a set of inherent sub objectives. The main objective is to minimize the misalignment between educational
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centres and organizations’ competency needs by determining competency gaps in the organizations, defining the training plan to fill in those gaps, and thus identifying the necessary personnel with the required competency profile. In order to fulfill this objective, organizations should be able to express and define their professional profiles and competency needs by means of a unified mechanism, and training centres and education systems should be able to define the profiles of their graduates in an equivalent way. Another interesting objective is the implementation of a mechanism to allow the exchange of information between both organizations and training centres so that they can establish a fluent and productive communication.
Overview An overview of Semantic Competence Pull is presented in Figure 1. The figure shows organizations which represent any enterprise or company with competency gaps in their personnel. These gaps can originate from market or technology changes, new business lines, new commercial relationships, or other economic or business factors. By means of a description based on competences, the organizations express their needs in terms of training
current workers or hiring trained professionals. On the other side of the system, Semantic Competence Pull allows education and training centres to analyse the gaps existing in the organizations and consequently determine, or design if necessary, the training plans constructed to fulfil the competency requirements of the organizations. The next section provides a detailed definition of the components of Semantic Competence Pull that permit the implementation of the aforementioned functions.
SOLUTION DETAILS In this section, we present a novel and promising architecture and a set of algorithms to provide a potential solution to the situation depicted in the previous section. We propose a tailor-made value-adding technological solution which addresses the aforementioned challenges and solves the integration problem with respect to searching, finding, and integrating heterogeneous sources through semantic technologies.
Figure 1. Semantic competence pull overview
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Knowledge-Extraction Algorithms First of all, we propose the application of a set of algorithms and knowledge extraction techniques to the various sources of information, where we obtain the semantic descriptions of each and every organization involved. These algorithms are usually applied in Information Retrieval, so their use in this domain is a novel contribution of the work presented. The first algorithm is the Vector Space Model (Salton, Wong & Yang, 1975), an algebraic model used for information filtering, information retrieval, indexing and relevancy rankings. It represents natural language documents (or any objects, in general) in a formal manner through the use of vectors (of identifiers, such as, for example, index terms) in a multi-dimensional linear space. Documents are represented as vectors of index terms (keywords). The set of terms is a predefined collection of terms, for example the set of all unique words occurring in the document corpus. Relevancy rankings of documents in a keyword search can be calculated, using the assumptions of document similarities theory, by comparing the deviation of angles between each document vector and the original query vector, where the query is represented as the same type of vector as the documents. The second algorithm applies Latent Semantic Analysis (LSA) (Deerwester, Dumais, Furnas, Landauer & Harshman, 1990), an algorithm for analyzing relationships between a set of documents and the terms they contain by producing a set of concepts related to the documents and terms. LSA uses a term-document matrix which describes the occurrences of terms in documents. A typical example of the weighting of the elements of the matrix is the TF-IDF (Term Frequency–Inverse Document Frequency): the element of the matrix is proportional to the number of times the terms appear in each document, where rare terms are up-weighted to reflect their relative importance. Finally, we validate the set of terms extracted from the different organizations with online lexi-
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cal resources, such as Wordnet. Dictionaries are generally considered as a valuable and reliable source containing information about the relationships among terms (e.g. synonyms). Also, Wordnet can add conceptual meaning to the tags, and there is an RDF transcript available.
Functional Architecture Competency gaps can be expressed as a set of instances, belonging to a particular organization whereby the organization to which it belongs to and the role it plays are clearly defined in a specific ontology. Each role has a particular policy (or policies). A Policy (P) represents a conceptual feature reserved for each role in a community and expressed through a set of Rules (R1,R2,...,Rn). Essentially a Rule is a function that takes an access request as input and results in an action (permit, deny or not-applicable). A rule is composed of the triple Subject (S), Resource (R) and Action (A) that must be fulfilled for a rule to apply to a given request. In the proposed conceptualization, Subjects are the identities that play specific Roles such as project leader, IT Supervisors, Customer Relationship Management (CRM) expert and sales manager. A resource is the organizations’ training resources such as deliverables, documents etc. So, the Rule is simplified as: R = {S,R,A} If “Mark Maedche” is an expert on formal methods for software validation and verification and a particular organization is interested in this knowledge, he might be subject of a training “call for experts” of that organization. Rules are then defined by means of Subject (“Mark Maedche”), Resource (“Software V&V expertise”) and Action (“Call for Experts”). Obviously, Policies are defined over the Rule, so an organization could simply list or cluster a number of organizational competences of interest. These Policies will imply
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a set of Rules that can be inferred by means of an underlying logical formalism. The framework presented would not have any real use if the inference capability of the framework were not taken into account. Defining the needs of an organisation according to Policies and Rules encapsulates a body of knowledge which represents the structure of the requirements of the organisation. Thus, further knowledge can be inferred from the established relationships to describe both the organisation and the application of the knowledge. Languages defined for providing Semantics give great support for reasoning properties, since when they were defined, requisites were established to guarantee enough expressive power and reasoning support. Any ontology language for Semantic Web is based on formal semantics, which means that the ontologies semantics defined by the language are not influenced by either subjective intuitions or open interpretations (Antoniou & Van Harmelen, 2004). This has particular relevance to mathematical logic, since it allows one-way inference from the knowledge expressed in a non explicit manner. The ontologies inference capacity also allows the identification of any instance with a class although it is not directly declared in it. For instance, if an employee has hierarchical relationships with other employees, we can deduce that he is a boss. In summary, automatic reasoning allows the verification of more cases that can be checked manually, since it evaluates all the ontology singularities and the characteristics declared in it. Consequently, the framework domain can establish relationships which are a closer representation of the real organization based on logical relationships. Unfortunately, an ontology language’s inference capacity and its expressivity are two divergent questions. The greater the expressive capacity of the language, the less inference, since the computationality cannot be guaranteed. Because of this, OWL language (W3C, OWL Web Ontology Language Overview, 2004), nowadays the most widespread ontology Semantic Web language,
offers three language versions that differ in their expressivity capacity: OWL Full, OWL DL and OWL Lite. OWL can be considered as being comprised of three sublanguages with increasing expressivity capacities (Gasevic, Djuric, & Devedzic, 2006). OWL Lite gives support to hierarchical constructions and simple restrictions. However, OWL DL offers maximum expressivity, based on Description Logics that can guarantee the ontologies computability, which means that it can be processed in a finite time. OWL Full offers maximum possible expressivity, based on FirstOrder-Logic, and a syntactic freedom, however, it does not guarantee ontology computability nor decidability. In the present context, the maximum expressivity capacities are intended since we need an ontology which most closely reflects the real world. In contrast, inference capacities cannot be affected since they are highly needed to infer privileges. Due to the inference restrictions of OWL Full, it has to be discarded, OWL Lite is also discarded since it places too many limitations on the expressivity of ontologies. However, OWL DL offers enough expressive power, guaranteeing the inference capacity for the framework. The ontology languages expressivity shows inherent limitations due to their tree-like structure. Some logic suppositions cannot be inferred natively; for example, if a person has a brother and a son, the uncle-nephew relationship cannot be inferred. This limitation is solved by applying horn logic languages on top of ontologies. Horn Logic languages are Rule-like languages where knowledge is defined by: A1,...,An → B where {Ai and B} are atomic formulas that can understood as, if {A1 … An} are true, then B is also true. These languages are the perfect complement to the logic offered by ontology languages. Horn Logic and Predicate Logic are orthogonal between them, which means that none of the
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logics is subset of the other. Languages based on Horn Logic have been defined to lie on an upper layer of ontology languages, integrating both expressivity and reasoning power. However, the decidability guarantee in Horn Logic languages needs to impose some restrictions on its expressiveness (W3C, SWRLSWRLSWRLSWRL: A Semantic Web Rule Language, 2004) and adds some additional complexity to the framework. In this section, a logics-based knowledgeenriched functional architecture has been outlined, which fully supports formally the approach and conceptual model for the Semantic Competence Pull. In the following section, the actual software architecture underlying the functional architecture will be discussed.
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Software Architecture Our architecture is a service oriented architecture (SOA), which is a software system consisting of a set of collaborating software components with well-defined interfaces that combined perform a task. These components may be distributed and executed in different network locations, connected through different communication protocols. Also, these components can be plugged-in and pluggedout from the system. The Semantic Competence Pull Architecture is composed by a number of components depicted in Figure 2. These components will now be described:
Figure 2. Semantic competence pull architecture
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Competence-oriented semantic descriptions: Competences are stored by means of semantic descriptions, which are based on the fundamental traits of the competencies. Particularly, Policies and Rules originating from the different organizations. RDF repository: The RDF repository is a semantic data store system that allows semantic querying and offers a higher abstraction layer to enable fast storage and retrieval of large amounts of RDF, while maintaining a lightweight architecture approach. An example of such a system is the OpenRDF Sesame RDF Storage system (Open RDF Sesame, http://www.openrdf. org), which deals with data integration. The advantages of using RDF as a “lightweight” ontology language partially rely on Faceted Search and Browsing techniques. These techniques will be analyzed at the end of this section. GUI: This is the component that interacts with the user. It collects the users request and presents the results obtained. In our particular architecture, the GUI will collect requests pertaining to search criteria, such as, for example, “competences related to Information Systems”. The GUI communicates with the Manager component providing the user request and displays the results provided as a response from the Manager component.
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Reasoning engine: The Reasoning Engine component uses Description Logics, which can guarantee the ontologies computability. As previously stated, this allows the processing of queries in a finite time. The selected reasoning engine is Pellet, a Javabased DL reasoning engine.
The workflow of the different components of the architecture is supported by the Functional Architecture described in the previous sections. Fundamentally, organizations define their core competencies using the Policies, Rules and Subject (S), Resource (R), Action (A) model. These descriptions can be extracted using the knowledgeextraction set of algorithms depicted previously, and they are stored by means of semantics in the Storage Component. Organizations interested in bridging their competencies gap can browse and search (by means of faceted search or browse or structured search, for example) the competencies of their organizations using Semantic Competence Pull. Since their needs in terms of competencies are also defined using the Policies- Rules model, inference serves as a basis for recommendation, and the Semantic Competence Pull provides a well-defined architecture providing matching functionality.
Example: Using Semantic Competence Pull Finally, we would like to illustrate the use of Semantic Competence Pull with a real-world case study scenario which demonstrates the breakthroughs of our system. Enterprise Inc. needs to fill twenty Software Engineering positions. The profile of the required professionals must include expertise in the Software Engineering Management knowledge area of SWEBOK (Abran & Moore, 2004). The competence level of the professionals should be above the level specified by SWEBOK for software engineers having four years of experience. Given this situation,
Enterprise Inc. establishes a complete competence description of the desired professional profile, paying special attention to the competency gap existing in Software Engineering Management, and more specifically in Software Process Planning. This necessity is defined by means of Semantic Competence Pull. The system would perform a careful analysis of the competency profile to determine, in this case, that professionals with a specific undergraduate level in Software Process Planning are required. The next step is a search in the system’s repository to retrieve those courses with competence specifications equivalent to those demanded by Enterprise Inc. At this point there are two possible situations: there are courses matching the established criteria or there are not. In the first case, the system would return the list of retrieved courses, so that education and training centres could satisfy the competency needs, contributing professionals which match the desired requirements. In the latter case, Semantic Competence Evaluation would propose the description of a specific course to the training centres. Upon receiving the request, those centres interested in teaching the course and having the necessary personnel, would design and implement the course, would enrol students fulfilling the aforementioned requirements, and the correct termination of the course would be contingent upon the subsequent hiring of the professionals by Enterprise Inc.
ALTERNATIVES Semantic Competence Pull confronts the problem of competency gaps by providing organizations with specifically trained practitioners to make up for their lack of competences in certain areas. Thus, the solution offered to solve the problem is unique and innovative. However, there are other alternatives to deal with these kinds of situations or similar ones. A set of possible alternatives is presented in this section.
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One of the most relevant solutions to produce professionals which conform perfectly to companies’ needs is the creation of tailored and specific degrees by means of joint ventures between academic institutions and the companies. The degrees are usually an adaptation of official or widespread degrees which include some tracks or sets of elective courses designed and given by the companies and that include those areas and topics of interest to them. These kinds of educational solutions can only be afforded by relevant companies which periodically need large groups of people with a certain profile. Additionally, if the designed degree is very distinct from the official one it may cause accreditation problems to graduates, with consequent loss of interest in the course. Some companies opt for the creation of their own corporate universities. In this way they can design, establish and implement the training plans they consider necessary. Similar to the previous alternative, this solution can only be afforded by large corporations. Even so, the construction of the necessary structures to finance the school signifies a major economic and investment effort for the companies, which may make it highly unprofitable. Corporate Universities have been subjected to numerous studies and have received considerable investments since the foundation of Disney University (Solomon, 1989). The importance of this phenomenon is highlighted by specific studies carried out in the USA (Prince & Stewart, 2002), China (Sham, 2007), Germany (Andresen & Lichtenberger, 2007) and worldwide (Holland & Pyman, 2006). The Universities-Companies collaboration has been identified as one of the key factors for business development regardless as full integration or achieved by the new capacities provided by the Internet (Hilse & Nicolai, 2004). Another possibility for the integration of hiring and training processes is the creation of a new generation of employment positions from the adaptation of currently existing ones, for example, those offered by Monster, among others.
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The offer of these portals should be an aggregation of job positions and the training options that candidates should follow to improve their fit to the positions and, hence, increase the probability of being hired. Dixon (2000), pointed out that generally, e-recruiters come in two varieties: corporate recruiters and third-party recruiters. Third-party recruiters do not restrict the types of jobs posted by the employers or select specific job seekers résumés. They function as a centre for all sorts of employment. Niche recruiters which focus on smaller market segments are aimed towards more specialised types of employment. However, the major players are the executive recruiters, hightech recruiters, and medical recruiters. One common characteristic of the solutions presented so far, including Semantic Competence Pull, is that all of them seek the incorporation of new human resources to the organization. Nevertheless, in order to meet companies’ competency needs, it may not be necessary to contract additional practitioners. This is the approach proposed by Prolink (Gómez-Berbís, ColomoPalacios, Ruiz-Mezcua & García-Crespo, 2008), which considers the creation of a social network with semantic characteristics to share and reuse knowledge, expertise and lessons learned from previously conducted projects.
COST AND BENEFITS This section presents an overview of the costs associated with the implementation of the Semantic Competence Pull solution. The cost analysis has been performed taking into account development, infrastructure, operation and maintenance costs. Due to the size of the problem, the development costs have been estimated to be similar to an average COCOMO II project (Boehm et al., 2000) with a temporal cost of 14,500 man-hours. This cost can be assumed as a differential cost of implementing the solution.
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Infrastructure and operation costs of adopting Semantic Competence Pull could be integrated into the current infrastructure and operation costs, because the solution could be added to the existing structure of the organisation. The only requirement with respect to infrastructure is that the solution should be accessible via Web, and the connection should have enough capacity to withstand the traffic generated by the system. Maintenance tasks for Semantic Competence Pull entail a significant human cost. There should be personnel dedicated to the addition, modification and maintenance of the information processed within the system. This information includes professional profiles, course plans, competence descriptions and needs, etc., and the tasks should be performed at both sides of the solution: the organizations as well as the training and education centres. In summary, the economic costs for implementing and adopting Semantic Competence Pull are not significantly excessive. However the adoption of such a solution must be accompanied by a modification of the traditional way of working in the organizations and the educational bodies, mainly because of the adaptation of the current profiles and requirements for the competency paradigm.
RISK ASSESSMENT A risk analysis of the implementation and adoption of Semantic Competence Pull has been made by means of a SWOT analysis. The strengths of the solution stem from the combination of two solid foundations. On the one hand, the application of the most novel academic recommendations which focus their efforts on the definition of professional profiles, academic degrees and training plans in terms of competences; and which are fully aligned with the emerging standardised educational framework in Europe. On the other hand, the adaptation of a set of widespread standards and tools (HR-XML,
OpenRDF Sesame, YARS, Semantic Web …) that perfectly complement the architecture contribute to the construction of this solution. When considering those aspects which might hinder the successful implantation of Semantic Competence Pull, two features should be outlined. The first one is the possible inability of the organizations to express and define professional roles and needs in terms of competences. This fact implies a profound change in the traditional structure of those organizations which have historically defined their needs according to legacy, stovepipe frameworks. In other words, defining competences in a static way, without their integration into the IT infrastructure of the organisation. The second issue is representative of the same weakness, but on the academic supply side. Universities and official education centres must adopt the competency paradigm into their models because of the standardisation of the European Higher Education Area. Non-official private centres should adopt the aforementioned paradigm in order to be able to use Semantic Competence Pull. Undoubtedly, the implantation of Semantic Competence Pull can take advantage of the current economic situation which promotes a buoyant labour market which will welcome the solution presented in this research. Moreover, the novelty of Semantic Competence Pull, in terms of technology and methodology, must be definitely considered as a positive aspect. Lastly, the intensive increase in the utilization of Internet and Semantic Web technologies paves the way for the globalization of the resources. Finally, two closely related threats to Semantic Competence Pull should be discussed. The first one is the evident shortage of training and education in the Information Technologies market, which is directly linked to the lack of consciousness of IT practitioners with respect to continuous improvement, education and training. The risk assessment performed in this section is summarized in Figure 3.
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Figure 3. SWOT analysis
FUTURE RESEARCH DIRECTIONS The definition of new academic initiatives for university degrees incorporating competences descriptions has been a widespread trend across Europe since the advent of the European Higher Education Area. According to the guidelines established by the European directive and the academic initiatives sponsored by the IEEE/ACM joint initiative, the creation of undergraduate and master university degrees oriented to the verification of semantic scenarios such as those presented in this work have been proposed. Secondly, it would be interesting to define and create career paths incorporating specific suggestions with regard to competency levels and the necessary courses and accreditations to reach all the defined levels. According to McConnell (2003), organizations currently do not provide career paths for ICT workers and Software Engineers. However, this aspect has proven to be a characteristic feature of mature professions (Ford & Gibbs, 1996). Taking into account previous works on Competence Management, from the perspective of either ontology creation (Sicilia, 2005), the construction of integrated systems for specific organizations (Lindgren, Stenmark & Ljungberg, 2003), or their exchange among isolated systems via HR-XML, the definition and development of competences must be performed not only following their veri-
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fication for a specific position or project, but should enrich learning organizations in an strategic way, providing a sound basis upon which to build a long term competitive advantage. This competitive advantage is achieved, in the case of the cited works, by means of the classification and management of the competences in organizations and, in the case of our work, by the collaboration between the providers and receivers of knowledge and those who harness it.
CONCLUSION Semantic Competence Pull, the technological solution introduced in this chapter represents a tailor-made value adding contribution aimed to the fulfilment of competency gaps in organizations, encompassing the distinctive features of semantic technologies. The solution comprises the software architecture of an information system supporting this solution. The main contribution of Semantic Competence Pull is the integration of a novel and promising architecture and the concept of realtime alignment of the necessities of companies with the possibilities of training professionals in education centres. The main objective of the presented solution is to fulfil competency needs in the fastest and most precise way as possible; which subsequently reduces the elapsed time for
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the incorporation of new subjects and courses to curricula. This is particularly interesting at master and specialization courses level because it increases the knowledge that training centres have about companies’ requirements. On the other hand, Semantic Competence Pull exhibits an evident drawback due to the fact that its implantation could imply a profound modification in the stakeholders’ way of working. Nevertheless, the significant benefits that it can produce for all parties identify it as an attractive solution to be adopted and supported.
REFERENCES Abran, A., & Moore, J. W. (2004). Guide to the Software Engineering Body of Knowledge: 2004 Version. IEEE Computer Society Press. Andresen, M., & Lichtenberger, B. (2007). The corporate university landscape in Germany. Journal of Workplace Learning, 19(2), 109–123. doi:10.1108/13665620710728484 Ang, S., & Slaughter, S. (2000). The Missing Context of Information Technology Personnel: A Review and Future Directions for Research. In: Zmud, R.W. (Ed.), Framing the Domains of IT Management: Projecting the Future through the Past. Pinnaflex Educational Resources, Cincinnati, Ohio. Antoniou, G., & Van Harmelen, F. (2004). A Semantic Web Primer. MIT Press. Armour, S. (2001). Companies Hire Even As They Lay Off. USA Today. May 15, A1. Boehm, B. W. (1981). Software Engineering Economics. Prentice Hall, Englewood Cliffs, New Jersey. Boehm, B. W., Horowitz, E., Madachy, R., Reifer, D., Clark, B. K., Steece, B., et al. (2000). Software Cost Estimation with COCOMO II. Prentice Hall, Upper Saddle River, New Jersey.
Brooks, F. P. (1987). No Silver Bullet: Essence and Accidents of Software Engineering. Computer, 20(4), 10–19. doi:10.1109/MC.1987.1663532 Bureau of Labor Statistics (Ed.). (2006). Computer Software Engineers. Occupational Outlook Handbook, 2006-07 Edition. U.S. Department of Labor. Career Space (Ed.). (2001). Directrices para el desarrollo curricular. Nuevos currículos de TIC para el siglo XXI: el diseño de la educación del mañana. International Co-operation Europe Ltd, Luxembourg. Casanovas, J., Colom, J. M., Morlán, I., Pont, A., & Sancho, M. R. (2004). Libro Blanco sobre las titulaciones universitarias de informática en el nuevo espacio europeo de educación superior. Proyecto Eice, ANECA. Curtis, B., Hefley, W. E. & Miller, S. A. (2001). People Capability Maturity Model (P-CMM®) Version 2.0. CMU/SEI-2001-MM-01. De Ansorena, A. (1996). 15 pasos para la selección de personal con éxito. Métodos e instrumentos. Paidos, Barcelona. Deerwester, S. Dumais, Furnas, G. W. Landauer, T. K. Harshman, R. (1990). Indexing by Latent Semantic Analysis. Journal of the Society for Information Science, 41(6), 391–407. doi:10.1002/ (SICI)1097-4571(199009)41:63.0.CO;2-9 DeMarco, T., & Lister, T. R. (1987). Peopleware: Productive Projects and Teams. Dorset House, New York. Dixon, P. (2000). Job Searching Online for Dummies. IDG Books Worldwide Inc., Boston, MA. Fernández Sanz, F. (2002). Estudio de la oferta de empleo en Nuevas Tecnologías de la Información y de las Comunicaciones. Requisitos para el empleo. Universidad Europea de Madrid.
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Ford, G., & Gibbs, N. E. (1996). A Mature Profession of Software Engineering. Software Engineering Institute, Technical Report CMU/ SEI-96-TR-004 ESC-TR-96-004. Gaaevic, D., Djuric, D., Devedzic, V., & Selic, B. (2006). Model Driven Architecture and Ontology Development. Springer-Verlag. Gibbs, W. (1994). Software’s Chronic Crisis. Scientific American, 271(3), 72–81. Gladwin, L. (2001). Dot-Com Bust A Mixed Bag for IT Staffing. Computerworld (39), May 7, p. 38. Gomez, J. M., Colomo Palacios, R., Ruiz Mezcua, B., & García Crespo, A. (2008). ProLink: A Semantics-based Social Network for Software Project. International Journal of Information Technology and Management, 7(4), 392–404. doi:10.1504/IJITM.2008.018656 González, J., & Wagenaar, R. (2003). Tuning Educational Structures in Europe. Universidad de Deusto. Bilbao. Goodwin, B. (2000). Government Slashes Red Tape to Let in Overseas IT Workers. Computer Weekly, May 11. Harth, A., & Decker, S. (2005). Optimized Index Structures for Querying RDF from the Web. Proceedings of the 3rd Latin American Web Congress. Hilse, H., & Nicolai, A. T. (2004). Strategic learning in Germany’s largest companies: empirical evidence on the role of corporate universities within strategy processes. Journal of Management Development, 23(4), 374–400. doi:10.1108/02621710410529811 Holland, P., & Pyman, A. (2006). Corporate universities: a catalyst for strategic human resource development? Journal of European Industrial Training, 30(1), 19–31. doi:10.1108/03090590610643851
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Joseph, D., Ang, S., & Slaughter, S. (2005). Identifying the prototypical career paths of IT professionals: a sequence and cluster analysis. Proceedings of the 2005 ACM SIGMIS CPR Conference on Computer Personnel Research (pp. 94-96). Koong, K. S., Liu, L. C., & Liu, X. (2002). A Study of the Demand for Information Technology Professionals in Selected Internet Job Portals. Journal of Information Systems Education, 13(1), 21–28. Lindgren, R., Stenmark, D., & Ljungberg, J. (2003). Rethinking competence systems for knowledge-based organizations. European Journal of Information Systems, 12(1), 18–29. doi:10.1057/palgrave.ejis.3000442 Mallet, L. (1997). Títulos y Mercado de trabajo: resultados y cuestiones. Ágora de Salónica. CEDEFOP. McConnell, S. (2003). Professional Software Development. Addison-Wesley, Boston. Ministerio de Industria, Turismo y Comercio (MITC). (2005). Gabinete de prensa. Ministerio de Industria, Turismo y Comercio (MITC). (2007). Las tecnologías de la información en España, 2006. Centro de Publicaciones. Nauer, P., & Randall, B. (Eds.). (1969). Software Engineering. NATO Scientific Affairs Division, Brussels. Otala, L. (1994). Industry-University Partnership: Implementing Lifelong Learning. Journal of European Industrial Training, 18(8), 13–18. doi:10.1108/03090599410068033 Pressman, R. S. (2005). Software Engineering: A practitioner’s approach. McGraw Hill, 6th edition, New York.
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Prince, C., & Stewart, J. (2002). Corporate universities – an analytical framework. Journal of Management Development, 21(10), 794–811. doi:10.1108/02621710210448057 Prud’hommeaux, E., & Seaborne, A. (2004). SPARQL Query Language for RDF. World Wide Web Consortium. Ruiz Antón, F. (in press). (2004). La Gaceta de los negocios. Salton, G., Wong, A., & Yang, C. S. (1975). A Vector Space Model for Automatic Indexing. Communications of the ACM, 18(11), 613–620. doi:10.1145/361219.361220 Sham, C. (2007). An exploratory study of corporate universities in China. Journal of Workplace Learning, 19(4), 257–264. doi:10.1108/13665620710747933
Sicilia, M. A. (2005). Ontology-based competency management: Infrastructures for the knowledgeintensive learning organization. In M. D. Lytras and A.Naeve (Eds.), Intelligent learning infrastructures in knowledge intensive organizations: A Semantic Web perspective (pp. 302-324). Hershey, PA: Idea Group. Solomon, C. M. (1989). How does Disney do it? The Personnel Journal, 68(12), 50–57. Yee, K. P., Swearingen, K., Li, K., & Hearst, M. (2003). Faceted metadata for image search and browsing. In Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI ’03), Fort Lauderdale, FL, USA, April 5 – 10. New York. ACM Press. Zamorano, P. (in press). (2003). Empleo y tecnología, dos términos antagónicos. Diario Expansión.
This work was previously published in Semantic Web for Business: Cases and Applications, edited by Roberto Garcia, pp. 321-335, copyright 2009 by Information Science Reference (an imprint of IGI Global).
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Chapter 2.11
Model on KnowledgeGovernance: Collaboration Focus and Communities of Practice Eduardo Bueno Campos University of Madrid, Spain Carlos Merino Moreno University of Madrid, Spain Reinaldo Plaz Landaeta University of Madrid, Spain
ABSTRACT The aim of this chapter is to deepen the concept of ‘Communities of Practice’ (CoPs) from the understanding of a reference framework for knowledge governance, stressing the grey area which distinguishes such governance from the traditional term ‘Knowledge Management,’ since knowledge governance means not just the management of such assets but also their creation and development, which generates a richer and more appropriate meaning or sense. Without DOI: 10.4018/978-1-60960-587-2.ch211
entering into exhaustive referential analyses, we attempt to offer the reader a practical approach which allows structuring an action plan that, in this case, will be explicated for the field of CoPs. Identification and measurement of assets based on information and knowledge and the processes carried out towards its improvement create the convergence of the dynamic of intellectual capital and the afore-mentioned knowledge governance as complementary subjects for an appropriate exploitation and monitoring of the impact which the organizational fostering of this strategic-reality has on business.
Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
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VALUATION OF ORGANIZATIONAL INTANGIBLE ASSETS The strategic approach of businesses in the current economy has an important part related with certain support processes linked to analysis tasks corresponding to dynamic processes of decision making, as an attempt to diminish the risks inherent to such processes. In this sense, such argument on intelligent or learning-capable organizations (Senge, 1990) gains a high value for the extraction of information and the creation of both appropriate internal and external knowledge. This approach insists on the importance of basic resources for strategic management focused on the couple information-knowledge (Itami, 1987; Vassiliadis et al., 2000) and on derived individual and organizational learning. In this case, corporative philosophy should create the necessary atmosphere to recognize the value of intangible assets, very close to the understanding of the theory of resources and abilities, which does not only take into account those resources related with the tangible field but also those linked to non-physical elements located in the organizational ‘roots’ (1). Obviously, it arises a requirement around a model or scheme of analysis; firstly, for the identification and measurement of such typology of assets, and also to facilitate a structured framework of reflection and analysis, an area covered by the intellectual-capital approach (Itami & Roehl, 1991; Grant, 1991; Bontis, 1999; Bueno & Salmador, 2000; Ordoñez, 2000). This thematic area of intangible assets —which we could qualify as emerging if study cases are observed, although it is has been historically tackled in organizational literature within the field of the theory of resources and abilities (Wernerfelt, 1984; Barney, 1991; Grant, 1991; Peteraf, 1993)— had already collected, in different ways, contributions which helped to the valuation of non-tangible assets.
The basic models of intellectual capital (2) are generally structured by three basic components (IADE-CIC, 2003). Firstly, human capital —where attitudes, competency and abilities are analysed developing a profile to identify and measure knowledge from an individual viewpoint. On the other hand, structural capital (3) —responsible for knowledge diagnosis of organizational nature (Nonaka & Takeuchi, 1995; Brown & Duguid, 1991 and 1998; Teece, 1998 and 2000; Nonaka et2000 al., 2000; Tsoukas & Vladimirou, 2001) — considers aspects such as organizational design, reported culture and processes, and also a technology reality related with efforts in I+D such as tools and results which facilitate and make knowledge tangible (Brooking, 1996). Finally, relational capital —which is explained by knowledge and information flows derived from the framework of alliances directly related with business processes (customers, suppliers, etc.) or involved with the social environment (4) (Nahapiet & Ghosal, 1996). However, measurement only lacks of sense without a sustainable exertion allowing the analysis of different initiatives developed to improve the stock of intellectual capital. Such initiatives are processes related with the idea of ‘knowledge in action’ (Davenport & Prusak, 1998), creating a requirement of a holistic model integrating different alternatives and options, and also avoiding the common error linked to the consideration of strategic plans for knowledge governance or management just as a mere accumulations of initiatives. This accumulative approach creates difficulty and complexity in understanding certain dimensions and interactions among assets, generates chaos and includes contradictions among different programmes. The result of such intellectual capital is centred on a ‘photograph’ (Bontis, 1999) as a traditional balance showing the status of the basic intangible assets identified by the organization; however, this approach may present a double objective —that is, the improvement of internal management and
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external communication through the information for stakeholders about a more complete organizational reality (5). The general argument of ‘knowledge in action’ is traditionally linked to ‘knowledge governance or management’, processes which develop intellectual capital looking for improving the results of the initial measurement scheme. In this sense, there is a basic difference between intellectual capital and knowledge governance, bearing in mind a static or dynamic perspective, respectively. However, the need for a complete exercise of management beyond the traditional financialaccountant approach creates an emerging line for the development of new areas within the structure of organizational responsibilities with a specific demand of abilities.
COLLABORATION APPROACH WITHIN KNOWLEDGE GOVERNANCE Organizations consider in their strategies those factors to which they recognize significant value contributions (Barney, 1991; Grant, 1991; Peteraf, 1993), certainly measurable or at least as presumptions. This initial argument means the possibility of different strategic approaches according to business orientation or awareness showed by the organization towards the relevance of the different types of assets it owns. In Figure 1 it is observed a distinct evolution and evidence towards the consideration of knowledge as a key asset (6), as an organizational value —that is, as a resource to which a significant contribution is recognized openly. Without deepening into the theoretical framework associated to the concept of knowledge, this resource owns a characteristic linked to its intangibility which is that of enriching through the exchange among the large agents owning it (Nonaka, 1994; Nonaka & Takeuchi, 1995; Grant, 1996; Kogut & Zander, 1992 and 1996; Spender,
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1996; Tsoukas, 1996), which implies the consideration of certain transference and exchange schemes as means supporting its advance and development. Individual knowledge is transformed and is the base of the collective since it is transmitted through oral, written, encoded, sign, etc. language. For Spender (1996), Von Krogh & Ross (1995) and Cook & Brown (1999), among others, social knowledge is not merely the sum of individual knowledge, but something else, different from that, which is especially important for organization survival and development in the long run. This transference pattern means that individual knowledge is enriched in the process of exchange and transmission adding a contextual dimension to it, which gives it organizational value. In this sense, individual knowledge is idiosyncratic by nature and owns strong links to the organizational context in which it is developed. Knowledge transference, from this perspective, is necessarily social and conclusively outdistances from the schemes of electronic transference of data and information. Social knowledge is built up from networks of agents creating a system of relations which facilitates, fosters and allows that individual knowledge is transferred and, at the same time, enriched, giving rise to social or organizational knowledge. It is precisely in this point where we can identify the difference between Knowledge Management and governance. In the first, management occurs Figure 1. Evolution of the economic paradigms (Source: Gorey & Dobat (1996) and Bueno & Salvador (2000))
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around an explicit and encoded object or entity which we call, usually in a wrong manner, knowledge, when in fact it is data or information. In the latter, we rather talk about a system of relations among agents governed by a series of guidelines, norms and rules regulating, leading and guiding knowledge flows or processes. In this system, the centre of attention is the subject of knowledge, which involves a more organic viewpoint of the concept —contemplating in a clear manner its different dimensions: explicit and tacit— and its relation with the context in which it is created and developed. From a viewpoint of governance, thinking of guiding knowledge processes transcends the very meaning of the expression. Many authors insist that knowledge, in an abstract sense, cannot be managed (Drucker, 2001). Knowledge, as we have already mentioned, lies in people and responds to mental models of behaviour intrinsic to the very nature of individuals. At most, we can induce certain behaviours in subjects. It is possible to give them tools and competences to exercise and develop their mental and cognitive abilities with the aim of increasing their knowledge stock and use. From this viewpoint, and in the field of cognitive processes, each individual will build patterns of social behaviour linked to processes of understanding, assimilation, learning and application of new knowledge (Bueno, 2005). In the sense of the contributions by Foss (2006), this knowledge governance is close to a double level —micro (individual) and macro (collective), where it is important to consider not just tools, but also those attitudes and motivations which come into play in this reality of behaviours. These processes are endogenous by nature and, therefore, they do not admit norms, rules and external intervention. A pedagogical method for learning, for instance, is nothing more than an instrument or tool to facilitate learning. However, its effectiveness will depend, deep down, on the individual’s ability, interest and motivation for learning. We can induce or favour behaviours and
stimulate processes; however, the governance of what-is-known is a subject concerning the individual him/herself and depends on his/her context (Cook & Brown, 1999). Organizations are increasingly giving more importance to the administration of their intangible assets and to the forms in which such assets contribute to generate business value (Bueno, 2003). In this sense, the processes of professional learning and development are oriented at the improvement of competences for innovation, allowing their articulation in organizational models and systems which in turn become differentiating elements to achieve competitive positioning in markets. This knowledge approach adopts an open and systemic viewpoint of the organizational processes —in which interactions, relations and collaboration processes act as channels for newknowledge transmission and assimilation (Plaz & Gonzalez, 2005). From this viewpoint, an ontological approach of knowledge centred on the governance of processes of social relations emerges. It is in this context that the transference of knowledge flows takes place, causing expressions of knowledge organization, codification and specification in the form of organizational records. It is this way how relations and relational capital, for instance, constitute key sources of organization enrichment and a means to keep the dynamic of knowledge renovation (Bueno, 2005). This approach has recently distinguished between individual knowledge and the creation (development), management or governance of organizational knowledge (Nonaka, 1994 and 1995; Bueno & Plaz, 2005). Such distinction is important since it focuses the discussion on Knowledge Management at the level of organizational system and its management. Knowledge management or administration places the debate in the field of governance of the exchange flows and key organizational processes which increase the value of intangible assets. In this sense, talking about organization
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implies referring to the system of relations and connexions allowing the interaction of agents and individuals, and that knowledge flows —as a part of such process— are produced in the same directions of such interaction. It is important to stand out that Knowledge Management —considered from this viewpoint and with a sense of governance— means the definition of policies, guidelines, channels, proceedings and resources to create optimum conditions for fostering, channelling, catalysing and promoting such flows of organizational knowledge.
PROPOSAL OF FRAMEWORK MODEL FOR KNOWLEDGE GOVERNANCE Talking about organizational-knowledge governance and development therefore means creating support structures for the processes of interaction individual-individual, individual-organizational system, and organizational system-organizational system. These structures facilitate knowledge flows and allow at the same time leaving a trace or record. This record is the result of specifying tacit knowledge to convert it into explicit codes leading to the definition of routines of organizational behaviour and progressively acquiring an own identity. Organizational culture is nothing but the historic trace of individual behaviours grounded on a collective expression. Stating that an organization owns a determined working culture makes us date back to and look for —in its founders and previous leaders— those behaviours which have been progressively modelled and have become in reference and standard. These processes are initiated through relations and interactions among knowledge agents or subjects from a determined viewpoint or strategic thought, given a context of reference which incardinates the process of knowledge. Information technologies are only the catalyser
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to facilitate collaboration among subjects and propose knowledge exchange as a common resource, which —once it is developed by action of practice— will be transformed from explicit into tacit, and from individual into social. Without this conviction, at least in its top-down version (7), it is very complex to face —moving away from the approach of simple fashion— a scheme aimed at a more appropriate way to tackle knowledge, or more precisely, the socalled knowledge governance (Plaz & Gonzalez, 2005), than just management, given that this term should gather those tasks related to creation and development. Going back to the argument on knowledge governance, such governance is obviously configured from a structure of processes acting as drivers of the business in question, assuring the exploitation of all organizational knowledge —an aspect which doubtlessly should be imbricated with a system of organizational intelligence (8) acting as a supplier of informative inputs for the recycling and updating of the organization’s knowledge base (Vassiliadis et al., 2000; Merino, 2004). The dynamics of creation of value occur around the tasks of internal transference of tacit and explicit knowledge, as well as around those tasks of incorporation of external knowledge or that created by other agents, generating learning cycles which build up the new knowledge within a process of transformation of essential competences which generate intangible or intellectual-capital assets (see Figure 2), as Bueno (2002) proposes in the new conception of the company as an economic system based on knowledge. Accompanying this overall framework and prior to tackling the projection of the model of knowledge governance on the role of transference and collaborative approaches, it should be stood out the need to aligning such structure with a series of business objectives which allow clarifying, visualizing and understanding the returns or impacts involved in knowledge valuation and acting in consequence. Those returns, beyond a
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Figure 2. Company as a system based on knowledge (Source: Bueno, 2002)
short-term period, will adjust to the context of the organization, looking for action lines adapted to its level of organizational and technological maturity, considering a set of possible key factors for success (Plaz & Gonzalez, 2005). At the same time, the achievement of results will require an appropriate scheme of measures which allow an appropriate evaluation not just of those variables of a finalist nature for business, but also of the statistics associated with the afore-mentioned chain of knowledge creation, development and management. For both analysis and fixation of objectives and the reality of these processes linked to knowledge governance, we may use the dynamic of a balanced scorecard (Kaplan & Norton, 1992) and even for more specific themes, like the support for the control panel, several instruments such as the model of the European Foundation for Quality Management (EFQM) or the models of intellectual capital (10) can be used.
Undoubtedly, the action on knowledge governance should pursue the improvement of the organization’s intellectual capital as a way to get to know the suitability of the actions aimed at putting into practice a strategy in the line of knowledge valuation (see Figure 3). The approach of processes which shapes the model of knowledge governance makes clear an action loop (Bueno & Plaz, 2005; Nonaka, 1991 and 1994; Kogut &1994 Zander, 1992; Blumentritt & Johnston, 1999; Shin et al., 2001; Alavi & Leidner, 2001; Staples et al., 2001; Zahra & George, 2002; Argote et al., 2003; Zack, 2003) around the dynamics of understanding, register, storage (Walsh & Ungson, 1991; Davenport & Prusak, 1998; Teece, 2000; Staples et al., 2001; McGrath & Argote, 2002), diffusion (Davenport & Prusak, 1998; Szulanski, 2000), use and improvement of information and knowledge, where the organization should consider the way of putting it into practice or value, already counting on
Figure 3. Improvement of intellectual capital (Source: Personal compilation)
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a traditional approach based on certain support departments —namely, documentation centres, system departments, training units, quality areas, etc.— whose mission is clearly positioned in relation to the afore-mentioned loop. In any case, it would be convenient to integrate the set of dynamics specified in a modelled framework which allows visualizing, in a complete manner, the reach of knowledge governance in order to be able to face its display properly. In this case, literature revision (Gupta & Govindarajan, 2000; Alavi & Leidner, 2001; Shin et al., 2001; Staples et al., 2001; Zack, 2003; Argote et al., 2003; among others) describes a wide range of references which partially raise the different viewpoints of the afore-mentioned knowledge governance, losing a reference of holistic sense. The configuration of this model joins the dynamic of the afore-mentioned loop and the stages which achieve its alignment with the key strategy and factors of the business, apart from the corresponding evaluation of impacts (see Figure 4). All this is included within a scheme characterized by complexity, given that the ‘act or fact of knowing’ is complex in itself, as well as the different knowledge processes (flows), given their diversity and functionality, which justify under-
standing governance as an action aimed at guiding such complexity. This decrease in the terms alluding knowledge government allows translating its conceptual framework into a series of action lines recognized by all organizations and that, therefore, own a history, a record, programmes and tools which in many cases merely lack of integration; that is, a model for knowledge governance is not about accumulating programmes. These action lines are centred on the afore-mentioned organizational intelligence, expert management, communication, quality, learning-training, I+D and documental management, and on the strategies/mechanisms briefly described next: •
•
Organizational intelligence is an action line which pursues the configuration of an alert system for the organization (Escorsa & Maspons, 2001; Kurtyka, 2003; Almeida et al., 2003). The activities linked to technological vigilance, competitive intelligence, benchmarking, etc., are practices recognized within this kind of action. Expert management is a mechanism mainly based on collaborative approaches, networks, communities of practice, etc., where knowledge exchange, especially
Figure 4. Knowledge-governance model (Source: Bueno & Plaz (2005) and personal compilation)
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•
•
•
•
•
that of tacit knowledge, becomes a key objective. Communication, strategy based on the information about the organization’s abilities, resources, results, etc., where communication models, existing channels, etc., play essential roles (Davenport & Prusak, 1998; Szulanski, 2000). Content management is centred on the systems allowing appropriate tackling and accessibility to documents through data bases. Individual learning —bearing in mind the dynamics of training, offer and demand, attendance and on-line, which generate cycles (Nonaka & Takeuchi, 1995) of knowledge recycling where performance of the learnt concepts is an important objective. Organizational learning is an action line based on the development of exchange and collaboration areas where the concept of communities in practice may favour knowledge register in organizational memory and the improvement of its degree of advance when shaping thematic groups of interest (Easterby-Smith & Lyles, 2003), and Innovation and improvement is centred on the organization’s efforts on I+D and the obtained results (Zack, 1999). Thus, those dynamics favouring creativity, incentives and recognition are an important part of this strategy.
Once the breadth of knowledge governance is observed, we can clearly state that the central positioning of collaboration dynamics in this matter goes further than the documental approaches which have characterized the first stages of the strategies of those companies concerned with Knowledge Management, in which great efforts for digitalization have also been raised. As a result, we have come to the subsequent replacement of knowledge stock by knowledge flow.
Once we have reached this point, and from the double dimension (see Figure 5) which intersects between the loop and the action lines, it is important to emphasize the enriching effect on coordination and individual and organizational learning derived from a collaborative working approach. Therefore, transference and exchange dynamics appear as recipes of high strategic interest from the couple collaboration-communication, where we can reflect, design and explore areas, channels and subject matters. From the field of collaboration, the main axes of action are centred, on one hand, on the creation of appropriate areas —attendance or virtual— which facilitate sharing ideas and documents, and, on the other hand, on establishing a culture prone to share, in which leadership, awareness and recognition exertion become key elements for its operation. Therefore, the phenomenon of transference as a communication process influenced by a set of causal contingencies or variables of contextual nature —so that we have to take into account the attitudes, competency and abilities of the emitter and receiver agents, and the existence, on one hand, of a wide range of messages (information and knowledge) with a comprehensive and available approach of added value and, on the other hand, of the appropriate channels for their transmission according to the nature of such messages with the aim of eliminating or avoiding, as much as possible, mechanic, semantic and contextual noises and interferences. Regarding the latter, message is linked to the information and the knowledge we attempt to transfer, both if it is of documental or tacit nature, all set in a specific cultural context. Thus, from the beginning, in spite of counting on a significant value offer, it may occur that the set of resources and abilities of the emitter or receiver may benefit or limit the process. This way, it should be emphasized that it would be more interesting to count on a motivated and capable emitter with a first-level offer, since —to a large
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Figure 5. Field of action for knowledge governance (Source: personal compilation)
extent— a relevant number of requirements are not found in the vanguard of knowledge. To sum up, we attempt to reach understanding between both extremes of the transference process, for which the channel or means should be adjusted to the nature of knowledge —whether it is explicit or tacit, intellectual or collective, since each of them will raise specific and different requirements. Active and passive communication may also be taken into account, bearing in mind those mechanisms which allow the message to reach its addressee (systems of selective information diffusion) or, on the contrary, others needing willingness from the addressee in order to achieve the objective of communication (e.g., notice-boards), according to the dimensions characterizing knowledge (epistemological, ontological, systemic and strategic), which leads to the design of different operative programmes of management of knowledge processes, according to the LICI index (Level of Information, Complexity and Imagination) of the transferred knowledge (Bueno, 2002). Among all options occurring nowadays on the subject of collaboration, it is to stand out communities of practice as a concept of high strategic interest, given its linkage to an area of specific knowledge and interest for organization which
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includes collaboration within a process from which a result is expected.
THE CONCEPT OF COMMUNITIES OF PRACTICE (COP) The purpose of existence of the communities of practice (Wenger, 2001; Wenger & Sneyder, 2000) is oriented towards the creation of a common area for individual meeting in order to interact in benefit of the generation, exchange and assimilation of experiences around specific application areas with clearly defined objectives. This common area should use, on one hand, the cycle of knowledge reception, diffusion, assimilation and renovation in the organizational data base, structuring the experiences and facilitating its members’ searches and contributions. This way, we can apply to CoP, as an agent, the whole model of knowledge governance from the viewpoint of both the loop and the seven defined strategies (see Figure 6). On the other hand, it should also facilitate the relation among community members beyond mere information exchange, which is the only way to make non-specified knowledge appear in reports
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Figure 6. Knowledge processes (Source: Personal compilation)
of formal nature. This exchange dynamic is only possible if mission and objective internalization occurs within the context of the community, since that internalization would facilitate the flow of the interaction cycle which will favour cohesion among its members. A consolidated community of practice represents the natural place we turn to when we need to seek for advice or raise requests linked to its field. The development of practice and attention to requests raised to the community facilitates the replication of experiences in order to dynamize and accelerate the velocity of the organizational learning cycle. Community of Practice is grounded on three basic pillars which provide it with a management framework and the necessary support tools for its operation: •
•
Technology provides with the necessary tools and means to create effective collaboration areas from an operational viewpoint. The organizational environment and the necessary culture to meet the objectives and necessities of the community, the organization and its individuals, in order to achieve an identity and generate policies and appropriate management plans grounded on a solid base of training, awareness (communication) and motivation (incentives and recognitions), and
•
The management model through which the rules of the game are established, the definition of flows and work processes, identification of actors (roles), knowledge types and their associated taxonomy.
In this sense, Figure 7 shows the relations of these three components with the community, as well as its linkage with the expected impact at the level of individuals, organization, business and the community itself, fields which lead to visualize the different returns which may be derived of an approach of CoPs. Therefore, monitoring of practice in the community is carried out through indicators linked to four dimensions —namely, people, group, organization and business— which allow measuring the impact of the results, the generated and seized know-how and, through that, establishing strategies of impulse/monitoring which contribute to the creation of improvements and the alignment of objectives and actions.
THE PROCESS OF CREATION AND DEVELOPMENT OF A COP The creation of a CoP may be mainly linked to two approaches:
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Figure 7. Overall approach of CoP (Source: Personal compilation)
1. A push one, declared by the organization, in which practices structuring the community are decided and chosen by headship, involving a previous exercise of strategic reflection, and 2. A pull one, whose approach is based on providing resources and support to those groups developing a certain successful collaboration labour within the organization. Obviously, success expectancy of both options may turn out to be very unequal, especially if we bear in mind the predisposition to collaboration showed by both alternatives. In any case, the process goes through a series of stages (see Figure 8): •
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Stage 1: Identification: It is linked to the strategic priorities of the organization, which may be originated from the previously-mentioned push and pull viewpoints.
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Stage 2: Design: The generation of a model which adjusts to collaboration necessities; that is, identifying the processes developed in its area and their fundamental requirements. Stage 3: Construction: Articulation of the preliminary organizational structure of the community, with its defined and necessary objectives, roles, responsibilities, and resources. In this case, the institutionalization of the CoP may be achieved through the formal recognition of its existence and certain responsibilities within the practice in question. Stage 4: Implementation: Turning on of a functional model through the generation of an area or platform supporting collaboration, an aspect in which non-area criteria prevail nowadays. Stage 5: Growth: Development of an extensive approach of the communities in-
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Figure 8. Process of creation of a CoP (Source: Personal compilation)
•
volving a higher number of people and, therefore, exceeding the idea of the organization’s preliminary structure. In this sense, preliminary stages can entitle the role of ‘observer’ as an agent which shows interest in becoming a part of the CoP in the future. This expansion clearly impacts in the ambiguity of the organizations’ limits, and Stage 6: Improvements: Establishment of a self-diagnosis policy, consolidating the benefits which it contributes to the community, especially through the generation of an organized set of indicators.
FINAL REFLECTION Through the approach of Communities of Practice we make clear important benefits which enable the identification of opportunities for growth and development of an organizational culture centred on the seizing of talent and continuous improvement. Among the most obvious general benefits of this approach we can emphasize the following:
1. Boast a structured and common data base containing relevant information for the different projects and activities carried out in the organization in the context of the influence areas of the CoPs. 2. Count on technological resources which allow creating new virtual areas of collaborative work for the generation and construction of documents in an asynchronic and ubiquitous manner, facilitating the exchange of documents and opinions among group members without depending on attendance meetings. 3. This interaction will work to generate —in real time— a record of all documents generated by the group, which may be consulted. 4. Facilitate and accelerate the processes of generation of records and work around the conclusions and commitments established in a meeting, and 5. Boast instruments and platforms which facilitate assessment processes of suppliers and the creation of a common data base on suppliers, an interface which optimize the actions of diffusion and access to informa-
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tion on suppliers, and registers (records) of the result of relevant indicators for CoPs in order to facilitate the activities related to benchmarking. Therefore, given the concept of CoP, the pillars on which its turning-on is grounded, and the general process which may act as a roadmap, we have come to meet a specific reality as a tool which —from a collaborative viewpoint— insists on the approach of the knowledge-governance model, making a proper use of transference and exchange dynamics, which is the aim of this chapter.
REFERENCES Alavi, M., & Leidner, D. E. (2001). Review: Knowledge Management and Knowledge Management Systems: Conceptual Foundations and Research Issues. MIS Quarterly, 25, 107–136. doi:10.2307/3250961 Almeida, P., Phene, A., & Grant, R. (2003). Innovation and Knowledge Management: Scanning Sourcing and Integration. In M. Easterby-Smith & M.A. Lyles (eds.), Handbook of Organizational Learning and Knowledge Management (pp. 356371). Oxford, UK: Blackwell Publishing. Argote, L., McEvily, B., & Reagans, R. (2003). Managing Knowledge in Organizations: An Integrative Framework and Review of Emerging Themes. Management Science, 49, 571–582. doi:10.1287/mnsc.49.4.571.14424 Barney, J. B. (1991). Firm Resources and Sustained Competitive Advantage: A Comment. Journal of Management, 17(1), 99–120. doi:10.1177/014920639101700108 Blumentritt, R., & Johnston, R. (1999). Towards a Strategy for Knowledge Management. Technology Analysis and Strategic Management, 11, 287–300. doi:10.1080/095373299107366
430
Bontis, N. (1999). Managing Organizational Knowledge by Diagnosing Intellectual Capital: Framing and Advancing the State of the Field. International Journal of Technology Management, 18, 433–462. doi:10.1504/IJTM.1999.002780 Brown, J. S., & Duguid, P. (1991). Organizational Learning and Communities of Practice: Towards a Unified view of Working, Learning and Innovation. Organization Science, 2, 40–57. doi:10.1287/ orsc.2.1.40 Brown, J. S., & Duguid, P. (1998). Organizing Knowledge. California Management Review, 40, 90–111. Bueno, E. (2002). Dirección estratégica basada en conocimiento: Teoría y práctica de la nueva perspectiva. In P. Morcillo & J. Fernández Aguado (eds.), Nuevas claves en la Dirección Estratégica (pp. 91-166), Madrid: Ariel. Bueno, E. (2003). Enfoques principales y tendencias en dirección del conocimiento (Knowledge Management). In R. Hernández (ed.), Dirección del conocimiento: Desarrollos teóricos y aplicaciones (pp. 21-54). Trujillo, Spain: Ediciones La Coria. Bueno, E. (2005). Fundamentos epistemológicos de dirección del conocimiento organizativo: Desarrollo, medición y gestión de intangibles. Economía Industrial [Spanish Ministry for Industry, Tourism y Trade], 357, 13-26. Bueno, E., & Plaz, R. (2005). Desarrollo y Gobierno del Conocimiento Organizativo: Agentes y procesos. Boletín Intellectus, 8, 16–23. Bueno, E., & Salmador, M. P. (Eds.). (2000). Perspectivas sobre Dirección del Conocimiento y Capital Intelectual. Madrid: Instituto Universitario Euroforum Escorial.
Model on Knowledge-Governance
Cook, S. D. N., & Brown, J. S. (1999). Bridging Epistemologies: The Generative Dance between Organizational Knowledge and Organizational Knowing. Organization Science, 10(4), 381–400. doi:10.1287/orsc.10.4.381 Davenport, T. H., & Prusak, L. (1998). Working Knowledge. How Organizations What They Know. Harvard, US: Harvard Business School Press. Drucker, P. (2001): The Next Society. The Economist, November 3rd, 3-22. Easterby-Smith, M., & Lyles, M. A. (Eds.). (2003). The Blackwell Handbook of Organizational Learning and Knowledge Management. Oxford: Blackwell. Escorsa, P., & Maspons, R. (2001). De la Vigilancia Tecnológica a la Inteligencia Competitiva. Financial Times. Madrid: Prentice Hall. Foss, N. (2006): The Emerging Knowledge Governance Approach: Challenges and Characteristics, DRUID Working Paper, no. 06-10. Gorey, R. M., & Dovat, D. R. (1996). Managing on the Knowledge Era. New York: Harper and Row. Grant, R. M. (1991). A Resource Based Theory of Competitive Advantage: Implications for Strategy Formulation. California Management Review, 33(3), 114–135. Grant, R. M. (1996). Toward a Knowledgebased Theory of Firm. Strategic Management Journal, 17, 109–122. doi:10.1002/ (SICI)1097-0266(199602)17:23.0.CO;2-P Gupta, A.K. & Govindarajan, V. (2000). Knowledge Management’s Social Dimension: Lessons from Nucor Steel. Sloan Management Review, fall issue, 71-80. IADE-CIC. (2003). Modelo de medición y gestión del capital intelectual: Modelo Intellectus. Madrid: Universidad Autónoma de Madrid: CIC-IADE.
Itami, H. (1987). Mobilizing Invisible Assets. Boston, Harvard University Press. Itami, H. & Roehl (1987). Mobilizing Invisible Assets. Cambridge, MA: Harvard University Press. Kaplan, R. S., & Norton, D. P. (1992). The Balanced Scorecard Measures that Drive Performance. Harvard Business Review, 70(1), 71–79. Kogut, B., & Zander, U. (1992). Knowledge of the Firm, Combinative Capabilities and the Replication of Technology. Organization Science, 3, 383–397. doi:10.1287/orsc.3.3.383 McGrath, J. E., & Argote, L. (2002). Group Processes in Organizational Contexts. In M.A. How & R.S. Tindale (eds.). Blackwell Handbook of Social Psychology. Oxford, UK: Blackwell. Merino, C. (2004). La Inteligencia Organizativa como Dinamizador del Capital Intelectual. Revista Puzzle, 3(14), 4–10. Nahapiet, J., & Ghoshal, S. (1998). Social Capital, Intellectual Capital, and the Organizational Advantage. Academy of Management Review, 23, 242–266. doi:10.2307/259373 Nonaka, I. (1991). The Knowledge-creating Company. Harvard Business Review, 69, 96–104. Nonaka, I. (1994). A Dynamic Theory of Organizational Knowledge Creation. Organization Science, 5(1), 14–37. doi:10.1287/orsc.5.1.14 Nonaka, I., & Takeuchi, H. (1995). The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation. New York: Oxford University Press. Nonaka, I., Toyama, R., & Cono, N. (2000). SECI, Ba and Leadership: A Unified Model of Dynamic Knowledge Creation. Long Range Planning, 33, 5–34. doi:10.1016/S0024-6301(99)00115-6
431
Model on Knowledge-Governance
Ordoñez, P. (2001). Relevant Experiences on Measuring and Reporting Intellectual Capital in European Pioneering Firms. In N. Bontis & C. Cheng (eds.) World Congress on Intellectual Capital Reading. New York: Butterworth-Heinemann. Peteraf, M. A. (1993). The Cornerstone of Competitive Advantage: A Resource-Based View. Strategic Management Journal, 14, 179–191. doi:10.1002/smj.4250140303 Plaz, R., & González, N. (2005). La gestión del conocimiento organizativo: dinámicas de agregación de valor en la organización. Economía Industrial, 357, 41–62. Senge, P. (1990). The Fifth Discipline: The Art and Practice of the Learning Organization. New York, Doubleday Currency. Shin, M., Holden, T., & Schmidt, R. A. (2001). From Knowledge Theory to Management Practice: Towards an Integrated Approach. Information Processing & Management, 37, 335–355. doi:10.1016/S0306-4573(00)00031-5 Spender, J. C. (1996). Making Knowledge the Basis of a Dynamic Theory of the Firm. Strategic Management Journal, 17, 45–62. Staples, D. S., Greenaway, K., & Mckeen, J. (2001). Opportunities for Research about Managing the Knowledge-based Enterprise. International Journal of Management Reviews, 3, 1–20. doi:10.1111/1468-2370.00051 Szulanski, G. (2000). The Process of Knowledge Transfer: A Diachronic Analysis of Stickiness. Organizational Behavior and Human Decision Processes, 82, 9–27. doi:10.1006/obhd.2000.2884 Teece, D. J. (1998). Research Directions for Knowledge Management. California Management Review, 40, 289–292.
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Teece, D. J. (2000). Strategies for Managing Knowledge Assets: The Role of Firm Structure and Industrial Context. Long Range Planning, 33, 509–533. doi:10.1016/S0024-6301(99)00117-X Tsoukas, H. (1996). The Firm as a Distributed Knowledge System: A Constructionist Approach. Strategic Management Journal, 17, 11–25. Tsoukas, H., & Vladimirou, E. (2001). What Is Organizational Knowledge? Journal of Management Studies, 38, 973–993. doi:10.1111/14676486.00268 Vassiliadis, S., Seufert, A., Back, A., & Von Krogh, G. (2000). Competing with Intellectual Capital: Theoretical Background. Institute for Information Management and Institute of Management, University of St. Gallen. Von Krogh, G., & Ross, J. (1995). Organizational Epistemology. New York: MacMillan and St Martin’s Press. Walsh, J. P., & Ungson, G. R. (1991). Organizational Memory. Academy of Management Review, 16, 57–91. doi:10.2307/258607 Wenger, E. (2001). Comunidades de práctica aprendizaje, significado e identidad. Barcelona: Paidós. Wenger, E. C., & Sneyder, W. (2000). Communities of Practice: The Organizational Frontier. Harvard Business Review, 78(1), 139–145. Wernerfelt, B. (1984). A Resource-Based View of the Firm. Strategic Management Journal, 5, 171–180. doi:10.1002/smj.4250050207 Zack, M. (1999). Developing a Knowledge Strategy. California Management Review, 41, 125–145. Zack, M. (2003). Rethinking the KnowledgeBased Organization. MIT Sloan Management Review, summer issue, 67-71.
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ENDNOTES 1
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It is important to consider not just the aspect of resource and ability property but also their availability —that is, the existence of an external offer of added value, frequently within the area or environment in which the organization is located. In the line of the model EFQM, intellectualcapital models propose a set of factors for reflection on organizational intangible assets. Due to management criteria, structural capital is composed by organizational capital and technological capital, where the first establishes a set of structural and non-technological factors and the second establishes all those elements linked to the use of technology and the results of innovation (intellectual and industrial property). In the case of public organizations, social capital is related with the task of public service. This consideration may transfer social capital to structural capital, since it is shaped as a nucleus which legitimizes the organization’s labour.
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In this case, the interest towards intellectual capital is oriented at better information for investors and other stakeholders who may be found within certain levels of technical or economic relations with the organization. Knowledge should be emphasized as a strategic key of the current economy, embodied in a person, transferred to the organization or social group according to real or moral contracts, and valued as a productive resource and dynamic competence. Where it is necessary to raise an appropriate management style articulated on the base of a leadership, awareness, etc. exercise which permeates the organization’s culture. Systems turning around the concept of corporate radar, as an antenna which feeds the organization on information and basic knowledge. Instrument which favours organizational diagnosis according to a series of key criteria looking for certain fields of improvement and strengthens, and Tool for reflection and report on the organization’s intangible assets, in its side of identification and measurement.
This work was previously published in Connectivity and Knowledge Management in Virtual Organizations: Networking and Developing Interactive Communications, edited by Cesar Camison, Daniel Palacios, Fernando Garrigos and Carlos Devece, pp. 89-105, copyright 2009 by Information Science Reference (an imprint of IGI Global).
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Chapter 2.12
Knowledge Integration through Inter-Organizational Virtual Organizations Montserrat Boronat Navarro Universitat Jaume I, Spain Ana Villar López Universitat Jaume I, Spain
ABSTRACT In this study we adopt an inter-organizational view to examine virtual organizations. Thus, we understand this phenomenon as a strategic agreement between organizations that collaborate and coordinate their work through information technologies. This dimension adds greater flexibility to the strategic alliance, which in turn is beneficial for the integration of knowledge. In high technology industries, inter-organizational virtual organizations add further advantages to this option of knowledge integration through DOI: 10.4018/978-1-60960-587-2.ch212
strategic alliances because of the importance of speed and flexibility. We put forward a series of propositions, following an initial approximation to this phenomenon through the combination of the strategic alliances, virtual organizations and the knowledge-based view literatures.
INTRODUCTION Progress in information and communication technologies has led to the development and increasing importance of virtual organizations. There are various definitions of this term. Greis and Kasarda (1997) recognize a common factor
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in all definitions: that a virtual organization is a related group of companies formed to enable collaboration toward mutually agreed on goals. One of the main features of virtual organizations is that people are linked not by face-to-face relationships but by sharing information through electronic networks (Weber, 2002); hence virtual organizations are associated with an intense use of computer networks and information technologies to support cooperation. Moreover, adaptability, flexibility and the ability to react quickly to changes in the market are properties that are usually assigned to virtual organizations (Grabowski and Roberts, 1999). We adopt an inter-organizational view to examine virtual organizations. Thus, we understand this phenomenon as a strategic agreement between organizations that collaborate and coordinate their work through information technologies. This last dimension lends greater flexibility to the strategic alliance, which in turn is beneficial for the integration of knowledge. According to the knowledge-based view (Nonaka, 1994; Nonaka and Takeuchi, 1995; Grant, 1996; Spender, 1996), knowledge integration is one of the main capabilities that organizations must possess in today’s markets. In some industries, such as biotechnology, that need to integrate different bases of specialized expertise, the sources of knowledge are distributed across a great variety of organizations. Strategic alliances are an option that may solve problems of speed or cost in these cases. Hence, in this chapter we draw on the knowledge-based view and strategic alliances literatures to identify advantages that inter-organizational virtual organizations may have in the creation of knowledge. The study begins with an overview of virtual organizations and their properties. We then review the idea of strategic alliances and networks as a way of integrating knowledge, explaining their advantages and placing special emphasis on the case of strategic alliances in which the main
aim is the joint creation of knowledge between partners and not simply the appropriation of this knowledge by one of the members of the agreement. In the following section, we argue that inter-organizational virtual organizations add more advantages to this type of alliance because of these special features. The latter two sections include some propositions, and the chapter closes with our conclusions.
VIRTUAL ORGANIZATION Since the concept of virtual organization was introduced by Mowshowitz (1986) and popularized by Davidow and Malone (1992), it has become increasingly used in management theory and, in particular, in the information systems literature. An initial approach to this term suggests that a virtual organization is a geographically distributed organization whose members are bound by a longterm common interest, and who communicate and coordinate their work through information technologies (Ahuja and Carley, 1999). Computers and information technologies favour the linking of corporate processes (Davidow and Malone, 1992) and the shift towards virtual organizations entails fundamental changes in managing daily operations and coordination tasks. According to some authors (e.g. Kasper-Fuehrer and Ashkanasy, 2003), there are two approaches to studying virtual organizations, depending on the unit of analysis: the intra-organizational view, in which virtual organization is a collaboration of business units within an organization, or the inter-organizational view, in which different organizations collaborate to form a cooperative agreement. We focus on the second approach since our interest lies in the integration of knowledge through various firms. Virtual organizations use information technologies such as electronic mail to share information and coordinate their work, and this characteristic enables a group to create and sustain its identity
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without a shared physical setting (Ahuja and Carley, 1999). The structure of a virtual organization allows a high degree of flexibility, competitiveness and cost efficiency (Fitzpatrick and Burke, 2000). In line with the inter-organizational approach, we consider a virtual corporation as a temporary network of independent companies linked by information technology to share skills and costs or to accomplish other specific objectives (Byrne, 1993). Other definitions exist, but all of them share the idea that a virtual corporation involves a loosely related group of companies formed to enable collaboration toward mutually agreed on goals (Greis and Kasarda, 1997). Technology allows sharing and communication of information, but virtual organizations also need a high level of trust between individuals involved in the network. As Daniels (1998) states, a cultural network that links people together is perhaps more important than the technology network on its own. Thorne (2004) reflects on some important characteristics of this type of organization: flow of information, permeable internal and external boundaries, shifting work responsibilities, shifting line of authority, and work practices which are more about communication and information than about any material structure. A key feature of virtual alliances or networks is their high degree of adaptability and flexibility (Grabowski and Robert, 1999; Weber, 2002), essential if they are to respond quickly to changes in today’s markets.
STRATEGIC ALLIANCES AS A SOURCE OF KNOWLEDGE INTEGRATION Strategic Alliances Strategic alliances may be an important source of the distinctive competencies that are at the root of competitive advantages (Ireland, Hitt andVaidyanath, 2002). The knowledge-based view (KBV) has acquired particular weight in strategic
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alliance research. This approach has highlighted knowledge and learning capabilities as the most valuable assets that partners can obtain or create through strategic alliances. The specialized literature has also generally accepted that distinctive competencies in knowledge creation and learning through strategic alliances have a positive effect on business performance (Emden, Yaprak and Cavusgil, 2005; George et al., 2001; Shrader, 2001; Dyer and Singh, 1998; Simonin, 1997; Powell, Koput and Smith-Doerr, 1996). The aim of strategic alliances may be to develop necessary resources or capabilities jointly or to gain access to them when other partners have complementary and valuable assets (Hamel, Doz and Prahalad, 1989; Buckley and Casson, 1988). Access to certain resources or capabilities lacking in the cooperating companies is an important underlying factor in the establishment of strategic alliances (Ireland, Hitt and Vaidyanath, 2002; Harrison et al., 2001; Rothaermel, 2001; Das and Teng, 2000; Gulati, 1999; Dyer and Singh, 1998; Madhok and Tallman, 1998; Eisenhardt and Schoonhoven, 1996; Glaister and Buckley, 1996; Grant, 1996; Mitchell and Singh, 1996; Crossan and Inkpen, 1994). Firms decide to stablish a strategic alliance when they find themselves in a vulnerable strategic position because they need resources or capabilities that cannot be developed internally at a reasonable cost in a reasonable time (Das and Teng, 2000), or cannot be achieved through an exchange on the market (Eisenhardt and Schoonhoven, 1996) because there are no organized markets in which they can be acquired, or because these capabilities can be learned or assimilated through cooperation (Ireland, Hitt and Vaidyanath, 2002; Cohen and Levinthal, 1990). Companies that need particular assets that they cannot efficiently transfer on markets or develop internally will seek alternative means of obtaining them. Strategic alliances appear especially attractive as they are a fast, flexible method and also involve a much lower commitment in terms
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of cost and resources than other possible options such as mergers. Environmental uncertainty in today’s markets and rapidly changing technologies need quick responses, which are more easily achieved through the establishment of strategic alliances than in isolation (Dodgson, 1993). Through the extension and combination of the partner firms’ assets, strategic alliance partners are able to learn by establishing valuable assets that can lead to sustainable competitive advantages, and therefore to economic rents (Ireland, Hitt and Vaidyanath, 2002; George et al., 2001; Shrader, 2001; Dyer andSingh, 1998; Simonin, 1997; Powell, Koput and Smith-Doerr, 1996). In this way, companies can create greater value through cooperation than that which they could generate by acting independently.
Alternatives in the Integration of Knowledge Integration of knowledge is a capability that may be developed in the context of a strategic alliance. According to the knowledge-based view, organization is a distributed system of knowledge (Tsoukas, 1996). Kogut and Zander (1992) advance the idea that the justification for the existence of organizations lies in the frame that these provide– like social communities of actions constructed on organizational principles, which cannot be provided by isolated individuals. The creation and transference of knowledge occurs efficiently within the organization (Kogut and Zander, 1992). Therefore, the main aim of organizations and the reason for their existence is the integration of knowledge (Grant, 1996). This is due to the fact that knowledge is stored in the individuals in the shape of specialized knowledge, which allows the creation of new knowledge to advance. Nevertheless, progress in the creation of value through processes of transformation of knowledge into new products and services requires a
combination of more than one type of specialized knowledge. Individuals have limits to make this knowledge integration.. Integration into the market is also problematic, due to difficulties in appropriating explicit knowledge by means of market contracts, or in transference of tacit knowledge, since it requires specific transactions associated with major investments. The organization has also been considered as a community of practice where collective knowledge is absorbed (Brown and Duguid, 1991; Lave and Wegner, 1992). This is also similar to the notion proposed by Tsoukas (1996) in which the organization is a distributed system of knowledge. This author believes that it is a distributed system, not only because it is diffused in the organization, but also because it is indeterminate. The evolution of the system cannot advance, and moreover, it is dependent on the context. Nonaka, Toyama and Nagata (2000) also argue that continuous creation of knowledge is the main aim of an organization. Nevertheless, this approach proposes that strategic alliances and networks also constitute a mechanism for integration of knowledge (Grant, 1996). Grant (1996) justifies the existence of strategic alliances and networks in the creation of knowledge, in some situations. The first of these refers to the transference of explicit knowledge that is not absorbed in specific products, and therefore, cannot be transferred across the market, yet due to uncertainty over its use and sources, neither can it be efficiently created internally. Secondly, an efficient utilization of knowledge requires a correspondence between knowledge and how it can be used, that is to say, how it develops firms’ products (Grant, 1996). When the company’s knowledge base does not match its product portfolio, or when uncertainty surrounds the relation between the two, collaboration between organizations will be an efficient mechanism for the integration of knowledge (Grant, 1996). This is because collaboration enables specialized knowledge to be utilized, since different organizations with different knowledge
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bases may find it easier to apply this specialized knowledge and also find more connections between new knowledge and products that can be developed through this knowledge. The third situation that justifies collaboration in this context is when the speed of innovation is an important factor in competition. In rapidly changing environments, collaboration provides a faster way of innovating (Grant, 1996). The importance of the time factor means internal development is not viable and the acquisition and merger option can turn out to be more expensive than alliances as there is a high degree of uncertainty over what is being acquired (Deeds and Rothaermel, 2003; Lambe and Spekman, 1997). The appropriation or imitation of tacit knowledge, such as technological know-how, is practically impossible mainly because there are no organized markets in which firms can acquire it, and because of the causal ambiguity and social complexity on which knowledge is based. In these conditions, strategic alliances are the main vehicle through which the company can access and internalize external knowledge (Das and Teng, 2000; Kogut, 1988). This value increases when the competencies are heterogeneous among the companies taking part in the agreement (Sakakibara, 1997). Grant (1996) indicates that, under certain circumstances, strategic alliances are the most effective option for integrating knowledge. One situation is- the case where the speed with which the company extends its knowledge is a fundamental issue in creating competitive advantage. Another situation is the case where there is a lack of fit between the knowledge the company has and its product portfolio. Even if the knowledge the firm needs could be obtained through an exchange in the market, it may be that its value deteriorates notably because it is embedded in either organizational routines or other assets possessed by the organization from which it is difficult to separate (Madhok and Tallman, 1998; Pucik, 1988). One characteristic of organizational know-how is precisely its cumulative
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nature, and the exchange of know-how among companies requires long-term relationships to be established (Kogut and Zander, 1992). Organizations in today’s markets need innovation as well as flexibility and efficiency, but they also concentrate their resources on core capabilities. Therefore, self-sufficiency is increasingly difficult (Inkpen, 1996). Grant (1996) postulates this idea when he states that flexibility is one of the characteristics essential to the integration of knowledge if it is to be capable of creating competitive advantage. Flexibility in the integration of knowledge is the degree to which a firm accesses additional knowledge and re-shapes existing knowledge (Grant, 1996), and it is one of the most important factors for the development of capabilities in hyper-competitive environments. In the search for this flexibility, advantages can be found in integration through collaboration with other organizations in some competitive industries such as biotechnology, since they allow access to a wider range of relations between knowledge and its possible applications. Therefore, collaboration provides a mechanism that will facilitate knowledge integration. The justification of the superiority of alliances over the market and over a single organization is therefore determined by the existence of imbalances between knowledge and its application, that is to say, products (Grant, 1996). Nevertheless, rather than conditioning efficiency of knowledge creation through inter-organizational collaboration to the situations proposed by Grant (1996) and Grant and Baden-Fuller (2004), we agree with Powell, Koput and Smith-Doerr (1996) that, in rapidly changing environments and in industries with particularly fast technological development, the specialized knowledge necessary to make innovations is distributed across a great variety of organizations. It is difficult for an isolated organization to have all the necessary capabilities to innovate continuously.
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This is more evident in high technology industries, where the knowledge needed to produce innovations rapidly and effectively is rarely found in a single, isolated firm. Hence, cooperation arises between companies as a mechanism that increases organizational learning and knowledge (Powell, Koput and Smith-Doerr, 1996; Hamel, 1991; Dogson 1993). Therefore, we propose that organizational collaboration is a mechanism which facilitates knowledge creation in certain circumstances. This idea is shared by some authors who contend that organizational performance and differences between companies cannot be understood nowadays without considering the collaboration and social networks in which they are situated. Gulati, Nohria and Zaheer (2000) analyze how the incorporation of strategic collaboration enriches discussion in different areas of strategic research. Our proposition suggests that external knowledge development through collaboration complements rather than substitutes internal knowledge integration (Powell, Koput and Smith-Doerr, 1996).Therefore, we put forward the following proposition: Proposition 1. In rapidly changing and hypercompetitive environments, knowledge sources are distributed across organizations and the establishment of strategic alliances will provide a superior mechanism that enables the generation of knowledge creation capabilities.
Specific Learning Alliances On the other hand, knowledge-related strategic alliances may be established in order to acquire knowledge from the partner or to jointly develop new knowledge. We agree with Grant and BadenFuller (2004) when they argue that strategic alliances will be more positive to all of the partners if their aim is to share diverse frameworks of specialized knowledge. Knowledge is distributed between different entities (Powell, Koput and Smith-Doerr, 1996) and the collaboration between
them will favour learning (Levinthal and March, 1994). Learning in collaboration will depend on sharing knowledge and also on sharing dynamic capabilities that allow it to be used and exploited (Powell, Koput and Smith-Doerr, 1996). Alliances whose chief aim is learning have been termed learning alliances (Lane and Lubatkin, 1998; Khanna, Gulati and Nohria, 1998). In this type of alliance, the process of establishing and implementing the alliance will be more important than the final result, since this process presents an opportunity for mutual learning (Khanna, Gulati and Nohria, 1998), rather than acting as a passive receptor of the partner’s capabilities (Hamel et al., 1989). Joint knowledge creation in the alliance will provide common benefits to partners, as opposed to the private benefits that will be only derive from copying partners’ skills for later application in individual operations (Khanna, Gulati and Nohria, 1998). These authors propose the concept of common benefits as those that every alliance partner accumulates from the collective application of the learning that organizations obtain as a consequence of forming part of an alliance (Khanna, Gulati and Nohria, 1998: 195). Hence, they implicitly recognize the joint creation of knowledge, or at least, that both partners learn. We therefore believe that the purpose of the alliance should be to create new knowledge together, and not to absorb the partner’s knowledge. New knowledge arising from the alliance has not previously existed for either of the partners (Phan and Peridis, 2000). This line of research is still in its first stages, since it differs from studies that analyze alliances as a way of accessing the partner’s knowledge. These studies do not specifically address the joint creation of knowledge. One of the few studies in this line is by Phan and Peridis (2000) who compare research into acquiring knowledge to single-loop learning, whereas, for new knowledge to be created, double-loop learning should take place.
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Double loop or second order learning (Argyris and Schon, 1978, 1996) also changes the paradigms on which organizational thought is based. For this type of learning to occur in alliances, the mental models partners use to resolve problems or to interpret conclusions must be changed. It provides a new way of drawing conclusions and of resolving conflicts in the alliance and therefore, of creating knowledge that will be new for the partners. Lubatkin, Florin and Lane (2001) follow a similar view. They study reciprocal learning, taking as their unit of analysis the two organizations that collaborate on a project rather than only one of the firms. The partners therefore become interdependent. These authors assimilate this type of learning to the concept of double loop learning proposed by Argyris and Schon (1978). Nevertheless, cooperation across strategic alliances is an organizational learning process through which companies internalize competencies from their partners (Kale, Singh and Permutter, 2000) or configure new knowledge together. It is not unusual to find companies that only take part in strategic alliances to gain access to their partners’ knowledge, but make no attempt to integrate this knowledge into their own operations. Therefore, we do not deny the existence of strategic alliances in which the main aim is the transference, acquisition or absorption of knowledge. The type of company that acts in this way may even make up the most numerous group. Lubatkin, Florin and Lane (2001) propose a typology of these types of alliances in which learning is the principal objective, depending on how tacit the knowledge the alliance attempts to create or acquire is, and on how difficult the governance of the alliance is. Reciprocal learning alliances are one of the proposed types: they are characterized by low levels of difficulty in governance and the creation of tacit knowledge. This is the type of alliance in which our interest lies, since our area of study concerns markets characterized by hyper-competition and rapid change. The same authors also argue that this type of alliance will become more common
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as a result of global competition, the convergence of technologies and the need to develop capabilities more rapidly. In these circumstances, the absorption of the partner’s knowledge, which may frequently be unfamiliar to the firm attempting to absorb this knowledge, may be a slow process. Therefore, our second proposition is: Proposition 2. In environments that demand rapid innovations, all partners in alliances based on the joint creation of knowledge will perform better than those in alliances in which the aim is to absorb knowledge from one of the organizations.
KNOWLEDGE INTEGRATION THROUGH INTER-ORGANIZATIONAL VIRTUAL ORGANIZATIONS We now turn to virtual organizations and the advantages this form of virtual collaboration may have in the integration of knowledge. Information and communication technology is the essential enabler of virtual organizations, defined as a conglomerate of firms that collaborate in a strategic alliance (Kasper-Fuehrer and Ashkanasy, 2004). This technology allows greater flexibility, which is an important characteristic to obtain competitive advantage in dynamic environments. Following the arguments of some authors (e.g., D’Aveni, 1994) who claim that traditional organizational designs such as functional structures are too rigid in today’s hyper-competitive markets, new inter-organizational structures need more dynamic and flexible ways of organizing. New information and communication technologies have the particular attributes to support the virtuality of these inter-organizational structures (Scholz, 1996), and add dynamism and flexibility. Temporal and distance barriers can easily be jumped with the use of these new technologies (Byrne et al., 1993; Mowshowithz, 1994; Goldman et al., 1995), which also facilitate global
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collaboration by allowing organizations to cross distance barriers (Byrne et al., 1993). As stated above, compared to the option of internal development, strategic alliances are a fast and flexible means to develop new resources, such as knowledge, and have lower costs than other options such as mergers. All of these advantages multiply in the context of inter-organizational virtual organizations, since they have the same properties as a strategic alliance, but with greater flexibility and reduced temporal and spatial barriers. If strategic alliances are the most effective option to integrate knowledge when speed is a fundamental issue in creating competitive advantage (Grant, 1996), the case of inter-organizational virtual organizations may be even more beneficial. This idea is embraced in our next proposition. Proposition 3. Inter-organizational virtual organizations contribute to increase flexibility in the collaboration between organizations and therefore they are superior to other options in the integration of knowledge in rapidly changing and hyper-competitive environments. Furthermore, one of the properties of knowledge integration that Grant (1996) explains is flexibility or the degree to which an organization accesses additional knowledge and reconfigures its existing knowledge. Since flexibility is an essential feature of knowledge integration, it must be present in the case of alliances in which the main objective is the creation of knowledge. In the context of a changing knowledge environment, flexibility is a requirement for the integration of knowledge (Van den Bosch, Volberda and de Boer, 1999) since this context demands that firms have different types of knowledge that are distributed across companies. Through collaboration, organizations can easily create a network between different blocks of knowledge and gain access to a wider application of this knowledge (Grant, 1996). Inter-organizational
virtual organizations facilitate this access because they reduce temporal and spatial barriers. Individuals from different organizations working together must be also trained to deal with their partners’ diverse organizational cultures. This training also enables individuals to break out of the mental prisons that prevent them from adopting an innovative attitude because of an organization’s strong identity and values. In this vein, Van den Bosch, Volberda and de Boer (1999) state that a strong culture makes flexibility for knowledge absorption more difficult, a perspective we adopt in the integration of knowledge from different organizations. Furthermore, strong cultures can cause - “xenophobia” (Ouchi, 1981). The wide range of knowledge necessary to create innovations in hyper-competitive environments could be constrained by this strong organizational culture. In the case of strategic alliances, cultural boundaries must be relaxed in order to deal with other partners. Introducing features from interorganizational virtual organizations is beneficial to the day-to-day working with different organizational cultures. The reasoning here is that individuals become used to the way other organizations do things if communication and information technologies connect these daily operations easily, without considering spatial barriers.Therefore, we make the following proposition: Proposition 4. Flexibility in the integration of knowledge is facilitated by inter-organizational virtual organizations due to their easy access to global collaboration without temporal and spatial barriers.
CONCLUSION This study examines virtual organizations from an inter-organizational point of view. Connections between organizations may be easier through the new communication and information technologies. Employees carry out their daily operations
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with other organizations without concern for spatial barriers. We apply this idea to strategic alliances since we define virtual organizations as a network of independent companies linked by information technology to share skills and costs or to accomplish specific objectives (Byrne, 1993). In this vein, we argue that the virtual factor may provide strategic alliances with certain advantages, specifically in alliances whose main purpose is knowledge integration. Knowledge integration is one of the main capabilities that organizations must possess in today’s markets (Grant, 1996). Organizations pertaining to high technology industries need to accelerate the speed with which they introduce innovations in the market in order to survive in hyper-competitive environments. Nevertheless, sources of knowledge are often distributed across a great variety of organizations. We propose that strategic alliances are a superior mechanism that enables the creation of new knowledge in this type of environment. We also argue that the advantage could be even greater in the case of alliances in which the main aim is the joint creation of knowledge, as compared to other kinds of agreements in which one partner absorbs knowledge from other partners. Common benefits to all of the partners may be higher if their objective is mutual learning and creating new knowledge (Khanna, Gulati and Nohria, 1998) as a consequence of being part of the alliance because of the distribution of expertise across organizations. In high technology industries, inter-organizational virtual organizations add further advantages to this option of knowledge integration through strategic alliances because of the importance of speed and flexibility. Moreover, one of the properties or dimensions in the integration of knowledge according to Grant (1996) is the flexibility or the degree in which an organization accesses additional knowledge and reconfigures its existing knowledge. We also argue that inter-organizational virtual organizations facilitate this knowledge
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reconfiguration because they reduce temporal and spatial barriers. Implications for managers concern the option of considering this kind of inter-organizational virtual agreement as an alternative and an opportunity to integrate knowledge faster than in isolation. This is an important strategic decision that they should bear in mind. Where their organizations participate in this type of collaboration, they should also consider changing the way daily operations are undertaken, and the fact that these changes can have both positive and negative effects. Our study has some limitations derived from its theoretical nature. We cannot confirm and generalize our arguments without testing the propositions through an empirical study. A deeper analysis is therefore required in order to prove whether the advantages of strategic alliances over other alternatives consist of superior forms of organizing in the case of knowledge integration in high technology industries and whether including the virtual dimension in these linkages adds even more advantages. Further research should also extract and contrast the true, specific characteristics of inter-organizational virtual organizations as compared to traditional strategic alliances and what their possible strengths may be. However, this is an initial approach to the phenomenon from a point of view in which we combine strategic alliances, virtual organizations and knowledge-based view literatures.
REFERENCES Ahuja, M. K., & Carley, K. M. (1999). Newtork structure in virtual organizations. Organization Science, 10(6), 741–757. doi:10.1287/ orsc.10.6.741 Argyris, C., & Schön, D. (1978). Organizational learning: a theory of action perspective. Mass: Addison-Wesley, Reading.
Knowledge Integration through Inter-Organizational Virtual Organizations
Argyris, C., & Schon, D. (1996). Organizational learning II. Theory, method and practice. Mass: Addison-Wesley, Reading. Brown, J. S., & Duguid, P. (1991). Organizational learning and communities-of-practice: toward a unified view of working, learning, and innovation. Organization Science, 2(1), 40–57. doi:10.1287/ orsc.2.1.40 Buckley, P. J., & Casson, M. (1988). A theory of cooperation in international business. In F.J. Contractor, & P. Lorange (eds.), Cooperative strategies in international business (pp. 31-54). Lexington: Lexington Books. Byrne, J. (1993). The virtual corporation. Business Week, 8, 98–102. Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity, a new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128–152. doi:10.2307/2393553 Crossan, M. M., & Inkpen, A. C. (1994). Promise and reality of learning through alliances. The International Executive, 36(3), 263–274. doi:10.1002/ tie.5060360302 D’Aveni, R. (1994). Hypercompetition: Managing the Dynamics of Strategic maneuvering. Free Press, New York. Daniels, M. (1998). Focussing in a fuzzy world: trading in the networking world. Journal of Information System, 24(6), 451–456. Das, T. K., & Teng, B. (2000). A resource-based theory of strategic alliances. Journal of Management, 26(1), 31–61. doi:10.1016/S01492063(99)00037-9 Davidow, W., & Malone, M. (1992). The virtual corporation: structuring and revilatizing the corporatin for the 21st Century. New York: Harper Collins.
Dyer, J. H., & Singh, H. (1998). The relational view, Cooperative strategy and sources of interorganizational competitive advantage. Academy of Management Review, 23(4), 660–679. doi:10.2307/259056 Eisenhardt, K. M., & Schoonhoven, C. B. (1996). Resource-based view of strategic alliance formation, Strategic and social effects entrepreneurial firms. Organization Science, 7(2), 136–150. doi:10.1287/orsc.7.2.136 Emden, Z., Yaprak, A., & Cavusgil, S. T. (1998). Learning from experience in international alliances, antecedents and firm performance implications. Journal of Business Research, 58(7), 883–892. doi:10.1016/j.jbusres.2003.10.008 Fitzpatrick, W. M., & Burke, D. R. (2000). Form, functions, and financial performance realities for the virtual organization. SAM Advanced Management Journal, 65(3), 13–22. George, G., Zahra, S. A., Wheatley, K. K., & Khan, R. (2001). The effects of alliance portfolio characteristics and absortive capacity on performance. A study of biotechnology firms. Journal of High Technology, 12, 208–226. Glaister, K. W., & Buckley, P. J. (1996). Strategic motives for international alliance formation. Journal of Management Studies, 33(3), 301–332. doi:10.1111/j.1467-6486.1996.tb00804.x Grabowski, M., & Roberts, K. H. (1999). Risk mitigation in virtual organizations. Organization Science, 10, 704–721. doi:10.1287/orsc.10.6.704 Grant, R. M., & Baden-Fuller, C. (2004). A knowledge accessing theory of strategic alliances. Journal of Management Studies, 41(1), 61–85. doi:10.1111/j.1467-6486.2004.00421.x Grant (1996). Prospering in dynamically-competitive environments: organizational capability as knowledge integration. Organization Science, 7, 375-387.
443
Knowledge Integration through Inter-Organizational Virtual Organizations
Greis, N. P., & Kasarda, J. D. (1997). Enterprise logistics in the information era. California Management Review, 39(3), 55–78. Gulati, R. (1999). Network location and learning, the influence of network resources and firm capabilities on alliance formation. Strategic Management Journal, 20, 397–420. doi:10.1002/ (SICI)1097-0266(199905)20:53.0.CO;2-K Gulati, R., Nohria, N., & Zaheer, A. (2000). Strategic networks. Strategic Management Journal, 21(3), 203–217. doi:10.1002/ (SICI)1097-0266(200003)21:33.0.CO;2-K
Kasper-Fuehrer, E. C., & Ashkanasy, N. M. (2004). The interorganizational virtual organization. International Studies of Management and Organization, 33(4), 34–64. Khanna, T., Gulati, R., & Nohria, N. (1998). The dynamics of learning alliances: Competition, Cooperation, and relative scope. Strategic Management Journal, 19(3), 193–212. doi:10.1002/ (SICI)1097-0266(199803)19:33.0.CO;2-C Kogut, B. (1988). Joint ventures: theoretical and empirical perspectives. Strategic Management Journal, 9(4), 319–333. doi:10.1002/ smj.4250090403
Hamel, G. (1991). Competition for competence and interpartner learning within international strategic alliances. Strategic Management Journal, 12, 83–103. doi:10.1002/smj.4250120908
Kogut, B., & Zander, U. (1992). Knowledge of the firm, combinative capabilities, and the replication of technology. Organization Science, 3(3), 383–397. doi:10.1287/orsc.3.3.383
Hamel, G., Doz, Y. L., & Prahalad, C. K. (1989). Collaborate with your competitors and win. Harvard Business Review, 67(1), 133–139.
Lane, P. J., & Lubatkin, M. (1998). Relative absorptive capacity and interorganizational learning. Strategic Management Journal, 19(5), 461–477. doi:10.1002/ (SICI)1097-0266(199805)19:53.0.CO;2-L
Harrison, J. S., Hitt, M. A., Hoskisson, R. E., & Ireland, R. D. (2001). Resource complementarity in business combinations, extending the logic to organizational alliances. Journal of Management, 27, 679–690. doi:10.1177/014920630102700605 Inkpen, A. C. (1996). Creating knowledge trough collaboration. California Management Review, 39(1), 123–140. Ireland, R. D., Hitt, M. A., & Vaidyanath, D. (2002). Alliance management as a source of competitive advantage. Journal of Management, 28(3), 413–446. doi:10.1177/014920630202800308 Kale, P., Singh, H., & Perlmutter, H. (2000). Learning and protection of proprietary assets in strategic alliances, Building relational capital. Strategic Management Journal, 21, 217–237. doi:10.1002/ (SICI)1097-0266(200003)21:33.0.CO;2-Y
444
Lave, J., & Wenger, E. (1992). Situated Learning: Legitimate Peripheral Participation. Mass: Harvard U. Press. Madhok, A., & Tallman, S. (1998). Resources, transactions and rents, managing value through interfirm collaborative relationships. Organization Science, 9(3), 326–339. doi:10.1287/orsc.9.3.326 Mitchell, W., & Singh, K. (1996). Survival of business using collaborative relationships to commercialize complex goods. Strategic Management Journal, 17, 169–195. doi:10.1002/ (SICI)1097-0266(199603)17:33.0.CO;2-#
Knowledge Integration through Inter-Organizational Virtual Organizations
Mowshowith, A. (1986). Social dimensions of office automation. In M. Yovitz, Advances in Computers (v.25). New York: Academic Press. Nonaka, I. (1994). A dynamic theory of organizational knowledge creation. Organization Science, 5(1), 14–37. doi:10.1287/orsc.5.1.14 Nonaka, I., & Takeuchi, H. (1995). The knowledgecreating company. New York: Oxford University Press. Nonaka, I., Toyama, R., & Nagata, A. (2000). A firm as a knowledge creating entity: a new perspective on the theory of the firm. Industrial and Corporate Change, 9(1), 1–20. doi:10.1093/ icc/9.1.1 Ouchi, W. G. (1981). Theory Z: How American business can meet the Japanese challenge. Reading, MA: Addison-Wesley. Powell, W. W., Koput, K. W., & Smith-Doerr, L. (1996). Interorganizational collaboration and the locus of innovation, networks of learning in biotechnology. Administrative Science Quarterly, 41(1), 116–145. doi:10.2307/2393988 Pucik, V. (1988). Strategic alliances, organizational learning and competitive advantage: the HRM agenda. Human Resource Management, 27(1), 77–94. doi:10.1002/hrm.3930270105 Rothaermel, F. T. (2001). Incumbent’s advantage through exploiting complementary assets via interfirm cooperation. Strategic Management Journal, 22, 687–699. doi:10.1002/smj.180 Sakakibara (1997). Heterogeneity of firm capabilities and cooperative research an development: an empirical examination of motives. Strategic Management Journal, vol. 18, n. 6, 143-165.
Shrader, R. C. (2001). Collaboration and performance in foreign markets, the case of young high-technology manufacturing firms. Academy of Management Journal, 44(3), 45–60. doi:10.2307/3069336 Simonin, B. L. (1997). The importance of collaborative know-how, an empirical test of the learning organization. Academy of Management Journal, 4(5), 1150. doi:10.2307/256930 Spender, J.C. (1996). Making knowledge the basis of a dynamic theory of the firm. Strategic Management Journal, 17 (Winter Special Issue), 45-62. Tsoukas, H. (1996). The firm as a distributed knowledge system: a constructionist approach. Strategic Management Journal, 17 (Winter Special Issue), 11-25. Van den Bosch, F. A. J., Volberda, H. W., & de Boer, M. (1999). Coevolution of firm absortive capacity and knowledge environment: organizational forms and combinative capabilities. Organization Science, 10(5), 551–568. doi:10.1287/orsc.10.5.551 Weber, M. M. (2002). Measuring supply chain agility in the virtual organization. International Journal of Physical Distribution & Logistics Management, 32(7), 577–590. doi:10.1108/09600030210442595
ENDNOTE a
The present study is part of a wider research project, which has received financial support through a grant (SEC2003-01825/ECO) from the Spanish Ministryof Science and Technology and FEDER (European Fund for Regional Development) andfrom the Valencian Institute of Economic Research (Convocatoria de a yudas a la investigación 2006).
This work was previously published in Connectivity and Knowledge Management in Virtual Organizations: Networking and Developing Interactive Communications, edited by Cesar Camison, Daniel Palacios, Fernando Garrigos and Carlos Devece, pp. 61-72, copyright 2009 by Information Science Reference (an imprint of IGI Global). 445
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The Development of Knowledge and Information Networks in Tourism Destinations Júlio da Costa Mendes University of Algarve, Portugal
ABSTRACT This chapter looks to analyse new paradigms in the relationship between public and private organisations towards tourism destinations. It proposes new approaches for increased performance both at the competitive and the organisational level. Based on the literature review, this chapter suggests new organisational forms of being and interaction directed at increased customer needs and growing competitiveness on the tourism industry. The development of public-private partnerships and knowledge networking in destinations and in organisations are issues also addressed. FurtherDOI: 10.4018/978-1-60960-587-2.ch213
more, the implementation of inter-organisational networks in a cooperative environment is important in developing and maintaining an adequate environment with shared objectives and practices in tourist destinations.
INTRODUCTION Globalisation has had a decisive impact on the changing environment and one in which nowadays economies are facing. This fact has stimulated growing interest from researchers who have turned their attention to issues of globalisation, the digital era, innovation and Knowledge Management.
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The Development of Knowledge and Information Networks in Tourism Destinations
The rise of the so-called New Digital Economy, characterised by the spread of new information and communication technologies, has provoked over recent years a revolution in the world of business and more specifically in tourism, causing changes in corporate strategies and organisational structures. For the majority of countries, the tourism sector represents an important service industry, socio-economically significant for hosting regions. This is not only related to dynamic sector growth but also to the multiple effects generated by globalisation to other sectors of the economy. Nowadays, tourism organisations face a dynamic and uncertain environment that require flexible and fast results essential to changing businesses. This, linked to the need for cooperation between the various actors in the value chain of the tourist destination, has generated the onset and development of several inter-organisational networks, aimed at improving competitiveness of destinations and involved organisations. Developing a climate of cooperation in tourist destinations implies firstly that actors are aware that they belong to a chain where their performance complements and contributes to the value of the tourist experience. The introduction of programmes and integrated projects, common visions, cooperative agreements and collaboration between public and private entities based on the pursuit of greater global objectives, is a networking reality for tourism destinations. The interactive process of close and coherent collaboration between all actors and organisations, public and private, at the regional, national and even international scale, is of central importance for competitiveness in tourist destinations. This creates synergies for networking providers and allows the development of a common vision towards tourism building based on concerted efforts from involved parties. Based on the review of the literature focused on the concepts of tourism destination and virtual knowledge and information networks, the paper
intends to discuss, in theoretical terms, the benefits of the establishment of partnerships and cooperation networks between public and private tourism organisations, contributing for the development and implementation of improvement competitiveness strategies in tourism destinations. To the effect, the paper begins by clarifying the tourism destination concept and characterizing the kind of consumption product that consubstantiates the tourism experience. Than, it discusses the need for new approaches in terms of tourism destination management, assuming that the main objective of the Destination Management Organisations is to maximize the synergies of the value chain, ensuring high levels of satisfaction for tourists as much as stakeholders. Finally, it suggests that the constitution of partnerships and the sharing of knowledge and information between the tourism sector organisations is a strategic issue for the competitiveness of the tourism destinations and, in that sense, it must be an object of the greatest attention from the Destination Management Organisations intending to succeed in terms of performance.
TOURISM DESTINATION Tourism destination is closely linked to new experiences and associated memories. Although a composite unit representing a region’s supply, it is considered a paradigmatic example of virtual organisation. As a setting comprising economic, cultural and social activities, the tourism destination has come to be understood as a product on offer, and thus the public institutions responsible for that destination and the regional tourism organisations operating within that destination see themselves as obliged to establish a set of facilities and actions that ensure the best possible positioning in a highly competitive market when it comes to attracting tourists (Beerli & Martin, 2004)
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The studies carried out by Butler (1980), Gunn (1993), Laws (1995) and Pearce (1989) regard tourism destination as a system containing a number of components such as attractions, accommodation, transport and other services and facilities. The tourism destination generally comprises different types of complementary and competing organisations, multiple sectors, facilities and an array of public/private linkages that create a diverse and highly fragmented structure (Pavlovich, 2003). The complexity of the system arises from the interactive environment and complementarity that characterises the relations that develop between the different types of service providers and their acting influence. Under a complex system of the provision of services, with product and services being provided simultaneously by different units of an organisation, or different organisations, involved agents should interact efficiently, so that no situation contributes negatively on the global tourist experience. Given the close and complementary interrelationships established between the different types of industry organisations, it becomes important to ensure efficient coordination of flow of information between organisations of the sector (Bouncken, 2000; Hope & Muhlemann, 1998; Smith, 1994; Pizam, 1991). In this sense, besides the organic structure embodied, the tourism destination develops its activity essentially through the pursuit of common objectives and strategic implementation grounded on a Web of relations and contacts with organisation of the sector. The destination must be considered as a whole – a system with inputs and outputs (Tinsley & Lynch, 2001).
The Composite Product The global or composite product, by definition is an interactive product that results from the total supply made available to tourists. Structurally, it is a product developed around a combination of
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experiences which are central to the expectations and overall assessment by customers. In this sense, it can be analysed as “an intangible composite of many interrelated components” (Pizam, Neumann & Reichel, 1978: p. 316) or as a combination of rendered and used services in a dynamic, multifaceted environment, domestic or international, where controversial issues and conflicting interests are always present (Silva, 1991; Papadopoulos, 1989; Guibilato, 1983). Klein (2000) considers that the tourist product is the destination and the process that results from the overall experience of tourists, while the subproducts are transports, excursions, food and drink, accommodation, entertainment and services, as well as the respective management. The same point of view is held by Silva, Mendes & Guerreiro (2001) and by Rita (1995) among others. The value chain joins actors and consumers, representing a chain link to an experience that the tourist classifies in terms of satisfaction and value. Managing the chain and maximising the value of experiences of customers by interacting with several chain links is a task which transcends the sectorial boundaries of industry. The break of a chain link, disfunctionality, an ill-established contact or an unpleasant surprise may result negatively in terms of tourist satisfaction and contribute toward a negative image of the destination. The “halo effect” can still occur, which means that satisfaction or dissatisfaction with one of the components leads to satisfaction or dissatisfaction with the total tourist product (Weiermair, 2000a,b; Stauss & Weinlich, 1997; Brathwaite, 1992; Pizam et al., 1978). Once the value is added at each level of the production process, it becomes important to understand to some degree of certainty how the tourist production chain for a specific destination or destination package will combine to produce added value for the different types of consumers and market segments. The tourists, in consuming the destination-product, look to obtain the greatest value for the least effort which assumes the maxi-
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mum destination competitiveness (Martín, 2000; Huete, 1994; Smith, 1994; Weiermair, 1994).
Tourism Experience The leisure and tourism experience has been described as an “a subjective mental state felt by participants” (Otto & Ritchie, 1996, p.166). While products are fungible and services intangible, the value of the experience remains in the memory of individuals investing in the event. For intangible services, the experiences are regarded as events that commit people in a particular manner and, as such, are memorable. While the supply of services ends with the experience of visitors to a destination, it begins before arrival and ends with memories and future visit plans (Pine & Gilmore, 1999; Commission Européenne, 1999). Various authors refer to the composite product associating it to the complex experience that the tourist has from the moment he or she leaves the place of residence until the moment he or she returns home (Silva et al., 2001; Davidson & Maitland, 1997; Smith, 1994; Papadopoulos, 1989; Buckley, 1987). For consumers that deal with a number of meetings during a stay, it is the sum of services that is at the origin of forming perceptions and not the specific products or isolated meetings of services. Regardless of the evaluation or perception of specific quality of subproducts, tourists assess the tourism experience as a whole. This suggests that what is consumed and evaluated in a holistic manner should also be produced and managed holistically (Weiermair, 2000a; Fayos-Solá & Moro, 1995; Gummesson, 1994; Brathwaite, 1992). The process by which the tourist perceives and recollects a destination travel experience is complex and multifaceted precisely because there are a significant number of involved actors in the experience. Consequently, complete destination experience results from a wide combination of
individual experiences by tourists, separated in time and space. In conceptual terms, the tourist experience consists in the continuous flow of services related and integrated, and which are acquired during a limited period of time, most often in different geographical areas. Most businesses that supply tourist products or services do so in the form of a package which includes a combination of physical items, services; interactions that a tourist experiences at different occasions and holds in perceived memory his or her tourist experience. Increasingly, how these packages are conceived and operated influence the experience of tourists at the destination (Albrecht & Zemke, 2002; Kandampully, 2000; Denmann, 1998; Ritchie & Crouch, 1997; Haywood, 1993; Michaud, Planque & Barbaza, 1991). Research in service marketing recognises that, although the performance of services is supported by tangible goods, in the case of tourism, what is actually bought by tourists is an experience, that is, an array of interactions, interpersonal relations that result from various contacts established between service providers and tourists during the period spent at the destination (Frochot & Hughes, 2000; Kandampully, 2000; Ritchie & Crouch, 2000; Weiermair, 2000a). During his or her stay, the tourist consumes not only reality but also representations and symbols of reality, asserting what Lutz & Ryan (1993, p.356) refer to as the rise of “consumption aesthetics”. In this sense, trying to attribute rationalism to the tourist experience may confuse the reason behind tourist motivation and behaviour, more so when there is an awareness that emotions and confusion that tourists reveal are part and parcel of the tourist phenomenon (Ryan, 1995). In this sense, the experience is embodied around a combination of emotions, experiences, in essence a holistic product, which has significant implication in terms of repositioning the supply of tourism destinations. On the other hand, it is clear that the tourist embarks on this experience with
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knowledge and demand levels increasingly more developed, resulting from comparisons with past experience, greater awareness to details, through communication and informal messages, word of mouth, etc. The paradigm of experimental vision analyses the experience consumption as “a subjective fundamental level of knowledge with a variety of symbolic meaning, hedonistic responses and aesthetic criteria (…) focused on caring answers by each person, including, though not limited to, fantasies, sentiments and enjoyment” (Otto & Ritchie, 1995, p. 38). The experience is affected by a vast set of factors, many of which are not directly related with the purchase of a specific product. It is the combination of inherent factors in terms of context and satisfaction of each of the purchased services, consumed throughout the unfolding holistic experience, which determines the overall level of tourist satisfaction. The quality of the experience is generally recognised as a more subjective measure, while quality service is often obtained in more objectively. While quality of service focuses generally on a specific service commitment, the quality of the experience includes a larger combination of commitments. A more comprehensive concept and greater temporal horizon on the quality context of the experience tends to highlight the hedonistic component of the relation that visitors establish with the tourist destinations (Ritchie & Crouch, 1997). The tourists look to obtain working benefits that are symbolic and experiences through activities and services that make up the tourist experience. In fact, the tourist experience is a continuum moment of truth, the quality of which is reached only when reality coincides with consumer expectations. But consumers are different; possessing different expectations transforms the concept of quality into one that is relative. Quality cannot be regarded in a singular manner rather it is diverse composed by different market segments (Vega, Casielles & Martín, 1995; Bordas, 1994).
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The tourist experience is thus consolidated around a vast set of components offered by several organisations with different objectives and form of operation. Service suppliers should recognise that satisfaction of visitors with organisation is influenced by several pre-arrival and post-arrival services. The success of the destination product depends on the provision of the right combination of components to satisfy the demands of visitors, requiring coordination, cooperation and partnerships. From the management point of view of Destination Management Organisations, it is clear that it is impossible to control many of the factors that contribute to a destination quality experience. On the other hand, the skills and possibilities of actors and operators controlling these factors are diverse and distinct; some of which are by separate organisations, other not yet controlled. This can compromise the standards promised or proposed in campaigns affecting how tourists experience their stay.
Competitiveness of Tourism Destinations Competitiveness is one of the central concerns by tourist destination managers. Improving performance levels of tourist destinations in order to meet stakeholder expectations, adapted to accommodate sustaining needs related to environment, heritage and culture of hosting regions, constitutes a challenge and an investment for most Destination Management Organisations. The challenges for organisational management and other local or regional virtual systems are today particularly high. In the case of tourist destinations, they are expected to react clearly and intelligently, to act simultaneously according to plans, to reinforce identity and added supply value, to conceive alliances for coordinated and cooperative networking actions, stressing product quality and culture service. Analysis, planning, implementation and control of programs intended
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to influence the visiting customer choice, especially before arriving at the destination, strategy selection, and destination marketing plans, represent the importance given to competitiveness of tourist destinations (Leoni, 1999; Ridley, 1995; Middleton, 1994). The issue is even more relevant when there is an awareness that “tourism is a highly decentralized industry consisting of enterprises different in size, location, functions, type of organization, range of services provided and methods used to market and sell them. In addition, a variety of trade associations, co-operative institutions and official or semi-official organisations at the local, regional and national and international level play an important role in the industry “(Schmoll, 1997, p.30). Most of these organisations are small-scale, constituting an added challenge for Destination Management organisers who among others should assume a dynamic or facilitating role in the process of formalising cooperation in the entrepreneurial sector. “Networking is also important for small and medium-sized enterprises, in that it offers a way of combining advantages such as flexibility, with economies of scale which networks offer” (Corvelo, Moreira e Carvalho, 2001, p. 23). The performance of the tourist destination benefits greatly if based on knowledge sharing and long-life learning and innovation. Maximising information flows for all those involved is essential to consolidate the learning process of involved actors (Klein, 2000; EFQM 1999). The need to learn, to generate greater value and differentiate supply constitutes nowadays a key component for competing systems. The competitive advantage is gained only by bringing together the knowledge, expertise, capital and other resources of the various tourism organizations (Fayall & Garrod, 2004).
NEW ORGANISATIONAL AND MANAGEMENT PARADIGMS IN THE CONTEXT OF TOURISM DESTINATIONS In this environment of great complexity, instability and uncertainty, organisational changes have been regarded as one of the main vehicles in structuring and exploring the new world of business (Toledo & Loures, 2006). The advent of the information era has made many of the fundamental assumptions of the industry obsolete and the more boundaries lessen the more involved corporate strategies and identity change. New organisational forms are possible because information technology has the capacity to modify the traditional space-time interaction (Schultze & Boland, 2000). The virtual reality, or the process of virtual reality, possesses two main characteristics that facilitate its use on organisations. Detachment of the here and now according to Lévy (1996), an organisation which virtualises itself, deterritorialises itself, becoming “non-present”. Customers can contact organisations virtually, regardless of where they may be as long as they possess access to a computer and modem. The second characteristic stated by the author is the passing from the interior to the exterior and the exterior to the interior, suggesting that there are no longer limits, place and time commix. Virtual organisation appears as an organisational model of the 21st century, sustained by a radical change of classical organisational concepts and work division. Previous research suggests that virtual organisations tend to be non-hierarchical (Goldman, Nagel & Preiss, 1995; Beyerlein, Johnson & Beyerlein, 1994; Camilus, 1993; Mills 1991) and decentralised (Baker 1992). Researchers have found that network structures explain organisational behaviour better than formal structures (Krackhard & Hanson 1993; Bacharach & Lawer 1980).
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The concept of virtual organisations can be understood as a form of cooperation between businesses and organisations, thus becoming true dynamic cooperation networks, which through the use of new information and communication technology have as objectives increasing competitiveness of network partners and enabling exploration of new market opportunities. The components of this new organisational form essentially develop from partnerships, response capacity in terms of market demands, quality of products and services rendered and greater awareness and environmental responsibility (Tapscoot & Caston, 1993). This strategic option which consists in supervising the running and organisation of business for virtualisation is one of the options being followed by organisations that seek sustainable competitive advantages. In recent literature, virtual organisations are presented as success models, suggesting that ultimately virtual reality represents innovation, a widening of the corporate value chain, better information flows and corporate decision-making (Toledo & Loures, 2006). There is a proliferation of terms used to define emerging “new organisations”: agile organisations, network organisations, virtual organisations, extended enterprises, knowledge enterprises, learning organisations and smart organisation (Carbo, Molina & Davila, 2003; Aladwani, 2002; Baker, Georgakopoulos, Schuster & Cichocki, 2002; Bradner 2002; CastelFranchi 2002; Merali, 2002; Ricci, Omicini & Denti, 2002; Shumar & Renninger, 2002; Inkpen & Ross, 2001; Burnett 2000; Devine & Filos 2000; Filos & Banaham, 2000; Frenkel, Afsaermanesh, Garita & Hertzberger, 2000; Goranson 2000; Molina & Flores 2000; Mundim & Bremer, 2000; Riempp 1998;). According to Devine & Filos (2000), a virtual organisation is a collection of geographicallydistributed and operating entities that may or may not be culturally diverse and use information and communication technologies supported by lateral and dynamic relationships for coordinated action needs.
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On the other hand, Frenkel et al., (2000), considers that virtual organisations should be seen as a group collaboration of self-governing and existing organisations, who share expertise, skills and resources in order to achieve a common product or service.. Molina & Flores (2000) define virtual organisations as temporary networks of independent organisations connected through information technology who share skills, facilities and business processes with the aim of responding to specific market demand. Finally, Ricci et al., (2002) argue that virtual organisations occur as a response to consumer needs and a temporary assemblage of self-governing and possibly heterogeneous organisations, conceived to provide flexibility and adaptability to the frequent changes that characterise business scenarios. We are therefore before a new organisational format that exceeds the physical boundaries of organisations in a process that includes complex relationships with partners, customers, suppliers and the market (Mowshowitz, 1997). The paradigm of virtual or network organisations assumes the presence of various service providers, operating autonomously and flexibly, though directed in the same direction as a result of a common culture, an information management system. This allows information sharing of crucial business information and an infrastructure in charge of controlling and developing the overall management process of the tourist destination (Martín, 2000; Valles, 1999; McHugh, Merli & Wheeler, 1995; Gummesson, 1994). The main challenges that these types of organisations face involve maintaining the balance between people and culture, maintaining the organisation in tune to processes, information and technology, and finally issues related to leadership in a new organisational structure format. Basic technologies supporting virtual organisations include the Internet and the World Wide Web, telecommunications, electronic mail, groupware
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such as Lotus Notes and video conferencing. It is important to note that understanding the technology is not enough. According to Strausak (1998), there are currently two different approaches of virtual organisations. The first identifies the virtual organisation as a business that relies more heavily on information and communication technology than on physical presence in order to interact and drive their businesses. The attribute “virtual” is used to define an organisational logic, where boundaries of time, geographical space, organisational units and information access are less important, while the use of communication technologies is considered highly useful. (Siebert 2000; Zimmerman, 2000; Kluber, 1998). The second approach considers virtual organisation as a network of independent organisations that possess a temporary characteristic through the use of information and communication technologies, in this way gaining greater competitive advantage. Regardless of the first or second approach, there are several motives that can prompt organisations to opt for a virtual solution. These include the sharing of resources and skills, the need to innovate, to divide risks, the need to reduce costs, market access, agility, better productivity, quality and competitiveness (Lipnack, 1993). Given this, incorporating both approaches need to be considered in order to provide a more consistent and operational concept in practical terms. In fact, both perspectives complement each other and it difficult to separate the two. The virtual organisation reflects both internally, when assuming a new structural form and more importantly when assuming a new form of thinking and positioning in the business world and relationally as with other sector and non sector organisations. The logic behind this process of strategic redirection of organisations has no defined boundaries and, as such, the concept should be assumed in a flexible and wide-ranging manner, interrelating
internal changes to new relational and interacting forms in the surrounding environment. To implement the virtual organisational concept, Les Pang (2001) recognises that there are a set of good practices that should be considered by all those that have a mission to impel organisations towards this new paradigm by: fostering cooperation, trust and empowerment; ensuring that each partner contributes to an identifiable strength or asset; ensuring skills and competences are complementary and not overlapping; ensuring that partners are adaptable; ensuring that contractual agreements are clear and specific on roles and deliverables; not replacing face-to-face interaction entirely, provide training which is critical to team success; recognising that it takes time to develop a team; ensuring that technology is compatible and reliable; and, providing technical assistance that is competent and available. In terms of the virtual organisations concept application to the specific context of tourism, it is argued that the new organisational paradigm be grounded on four fundamental pillars: cooperation, innovation, flexibility and knowledge. The first pillar is represented in terms of inter-organisational networking and in the sharing of resources and know-how. The second is essentially related to promoting creativity between organisations and the search of new solutions for business management problems. The third involves adapting organisations to the surrounding environment and to quick solutions to environmental changes. Lastly, knowledge is a fundamental requirement which upholds the concept of “learning organisation” and what it entails in terms of sharing and free information access. This new organisational structure, which should be undertaken and lead by the Destination Management Organisations, will have as a mission to promote the creation of new value systems and a new culture in the relationship between stakeholders. The restructuring of organisational and architectural models will give rise to the development of new management paradigms
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both at the organisational and tourist destination management levels. A new managerial style is required because of the special issues one must face in an interorganisational environment. As Tapscoot (1995) states, interactive multimedia technologies and the information highway contribute to a new economic order based on human intelligent networks. According to this author, it is possible to foresee the document and paper circuits as well as traditional forms of running businesses. So that the Destination Management Organisation can begin the prepare the future and the transition for these new organisational and management paradigms, it becomes important to rethink its role in terms of considering how actors are influenced, redefining a vision intended for the destination, re-equating aspects of technical and logistic order of cooperation networks, identifying benefits of various technologies that support virtual organisations and lastly, considering new forms of operation in terms of partner relationships and managements and stakeholders in the field of tourist destination. In this context, and considering that the tourism sector essentially comprises small and medium enterprises, it is crucial that tourism destination management directors assume leadership in the process of change and, from the first moment, create a basis for active participation from the majority of stakeholders. Besides following through with mega projects and the involvement of small and medium enterprises in this process, it is important to make entrepreneurs and managers aware of the advantages in knowledge and information sharing based on commitment with new forms of greater and continued cooperation in tourist destinations.
THE COOPERATIVE ENVIRONMENT IN TOURISM DESTINATIONS In a growing scenario of competitiveness and for reasons related to the need to overcome the
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specific difficulties or pursuit of common objectives at the tourist destination level, it has become common practice to create ways to cooperate inter-organisationally in tourist destinations. The “relational” perspective is particularly relevant in the tourism industry, as groupings of organisations cluster together to form a destination context. Bjork and Virtanen (2005) consider that the necessity of well functioning co-operation networks is well articulated in the tourism literature, whether in terms of destination marketing (von Friedrichs Grangsjo, 2002), destination planning (Jamal & Getz, 1995; Ladkin & Betramini, 2002) or development of tourism partnerships (Selin & Chavez 1995). Different forms of inter-organizational relations (e.g., co-ordination, network, collaboration, partnership, cooperation) have started to receive growing attention in recent years from researchers worldwide as a means of finding solutions to resource management and destination development problems (Augustyn & Knowles, 2000; Bramwell & Lane, 2000; Hall, 2000; Selin, 2000; Timothy, 1998; Jamal & Getz, 1995; Selin & Myers, 1995; Benson, 1975). These forms of inter-organisational cooperation in tourist destinations are all the more necessary when there is a clear understanding that objectives can only be fulfilled with the effort and participation of all destination actors and organisations. In this context, the involvement of organisations with partnerships is increasingly greater, going beyond traditional organisational boundaries in order to achieve consumer needs more rapidly (Glendinning, 2003; Austin, 2002, Bradner, 2002; Molina & Flores, 2000; Riempp, 1998). According to Pearce (1989), tourist organisations can better achieve their objectives when they are able to coordinate the activities of the vast participants who contribute towards to composite product and the tourist experience. Watkins and Bell (2002, p.20) believe that “the experience of co-operation was described as stimulating more
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business through working together to share information and engage in joint activities”. Collaboration can be regarded as a process of shared decision-making among key stakeholders regarding future issues. Joint decision-making is important for all those parties having an interest or stake in tourism destinations (Gray, 1985). Usually, what arises from these cooperative projects are cooperation and formal agreements established by the organisations involved and the common objective that justifies and polarises joint efforts. What is equally relevant is to understand the expectations, objectives and benefits that the managers wish to obtain in exchange. Wang & Fesenmaier (2005) identified four broad issues related to collaboration in the area of marketing, which can be adopted for the tourism case: the precondition construct, which delineates the economic, social, and environmental conditions for alliance and network formation; the motivation construct which attempts to explain why organisations choose to enter into strategic alliances and networks to achieve their specific goals; the stage construct which captures the dynamics of collaborative process and the outcome construct which attempts to describe the consequences of collaborative activities. This type of inter-organisational cooperation should rely on some degree of virtuality in order to offer greater ease and response to market changes, stakeholders and unexpected alterations, besides repercussions in the performance of involved organisations, profitability level productivity and quality of rendered services. Actors should recognise and understand that cooperation facilitates the introduction of change, enabling strategic direction for organisations, stimulating and facilitating learning for all, developing business interaction and providing better relationship between actors. It is important, however, not to lose sight that cooperative effort is based on a relationship of interests, costs and expected benefits. It can be assumed then that as a question of principle, the synergy effects that are created as a combination
should reverberate in better organisational performance. This reflects a need to analyse information and monitor systems that support the evaluation process of performance results, whether in terms of organisational networks whether in terms of determining the reciprocal impact established between both levels of decision-making. The development and consolidation of these types of tourist destination networks should begin to by interiorising in the set of actors the need to adopt new management paradigms based on a culture of chain relationships, driven by quality principles and entrepreneurial excellence in the entire region. Given the developing processes, whether in terms of costs or benefits, it is important to comprehend that from the first moment, the advantages to be gained by each participant will be greater if there is an awareness that businesses will continue to compete with one another in line with the less or more advanced cooperative ties established. The climate of cooperation and collaboration between the various actors represents significant importance for a sustained global vision of the tourist product. The development of partnerships, especially between the public and private sector, constitutes one of the more effective formulas for the development of tourist destinations and the exploration of local resources, as well as the key for destinations to offer quality products (Buhalis, 2000; Leoni, 1999; Manente & Furlan, 1998; Ritchie & Crouch, 1997; Wanhill, 1995). Participation and engagement in a tourism network relies on favourable behavioural disposition influenced by the individual participant’s attitude and, more specifically, his or her values. From an integrated management perspective, what is sought is a balanced development of behaviour, attitude, equipment and other facilities to satisfy consumer and stakeholder requirements in the service sector. Increasingly, tourist destination competitiveness and the image of countries and regions, that represent tourist destinations and providers of quality service, depend essentially
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on the creative capacity of people, introduction of new technologies, the use of new processes and new organisational forms (Gibson, Lynch & Morrison, 2005; Sancho, 1993). According to Yuksel and Yuksel (2005), factors critical for the success of inter-organizational relations which include recognising a high degree of interdependence in the planning and managing of the domain/project; recognising individual and/or mutual benefits to be derived from the collaborative process; understanding that decisions arrived at will be implemented; including key stakeholder groups; appointing legitimate convenors to initiate and facilitate community-based collaboration; and, formulating aims and objectives. Some of these key tasks of Destination Management Organisations are related with the need to conciliate diverging interests of the different actor, with balance and satisfaction of the relevant needs of stakeholders (industry professionals, clients, suppliers and society in general), with the adoption of strategies that incorporate ethical principles based on sustainability and regional development (Silva et al., 2001; Davidson & Maitland, 1997; O’Neill, Watson & Mckenna, 1994). In order to achieve these objectives, it is strategically important that organizations and leaders possess the necessary skills to motivate and involve all those interested in an integrated vision of destination and common projects that result from a social contract allowing for a coordinated, responsible and beneficial performance for all (Laszlo, 1999). There are several major types of environmental forces that lead to interaction among potential partners. Some of the reasons more frequently referred to in the literature as reasons for the construction and development of networks in tourism are: crises – which direct energies of potential partners towards a specific problem (Croitts & Wilson, 1995; Fosler & Berger, 1982); existing networks which introduce members of a potential partnership to each other (Fyall & Garrod, 2004); visionary leadership - which is embodied in an
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individual as opposed to a group (Fyall, Callod & Edwards, 2003; Gray, 1985); economic and technological change in which individual organizations are not able to compete successfully by acting alone (Wahab & Cooper, 2001; Poon, 1993) and finally the existence of a third party convener, providing a forum or opportunity for interaction (Hall, 1999).
DEVELOPMENT OF INTERORGANISATIONAL NETWORKS IN TOURISM DESTINATIONS As World Tourism Organisation recognised in the 2000 report, two key forces, globalisation and technology, are transforming the tourism sector into a dynamic economic force that has never been possible before. New forms of organisations arise in different cultural contexts, adapting to the new information era and witnessing a point of historical discontinuity (Castells, 1996). Due to the need of exceeding specific difficulties or proceeding with common objectives at the destination level, the creation of public-private partnerships has become a common practice. This fact has been widely recognized by the tourism literature, which emphasises the substantial importance of networks and partnership for tourism sector (Costa, 1996). In spite of the popularity of partnerships, few empirical investigations have been done in order to explain the processes occurred whenever these interactions are implemented (Selin & Chavez, 1995). The need for the cooperation at a destination is inevitable, given the recognised importance of the cooperation networks integrated in the analysis of the production systems of goods and services. However, and according to Framke (2001), only in marketing-driven organisations has cooperation reached its meaning. Also, according to this author, the cooperation theme at the tourism level has not been properly investigated, mainly where
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its meaning is concerned and the importance of the relationship between tourism enterprises. According to Easton (1992), a network can be defined generically as a model or metaphor which describes a generally high number of linked entities. Van de Ven and Ferry (1980) regards a network as a complete pattern of relationships between organisations that act with a view towards common objectives. Networks can be observed as a set of ties and social relationships that unite organizations (Lundgren, 1995), as a specific type of relation linking a set of persons, objects or events (Knoke & Kuklinski, 1983) or a set of actors that control resources and perform activities (Hakansson & Snehota, 1995; Hakansson & Johanson, 1992). The Scottish-Scandinavian Discussion Group (2001), referred to in Gibson, Lynch, and Morrison (2005) regard a network as belonging to a set relationships between individuals acting in an organisational and/or private capacity to achieve a particular purpose. Such networks may be of three types: formal – a formalised set of actors who interact in the context of identified aims; semi-formal – a formalised set of actors who interact in the context of identified aims, and informal – a set of actors who meet mainly for social purposes but also exchange information which has instrumental (business) value. In essence, the tourism virtual networks are characterised by a variety of participants that transcend organisational boundaries and structures (Mars, 1998; Rhodes, 1997; Howlett and Ramesh, 1995) and are recognised as stimulators of interorganizational coordination of policies (Selin & Myers, 1998; Costa, 1996). Dredge (2006, p 269), believes that “networks operate within and around tourism’s formal organisations, between industry actors, different government agencies and civil society to provide an important forum for the development and communication of interests and strategies.”
“A networking organisation appears as a form of inter-entrepreneurial organisation able to overcome some of the inherent market and hierarchical restrictions, whether from the point of view of reduced transaction costs, whether from the decrease of diseconomies of scale, though, more importantly as another form of inter-entrepreneurial relationship with individual virtues that surpass these benefits and belong to domains that are nowadays essential: innovation, learning and knowledge.” (Corvelo et al., 2001, p 76.) Network theory assumes that “relationships do not occur within a vacuum of dyadic ties, but rather in a network of influences, where a firm’s stakeholders are likely to have direct relationship with one another” (Rowley, 1997, p. 980) and, nowadays, plays a critical role in determining the way planning and management solutions are designed (Miguéns e Costa, 2006). The need to learn, in order to generate greater differentiated value, becomes in reality one of the crucial issues of the competing system. In this sense, and as recognised by Corvelo et al. (2001, p. 78), “networking, through the arrangement and type of commitment between actors, there is a more favourable environment in terms of satisfaction of needs since no imposed obstacles are encountered from hierarchical rigidness, nor sporadic or more distant market relationships.” Corvelo et al. (2001, p. 78) assert yet that, “in fact networking works as a last measure, as a privileged system of creation and exploration of value because this is constructed and generated as a “constellation” in the sense that economies of scale are not only considered together with the supply of production variety, but as greater customisation, given the set of distinctive skills from markets which and unattainable through individual network actors, act so as a group and in a synergetic manner.” The impacts that tourism provokes in the environmental, cultural and societal systems require that the construction and the development of networks be developed through holistic approaches,
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framed in wider and multidimensional contexts, where besides business profitability and purely economic visions be considered aspects of social responsibility of all involved parties. According to Helgensen (1995), the organisational architecture in the form of a network is recommended based on the following reasons: (1) the context in which firms currently operate is characterised by a high level of change, in the face of growing innovation and complexity; (2) the assertion of globalisation from markets and original technology to worldwide distribution of value and wealth; (3) the needs of specialising in skills and focusing on the specific links in the value chain; (4) the shortening of the life cycle of products and technologies; (5) the need to place products in the market, more speedily, less costly and of higher quality; (6) the increase in cost and risk, associated to the development of new products. The performance of the tourist destination is maximised when based on the sharing of knowledge and a culture of continued learning and innovation. Maximising information flows for all those involved is essential in order to consolidate the learning process of involved actors. As such, “networks are best seen as primarily a cultural phenomena, that is, as sets of meanings, norms and expectations usually linked with behavioural correlates of various kinds“(Curran, Jarvis, Blackburn & Black, 1993). In this context, setting up partnerships, especially between the public and private sectors, constitute one of the more efficient formulas for the development of tourist locations and the exploration of local resources, as well as the key for destinations to offer quality products (Buhalis, 2000; Leoni, 1999; Manente & Furlan, 1998; Ritchie & Crouch, 1997; Wanhill, 1995). Another possible form of prompting and institutionalizing cooperation between the actors in tourist destinations would be through the creation of “holonic networks”. The concept, introduced by McHugh et al. (1995), looks to bring a new form of being and response from organizations
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based on establishing communication platforms, the exchange of information and efficient response to market needs. This new operational concept in the service chain is based on a process of business reengineering, centred on customer satisfaction and the success of organizations in a competitive environment, has been applied successfully in the tourism destination context and meets the needs of cooperation between actors organizations and other regional entities. The concern with customers is the focal point of the holonic system. Holonic organisational networks share common objectives, and uses total quality as well as other management techniques so that all participants work towards greater level of customer satisfaction (McHugh et al., 1995). The holonic network can be described as a group of organizations that act in an integrated form and are organically linked. The following characteristics of the network include: (1) the network not organizationally hierarchical, (2) each business or holon containing whole network characteristics and identical to others, (3) being dynamically balanced, (4) auto-regulated, (5) open access and exchange of information, (6) an evolutionary network in constant interaction with the environment, and (7) a knowledge network and auto-learning. Each organisation, with its specific set of skills, is referred to as a holon. For the tourism case and through a set of competences, the network assumes a specific arrangement, known as virtual organisation whose purpose is to manage each business opportunity observed in the market and in this way contribute to better performance and service of each organisation of the tourist destination. As already mentioned, the fundamental concept associated to a network of information sharing is the creation of a network of contacts between the different parties for the sharing of knowledge, experience and practice, and information dissemination (electronic or personal) in order to improve competitiveness, sustainability and quality of activities and products. Finally, information
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sharing networks in tourist destinations can: (1) promote and develop an interactive dynamic system in constant evolution between agents, public or private, involved in the tourist sector, (2) help the different actor to plan and manage activities in a coordinated and efficient manner, (3) develop benchmarking systems, (4) promote cooperation and development of partnerships between actors, (5) develop good practices and lines of action for integrated quality management, and (6) to offer support and manage information sharing with other institutions. The cooperation lays in a relationship between expected interests, costs and benefits, and synergism should reflect on the best performance of organisations. This thought leads to the need of analysing the information and monitoring systems which will support the evaluation process of the expected performance results, in terms of the partnership and organisations as well as in terms of the study of mutual impacts established between both decision levels. Different organisations, with different organisational cultures will inherently have different views on how a network should be managed and developed (Allen, Colligan & Finnie, 1999).
CONCLUSION From the literature review we can infer that the constitution of information and knowledge networks should be seen as a strategic issue for the greater part of public and private organisations. The tourism sector is no exception and the development of ways of virtual cooperation in the tourism destinations, no doubt constitutes a challenge to overcome. In effect, without this kind of interaction and commitment structures between the organisations in a specific tourism region, it becomes hard for a Destination Management Organisation to, efficiently, manage the value chain and take re-
sponsibility in terms of the tourism destination’s global performance On the other hand, it is noted that the virtual networks’ characteristics are perfectly adequate for the structure that the Destination Management Organisations must develop with the remaining stakeholders in order to ensure the fulfilment of goals and the competitive positioning facing other competitors. Tourism destinations currently face challenges and problems that require quick decision making and a collective effort to adapt to a constantly changing reality. Times are changing, whether in terms of organisational arrangement and new attitudes in the relationship of actors in tourist destinations, whether in terms of vision and pursuits by destination management organisations. The development of processes for continued improvement of global performance and competitiveness of tourist destination, aims above all to redirect tourist activity to adopt new management paradigms based on a culture of network relations guided by principles of sustainability, quality and entrepreneurial excellence. The cooperation and collaborative environment between actors is of crucial importance in order to achieve a sustained global vision of the tourist product. This chapter presents an overview of research concerned with destination competitiveness, the concept of virtual organisations, cooperative environments, new organisational and management paradigms and the development of interorganisational cooperation networks. Based on a theoretical framework the chapter contributes to enlighten the applicableness of the virtual networks concept in a tourism destination context. All the while, it highlights the need and the opportunity the Destination Management Organisations have to assimilates and implement this kind of structures and strategies leading to a news organisational and management paradigms. It must be admitted that the chapter has the limitations inherent to a reflection developed only around the theoretical knowledge on the subject.
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Furthermore, the chapter doesn’t consider the specificities that characterize and differentiate the coastal tourism destinations from the urban and rural ones. The entrepreneurial fabric that supports each of these kinds of tourism destinations is substantially different; witch may imply different formats of partnerships to be established between stakeholders. In terms of future research, several possibilities must be considered. First of all, it is important to reinforce the theoretical knowledge framework on the cooperation between public and private organisations of the tourism sector, as much as the research on costs, benefits, expectations and the other aspects of the virtual partnerships from management process in the tourism destinations. The paper also stimulates the development of empirical research in different kinds of tourism destinations, promoting comparison between formats, methodologies, good practices and results of the implementation of virtual networks between organisations in a cooperative environment of tourism destinations.
REFERENCES Aladwani, A. M. (2002). An empirical examination of the role of social integration in sytem development projects. Information Systems Journal, 12(4), 339–353. doi:10.1046/j.1365-2575.2002.00133.x Albrecht, K., & Zemke, R. (2002). Serviço ao Cliente – A Reinvenção da Gestão do Atendimento ao Cliente, Rio de Janeiro, Editora Campus. Allen, D., Colligan, D., & Finnie, A. (1999). Trust, power and inter-organizational information systems: The case of the electronic trading community translease. The 7th European Conference on Information Systems (pp. 834-849). Copenhagen, Denmark: Copenhagen Business School.
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Augustyn, M. M., & Knowles, T. (2000). Performance of tourism partnerships: A focus on York. Tourism Management, 21, 341–351. doi:10.1016/ S0261-5177(99)00068-0 Austin, J. E. (2002). Meeting the Collaboration Challenge Workbook: Developing Strategic Alliances Between Nonprofit Organizations and Businesses. New York: Peter F. Drucker Foundation for Nonprofit Management. Bacharach, S., & Lawler, K. (1980). Power and politics and organizations. San Francisco: Jossey-Bass. Baker, D., Georgakopoulos, D., Schuster, H., & Cichocki, A. (2002). Awareness provisioning in collaboration management. International Journal of Cooperative Information Systems, 11(1-2), 145–173. doi:10.1142/S0218843002000522 Baker, W. E. (1992). The network organization in theory and practice. In Nohria, N. and R. Eccles (Eds.), Networks and Organizations. (pp 397-429). Boston, MA: Harvard Business School Press. Beerli, A., & Martin, J. D. (2004). Tourists’characteristics and the perceived image of tourist destinations: a quantitative analysis – a case study of Lanzarote, Spain. Tourism Management, 25(5), 623–636. doi:10.1016/j. tourman.2003.06.004 Benson, J. K. (1975). The inter-organizational network as a political economy. Administrative Science Quarterly, 20(2), 229–249. doi:10.2307/2391696 Beyerlein, M., Johnson, D., & Beyerlein, S. (1994). Theories of self-managing work teams (Advances in Interdisciplinary Studies of Work Teams). Stamford, CT: JAI Press.
The Development of Knowledge and Information Networks in Tourism Destinations
Bjork, P., & Virtanen, H. (2005). What Tourism Project Managers Need to Know about Co-operation Facilitators. Scandinavian Journal of Hospitality and Tourism, 5(3), 212–230. doi:10.1080/15022250510014354 Bordas, E. (1994). La Calidad de los Servicios Turísticos: De la Teoria a la Prática, WTO Seminar on “Quality - A Challenge for Tourism” (pp. 133-159). Madrid: World Tourism Organization. Bouncken, R. B. (2000). The Effect of Trust on Quality in the Culturally Diverse Tourism Industry. Journal of Quality Assurance in Hospitality & Tourism, 1(3), 85–104. doi:10.1300/ J162v01n03_05 Bradner, E. (2002). Computer mediated communication among teams: what are “teams” and how are they “virtual”? In C. & D. FISHER (Eds). From UseNet to CoWebs: interacting with social information spaces (pp. 135-152). London: Springer-Verlag. Bramwell, B., & Lane, B. (2000). Collaboration and partnership in tourism planning. In B. Bramwell, & B. Lane (Eds.), Tourism collaboration and partnerships: Politics, practice and sustainability (pp. 143-158). Clevedon, Uk: Channel View Publications. Brathwaite, R. (1992). Value-Chain Assessment of the Travel Experience. The Cornell Hotel and Restaurant Administration Quarterly, 33(5), 41–49. Buckley, P. J. (1987). Tourism - an economic transactions analysis. Tourism Management, 8(3), 190–194. doi:10.1016/0261-5177(87)90050-1 Buhalis, D. (2000). Marketing the competitive destination of the future. Tourism Management, 21(1), 97–116. doi:10.1016/S0261-5177(99)00095-3 Burnett, G. (2000). Information exchange in virtual communities: a typology. Information Research, 5(4).
Butler, R. (1980). The concept of a tourist area cycle of evolution: implications for management of resources. Canadian Geographer, 24(1), 5–12. doi:10.1111/j.1541-0064.1980.tb00970.x Camillus, J. (1993). Crafting the competitive corporation: Management systems for the future organizations. In P. Lorange, B. Chakravarthy, J. Roos, & A. Van De Ven (Eds), Implementing strategic process: Change, learning, and cooperation (pp. 313-328). Oxford, Uk: Blackwell. Carbo, J., Molina, J. M., & Davila, J. (2003). Trust management through fuzzy reputation. International Journal of Cooperative Information Systems, 12(1), 135–155. doi:10.1142/ S0218843003000681 CastelFranchi, C. (2002). The social nature of information and the role of trust. International Journal of Cooperative Information Systems, 11(3-4), 381–403. Castells, M. (1996). The Information Age: Economy, Society, and Culture. Volume I: The Roise of the Network Society. Oxford: Blackwell Commission Européenne. (1999). Pour un tourisme urbain de qualité – La gestion integrée de la qualité (GIQ) des destinations touristiques urbaines. Bruxelles: Commission Européenne. Corvelo, S., Moreira, P. S., & Carvalho, P. S. (2001). Redes Interorganizacionais. Lisboa: Inofor. Costa, C. (1996). Towards the Improvement of the Efficiency and Effectiveness of Tourism Planning and Development at the Regional Level – Planning and Networks. The case of Portugal. Unpublished doctoral dissertation, University of Surrey, Guildford. Croitts, J. C., & Wilson, D. (1995). An integrated model of buyer-seller relationship in the international travel trade. Progress in Tourism and Hospitality Research, 1(2), 125–140.
461
The Development of Knowledge and Information Networks in Tourism Destinations
Curran, J., Jarvis, R., Blackburn, R., & Black, S. (1993). Networks and small firms: constructs, methodological strategies and some findings. International Small Business Journal, 11(2), 13–25. doi:10.1177/026624269301100202 Davidson, R., & Maitland, R. (1997). Tourism Destinations. London: Hodder & Stoughton Educational. Denmann, R. (1998). Integrated quality management of rural tourist destinations. Paper presented at the European Tourism Forum of the Austrian Presidency of the Council of the European Union and the European Commission, Mayrhofen. Devine, M., & Filos, E. (2000). Erastos. Virtual teams and the organisational gravepine. In Kluwer Academic Publishers (Ed.), International Federation for Information Processing; Working Conference on Infrastructures for Virtual Organisations, Florianopolis. Dredge, D. (2006). Policy networks and the local organisation of tourism. Tourism Management, 27(2), 269–280. doi:10.1016/j.tourman.2004.10.003 Easton, G. (1992). Industrial Networks: A Review. In B. Axelsson & G. Easton (Eds.), Industrial Networks: A new View of Reality, London: Routledge.
Fosler, R., & Berger, R. (1982). Public-private sector partnership in American cities: Seven case studies. Lexington: Heath. Framke, W. (2001). The Destination: a problematic concept. IPaper presented at the 10th Nordic Tourism Research Conference, Vasa, Finland. Frenkel, A., Afsarmanesh, H., Garita, C., & Hertzberger, L. (2000). Supporting information access rights and visibility levels in virtual enterprises. In Kluwer Academic Publishers (Ed.), International Federation for Information Processing; Working Conference on Infrastructures for Virtual Organisations, Florianopolis. Frochot, I., & Hughes, H. (2000). Histoqual: the development of a historic houses assessment scale. Tourism Management, 21(2), 157–167. doi:10.1016/S0261-5177(99)00045-X Fyall, A., Callod, C., & Edwards, B. (2003). Relationship marketing: The challenge for Destinations. Annals of Tourism Research, 30(3), 644–659. doi:10.1016/S0160-7383(03)00046-X Fyall, A., & Garrod, B. (2004). Tourism marketing: A collaborative approach. Cleveland: Channel View Publications.
EFQM. (1999). Eight Essentials of Excellence, Brussels: European Foundation for Quality Management.
Gibson, L., Lynch, P. A., & Morrison, A. (2005). The Local Destination Tourism Network: Development Issues. Tourism and Hospitality Planning & Development, 2(2), 87–99. doi:10.1080/14790530500171708
Fayos-Solá, E., & Moro, J. R. (1995). Calidad Ecoturística para el Desarrollo Sostenible, Conferencia Mundial de Turismo Sostenible (pp. 33-42). Islas Canarias.
Glendinning, C. (2003). Breaking down barriers: integrating health and care services for older people in England. Health Policy (Amsterdam), 65(2), 139–151. doi:10.1016/S0168-8510(02)00205-1
Filos, E., & Banahan, E. (2000). Will the organization disappear? The challenges of the new economy and future perspectives. In Kluwer Academic Publishers (Eds.), International Federation for Information Processing; Working Conference on Infrastructures for Virtual Organisations, Florianopolis.
Goldman, S., Nagel, R., & Preiss, K. (1995). Agile competitors and virtual organizations: Strategies for enriching the customer. New York: Van Nostrand Reinnhold.
462
The Development of Knowledge and Information Networks in Tourism Destinations
Goranson, H. T. (2000). Infrastructure for the advanced virtual enterprise: a report using a Brasilian-based example. In Kluwer Academic Publishers (Ed.), International Federation for Information Processing; Working Conference on Infrastructures for Virtual Organisations, Florianopolis. Gray, B. (1985). Conditions facilitating interorganizational relations. Human Relations, 38(10), 911–936. doi:10.1177/001872678503801001 Guibilato, G. (1983). Economie Touristique, Suisse: Delta & Spes. Gummesson, E. (1994). Service Management: An Evaluation and the Future. International Journal of Service Industry Management, 5(1), 77–96. doi:10.1108/09564239410051920 Gunn, C. (1993). Tourism Planning. London: Taylor & Francis. Hakansson, H., & Johanson, J. (1992). A model of industrial networks. In B. Axelsson & G. Easton (Eds.) Industrial Networks: A New View of Reality, (pp. 28-34), London: Routledge. Hakansson, H., & Snehota, I. (1989). No business is an island: The network concept of business strategy. Scandinavian Journal of Management, 5(3), 187–200. doi:10.1016/0956-5221(89)90026-2 Hall, C. M. (1999). Rethinking collaboration and partnership: A public policy perspective. Journal of Sustainable Tourism, 7(3/4), 274–289. doi:10.1080/09669589908667340 Hall, C. M. (2000). Rethinking collaboration and partnership: A public policy perspective. In B. Bramwell, & B. Lane (Eds.), Tourism collaboration and partnerships: Politics, practice and sustainability (pp. 143-158). Clevedon, Uk: Channel View Publications. Haywood, K. M. (1993). The Price-Value Relationship: Perspective and Definitional Issues. World Travel and Tourism Review, 3, 213–217.
Helgensen, S. (1995). The Web of Inclusion: Building an Organization for Everyone. Currency Doubleday. Hope, C. A., & Muhlemann, A. P. (1998). Total quality, human resource management and tourism. Tourism Economics, 4(4), 367–386. Howlet, M., & Ramesh, M. (1995). Studying public policy: policy cycles and policy subsystems. Toronto: Oxford University Press. Huete, L. M. (1994). Factores que infuyen en la calidad del producto, In World Tourism Organization (Ed.), WTO Seminar on Quality - A Challenge for Tourism (pp. 53-55). Madrid. Inkpen, A., & Ross, J. (2001). Why do some strategic alliances persist beyond their useful life? California Management Review, 44(1), 132–148. Jamal, T., & Getz, D. (1995). Collaboration theory and community tourism planning. Annals of Tourism Research, 22(1), 186–204. doi:10.1016/01607383(94)00067-3 Kandampully, J. (2000). The impact of demand fluctuation on the quality of service: a tourism industry example. Managing Service Quality, 10(1), 10–18. doi:10.1108/09604520010307012 Klein, R. (2000). EU activities to improve the quality of European tourist products, In Workshop on Quality in Tourism: from Patterns to indicators. Faro: Universidade do Algarve. Kluber, R. A. (1998).A framework for virtual organizing. In Sieber, P. & Griese J. (Eds), Organizational Virtualness. Proceedings of the VoNet – Workshop (pp. 9-24). Bern: Simona Verlag Bern. Knoke, D., & Kuklinski, J. (1983). Network Analysis.Beverly Hills: Sage. Krackhard, D., & Hanson, J. (1993). Informal networks: The company behind the chart. Harvard Business Review, 71(4), 104–111.
463
The Development of Knowledge and Information Networks in Tourism Destinations
Ladkin, A., & Bertramini, A. M. (2002). Collaborative tourism planning: Case study of Cusco, Peru. Current Issues in Tourism, 5(2), 71–93. doi:10.1080/13683500208667909 Laws, E. (1995). Tourism Destination Management: Issues, Analysis and Policies. London: Routledge. Lazlo, G. P. (1999). Implementing a quality management program- three Cs of success: commitment, culture, cost. The TQM Magazine, 11(4), 231–237. doi:10.1108/09544789910272896 Leoni, P. (1999). La città ospitale, Paper presented at the International Conference “From Destination to Destination Marketing and Management”, Venice. Les Pang (2001). Understanding Virtual Organizations. Information Systems Control Journal, 6. Lévy, P. (1996). O que é o virtual, São Paulo: Editora 34. Lipnack, J. S. (1993). Rede de Informações. Rio de Janeiro: Makron Brooks. Lundgren, A. (1995). Technological Innovation and Network Evolution. London: Routledge. Lutz, J., & Ryan, C. (1993). Hotels and the businesswoman - An analysis of businesswomen’s perceptions of hotel services. Tourism Management, 14(5), 349–356. doi:10.1016/02615177(93)90003-4 Manente, M., & Furlan, M. (1998). Quality in the Macroeconomics System of Tourism. Revue de Tourisme, 2, 17–28. doi:10.1108/eb058272 Mars, D. (1998). Comparing policy networks. Buckinghan: Open University Press.
464
Martín, D. (2000). Metodología de Calidad en Turismo, in Turismo: comercialización de productos, gestión de organizaciones, aeropuertos y protección de la naturaleza. In Tirant lo Blanch (Ed.), II Congreso Universidad y Empresa, Turismo: comercialización de productos, gestión de organizaciones, aeropuertos y protección de la naturaleza (pp. 429-447), Benicasim. McHugh, P., Merli, G., & Wheeler, W., III. (1995). Beyond business process reengineering – Towards the Holonic Entreprise. Chichester: John Wiley & Sons. Merali, Y. (2002). The role of boundaries in knowledge process. European Journal of Information Systems, 11(1), 47–60. doi:10.1057/palgrave/ ejis/3000413 Michaud, J.-L., Planque, V., & Barbaza, Y. (1991). Tourisme qualitatif - Ses Conditions et ses Chances Futures sur le Plan Economique, Social et Ecologique. In AIEST (Ed.), 41ème Congrès de l’Association International d’Experts Scientifiques du Tourisme (pp. 63-78), Mahé, Seychelles. Middleton, V. T. (1994). The marketing and Management of Tourism destinations: research directions for the next decade, In AIEST (Ed.) 44ème Congrès de l’Association International d’Experts Scientifiques du Tourisme (pp. 115141), Vienne, Austria. Miguéns, J., & Costa, C. (2006). Tourism Network: New methodologies, potential approach to tourism analysis. In School of Management, University of Surrey (Ed.), Proceedings of Cutting Edge Research in Tourism: New directions, Challenges and Applications. School of Management, University of Surrey, UK. Mills, D. (1991). Rebirth of the corporation. New York: John Wiley and Sons, Inc.
The Development of Knowledge and Information Networks in Tourism Destinations
Molina, A., & Flores, M. (2000). Exploitation of business opportunities: the role of the virtual enterprise broker. In Kluwer Academic Publishers (Ed.), International Federation for Information Processing; Working Conference on Infrastructures for Virtual Organisations, Florianopolis. Mowshowitz, A. (1997). Virtual organization. Communications of the ACM, 40(9), 30–37. doi:10.1145/260750.260759 Mundim, A. P., & Bremer, C. F. (2000). Design of a computer-supported cooperative environment for small and medium enterprises. In Kluwer Academic Publishers (Ed.), International Federation for Information Processing; Working Conference on Infrastructures for Virtual Organisations, Florianopolis. O’Neill, M., Watson, H., & Mckenna, M. (1994). Service quality in the Northern Ireland Hospitality Industry. Managing Service Quality, 4(3), 36–40. doi:10.1108/09604529410057765 Otto, J. E., & Ritchie, J. R. (1995). Exploring the Quality of the Service Experience: A Theoretical and Empirical Analysis. Advances in Services Marketing and Management, 4, 37–61. doi:10.1016/S1067-5671(95)04018-8 Otto, J. E., & Ritchie, J. R. (1996). The service experience in tourism. Tourism Management, 17(3), 165–174. doi:10.1016/0261-5177(96)00003-9 Papadopoulos, S. I. (1989). Greek marketing strategies in the European tourism market. The Service Industries Journal, 9(2), 297–314. doi:10.1080/02642068900000030 Pavlovich, K. (2003). The evolution and transformation of a tourism destination network: the Waitomo Caves, New Zealand. Tourism Management, 24(2), 203–216. doi:10.1016/S02615177(02)00056-0 Pearce, D. (1989). Tourism development. New York: Longman.
Pine, B. J., II, & Gilmore, J. H. (1999). The experience economy – Work is theatre & every business a stage. Boston: Harvard Business School Press. Pizam, A. (1991). The management of quality tourism destinations. In AIEST (Ed.) 41ème Congrès de l’Association International d’Experts Scientifiques du Tourisme (pp. 79-87), Mahé, Seychelles. Pizam, A., Neumann, Y., & Reichel, A. (1978). Dimensions of tourist satisfaction with a destination area. Annals of Tourism Research, 5(3), 314–322. doi:10.1016/0160-7383(78)90115-9 Poon, A. (1993). Tourism, technology and competitive strategies. UK: Cab International. Rhodes, R. A. (1997). Understanding governance: policy networks, governance, reflexitivity and accountability. Buckingham, UK: Open University Press. Ricci, A., Omicini, A., & Denti, E. (2002). Virtual enterprises and workflow management as agent coordination issues. International Journal of Cooperative Information Systems, 11(3-4), 355–379. doi:10.1142/S0218843002000637 Ridley, S. (1995). Towards a new business culture for tourism and hospitality organizations. International Journal of Contemporary Hospitality Management, 7(7), 36–43. doi:10.1108/09596119510101912 Riempp, G. (1998). Wide area workflow management: creating partnerships for the 21st century. London: Springuer-Verlag London. Rita, P. (1995). O Turismo em Perspectiva: Caracterização e Tendências do Mercado Internacional. Revista Portuguesa de Gestão, II(III), 7–18. Ritchie, J. R. B., & Crouch, G. I. (1997). Roles and contributions to destination competitiveness, In AIEST (Ed.), 47th Congress of the Association International d’Experts Scientifiques du Tourisme (pp. 117-139), Cha-Am, Thailand.
465
The Development of Knowledge and Information Networks in Tourism Destinations
Ritchie, J. R. B., & Crouch, G. I. (2000). The competitive destination: a sustainability perspective. Tourism Management, 21(1), 1–7. doi:10.1016/ S0261-5177(99)00093-X Rowley, T. J. (1997). Moving beyond dyadics ties: a network theory of stakeholder influences. Academy of Management Review, 22(4), 887–910. doi:10.2307/259248 Ryan, C. (1995). Learning about tourists from conversations: the over - 55s in Majorca. Tourism Management, 16(3), 207–215. doi:10.1016/02615177(95)00005-9 Sancho, A. (1993). Calidad Y Educación: Un reto para el Sector Turístico. Estudios Turísticos, 119/120, 23–28. Schmoll, G. (1977). Tourism Promotion. Marketing Background, Promotion Techniques and Promotion Planning Methods. London: Tourism International Press Schultze, U., & Boland, R. J. (2000). Place, space and knowledge work: a study of outsourced computer systems administrators. Accounting Management and Information Technologies, 10(3), 187–219. doi:10.1016/S0959-8022(00)00006-0 Selin, S. (2000). Developing a typology of sustainable tourism partnerships. In B. Bramwell, & B. Lane (Eds.), Tourism collaboration and partnerships: Politics, practice and sustainability (pp. 143-158). Clevedon, Uk: Channel View Publications. Selin, S., & Chavez, D. (1995). Developing an evolutionary tourism partnership model. Annals of Tourism Research, 22(4), 844–856. doi:10.1016/0160-7383(95)00017-X Selin, S., & Myers, N. (1995). Correlates of partnership effectiveness: the coalition for unified recreation in the Eastern Sierra. Journal of Recreation Administration, Winter, 13(4), 37-46.
466
Selin, S., & Myers, N. (1998). Tourism marketing alliances: member satisfaction and effectiveness attributes of a regional initiative. Journal of Travel and Tourism Research, 7, 79–94. doi:10.1300/ J073v07n03_05 Shumar, W., & Renninger, K. A. (2002). On conceptualizing community. In K. Renninger & W. Shumar (Ed.) Building virtual communities: learning and change in cyberspace. Cambridge: Cambridge University Press. Siebert, P. (2000). Virtual organizations: static and dynamic viewpoints. VoNet: The Newsletter. Silva, J. A. (1991). O Turismo em Portugal – Uma Análise de Integração Micro-Macroecómica, Unpublished doctoral dissertation, Universidade Técnica de Lisboa, Lisboa, Portugal. Silva, J. A., Mendes, J., & Guerreiro, M. M. (2001). A Qualidade dos Destinos Turísticos: dos Modelos aos Indicadores. Revista Portuguesa de Gestão, III(1), 65–81. Smith, S. L. (1994). The tourism product. Annals of Tourism Research, 21(3), 582–595. doi:10.1016/0160-7383(94)90121-X Stauss, B., & Weinlich, B. (1997). Processoriented measurement of service quality. European Journal of Marketing, 31(1), 33–55. doi:10.1108/03090569710157025 Strausak, N. (1998). Resumée of Vo Talk. In Sieber, P & Griese J. (Eds). Organizational virtualness. Proceedings of the VoNet – Workshop (pp. 9-24), Simona Verlag Bern. Tapscoot, D. &. Caston, A. (1993). Paradigm shift. McGraw-Hill. Tapscoot, D. (1995). The digital economy. Richard D. Irwin.
The Development of Knowledge and Information Networks in Tourism Destinations
Timothy, D. J. (1998). Co-operative tourism planning in a developing destination. Journal of Sustainable Tourism, 6(1), 52–68. doi:10.1080/09669589808667301 Tinsley, R., & Lynch, P. (2001). Small tourism business networks and destination development. International Journal of Hospitality Management, 20(4), 367–378. doi:10.1016/S02784319(01)00024-X Toledo, L. A., & Loures, C. A. (2006). Organizações Virtuais. Cadernos EBAPE. BR. IV(2), 1-17. Valles, D. M. (1999). Calidad en los Servicio. Una aproximación metodológica. Estudios Turísticos, 139, 15–33. Van de Ven, A. H., & Ferry, D. L. (1980). Measuring and assessing organizations. New York, John Wiley. Vega, A. V. R., Casielles, R. V., & Martín, A. M. D. (1995). La Calidad Percibida Del Servicio en Establecimientos Hoteleros de Turismo Rural. Papers de Turisme, 19, 17–33. Von Friedrichs Grangsjo, Y. (2002). Marketing equilibrium in entrepreneurial cluster: An idea of a dynamic relationship between co-operation, competition and institutions. Paper presented at the 11th Nordic Symposium in Tourism and Hospitality Research, Goteborg, Sweden. Wabad, S., & Cooper, C. (2001). Tourism in the age of globalization. London: Routledge. Wang, Y., & Fesenmaier, D. (2005). Towards a theoretical framework of collaborative destination marketing. In Proceeding of the 36th travel and tourism research association annual conference. New Orleans, USA.
Wanhill, S. (1995). Some fundamentals of destination development. Revista Portuguesa de Gestão, II(III), 19–33. Watkins, M., & Bell, B. (2002). The experience of forming business relationships in tourism. International Journal of Tourism Research, 4(1), 15–28. doi:10.1002/jtr.337 Weiermair, K. (1994) Quality management in tourism: Lessons from the service industries? In AIEST (Ed.) 44éme Congrès de l’Association International d’Experts Scientifiques du Tourisme (pp. 93-113), Vienne, Austria. Weiermair, K. (2000a). Tourist’s perceptions towards and satisfaction with service quality in the cross-cultural service encounter: implications for hospitality and tourism management. Managing Service Quality, 10(6), 397–409. doi:10.1108/09604520010351220 Weiermair, K. (2000b) Quality Assessment and Measurement in Tourism: Issues and Problems, Paper presented at the Workshop Quality in Tourism: from Patterns to Indicators, Universidade do Algarve, Faro, Portugal. WTO. (2000). Global Tourism Forescast to the Year 2000 and Beyond╯: The World, WTO, Madrid. Yuksel, A., & Yuksel, F. (2005). Managing relations in a learning model for bringing destinations in need of assistance into contact with good practice. Tourism Management, 26(5), 667–679. doi:10.1016/j.tourman.2004.03.016 Zimmermman, F. (2000). Structural and managerial aspects of virtual entreprises. University of Bamberg, Business Information Systems, Germany.
This work was previously published in Connectivity and Knowledge Management in Virtual Organizations: Networking and Developing Interactive Communications, edited by Cesar Camison, Daniel Palacios, Fernando Garrigos and Carlos Devece, pp. 183-204, copyright 2009 by Information Science Reference (an imprint of IGI Global).
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Designing Digital Marketplaces for Competitive Advantage Dinesh Rathi University of Alberta, Canada Lisa M. Given University of Alberta, Canada
ABSTRACT In today’s digital world the majority of companies, including small and medium-sized enterprises (SMEs) and large firms, aim to have an online presence. However, SMEs differ from large-sized companies in terms of financial and staffing resources, which have implications for the development of e-business strategies. Thus, SMEs must not only overcome these barriers but must also take care of critical success factors (CSFs), including developing a good website and ensuring that their websites are listed among the DOI: 10.4018/978-1-60960-587-2.ch214
top search engine results. This chapter discusses three elements (i.e., design principles, web usability and search engine optimization), which are vital to the effective design of a successful digital marketplace. The chapter discusses the importance of integrating these three elements in website design especially for SMEs.
INTRODUCTION Consumers (or users of business services) have different types of informational and goods/services needs. There are generally two ways that individuals explore digital spaces to satisfy their
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Designing Digital Marketplaces for Competitive Advantage
perceived needs: 1) either users know of specific resources (e.g., websites where they can find the answers they need); or, users use search engines (such as Google, Altavista, Yahoo and MSN) to identify available resources in cyberspace. In cases when users rely on search engines to identify resources, users formulate a query based on their perceived needs and enter the query term(s) in the search box of the search engine. Generally, users’ queries are presented in natural language and the search engines are designed to handle queries in this form (Ding, et al., 2004). A large number of published papers and books (e.g., Brin and Page (1998); Morgan and Hunt (2006)) have described details regarding how search engines work, including how users query search engines, mechanisms for indexing billions of webpages, the different types of data collected from webpages (e.g., contents, title, tag and link details) and the complexities involved in webpage ranking and search engine optimization (SEO) techniques. Search engines match the indexed webpages with the user’s query terms and then return results which include both paid search results (i.e., where companies have paid for ranking and placement in the search engine’s results) and organic search results (i.e., where pages are retrieved based on metadata relevant to the query). The organic search results presented to the user are ordered based on relevance criteria determined by a complex page rank algorithm which uses a large number
of criteria to rank the webpages. The user then explores the search results to seek answers to his/ her perceived needs. Xing and Lin (2004) reported survey results from a study conducted at the Georgia Tech University in which it was found that 85 percent of users use search engines. The findings of the study reflect the importance of search engines in identifying resources for consumers and, at the same time, highlight the value of having a website indexed by the search engine and consistently retrieved among the top ranked websites. Once users identify useful resources (i.e., websites), users will then explore these sites to satisfy perceived needs. This leads to the next issue of how well the consumer can explore the website, itself (i.e., web usability), and how easy it is for the user to complete the information-seeking activity. For example, in an e-commerce context, how easy is it for the user to search for a particular product on a company’s website, place an order for that selected product and complete the sales transaction? All of these steps are dependent on the usability aspects of the website (e.g., ease of navigation; intuitive organization of information) which emanates from appropriate website design. Thus from the perspective of both search engine optimization and usability, a well-designed website is integral to ensuring consumer success in looking for web-based information and goods/ services (see Figure 1).
Figure 1. Inter-relatedness of Website design, Usability and SEO
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Schmid (1999) and Meffert (2000) as cited by Schmees (2003) defined electronic market place (e-marketplace) as a place where all or some business transactions (i.e., goods, services and/or information transfer (Ordanini and Pol, 2001)) are done by using Information and Communication Technologies (ICT). According to Issa et al. (2003) electronic market places are also known as online exchanges, internet markets, digital marketplaces, virtual store, virtual marketplace, e-market, etc. Thus, in this chapter, a digital marketplace is defined as a virtual place (i.e., a website) where consumers and buyers come together to interact; it is the online space where an organization engages with its customers. A well-designed website is not only vital for successful (and satisfactory) interactions between buyers and sellers but also has implications for search engine optimization. A website is one of the critical elements in the success of any type of e-commerce models (i.e., B2B [Business-to-Business] or B2C [Business-to-Consumer] or G2C [Governmentto-Citizen] or C2C [Consumer-to-Consumer]). Out of the four e-commerce models, B2B and B2C are the key models for web transactions for small to medium-sized enterprises (SMEs). It is estimated that B2B is much larger than B2C, which constitutes only 10% of all e-commerce transactions (Connor, Galvin, Evans, 2004). According to E-Stats (http://www.census.gov/retail/ mrts/www/data/pdf/09Q1.pdf), e-commerce retail sales (i.e., online sales) were over $120 billion in 2007 in the United States alone. According to Aspedia.com, a study done by “Forrester in May 2007 estimates that around $400 billion of in-store sales are influenced by the web” (http://aspedia. net/index.php?module=pagesetter&func=viewp ub&tid=4&pid=48) and, in the next five years, this value is expected to be around $1 trillion. This value represents the significance of the ecommerce activity in the business domain. The e-commerce activities are important for every type of organization (including small and medium types of organizations) in order to have wider
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outreach, lowering spatial and temporal barriers and increasing interactivity with customers at a relatively low cost. However SMEs differ from large companies in many ways, which have a bearing on the adoption of e-business models for these organizations. SMEs are in a resource deficit position, as compared to large firms (Mosey, 2005), in terms of financial capabilities, technology use, availability of technologically competent employees and staff time (Tödtling and Kaufmann, 2001; Rostro and Grudzewski, 2008; Mosey, 2005; Pelham and Wilson, 1996; Hamill, 1997; Urwin, 2000; Harker and Akkeren, 2002; Hill and Wright, 2001). There are other barriers, as well, which can adversely affect the adoption of e-commerce; these include: SME managers who are not willing to take responsibility for technological changes; SME managers’ and employees’ misunderstandings of the importance of e-business; an overall lack of awareness of (or concerns for) the processes and different elements of e-business (e.g., technology, security, etc.); and other issues like trust and help within the organization (Simpson and Docherty, 2004). Thus, SMEs must not only overcome these barriers but must also take care of critical success factors (CSFs) in implementing an e-business strategy. Some of the identified CSFs include: having simple business processes (e.g., simple order placement, payment process, etc.); recognizing local culture and regulations; having good communication with consumers; being listed among the top search engine results (i.e., SEO); and implementing a good website design (i.e., creating a usable website) (Jennex, et al., 2004; Taylor and Murphy, 2004; Feindt, et al., 2001; Eid et al., 2002). This chapter will focus on two of these CSFs i.e., usable website design and SEO. Barnard and Wesson (2003) state that large brick-and-mortar businesses have the finances to locate themselves at a prime location and thus have competitive advantage than small businesses; however, they also argue that the Internet provides SMEs comparatively the
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opportunity to level the playing field. Thus, a good, usable website is a prerequisite for success (Barnard and Wesson, 2003) and is “one of the key potential sources of competitive advantage for SMEs engaging in Internet adoptions” (Griffin, 2004, p. 134). According to Murphy and Kielgast, (2008) who conducted research on SMEs (small hotel businesses), SMEs that have a very basic online presence and are not using their website effectively risk losing business opportunities to competitors who are able to provide a good online experience to the customers. Thus, an organization that has a well designed website (e.g. appropriate layout, usable navigation) will have a competitive advantage compared to an organization that has a website with design flaws (Elsammani, et al., 2004; Grigoroudis et al., 2008).
DIGITAL MARKETPLACE Digital Marketplace Design There are many reasons identified in the literature for businesses to have a digital presence. These include wider market access, competitive advantage, online distribution, connection to consumers, lower transaction costs and improved and quick consumer feedback (Iyer, 2005; O’Connor, Galvin and Evans, 2004; Wilson and Abel, 2002). Advances in internet technologies have led to a proliferation in online businesses, with low entry and exit barriers for both corporations and consumers. This has created opportunities for global expansion for even small and medium-sized companies (Wilson and Able, 2002). Thus, organizations from every domain are venturing into the digital space; however, in order to succeed in an online business model, the organization needs to design a digital marketplace which is both usable and searchable. Well designed marketplaces will be attractive, accurate and convenient for consumers (Reedy and Schullo, 2004), they will build trust with consumers (Egger, 2001), they will allow for
successful online transactions (Oppenheim and Ward, 2006) and for quick response by the web manager, when needed (dellaert and kahn, 1999). Although the human-computer interaction (hci) literature highlights the importance of designing good and usable websites, in e-business this focus has been sidelined as many organizations focus on business strategies alone. There are two key aspects to building a successful digital marketplace: first, whether the website has been indexed by search engines for organic results display; and second, whether the website displayed in an organic results list is usable or not. The design concepts and usability principles discussed in this chapter are important elements of e-business strategies which are, unfortunately, not given prominence in e-business books. A well designed website can address most usability and SEO issues, which will (in turn) enhance an organization’s overall business strategy. A website is a very important element of an e-commerce business model. However, in many e-business books the importance of a well designed digital market is often discussed only briefly; this is counter-productive in planning for e-business success, as consumers experience the 4Ps (i.e., Product, Price, Place, and Promotion) of marketing at the same time and in the same place in a web-based environment (Constantinides, 2002a). A few researchers have argued strongly in favour of re-visiting the current 4Ps of marketing management in the current context of e-commerce. For example, Constantinides (2002a, 2002b) proposed a new 4S (i.e., Site, Scope, Synergy and System) web-marketing mixed model, which included Site design as one of the core elements for success in an e-commerce environment because the “website is the counter, helpdesk and sales outlet where the actual commercial or non-commercial transaction takes place. Moreover for products delivered in digital form, the site fulfills even the task of the physical distributor by allowing the product delivery online” (p. 3). With the growth and increased penetration of the internet
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and the subsequent expansion of business into the online domain, organizations’ websites have started playing a crucial role in business. Today, websites have become an important channel to disseminate organizational promotional plans, to support and enhance the brand image of products and the organization, itself (Singh and Dalal, 1999), and to distribute products online such as software, photos, movies and music. Thus the web is becoming progressively not only a medium of communication but also an “important component of promotional strategy” (Geissler, et al., 2006, p. 69) and distribution strategy (Dholakia et al., 1999) for a large number of organizations. Many online ventures have failed not because of the products that are being sold on the website but due to the poor design of the website itself. For example, one of the reasons for the failure of Boo.com was “… its ambitious Web site, which was graphics heavy, meaning for users with a 56K modem, it could take several minutes to load” (Wood, 2000 as presented in Shabazz, 2004, p. 123), and which created antipathy among consumers using the website. This idea is echoed by Constantinides (2002a, 2002b) who notes that there should be a particular focus on different aspects of site design, such as findability and speed, to suit users’ needs. Mandel and Johnson (1999) (as presented in Fortina et al. 2002) argued that “even minute changes in the design and configuration of the interface of a website have significant effects on consumer attitudes and intentions” (p. 626). These effects could arise, for example, due to web changes that inadvertently result in poor usability; where an organization redesigns or changes its e-market interface it must take care to ensure that those changes do not render the website less usable from the customer’s perspective. Hence it is important to consider the design of the digital marketplace so that it meets users’ preferences and needs; unfortunately, this aspect of e-business is often neglected by organizations (especially small and medium-sized enterprises, where the resources to have a dedicated informa-
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tion technology department to support and manage effective web design may be cost prohibitive). Poor design of a digital marketplace has an impact not only on the consumers’ attitude (resulting, potentially, in a loss of business) (Oppenheim and Ward, 2006) but also on search engine optimization. The design of a good digital marketplace is not the sole determinant of the success of a business venture, but it will certainly act as one of the key “hygiene factors” outlined in Herzberg’s Motivation-Hygiene Theory in Organizational Behaviour. Hygiene factors are those elements which do not give positive satisfaction, but whose absence can lead to dissatisfaction among users (Zhang, et al., 2000), resulting in a loss of business to competitors. For example, Zhang et al. (2003) identified dead links (or ‘broken links’) as hygiene factor because users assume that the links on the website will work but if the links are not working (i.e., are dead or broken) then users will be disappointed. Hence, organizations must strive to minimize the impact of hygiene factors on e-business. A well designed website will evoke positive emotions, perceptions and attitudes among consumers due to the “the impact the user’s attitude towards the Web site’s content, advertised products, company, credibility and site usability” can have on the business itself (Chen, 2009, p. articles/062009news.html). A recent study conducted by Geissler, et al. (2006) noted that design principles such as the home page length, graphics, links and text affect the user’s perception of the website, which has a bearing on consumers’ attitudes and purchase intentions. A well designed website will provide a strong visual appeal which will lead to quick judgment among users, positively affecting consumers’ buying behaviors and “influence brand perception and credibility” (Chen, 2009, p. articles/062009news. html). According to Lindgaard et al. (2006) the visual appeal of the website can be assessed within 50 milliseconds (ms), so it is vitally important that businesses get the design right, the first time.
Designing Digital Marketplaces for Competitive Advantage
Large organizations with significant budgets to devote to web design often do understand (and design for) the concepts of usability and SEO optimization; however (as discussed previously), SMEs often lack the resources to implement web usability and SEO concepts. A large number of organizations fail to understand the integrated nature of the three activities (i.e., website design, SEO and usability). Often, the web designer is not aware of the impact their design will have on SEO; similarly, copywriters (i.e., website content writers) may not realize how the choice of the words, placement of the words, etc., can affect SEO and usability. This is because the designers and copywriters are, typically, not trained in usability principles and are not experts in SEO techniques. Hence, it becomes imperative that the design and development of a digital marketplace should happen in a collaborative and integrated manner, with team members with varied expertise working together, rather than in silos. A well designed marketplace can lead to competitive advantages in many ways; for example, having the website among the top ranked sites in an organic results list can lead to repeated visits by users and a greater likelihood of repeated transactions (e.g., higher sales). If users are not able to find a website in the search results, there is a greater likelihood that the user will not visit the website and the company will lose the business opportunity. However, being ranked in the top list of returned results is only half of the equation; if a user cannot navigate the website and complete the transaction, then the user will leave the website and go to a competitor’s website, resulting in a gain for that competitor. In the section that follows, we will outline the central design principles that small and mediumsized enterprises should consider, followed by an overview of key usability principles and methods, including the impact of good website design on SEO techniques.
Website Design Principles There are a large number of research papers on website design principles; different research papers have highlighted the importance of different website design elements that can make websites effective and attract users’ attention in a visually appealing way, in a very short period of time. Oppenheim and Ward (2006) have identified numerous design elements, such as presentation, content, accessibility, navigation, language, transaction pages, security, privacy and authority. Liu and Arnett (2000) note the importance of information quality and playfulness in effective design. Palmer (2002) and Ranganathan and Ganapathy (2002) have noted content quality, security, privacy and navigation as central to good design. Webb and Webb (2004) have identified navigability, accuracy, security, trust and representation relevancy. Cao, et al. (2005) have outlined four main elements (and a few sub-elements) for quality evaluation of e-commerce websites, specifically, including System Quality (i.e., search, multimedia and responsiveness), Information Quality (i.e., accuracy and relevance), Service Quality (i.e., trust and empathy) and Attractiveness (i.e., playfulness). Similarly, Gehrke and Turban (1999) identified a few important website design factors and emphasized in their conclusion that “cool stuff is on its way out. Revolving wingdings, flashing banner ads, grotesque background colors and textures, and a meaningless multitude of multimedia effects that require endless plug-ins will be extinct as electronic commerce continues to advance” (p. 6-7). Interestingly, although the latter paper was published a decade ago, many e-business websites continue to privilege “cool stuff” while ignoring many of these key principles of quality design, which customers crave. E-business must embrace the principles of effective design and move away from flashy trends in web design, which often do not satisfy customers’ web-based needs.
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The findings of these research projects have been compiled and summarized in a number of guides, including U.S. Department of Health and Human Services (2006 ed.) that is available at the website www.usability.gov, ‘an official U.S. Government Web site managed by the U.S. Department of Health & Human Services’. A comprehensive and detailed description of key design principles and practical solutions are presented on this site, which was developed based on findings from different domains, including “cognitive psychology, computer science, human factors, technical communication, and usability” (http://www.usability.gov/pdfs/guidelines.html). The following are identified as high level elements for website design: •
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Design Process and Details: e.g., identifying website goals and detailed users’ requirements; Accessibility: e.g., support for assistive technologies and presenting webpages in text only format; Homepage: e.g., designing a website to allow home page access from any page of the website; Page Layout: e.g., organization and structuring pages for easy and quick comprehension; Navigation: includes the ability to find information on the website by adopting consistent policies on different elements such as tabs, heading, listing, layout, layering of menus, etc.; Scrolling and Paging: e.g., designing appropriate page length for the content presented (i.e., longer page length for reading comprehension; minimizing horizontal scrolling); Text Appearance: e.g., use of familiar font size, bold, background and text color combination, font consistent across webpages;
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Lists: e.g., providing headings for lists and ordering elements to support quick scans of the purpose of the list; Widgets: e.g., consistent use of buttons, check boxes, drop down lists, etc.; Graphics and Multimedia: e.g., appropriate image-text ratio, size of graphics to minimize impact on downloading speed, corporate logo placement consistency; Search: e.g., having search features on the website, full website search capability, case- insensitive and natural language search support; Links: e.g., appropriate colors and labels for links, checking for dead links and relevancy of links; Content and Content Organization: e.g., placement of critical information near the top of the page; consistency and clarity of organization of information at the website, page, paragraph and list levels; Heading, Titles and Labels: e.g., use of correct HTML tags (h1, h2, p, …), appropriate and meaningful page headings, meta tags; Hardware and Software Configuration: e.g., designing the website of (all or) commonly used web browsers by the target audience, typical user connection speed; Practice Web Standards: e.g., using website design standards such xHTML standards, validations, etc. Meet Accessibility Guidelines: e.g., use alt-tags for images, avoid the use of frames, etc.
An appropriate adoption and deployment of each of these design elements will enhance the e-commerce website’s usability (i.e., ease of use) and attractiveness. Some of the above-listed design elements, such as content, heading, title, content organization and page layout, will also have an impact on both usability and SEO. In the next sec-
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tion, we discuss usability principles and evaluation methods, followed by a section on SEO. In addition, websites should explicitly address how customers’ privacy will be maintained (e.g., how users’ confidential financial information will be managed). Similarly, companies must maintain secure transactions with consumers by implementing technologies such as SET (Secure Electronic Transaction), SSL (Secure Sockets Layer) and digital ID (Gehrke and Turban, 1999) and displaying the logos and icons that represent these technologies. When consumers see a padlock icon or an “s” added to the http code, they gain an enhanced sense of security and see that it is safe to complete a transaction on that company’s website.
Usability According to Gullikson et al. (1999) the visual appearance, utility aspect (i.e., “the ability of the web site to do functionally what it is supposed to do” (p. 294)) and usability are the three important aspects of a well-designed website. A website should enhance visual appeal and utility while reducing usability problems, substantially. Often, website designers primarily focus on the “look and feel” (Gullikson et al., 1999) of a site, so that the usability aspects are ignored. Usability is about the ease with which users’ interact with a system or website (Nielsen and Mack, 1994; Nielsen, 2000) as they search for information or place product orders on the web (Benbunan-Fich, 2001; Nah and Davis, 2002). There are different usability definitions proposed in the literature; for example, Matera et al., 2006 define usability as “the extent to which a product can be used by specified users to achieve goals with effectiveness, efficiency and satisfaction in a specified context of use” (p. 4). The most cited usability definition is from Jacob Nielsen’s work; Nielsen (2003) defined usability as “a quality attribute that assesses how easy user interfaces are to use” and “refers to methods for improving ease-of-use during the design process” (p. http://www.useit.com/alertbox/20030825.
html). Nielsen (2003) identified five elements of usability which include learnability (i.e., ease of use even in the first instance of interaction), efficiency (i.e., the ability to undertake an activity quickly after learning the design), memorability (i.e., the ability to undertake an activity efficiently after prolonged absence from the site), errors (i.e., the types of errors, their severity and the ability to recover from them), and satisfaction (i.e., enjoyment of the site in use). Nielsen (2003) has also presented a few misconceptions about usability. First, usability is often considered as an expensive exercise and many corporations are not inclined to undertake it. However, the objective of the usability study dictates the cost of the exercise. In some cases, usability testing can cost many thousands of dollars; however, this is typically only if the usability project involves multiple websites, which are examined over a long period of time. However, as small and medium-sized organizations typically have small-scale websites, often with a smaller target audience than a large organization, these studies can be undertaken at a very low (or even no) cost. A low cost usability exercise could capture a large number of problems in a website, resulting in resolutions of major issues that can lead to increased sales with only a few changes to the organization’s website. The rule of thumb proposed by Jacob Nielsen is that “on average, best practices call for spending 10% of a design budget on usability” (p. Alertbox, September 8, 2003). A second myth is that usability testing will delay a website launch; however, employing a usercentered design process throughout can minimize the impact of time needed to incorporate changes to a site, resulting in an on-time launch that will meet users’ website needs. According to Maguire (2001) the design process and usability testing were originally considered independent events, but the new approach to design (as reflected, for example, in the ISO 13407 human-centred design framework) integrates these steps, so that usability is now part of the website development process.
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A third myth is that usability can kill creativity. However, Nielsen has been firm in noting that “following design conventions doesn’t destroy creativity” (Nielsen, 2003, p. Alertbox, September 8, 2003); rather, finding creative solutions that support customers’ intentions can enhance design creativity, while serving customers’needs. A fourth myth is that users do not need to use the website to do usability testing; i.e., that the website can be evaluated by using market research techniques such as customer satisfaction survey. According to Nielsen (2003), in actual practice, market research might not always be able to provide insight into usability issues of the website because the websites that “look incredibly cool and compelling, yet they almost never work in actual use” (p. Alertbox, September 8, 2003). In the HCI literature, three different major usability methods and techniques (i.e., inquiry, testing and inspection), have been proposed (Paas and Firssova; 2004; Folmer and Bosch; 2004; Nielsen, 1994). In a Usability Inquiry method, data are collected by talking to users about their experiences with websites when they try to engage in real-life tasks. This could be done by using instruments such as questionnaires, focus groups, panel discussions and interviews (Paas and Firssova; 2004; Folmer and Bosch; 2004). In Usability Testing methods, experts evaluate how the website would support the user to complete tasks; data are collected by observing users as they engage in representative tasks on prototype models. Data collection methods include think aloud protocols, co-discovery learning, trial runs, coaching methods, etc (Nielsen, 1993; Paas and Firssova; 2004; Folmer and Bosch; 2004). In Usability Inspection, the experts play the role of users’ (in addition to relying on their expert knowledge) as they review websites using various formal and informal methods; these include heuristic evaluation cognitive walkthrough, pluralistic walkthrough, feature inspection, and standard inspection (Nielsen, 1994; Paas and Firssova; 2004; Folmer and Bosch; 2004; Maguire, 2001). The
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most commonly used usability inspection method is heuristic evaluation and Nielsen (1994) has identified ten heuristic principles: visibility of system status; the match between the system and the real world; user control and freedom; consistency and standards; error prevention; recognition rather than recall; flexibility and efficiency of use; aesthetic and minimalist design; helping users recognize, diagnose, and recover from errors; and help and documentation (www.useit.com/papers/heuristic/ heuristic_list.html). Although inspection methods can give a designer (and an organization) a clear sense of areas for development (e.g., to audit a website for its adherence to accessibility design principles), these approaches should be used in conjunction with – not, in isolation from – methods that engage real users in real web searching tasks. As experts cannot anticipate a user’s potential use of a given website, it is vital to include members of the site’s target audience in the web design and evaluation process, prior to launch. A large number of studies have discussed and propagated the importance of usability, but many organizations continue to fail to understand its importance; for this reason, websites continue to be designed with usability errors (Nah and Davis, 2002, p. 98) and customers continue to be lost. The commonly identified problems on websites are poor navigability, low response times and confusing content (Nielsen, 1999; Nah and Davis, 2002). Tedeschi (1999) [as reported by Benbunan-Fich, 2001] argued that “better usability will result in more efficient interaction between the user and the site and will increase the probability that the user will return and/or make a purchase” (p. 151). If website usability is not addressed in the design of a site, this will lead to loss of customers and will risk the economic viability of the e-business enterprise (Nah and Davis, 2002). Nielsen (1998) cited a research report by Forrester (1998) that reflects the loss of potential business opportunities due to poor usability caused by poor website design. The author noted that there is expected to be a
Designing Digital Marketplaces for Competitive Advantage
“loss of approximately 50% of the potential sales from the site as people can’t find stuff” in addition to “losing repeat visits from 40% of the users who do not return to a site when their first visit resulted in a negative experience” (Nielsen, 1998, p. Alertbox for October 18, 1998). This potential loss was confirmed by Konradt et. al (2003). The authors in their work presented an interesting finding from a study conducted by Manhartsberger and Musil (2001) in which the 100 consumers who participated were given a task to buy products from the websites; the e-business companies involved lost 63% (USD 5,645 out of USD 9,000) of the potential revenue as consumers were not able to locate the product of their choice. These studies are just a few examples that reflect the idea that poorly designed websites with poor usability can lead to loss of potential business opportunities. As Nielsen (2003) notes, “the first law of e-commerce is that if users cannot find the product, they cannot buy it either” (p. alertbox/20030825.html).
Search Engine Optimization (SEO) The growth of the internet is demonstrated in the increasing number of registered domains; there were 174 million, 150 million and 120 million domains registered at the end of the third quarter of 2008, at the end of 2007 and 2006 respectively (http://www.verisign.com/domain-nameservices/domain-information-center/domainname-resources/domain-name-report-dec08.pdf). Verisign.com report has also reported that annual domain renewal is in the range of 74% to 77% for years 2006 and 2007. Thus the high renewal rate and continuous registration of new domains is leading to a crowding of the internet search space as every domain vies for a slot in the search engine results space. E-commerce websites must compete not only with the competitors from their own business domains but also with other websites (e.g., informational websites; entertainment
sites) for users’ attention. Research in HCI and information science demonstrates that users will reduce the cognitive load involved in searching for information by (for example) scanning only through the first page of results retrieved by search engines (Sen, 2005). Hence it becomes imperative for businesses to design a marketplace which not only adheres to website design principles and is usable, but that is also indexed by search engines so that the website will be listed among the top 20 organic search results (i.e., the first page) for a user query. There are two major ways in which a website can be included in the search engine results. First, a business can design a search enginefriendly website, so that it will be indexed by the search engine (i.e., organic results); or, second, a business can pay the search engine company to ensure that their website is displayed in the search engine results list (i.e., paid results) (Yu and Lin. 2007). Paid results are of two types, i.e., paid inclusion and paid placement. Paid inclusion means paying the search engine to “guarantee a web site’s pages are stored in the search index” (Moran and Hunt, 2006, p. 513); however, in this approach, there is no guarantee for a high search result ranking for the website. Paid placement, on the other hand, involves paying the search engine to show the pages of the website in the search results in response to the particular set of query (or search) terms “regardless of how closely the page matches” the query (or search) terms (Moran and Hunt, 2006, p. 5). For example, with paid placement the website links display as sponsored links by Google on the top of the search results or on the right side of the search result pages. The main revenue model for search engine for paid placement is CPC (cost per click) (Xing and Lin, 2004). The organic results are the “best pages found for the words the searcher entered” (Moran and Hunt, 2006, p. 5) by the search engine, which is commonly linked to SEO. SEO is a technique to optimize the website so that it has a better ranking in the organic search
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(Moran and Hunt, 2006; Xing and Lin, 2004; Joshi and Motwani, 2006; Sen, 2005). There is always competition between paid placement and SEO but there are contradictory assessments among researchers. Sen (2005) argued that a large number of businesses do not want to invest in SEO because the organizations believe that adopting SEO strategies is more expensive than investing in paid placement; however, SEO might become more attractive to companies than paid placement if SEO costs are controlled. Xing and Lin (2004) argued that SEO is more popular than paid placement because unbiased organic results appeal more to the consumers. Also the CPC have problem of fraudulent clicks which is estimated to be in the range of 20-35% (i.e., 20-35% clicks are fraudulent) when using generic keywords (e.g., automobile, cell phones) (Quinton and Khan, 2009). Malaga (2007) compared the SEO cost vis-à-vis CPC rate for an iPod-related website; the author found that their CPC for their SEO project was $0.16 (as the website had 7500 unique visitors per month and their SEO cost was 1200, hence 1200/7500=$0.16) while the CPC rate for iPod related keywords was $0.40 and $0.30 for Google and Yahoo respectively. SEO is important because websites need to be high in the ranking in the organic search results, especially as most consumers browse top-listed websites of the organic search results (Sen, 2005) which affects traffic onto the website (Yu and Lin, 2007). The results from the survey conducted by Georgia Tech University and by the Search Engine Marketing Professional Organization (SEMPO) as reported in Xing and Lin (2004) indicate that 70% of users prefer organic results; paid listings only received about 24.6% of clicks. This was confirmed by Moran and Hunt (2006) who noted that organic search results are important because “searchers click organic results 60 percent of the time” (p. 5). The number of people using search engines to search and browse for information and products is constantly increasing. Hence it is important for companies involved in e-business (either in
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online commerce or information dissemination businesses) to include SEO strategies in the design phase for their websites because 62% of users generally examine the first page search results, only, and a very few users (less than 10%) browse the search results beyond third page of the search results (Malaga, 2008; Malaga, 2007; Zhang and Dimitroff, 2005; Yu and Lin, 2007). There are a large number of organizations that are involved in search engine marketing, an important marketing activity in e-business. These organizations specialize in the area of SEO. In their services for SEO, these search engine marketing organizations such as Wordtracker.com, Yahoo (Small Business), Google, and Marketleap.com offer (one or more) services that include keyword analyses, word trackers (i.e., to highlight the best keywords for your website), keyword selection (i.e., choosing the right keywords for marketing), website ranking evaluation, link popularity analysis and Meta tag generators. These elements all have an impact on SEO. The SEO can be done by making changes in the website design and code (Sen, 2005; Zhang and Dimitroff, 2005; Moran and Hunt, 2006; Abel, 2002). Hence, the design of the digital marketplace requires an approach that interweaves website design principles and theories and SEO techniques in the early development stage. By incorporating SEO techniques during the design phase, the organization can save substantial amounts of money by not needing to pay SEO consultants at a later stage, to increase website traffic. According to Malaga (2007), many SEO consultants charge more than $5000 for a SEO research project. The design elements that can affect SEO include: headings, titles, website content and content organization, tags (such as meta tags and image tags), links, as well as web standards and the design process itself (Joshi and Motwani, 2006; Moran and Hunt, 2006; Wilson and Abel, 2002; Zhang and Dimitroff, 2005; Yu and Lin, 2007; Weideman and Schwenke, 2006; Malaga, 2007).
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In the following paragraphs, some of the design elements that impact SEO will be discussed.
Impact of Different Design Elements on SEO Organizations with a digital presence need to identify the website’s goals (Design Process and Details) and align these with the organization’s goals. This is important because this will inform the choice of a target audience for the site and an understanding of what search engine would best meet the potential customers’ requirements, as different search engines have different ranking criteria and indexing strategies (Zhang and Dimitroff, 2005). By identify the goals and objectives, the organization can target particular search engines. Even though there are over 30,000 search engines in existence (Zhang and Dimitroff 2005), the three most prominent search engines (i.e., Google, Yahoo and MSN) account for over 80% of the search engine market (Malaga, 2007). There is a crowding of cyberspace with an increasing number of websites in the digital space. Hence, search engines are working towards developing more and more innovative algorithms to better the search results. A large number of design elements can affect a site’s ranking in major search engines. The design elements such as heading, title, website content and content organization have an impact on SEO as they affect keyword selection, keyword density, keyword proximity and keyword prominence. Keyword density (also known as keyword weight) is the ratio of the total number of times a word occurs on a page to the total count of all words in a page (Moran and Hunt, 2006; Malaga, 2007). Previously, a search engine gave importance to a term count (i.e., a page that had a higher number of instances of the query term was considered ‘good’); more recently, search engines changed to examine keyword density, so that the target density should be around 7% (Moran and Hunt, 2006, p. 39). Keyword proximity is the distance
between the query terms on a page (i.e. if the user uses more than one query term, how far are these query terms from one another on the webpage). Thus, the closer the query terms the better it is from a retrieval standpoint re: the relevance of the page to the query itself. For example, if a user employs the query terms ‘cell phones’, then having both the terms next to each other is better than the term ‘cell’ separated from the term ‘phone’ by a few words or in a separate paragraph (Moran and Hunt, 2006). Keyword prominence refers to the location of the keywords on the page (i.e. whether they are in the header, title, or top of the page) (Moran and Hunt, 2006); here, the higher the prominence of the keyword, the more likely that the page will match the relevance content of the user’s query. The quality, relevance, completeness and currency (Konradt et al., 2003) of the content are not only important factors in consumers’ buying decision processes, but also have an impact on the SEO. Cole et al. (2003), Agarwal and Venkatesh (2002), and Kim and Lee (2002) [as referenced in Konradt et al. (2003)] have highlighted the importance of quality of content on websites. The quality of the content will influence the selection of keywords along with density, proximity and prominence. Wilson and Abel (2002) noted that it is important to optimize the content of the web with the appropriate choice of keywords and to ensure that those keywords are positioned in an important area of the page (i.e., top of the page); this notion was also supported by Sen (2005) who suggested that companies can improve their website page ranking by modifying the website title tag, heading tags, etc. Hence, content writers and website designers are required to work in close collaboration to ensure SEO. Content writers need to identify the important keywords which they feel reflect their business and are frequently used by consumers to identify specific business websites. For example, if a the company is in the business of online selling of cameras, content writers need to identify which keywords
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users will use to find websites that sell cameras. One of the keywords that users might commonly use is ‘digital camera’. The company’s website should have keywords ‘digital’ and ‘camera’ in close proximity to each other and on the top of the webpage. The top keywords that users use to find webpages can be identified by using online resources such as wordtracker (available at http:// www.wordtracker.com/). The importance of keyword density and prominence in title and main text is confirmed by the results that Zhang and Dimitroff (2005) found in their experimental study. Zhang and Dimitroff (2005) note that the website achieved a better search ranking by having the same keywords used multiple times (i.e., increasing keyword density) and also by having the same keywords both in the title and in the initial part of the full-text, which is, generally, on the top of the webpage (i.e., increasing keyword prominence) (Malaga, 2007; Zhang and Dimitroff, 2005; Curran, 2004). Yu and Lin (2007) have identified over 41 different types of tools that can be used in SEO. For example, the keyword density tool provided by SEO Chat (available at http://www.seochat.com/seo-tools/) can help both content writers and website designers, as they can make informed decisions on the choice of keywords to be included in the webpage. However, companies should also be ethical in their practices in use of SEO techniques. The use of unethical practices (e.g., artificially increasing the keyword density by using the same term multiple times in the content or changing the font color of the keyword to white so that the high visibility of the keyword does not irritate the user or alter the content flow, while increasing the term count) could lead to penalization such as “worse placement in the SERPs (Search Engine Result Pages) or an outright ban from the search engine” (Malaga 2008, p. 147; Malaga, 2007). For example, BMW used unethical practice in order to have a high page ranking for its German website in Google organic search results. The company used a technique called ‘doorway page’ (Malaga 2008) which
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means that the company had two separate sets of webpages, where one set of webpages were for indexing purposes while the other set of pages were for users to view. Google thus banned the website because the webpages that were indexed by Google were not shown to the users but were redirected to different sets of webpages. Another element that needs to be addressed in the design process, which affects SEO, is the appropriate and effective use of meta tags and image tags. Meta-tags are the tags that provide additional data (e.g., such as keywords, description) from a page to search engines (Joshi and Motwani, 2006; Sen, 2005; Malaga, 2007; Wilson and Abel, 2002). The meta tags are part of the head element of an HTML and xHTML document, and “are typically used to specify page description, keywords, author of the document, last modified and other metadata” (http://w3schools.com/tags/tag_meta. asp) of HTML/xHTML page (Malet, et al., 1999). For example: <meta name=”description” content= “E-business Book Chapter” /> and <meta name=”keywords” content= “SEO, Usability, Digital Market, Website Design” />. “Meta tags are important pieces of code that many search engines use to analyze, categorize and rank a website” (http://www.mailworkz.com/tools.htm). According to Joshi and Motwani (2006), a large number of websites include important keywords in meta tags, which are crawled by search engine spiders (or crawlers). Spiders are computer programs that continuously traverse the Web and download the pages, collect webpage location information and store them on the server for indexing purpose (Heydon and Najork, 1999; http:// www.kbkmarketing.com/other-seo-definitions. php). Some search engines use meta tags in page ranking while others collect the meta tag data but do not use them in page ranking (Wilson and Abel, 2002). For example, Google does not make use of meta tags in ranking of search results (http:// searchenginewatch.com/2167931). In addition, other tags such as image tags (e.g., ALT) i.e., text associate with images or text in comment are
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indexed by some of the search engines such as Google and AltaVista (http://searchenginewatch. com). Hence designers need to pay attention in naming or commenting on the images. Search engines such as Google use link analysis to enhance the organic search results of websites (Moran and Hunt, 2006; Sen, 2005; Weideman and Mgidana, 2004; Yu and Lin, 2007; Zhang and Dimitroff, 2005; Wilson and Able, 2002). Link analysis used by a search engine has its grounding in the Hub and Authority model, proposed by Jon Kleinberg (Kleinberg, 1999a; 1999b), which aims to harness the “diversity roles among different types of pages” (Kleinberg, 1999b, p. 2). Kleinberg proposed that the hubs are those pages which act as guides and resource to users by recommending them to a website which is an authority on the content; and, authorities are those pages which are the primary sources of the information. For example, www.useit.com is the authority (website) on usability and any other website providing the link to this website will be the hub for the topic. The presence of the links as well as the anchor text (i.e., label name) given to the link on the website has been identified as one of the techniques for SEO (Moran and Hunt, 2006). For example, a website (say, ‘www.helloworld. com’) is in the business of usability consultancy. This website has many usability related links including ‘http://www.useit.com’, which has the anchor text label ‘Heuristic Evaluation by Jacob Nielsen’. The website (www.helloworld.com) is a ‘hub’ for usability and ‘www.useit.com’ is the ‘authority’ on usability (as many other websites also point to www.useit.com for usability-related concepts). Now, when a user uses the query terms ‘Heuristic’ and ‘Nielsen’, the search engines used for link analysis to rank ‘www.helloworld. com’ would evaluate both the link itself (www. useit.com) and the anchor text label (‘Heuristic Evaluation by Jacob Nielsen’). Hence. SMEs’ in designing their webpages, should consider the link analysis element and should strive to become hubs
for information in their specialty area by providing links to other websites (i.e., authorities). Finally, following the website design standards such as those proposed by W3C (World Wide Web Consortium) (www.w3.org) is a good design practice, and certainly would support in optimizing the website for search engine indexing as “the search engine spider/crawlers can easily understand the content of your page and follow all the links throughout your site. Web standards were developed with specific accessibility issues in mind and following these standards not only aids those visiting your site with visual impairment, it also helps search engine spiders understand the graphical content of your site as well. Another key component to building pages with Web standards is separating content from page structure, formatting and functionality. In doing this it helps load times, assists the search engine spiders in focusing on content and decreases the ratio of code to content” (Hendrikse, 2008, p. 7-8).
CONCLUSION AND FUTURE RESEARCH DIRECTIONS In today’s digital world, firms should have an online presence and should explore the ways to harness the internet’s potential to advance their business goals. The firms (whether large or small and medium-sized) should take care of critical success factors (including those discussed in this chapter) required to benefit from e-commerce. One of the critical success factors is the online presence of a business via a website. However, the mere online presence of a firm is not adequate; consumers should also be able to search the website easily and place the order quickly. Thus, the firm’s website should be designed so that it is not only usable but also optimized to support search engine marketing. This requires an investment of time and human resources; although large firms generally have adequate resources (e.g., skilled manpower,
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technological base, and financial strength) to support their website design process, usability testing and SEO for search engine marketing, small-scale firms may have limited resources to devote to these activities. These organizations should strive to optimize their resources by carefully planning their online strategies; this includes planning well ahead before designing of the website and involving consumers throughout the design process, to manage time and finances devoted to usability, effectively. SMEs should strive to achieve multiple goals, such as usable website and optimized for search engine, in their website design phase by carefully adopting the design principles and incorporating SEO technique. A large number of usability elements and SEO techniques can be done at low cost and do not require expensive consultants to undertake these activities. All of these factors are crucial – and doable – for small and medium-sized enterprises that plan to embark on (or enhance) e-business activities. In future, we would like to examine the current practices of SMEs in terms of usability and SEO practices; i.e., how usability is being currently practiced in SMEs, what SEO techniques SMEs are using to enhance their ranking on the web, what resources (i.e., external consultants or internal expertise) SMEs are using in SEO techniques implementation. Finally, there is a need to develop a set of best practices for SMEs for designing, usable and SEO-compliant websites.
REFERENCES Barnard, L., & Wesson, J. L. (2003). Usability issues for E-commerce in South Africa: an Empirical Investigation.In Proceedings of SAICSIT 2003, 258 – 267. Benbunan-Fich, R. (2001). Using Protocol Analysis to Evaluate the Usability of a Commercial Web Site. Information & Management, 39, 151–163. doi:10.1016/S0378-7206(01)00085-4
482
Brin, S., & Page, L. (1998). The Aanatomy of a Large-scale Hypertextual Web Search Engine, Proceedings of the Seventh International World Wide Web Conference, 30(1-7), p. 107-117. Cao, M., Zhang, Q., & Seydel, J. (2005). B2C E-Commerce Web Site Quality: An Empirical Examination. Industrial Management & Data Systems, 105(5), 645–661. doi:10.1108/02635570510600000 Chen, J. (2009). The Impact of Aesthetics on Attitudes Towards Websites. Retrieved from July 24, 2009 from http://usability.gov/ articles/062009news.html. Constantinides, E. (2002a). The 4S Web-Marketing Mix Model. Electronic Commerce Research and Applications, 1, 57–76. doi:10.1016/S15674223(02)00006-6 Constantinides, E. (2002b) From Physical Marketing to Web Marketing: The Web-Marketing Mix. Proceedings of the 35th Hawaii International Conference on System Science (HICSS), 7, 205-216. Curran, K. (2004). Tips for Achieving High Positioning in the Results Pages of the Major Search Engine. Information Technology Journal, 3(2), 202–205. doi:10.3923/itj.2004.202.205 Dellaert, B. G. C., & Kahn, B. E. (1999). How Tolerable is Delay? Consumer’s Evaluation of Internet Web Sites after Waiting. Journal of Interactive Marketing, 13, 41–54. doi:10.1002/(SICI)15206653(199924)13:13.0.CO;2-S Dholakia, N., Dholakia, R. R., Laub, M., & Hwang, Y.-S. (1999). Electronic Commerce and the Transformation of Marketing, In Wolfgang, F., (Ed.), Internet Marketing, (pp. 55-80) Germany, Schaefer-Poeschel: Verlag. Ding, L., Finin, T., Joshi, A., Pan, R., Cost, R. S., Pen, Y., et al. (2004). Swoogle: A Search and Metadata Engine for the Semantic Web. Proceedings of the thirteenth ACM international conference on Information and knowledge management.652 - 659.
Designing Digital Marketplaces for Competitive Advantage
Egger, F. N. (2001). Affective Design of ECommerce User Interfaces: How to Maximise Perceived Trustworthiness. Proceedings of the International Conference on Affective Human Factors Design, 317-324. Eid, R., Trueman, M., & Ahmed, A. M. A. (2002). Cross-Industry Review of B2B Critical Success Factors. Internet Research: Electronic Networking Applications and Policy, 12(2), 110–123. doi:10.1108/10662240210422495 Elsammani, Z. A., Hackney, R., & Scown, P. (2004). SMEs Adoption and Implementation Process of Websites in the Presence of Change Agents. In Al-Qirim, N. A. Y. (Ed.), Electronic Commerce in Small to Medium-Sized Enterprises: Frameworks, Issues and Implications (pp. 146–163). Hershey, PA: Idea Group Publishing. Feindt, S., Jeffcoate, J., & Chappell, C. (2001). Identifying Success Factors for Rapid Growth in SME E-Commerce. Small Business Economics, 19, 51–62. doi:10.1023/A:1016165825476 Folmer, E., & Bosch, J. (2004). Architecting for Usability: A Survey. Journal of Systems and Software, 70(1-2), 61–78. doi:10.1016/S01641212(02)00159-0 Fortina, D. R., Dholakia, R. R., & Dholakia, N. (2002). Emerging Issues in Electronic Marketing: Thinking Outside the Square. Journal of Business Research, 55, 623–627. doi:10.1016/ S0148-2963(00)00202-2 Gehrke, D., & Turban, E. (1999). Determinants of Successful Website Design: Relative Importance and Recommendations for Effectiveness. Proceedings of the 32nd Hawaii International Conference on System Sciences (HICSSS-32), 1-8. Geissler, G. L., Zinkhan, G. N., & Watson, R. T. (2006). The Influence of Home Page Complexity on Consumer Attention, Attittudes and Purchase Intent. Journal of Advertising, 35(2), 69–80.
Griffin, J. (2004). Mapping the Diffusion of the Internet Technology Cluster: An Examination of Irish SMEs. In Al-Qirim, N. A. Y. (Ed.), Electronic Commerce in Small to Medium-Sized Enterprises: Frameworks, Issues and Implications (pp. 128–145). Hershey, PA: Idea Group Publishing. Grigoroudis, E., Litos, C., Moustakis, V. A., Politis, Y., & Tsironis, L. (2008). The Assessment of User-Perceived Web Quality: Application of a Satisfaction Benchmarking Approach. European Journal of Operational Research, 187, 1346–1357. doi:10.1016/j.ejor.2006.09.017 Gullikson, S., Blades, R., Bragdon, M., McKibbon, S., Sparling, M., & Toms, E. G. (1999). The Impact of Information Architecture on Academic Web Site Usability. The Electronic Library, 17(5), 293–303. doi:10.1108/02640479910330714 Hamill, J. (1997). The Internet and International Marketing. International Marketing Review, 14(5), 300–323. doi:10.1108/02651339710184280 Harker, D., & Akkeren, J. V. (2002). Exploring the Needs of SMEs for Mobile Data Technologies: the Role of Qualitative Research Techniques. Qualitative Market Research: An International Journal, 5(3), 199–209. doi:10.1108/13522750210432002 Hendrikse, M. (2008) Search Engine Marketing 101: A Guide for Small Businesses and Not-ForProfits to Engage in Search Engine Marketing. Retrieved from on July 25, 2009 from http:// markhendrikse.com/storage/post-images/june2009/SearchEngineMarketing101_MarkHendrikse.pdf. Heydon, A., & Najork, M. (1999). Mercator: A Scalable, Extensible Web Crawler. World Wide Web (Bussum), 2, 219–229. doi:10.1023/A:1019213109274 Hill, J., & Wright, L. T. (2001). A Qualitative Research Agenda for Small to Medium-Sized Enterprises. Marketing Intelligence & Planning, 19(6), 432–443. doi:10.1108/EUM0000000006111
483
Designing Digital Marketplaces for Competitive Advantage
Issa, R. R. A., Flood, I., & Caglasin, G. (2003). A Survey of e-Business Implementation in the US Construction Industry. In Bjork, B.(ed.), Journal of Information Technology in Construction, 8, 15-28.
Maguire, M. (2001). Methods to Support HumanCentered Design. International Journal of HumanComputer Studies, 55, 587–634. doi:10.1006/ ijhc.2001.0503
Iyer, G. R. (2005). Global Internet Marketing Strategy: Framework and Managerial Insights. In Clarke, I. III, & Flaherty, T. (Eds.), Advances in Electronic Marketing (pp. 84–102). Hershey, PA: Idea Group Publishing.
Malaga, R. A. (2007) The Value of Search Engine Optimization: An Action Research Project at a New E-Commerce Site. In Khosrow-Pour, M. (Ed.), Journal of Electronic Commerce in Organizations, 5(3), 68-82.
Jennex, M. E., Amoroso, D., & Adelajun, O. (2004). E-Commerce Infrastructure Success Factors for Small Companies in Developing Economies. Electronic Commerce Research, 4, 263–286. doi:10.1023/B:ELEC.0000027983.36409.d4
Malaga, R. A. (2008). Worst Practices in Search Engine Optimization. Communications of the ACM, 51(12), 147–150. doi:10.1145/1409360.1409388
Joshi, A., & Motwani, R. (2006). Keyword Generation for Search Engine Advertising. Sixth IEEE International Conference on Data Mining Workshops, ICDM Workshops, 490-496. Kleinberg, J. M. (1999a). Authoritative Sources in a Hyperlinked Environment. Journal of the ACM, 46(5), 604–632. doi:10.1145/324133.324140 Kleinberg, J. M. (1999b). Hubs, Authorities, and Communities [CSUR]. ACM Computing Surveys, 31(4es), 1–3. doi:10.1145/345966.345982
Malet, G., Munoz, F., Appleyard, R., & Hersh, W. (1999). A Model for Enhancing Internet Medical Document Retrieval with “Medical Core Metadata. Journal of the American Medical Informatics Association, 6(2), 163–172. Matera, M., Rizzo, F., & Carughi, G. T. (2006). Web Usability: Principles and Evaluation Methods. In Mendes, E., & Mosley, N. (Eds.), Web Engineering (pp. 143–180). Berlin, Heidelberg: Springer. doi:10.1007/3-540-28218-1_5 Moran, M., & Hunt, B. (2006). Search Engine Marketing: Driving Search Traffic to Your Company’s Web Site. Upper Saddle River, NJ: IBM Press, Pearson PLC.
Konradt, U., Wandke, H., Balazs, B., & Christophersen, T. (2003). Usability in Online Shops: Scale Construction, Validation and the Influence on the Buyers’ Intention and Decision. Behaviour & Information Technology, 22(3), 165–174. doi:10.1080/0144929031000107072
Mosey, S. (2005). Understanding New-to-Market Product Development in SMEs. International Journal of Operations & Production Management, 25(2), 114–130. doi:10.1108/01443570510576994
Lindgaard, G., Fernandes, G., Dudek, C., & Brown, J. (2006). Attention Web Designers: You have 50 Milliseconds to Make a Good First Impression. Behaviour & Information Technology, 25(2), 115–126. doi:10.1080/01449290500330448
Murphy, H. C., & Kielgast, C. D. (2008). Do Small and Medium-sized Hotels Exploit Search Engine Marketing? International Journal of Contemporary Hospitality Management, 20(1), 90–97. doi:10.1108/09596110810848604
Liu, C., & Arnett, K. P. (2000). Exploring the Factors Associated with Website Sucess in the Content of Electronic Commerce. Information & Management, 38(10), 269–282.
Nah, F. F.-H., & Davis, S. (2002). HCI Research Issues in E-commerce. Journal of Electronic Commerce Research, 3, 98–113.
484
Designing Digital Marketplaces for Competitive Advantage
Nielsen, J. (1993). Usability Engineering. San Diego, CA: Academic Press. Nielsen, J. (1994). Heuristic Evaluation. In Nielsen, J., & Mack, R. L. (Eds.), Usability Inspection Methods. New York: John Wiley & Sons. Nielsen, J. (1994) Usability Inspection Methods, Conference on Human Factors in Computing Systems413-414. Nielsen, J. (1998) Failure of Corporate Websites, Retrieved from July 21, 2009 from http://www. useit.com/alertbox/981018.html. Nielsen, J. (1999) Who Commits the Top Ten Mistakes of Web Design?Retrieved from www. useit.com/alertbox/990307.html. Nielsen, J. (2000). Designing Web Usability. Indianapolis, USA: New Riders Publishing. Nielsen, J. (2003) Misconceptions About Usability. Retrieved from July 20, 2009 from http://www. useit.com/alertbox/20030908.html. Nielsen, J. (2003). Usability 101: Introduction to Usability. Retrieved from July 24, 2009 from http://www.useit.com/alertbox/20030825.html. Nielsen, J., & Mack, R. L. (1994). Usability Inspection Methods. New York: Wiley. O’Connor, J., Galvin, E., & Evans, M. (2004). Electronic Marketing: Theory and Practice for the Twenty-First Century. London: Prentice Hall.
Paas, F., & Firssova, O. (2004). Usability Evaluation of Integrated e-Learning. In Jochems, W., van Merrienboer, J., & Koper, E. J. R. (Eds.), Integrated eLearning: Implications for Pedagogy, Technology and Organization (pp. 112–125). London: RoutledgeFalmer. Palmer, J. W. (2002). Web Site Usability, Design and Performance Metrics. Information Systems Research, 13(2), 151–167. doi:10.1287/ isre.13.2.151.88 Pelham, A. M., & Wilson, D. T. (1996). A Longitudinal Study of the Impact of Market Structure, Firm Structure, Strategy, and Market Orientation Culture on Dimensions of Small-Firm Performance. Journal of the Academy of Marketing Science, 24(1), 27–43. doi:10.1007/BF02893935 Quinton, S., & Khan, M. A. (2009). Generating web site traffic: a new model for SMEs. Direct Marketing: An International Journal, 3(2), 109–123. doi:10.1108/17505930910964777 Ranganathan, C., & Ganapathy, S. (2002). Key Dimensions of Business-to-Consumer Web Sites. Information & Management, 39(6), 457–465. doi:10.1016/S0378-7206(01)00112-4 Reedy, J., & Schullo, S. (2004). Electronic Marketing: Integrating Electronic Resources into the Marketing Process. Florence, KY: Thompson Learning.
Oppenheim, C., & Ward, L. (2006). Evaluation of Web Sites for B2C E-commerce. Aslib Proceedings: New Information Perspectives, 58(3), 237–260.
Rostro, F. R. & Grudzewski, W. M. (2008). Marketing Strategic Planning as a Source of Competitive Advantage for Mexican SMEs.Institute of Organization and Management in Industry (“ORGMASZ”), 1(1), 19-26.
Ordanini, A., & Pol, A. (2001). Infomediation and Competitive Advantage in B2b Digital Marketplaces. European Management Journal, 19(3), 276–285. doi:10.1016/S0263-2373(01)00024-X
Schmees, M. (2003). Distributed Digital Commerce. Proceedings of the 5th International Conference on Electronic Commerce (ICEC2003), 131-137.
485
Designing Digital Marketplaces for Competitive Advantage
Sen, R. (2005). Optimal Search Engine Marketing Strategy. International Journal of Electronic Commerce, 10(1), 9–25. Shabazz, D. (2004). Towards a Better Understanding of e-Marketing Strategy: Past and Present. Services Marketing Quarterly, 26(2), 117–130. doi:10.1300/J396v26n02_08 Simpson, M., & Docherty, A. J. (2004). ECommerce Adoption Support and Advice for UK SMEs. Journal of Small Business and Enterprise Development, 11(2), 315–328. doi:10.1108/14626000410551573 Singh, S. N., & Dalal, N. P. (1999). Web Home Pages as Advertisements. Communications of the ACM, 42(8), 91–99. doi:10.1145/310930.310978 Taylor, M., & Murphy, A. (2004). SMEs and e-Business. Journal of Small Business and Enterprise Development, 11(3), 280–289. doi:10.1108/14626000410551546 Tedeschi, B. (1999). On-Line Merchants Find That a Well Designed Web Site can have a Big Impact on the Bottom Line. E-Commerce Report, New York Times, 30 August 1999, As accessed on August 10, 2009. Tödtling, F., & Kaufmann, A. (2001). The Role of the Region for Innovation Activities for SMEs. European Urban and Regional Studies, 8(3), 203–215. doi:10.1177/096977640100800303 Urwin, S. (2000). The Internet as an Information Solution for the Small and Medium Sized Business. Business Information Review, 17(3), 130–137. doi:10.1177/0266382004237647 U.S. Department of Health and Human Services. (2006 ed.) Research-Based Web Design & Usability Guidelines. Retrieved September 10, 2009, from http://www.usability.gov/pdfs/guidelines. html.
Webb, H. W., & Webb, L. A. (2004). SiteQual: An Integrated Measure of Website Quality. Journal of Enterprise Information Management, 17, 430–440. doi:10.1108/17410390410566724 Weideman, M., & Mgidana, M. (2004). Website Navigation Architectures and their Effect on Website Visibility: A Literature Survey. Proceedings of SAICSIT, 292-296. Weideman, M. & Schwenke, F. (2006).The Influence that JavaScriptTM has on the Visibility of a Website to Search Engines – A Pilot Study. Information Research, 11(4). Wilson, S. G., & Abel, I. (2002). So You Want to Get Involved in E-Commerce. Industrial Marketing Management, 21, 85–94. doi:10.1016/S00198501(01)00188-2 Xing, B., & Lin, Z. (2004).The Impact of Search Engine Optimization on Online Advertising Market. Proceedings of the 8th international Conference on Electronic Commerce, 519-529. Yu, W. D., & Lin, A. (2007). The Design and Implementation of a Search Engine Marketing Management System (SEMMS) Based on Service-Oriented Architecture Platform. IEEE International Conference on e-Business Engineering, 513-519. Zhang, J., & Dimitroff, A. (2005). The Impact of Webpage Content Characteristics on Webpage Visibility in Search Engine Results (Part 1). Information Processing & Management, 41, 665–690. doi:10.1016/j.ipm.2003.12.001 Zhang, P., Small, R. V., von Dran, G. M., & Barcellos, S. (2000). A Two Factor Theory for Website Design. Proceedings of the 33rd Hawaii International Conference on System Sciences (HICSS), 1, 1-10.
This work was previously published in E-Business Issues, Challenges and Opportunities for SMEs: Driving Competitiveness, edited by Maria Manuela Cruz-Cunha and João Varajão, pp. 1-19, copyright 2011 by Business Science Reference (an imprint of IGI Global). 486
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Business Models for Insurance of Business Web Services Liu Wenyin City University of Hong Kong, China & CityU-USTC Advanced Research Institute, China An Liu University of Science & Technology of China, China & City University of Hong Kong, China & CityU-USTC Advanced Research Institute, China Qing Li City University of Hong Kong, China & CityU-USTC Advanced Research Institute, China Liusheng Huang University of Science & Technology of China, China & CityU-USTC Advanced Research Institute, China
ABSTRACT A new business—insurance on business Web services—is proposed. As more and more Web services will be developed to fulfill the ever increasing needs of e-Business, the e-marketplace for Web services will soon be established. However, the qualities of these business Web services are unknown without real experiences and users can
hardly make decisions on service selection. We propose that insurance can help build trust in the market of Web services. In this chapter, we propose three insurance models for business Web services and enabling technologies, including quality description, reputation scheme, transaction analysis, etc. We believe that the insurance of business Web services will help service competition and hence boost the development of more and more business Web services, and the software industry at large.
DOI: 10.4018/978-1-60960-587-2.ch215
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Business Models for Insurance of Business Web Services
INTRODUCTION Electronic Business, or e-Business, is the business that can be conducted via computers and software over information networks. It is a revolutionary business paradigm that has emerged with the advent of the Internet era. It is currently transforming the commercial world. E-Business features automatic information transfer on the Web and automatic information processing at the nodes of the Web, known as Web servers. Software applications are playing critical roles in automating these tasks. Currently, software applications on the Web can deliver a wide variety of solutions to address a wide variety of customer and business needs. Electronic purchase orders, payments, negotiations, collaborative work, stock trading, are just a few examples of these applications in e-Business. What a server can provide can be called services in general. Hence, traditionally, what a Web server can provide has also been called Web services. However, just in the recent several years, Web services have been mainly used to refer to those platform-neutral, self-describing software components that implement business functions and can be automatically discovered and engaged with other Web components to complete complex tasks over the Internet. In other words, Web services are just software components that are networked—instead of applications that are networked. The Web services approach can greatly simplify B2B collaboration and provides a new model for the way businesses share their data and systems. By packaging business processes as software components, Web services will drive much of the still-to-be-developed e-business landscape. Web services will be the main driver of e-business as more business processes are transformed into software elements. Most of such Web services that implement core functions of business will be delivered to customers with service charge and we refer to this kind of Web services as business
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Web services. Gartner says that the market of software as a service (SaaS) will reach $9.6 billion in 2009, a 21.9 percent increase from 2008 revenue of $6.6 billion, and will show consistent growth through 2013 when worldwide SaaS revenue will total $16 billion for the enterprise application markets. Therefore, in the remaining parts of this paper, we also mean “business Web services” when we talk about “Web services”, if it is not clearly specified. Many experts have highly evaluated the impact of Web services, which will fundamentally transform Web-based applications by enabling them to participate more broadly as an integrated component to an e-Business solution. As pointed out by Alexander Linden, research director for Gartner, Web services will facilitate much faster software development and integration, enable businesses to become more agile, and help them focus on their core competencies (Coursey, 2001). Gartner had predicted that software Web services will be the next big business IT trend, picking up speed soon. Several companies have already seen the potential commercial opportunities and have invested largely on the Web services infrastructures, which can facilitate the development, delivery, and integration of Web services. For instances, Microsoft has already released their Web service platform, known as Microsoft.NET (http://www. microsoft.com/net/); Sun Microsystems has also launched their own counterpart project, which is named Sun Open Net Environment, or in short, Sun ONE (http://www.sun.com/sunone/), to compete with Microsoft.NET. Other big companies also join this competition, including IBM Web Services Toolkit (http://www.alphaworks.ibm.com/ tech/webservicestoolkit/) and HP Web Service Platform (http://www.bluestone.com/products/ hp_web_services/). Actually, competition will not be limited on Web services platforms. The Web service technologies can also bring competition among different Web services and service providers (Cheng, Chang
Business Models for Insurance of Business Web Services
& Zhang, 2007). It can be expected that, with the facilities of advanced Web service technologies, more and more Web services of various functions will be developed, deployed, published soon on the Web and users will have more opportunities to choose among these services. The factors that may affect a user’s decision on service selection (from the service marketplace) include service price and quality (we use the term “quality” in this paper to refer to the general performance of Web services, including security, stability, correctness, accuracy, responsive speed, and information processing speed, etc). Just like other kind of services, people have to make tradeoffs between price and quality (Liu et al., 2008). Some services with the same functions or qualities may ask for different prices, which may not be worthy of (or matching) their qualities. It is quite hard for a user to choose a service provider and its service from available ones (of the same or similar kinds). Actually, users may require different levels of qualities of services for different purposes of businesses and different qualities of services should deserve different prices. For those critical businesses, users usually are willing to pay a higher price for a more reliable service, and for non-critical businesses, a moderate quality with a lower price is more preferable. However, users are usually unable to know the qualities of these services in detail before really using them. They usually get to know these services and their qualities from their providers’ own reports or advertisements. No objective, thirdparty, independent report is currently available. Sometimes, quality of service is more critical in the success of a business since potential lost due to quality of service is risky (Kokash & D’Andrea, 2007). Losses caused by the software services can be huge, depending on the role of the services in the entire business. Similar to hardware devices and equipments, software products or services also cannot be technically and completely guaranteed to function as expected all the time. Hence,
the customers of these software products and services are suffering some critical losses while benefiting from their functionalities. Actually, Standish Group has reported that software bugs have cost US companies about 100 billion dollars in 2001. And that does not include the cost of losing angry customers. A concrete example is that, eBay Inc. had ever suffered a 22-hour outage of its E-commerce Web site, traced to a bug in the Solaris operating system (product of Sun Microsystems) that corrupted information in an Oracle database. Sun CEO Scott McNealy had acknowledged a known bug that caused the problem. Due to the impossibility of complete testing (Liu, Jia & Au, 2002), no matter how many time spent on software testing, we cannot test all inputs or all combinations of inputs. This even does not include the case of potential problems of the complicated Internet environment, which makes the testing more difficult. Hence, the situation of buggy software or services is very likely to stay for a long period of time. Before the quality of a service (or the potential risk due to service failure) is completely known, insurance of Web services is absolutely one means among the others to increase the service quality in some sense, at least in the sense that customers can trust the service quality more, though additional cost may be needed. Web service providers can also use insurance to survive the coming fierce competition. Thus, it is necessary for insurance companies to step into this area and cover the insurance of Web services, which will become a new prosperous business to greatly help and push the development and pervasion of insured Web services. We define an insured business Web service as a Web service with a service charge, whose service quality, including operation correctness, response time, and other quantitative performance, is insured such that any deteriorated quality/performance causing any kind of loss from its clients can result in a claim for compensation.
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Business Models for Insurance of Business Web Services
THE STATE OF THE ART OF SOFTWARE INSURANCE The insurance industry began in the middle of 19th century as the engineering insurance emerged with the advent of steam power (Daley, 1999). After that, it took more than one hundred years for the insurance industry to get full development. In the last half century, especially, in the last 20 years, insurance has been expanded to many new areas, e.g., medical insurance and liability insurance, and has become more and more popular in our daily lives and works. However, software, as either products or services, has constantly been out of from the policy coverage of insurance companies. As Voas (Voas, 1999) pointed out, the reason is that the insurers do not have enough time to collect sufficient historical data for actuaries to estimate premium before a software product becomes obsolete. Another reason is that the intrinsic software quality is usually not guaranteed. For example, it was estimated that the well-known Y2K problem might have needed 300~600 billion dollars for the massive repair effort, which might be beyond the capability of the entire insurance industry. The high risk of software mishap has kept insurers away from this area. Only in recent years, several companies (SpamEater. Net, 2004; Voas, 1999) began to offer insurance on certain types of software/service hazards, such as security breach. A general framework for insurance for such cyber-risks has been discussed by Gordon et al. (Gordon et al., 2003). However, the compensation is usually in fixed amounts and the coverage is too limited. Users can hardly benefit from such insurance.
THE SIGNIFICANCE OF INSURANCE ON WEB SERVICES Sriram et al. (Sriram et al., 2001) have predicted that more and more commercial off-the-shelf software component will be developed and put on the
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market for search and integration. To fulfill the ever increasing needs of e-Business, the e-marketplace for Web services will soon be established. It means that someday there will also be a wide variety of Web services available and e-Business systems can automatically search from the market for those that will meet their requirements. Actually, there are already some Web services available (e.g., at www.xmethods.com), which have been developed on several different platforms. However, whatever the market type, the key barrier to entry is trust (Norris, 2000). People especially do not trust those automatic systems they had never experienced before. Linketscher and Child (Linketscher & Child, 2001) have found that users would be nervous relinquishing total control to such systems from the outset. They would like to be able to develop a relationship with the system over time and when trust has been established, to increase delegation and reduce their monitoring of the system. We believe that providing insurance on these systems (or Web services) can help reduce the initial mistrust (or doubt) of their users and gradually establish such trust. Once their reputations have been built, they can also help reduce the insurance premium and eventually benefit the system owners or the service providers.
BUSINESS MODELS OF INSURANCE OF BUSINESS WEB SERVICES Figure 1 is the working model of Web services. In such a model, a Web service is registered in a Web service directory and its client searches from the directory, and requests the service and binds (calls) it within itself. Currently, this working model is supported by the following three core technologies: Web Services Description Languages (WSDL); Universal Description, Discovery and Integration (UDDI); and the Simple Object Access Protocol (SOAP). WSDL is a language that programmers can use to describe the programmatic interfaces
Business Models for Insurance of Business Web Services
Figure 1. The working model of Web services
of the Web services. UDDI lets Web services register their characteristics with a registry so that other Web applications can look them up. SOAP provides the means for communication between Web services and client applications. We propose three business models for insurance of Web services: service provider insurance, service user insurance and service agent insurance. Figure 2 shows the relationship among stakeholders in the service provider insurance model. In this model, the service provider requests insurance for his service in total from the insurance company. Once a service user/client claims for compensation, the provider first claims and obtains
the compensation from the insurance company and then pays to the service user/client. In this case, the service charge includes the premium paid to the insurance company. Figure 3 shows the relationship among stakeholders in the service user insurance model. In this model, the service user/client requests insurance for this service as individual from the insurance company. The service user should claims for compensation from the insurance company directly once a loss happens. In this case, the service charge requested by the service provider can be lower since it should not include the premium. But the insurance company might need to estimate
Figure 2. The business model for service provider insurance
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Figure 3. The business model for service user insurance
the insurance premium for each individual case of the applications of this Web service. Figure 4 illustrates the relationship among the stakeholders in the service agent insurance model. In this model, a new party---web service agent is introduced. Unlike the above two models, web service user and web service provider do not communicate directly in the service agent model but through a web service agent. This is based on the observation that the web service user may not be familiar with the provider. When a user decides to purchase a web service, the information obtained by searching the web service directory is not enough. He would probably need to pay a lot of effort to investigate the details of the service provider and compare between different vendors. In this situation, a delegated web service agent is useful. The web service agent is supposed to be familiar with the web service market and know the advantage and disadvantage of each provider. Hence, when the user raises his requirements, the web service agent is able to provide the user with a good suggestion and specific training for the
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user to consume the web service. Since the web service agent has a profound insight on the market, it can better estimate the risk of using specific web service and buy the suitable insurance accordingly for the user. The process is transparent to the user. The user just needs to provide his requirements, pay the service charges (which includes the premium, and service charge of web service and agent), and receive compensation from the agent if any problem occurs. In other words, the web service agent plays a role similar to the retailer between the factory and the user, and the consulting firm between the market and the client. Each model may be suitable for certain types of services. The service provider insurance model is more suitable for those services focusing on calculation and generation of data in a core business solution. The providers of such services are responsible for the correctness, speed, and other internally responsible qualities of these services. Hence, it is the liability of service providers to buy insurance on such services. For
Business Models for Insurance of Business Web Services
Figure 4. The business model for service agent insurance
example, a service provider can buy insurance on his security service, such as a 128-bit encryption scheme, which will need billions of years to test all the keys to break the code. Although it can also be very lucky to find the key on the first attempt, this possibility is very low (e.g., a billionth per year in this case), and the insurance company can estimate on the premium based on this possibility. The service user insurance model is more suitable for those services focusing on communication, delivery of data, and other externally dependent functionalities. The quality of such services can hardly be controlled by the providers. E.g., the delivery of data can be delayed due to network congestion. Since the data channel is public and involves more factors and can hardly be guaranteed by few providers, users can buy insurance on such services for themselves. Actually, current software insurance practices are mainly of this model. The service agent model is more suitable for those large services which have plenteous budget and require high quality. Generally, in large software projects, investigation to the market to choose a suitable middleware may be crucial to the final quality and cost of the whole project. By delegating this as well as the insurance affair to a
professional agent, the web service user can focus on his own affair. Furthermore, as a third party, the web service agent can provide an objective to the web service quality, which has strong influence on how much insurance that the user should buy in his optimal case.
CASE STUDIES In this section, we use three Web services as examples to show how insurance can help Web services serve users better. They are services that can help filter computer viruses, filter spams from emails sent to users, and outsource software components.
Virus Data Update Service The first example service is related to anti-virus software. In order to do virus scan and cleaning, the software (or its end user) should frequently download the virus update files (DAT files) in order to know what viruses are and what not. Usually the DAT files are owned by the same software company (e.g., McAfee or Symantec). Now in the Web service model, the DAT files can
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Business Models for Insurance of Business Web Services
be provided as an online Web service by a provider independent to all anti-virus software companies. The DAT service provider can focus on this service and hence can do it much better, e.g., provide very quicker update when a new virus emerges. It is quite possible since it can focus all its efforts on this matter. Then all anti-virus software can call this online Web service when they want to do virus scan. Suppose the service is called VirusUp2date (it is just a coincidence if this name has been used by some company). In order to compete with other similar services, VirusUp2date guarantees no virus infections (due to late update of virus data files or unavailability) to end users if they pay a monthly fee (say at $19.99). If a data loss due to this reason happens, VirusUp2date promises to pay $1,000 each time to the end user. Actually, the monthly service fee ($19.99) has already included a premium and hence in overall the VirusUp2date service provider can still make a big amount of money even though it may pay some compensation to some early virus victims. The effect is similar if the service provider pays these premiums to an insurance company and if this insurance company trusts this provider. Actually, this scenario follows the business model of service provider insurance. The effect of the service user insurance model is similar but the end users should pay premiums to and claim compensations from the insurance company directly. One of the key issues here is how to know the exact reason of the data loss since there is another stakeholder got involved—the independent anti-virus software. Is it due to service or due to the anti-virus software? The operating system should keep a log of the usage such that the exact reason should be identified. Another issue is how the insurance companies trust the reliability of the service. In the earlier stage of this service, it may be a good idea for the provider to pay the loss to the end users. At a later stage, after sufficient data are collected, the insurance company can calculate a more reasonable premium value for this service and its compensation scheme and then insure this service.
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Spam Filtering Service The second example service is related to spam filtering. Spam, or junk mail, refers to unsolicited commercial e-mail (UCE) and unsolicited bulk e-mail (UBE), e.g., unsolicited advertisements. Spam spreads everywhere on the Internet nowadays and create problems to most of the e-mail users. Although e-mail companies and standards bodies are trying to work on new ways to deal with this problem, receiving junk mail is still unavoidable with today’s e-mail standards and technology. All parties are trying their best to cut down the number of spam. Hence, anti-spam is also a good business. Actually, some companies, including SpamEater.Net, have already provided services for spam filtering. It charges a monthly fee to end users (or enterprise users) for filtering the spam from the emails sent to the users bypassing its server. However the accuracy cannot be 100%. For example, SpamEater.Net claims that they can catch more than 96% spam with a less than 1% false alarm (i.e., wrongly filter out a good email) rate. SpamEater.Net has already noticed this problem and promise to refund back the money paid if the user is not satisfied with the anti-spam effect within 30 days. This is a kind of insurance in some sense. However, if they are confident in their accuracy, they may still make an insurance scheme, like 1$ payback for each wrong spam identification or even higher for those caused bigger loss or inconvenience. By doing so, the users may want to continue with this service. Another spam filtering service, SpamAssasin (SpamAssasin, 2009), does not really remove suspected spam. Instead, it just labels it with a likelihood tag. The email reader at the client (user) side can do the final action to these suspected emails. Since the accuracy is not 100%. The end user can also do necessary actions to manually check those emails with lower likelihood. In this sense, if an insurance scheme is applied, the risk is not high and therefore the premium can be much lower for each wrongly identified email. But the overall
Business Models for Insurance of Business Web Services
monthly service fee should also be lower since the end user may have to conduct manual check and hence reduce his/her productivity.
Software Components Outsourcing Services Nowadays, outsourcing has become a very popular way to software development due to the large laboring expense differences between different countries and areas. According to the statistics studies by the marketing researchers, the US IT offshore outsourcing market is growing in a rate of 14.4% annually and will nearly double to 14.7 billion dollars by year 2009 (IDC, 2005), and it is reported (Global Outsourcing Report, 2005) that three quarters of US companies outsourced some or all their information technology activities in year 2004, and this percentage is expected to increase furthermore in 2005. Nearly three quarters of the international software outsourcing companies expect to grow their revenues by 11% within the next 12 months (ComputerWeekly, 2005). Web service, as a platform neutral technology, is a very convenient and reliable framework to the outsourcing industry. The whole software project can be divided into several functional components by the development company, and some of them could be outsourced, which could be implemented in web service technology. Since the web service technology has few requirements on caller components, such a way can utilize many existing software modules, without consideration of their platforms. For example, there may be some existing modules in Linux and using web service technology can reduce the migration/re-development cost greatly. Furthermore, the whole infrastructure, e.g., the hardware, of the components could be outsourced. In such a software development process, every task could be much more specialized, and dispatched to an experienced or low cost company. The developing efficiency could be boosted while the cost could be reduced. However, web service components also bring the risk into the whole
project. The quality of outsourced components is beyond the control of the project development company, and there may be some interoperability bugs between the distributed components. Though the full system testing could fix the bugs within and between components and reduce the risk, it is not sufficient to guarantee the overall quality. In this situation, the web service insurance of component outsourcing could be introduced to further guarantee the quality of the whole product, such that the project development company can be compensated in case of any individual or interoperability problem occurs.
KEY TECHNOLOGIES FOR INSURANCE OF BUSINESS WEB SERVICE In either model, the key technologies are how to estimate the premium for an insured Web service and how to determine the loss and compensation due to this service. Other related technologies, including how to test/evaluate Web services qualities, how to improve Web services qualities, and how to build and manage the reputation record of Web services, are also important in the insurance business of Web services. How to estimate premium? Although the role of a Web service in a business solution can also affect the premium, we focus on the influence of the quality of service in this paper. As we mentioned before that the reason why insurance companies do not want to get involved in software insurance is that the insurers do not have enough time to collect sufficient historical data for actuaries to estimate premium before a software product becomes obsolete. While in the case of Web services, they will not expire since they will frequently be upgraded and maintained as the same services. Through a period of time in service, the reputation of the services can be built. Currently, most Web services are generally not concerned about the level of quality of service presented to
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their users/client. However, the quality of service that is experienced by its users will become a dominant factor for the success of a business Web service. First of all, the principle quality attributes these users can perceive include those related to the “responsiveness” of the service, i.e., the service availability and timeliness. A service that is frequently unavailable may have the effect of tarnishing the reputation of the service provider or result in loss of opportunity. Secondly, security level of the services is also a reputation. Those websites frequently be hacked will definitely lose reputations. Finally, other qualities, including functionality correctness and stabilities, caused by software bugs can also affect the reputation of a service. Hence, Web service quality test/ evaluation is a key technology for insurance of Web services. For example, active monitoring and user feedbacks could be used to evaluate nondeterministic qualities such as service availability and timeliness (Liu, Ngu & Zhang, 2004; Jurca, Binder & Faltings, 2007) Related technologies that could help users experience better services, e.g., work load balancing and exception notification of Web services (Liu, Jia & Au, 2002), are also useful in the insurance business of Web services. Insurance premium can also be set differently at different times, like temporal fares for telephone systems. Some service can guarantee more immediate response at non-busy period, e.g., in weekends; but others may heavily rely on human supports, which are more expensive in weekends. Either they can change such service prices or they can change the insurance premium. How to determine loss and compensation? Every transaction of the Web service execution, including the situation of the environment, e.g., input/output, time, network status, etc., should be logged such that the execution of this service can be repeated. Once a claim on loss compensation happens, the cause of such loss can be found through transaction analysis and the loss and compensation can then be calculated according to related insurance terms. For example, Liu et
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al. (2008) proposed a methodology to predict the expected loss and profit of service-oriented business applications. Moreover, transaction analysis can also help find other quality problems of the Web services. Currently, since there is no exercise of such insurance compensation, there should be much research work to do in this aspect for the insurance business of Web services. How to build and manage a reputation record of (insured) business Web services? A historical record of users’ rating can help. A mechanism similar to Platform for Internet Content Selection (PICS) can also help. For new services, third party testing can also help build initial quality rating. The insurance company can also hold a website like www.methodx.com and rate all services for users to look up and choose among them. The original quality level claimed by the service providers can also be used to compare with the real qualities and reputations. Both the quality level (in all aspects) and the reputation should be included into the description of services. Currently, WSDL and UDDI specifications do not support QoS description and query, but they provide extension mechanisms that can be used to advertise QoS. For example, service providers can attach execution price to the operation elements in the WSDL to specify how much the service consumer should pay to the service provider when invoking these operations. In addition, UDDI can be extended to support publish and query QoS (Zhou et al., 2004). However, these approaches need to modify WSDL and UDDI. To follow the design strategy, separation of concern, which is widely accepted in the service oriented architecture, some other approaches are proposed recently. For example, Web services agreement specification (Andrieux et al., 2007) is a piece of work that allows service providers to advertize QoS separately. We hope that the future versions of WSDL, UDDI, and SOAP can also include or help automation of contract signing, accepting the insurance terms and prices, negotiations, payment, fulfill-
Business Models for Insurance of Business Web Services
ment reputation records, etc. In this case, decision on service selection can also be automated.
CONCLUSION We have proposed the insurance on business Web services as a new business, which can help both to build trust in the e-marketplace of business Web services and to ensure lossless e-Business. Three insurance models for business Web services—service provider insurance, service user insurance and service agent insurance—have been proposed. Their enabling technologies, including reputation scheme, quality description, transaction analysis, have been discussed. We believe that the insurance of business Web services will help service competition and hence boost the development of more and more business Web services, and the software industry at large. To further promote business Web services and the software industry at large and reduce the risk of e-Business (including risks of both service providers and services customers), we also advocate the impact of governments and legislatures on Web service insurance and Web service qualities. The governments’ attitudes to the Y2K problem have successfully helped the world pass that time smoothly. We hope they can help again in the insurance of business Web services.
ComputerWeekly. (2005). UK jobs to benefit from outsourcing growth. Retrieved from http:// www.computerweekly.com/Article138576. htm?src=rssNews Coursey, D. (2001). The four biggest biz-tech trends of the coming decade. ZDNet/AnchorDesk, http://www.zdnet.com/anchordesk/stories/ story/0,10738,2816779,00.html Daley, A. (1999). Towards safer electrical installations: The insurer’s view. In Proceedings of IEE Colloquium on toward safer electrical installations - learning the lessons (pp. 1-6). Global Outsourcing Report. (2005). Release of the Global Outsourcing Report. Retrieved from http:// pdfserver.prweb.com/pdfdownload/220341/ pr.pdf Gordon, L. A., Loeb, M. P., & Sohail, T. (2003). A framework for insurance for cyber-risk management. Communications of the ACM, 46(3), 81–85. doi:10.1145/636772.636774 IDC. (2005). US off shoring to double to $14.7 billion by 2009. Retrieved from http://www. financialexpress.com/fe_full_story.php?content_ id=102877 Jurca, R., Binder, W., & Faltings, B. (2007). Reliable QoS Monitoring based on client feedback. In Proceedings of International Conference on World Wide Web (pp. 1003-1011).
REFERENCES
Kaner, C. (1997). The impossibility of complete testing. Software QA, 4(4), 28–44.
Andrieux, A., Czajkowski, K., Dan, A., Keahey, K., Ludwig, H., Nakata, T., et al. (2007). Web services agreement specification (WS-Agreement). http://www.ogf.org/documents/GFD.107.pdf
Kokash, N., & D’Andrea, V. (2007). Evaluating quality of web services: a risk-driven approach. In Proceedings of International Conference on Business Information Systems (pp. 180-194).
Cheng, S., Chang, C. K., & Zhang, L.-J. (2007). Towards competitive web service market. In Proceedings of International Workshop on Future Trends of Distributed Computing Systems (pp. 213-219).
Linketscher, N., & Child, M. (2001). Trust issues and user reactions to e-services and e-marketplaces: a customer survey. In Proceedings of 12th International Workshop on Database and Expert Systems Applications (pp. 752-756).
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Business Models for Insurance of Business Web Services
Liu, A., Li, Q., Huang, L., & Liu, H. (2008). Building profit-aware service-oriented business applications. In Proceedings of the International Conference on Web Services (pp. 489-496).
Rossi, M. A. (2001). Stand alone e-commerce market survey. IRMI Expert Commentary. Retrieved from http://www.irmi.com/expert/articles/ rossi004chart.asp
Liu, W., Jia, W., & Au, P. O. (2002). Add exception notification mechanism to Web services. In Proceedings of International Conference on Algorithms & Architectures for Parallel Processing (pp. 483-488).
SpamAssasin. (2009). Retrieved from http:// spamassassin.apache.org/
Liu, Y., Ngu, A., & Zeng, L. (2004). QoS computation and policing in dynamic web service selection. In Proceedings of the International Conference on World Wide Web (pp. 66-73). Muse, D. (2001). Gartner says Web services coming soon. Internetnews/ASP News, Oct. 10, (http://www.internetnews.com/asp-news/ article/0,3411_901271,00.html). Norris, M. (2000). Survival in the eBusiness jungle. Software Focus, 1(1), 23–26. doi:10.1002/15297950(200009)1:13.0.CO;2-A PICS. (Platform for Internet Content Selection (PICS)). Retrieved from http://www.w3.org/PICS/
SpamEater. Net (2009). Retrieved from http:// www.spameater.net. Sriram, S., Kumar, A., Gupta, D., & Jalote, P. (2001). ComponentXchange: a software component marketplace on the Internet. In Proceedings of the International Conference on World Wide Web (pp. 1098-1099). Voas, J. (1999). The cold realities of software insurance. IT Professional, 1(1), 71–72. doi:10.1109/6294.774795 Zhou, C., Chia, L.-T., & Lee, B.-S. (2004). QoSaware and federated enhancement for UDDI. International Journal of Web Services Research, 1(2), 58–85.
This work was previously published in Service Intelligence and Service Science: Evolutionary Technologies and Challenges, edited by Ho-fung Leung, Dickson K.W. Chiu and Patrick C.K. Hung, pp. 261-272, copyright 2011 by Information Science Reference (an imprint of IGI Global).
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Chapter 2.16
Business Model of Internet Banks Jean-Michel Sahut Amiens School of Management, France
ABSTRACT
INTRODUCTION
Internet is not simply one more distribution channel among the multi-channel strategies used by the financial industry; it is fostering new “e-Business Models” such as Internet-primary banks. However, in spite of its strong development potential, this type of bank has often achieved a weak breakthrough onto this market and shows modest financial results. The goal of this chapter is to study the “e-Business Model” of Internet-primary banks and to determine if it can perform better than the “Business Model” of a traditional bank.
The development of Information and Communication Technologies, and more specifically Internet, has increased competition in the banking sector and brought about the separation of production from the distribution of financial services and products. The arrival of Internet has given a new dimension to the convergence and the deconstruction of the value chain by making it possible to lower information costs, and by reducing barriers to entry into the financial sector.
DOI: 10.4018/978-1-60960-587-2.ch216
Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
Business Model of Internet Banks
Convergence has taken place on three levels: •
•
•
convergence of offers; by widening their product range, banks and insurance companies have entered into direct competition, convergence of the sub-sectors of the financial industry; banking, insurance and asset management activities increasingly overlap, financial institutions and non-finance actors have become more closely linked
Previously, deconstruction came mainly from the offer side, i.e. from the emergence of new entrants (e.g. consumer credit). With Internet, it comes from the demand side: customers can choose the best supplier depending on their preferences (e.g. real estate loans, online brokering). With the appearance of banks which mainly sell their services by Internet (Internet-primary banks), the major competitive advantage of traditional banks - a network of local branches - has been diminished for certain types of customer. These customers have been attracted by the prospect of accessing their accounts and carrying out bank transactions 24 hours a day, seven days a week without having to go anywhere, and sometimes with a better quality of service than was offered by a bank branch. Online brokers were the first to offer private individuals the opportunity to invest on the stock exchange via Internet. Moreover, the vast majority of Internet-primary banks charge lower account administration fees than those charged by traditional banks. This has often been used as an argument to attract customers in a nearly saturated market. The goal of this chapter is to study the “Electronic Business Model” of Internet-primary banks and to determine if it can out perform the “Business Model” of a traditional bank. After having defined the Business Model and e-Business Model (e-BM) concepts, we will analyze the e-BM of online banks as an economic model through the study of its revenue sources, costs incurred, and how it
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creates value for customers. Then, we will question its strategic development prospects. Lastly, we look at Internet’s impact on performance in the case of both traditional institutions as well as Internet-primary banks.
BUSINESS MODELS IN THE FINANCIAL SECTOR Business Models and Electronic Business Models The objective of this section is to better understand the “Business model” (BM) concept. Many papers have already been written which attempt to clarify this concept due to its dynamic dimension. We will look at how this concept has been applied to electronic services: the “Electronic Business Model” (e-BM). One of the first workable definitions of this concept was provided by Timmers (1998). He defines a BM as being: •
• •
the architecture for product, services and information flows including a description of the model’s various business actors and their roles; a description of the potential benefits for each business actor involved; a description of the sources of revenue.
Other writers have since expanded this idea. Linder and Cantrell (2000) state: “It’s a rich, tacit understanding about how all the pieces work together to make money”. These authors confirm this vision of BMs by the fact that 62% of the company directors they interviewed found it difficult to describe their BM over and above its success1. While for Loilier and Tellier (2001), a BM can be likened to a firm’s value creation method. In fact, defining what a BM is can be a difficult exercise because this concept is associated with dynamic dimensions such as value creation,
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competitiveness and organizational change. Porter (2001) in particular described this concept as “fuzzy”, “superficial”, and “theoretically difficult to grasp”. Magretta (2002) specifies that the usual error with respect to BMs is to regard them as being a strategy: “Business modeling is the managerial equivalent of scientific method - you start with a hypothesis, which you can test in action and revise when necessary”. For this author, the BM describes in system form, how the firm manufactures and sells a service or a product. Equally, for Afuah and Tucci (2003), the BM is a basket of activities which allows a business to earn money in a sustainable way. Along the same lines, Demil et al. (2004) approach it as an intermediate concept used to make strategies operational. They define the BM as all the choices which a firm makes in order to generate revenue. Whatever definition you choose, it is important to dissociate the concept of BM from that of strategy and to regard it as a dynamic concept which is constantly reconsidered according to market conditions, technology, regulations, inter-company relations, etc. The development of ICTs, and specifically the Internet, has generated new activities resulting either from technological innovation (for example Internet portals), from the deintegration of value chains (e.g. loan comparison sites), or from new channels (e.g. online brokers). These activities then brought about the appearance of new BMs or redefined those which already existed (Applegate, 2001). For example, Internet strengthens the Research and Development function (a support service according to Porter’s value chain concept) by helping in the collective design of products between sites and participants in the value system, by listing the concepts accessible to all the branches of the business and by giving access in real-time to all the sales and services databases. Also, Internet makes it possible to reduce order transmission times by automating both customer and supplier contacts and enables a truly integrated management system to be put in place. The impact
of such practices on work efficiency creates an additional added value for the firm (Porter, 2001). The term “Electronic Business Model” (eBM) has since appeared to qualify the BM of these new activities. As the concept is derived from that of BMs, it is also difficult to define and can be understood in different ways. This is why many authors have tried to define it using a heuristic approach, in other words starting from their observations of the market. The result has been a wide diversity of studies which cover both the number of e-BMs identified and their characteristics: Timmers (1998) counted eleven different types, Loilier and Tellier (2001) counted five and Rappa (2001) nine. Even if many similarities are identified, convergence between these typologies started to take place in 2001 with the analysis of value creation. Indeed, Timmers (1998) has a vision which focuses on the internal dynamics of e-BMs and on their interaction with the environment. As for Mahadevan (2000), he prefers a “macro” vision in which e-BMs depend on the types of relations which exist between actors from the same market. Applegate’s article (2001) marks a transition by putting forward a very precise classification of e-BMs concerning value creation for the e-BM (sources of differentiation, revenue and costs incurred), but the value created for customers is not a central issue. It wasn’t until Novak and Hoffman’s article (2001) that the different dimensions of e-BMs were brought closer together. Novak and Hoffman present “Customer Model Integration” in which the definition of an e-BM is jointly linked to both value models for customers and revenue models. More precisely Novak and Hoffman identify the twelve value models shown in Table 1. However, these revenue or value models created for customers cannot be regarded as exhaustive for two primary reasons: •
Given the difficulty of defining only one typology of e-BM, it is possible to present
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Figure 1. Values, revenues and customer model integration •
as many models as there are combinations of sources of revenue; the appearance of a new e-BM means the existence of new
original combination of sources of revenue, even the creation of a new element for generating revenue; It would seem that revenue sources other than those presented by Novak and Hoffman can exist, for example the sale of customer data (e-mail, addresses, purchasing behavior, etc), a purchase made in a store following the consultation of the product on Internet, etc.
Moreover, the type of activity strongly influences the structure of an industry (Porter, 2001). As a result e-BMs are very different from one sector to another. Hereafter, we will look at the financial sector and at the different e-BMs which
Table 1. Value models for customers (Novak & Hoffman, 2001) Value Models
Value created for the customer
Example of e-BM
Brokerage
Facilitates bringing buyers and sellers together (B2B, B2C or C2C).
VerticalNet PaperExchange.com
Content
Meets all types of customers’ information needs.
About.com
Search
Targets the information the customer is looking for.
Google.com
Incentive
Gives customer access to certain services and products after they have accumulated points (loyalty scheme)
Beenz.com MyPoints.com Webmiles.com
Freeware
Customers are given free access to software which is useful to them.
Blue Mountain Freemerchant.com
Communication
Provision of an e-mail service or free computer-to-phone calls.
Net2phone
Control
Pressure from customer groups concerning protection of their private life, intellectual property rights of content and the boycott of unethical content is a source of customer value.
Anonymizer Copyright Agent
Outsourcing
The customer is directly connected by Internet-ERP to the producer for greater control over his requirements.
I Print.com servicelane.com
Entertainment
The concept is based on the offer of information specific to a field of specific interest.
Sportingbet.com eMode
Transaction
The customer benefits from access to stores not (or not easily) accessible geographically.
Retromodern.com
Affiliate
This model is mainly for SMEs which want to make themselves known on the web. Payment for advertising costs is limited to the number of clicks to their ad banner.
Amazon.com Art.com PayTrust American Express
Community
Provides like-minded people with range of services relating to their center of interest as well as services for putting people in contact and exchanging information (forum, email, etc)
Epinions.com Participate.com
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characterize it, and more specifically, at Internet banks.
Typology of E-Business Models for Financial Services Due to their apparent contradictions, it is difficult to come to any firm conclusions on the positioning of Internet-primary Banks compared to more general e-BMs. On the other hand, if one focuses on the specific sector of financial services, a greater convergence of e-BMs can be clarified by studying the work of Muylle (2001) and Sahut (2001) and Horsti et al. (2005). Between these different e-BMs for financial services, there exist several forms of exchange, partnership and strategic alliances. In particular, portals offer virtual banking agencies, aggregators and financial actors in general a space to advertise and be referenced. Moreover, certain portals
develop co-branding strategies (coproduction) by coming together with certain producers to produce or sell joint services. Thus while calling into question the comparative advantages of traditional actors, the financial service sector on Internet has become very competitive and obliges actors to innovate by creating alliances, partnerships or mergers making it possible to build up new comparative advantages, to catch up with competitors, or to break into new markets. The movement which recently saw a consolidation of online brokers in Europe illustrates this phenomenon. Between 2002 and 2006, 22 brokers were taken over or merged in France (Les Echos, n° 19783, 30/10/2006). Moreover, it is difficult to understand the financial equilibrium of e-BMs because not only have they brought about new commercial concepts but, above all they have provided a new logic for value creation. In the start-up phase, companies in the
Table 2. Typology of e-BMs for financial services Type
Characteristics
Revenue Created
Value Model
Vertical Portal Financial Portal [MUY 01] Portals [SAH 01]
They mainly offer general or specialized information services in several fields. Some have created “personal finance spaces”, like Yahoo with “Yahoo Finance”, which proposes, in addition to informational services, transaction services (credit card, account aggregation, advice about stock market investments, etc).
Advertising, Affiliation, Commission, Sale of products and services.
Brokerage; Content; Search; Communication; Community; Affiliate, Transaction.
Aggregator [MUY 01] Aggregators: • Brokers • Quoters [SAH 01]
These are sites whose role is to act as online intermediary between different actors. “Quoters”, contrary to brokers, do not carry out the transaction, they are infomediaries which bring business to virtual agencies, or compare offers for consumers.
Brokers: Sale of products and services. Quoters: Commission, Advertising, Affiliation.
Brokers: Content, Transaction. Quoters: Content, Brokerage.
Speciality manufacturer [MUY 01] Suppliers [SAH 01]
These are producers of financial services (like Visa, equity funds, traditional banks, etc) which distribute them through their own network, or external networks (resale or co-branding).
Commission, Sale of products and services.
Outsourcing, Transaction.
Company sites [ Company web sites [MUY 01] Virtual agencies (banks, insurance, or broking on line) [SAH 01]
These are online banking, investment or insurance services. The sites with the best performance offer, in addition to advanced information and transaction services, customer relations management services (tools to help in decision-making, online advice, development of personalized products, etc). The main difference with brokers/aggregators is that they are not satisfied to aggregate the existing offer. They mainly sell products in their brand.
Product sales and services, Commission, Advertising.
Outsourcing, Transaction, Content, Brokerage, Community.
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e-business field generate large negative free cash flows for a certain length of time, before turning round and progressing exponentially. This type of cycle which is more marked than for traditional industries can be explained in particular through the theory of the network economy (Shapiro and Varian, 2003). In fact, the main specificities of e-BMs which develop in an economy based on networks show that: •
•
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profitability is only achieved by developing the use of a good or product (one speaks about “an experience good”) because the consumers are not motivated to buy or carry out transactions on line when they have doubts about the quality of the products or the operation’s level of security. Once the “reputation” of the e-BM has been made, this type of psychological barrier decreases; profitability is determined by “the attention” paid to the e-BM. In fact, Internet provides an important mass of information with rapid, permanent and inexpensive access. Many BMs therefore try to benefit from this by setting up an informational website. Thus, gradually, competition in the physical markets has moved onto Internet. However, there are so many websites for companies selling the same products that saturation has been reached: far from increasing their visibility, these companies have provoked an “attention shortage”. It is therefore imperative for an online bank wishing to “grab the attention” of customers from other banks already offering Internet Banking services, to propose superior value to that offered by its competitors. This requires big investment (in the development of services and the acquisition of customers) and explains the high level of negative free cash flows suffered by e-BMs at the beginning of their life cycle;
•
profitability depends on the technological infrastructure and the capacity to give added value to the offer on Internet. In fact, contrary to a BM, e-BMs are characterised by the high costs of technological infrastructure (computers, software, data-base servers, computer maintenance, network equipment, etc.). This technological infrastructure can be the basis for the acquisition of a competitive advantage as soon as it improves capacity for storing, researching, sorting, filtering and sending out information (Applegate 2001). It increases, at the same time, the value of the information itself (and the service provided to the customers in general). But the high fixed cost that technology represents can not be amortized until a critical number of customers has been reached. However, such an acquisition takes a long time to achieve.
Lastly, we can notice that the profits expected by Internet Banking services are more indirect, in other words they come from efficiency to the detriment of productivity in value. Even before the appearance of Internet banks, Rowe (1994) had noticed that the IT expenditure of French banks was increasing faster than productivity. He saw this phenomenon as confirmation of “the Solow paradox”. Should we therefore call into question Internet’s productivity and its contribution as a channel of distribution? Will the traditional banks continue to perform the same with or without Internet? What are an online bank’s real prospects for profitability?
IMPACT OF INTERNET BANKS ON PERFORMANCE After having analyzed different e-BMs, their sources of revenue, their costs and their method of creating value, we study the profitability of Internet banking services.
Business Model of Internet Banks
The few studies which have looked into this aspect are divided into two categories: those interested in the introduction of Internet banking services on the profitability of traditional banks (known as click-and-mortar), those comparing the performance of Internet banks with other banks. The first studies tried to show whether or not the introduction of Internet banking services in traditional banks in the USA increased their profitability (Egland et al, 1998; Carlson et al, 2000; Furst et al, 2002). But, these services represented too small a proportion of the activity to really influence the profitability of these banks. Similarly, Sullivan (2000) showed that the multichannel banks of the 10th Federal Reserve District do not appear more profitable on average when they have a transactional website. In Italy, Hasan et al. (2005) demonstrate a positive relationship, over the 1993–2001 period, between Internet adoption and the profitability of click-and-mortar banks. More recently, Degado et al. (2007) studied the impact of the adoption of Internet Banking services on the performance of 72 commercial banks in Spain over the period 1994-2002. They conclude that the effects of this adoption take time to appear and result in a fall of overhead expenses. One needs 1 year and a half to notice a significant increase in ROA (return on assets) and three years for ROE (return on equity). In this context, Internet is used more as a complementary channel than as a substitute to the physical branches. These contrasting conclusions are debatable because they are based on average results obtained at the beginning of the development of these services. Thus they depended more on the customers’ adoption of Internet than on the real contribution of Internet Banking services on the overall profitability of the bank. In fact, these studies have mainly highlighted the problems of measuring the profitability of these services. The second wave of studies tried to free themselves from these limits by defining a broader measurement of the performance of Internet banks compared to that of the other banks. We are go-
ing to concern ourselves mainly with this second type of study. But beforehand, we will look at performance measurement in the banking sector.
How to Measure Profitability? Demirguc-Kunt and Huizinga (2000) highlight that “the approach to profitability in banking and finance is characterized by its complexity and its multiform aspect”. They explain their analysis through five main points: •
•
•
•
•
The merging of “raw material”, “money deposited”, “final product” and “money loaned”: the fungibility of money makes it more complicated to calculate profitability due to the difficulty of dissociating resources from their uses; The impossibility of establishing provisions of profitability in the short term because of the existence of several uncertainties which are part of bank-customer relations (loan prepayment, litigation, change of address, etc.); The difficulty in establishing profitability per product because traditional banking is based on linked product sales which have high indirect costs; The strong regulation (or commoditization) of some products: an innovation in the banking sector cannot be patented and can easily be copied; The strong constraint of rigidity of costs in banking which are mainly “overhead costs” and indirect. Defining the profitability of a product, a customer segment or a center of responsibility (branch, area, etc) is a complicated task and depends on method of indirect cost allocation.
For all these reasons, banks performances are assessed ex-post starting from general accounting indicators such as the level of deposits, the losses on loans, the ROA (return on assets) or
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Business Model of Internet Banks
the ROE (return on equity). But, in the case of a comparison of the performance of newly created Internet banks with that of traditional banks, these indicators (ROA and ROE) are not very relevant because the net income can be negative (because the activity is starting up), and they do not take into account other elements such as “possible market power” (Shepherd et al., 1999). Among the other methods used, the most famous is the profit efficiency model (DeYoung, 2005). This method allows us to identify between the technology-based scale effects and the technology-based experience effects, showing whether the profitability gaps evaporate as Internet banks grow larger, gain experience and capture economies of scale. For Cyree et al. (2008):“Profit efficiency indicates how well management produces outputs for a given input mix along with other market characteristics and is measured as the distance from the best-practice frontier”. Moreover, this methodology captures “technology-based experience” and “technology-based scale” effects.
Do Internet Banks Give a Superior Performance? On the basis of the idea that “experience” could be a determinant of cost reduction and production efficiency, DeYoung (2001) presented a first comparison of the ROA between newly chartered banks (newly created traditional banks) and Internet banks (Internet-primary banks) between 1997 and 1999. He notes that the Internet-primary banks show significantly lower profits than those achieved by the newly chartered banks because of difficulties generating deposit accounts and higher non-interest expenses. The gap is very wide during the first two years but is reduced quickly thanks to technology experience effects. The growth rate of the Internet-primary banks declines to meet that of the newly chartered banks. The banks then progress at the same rate except for the deposit-toasset ratio. The maturity effects are similar for the
506
two types of bank. Lastly, Internet-primary banks, just like the newly chartered banks, can only reach the same profitability (ROA) as traditional banks at the end of approximately 10 years of activity (DeYoung, 2001). In a second study, DeYoung (2005) confirms these results by using the profit efficiency model. He shows that the Internet-primary bank startups tended to underperform the branch bank startups over the period 1997-2001 in the USA. This seems to call into question the viability of the Internet bank e-BM. One can conclude from this that the success of an Internet bank is only possible if it reaches a sufficient level of economy of scale and has efficient management practices, particularly for cost management. The more recent results from Cyree et al. (2008), which study the performance of Internetprimary banks and newly chartered traditional banks from 1996 to 2003, provide more details of these performance gaps with certain conflicting conclusions to the studies of DeYoung (2001, 2005). Their univariate analysis shows that Internet-primary banks have lower ROA, ROE, loan losses, and net-interest margin, compared to newly chartered traditional banks. But, they indicate that the Internet-primary banks are more profit efficient than the newly chartered traditional banks. In fact, several elements can justify the performance gap of Internet banks with traditional banks especially when starting up (Les Echos n° 19586, 18/01/2006): •
•
Incompressible structural costs: These are expenses inherent to all banking activities and are mainly composed of high fixed charges and costs of IT development. In the case of Axa Banque, these IT costs account for 30% of total operating costs, A high turnover of advisers and the difficulty of arranging schedules spread over 12 or even 24 hours to man a hot-line,
Business Model of Internet Banks
•
A very high cost of customer acquisition: For Axa Banque, this cost must not exceed 300 euros per customer recruited to be profitable. This stumbling block can only be overcome with a diversification of customer recruitment methods, loss leaders, and precise customer targeting.
•
On the other hand, other factors are favorable to the development of online services including (Les Echos n° 19586, 1/18/2006; EFMA, 2007): •
•
•
•
the specific characteristics of customers who use on line banks: 20% are on average expert users in Europe (48% in the Netherlands). This clientele is autonomous in decision making, they are mainly men, managers, with a high income who subscribe regularly to financial products on line; Internauts are more profitable than noninternaut customers: In the case of Axa Banque, their internaut customers bring in 15% more revenue than the non-internaut customers as soon as they join and achieve the target revenue after 18 months instead of 30 months on average; the potential of productivity for online banks is higher than that of the traditional bank: in the case of Axa Banque, the productivity by employee is 405 customers (which is a higher performance than the average French bank) with a productivity potential which can reach double that of a traditional bank; the structure of the net banking income from an online bank is very different from that of a traditional bank: for example, Axa Banque draws 70% of its net banking income from payment methods. The remaining 30% comes from the banking offer (credit, savings and stock exchange transactions) which have strong development potential;
the backing of a big group means that certain costs can be minimised by benefiting from a phenomenon of material synergy (compensation operations, debit and credit cards, etc.) and intangible synergy (experience, notoriety, etc.). For example, the Midland Bank provided First Direct with a back office of 7 000 ATMs in Great Britain which was the basis of its success. The risk of the cannibalisation of channels, competition between the online bank and the mother company (traditional bank) is low because the banks attract a different clientele.
In fact, these studies and research show that the success of an online bank is mainly conditioned by: •
•
Building a strong competitive advantage which lies in access to customers and a good understanding of their behaviour and tastes. Many banks believed that the competitive advantage depended on the technology used; however, technological advances are very quickly copied. This advantage makes it possible to control the cost of acquiring a new clientele. The support of an institution delivering financial services (insurance, supermarkets, banks, etc), the creation of an attractive loss leader (savings accounts with a high interest rate like ING Direct, etc) or an innovating service (for example: online brokers at the end of the 90s, etc) are the main means of building up a competitive advantage; The difficulty of maintaining continuous investments without making profits forces certain online financial operators to merge with each other. This was specially the case of certain online brokers who, when they started dealing on the stock exchange, were able to collect large funds. But, as their period of investing at a loss lengthened, they had difficulties accessing other
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•
investments. The only way out for those in most difficulty was to merge. One finds several examples in the case of online banks such as the absorption of ZeBank by Egg (which gave it access to the French market), the merger of First-e (Ireland) and Uno-e (Spain), etc; A strong brand which inspires trust from potential customers and which also helps reduce the cost of acquiring new customers.
These conditions highlight the difficulty of creating an online bank for actors from outside the banking sector.
CONCLUSION In conclusion, we have shown that the dynamic of the financial services sector on Internet is intensifying and that a certain structuring of the sector can be observed. Indeed, the actors are looking for new “revenues-created values” combinations following the example of online brokers, such as Schwab, who have become information providers for the portals, and are trying to reach a critical size via mergers and strategic alliances. However, the shape of an e-BM specific to online banks hasn’t clearly emerged. Despite the strong development potential of online banks, their survival as a specific e-BM can be questioned because of their weak breakthrough onto the international and national markets and their modest financial results. The most successful actors have concentrated on market niches, like ING Direct in Europe. One can question the capacity of online banks, as e-BMs, to remain banks which are virtual, independent and generalist. In this case, it is extremely probable that they will have to develop their own physical sales network (like Schwab) or enter into partnerships with traditional establishments. Otherwise, they are likely to disappear or be ab-
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sorbed by traditional banks and become gradually integrated into their multi-channel strategy.
REFERENCES Afuah, A., & Tucci, C. (2003). Internet Business Models and Strategies. New York: McGraw-Hill. Applegate, L. M. (2000). Emerging e-Business Models: Lessons from the Field. Boston: Harvard Business School Press. Berger, A. N., Demsetz, R. S., & Strahan, P. E. (1999). The consolidation of the financial services industry: Causes, consequences, and implications for the future. Journal of Banking & Finance, 23(2-4), 135–194. doi:10.1016/S03784266(98)00125-3 Carlson, J., Furst, K., Lang, W., & Nolle, D. (2000) Internet Banking: Markets Developments and Regulatory Issues. Office of the Comptroller of the Currency, Economic and Policy Analysis Working Papers 2000-9. Cyree, K.B., Delcoure, N., & Dickens, R. (2008). An examination of the performance and prospects for the future of internet-primary banks.Journal of Economics and Finance, June. Delgado, J., Hernando, I., & Nieto, M. J. (2007). Do European Primarily Internet Banks Show Scale and Experience Efficiencies? European Financial Management, 13(4), 643–671. doi:10.1111/j.1468036X.2007.00377.x Demil, B., Lecoq, X., & Warnier, V. (2004).Le business model: l’oublié de la stratégie? 13th AIMS Conference, Normandie, 2-4 June. Demirguc-Kunt, A., & Huizinga, H. (2000), Financial structure and bank profitability. World Bank, Policy Research Working Paper Series 2430.
Business Model of Internet Banks
DeYoung R. (2001), The financial progress of pure-play internet banks Bank for International Settlements, Monetary and Economic Department, BIS Papers n°7, 80-86. DeYoung, R. (2005). The Performance of Internet-Based Business Models: Evidence from the Banking Industry. The Journal of Business, 78(3), 893–947. doi:10.1086/429648 EFMA (2007). Online consumer behaviour in retail financial services, with Novametrie, Capgemini and Microsoft, EFMA Studies, December Egland, K. L., Robertson, D., Furst, K., Nolle, D. E., & Robertson, D. (1998). Banking over the Internet. Office of the Comptroller of the Currency. Currency Quarterly, 17, 25–30. Essayan, M., Rutstein, C., & Wetenhall, P. (2002). Activate and Integrate: Optimizing the Value of Online Banking. Boston: Boston Consulting Group. Furst, K., Lang, W. W., & Nolle, D. E. (2002). Internet banking. Journal of Financial Services Research, 22, 95–117. doi:10.1023/A:1016012703620 Hasan, I., Zazzara, C., & Ciciretti, R. (2005). Internet, Innovation and Performance of Banks: Italian Experience. unpublished manuscript. Hensman, M., Van den Bosch, F. A., & Volberda, H. (2001). Clicks vs. Bricks in the Emerging Online Financial Services Industry. Long Range Planning Journal, 34, 33–235. Hernando, I., & Nieto, M. J. (2007). Is the Internet delivery channel changing banks’ performance? The case of Spanish banks. Journal of Banking & Finance, 31(4), 1083–1099. doi:10.1016/j. jbankfin.2006.10.011 Horsti, A., Tuunainen, V. K., & Tolonen, J. (2005). Evaluation of Electronic Business Model Success: Survey among Leading Finnish Companies.Proceedings of the 38th Annual Hawaii International Conference on System Sciences, Volume 7.
Linder, J., & Cantrell, S. (2000). Changing Business Models: Surveying the Landscape. Accenture Institute for Strategic Change. Loilier, T., & Tellier, A. (2001). Nouvelle Economie, Net organisations. Paris: EMS Eds. Magretta, J. (2002). Why Business Models Matter? Harvard Business Review, (May): 90–91. Mahadevan, B. (2000). Business Models for Internet-based e-Commerce: An anatomy. California Management Review, 42(4), 55–69. Muylle, S. (2001).e-Business in Financial Services”, KPMG,Retrieved from http://www.einvestments.be/KPMG.pdf. Novak, T.P., & Hoffman, D.L. (2001). Profitability on the Web: Business Models and Revenue Streams. eLab Position Paper, Owen Graduate School of Management, Vanderbilt University, January: 9-18. Porter, M.E. (2001).Strategy and the Interne. Boston: Harvard Business Review, June. Rappa, M. (2001)Business models on the Web. Retrieved from http://digitalenterprise.org/models/models.html. Rowe, F. (1994). Des Banques et des Réseaux: Productivité et Avantages Concurrentiels. ENSPTT-Economica, janvier: 246-247 Sahut, J.M. (2000), L’impact de l’Internet sur les métiers de la banque. Les Cahiers du Numérique, septembre: 158-162. Sahut, J.M. (2001).Vers une révolution du secteur bancaire ? La Revue du Financier n°131, 34-38. Sahut, J. M. (2004). Why does SSL dominate the e-payment market? Journal of Internet Banking and Commerce, 9(1). Shapiro, C., & Varian, H. R. (2003). Information rule. Ethics and Information Technology, 5(1).
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Business Model of Internet Banks
Sullivan, RJ (2000), How has the adoption of internet banking affected performance and risk in banks? Federal Reserve Bank of Kansas City, Financial Perspectives, December: 1-16.
Giordani, G., Floros, C., & Judge, G. (2009). Internet banking services and fees: the case of Greece. International Journal of Electronic Finance, 3(2). doi:10.1504/IJEF.2009.026359
Timmers, P. (1998). Business models for electronic markets. Electronic Markets, 8(2), 2–8. doi:10.1080/10196789800000016
Krostie, J. (1996). Using Quality Function Deployment in Software Requirements Specification. Andersen Consulting and IDI. Oslo, Norway: NTNU.
ADDITIONAL READING Berry L., A., Parasuraman, V., & Zeithaml V. (1990). Delivering Quality Service: Balancing Customer Perceptions and Expectacions. The Free Press, March. Chen, S.-H., & Chen, H.-H. (2009). The empirical study of customer satisfaction and continued behavioural intention towards self-service banking: technology readiness as an antecedent. International Journal of Electronic Finance, 3(1). doi:10.1504/IJEF.2009.024270
Liljander, V., van Rien A., & Pura M. (2002). Customer Satisfaction with e-Services: The case of an Online Recruitement Portal. Published in the Yearbook of Services Management 2002 – e-Services. Migdadi, Y. K. A. (2009). Quantitative Evaluation of the Internet Banking Service Encounter’s Quality: Comparative Study between Jordan and the UK Retail Banks. Journal of Internet Banking and Commerce, 14(1). Sahut, J. M. (2006). Electronic wallets in danger. Journal of Internet Banking and Commerce, 11(2).
Claessens, S., Glaessner, T., & Klingebiel, D. (2002). Electronic Finance: Reshaping the Financial Landscape Around the World. Journal of Financial Services Research, 22(1), October, Available at SSRN: http://ssrn.com/abstract=382932
Sahut, J. M. (2008). Internet Payment and Banks. International Journal of Business, 13(4).
Dong, J., & Bliemel, M. (2008). Strategies for Increased Integration of Online and In-Branch Services of Banks in Canada. Journal of Internet Banking and Commerce, 13(3).
Sahut, JM. (2008). On-line Brokerage in Europe: Actors & Strategies. Journal of Internet Banking and Commerce, 8(1), June 2003
Ghobadian, A. (1994). Service Quality: Concepts and Models. International Journal of Quality & Reliability Management, 11(9). doi:10.1108/02656719410074297 Ghobadian, A., Speller, S., & Jones, M. (1994). Service quality: concepts and models. International Journal of Quality & Reliability Management, 11(9). doi:10.1108/02656719410074297
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Sahut, J. M. (2008). A TAM extension for e-wallet adoption: The case of Moneo. Journal of Internet Banking & Commerce, 13(1).
Sahut, J. M., & Hrnciar, H. (2003). Problématique de la qualité des services d’Internet Banking. Gestion, 2000(2). Sahut, J. M., & Jegham, M. (2008). ICT acceptation: The case of CRM project. Gestion, 2000(2). Sahut, JM., & Kucerova, Z. (2005). Improving End-User Experience via Quality Performance Evaluation: Internet Banking Case. La revue du Financier, October.
Business Model of Internet Banks
Sahut, J. M., & Kucerova, Z. (2005). Enhance Internet Banking Service Quality with Quality Function Deployment Approach. Journal of Internet Banking and Commerce, 8(2). Schaechter, A. (2002)., Issues in Electronic Banking: An Overview. IMF Policy Discussion Paper No. 02/6, Washington: International Monetary Fund. Settlements, Bank for International (2001), Electronic Finance: A New Perspective and Challenges. BIS Paper No. 7, November, Available at SSRN: http://ssrn.com/abstract=1187567 Tam, Ch. T. W., Leung, T. K. P., & Wong, Y. H. (2003). An integrated model of online customer loyalty. [Brussels, Belgium.]. Proceedings of ABAS International Conference, 2003(July), 11–13. Van Riel, A. C. R., Liljander, V., & Jurriens, P. (2001). Exploring consumer evaluation of eservices: a portal site. International Journal of Service Industry Management, 12(4).
KEY TERMS AND DEFINITIONS Bank Performance: Any of many different mathematical measures to evaluate how well a company is using its resources to make a profit (Farlex dictionary). Business Model: All the choices which a firm makes in order to generate revenue.
Click-and-Mortar Banks: Traditional banks. Distribution Channel Strategy: The route by which a product or service is moved from a producer or supplier to customers (bnet dictionary). Electronic Business Model: Qualify the BM of electronic activities. Information and Communication Technology (ICT): “Is an umbrella term that covers all technical means for processing and communicating information. While this technically encompasses pre-digital technologies, including paper-based writing, it is most often used to describe digital technologies including methods for communication (communication protocols, transmission techniques, communications equipment, media (communication)), as well as techniques for storing and processing information (computing, data storage, etc.) The term has gained popularity partially due to the convergence of information technology (IT) and telecom technology.” (Wikipedia) Online Banking: A system allowing individuals to access to remote bank services, via the internet and/or phone. Profitability: The ability to earn a profit. Pure Player Banks: All the bank activity is only accessible via Internet oand/or phone.
ENDNOTES 1
Study carried out by Accenture Institute for Strategic Change.
This work was previously published in E-Banking and Emerging Multidisciplinary Processes: Social, Economical and Organizational Models, edited by Mohammad Ali Sarlak and Asghar Abolhasani Hastiani, pp. 101-113, copyright 2011 by Business Science Reference (an imprint of IGI Global).
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Chapter 2.17
A Reverse Auction-Based E-Business Model for B2C Service Markets1 Tobias Kollmann University of Duisburg-Essen, Germany Matthias Häsel University of Duisburg-Essen, Germany
ABSTRACT LetsWorkIt.de is a German B2C platform for different kinds of service and handcraft orders. Based on the concept of reverse auctions, demanders compose descriptions of the required services to place orders on the platform. The supplier bidding lowest at the end of the auction obtains the right to carry out the order. Drawing upon and widely confirming existing theories on e-marketplaces, this chapter examines the underlying e-business model and the competitive strategy of LetsWorkIt. The case provides evidence
that the reverse auction-based intermediation of handcraft and service orders is suitable to form the basis of an e-marketplace and points out that for such ventures, a combination of public relations, performance marketing, and cooperation, represents an ideal strategy to increase the number of demanders and suppliers. Moreover, the case suggests that, depending on the business model, it may be feasible to concentrate marketing activities on one of these two customer groups, since LetsWorkIt has managed to achieve a significant number of successful, high-quality auctions by primarily aligning its competitive strategy with the demand side.
DOI: 10.4018/978-1-60960-587-2.ch217
Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
A Reverse Auction-Based E-Business Model for B2C Service Markets
COMPANY OVERVIEW AND HISTORY In early 2004, Alexander Bugge, Carsten Seel and Jörg Holtmann were wondering whether, in spite of the burst of the dot com bubble, an Internet-based business could become the center of their professional life. At that time, the idea of LetsWorkIt.de, a German business-to-consumer (B2C) auction platform for different kinds of service and handcraft orders, was born. Service auctions to be placed on the platform would include, for instance, gardening, wallpapering a flat, repairing a car, or printing advertising brochures. Although there was already a first-mover offering such auctions, the corresponding market was hardly existent and the publicity for placing service and handcraft orders on the web was still low. Bearing in mind the success of eBay and the fact that the target group of craftsmen was becoming increasingly affine to the World Wide Web, the three entrepreneurs began to develop their business idea and formulated their mission: “to become the leading electronic marketplace for service and handcraft orders and to provide our customers a high level of quality at a fair price.” According to their respective competencies, Bugge, holding a degree in business administration, took over the areas of finance and marketing, whereas Seel, an experienced web developer with a degree in communication science, was responsible for the technical implementation issues and content management. Holtmann, also holding a degree in communication science, would focus on customer relations and PR work. However, having these highly complementary skills would not guarantee LetsWorkIt’s activities from a liquidity point of view. On the one hand, there was a significant need for investing in technology and in establishing the company; whereby, on the other hand, the free-cash-flow could not be too negatively influenced. Consequently, the founders decided to manage without salary in the beginning phase, and each of them subscribed a limited amount of capital. Moreover, they were
supported by a business angel, an external expert on e-marketplaces who helped them from both a financial and a professional point of view. In order to minimize development costs, Seel went for conducting the technical implementation of LetsWorkIt.de and the underlying database on his own, while his two colleagues carefully designed the electronic business processes to be implemented. For the server-side programming of the platform, Seel applied Microsoft’s ASP technology. “Concerning hardware, we decided to fall back on a quality service provider ensuring that the platform would be available twenty-fourseven”, Seel remembers. After less than half a year of exhaustive work, LetsWorkIt.de went online on July 1st, 2004. The main concept is as follows: demanders position orders in form of reverse auctions and compose descriptions of the required services. The duration of an auction can be between one day and six weeks. Suppliers then bid on these orders. The supplier bidding lowest at the end of the auction obtains the right to carry out the order – and is legally obliged to do so since there is a legally binding contract (i.e. a work or services contract) between demander and supplier. This contract is based on the description of the demander and the price of the supplier. Demanders include private persons, enterprises and tradesmen. Suppliers, however, are required to be enterprises or registered craftsmen and have to verify their accreditation. “LetsWorkIt provides some obvious advantages for both demanders and suppliers”, Holtmann states. For the demander, these advantages include: • • • • •
Saving money when placing handcraft and service orders, Being sure to pay the lowest price, Finding a service provider or craftsman very easily and quickly, Avoidance of unpleasant negotiations, and Reaching a wider range of service providers or craftsmen.
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Advantages for the supplier include: • • •
Acquiring orders in a simple and innovative way, Increasing the workload of the own business, and Saving advertising and distribution costs.
Acting as an intermediary between supply and demand that offers aggregation and matching functions, LetsWorkIt.de can be referred to as an electronic marketplace (Bakos, 1997; Kollmann, 2000; Dai & Kauffmann, 2002). “Our unique selling proposition is that placing orders on our platform is free of charge”, Bugge stated when he was asked about competitive strategy. Even after a successful auction procedure there are no costs for the demander. Solely the service providers or craftsmen are charged with a intermediation fee after a successful auction. The amount of this fee for the intermediation of supply and demand depends on the contract value. Payment flows and activities between demander, supplier and LetsWorkIt.de are illustrated in Figure 1. The founders were aware that the success of LetsWorkIt would not only depend on the successful realization of their business model, but also on the continued development and appropriate adjustment to market demands. Since the start Figure 1. Payment flows and activities between demander, supplier and LetsWorkIt.de
of the operating business, the three founders therefore, as described in the remainder of this chapter, continued their activities focusing on three main areas: • • •
Acquiring investors and cooperation partners (Bugge), Improving and extending platform functionality (Seel), and Investing high efforts in marketing and public relations (Holtmann).
In the first quarter of 2005, both the number of registered participants and LetsWorkIt’s revenues grew by approximately 350%. Having obviously proven the potential of the concept of service and handcraft auctions, LetWorkIt.de became a public limited company (GmbH) on May 1st, 2005. Three months later, the platform had about 12,000 registered demanders and 5,500 registered suppliers. On average, there were 1,800 new auctions per month. The auction success rate figured 60%. The continuing success of LetsWorkIt is based on two interrelated factors – their innovative business model and their efforts in cooperation, marketing and public relations. Building on current literature, the two subsequent sections will consequently analyze the electronic business model and the competitive strategy of LetsWorkIt.
ELECTRONIC BUSINESS MODEL LetsWorkIt.de is a true company of the so-called Net Economy, i.e. a pure Internet-based business (Kollmann, 2006): With the heightened importance of the factor information, new possibilities resulted with respect to how enterprises create value (Amit & Zott, 2001; Lumpkin & Dess, 2004). An enterprise can create customer value not only through physical activities on the real level, but also through the creation of value on the electronic level (Weiber & Kollmann, 1998). These electronic value creation activities are,
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however, not comparable with the physical value creation activities presented by Porter (1985), rather they are characterized by the way in which information is used. In the case of LetsWorkIt.de, these activities include the collection, systemization, selection and distribution of information on orders and marketplace participants. An electronic value chain manifests itself through these specific activities of creating value that originates in and impacts only the Net Economy.
plex and varied, and the corresponding markets seem to be highly fragmented, platforms such as LetsWorkIt.de can add value by simplifying information search, respectively, reducing search costs (Giaglis, Klein, & O’Keefe, 2002; Bakos, 1997). According to a classification suggested by Kollmann (2006), the resulting customer value comprises these three aspects: •
The Electronic Creation of Customer Value The basis of a Net Economy venture’s income must be formed by the added value for the customer. In the case of LetsWorkIt, customer value is not necessarily just the service or handcraft order. “In the first instance, value rests in our platform functionality related to an auction and the availability of information – regardless of temporal and spatial restrictions”, Bugge explains. “This electronic product is made possible only through the use of information technologies”, he further elaborates. Thus, the creation of customer value only occurs at the electronic level. This does not mean that LetsWorkIt does not require real resources such as personnel. LetsWorkIt also possesses a physical value chain, which plays, however, only a supporting role in order to successfully offer the electronic creation of value (Weiber and Kollmann, 1998). Such physical activities include the permanently staffed customer hotline – which, however, results in additional charge for the customers. Building upon the underlying value chain in the Net Economy, it must also be determined what form of electronic value is created in the eyes of the customer for which he would be prepared to pay, i.e. what makes LetsWorkIt.de attractive from the customer’s point of view. When implementing their idea, the most pertinent question for the three founders was: What kind of value is created for the demanders and the suppliers? As purchase decisions in the service sector are com-
•
•
Overview value: The aspect that LetsWorkIt.de provides an overview of a large amount of information that would otherwise involve the arduous gathering of information. By structuring service and handcraft orders in many different categoriesa and presenting them in a common format, overview value is especially created for the suppliers looking for orders they can bid on. Also, demanders might browse the categories, orders, as well as detailed supplier profiles to get a first impression of the marketplace and its participants. Selection value: By submitting database queries, consumers can locate exactly the desired information/services more quickly and, thus, more efficiently. LetsWorkIt. de creates selection value by offering a search form that allows querying the database by keywords, order category, or zip code. Furthermore, after registering to the platform, suppliers have the possibility to apply for an e-mail-based “auction alarm” functionality that automatically informs them about new orders that are requested in their specific region. Matching value: This aspect deals with the ability, when using an online offer, to more efficiently and effectively match supply and demand (Bakos, 1998). LetsWorkIt. de collects service offerings and the demanders’ wishes, coordinates the participants and offers them a suitable trading partner. In the optimal case, both market partners (i.e. demanders and suppliers) will
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be matched with the best overall market allocation. Considering these aspects, it becomes obvious that LetsWorkIt.de creates several different types of value and that both overview value as well as selection and matching values are created. In combination, these values result in an increased market transparency, an optimal price finding, greater efficiency through electronic order completion, cutting down transaction costs and convenience. Still, the question how these values are created remains. For the purpose of answering this question, the previously introduced electronic value chain can be applied. The electronic value chain separates an e-business into strategically relevant activities in order to better understand cost behavior and recognize present and potential sources of differentiation (Kollmann, 2006). Thus, the electronic value chain represents respectively those value activities which, for example, involve collecting, systemizing and distributing information. Through specific value activities, an electronic information product is created that presents value for which the LetsWorkIt customer is willing to pay. Therefore, the electronic value chain embodies the total value that is generated by the individual electronic value activities plus the profit margin. The electronic creation of value on LetsWorkIt. de is depicted in Figure 2: The business idea is based upon reversely auctioning all kinds of service and handcraft orders on an e-marketplace (founder view). The electronic value creation is directly reflected in the resulting added value for the user (customer view) and refers centrally to the overview, selection and matching functions. An example: Both the supplier and the demander would be prepared to pay for the matching function, whereas only the supplier would be eventually willing to pay a fee for the selection function. In order to realize this creation of value, LetsWorkIt’s founders applied the value chain concept to identify particularly those value activities that form
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the core of value creation. Simplified, information on an order must be first collected; secondly, the location and the demander of the order must be determined and, in a third step, systematically stored in the database. Using this database, information is then offered to the potential suppliers who can formulate a query using appropriate search mechanisms. If a match is found through the query process, then the accompanying information pertinent to the request is exchanged. If all of this occurs, the final product is a transaction. The electronic process of creating value is thus collecting information, processing and transferring it (company view).
Electronic Value Creation Processes As already noted, the business principle of LetsWorkIt.de applies reverse auctions for finding the lowest price for a given service or handcraft order. In opposite to forward auctions (as, for instance, known from eBay), the respective electronic value creation processes usually begin with the demander who places an order on the platform. While the price is decreasing, it is the suppliers who have to bid. So far, downward price auctions have mainly been applied in the business-to-business (B2B) area, in particular for direct material purchasing (Emiliani, 2000). In this context, LetsWorkIt.de represents one of the first business models transferring the concept to B2C, with private consumers initiating the pricing process. The respective electronic value creation involves both the core and service processes (Kollmann, 2006). Core processes such as placing an order (demander side) or bidding on an order (supplier side) hold a true function in the creation of value, whereas service processes support the business processes along the value chain. Service processes are for instance initiated in connection with the rating system of LetsWorkIt.de: After an order has been completed, demanders are asked to fill out an electronic evaluation form on the
A Reverse Auction-Based E-Business Model for B2C Service Markets
Figure 2. Electronic creation of value on LetsWorkIt.de (according to Kollmann, 2006)
supplier. The data collected is then used to update the supplier profile and finally displayed when the supplier is engaged in subsequent auctions. Within the reverse auction principle, LetsWorkIt.de features two different auction types: standard auctions and, so-called “selective” auctions. A standard auction features the placement of an auction for a certain time period, and every registered supplier is able to place a bid on the auction. At the end, the supplier bidding lowest obtains the job. Consequently, the demander is required to accept the supplier’s offer and pay the agreed price. In contrast, a selective auction features the possibility to reject bidders. Before being able to place a bid on a selective auction, the bidder has to address the demander and request participation; the demander may then decide whether the bidder meets the specific requirements. During
the auction, bids are hidden. However, suppliers are informed in case of being underbid and may then bid again. Figure 3 illustrates the concept of selective auctions. For both auction types, the electronic value chain process begins with the input of information. In order to provide the targeted added value (i.e. the matching function), the required information must first be gathered. In the next step, the information is processed internally such that it can then be transferred on to the customer in the desired form as information output and in a way that specifically adds value for that customer. With this in mind, the processes of LetsWorkIt.de can be characterized as follows: •
Information collection: The first step involves gathering relevant data that serves
Figure 3. Concept of selective auctions
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•
518
as information input for the additional creation of value. LetsWorkIt.de features category-specific central questions when placing new auctions: By specifying details for the order, e.g. relating to material, period and particularities, the demander provides potential bidders with a basis for calculating their bids respectively deciding whether to apply for a selective auction or not. An important detail is the maximum price the demander is willing to pay. Based on this price, suppliers can place bids on the requested services. In the case of a selective auction, information collection also includes asking demanders which of the respective suppliers should be selected. Prior to this, the demander also needs to provide the suppliers with information pertaining to how he values some nonprice attributes (Beil & Wein, 2003), such as experience and proficiency. Seel states that the question behind gathering information on LetsWorkIt.de is: “who demands what at which level of quality and who offers this for the lowest price?” Information processing: The second step involves the conversion of the collected data into an information product for the customer. For LetsWorkIt, information processing includes matching the demanders’ requests with supplier profiles (as it is the case for abovementioned auction alarm functionality), matching the suppliers’ search queries with appropriate orders that match their capabilities, as well as comparing the incoming bids. Building on the concept known from eBay, an incoming bid is passed to a bidding agent that treats the bid as the minimum price at which the bidder would accept the order and automatically decreases the bid by the amount necessary to win the auction. Also, with respect to the rating system, information processing in-
•
cludes updating supplier profiles with the abovementioned evaluation results. Information transfer: The third step involves actually implementing the newly acquired or confirmed knowledge obtained from collected, saved, processed and evaluated data for the benefit of customer. The result is an output of information which creates value. Outputs of LetsWorkIt.de include displaying auction details, sending e-mails that inform suppliers about appropriate orders (auction alarm) and being underbid, as well as displaying the member profiles of suppliers that have placed a bid respectively applied for a selective auction. As only the bidder with the lowest bid at the end of the auction wins the order, information transfer finally also includes informing both demander and supplier(s) about the end of the auction.
It is important to recognize that it is not sufficient for LetsWorkIt.de to go through this sequence of electronic value creation just once. Rather, it is a continual process of acquiring, processing and transferring information, which is necessary. This is even more essential, as the underlying information – such as the current price – is constantly subject to change. The most important value creation processes of LetsWorkIt. de are summarized in Figure 4.
Proceeds Model An e-marketplace operator’s income may result from fixed participation fees or variable, transaction-based provisions, as well as from banner advertising, cross-selling or selling gathered market information. Direct proceeds of LetsWorkIt result from successfully completed auctions and are variable provisions. For the demander, all services offered by LetsWorkIt are free of charge. Successful bidders, however, have to pay a com-
A Reverse Auction-Based E-Business Model for B2C Service Markets
Figure 4. Electronic value processes of LetsWorkIt.de
Table 1. Proceeds model of LetsWorkIt.de Order volume (€)
Commision fee (+VAT)
=
100,000.01
1,00%
mission fee based on the order volume. Table 1 shows the proceeds model of LetsWorkIt.de.
COMPETITIVE STRATEGY Due to the nature of electronic processing, customer’s switching costs of switching from one e-marketplace to another are nearly none (Porter, 2001). The decision to participate on a platform is more or less made by mouse-click (Kollmann, 2000). Due to the fact that switching barriers for
the market they were operating in are so low, the three founders soon realized the necessity to differentiate their electronic product from the competition.
Market Situation Shortly after LetsWorkIt.de entered the German market for service and handcraft auctions as a second-mover in summer 2004, two additional competitors joined the market. As a result of this development, competition between the four site operators took on a greater importance. “At the beginning, our competitors were as weak as ourselves”, Bugge stated. “Hefty competition, however, became quickly visible. What’s more, we feared that a big-budget player such as eBay could enter the market”, he further elaborated. “Fortunately, this has not happened up to now.” However, competitors have become significantly stronger. Although all competitors follow the same
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they helped to form the market for service and handcraft auctions. Actually, they did a good deal making the concept of reverse auctions known to the general public.” However, Holtmann and his two friends were aware that they were operating in a winner-takes-all market and that, on the long run, there would be no reward for being second best. Consequently, they made some important business decisions with respect to their competitive strategy. The main question was fairly simple: How could LetsWorkIt.de promote its performance and sustain competitive advantage in spite of its low marketing budget?
main principle, they differ in the variety of services and in details relating to the bidding process: •
•
•
Undertool.de, founded in October 2003, became the first German e-marketplace for service and handcraft orders. Although the venture held the highest number of registered customers, they were unable to transfer this advantage to a higher number of running auctions. Jobdoo.de launched its e-marketplace in August 2004, facing a similar market position as LetsWorkIt. After one year of operating business, the venture counted 11,000 registered customers and an average of 1,000 running auctions – and thus held a leading position until the market entrance of the fourth player in the market. My-Hammer.de is the youngest, and soon also became LetsWorkIt’s most threatening competitor. It went online in May 2005, accompanied by a big advertising campaign on federal TV stations. With an average of 1,000 running auctions in September 2005, the venture had quickly catched up with both LetsWorkIt.de and Jobdoo.de.
Bilateral Marketing Particularly at the beginning, LetsWorkIt.de was confronted with start-up problems that were related to critical masses, as e-marketplace success requires a critical mass of both supplier and demander participation (Yoo, Choudhary, & Mukhopadhyay, 2002). For the supplier, a certain number of demanders of a certain quality had to be present to make the marketplace attractive. At the same time, a certain number of suppliers with certain characteristics had to exist so that demanders enter the marketplace. In other words, an e-marketplace faces a two-sided network effect, with demanders reacting to suppliers, and suppliers reacting to demanders (Galbreth, March, Scudder, & Shor, 2005). It is characterized by the presence of two distinct sides whose ultimate benefit comes from interacting through the marketplace platform. Consequently, also LetsWorkIt needed to address this “chicken and-egg problem” and be careful to get both sides on board (Rochet &
Table 2 summarizes the competitive situation in September 2005. Due to high marketing expenses in the following months, My-Hammer. de soon reached higher brand awareness than its competitors and very quickly attained a leading market position. “First, we thought that we would not been able to keep up with them”, Holtmann remembers. “But then I realized that their TV spots were also boosting our sales – probably because
Table 2. LetsWorkIt.de and its three main competitors in September 2005 Undertool.de Platform launch
October 2003
Jobdoo.de August 2004
My-Hammer.de May 2005
LetsWorkIt.de July 2004
Users
70,000
11,000
1,000
14,000
Auctions per month
1,000
1,200
1,000
1,000
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Tirole, 2003). The need for a balanced ratio of marketplace participants implicates a constant bilateral marketing strategy that is aiming at both demanders and suppliers (Kollmann, 1998). The three founders were well aware of this necessity. However, a custom-tailored marketing for both target groups would have gone far beyond their financial means. “Marketing was already making up 65% of our expenses. We had to carefully examine what to spend our money on”, Holtmann says. Consequently, the founders conducted a thorough analysis of their customers, especially concerning their role on the e-marketplace. Bugge: “We were thinking about whether – from the marketing point of view – one target group might be more relevant than the other.” They soon realized that it would be reasonable to focus their activities on the demand side. The rationale behind this decision is as follows: •
•
First, in the real transaction process, the demander turns into a customer of the supplier. As the suppliers are per se interested in acquiring new orders on a regular and recurring basis, as well as increasing the workload of their own business, they do not necessarily need to be attracted to LetsWorkIt.de. In fact, ignoring LetsWorkIt as an additional distribution channel would be unwise for the suppliers. Second, suppliers participating on the competitors’ platforms do not harm
•
LetsWorkIt’s revenues, as they may bid on multiple orders at the same time. Demanders, however, can place a single order only on one of the platforms, and thus represent a required, but not sufficient criterion for turning an auction into revenue. Third, the orders placed by the demanders are directly visible on the platform and thus represent the main criterion that customers and the media apply to compare the available e-marketplaces for service and handcraft orders.
“Actually, suppliers are not the bottleneck. If one disregards auctions that have an unattractive starting price, our regular suppliers do fully cover the demand”, Bugge concludes. “Although a quantitative definition of balance currently lacks empirical data, our estimations propose that a sufficient ratio between suppliers and demanders is one to three.” Comparing demanders and suppliers from different perspectives, Table 3 summarizes the rationale for focusing on the demander as the primary target group. As a consequence, LetsWorkIt particularly aligned its whole marketing mix with the demander. At the beginning, increasing the sheer quantity of new auctions and getting ahead of the competition in terms of numbers became the focus of LetsWorkIt’s competitive strategy. As described in the following, the respective
Table 3. Comparing demanders and suppliers Perspective
Demander
Supplier
Customer Relationship
Registered participant
Registered participant
Transaction process
Real recipient of service
Real renderer of service
Matching process
Places order
Bids on orders
Frequency
Irregular and infrequent need
Regular and recurring need
Market participation
One order, one platform
Multiple orders, multiple platforms
Transparency
Directly visible on platform
Only indirectly visible
Revenue
Uses LetsWorkIt free of charge
Pays for successful intermediation
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communication and distribution strategies of LetsWorkIt.de grounded on three distinct building blocks from the very beginning: public relations, performance marketing and cooperation.
Public Relations “We have strongly benefited from the mass media”, Holtmann replies when asked about public relations. Due to several reports on federal radio and TV stationsb as well as in the pressc, the concept of service and handcraft auctions in general, as well as LetsWorkIt.de in particular, became known to the wide public. “After appearing on TV, the number of auctions was boosting by up to 300%”, Holtmann explains. The same phenomenon could be observed when the press dealt with the subject. To fully leverage the potential of the mass media, the founders soon decided to engage a PR agency that continually releases news items about LetsWorkIt.de. Bugge: “This was certainly one of our most important marketing decisions. They are really doing a good job.”
Performance Marketing Despite the success of the abovementioned PR campaigns, the major advertising channels for LetsWorkIt.de are, of course, web-based. One of the major advantages of online advertising is the possibility to measure detailed metrics for the respective channel, such as the number of page impressions and click-trough rates. The utilization of advertising channels that are paid on a performance basis can be referred to as performance marketing. For LetsWorkIt.de, this concept became the basis of a very cost-effective marketing controlling: “From the very beginning, we strongly aligned our online marketing campaigns with clear-cut performance targets”, Bugge explains. In order to measure a channel’s performance, this first means defining a target cost for each metric – for example, a target cost of €2.00 for a new registration. Thereafter, the
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campaign is continually adjusted regarding both qualitative and quantitative aspects in order to generate as many prospects as possible within the given campaign budget. LetsWorkIt.de focused on two main performance marketing measures: •
•
Keyword advertising: Via Google’s Adwords program, LetsWorkIt purchased sponsored links that guarantee a top Google rank in searches for relevant keywords like “Handwerk” (handcraft) or “Dienstleistung” (services). This classical Internet advertising effort was especially intended to raise overall brand awareness for LetsWorkIt.de. Affiliate advertising: Instead of implementing a software solution to control online advertising channels, LetsWorkIt decided to make use of affilinet.de, an affiliate network provider that offers a standardized solution to efficiently acquire many small advertising partners and effectively control the performance metrics of the respective channel. LetsWorkIt’s affiliate program includes miscellaneous banners and links that can be integrated into the affiliates’ websites. The program features attractive remuneration terms that have already attracted a lot of affiliates (€2.00 for a new registration, €10.00 for a new registration followed by an auction placement). The program started in August 2005. Two months later, a total of 1,300 affiliates had mediated 250 registrations and 60 auctions.
After some time, LetsWorkIt was able to identify notably diligent affiliates and individually approached them in order to transform the respective business connections into more effective, strategic partnerships. “Beyond that, I began to personally approach web portals offering information and services related to the topic of service and handcraft orders”, Bugge remembers. Strategic cooperation soon became the third
A Reverse Auction-Based E-Business Model for B2C Service Markets
building block of LetsWorkIt’s communication and distribution strategy.
Strategic Cooperation As a lack of financial means often leads to deficits in the areas of sales and market positioning, cooperation strategies play an elementary role regarding the growth of Internet-based ventures (Kollmann & Häsel, 2006a; Kollmann & Häsel, 2006b; Volkmann & Tokarski, 2006). Cooperative agreements with topic-related partner sites thus have become a fundamental building block of LetsWorkIt’s competitive strategy, intended to decrease the high acquisition costs per customer. Table 4 lists the most important partner sites cooperating with LetsWorkIt.de. With each partner, LetsWorkIt.de negotiated one of the following cooperation modes, depending on the scope of integration into the partner’s website: •
•
•
Banner/link integration: This merely refers to integrating a banner, button or a text link into the partners website, pointing to LetsWorkIt.de. Editorial integration: The partner seamlessly integrates an editorial content that actively promotes LetsWorkIt.de. Content frame sharing: This cooperation mode features the possibility of directly displaying a list of current auctions
•
on the partner’s website. Depending on the website visitors, the partner may follow different strategies: Being redirected to LetsWorkIt.de, potential bidders can directly bid on the respective orders. Potential demanders, on the other hand, can experience the different kinds of auctions placed on the e-marketplace. Co-branded marketplace: Applying this cooperation mode, LetsWorkIt offers its partners to adapt the LetsWorkIt.de platform and offer it as a supplementary service. The affiliate can choose between either a co-branded version of the marketplace opened in a new browser window (with the website header and colours adapted to the partner’s look and feel), or a version that is directly integrated into the partner website. Both versions are hosted on LetsWorkIt’s web server.
Applying these cooperation modes, the partners enhance their own offers by a complementary product that represents an added value for their customers. In banner/link or editorial integration modes, the partner is additionally remunerated for new registrations, respectively, registrations followed by an auction placement. Particularly in connection with the co-branded marketplace mode however, the partner is remunerated by revenue sharing, i.e. the revenue generated on the
Table 4. Cooperation partners in January 2006 Partner
Platform description
Cooperation mode
ImmobilienScout24.de
Real estate marketplace (catalogue)
Co-branded marketplace
Immoauktionen.de
Real estate marketplace (auctions)
Banner/link integration
Bauen.com
Building portal
Content frame sharing
Bauen.de
Building portal
Co-branded marketplace
Quoka.de
Publishing house (small advertisements)
Link integration
Sebworld.de
Insolvencies, mortgages and auctions
Link integration
Meldebox.de
Moving house portal
Content frame sharing
Baubeteiligte.de
Building/real estate web directory
Editorial integration
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basis of the adapted platform is shared between LetsWorkIt.de and its strategic partner. The ratio depends on the acquisition potential of the partner. “Current models feature ratios between 30% and 50% for the partner”, Bugge says.
Product Strategy Besides the quantitative problem of acquiring marketplace participants, e-marketplaces also needed to provide for qualitative marketing problems in their competitive strategy. The number of participants as such on the demander and supplier side does not yet allow any conclusions about the level and quality of the assigned transaction partners. Therefore, it has to be clarified to what extent the demand on both sides can be satisfied (Kollmann, 1998). “At the beginning, many auctions were simply unattractive for the suppliers – either because of the starting price, or in terms of descriptions that have been just too opaque to be used as a basis for calculating the amount of work to be done”, Seel says. Apparently, the decision to actively participate in the marketplace also depends on the way transactions are coordinated, i.e. the design and features of the matching function. This goes along with research by Soh, Markus, & Goh (2006), who find that differences in features such as content creation are important because they not only contribute to the strategic alignment between value creation activities and the target market(s), but also are highly consequential for the benefits demander and suppliers get from an e-marketplace. Consequently, only a few months after launching the initial version of the platform, Seel revised the core process of placing an order, adding central questions and pieces of advice depending on the type of order to be placed. Additionally, the number of auctions that have been concluded does not say anything about the quality of the respective business deal, i.e. form, degree and dimension of transactions done and their effect on the whole market system. Cor-
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respondingly, as revenues result from a market fee that depends on the order volume, the value of each transaction plays an important role for LetsWorkIt. “Unfortunately, order volumes have been alarmingly low at the beginning. People were lacking trust into the concept of service and handcraft auctions”, Holtmann says. “Probably they first wanted to gain experience with low-volume orders, or simply minimize risk”, Bugge amends. “This is why we introduced the concept of selective auctions at a very early stage – outrunning our competitors, who did not offer such a concept.” As illustrated in Figure 5, the concept of selective auctions is intended for high-priced orders with a high demand of quality. “As the demander may rather control the actual outcome of the auction, the introduction of selective auctions significantly increased the average order volume, and thus our revenues“, Seel remembers. Similarly, LetsWorkIt’s rating system became part of a product strategy that emphasized quality aspects as key to success. An experimental study conducted by Ba & Pavlou (2003) confirms that demanders develop trust in a supplier’s credibility as a result of feedback mechanisms. “The rating system builds trust into the transaction partner, and is an important instrument for deciding which suppliers to select for a selective auction”, Seel states. The system makes the quality of work directly visible on the platform. “BasiFigure 5. Selective auctions as an essential part of product strategy
A Reverse Auction-Based E-Business Model for B2C Service Markets
cally, due to the transparency of the rating system, our suppliers cannot afford to provide bad quality”, he adds. Indeed, results from Ba & Pavlou (2003) indicate that negative ratings carry a much stronger effect than positive ones on a demander’s trust level and consequently the individual order volumes that a demander is willing to handle via the platform. Concerning its product strategy, LetsWorkIt still needs to achieve an advantage over other competing marketplaces so that the coordination via LetsWorkIt.de would be more reliable than via comparable platforms. However, the management team still has to assure that the coordination is based on a balanced ratio of emarketplace participants. “The reason for this is the comparison that is performed by both demanders and suppliers”, Holtmann says. It is this comparison that determines the participation of quality-oriented demanders and suppliers. Against this background, it can be expected that in the course of the expansion of LetsWorkIt.de, quality aspects will be of primary importance. Apparently, over time, a shift oft the relevance from the quantitative to the qualitative problem area can be postulated for being competitive in the market of service and handcraft auctions. Figure 6 illustrates the development of coordination problems on LetsWorkIt.de. Before reaching the quantitative critical masses, the acquisition of further market participants is in the foreground. For LetsWorkIt.de, this is still the case. However, as LetsWorkIt’s proceeds model builds on order volume, a product strategy focusing on the quality of individual transactions has already become a key component of the venture’s competitive strategy. “It is the form and the number of real business deals that decides whether we will be successful or not”, Bugge summarizes.
Figure 6. The development of coordinating problems (according to Kollmann, 1998)
leading German e-marketplaces for service and handcraft auctions. “Competition has become even stronger. But we are confident that we will be able to stand up to them. Currently, we are number two in the German market”, the three founders state. And they are no longer alone: in early 2006, LetsWorkIt was officially taken over by Quotatis S.A., a French competitor expanding its business to the German market. Since May 1st, 2006, LetsWorkIt.de is officially named “Quotatis” and has recruited six new employees, including a new chief executive officer. Chief marketing officer Bugge: “At last, the take-over strengthened our marketing budget.” Renaming the e-marketplace was accompanied by a TV campaign with commercials during do-it-yourself and interior design shows on five German TV channels, as well as a new online advertising concept that includes cooperation with several well-known German portal sites. With 3,500 orders per month and 60,000 marketplace participants, Quotatis is now number two in the German market for service and handcraft auctions (see Table 5). It will remain exciting to watch this market and, in particular, to keep track of the competitive strategy of Quotatis.
From LetsWorkIt to Quotatis
CONCLUSION
Looking back on two years of operative business now, LetsWorkIt.de has evolved into one of the
The case of LetsWorkIt.de provides evidence that the intermediation of handcraft and service orders
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Table 5. Quotatis and its three main competitors in May 2006 Undertool.de
Jobdoo.de
My-Hammer.de
Quotatis.de
Orders per month (compared to September 2005)
1,400 (+40%)
1,500 (+25%)
5,500 (+450%)
3,500 (+350%)
Users
87,000
31,000
60,000
60,000
is suitable to form the basis of an Internet-based B2C business model. This solely electronic business model is based upon a concept that involves the electronic creation of customer value by matching supply and demand on an electronic platform of the Net Economy. In this regard, the case confirms existing theory postulating that e-marketplaces can add value by simplifying information search in highly fragmented markets, where purchase decisions are complex and varied (Giaglis, Klein, & O’Keefe, 2002). For the service sector, reverse auctions have proven to represent an ideal matching mechanism. However, introducing the concept of selective auctions, the case also suggests that especially for high-priced orders with a high demand of quality, demanders should be enabled to minimize risk by rejecting non-compatible bidders. Furthermore, this case study points out that for Internet-based ventures, which are unknown and have limited capital, an ideal combination of public relations, performance marketing and strategic cooperation represents a very effective communication and distribution strategy. In particular, e-marketplaces are well advised to make use of such approaches to overcome quantitative marketing problems in the early phases of business development. The case underlines the importance of considering the complex interrelations of two-sided network effects and confirms the chicken-and-egg problem that is well-documented in current literature on electronic markets (Galbreth, March, Scudder, & Shor, 2005; Rochet & Tirole, 2003). Finally, supplementing existing theory that postulates a well-balanced bilateral marketing
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(Kollmann, 1998), the case of LetsWorkIt.de suggests that, depending on the concrete business model, it may be feasible for an e-marketplace to concentrate marketing activities on a primary customer group. By primarily aligning competitive strategy with the demand side, LetsWorkIt was able to reach a sufficient number of successful auctions. Besides quantitative aspects, strategy must include qualitative means that positively affect the form of the real business transactions standing behind an auction. The strategic combination of selective auctions and feedback mechanisms supports existing theory on the positive effects that rating systems may have on the demander’s trust level (Ba & Pavlou, 2003), respectively, the individual order volumes that a demander is willing to handle via the platform. As revenues depend on the order volume, a product strategy covering the whole range of the demander’s quality expectations, while at the same time signaling trustworthiness, turned out to be the key to success.
REFERENCES Amit, R., & Zott, C. (2001). Value creation in E-business. Strategic Management Journal, 22, 493520. doi:10.1002/smj.187 Ba, S., & Pavlou, P. A. (2003). Evidence of the effect of trust building technology in electronic markets: price premiums and buyer behavior. MIS Quarterly, 26(3), 243–286. doi:10.2307/4132332 Bakos, J. Y. (1997). Reducing buyer search costs: Implications for electronic marketplaces. Management Science, 44(12), 1676–1692. doi:10.1287/ mnsc.43.12.1676
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Bakos, J. Y. (1998). The emerging role of electronic marketplaces on the Internet. Communications of the ACM, 41(8), 35–42. doi:10.1145/280324.280330 Bein, D. R., & Weil, L. M. (2003). An inverseoptimization-based suction mechanism to support a multiattribute RFQ process. Management Science, 49(11), 1529–1545. doi:10.1287/ mnsc.49.11.1529.20588 Dai, Q., & Kauffmann, R. J. (2002). Business models for Internet-based B2B electronic markets. International Journal of Electronic Commerce, 6(4), 41–72. Emiliani, M. L. (2000). Business-to-business online auctions: key issues for purchasing process improvement. Supply Chain Management: An International Journal, 5(4), 176186. doi:10.1108/13598540010347299 Galbreth, M. R., March, S. T., Scudder, G. D., & Shor, M. (2005). A game-theoretic model of Emarketplace participation growth. Journal of Management Information Systems, 22(1), 295–319. Giaglis, G. M., Klein, S., & O’Keefe, R. M. (2002). The role of intermediaries in electronic marketplaces: developing a contingency model. Information Systems Journal, 12, 231–246. doi:10.1046/j.1365-2575.2002.00123.x Kollmann, T. (1998). Marketing for electronic market places – The relevance of two “critical points of success”. Electronic Markets, 8(3), 36–39. doi:10.1080/10196789800000039 Kollmann, T. (2000). Competitive strategies for electronic marketplaces – A study of Germanlanguage trading sites for used cars on the World Wide Web. Electronic Markets, 10(2), 102–109. doi:10.1080/10196780050138155 Kollmann, T. (2006). What is E-entrepreneurship? – Fundamentals of company founding in the Net economy. International Journal of Technology Management, 33(4), 322–340. doi:10.1504/ IJTM.2006.009247
Kollmann, T., & Häsel, M. (2006a). Cross-Channel Cooperation: The Bundling of Online and Offline Business Models. Wiesbaden, Germany: Deutscher Universitäts-Verlag. Kollmann, T., & Häsel, M. (2006b). Cross-channel cooperation: A collaborative approach of integrating online and offline business models. In F. Feltz, B. Otjacques, A. Oberweis, & N. Poussing (Ed.), AIM 2006 – Information Systems and Collaboration: State of the Art and Perspectives (pp. 69-82). Bonn: Gesellschaft für Informatik. Lumpkin, G. T., & Dess, G. G. (2004). E-business strategies and Internet business models: How the Internet adds value. Organizational Dynamics, 33(2), 161–173. doi:10.1016/j.orgdyn.2004.01.004 Porter, M. E. (1985). Competitive Advantage: Creating and Sustaining Superior Performance. New York, NY: Free Press. Porter, M. E. (2001). Strategy and the Internet. Harvard Business Review, 79(3), 62–78. Rochet, J.-C., & Tirole, J. (2003). Platform competition in two-sided markets. Journal of the European Economic Association, 1(4), 990–1029. doi:10.1162/154247603322493212 Soh, C., Markus, M. L., & Goh, K. H. (2006). Electronic marketplaces and price transparency: strategy, information technology, and Success. MIS Quarterly, 30(3), 705–723. Volkmann, C., & Tokarski, K. O. (2006). Growth strategies for young E-ventures through structured collaboration. International Journal of Services Technology and Management, 7(1), 68–84. Weiber, R., & Kollmann, T. (1998). Competitive advantages in virtual markets perspectives of “information-based marketing” in the cyberspace. European Journal of Marketing, 32(7/8), 603–615. doi:10.1108/03090569810224010
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Yoo, B., Choudhary, V., & Mukhopadhyay, T. (2002). A model of neutral B2B intermediaries. Journal of Management Information Systems, 19(3), 43–68.
ENDNOTES 1
A prior version of this chapter titled ‘Reverse Auctions in the Service Sector: The Case of LetsWorkIt.de’ has been published in the International Journal of E-Business Research, 3(3), 57-73.
2
3
4
According to the sales numbers in September 2005, the most successful categories have been: building & renovating, painters & varnishers, gardening, moving & transports, heating installation & sanitary, and furniture & furnishing. TV reports about LetsWorkIt.de have been broadcasted on PRO7 (BIZZ), ARD (Ratgeber Geld), ZDF (WISO), and KABEL1 (K1 Journal). Articles about LetsWorkIt.de have been published in BILD am Sonntag, Stern, Focus, DIE WELT, and Tommorow, among others.
This work was previously published in Emergent Strategies for E-Business Processes, Services and Implications: Advancing Corporate Frameworks, edited by In Lee, pp. 155-173, copyright 2009 by Information Science Reference (an imprint of IGI Global).
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Chapter 2.18
Multi-Tier Design Assessment in the Development of Complex Organizational Systems Melissa A. Dyehouse Purdue University, USA John Y. Baek Center for Advancement of Informal Science Education, USA Richard A. Lesh Indiana University, USA
ABSTRACT This chapter describes a model for evaluating complex organizations or systems. The design assessment model the authors propose is a response to current notions of assessment. There are assumptions we make about learning and the functioning of complex systems such as academic programs that do not match assumptions that are inherent in traditional forms of assessment. The authors use a case study of Purdue University’s DOI: 10.4018/978-1-60960-587-2.ch218
strategic planning process to provide the context for describing how design assessment takes place in a higher education setting. Based on interviews and observations, we identify areas problematic for some notions of assessment and distinguish several implications based on these findings. The design assessment model may be useful when assessing complex educational organizations or programs, such as when (a) educational entities at the university level need to assess new programs or curriculum materials; or (b) curriculum developers need to assess new software or tools for instruction.
Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
Multi-Tier Design Assessment in the Development of Complex Organizational Systems
INTRODUCTION Assessment and evaluation are increasingly important to evaluate programs or initiatives in higher educational settings. For example, a National Science Foundation (NSF) grant proposal must include an evaluation component (Frechtling, 2002). However, how does one go about evaluating a complex educational entity (i.e., with many interacting/conflicting components, stakeholders, and ideas) in a way that will produce valid and accurate results while balancing time and budgetary constraints? The kind of multi-tier design assessment procedures discussed in this chapter are based on principles that are well established in “design sciences” such as engineering where: (a) the goals of projects typically involve the development of complex tools, and (b) the underlying design is one of the most important components of the product being assessed. Thus, the development of documentation, as well as knowledge, proceeds in parallel and interactively through sequences of rigorous testing and revising cycles. The proposed design assessment model is contrasted with other types of assessments that are not appropriate for accomplishing the particular goals of the complex organization under investigation. Purdue University’s strategic planning process uses many of the same methods and has characteristics that are similar to a design assessment model. This research uses a case study method, drawing upon interviews of key stakeholders involved in a higher educational organization as well as observations that took place during a university strategic planning process for a new Department of Engineering Education. Using this method, we document the main challenges inherent to assessing a complex organization that is attempting to meet the goals outlined in a strategic plan. Next we weave together the process employed by the design researchers in the strategic planning process to the multiple tiers and processes that are used in
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the design assessment model. The design assessment model, which is based on design research principles, provides a solution to the problems frequently encountered in assessment and evaluation situations in higher education settings. The main objectives of this chapter are as follows: •
•
•
Identify areas problematic for some notions of assessment (e.g., existing curriculum and assessment standards describe goals for instruction that often do little to clarify how relevant achievements can be assessed, particularly for higher education programs); Use a case study of the strategic planning process as an example of how design assessment practices are employed; and Describe a model of design assessment that is based on design research principles.
BACKGROUND We recently published a book about our NSFfunded research on design research principles (Kelly, Lesh, & Baek, in press) and believe that design assessment is the next logical step. Design research is an approach that is becoming more widespread in educational research (Kelly, Lesh, & Baek, in press; Kelly, 2003; Lesh, 2002). Design researchers make use of existing research to develop a product using techniques that engineers commonly employ in cycles of designing, testing, and revising. Several studies have found positive outcomes about the effects of design research experiences for students’ learning and developmental process, which is summarized by Lesh, Kelly, and Yoon (in press): …the power and the range of usefulness of their underlying ways of thinking tend to increase significantly. This is because every time they design
Multi-Tier Design Assessment in the Development of Complex Organizational Systems
a new, thought-revealing tool, they are extending and revising the underlying ways of thinking that the tools embody. As a result, the development of the tools involves significant forms of learning, and, as learning occurs, the tools produce auditable trails of documentation that reveal important information about the constructs and conceptual systems that the students are developing. Hence, the activities contribute to both learning and assessment. Design research, viewed from an engineering perspective, is a type of research that takes place in higher education settings with the purpose of designing important products and systems, which leads to the development of a product such as a strategic plan, curricula, interventions, or tools (Middleton, Gorard, Taylor, & Bannan-Ritland, in press). We believe that the design research approach can be extended to assessment and evaluation in higher education settings. Similar to the design research model, design assessment employs several phases that occur in the assessment and evaluation process. The phases include: (a) the creation of an artifact or product, (b) the cyclical testing and revision of a product that is used as a tool, (c) the utilization of multiple models and theories, and (d) the results are generalized to similar settings. It is important to note that the participants are not passive during the phases, but instead are referred to as agents who take part in the collaborative design/evaluation process. There is a difference between the terms design assessment and assessment design. Assessment design has clear objectives and an agreed upon method of measurement. Design assessment, on the other hand, has unclear objectives and no agreed upon methods of measurement. To more clearly explain the reasoning for design assessment, we must first briefly discuss assessment in general.
ASSESSMENT Assessment is the process of collecting data that will be used to provide relevant information to decision makers (Jackman, 2001). Assessment is most effective when it reflects an understanding of learning as multidimensional, integrated, and revealed in performance over time (Pellegrino, Chudowsky, & Glaser, 2001). Because the purpose of assessment is to provide information for decision makers, assessment designs (and accompanying instruments and analysis procedures) need to be based on appropriate assumptions about: (a) who these decision makers are, (b) what decisions are priorities to make, (c) which kind of information is most important to consider—as well as on appropriate assumptions about the nature of the “subjects” (e.g., programs, curriculum materials, participants) being assessed. Every assessment design presupposes a model that determines principles for selecting, filtering, and organizing information and that expresses patterns, regularities, or relationships that are presumed to lie beneath surface-level data. There is no such thing as a methodology that is “scientific” for all purposes and situations. Unscientific methodologies are those that are ignorant of their own assumptions and models, and/or those whose underlying models are inconsistent with reasonable assumptions. For instance, take the following situations: (a) when educational entities at the university level need to assess new programs or curriculum materials, or (b) when curriculum developers need to assess new software or tools for instruction. However, unlike higher education settings in particular, existing curriculum and assessment standards describe goals for instruction that often do little to clarify how relevant achievements can be assessed. For example, consider the following Accreditation Board for Engineering and Technology (ABET) criteria for accrediting engineering programs:
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Engineering programs must demonstrate that their students attain the following outcomes:
CHARACTERISTICS OF A HIGHQUALITY ASSESSMENT
a. An ability to apply knowledge of mathematics, science, and engineering; b. An ability to design and conduct experiments, as well as to analyze and interpret data; c. An ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability; d. An ability to function on multi-disciplinary teams; e. An ability to identify, formulate, and solve engineering problems; f. An understanding of professional and ethical responsibility; g. An ability to communicate effectively; h. The broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context; i. A recognition of the need for, and an ability to engage in life-long learning; j. A knowledge of contemporary issues; and k. An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice (ABET, 2007).
This section makes the following points: (a) the properties of what is being assessed should be examined to help decide which type of measure is most appropriate, (b) four different categories are described that can help to determine the type of assessment tool that is needed, and (c) a discussion about the assumptions of a high-quality assessment. Ruiz-Primo (2002) characterizes a quality assessment system as one which is multifaceted and that has a coherent, comprehensive, and continuous structure. The coherency of an assessment relates to the alignment to the other activities and goals of the program. Therefore, a quality assessment will not run at cross-purposes with other types of measures being used at each level of the system. In addition to having coherency, the assessment should be comprehensive enough to provide a variety of evidence to support decisionmaking. Having the right amount of information from a variety of sources is necessary to making informed decisions. Furthermore, a quality assessment should be continuous so that it can measure progress over time. Consider a pre-test and post-test that is given once before and once after an intervention or a program. By using a measure that can only capture two fixed points in time one cannot be certain how or why these changes took place. Without this rich body of evidence a decision-maker may not be equipped to make the best decisions. Consideration of the type and structure of the assessment is important; however of equal importance are the properties of that which is being assessed. For example, see Figure 1. These are different kinds of entities/activities that must be measured using very different methods. Consider speed, which is commonly measured using a speedometer. Measuring speed will not have an effect on what speed the car is traveling while a speedometer provides a standardized way of
Consider criterion g. Is an ability to communicate effectively really a “thing” to be learned? Or is it—like cooking or carpentry—simply the name for a large category of things to be learned? (M. Dark, personal communication, February 2003) Is anyone ever really an all-purpose, content-independent, context-independent “good” communicator? Certainly it is meaningful to speak about students “developing communication abilities”; and certainly, there are some obvious ways that such abilities can be emphasized in instruction, but how can a given student’s level of development be documented or assessed?
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Multi-Tier Design Assessment in the Development of Complex Organizational Systems
measuring it. Based on interviews with Purdue’s strategic planning committee as well as administrators in charge of assessment and decision-making, there are four main categories of properties to assess, which are: (a) objectively, (b) subjectively, (c) changes by interaction, and (d) the consumer decides. See Figure 2 for examples from each type of category. For that reason, it may not be the best choice to use traditional standardized tests when attempting to assess a complex system because certain measures function differently depending on the system to be assessed. Several implications can be derived from these types of measurement properties. One implication that is central to design assessment is the consideration of both the properties being assessed and the type of assessment to be used. In other words, it is possible to assess something by using any number of measures; however it should be noted that certain measures work best to measure certain types of things. With this in mind, these properties were divided into several categories, which will aid in determining how to most effectively measure them. These categories are: (a) properties that can be measured with standardized instruments and will not change by being measured, (b) activities that cannot be clearly defined and
for which there are no standardized instruments, (c) systems for which interaction changes what is being measured and are associated with multiple layers and tradeoffs, and (d) activities or systems whose indicators change depending on the consumer or stakeholder.
A DESIGN ASSESSMENT MODEL This section explains the main components of a design assessment model and how they work, including: (a) agents making up a multi-tiered system, (b) artifacts and tools, (c) feedback, (d) evaluation, and (e) the end-in-view. The assessment of complex organizational systems (e.g., a new engineering education program) entails a unique set of challenges for those developing appropriate assessment tools. Often, we are not sure how it is we will define precisely what it is that we are trying to measure. For example, what defines a successful science and math education program? Everybody has different ideas about what this really means. Additionally, there are many different things going on in a complex organization and often very large numbers of people, which makes measuring every
Figure 1. Examples of different measurements and methods
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Figure 2. Categories of measurement properties
person and every variable a difficult and costly process. We propose a design assessment model to overcome many of these obstacles. First, we make three assumptions that are fundamental to design assessment: (a) that people see things differently over time, (b) that we care about how those agents see things, and (c) that a measure of how they see things can be obtained. Essentially, design assessment is a method of designing the system as it is being measured. Design assessment models the organizational system of interacting parts (tiers) such as professors, administrators, and students who produce
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documentation (artifacts) that can be used to track changes over time (tools). Methods of design assessment are reviewed retrospectively because they are an emergent property of the process of interacting with the system.
Agents The agents make up different levels, or tiers of the system that is being assessed. Because all agents in the system (such as administrators, faculty, and students) make up the designed system, it is important to obtain documentation across all of
Multi-Tier Design Assessment in the Development of Complex Organizational Systems
these tiers. This is called a multi-tiered system. Decision-makers are a critical element in the system because they need to get this information in order to act and to make the most effective decisions. The role of the designer is to bring design processes and theoretical knowledge to the change process, to make sure information gets to the decision-makers as needed, and to ensure that the design assessment process is functioning as intended. A designer might be selected internally or alternatively may serve the role of an external evaluator.
Artifacts and Tools The instruments, or tools, refer to a measure of how agents view things. Documentation, or artifacts, refers to the evidence used to design the tools. Artifacts may be viewed simply as all documentation that is collected while the tools constitute the relevant artifacts. Constant documentation over the course of the project is necessary to reveal changes over time. An example of an artifact is a course syllabus produced by a faculty member. Over time, by using feedback from students, faculty may develop and revise the course format and syllabus to reflect new ideas of how to best present the course material. The changes in the syllabus over time will be used as a tool reflecting how the faculty thinks about how the students are learning and thinking. Agents’ underlying conceptual systems are embedded in the tools; therefore when the tools are tested and revised so are agents’ conceptual systems. There is no need for additional assessment instruments because artifacts are produced from what people are already doing.
Feedback Loops Evaluation occurs by the process of feedback. Feedback is an essential component of the design assessment process because it allows for the testing of the tools. This can occur in many ways, one
of which is comparison with other agents who are doing the same thing and getting feedback on what works or does not. For example, faculty meetings provide an opportunity to voice thoughts and receive other opinions and feedback from colleagues. Feedback can also come from other tiers, or levels in the organization. For example, feedback occurs during the process of teaching and learning when an instructor receives feedback from students and accordingly revises the method of instruction. Feedback occurs in a circular manner, with several iterations of revising and testing the tools.
Evaluation Evaluation occurs as part of the assessment process. The agents who make up each tier will evaluate, reiterate, and continuously refine ideas without the need of external analysis. The actual results of the assessment are the designs that underlie the tools (i.e., the changes over time to the current tool). In this way each tier will be coevaluators rather than taking a top-down approach to evaluation. The following section describes how a bottom-up approach using feedback has been successful in a business setting.
Example of a Business Approach to Design Assessment Principles Typically, business has a top-down approach to decision-making and evaluation. In the case of Target Corporation, a less hierarchical approach was taken regarding a person’s reviews and feedback. Target is a discount chain that has become one of America’s most profitable retailers (Rowley, 2003). Rowley (2003) describes Target’s innovative assessment techniques, which have allowed learning, improvement, and the monitoring of all aspects of the organization.
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Feedback from all Levels Including people from all levels is a critical part of the assessment strategy for Target Corporation. Besides getting input from outside tiers, Target encouraged workers at all levels to identify problems and then implemented the recommended strategies given by the employees. This kind of feedback addressed the real issues that other people higher up could not spot and subsequently helped to improve business. For example, the people working the floor (lower level of the tiers) were asked what things were problems. They listed issues that managers had overlooked and when asked for their suggestions to fix or improve the situation the business operated more smoothly as a result.
Evaluation Self-evaluations were introduced for professionals at all levels in order to compare with the reviews made by other people and to encourage them to stay on track. For example, if a person’s self-evaluation did not match with another person’s evaluation of them, then the two would be compared to iron out any inconsistencies or to discuss the problem. Self-evaluations and feedback allow people to take part in monitoring their own progress and to have a say in the assessment and evaluation process. Self-monitoring and including all levels of agents to participate in the feedback and assessment process is a key component of design assessment.
End-in-View Another component of design assessment is the end-in-view. Ends-in-view, unlike objectives, metrics or goals are the overall purpose or aim of the assessment and should not change, even though the goals and other measurable ways to achieve the end-in-views might change. That is, the method of arriving at the end-in-view may change but the end-in-view itself remains the
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same. This serves the purpose of making sure the standards are not lowered while attempting to achieve the aims and to provide a sense of direction and purpose. For example, an end-in-view might be to develop an efficient method of providing new students with guidance upon arrival at the university. There may not be a clear definition at the beginning about what exactly constitutes an “efficient” method, but as time progresses new techniques and ideas will be developed and refined. In this way the best techniques will be selected, meeting the end-in-view of an efficient method of providing guidance for new students.
Figure 3. A design assessment model
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Figure 3 provides a visual representation of a design assessment model. Key questions to address when using a design assessment model are: (a) What system is being designed and measured? (b) Who are the agents? What are their interpretations? (c) What were the artifacts? What changed? (d) What tools were designed to capture interpretations? (e) What feedback occurred? and (f) What was the end-inview? Design assessment is meant to eliminate many challenges inherent to assessing complex educational organizations. The time-consuming nature of traditional assessments is eliminated because the trail of documentation is something that is already being done. Large numbers of people can be assessed at the same time because each agent collects his or her own tools. The nature of this type of assessment may also preclude the reporting of false results. Finally, because all agents hold differing opinions it is not necessary to precisely define what to measure because what is being measured can differ for each agent. Figure 4 lists some possible objections and counters to design assessment.
HOW ASSESSMENT WORKS IN COMPLEX SYSTEMS To discuss general issues of design assessment, this section focuses on a specific example - Purdue University’s strategic planning process. The participants in the case study were stakeholders in the strategic planning process, including university administrators and assessment personnel. Interviews and observations took place from October 2003 to August 2004. Content analysis was used to find common themes about assessment. Methods of design assessment are reviewed retrospectively because they were an emergent property of the strategic planning process interacting with the complex organizational system.
Strategic Planning The strategic planning process is a good example of how to assess and evaluate a complex organization. The assessment of organizations or programs at a university, a business, or a school system share several characteristics that include a high-stakes evaluation, a summative report, feedback, many agents/people involved, decision-makers, constant change, and the use of indices such as metrics to assess progress. These features of complex organizations lead to unique challenges in assessment
Figure 4. Possible issues encountered when implementing a design assessment model
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that cannot be adequately solved by using more traditional methods. The strategic planning process is one method that has been used as a means to assess and evaluate a complex organization. The strategic plan works within a high-stakes setting to address issues like performance reviews, summative reports, decision-makers, and many agents. All relevant pieces of the plan are monitored, including people (administrators, faculty, deans, and students) and programs (departments, centers, and schools). These pieces are monitored using criteria that can measure progress such as goals, strategies, metrics, and benchmarks. The plan creates the impetus for continuous improvement and creates a focus for progressing toward the vision of the organization. A critical component of the process is to determine who the decision-makers are so that relevant information can be provided in an efficient manner.
Implications Based upon interviews and research on Purdue’s strategic planning process, we have constructed several implications based upon these findings. The following implications are described using the strategic planning process as an example.
Implication 1: Decision-Makers Selecting and informing decision-makers is, according to the director of strategic planning and assessment at Purdue University, one of the most important elements of the strategic planning process. For example, one of the decision-makers in a university setting is a departmental dean who must determine how to allocate funding to different departmental programs based on the data. Therefore, it is critical that the dean get the appropriate reports and data so that he is able to make suitable decisions about which programs should receive more funding. To identify the decisionmakers the strategic planning process involves what is called an action plan, which identifies
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who does what. The next step in action planning is to determine who has what responsibility. For example, an action plan might state that the dean has the responsibility of making departmental funding decisions. In a university setting, the main decision-makers are usually internal, such as the president, provost, dean, department, and faculty. Clearly delineating every agent’s task makes accountability clear in addition to fostering a sense of ownership of the plan. The action planning process also specifies an annual list of priorities including what has been learned, future directions, who is responsible, what the investments are, and what the timeline is. Then the provost does an annual review of each school in the university to see if these targets have been met. For example, if the School of Engineering has not completed a goal within a certain timeline, action will be taken to determine why this did not happen and what can be done. The action planning process keeps everything moving forward and on track. Without feedback and evaluation, the plan cannot work because schools and programs falling behind will not be recognized. A decision-maker is not necessarily just one person; there can be several different levels of decision-makers. For example, the dean may decide that more resources should be allocated to a program that is falling behind and a faculty member can make the decision on how to best use the resources for program improvement. Other decisions rest with an individual but are carried out by groups, such as decisions made by the dean and carried out by several departmental deans. Decision-makers may also be groups of people, such as planning committees. Distinctions are made between people, (e.g., the faculty) who have input but are not the ultimate authority. In most cases the decision-makers are the heads, deans, key staff, and a couple of faculty, with the dean having the veto authority over all. However, due to the uniqueness of universities, it is difficult to have a top-down process because of the independence of faculty, who will have strong input in
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the decisions being made. In some cases, every stakeholder will be a decision-maker. For example, surveys may be used to get a broad opinion from all of the stakeholders, which are then analyzed and used to inform decisions. Certain elements come from the upper administration, but a good number of decisions come from middle management and the faculty. The president might decide to increase discovery, but the decision as to how this will be accomplished is made at the faculty level. Similar to a design assessment model, there is not a top-down assessment; rather, input/feedback comes from all levels. There is a clear delineation of tasks and a system of accountability that keeps agents on track.
Implication 2: Prioritizing Decisions In a complex organization, there are a large number of decisions that must be made and a limited amount of time and resources. It is therefore essential to establish the decisions that will be prioritized so that the most important tasks will get accomplished first. Strategic planning teams have several ways of determining priorities. One of these ways is through the use of dashboard metrics. Dashboard metrics are the most salient metrics that must provide instant feedback and be monitored continuously. These metrics are also termed “self-fulfilling” metrics because they encourage people to make progress towards the goals. Dashboard metrics relate to the third diagram in Figure 2 illustrating how the activity being measured changes with interaction. With a metric targeting a specific skill for example, people will try to perform well if they know that their progress is being monitored.
Implication 3: Relevant Information Consider the dilemma of a dean who must decide if it is worth the large cost of adding an additional department to the university. The strategic planning process devotes a considerable amount of
effort to deciding what information is the most important to consider so that these decision-makers can most effectively determine what to do. The strategic planning committee determines this by looking at an investment return analysis, which is an analysis of the resources (inputs) and the returns (outputs). This analysis involves variables like costs and benefits that run at cross-purposes. For example, when deciding whether to add a new department to the university, several variables are considered such as: the costs of hiring new faculty, constructing and planning new facilities, and ways to recruit new students. These variables are contrasted with the eventual benefits of retaining a diverse and outstanding faculty, bringing new funding into the university, and adding to the prestige and recognition of the university. This allows for a view of how much is invested and what the potential returns will be. Similar to a design assessment model, the selection and revision of these tools provides the means for which the most meaningful information is retained; that is, the best tools for the purpose of the assessment. This testing of the tools is also a process of experimentation.
Implication 4: Divergence and Experimentation There are at least two ways that people and organizations deal with decision-making: convergence and divergence. Convergence occurs when a decision-maker specifies what agents should do in order to reach a goal and then the agents converge to that goal. For example, if a dean decides to create a new program she will tell the faculty exactly how to go about doing so and the faculty will subsequently adjust their ideas to converge to this goal. If agents are told what to do in order to achieve a goal there is no sharing of diverse ideas and no experimentation that leads to the development of the best ideas. Thus, convergence to a goal will most likely not
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produce the potentially superior results that might have been obtained by divergence. Another way that people and organizations can make decisions is by divergence. Divergence takes place when the decision-maker specifies the goal but not the means of arriving there. If directions about how to reach a goal are not immediately specified then people can exchange ideas and receive feedback in a cycle of express→test→revise to select the best ideas. For example, using a design assessment model, agents will collect artifacts, express ideas about how and why to use the artifacts as tools, select and test the artifacts, obtain feedback, and revise the tools. In this way, a culture of experimentation and divergence is formed. Divergence is a multi-tiered approach where decision-making is informed from all levels, which also encourages diversity. People and ideologies, especially in academic institutions, can vary greatly. In a university setting in particular it is vital to allow for diversity but at the same time allow people to integrate their ideas. Agents can Figure 5. Convergence and divergence
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have different foci and still remain consistent with the university’s plan yet separate with their own character. Figure 5 represents how divergence and convergence differ. A distinctive feature of a system like the academic sector is a higher agility factor. Agility refers to decision-making and the free exchange of ideas coming from all levels of the system. Higher agility means that the bottom tiers are given more say in the decision-making process and that decisions may be informed from the bottom-up. Higher agility helps to create a culture of experimentation rather than a top-down culture of conformity/convergence. With the end-in-view in mind different departments in the university are able to develop their own strategic plans in relation to the end-in-view.
Implication 5: Metrics Even in cases where existing standardized tests provide sensible “indicators” of progress, they
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seldom constitute acceptable “operational definitions” of the constructs they are used to assess. Operational definitions allow for the separation of behavioral objectives into individual components (Lesh, 2002). The situations, tools, and criteria are able to be treated separately and occur in natural situations (see Figure 6). Naturalistic observations allow greater interpretability in the context where the behavior occurs, allow for the examination of behavior that cannot be adequately captured by traditional measures, and the behavior can occur over an extended period of time. On the other hand, most standardized tests use behavioral objectives in the form of restricted and easy-to-administer-and-score formats that usually prevent them from emphasizing deep or complex achievements (see Figure 7). For this reason, teaching to tests usually is not a prudent policy. In much the same way that it is possible to change the time or the weather, improving test scores often does little to improve the development of understandings and abilities for which they were intended to be indicators. In fact, because of feedback loops, tests that are used in isolation as the only indicator of progress often have strong
influences on what is taught and how it is taught. So, if tests emphasize narrow and shallow conceptions of achievement, then instruction often tends to do likewise. This is one reason why strategic plans for businesses, or universities, or Schools of Engineering tend to identify a variety of benchmarks, indicators, and metrics to monitor and assess their progress. Complex organizations involve multiple levels, interacting and often conflicting agents, feedback loops, and constant change. Because of this complexity a linear condition-action rule that is commonly used in traditional assessments is not appropriate for assessing a complex organization. Because of the strategic plan’s broad scope there must be a variety of indicators to obtain information on all pieces of the organization. In the case of Purdue’s strategic plan, selecting indicators for the faculty in one department while overlooking another department is unwise because each part will provide different information. In addition, having a large number of indicators can eliminate selective comparison of these indicators in order to obtain a more favorable evaluation. On the other
Figure 6. Operational definitions
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Figure 7. Behavioral objectives
hand, too many indicators lead to an overwhelming amount of data and a loss of focus on what is most important. To resolve this issue, Purdue’s strategic planning process identifies metrics that are most important, which are selected by outcomes that: (a) have the most impact, (b) for which data are readily obtainable, (c) for repeatable processes, and (d) are useful for tracking performance as well as directing resources. Purdue’s strategic planning process uses criteria that are formed using judgments based on empirical data from reported national institutions (e.g., retention rates, graduation statistics). Next, a collective review of all of metrics and benchmarks takes place to decide if any criteria should be added or dropped. The indicators are refined and changed on an ongoing basis as well as re-examined yearly. Having a variety of indicators, or criteria, is a property of the design assessment model because the tools are designed for different purposes, people, situations, and associated tradeoffs. Useful assessment results tend to resemble consumer guidebook criteria or strategic plans that contain a variety of indicators and benchmarks for tracking progress (Lesh, et al., in press). To decide what criteria to use, first consider why: come up with a set of factors that are deemed most important. Then look at the purpose of picking certain indices (i.e., for making external comparisons). See the last category in Figure 1 for a description of how things are measured using these criteria. Instead of
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being a reflection of daily operations, indicators are most effective when they are related to future directions, or the end-in-view. The following section describes some of these strategic planning metrics in more detail.
Types of Metrics Purdue’s strategic plan contains a variety of different criteria that can be used to measure progress. Each of these criteria serves different functions and includes goals, actions, metrics, and benchmarks. A strategic plan also includes broad overarching strategies, such as the vision or end-in-view, which can be considered the most unquantifiable component of the plan. The following is a list of several types of metrics and their descriptions: •
•
•
Goals are broad standards of performance that are broken down into small pieces to be measured as indicators. Indicators are distinctive from other outcomes because they describe what must occur to meet a certain benchmark. They are measurable states that allow the assessment of whether or not associated objectives are being met and are often called metrics or trends. Objectives are descriptions of measurable expectations based on a goal, but they only measure a small part of something.
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•
Objectives are referred to as targets, criteria, and outcomes. Benchmarking can be defined as a method of evaluation based on referencing and comparison to an ideal. Benchmarks, also called exemplars or anchors, are developed following a set of criteria that represent such things as desired attributes or principles. Some characteristics of benchmarks are that they can differ can differ for each peer, they are changeable, the characteristics by which the peers are selected may not change, and they serve the function of assessing competitiveness with peers.
In contrast, characteristics of the end-in-view are that it: • • • •
•
Describes the desired outcome, Does not say how to reach the outcome, Is unchangeable, May use an operational definition to state the desired outcome and whether or not it has been achieved, and Restricts lowering the standards because the desired outcome is always the same no matter what method is used to achieve it.
For example, a goal for Purdue is to achieve and sustain preeminence in discovery. A strategy for this goal is to create incentives that encourage faculty productivity in research and scholarship. The associated metric is the number of publications/citations of faculty.
Implication 6: The End-In-View How can there be accountability if the goals or indicators are subject to change? Oftentimes when developing these indices you know where you want to end up and what the aim is, but are not quite sure how to get there. As a consequence the first attempt at laying out the metrics may not result in the best version. However, through this process
you will become smarter about how to achieve the end-in-view as you receive feedback, gain experience, or discover new ways of conceptualizing success. For that reason, changing the goals and indicators over time is simply the result of becoming smarter and more informed about how to achieve the end-in-view. The strategic planning process is one example of how a complex organization can adapt rapidly to change and become smarter in the process. The strategic plan must be somewhat resilient, yet still able to change and adapt when necessary. Picture a high-rise building that sways with the wind versus a wind toppling the building because it is too rigid. To allow for change, the end-in-view must remain constant while allowing for different means of arriving there. Goals, however, may be changeable depending on their level of abstraction and context. Thus, a changeable goal is less abstract and more concrete. For example, an abstract goal from Purdue’s strategic plan is a mission of service (service to the state, students, etc.). On the other hand, a related, but more concrete goal is to increase service learning opportunities. Because some of the goals may change, most people recognize that the associated metrics will too. On the other hand, very broad levels of the strategic plan probably will not change. For example, Purdue’s broad mission of discovery, learning, and engagement is not likely to change. The function of the vision, or end-in-view, is to allow the desired outcome to remain the same. Therefore, the standards will not be lowered no matter what other metrics change because the desired outcome remains the same. The end-in-view serves the same function in a design assessment model in that the tools are expected to change over time but the end-in-view does not.
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Implication 7: Continuous Feedback Loops The university keeps track of each part of the organization using a holistic, or systems approach. A systems approach is derived from systems theory, whereby examining the big picture and seeing patterns of change rather than focusing on the detailed parts of a system provides a means to better understand and explain the workings of complex organizations. Essentially, the parts of the system will act differently if viewed in isolation because of the complex interrelationships between the parts. All decisions and learning in a system take place within the context of feedback loops (Sterman, 1994). Feedback loops show how actions can reinforce or counteract one another (Senge, 1990). In a simple model of a systems feedback concept, learning takes place in an iterative cycle of invention, observation, reflection, and action. For example, decision-makers in a single feedback loop compare information about the state of the real world to various goals, perceive discrepancies between desired and actual states, and take actions they believe will cause the real world to move toward the desired state based on mental models and feedback. When assessing a complex organization such as a School of Engineering Education, a systems approach maintains that any preoccupation with individual elements of the system mean that the unity of the whole system is missed. In a design assessment model, each level of the organization (e.g., students, teachers, researchers, administrators) cannot be understood completely without taking the others into account. For instance, if the dean of the School of Engineering Education had to wait until the annual report to obtain any data about the department’s programs, problems could not be corrected right away. The deans, faculty, and other tiers must have access to relevant information at all times. The process requires holistic, conceptual thinking because
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the agents must have the ability to understand the relationship between the goals and how the goals relate to everyday tasks. For this reason agents in each tier must gradually be empowered to take information and use it appropriately. Even bottom-level tiers should have access to relevant information so they are not reliant on the central power.
Implication 8: Reports Reports are the means by which relevant information is provided to the decision-makers and may differ depending on their purpose. For the type of situation in which the consumer must decide based on a set of criteria, it is necessary to have all the information at one time in order to make an informed decision. For example, decision-makers for Purdue University’s admissions committee must have all of the admissions documentation from a prospective student because there are tradeoffs to be considered (e.g., an in-state student with a lower G.P.A. versus an out-of-state student with a higher G.P.A.). The information can be laid out in a flowchart so that a decision-maker can see the more relevant information at the top as well as consider all criteria at the same time. For example, examining a flowchart based upon Purdue University’s selection process for admitting undergraduate students might look like the following: At the top of the flowchart are all students who applied to the university. From there, students are filtered through the next level of the chart by (a) when they applied, (b) if they are an in-state resident, and (c) if they meet departmental requirements. The students who have been selected based on these criteria are filtered through to the next level of the chart, where standards such as G.P.A. and letters of recommendation are considered. This process continues until all students are selected. In contrast, examining all the criteria at one time is not necessary for other types of reports. For example, in the context of Purdue University’s strategic planning process priority progress
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reports monitor the progress of the most important priorities. In evaluating Purdue’s strategic plan for instance, the leadership team chooses ten of the most salient priorities to focus on and then selects metrics from the strategic plan to use as the milestone guides for measuring success. The main functions of these reports are to decide what types of redirects to make, how to allocate resources, and as a communication tool. Reports serve a useful function in a design assessment model. If there is a gap in the report that is widening it compels people to ask what is being done and why. Thus, the report becomes a tool for the decision-makers.
Is Design Assessment Appropriate? The stakeholders who were interviewed for this case study perceived several challenges inherent in the assessment of a higher education organization. These challenges may be turned into questions to determine whether design assessment is appropriate given the conditions of the situation and the goals for the assessment. In many cases, design assessment is proposed when other types of assessment might not be appropriate for accomplishing the particular goals of the project or when other types of assessment might violate aspects of the system under investigation.
Are There Clear Definitions of Objectives? If there are no clear definitions of objectives, design assessment may be useful. Defining what is to be accomplished by the design process means operationally defining what is desired and how participants will know when the objective has been met. For example, in a recent engineering study, one objective was to design curricula to help students learn more about teamwork. However, the research team had to determine what “good” teamwork would look like, how good teamwork would be measured, and how good teamwork
would be encouraged. Students who were enrolled in an undergraduate engineering course were asked to write a code of cooperation for their team that described the team’s agreed-upon rules, procedures for working together, and explicitly defined “good” teamwork. In order to evaluate the effectiveness of their teamwork, the students were asked to evaluate their team members based on the code of cooperation and to make revisions if necessary. The faculty uses the code of cooperation as a tool to analyze students’ changing interpretations of “good” teamwork and by students’ peer evaluations based on their codes of cooperation. There are two parts to an objective—the goal and how to measure the goal. Accordingly the measurement devices used for the goals should both match the goal and not infringe upon achievement of the goal. Take the previous example of teamwork in an undergraduate engineering class. Performance on traditional multiple-choice tests is not a good measure of teamwork given that group interactions and problem-solving involve multiple complex, interacting variables. Therefore more appropriate indicators (e.g., a code of cooperation) can be used to measure the quality of teamwork.
Are There Clear and Understandable Methods for Mastering Objectives? If there are no clear and understandable methods for mastering objectives, design assessment may be an appropriate way of evaluating whether the objectives are met while designing the indicators to measure them. For example, the Department of Engineering Education would like to know whether first-year students can work in teams to solve an engineering task. Teamwork is a complex activity that involves many factors such as the experiences of the team members, the task at hand, the context for the teamwork, and the goals for working in teams. Simply stating that students have worked in teams is not enough to document whether they are prepared for teamwork in future courses and in the workplace. Consequently, sys-
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tems are designed that allow students to design teamwork goals for themselves, evaluate their teams’ adherence to the goals, and revise the goals given more experience working in teams. Furthermore, the department is simultaneously learning about what it means to work in a team on an engineering project.
Do Indicators of Improvement Involve Different Agents’ Evolving Conceptions of What it Means to Achieve the Goals? Design assessment is useful in organizations where objectives and indicators are not clearly defined. In these situations it does not make sense to align the indicators of improvement with the current conceptions of what it means to achieve certain goals when those goals are also evolving. Design assessment allows for movement between the goals and the indicators of improvement as both evolve and represent evolving understandings of the agents in the organization. For example, the Department of Engineering Education has evolving notions of what it means for a team of students to work effectively together.
Is the Program One that is Evolving or Changing and for Which Long-Term Data is Needed? If the program or organization is meant to evolve and undergo significant changes, design assessment may overcome limitations of other types of assessments. Because design assessment is based on evolving ideas of what it means to achieve a certain goal or end-in-view, the organization is undergoing design as it is being measured. For example a pre- and post- assessment is only capable of capturing two fixed points in time, which does not provide important information about how or why these changes occurred. In contrast, the design assessment process creates a trail of documenta-
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tion over time so that a rich body of information is provided. Progress is driven by repeated cycles of testing and revision with feedback at each stage.
Are There Many Agents from Whom Information is Needed or is Relevant Information Embedded in Several Sources? When attempting to assess a large number of agents or programs in an organization, issues such as time and resources can make this a difficult if not impossible task. In many cases relevant information will be overlooked or excluded for these reasons. However, if a design assessment model is implemented information can be collected from all agents, their interactions, and their development. These artifacts can be collected from many sources and by means of things that agents are already doing. Thus, time is saved because participants in the assessment process will not have to do something that they are not already doing, which in turn makes the assessment more meaningful. Each agent is responsible for his or her own tools that illustrate evolving conceptions, which eliminates a large amount of data analysis.
Is the Assessment High-Stakes and Have Significant Impacts? In a high-stakes environment where the assessment will have significant impacts on the people involved, it is of critical importance that the assessment measure what it is supposed to with a high level of accuracy. As mentioned earlier, it is more difficult to measure complex systems or concepts with traditional types of assessments; one reason is that there is no clear definition of the concept that is being assessed. Design assessment on the other hand does not presuppose any one definition of the concept or how the concept should be measured. For these reasons, design assessment may be more appropriate to use in a high-stakes
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environment where there could be significant negative impacts when using an assessment that does not function well for complex organizations or concepts. To summarize, the challenges that may be overcome using design assessment include: • • •
• •
•
The program objectives are not clearly defined, There are no clear and understandable methods for mastering the objectives, Stakeholders have differing conceptions of what it means to achieve the end-in-view or goals, The program is evolving or changing and for which long-term data is needed, There are many stakeholders from whom information is needed and the relevant information should come from a variety of sources, and The program or organization is high-stakes and has significant impacts.
CONCLUSION The complex nature of many organizations calls for an assessment that can take into account the many challenges and elements that make up an organization that is continuously evolving. We have used a case study to demonstrate how features of Purdue University’s strategic planning process can be used to assess a complex organization in higher education. One reason that design assessment is most useful for assessing these types of complex organizations is because of the iterative nature of the process and how design assessment fits with what is already being done. Information can come from many sources, formative feedback is provided at each cycle, and decision-makers select the best ideas and methods in order to constantly improve. Each objective is assessed using artifacts from what agents are already do-
ing. These tools reveal changes over time and are used by the decision-maker to select the best ideas. This multi-tiered assessment method uses a holistic approach that makes design assessment particularly useful as an assessment model for complex organizations in higher education. We hope that this chapter provokes discussion about assessing complex organizations in higher education and ways in which to ensure a valid and quality measure of progress. We also wish to stimulate research about design assessment, for example: (a) how design assessment works in practice, (b) how design assessment works at different levels (e.g., university-level, undergraduatelevel, programmatic level, classroom level), and (c) the viability of the design assessment model.
REFERENCES Accreditation Board for Engineering and Technology (ABET). (2007). Criteria for accrediting engineering programs: Effective for evaluations during the 2008-2009 accreditation cycle. Retrieved June 16, 2008, from http://www.abet.org/ forms.shtml Frechtling, J. (2002). The 2002 user-friendly handbook for project evaluation. REC 99-12175. Arlington, VA: NSF. Jackman, H. L. (2001). Early education curriculum: A child’s connection to the world (2nd ed.). Albany, NY: Delmar. Kelly, A. E. (Ed.). (2003). Theme issue: The role of design in educational research. [Special issue]. Educational Researcher, 32(1). doi:10.3102/0013189X032001003 Kelly, A. E., Lesh, R. A., & Baek, J. Y. (Eds.). (in press). Handbook of design research methods in education: Innovations in science, technology, engineering, and mathematics education. New York: Routledge.
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Lesh, R. A. (2002). Research design in mathematics education: Focusing on design experiments. In L. English (Ed.), Handbook of international research in mathematics education (pp. 27–49). Mahwah, NJ: Lawrence Erlbaum Associates.
Sterman, J. D. (1994). Learning in and about complex systems. System Dynamics Review, 10(2-3), 291–330. doi:10.1002/sdr.4260100214
Lesh, R. A., Kelly, A. E., & Yoon, C. (in press). Multitier design experiments in mathematics, science, and technology education. In A. E. Kelly, R. A. Lesh, & J. Y. Baek (Eds.), Handbook of design research methods in education: Innovations in science, technology, engineering, and mathematics education. New York: Routledge.
KEY TERMS AND DEFINITIONS
Middleton, J., Gorard, S., Taylor, C., & BannanRitland, B. (in press). The “compleat” design experiment: From soup to nuts. In A. E. Kelly, R. A. Lesh, & J. Y. Baek (Eds.), Handbook of design research methods in education: Innovations in science, technology, engineering, and mathematics education. New York: Routledge. Pellegrino, J. W., Chudowsky, N., & Glaser, R. (Eds.). (2001). Knowing what students know: The science and design of educational assessment. National Research Council Committee on the Foundations of Assessment. Division of Behavioral and Social Sciences and Education. Washington, DC: National Academy Press. Ruiz-Primo, M. A. (2002, February). Seamless science education. On a seamless assessment system. Symposium conducted at the annual meeting of the American Association for the Advancement of Science, Boston. Senge, P. M. (1990). The fifth discipline: The art and practice of the learning organization. New York: Doubleday.
Agents: Participants who are part of the organization at all levels and capacities. Artifacts: Documentation, or a measure of how agents view things. Assessment: The process of gathering data in order to make decisions. Assessment is the collection of data while evaluation (see below) uses these data to determine the quality of that which is being assessed and whether or not the goals have been met (Jackman, 2001). Design Assessment: A method of designing the organization/product as it is being measured, which models a system of interacting parts such as professors, administrators, and students who produce documentation that can be used to track changes over time. Design Research: A type of research often taking place in higher education settings with the purpose of developing a product such as curricula or tools by using techniques that engineers commonly employ in cycles of designing, testing, and revising. Evaluation: The use of assessment data to determine whether goals are being met. Goals: Broad standards of performance that cannot be measured directly. Indicators: Measurable states that are used to determine if associated objectives are being met. Tiers: The levels made up of agents from various parts of the organization. Tools: Auditable trails of documentation used to evaluate changes over time.
This work was previously published in Handbook of Research on Assessment Technologies, Methods, and Applications in Higher Education, edited by Christopher S. Schreiner, pp. 1-21, copyright 2009 by Information Science Reference (an imprint of IGI Global).
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EBDMSS:
A Web-Based Decision Making Support System for Strategic E-Business Management Fen Wang Central Washington University, USA Natalie Lupton Central Washington University, USA David Rawlinson Central Washington University, USA Xingguo Zhang Aging and Disability Service Administration, USA
ABSTRACT This paper describes a Web-based intelligent decision making support system (DMSS) to deliver balanced scorecard (BSC) based modelling and analysis in support of strategic E-business management. This framework supports E-business managers during the strategy making process in a comprehensive, integrated, and continuous manner. The paper demonstrates how practitioners DOI: 10.4018/978-1-60960-587-2.ch219
can use this system to deliver a wide range of embodied E-business strategy expertise in support of real-time decision making.
INTROUCTION E-business has evolved into an accepted way of doing business and has opened new channels for communication and selling (Whelan & Maxelon, 2001; Laudon & Traver, 2007; Phillips & Wright, 2009). It provides a new source of data on every-
Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
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thing from customers to competitors and changes the face of competition tremendously (Hong & Zhu, 2006; Ba, Stallaert & Zhang, 2007; Sanders, 2007). As Raisinghani and Schkade (2001) pointed out: “perhaps, one of the best ways to succeed in the world of E-business is to start off with a dynamic and new E-business strategy” (p. 601). In earlier studies, an E-business balanced scorecard based model (EBBSC) for strategic management was established and estimated with real business data (Wang & Forgionne, 2005, 2007). Figure 1 presents the EBBSC model which consists of a business core, analytic e-CRM, process structure, and e-knowledge network perspectives. Wang and Forgionne (2007) explained this model could be utilized to translate E-business strategies into conceptual blueprints for strategic management control and performance evaluation as well as provide a stable point of reference for businesses to understand and explore E-business initiatives effectively. In practice, such a framework can assist Ebusiness managers in overcoming deficiencies in awareness and proficiency regarding the business models useful to generate effective strategies (Forgionne, 2000; Forgionne & Kohli, 2000; Holian, 2002). When analytical and technical skills are not available in-house, the specialized
modelling and analysis expertise suggested by the EBBSC framework can be delivered through an intelligent decision making support system (DMSS). Figure 2 depicts a conceptual functional framework of such a system for strategic E-business management, which is referred to as the EBDMSS hereafter. As Figure 2 indicates, the EBDMSS is the delivery vehicle for the EBBSC model functionality. This paper presents the EBDMSS and its role in supporting effective and efficient E-business strategy development. First, a literature review of the evolution of intelligent support for decision making in E-business is presented. Next, the paper presents the EBDMSS architecture. Then, a prototype EBDMSS is depicted to illustrate the system’s potential as a strategic E-business management tool. The paper concludes with implications for decision making support and E-business management.
BACKGROUND REVIEW: THE EVOLUTION OF INTELLIGENT SUPPORT Decision making support systems (DMSS) have evolved over time and across disciplines (For-
Figure 1. The comprehensive EBBSC framework (adapted from Wang & Forgionne, 2007)
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Figure 2. EBDMSS functional framework
gionne, 2000; Arnott, 2004; Turban et al., 2007). DMSS has progressed from simple data access and reporting to complex analytical, creative, and intelligent support. With the rapid development of Internet technology, web-based decision support has become part of the evolution. Whether web-based or local, an intelligent DMSS is an interactive and dynamic management system that supports non-routine decision-making and evaluation (Marakas, 2003). Figure 3 sketches this evolution by highlighting the dominant decision support techniques during each decade. Attention has focused on decision technology in support of various E-business activities, but there has been a paucity of research exploring DMSS for E-business strategy development. Some research surveys the state of the art or the trends and potentials of decision technology mediated
E-business (Eom, 1999; Papazoglou, 2001; Carlsson & Turban, 2002; Gregg & Philippakis, 2002; Shim et al., 2002; Ganguly & Gupta, 2004; Hayes & Finnegan, 2005; Bhargava et al., 2007; Valente & Mitra, 2007). Most researches agree that rapid advancements in data warehousing, OLAP, data mining, intelligent agents, and the web technology add new and powerful capabilities to decision making support systems. Other studies offer conceptual decision support models in support of general E-business applications (Mavetera & Kadyamatimba, 2003; O’Brien, 2007; Syam & Bhatnagar, in press). A number of these studies focus on web-based decision support from the online customer’s perspective (O’keefe & Mceachern, 1998; Chiasson & Lovato, 2001; Grenci & Todd, 2002; Manshady & Dai, 2005; Levent, 2007; Kim et al., 2007; Razmerita &
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Figure 3. Evolution of decision support techniques
Kirchner, 2010). Most of these studies focused on conceptual models without establishing practical decision support prototypes. A third group of studies present DMSS prototypes to facilitate particular E-business activities. Examples include a worldwide real-time decision support system that delivers operations research (OR) tools to facilitate E-commerce applications (Kalakota et al., 1996), web-based decision support applications using SAS software for data management, statistical analysis, and forecasting (Cohen et al., 2001), and a web-based physician profiling system to manage customer relationships through E-business decision support applications (Kohli et al., 2001). Others present intelligent product recommendation systems for E-commerce (Xiao et al., 2003), a business to business (B2B) approach that deals with E-business people interactions and negotiation to settle strategic differences (Ramos et al., 2003), and agent-based merchandise management support systems for B2B e-commerce
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(Park & Park, 2003). Still others offer a web-based consumer-oriented intelligent decision support system for personalized e-services (Yu, 2004). Al-Qaed and Sutcliffe (2006) designed an adaptive decision support system for E-Commerce that matches the appropriate tool support and decision strategy advice to the user’s preferences and motivations. Their focus was on providing proper system advice during operation rather than providing an integrated decision support framework to guide strategies. In addition, McGregor et al. (2006) presented a shareable, web service-based intelligent decision support system for on-demand business process management. More recently, Denguir-Rekik et al. (2009) developed a multicriteria decision making support system to aid the marketing team of an e-commerce organization in its activities. In Chongwatpol and Sharda (in press), a spreadsheet-oriented decision support system was implemented to help making telecommunications pricing decisions for state networks.
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None of the previous studies offer comprehensive decision support architecture to facilitate E-business strategies in real applications. The EBDMSS architecture promises to close this research gap by linking business strategies to a broad range of measures, examining important business issues facing E-business managers, and providing a complete and integrated view of Ebusiness management.
EBDMSS ARCHITECTURE SPECIFICATION The EBDMSS aims to assist E-business managers in: (1) precisely forecasting the E-market demand/ supply quantity and total profit, (2) accurately making long-term and short-term E-business strategy plans, (3) explaining, justifying, and reporting
the outcome forecasts and recommendations, (4) performing effective simulation experiments with proposed policy changes (pricing, advertising etc.) and marketing conditions (competition, coordination etc.). In the process, the EBDMSS will support managerial decision making in a comprehensive, integrated, and continuous manner (Forgionne, 2000).
EBDMSS CONCEPTUAL ARCHITECTURE The proposed EBDMSS, like its DMSS predecessors, has the conceptual architecture shown in Figure 4 (Wang & Forgionne, 2007). As the figure illustrates, the architecture is organized around the paradigm of inputs, processing, and outputs.
Figure 4. EBDMSS conceptual architecture
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Inputs The EBDMSS has a data base, knowledge base, and model base. The data base contains critical problem and attribute data directly relevant to E-business strategy, including the values for uncontrollable events, decision alternatives, and decision criteria. Critical problem data includes relevant elements needed to estimate marketing requirements, network performance, and personnel skill sets, among Figure 2’s EBDMSS functions. Attribute data consist of the economic variables needed to perform the strategic analyses and the e-marketing characteristics of interest to E-business managers. The knowledge base holds problem knowledge, such as formulas for converting available data into the EBDMSS model’s parameters, guidance for selecting decision alternatives and problem relationships, production rules describing the relationships between the screen interactions and desired display reports, or advice in interpreting possible outcomes. Intelligent and real-time assistance will be available when the user selects system functions dealing with model, data, and dialog management. A final input is the model base, a repository for the fully specified E-business strategy models and the methodology for developing results (simulations and solutions) from the models. The model is delivering intelligent support dynamically by delivering the economic, management science, and other expertise embedded in the stored accounting, economic, and management science constructs. Processing E-business managers utilize webbased computer technology to process the inputs into problem-relevant outputs. Figure 5 illustrates the EBDMSS processing architecture with the major measures (depicted in squares) and the corresponding decision factors (depicted in ovals) and relationships (depicted as arrow lines) specified. Processing will involve: (1) organizing problem parameters – accessing the data base, extracting the decision data, and organizing the information in the form needed by the EBDMSS decision model and solution methodology; (2) structur-
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ing the decision problem – accessing the model base, retrieving the EBDMSS decision model, and operationalizing (attaching organized parameters to the EBDMSS decision model components); (3) simulating policies and events – using the operationalized EBDMSS model to perform the computations needed to simulate outcomes from user-specified alternatives and then identifying the alternative (or alternatives) that best meets the decision criterion (or criteria) among those tested; (4) Finding the best problem solution – accessing the model base, retrieving the appropriate solution method, and using the retrieved method to systematically determine the strategy alternative (or alternatives), among all possible alternatives, that best meets the decision criterion (or criteria). The EBDMSS can use E-business component problem ideas, concepts, and knowledge drawn from the knowledge base to assist users in performing these processing tasks. Such intelligent assistance distinguishes the proposed system from a traditional decision support system. Meanwhile, as indicated by the top feedback loop in Figure 4, the data and reports created during the Ebusiness strategy analyses and evaluations can be captured and stored as INPUTS for future processing. These captured inputs are stored as additional or revised fields and records, and the data base is dynamically updated accordingly. As in DMSS predecessors, the EBDMSS input feedback helps to support the E-business manager’s strategic decision making process in a continuous and interactive manner (Cook, 1993; Balasubramaniana et al., 1999; Forgionne, 2000). Outputs Processing will automatically generate visual displays of the status reports, forecasts, recommendations, and explanations desired by E-business managers (Figure 5). The status reports will identify relevant EBDMSS uncontrollable events, decision alternatives and criteria, and show the current values for these problem elements. Forecasts will report the events and alternatives specified in the E-business strategy simulations and the resulting projected values of the deci-
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Figure 5. EBDMSS processing architecture
sion criteria. The recommendations will suggest the values for the E-business strategy decision alternatives that best meet the criteria, and the corresponding criteria values, under current and forecasted values for the uncontrollable events. Explanations of the variables and reports, which are offered to the user through readily accessible Help screens, will justify the recommendations and offer advice on further processing. Such advice may include suggestions on interpreting the output as well as guidance for examining additional scenarios. As indicated by the bottom feedback loop in Figure 4, the E-business manager can utilize the outputs to guide further EBDMSS processing before exiting the system. Typically, the OUTPUTS feedback will involve E-business strategy outcomes, cognitive information, task models, and what-if, goal-seeking, and other types of
sensitivity analyses. As with DMSS predecessors, the EBDMSS output feedback can be used to extend or modify the original strategy analyses and evaluations and can also help to support Ebusiness strategy decision-making in a continuous manner (Steiger, 1998; Forgionne, 2000). The proposed EBDMSS can support all phases of the E-business strategy decision making process in a complete, integrated, and continuous manner. Critical problem data can be captured in the data base. The EBDMSS can be used to organize this captured information, generate timely focused reports, and project E-business strategy-relevant trends. Such processing helps the decision maker to quickly monitor the E-business decision environment, set objectives, and evaluate the processed information for strategic opportunities or problems, thereby supporting the intelligence phase of decision making.
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The EBDMSS can provide the analyses in vivid detail with tables, graphs, and other supporting material. Such material will increase the E-business manager’s confidence in the recommendations, improve the manager’s perception of system effectiveness, and enable the E-business manager to better explain, justify, and communicate the strategic decisions during the implementation process. Along with the original analyses and evaluations, the EBDMSS feedback loops also increase the E-business manager’s confidence in the recommendations.
EBDMSS COMPONENTS The EBDMSS supports the decision making phases introduced in Simon (1960). As Figure 6 indicates, the integrated system delivers the functions of an executive information system (EIS), a decision making support system (DMSS), and an expert system (ES), while supporting all phases of the decision process in the E-business strategy making situation. The embedded EIS is an integrated series of applications that enables E-business managers to easily access critical information related to Ebusiness strategy. Like most executive information systems, it locates and extracts pertinent EFigure 6. EBDMSS components
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business data, captures the extracted data, and automatically forms the data warehouse needed to perform the EBDMSS analyses and evaluations. This EIS component helps users discern E-business strategy problems and opportunities and gather pertinent environmental information, which supports decision making intelligence. As with EIS predecessors, E-business managers can utilize the EBDMSS EIS functionality to interactively filter and focus the relevant information, utilize the information to operationalize E-business strategy models, and justify the system’s reports with explanatory details (Forgionne, 1997). This is realized by setting up filters in the query which can be defined from a list of parameters, for example, time window, market sector, region, etc. With expert system (ES) assistance, the EBDMSS EIS, like its IDMSS predecessors, also displays reports from the user’s specific queries (Forgionne & Kohli, 2000). By using the EBDMSS’s DMSS component, and with the aid of the embedded ES and EIS components, E-business managers can utilize the information gathered through the intelligence phase of strategy making to generate decision alternatives and to establish the environmental variable levels for the models (Design phase). These operationalized models can then be used with the DMSS component and the embedded ES
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component to help E-business managers evaluate the alternatives and select the best one (Choice phase). For example, SAS ETS Times Series Forecasting System is capable of making forecasts for time series data from beginning to end, managing data, building model, and providing all reasonable forecast models and delivering them in different file format to users. The system chooses the best model according to certain statistics criteria, but other alternatives are available. The EIS and ES components can offer problem ideas, concepts, and knowledge drawn from the knowledge base to help users gain confidence in, and execute, the selected E-business strategies. Such support promotes the Implementation phase of decision making (Sauter, 1997; Forgionne, 2000; Forgionne & Kohli, 2000). The E-business implementation assistance is offered through readily accessible EBDMSS Help screens. Within the help screens, the E-business manager can browse archived and categorized problem knowledge, or conduct keyword and advanced searches through the extensible EBDMSS knowledge base. These captured inputs, after being properly parsed and verified, will be added to the EBDMSS Knowledge Base for future usage.
EBDMSS SYSTEM IMPLEMENTATION Successful application of DMSS techniques involves understanding the risks and addressing them in implementing the system (Gallegos, 1999). To promote this notion, a Web-based prototype system was developed for E-business applications using the proposed EBDMSS framework.
EBDMSS Implementation Methodology The current version of the EBDMSS prototype is based on the Client-Intermediary-Server network technology. A software integration and prototyp-
ing approach was adopted for facilitating system implementation and operation. Microsoft Windows Server 2008, running Internet Information Server (IIS) and Microsoft Visual Studio.Net, provides the backend and web-server functionality. Microsoft’s recommended hardware was implemented for optimal performance. To efficiently and effectively implement the EBDMSS for specific E-business applications, we utilize an Object-Oriented conceptual modelling approach to uniformly represent classes and relationships of items, services, consumers, vendors, as well as decision procedures, data, models, and knowledge. To enable intensive, dynamic, and speedy applications of data inquiry, update, and management to support strategic decision making, we implement MS Access database technologies enhanced with the ADO.Net connection, which provides easy and consistent access to data sources. At this stage, the dot Net (.Net) based approach is selected as the desired development and implementation environment. The.Net approach was favored in this case because it offered a consistent, secure, cost-effective, and more flexible development and implementation than the available alternatives. This approach lends itself well to Object-Oriented design and web-based applications. The ultimate goal is to distribute the EBDMSS applications over the Internet, for easy and timely access, and the.Net approach facilitates this goal. Future implementations may make use of Service-Oriented Architecture (SOA) and/or Representational State Transfer (REST) architectures. Using the web as the front-end, the current EBDMSS can facilitate E-business strategy-making efficiently and effectively in the dynamic and fast-changing global business environment. From the data perspective, when a query or a request to model forecast occurs, a connection is made to the database where the business critical data (including historical records and simulation results) are stored (Pol & Ahuja, 2007). The data
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adaptor is then created with the desired SQL query statement on the data storage. While processing the query or the model forecast simulation, a dataset is generated to store the query or forecasting output. Different control methods can be employed on the dataset to create illustrating forms and diagrams. Also, by building the connection to the database via ADO.NET, records can be added, updated, or deleted from the database whenever needed. In brief, the EBDMSS is implemented as a web-based decision support application. Once in the system, the user performs the E-business management analysis and evaluations by navigating with point and click operations through the display pages of the system. These operations invoke the EIS, DMSS, and ES functions of the integrated EBDMSS. While all major operations
Figure 7. EBDMSS sample system displays
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are described briefly, only some are displayed (Figure 7) for the sake of brevity.
EBDMSS System Illustration In a typical E-business strategy session, the manager will explore new opportunities and problems or conduct a strategy evaluation. If the session involves exploration, management will be facilitated if available patterns are presented and suggestions are presented for consideration and refinement. Strategy evaluation can be facilitated by providing a vehicle for the E-business manager to quickly examine potential alternatives, study the consequences, and refine the analyses dynamically as the results unfold. These typical
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scenarios are fully supported by the EBDMSS Web-based prototype. As displayed in Figure7a, the WELCOME page enables the user to access the EBDMSS. Once in the system, the user can interactively select the EIS or go directly to the DMSS. Selecting the EIS button will lead the user to the EIS page of EBDMSS. From the EIS page, the user will be asked to interactively select the desired data range (e.g., year 2010 by month or September 2010 by day) from the predefined drop-down list (which is called from the EBDMSS data base), as shown in Figure 7b. The system will ensure the user has selected the “REQUIRED” Installation (i.e. data reports during a certain time period). If not, a warning message window will pop up to remind the user to choose properly. After choosing the required data source from the drop-down list, the user can further select desired information operations, such as the “View” and “Update” buttons, offered from the EIS screen. Selecting the first “View” button will access the Information View page. From the Information View page, the user can select to “Sort” the current data records by specifying a sort criteria (e.g., by date or the value of Unit Cost) or to “Filter” the current data set by specifying the filter property (e.g., to show the data records with Quantity Demanded higher than 10), and these selections will generate customized reports of the selected data records, and therefore offer an ad hoc view of the E-business critical data of interest during a specified time period. Alternatively, selecting the “Update” button will put the user in the Information Update Page. From the update screen, the user can obtain Information on the proper format needed to input the data successfully into the EBDMSS, modify the current records if necessary by clicking the “Edit” link at the beginning of each record, or add new records by selecting the “Add new data” button above the data table. Once in the proper format, the updated data will be read into the EBDMSS
database for further and future processing. The user can also choose to delete any existing record by clicking the “Delete” link at the end of each record. By using the Visual Basic.Net data form classes, it is possible to protect columns and validate data entries, to generate audit trails which record who changed what and when, and to handle user input interactions. Selecting the “Analyze” button will lead the user to the Information Analyze page as displayed in Figure 7c. From this screen, the user can select the desired variable from the list on the left column, in the range which has been specified by the data selection from the previous EIS page. When the user has chosen a certain variable, s/he can then view the corresponding analysis histograms for the specified time range. As illustrated in Figure 7c, variable “SC” (sales cycle) has been selected and the chart shows the resulting histograms for the period specified at the previous data selection page (Figure 7b). The user can also change the variable and analyze other available variables from the specified data source on this page. Within the EIS page, if desired, all ad hoc query reports, data updates, and analysis reports can be printed by clicking the “Print” button embedded in the IE window. The user can return to the EIS page by clicking the “Go-back” link on every sub-page anytime and select other data sources for further information analysis. Selecting the DMSS button from the Welcome display will invoke the functions of the DMSS component. Within this module, the user can compute and estimate the E-business revenue and cost with specified input, and generate the Ebusiness forecasting and strategy reports. Prior to the forecasting and simulation, a brief introduction to the DMSS session will be displayed (Figure 7d). E-business strategy involves a wide range of measures and corresponding decision factors. These elements will influence the feasibility and desirability of strategy initiatives. The EBDMSS contains a fully specified decision model, which uses such predictors to forecast outcomes from
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these initiatives. To use the model, the user must specify the required initiatives such as quantity supplied (QS), unit cost of the product/service (UC), and company’s fixed cost (FC) such as utility and management overhead. Selecting the “Forecast” button will take the user to the forecasting session, from where the user will be able to enter proposed inputs and view the forecasted outcomes. Alternatively, if the user selects the “Analyze” button, s/he will enter the strategy analysis session and s/he can compare and analyze multiple strategy plans and corresponding outcomes. Selecting the “Forecast” button on the DMSS introduction page will display an electronic form that enables the user to enter such input for forecasting (Figure 7e). From the Forecast Input Specification page, the user can specify the required E-business strategy initiatives and get a corresponding outcome forecast. There is a list of required inputs and explanations for such inputs and general guidance for selecting decision alternatives and problem relationships are readily available by clicking the “Help” button (a sample pop-up page is shown). After entering the inputs, the user can select the “Run” button to generate the forecast report and display the forecasted outcomes. From the FORECAST REPORTS page (Figure 7f) the user can obtain detailed explanations to support outcome reports by selecting the “Details” button. The detail reports offer explanatory computations that justify the summary report. For instance, selecting the “Business Core” button yields the Business Core Report, while the “Analytical eCRM” selection generates the e-CRM Report. Alternatively, the user can select the “Print” button to print the forecast report in a printer-friendly version. Selecting the “Back” button will return the user to the DMSS introduction page. By selecting the “Analyze” button from the DMSS introduction page, the user will enter the strategy analysis session from where s/he can compare and analyze multiple strategy plans and corresponding outcomes. To start the strategy
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analysis session, the user can select the “Start to Play” button and enter an electronic input form page that looks similar to the forecast input specification page. Different from the forecast input page, here the user must click the “Confirm” button after entering the required input data. Then selecting the “Run” button will lead the user to the accumulative outcome analysis page, which enables him/her to compare multiple inputs and outcomes simultaneously. With the plot chart analysis, the user will obtain a clear picture of the projected relationship between a specific input plan and the forecasted outcome. As a result, the user will understand better the effect of the input decisions on the outcomes and plan better accordingly. If the user wants to start a new analysis session, s/he can click the “Clear and play again” link from the output page.
EBDMSS IMPLEMENTATION STRATEGIES In designing a system, information system specialists often consult with end users, identify current and potential requirements, and then design the system to meet the identified requirements with prototyping and other rapid application development (RAD) tools (Dzida & Freitag, 1998; Chandar & Krovi, 1998; Forgionne, 2000; Sauter & Free, 2005). Through exploratory study with managers, the desire to establish an information center typically staffed with information system specialists to assist practitioners with the application and identify potential enhancements is recognized (Forgionne, 1997; Shen-Hsieh & Schindler, 2002; Sauter & Free, 2005). As noted by Forgionne (1997), the focus has been put on efficiency, cost effectiveness, and user acceptance. In the context of this paper, three basic requirements for such an EBDMSS were identified at the beginning: (1) the practitioners should be provided a friendly and adaptive interface (Jolly-Desodta et al., 2002; Al-Qaed & Sutcliffe, 2006); (2) the users
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should be able to manage data in a transparent and visual way (Zhang & Pu, 2006; Levent, 2007); (3) the managers should get timely and intelligent support throughout the decision making process (Forgionne, 2000; McGregor et al., 2006). Set against this current field setting, the EBDMSS was designed, developed, and implemented with an adaptive design strategy that relied on rapid prototyping and interfacing, and other forms of RAD tools. Besides the heavy use of prototyping, several new strategies were utilized and evaluated in the process. These strategies, which involved but were not limited to adaptive development tools, team composition, and organizational issues, offer important lessons for successful design, development, and implementation of future decision making support systems. Generally, the strategy relied heavily on computer software engineering (CASE) and ObjectOriented Analysis (OOA), using the dot Net-based approach the Visual Studio.Net System. As with previous studies, these approaches have led to greater clarity of usage, more ease of development, and reusability for future enhancements (Pol & Ahuja, 2007). The Visual Studio.Net system based E-business planning reports or graphs can be viewed in corresponding HTML format for rapid distribution via the Web and can also be saved to the local computer for future reference. The current Visual Studio.Net version provides new Web-enabled data visualization capabilities which enable us to embed interactive graphics in a Web page (Pol & Ahuja, 2007). The design and development experiences suggest that decision making support systems can be effectively implemented through an adaptive design strategy. While the Visual Studio.Net system offers one such suite, there are others available, such as the SAS System for Information delivery. Studies that utilize such alternative integration tools can broaden the application base, and confirm or refute the findings from this study. Empirical experiences also suggest that DMSS design, development, and implementation should
be a team effort (Forgionne, 1997; Ruland & Bakken, 2002). As suggested by Forgionne (2000), the team should be composed of the affected managers, information system personnel, and technological specialists proficient with the tools needed to address the management problems. A single information system specialist is unlikely to be proficient with, or even aware of, all the pertinent tools (Nader & Merten, 1998; Forgionne, 2000; Al-Qaed & Sutcliffe, 2006). Therefore, several specialists with problem-specific technological expertise are needed to design and develop a decision making support system. The current E-business planning application required personnel with econometric, management science, marketing science, and information systems expertise.
EBDMSS Implications The EBDMSS can be expected to improve the efficiency and effectiveness of the E-business strategic decision making process and outcome. By supporting all phases of decision making in a complete and integrated manner, the system can be expected to help the E-business manager recognize more strategic opportunities and problems, better identify the important strategy alternatives and events, more systematically and scientifically evaluate strategic alternatives, and generate pertinent justification to facilitate strategy implementation than current largely unguided approaches. These process improvements can be expected to yield more attractive E-business plans with resulting lower costs, higher revenues, and increased profits when compared to current efforts. The effort should also improve the strategy making skills of the E-business manager. Empirical studies will be needed to evaluate the theoretical gains. In the context of E-business management, the outcome evaluation criteria are mainly concerned with the business core and customer relationship perspectives, which can be manifested by the strategic measures and factors under each perspective in the EBDMSS frame-
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work. Such measures can be objectively recorded in a field setting or a simulated experiment. Staff proficiency properly measures the learning and maturation of the E-business decision maker. In addition to a periodical staff qualification assessment, users’ feedback can be assessed through a directed self evaluation survey on their experiences or acquired knowledge and skills with the use of the decision aid (Adelman, 1991). Process improvements may be assessed using two major measures: process effectiveness and efficiency. Process effectiveness is concerned with decision outputs, such as the quality of e-services with the decision aid and the number of products offered for sale or shipped out during a certain period, while process efficiency is concerned with how resources are used to achieve the objectives, such as the time for a sales cycle, the lead time (order-to-deliver time), and the general cycle time. Such process effectiveness and efficiency assessments can be objectively recorded in a field setting or a simulated experimental setting. Using the multiple criteria EBDMSS framework (as shown in Figure 5), the E-business manager can establish an evaluation model for strategic e-business decision support. Figure 8 shows such a strategy evaluation model utilizing the strategic measures specified in the framework. Based on the Analytic Hierarchy Process (AHP) concept (Forgionne, 1999), this strategy evaluation model associates a hierarchy of evaluation Figure 8. EBDMSS strategy evaluation model
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measures (for both decision making process and outcome assessment) relevant to the context of E-business strategy in an integrated fashion. Using the hierarchy in Figure 8, the E-business manager can make pairwise comparisons of alternative support systems, including the EBDMSS, across the multiple decision criteria. The AHP methodology then will convert the multiple measures into an overall scorecard value for each considered system. This AHP-based EBDMSS evaluation model, then, will identify, in rank order, the most best performing E-business strategy making support systems. The specifications of the evaluation model will be determined by the specific application settings and the data sources selected to operationalize the model and system. By collecting pertinent data and performing an AHP analysis on Figure 8’s hierarchy, the E-business manager can determine if there was more strategic decision value with or without the DMSS. The improvement, if any, can be expressed in relative terms and tied to the specific sources (measures) generating the improvement by working down the hierarchy. Moreover, this examination will reveal which sources contributed most to the improvement. Other sources, then, will be candidates for Ebusiness remedial efforts in the future.
EBDMSS
CONCLUSION The ongoing Internet and WWW revolution is dramatically changing the way individuals, groups, and organizations live, work, and conduct and manage business globally. In this paper, we investigated the decision support issues embedded in strategic E-business management by developing, operationalizing, and illustrating the integrated and comprehensive EBDMSS framework. Web-based decision making support systems, such as the EBDMSS, are ideal delivery vehicles for tools that provide dynamic and intelligent decision support to E-business managers (Forgionne, 1991, 1997; Marakas, 2003; Turban et al., 2007). The EBDMSS delivers, through web-based computing technology, econometric and heuristic programming models, statistical methodologies, data conversion formulas, production rules, and data warehousing techniques to assist E-business management in specifying a variety of decision factors, establishing profitable E-business plans, and forecasting for future development. As such, the EBDMSS is effectively delivering to practitioners, in a virtual and adaptive manner, a wide range of embodied expertise particularly focused on the E-business strategy making process. The proposed EBDMSS can enable practitioners to improve the decision making required in the E-business planning process by providing: (1) quicker and more accurate sensitivity analysis of market conditions and their impact on the demand relationships, (2) more timely sensitivity analyses of the proposed policy changes and their impact on profit, (3) operationally and computationally errorfree outcome evaluations and forecasts, (4) more intelligent, adaptive, and effective decision support for the long-term and short-term E-business planning process. As such, this system supports the managers during the E-business planning process in a comprehensive, integrated, and continuous manner. Using the web as front-end, the EBDMSS can facilitate E-business strategy making
more efficiently and effectively in the dynamic and fast-changing global business environment. The design of the EBDMSS illustrates how a link from E-business strategy to an E-business decision model could be established and how the model could be physically delivered through a DMSS. The EBDMSS framework also indicates that E-business strategy making will involve multiple decision criteria. Using this framework, the decision maker can establish an evaluation model for strategic e-business decision support, such as an AHP-based EBDMSS evaluation model. In practice, the EBDMSS architecture provides a means of identifying E-business opportunities and threats in the internal and external environment, analyzing current E-business capabilities and resources to address the opportunities and threats, and generating effective E-business strategies that would improve the company’s overall business performance and profitability. The EBDMSS also provides a stable point of reference for E-business companies to understand and manage the fundamental changes introduced by E-business initiatives, and it enables E-business managers to plan and allocate resources (including tangible and intangible strategic assets) more effectively and align strategic objectives with performance results. The reported EBDMSS implementation strategies also add value to information systems project management practice by identifying adaptive design approaches, tools, and experiences. We hope that this article stimulates additional research to overcome some limitations of this research. This paper offered a generic system for E-business strategic decision making. There is a need for additional studies that test alternative EBDMSS configurations, including the application of Service-Oriented Architecture (SOA) and/or Representational State Transfer (REST) based architectures, or utilize other integration tools. Further research could empirically test the proposed EBDMSS architecture within a corporate E-business and evaluate the effectiveness and efficiency of the system in the real E-business
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world. Multiple test users will be experimenting with the system and their behaviour and personal productivity will be tracked and recorded. Then using the AHP-based EBDMSS evaluation model (Figure 8), or an operationalized and updated version of the evaluation model, testing results can be generated to verify the significant improvement, or lack thereof, in both E-business decision making process and outcome with the use of the EBDMSS framework.
REFERENCES Adelman, L. (1991). Experiments, quasi-experiments, and case studies: A review of empirical methods for evaluating decision support systems. IEEE Transactions on Systems, Man, and Cybernetics, 21(2), 293–301. doi:10.1109/21.87078 Al-Qaed, F., & Sutcliffe, A. (2006). Adaptive Decision Support System (ADSS) for B2C Ecommerce. ACM International Conference Proceeding Series, 156, 492-503. Arnott, D. (2004). Decision support systems evolution: framework, case study and research agenda. European Journal of Information Systems, 13(4), 247–259. doi:10.1057/palgrave.ejis.3000509 Ba, S., Stallaert, J., & Zhang, Z. (2007). Price competition in e-tailing under service and recognition differentiation. Electronic Commerce Research and Applications, 6(3), 322–331. doi:10.1016/j. elerap.2006.06.005 Balasubramaniana, P., Nochur, K., Hendersona, J. C., & Kwana, M. M. (1999). Managing process knowledge for decision support. Decision Support Systems, 27(1-2), 145–162. doi:10.1016/S01679236(99)00041-X Bhargava, H. K., Power, D. J., & Sun, D. (2007). Progress in Web-based decision support technologies. Decision Support Systems, 43(4), 1083–1095. doi:10.1016/j.dss.2005.07.002
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Carlsson, C., & Turban, E. (2002). DSS: Directions for the next decade. Decision Support Systems, 33, 105–110. doi:10.1016/S0167-9236(01)00137-3 Chandar, A., & Krovi, R. (1998). User cognitive representations: The case for an object oriented model. Journal of Systems and Software, 43(3), 165–176. doi:10.1016/S0164-1212(98)10030-4 Chiasson, M., & Lovato, C. (2001). Factors influencing the formation of a user’s perceptions and use of a DSS software innovation. The Data Base for Advances in Information Systems, 32(3), 16–35. Chongwatpol, J., & Sharda, R. (in press). SNAP: A DSS to analyze network service pricing for state networks. Decision Support Systems. Cohen, M.-D., Kelly, C. B., & Medaglia, A. L. (2001). Decision support with web-enabled software. Interfaces, 31(2), 109–129. doi:10.1287/ inte.31.2.109.10625 Cook, G. J. (1993). An Empirical Investigation of Information Search Strategies with Implications for Decision Support System Design. Decision Sciences, 24(3), 683–698. doi:10.1111/j.1540-5915.1993.tb01298.x Denguir-Rekik, A., Montmainb, J., & Mauris, G. (2009). A possibilistic-valued multi-criteria decision-making support for marketing activities in e-commerce: Feedback Based Diagnosis System. European Journal of Operational Research, 195(3), 876–888. doi:10.1016/j.ejor.2007.11.020 Dzida, W., & Freitag, R. (1998). Making Use of Scenarios for Validating Analysis and Design. IEEE Transactions on Software Engineering, 24(12). doi:10.1109/32.738346 Eom, S. B. (1999). Decision support systems research: Current state and trends. Industrial Management & Data Systems, 99(5), 213–220. doi:10.1108/02635579910253751
EBDMSS
Forgionne, G. A. (1991). Decision Technology Systems: A Vehicle to Consolidate Decision Making Support. Information Processing & Management, 27(6), 679–697. doi:10.1016/03064573(91)90007-9
Hayes, J., & Finnegan, P. (2005). Assessing the of potential of e-business models: towards a framework for assisting decision-makers. European Journal of Operational Research, 160(2), 365–379. doi:10.1016/j.ejor.2003.07.013
Forgionne, G. A. (1997). A decision technology system to support Army housing management. European Journal of Operational Research, 97(2), 63–379. doi:10.1016/S0377-2217(96)00204-4
Holian, R. (2002). Management decision making and ethics: practices, skills and preferences. Management Decision, 40(9), 862–870. doi:10.1108/00251740210441422
Forgionne, G. A. (1999). An AHP model of DSS effectiveness. European Journal of Information Systems, 8, 95–106. doi:10.1057/palgrave. ejis.3000322
Hong, W., & Zhu, K. (2006). Migrating to internet-based e-commerce: Factors affecting ecommerce adoption and migration at the firm level. Information & Management, 43(2), 204–221. doi:10.1016/j.im.2005.06.003
Forgionne, G. A. (2000). Decision-Making Support System Effectiveness: the Process to Outcome Link. Information Knowledge Systems Management, 2(2), 169–188. Forgionne, G. A., & Kohli, R. (2000). Management Support System Effectiveness: Further Empirical Evidence. Journal of the Association for Information Systems, 1(3), 1–37. Gallegos, F. (1999). Decision Support Systems: Areas of Risk. Information Strategy, 15(2), 46–48. Ganguly, A. R., & Gupta, A. (2004). Data mining technologies and decision support systems for business and scientific applications. In Encyclopedia of Data Warehousing and Mining. Hershey, PA: Idea Group Publishing. Gregg, D. G., Goul, M., & Philippakis, A. (2002). Distributing decision support systems on the WWW: the verification of a DSS metadata model. Decision Support Systems, 32, 233–245. doi:10.1016/S0167-9236(01)00095-1 Grenci, R. T., & Todd, P. A. (2002). SolutionsDriven Marketing. Communications of the ACM, 45(3), 65–71. doi:10.1145/504729.504730
Jolly-Desodta, A. M., Jollyb, D., & Wawakc, F. (2002). Conception of a decision support system and its interface: Application to a teleoperation system. Journal of Intelligent & Fuzzy Systems, 12, 107–117. Kalakota, R., Stallaert, J., & Whinston, A. (1996). Worldwide real-time decision support systems for electronic commerce applications. Journal of Organizational Computing and Electronic Commerce, 6(1), 11–32. doi:10.1080/10919399609540265 Kim, D. J., Ferrin, D. L., & Rao, H. R. (2007). A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision Support Systems, 44(2), 544–564. doi:10.1016/j. dss.2007.07.001 Kohli, R., Piontek, F., Ellington, T., VanOsdol, T., Shepard, M., & Brazel, G. (2001). Managing customer relationships through E-business decision support applications: a case of hospital–physician collaboration. Decision Support Systems, 32(2), 171–187. doi:10.1016/S0167-9236(01)00109-9 Laudon, K., & Traver, C. (2007). E-Commerce: Business, Technology, Society (3rd ed.). Upper Saddle River, NJ: Prentice Hall.
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Levent, O. V. (2007). Consumer Support Systems. Communications of the ACM, 50(4), 49–54. doi:10.1145/1232743.1232747 Manshady, H., & Dai, W. (2005). Online Decision Support and Transactional System: A study of web-based technologies. Soft Computing as Transdisciplinary Science and Technology: Advances in Soft Computing, 29, 787–796. doi:10.1007/3540-32391-0_83
Park, J. H., & Park, S. C. (2003). Agent-based merchandise management in Business-to-Business Electronic Commerce. Decision Support Systems, 35, 311–333. doi:10.1016/S0167-9236(02)001112 Phillips, P. A., & Wright, C. (2009). E-business’s impact on organizational flexibility. Journal of Business Research, 62(11), 1071–1080. doi:10.1016/j.jbusres.2008.09.014
Marakas, G. M. (2003). Decision Support Systems in the 21st Century (2nd ed.). Upper Saddle River, NJ: Prentice-Hall.
Pol, A. A., & Ahuja, R. K. (2007). Developing Web-enabled Decision Support Systems. Belmont, MA: Dynamic Ideas.
Mavetera, N., & Kadyamatimba, A. (2003). A comprehensive agent mediated e-market framework. In Proceedings of the 5th International Conference on Electronic Commerce.
Raisinghani, M. S., & Schkade, L. L. (2001). EBusiness Strategy: Key Perspectives and Trends. In Proceedings of the IRMA 2001 Conference.
McGregor, C., Schiefer, J., & Muehlen, M. (2006). A shareable web service-based intelligent decision support system for on-demand business process management. International Journal of Business Process Integration and Management, 1(3), 156–174. doi:10.1504/IJBPIM.2006.010902 Nader, P. F., & Merten, G. A. (1998). The Need to Integrate and Apply Knowledge from three Disciplines-Business-Process Redesign, Information Technology, and Organization Development. The Journal of Applied Behavioral Science, 34, 246–249. doi:10.1177/0021886398343001 O’Brien, J. A. (2007). Introduction to Information Systems (12th ed.). New York, NY: McGraw-Hill. O’keefe, R. M., & Mceachern, T. (1998). Webbased customer decision support systems. Communications of the ACM, 41(3), 71–78. doi:10.1145/272287.272300 Papazoglou, M. P. (2001). Agent-oriented technology in support of e-business. Communications of the ACM, 44(4), 71–77. doi:10.1145/367211.367268
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Ramos, F., Junco, M. A., & Espinosa, E. (2003). Soccer strategies that live in the B2B world of negotiation and decision-making. Decision Support Systems, 35(3), 287–310. doi:10.1016/ S0167-9236(02)00083-0 Razmerita, L., & Kirchner, K. (2010). A Case Study in e-Custom Systems. In Web-based Support Systems: Advanced Information and Knowledge Processing (pp. 387–402). Data Mining for WebBased Support Systems. Ruland, C. M., & Bakken, S. (2002). Developing, implementing, and evaluating decision support systems for shared decision making in patient care: a conceptual model and case illustration. Journal of Biomedical Informatics, 35(5-6), 313–321. doi:10.1016/S1532-0464(03)00037-6 Sanders, N. R. (2007). An empirical study of the impact of e-business technologies on organizational collaboration and performance. Journal of Operations Management, 25(6), 1332–1347. doi:10.1016/j.jom.2007.01.008 Sauter, L. V. (1997). Intuitive decision-making. Communications of the ACM, 42(6), 109–115. doi:10.1145/303849.303869
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Sauter, V. L., & Free, D. (2005). Competitive Intelligence Systems: Qualitative DSS for Strategic Decision Making. The Data Base for Advances in Information Systems, 36(2), 43–57. Shen-Hsieh, A., & Schindler, M. (2002). Data visualization for strategic decision making. In Proceedings of the Conference on Human Factors in Computing Systems (pp. 1-17). Shim, J. P., Warkentin, M., Courtney, J. F., & Power, D. J. (2002). Past, present, and future of decision support technology. Decision Support Systems, 33, 111–126. doi:10.1016/S01679236(01)00139-7 Simon, H. A. (1960). A Behavioral Model of Rational Choice. In Simon, H. A. (Ed.), Models of Man (pp. 241–260). Steiger, M. D. (1998). Enhancing user understanding in a decision support system: a theoretical basis and framework. Journal of Management Information Systems, 15(2), 199–220. Syam, S., & Bhatnagar, A. (in press). A Decision Model for E-commerce-enabled Partial Market Exit. Journal of Retailing. Turban, E., Aronson, J. E., Liang, T., & Sharda, R. (2007). Decision Support Systems and Intelligent Systems (8th ed.). Upper Saddle River, NJ: Prentice Hall.
Wang, F., & Forgionne, G. (2005). BSC-Based Framework for E-business Strategy. In KhosrowPour, M. (Ed.), Encyclopedia of E-Commerce, EGovernment and Mobile Commerce (pp. 64–71). Hershey, PA: Idea Group. Wang, F., & Forgionne, G. (2007). EBBSC: A Balanced Scorecard Based Framework for Strategic E-business Management. International Journal of E-Business Research, 3(1), 18–40. Whelan, J., & Maxelon, K. (2001). E-business matters: a guide for small and medium-sized enterprises. London, UK: Pearson Education. Xiao, B., Aimeur, E., & Fernandez, J. M. (2003). An intelligent product recommendation agent for e-commerce. In Proceedings of the IEEE International Conference on E-Commerce (CEC’03). Yu, C.-C. (2004). A web-based consumer-oriented intelligent decision support system for personalized e-services. In Proceedings of the 6th International Conference on Electronic Commerce ICEC ‘04. Zhang, J., & Pu, P. (2006). Performance Evaluation of Consumer Decision Support Systems. International Journal of E-Business Research, 2(3), 28–45.
Valente, P., & Mitra, G. (2007). The evolution of web-based optimization: From ASP to e-Services. Decision Support Systems, 43(4), 1096–1116. doi:10.1016/j.dss.2005.07.003
This work was previously published in International Journal of Decision Support System Technology (IJDSST), Volume 2, Issue 4, edited by Pascale Zarate, pp. 50-68, copyright 2010 by IGI Publishing (an imprint of IGI Global).
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Section III
Tools and Technologies
This section presents an extensive coverage of various tools and technologies available in the field of global business that practitioners and academicians alike can utilize to develop different techniques. These chapters enlighten readers about fundamental research on the many methods used to facilitate and enhance the integration of this worldwide industry by exploring the usage of such tools as supply chain design, IT strategy, and new business models, all increasingly pertinent research areas. It is through these rigorously researched chapters that the reader is provided with countless examples of the up-and-coming tools and technologies emerging from the field of global business. With more than 20 chapters, this section offers a broad treatment of some of the many tools and technologies within the global business community.
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Chapter 3.1
MICA:
A Mobile Support System for Warehouse Workers Christian R. Prause Fraunhofer FIT, Germany Marc Jentsch Fraunhofer FIT, Germany Markus Eisenhauer Fraunhofer FIT, Germany
ABSTRACT Thousands of small and medium-sized companies world-wide have non-automated warehouses. Picking orders are manually processed by bluecollar workers; however, this process is highly error-prone. There are various kinds of picking errors that can occur, which cause immense costs and aggravate customers. Even experienced workers are not immune to this problem. In turn, this puts a high pressure on the warehouse personnel. In this paper, the authors present a mobile assis-
tance system for warehouse workers that realize the new Interaction-by-Doing principle. MICA unobtrusively navigates the worker through the warehouse and effectively prevents picking errors using RFID. In a pilot project at a medium-sized enterprise the authors evaluate the usability, efficiency, and sales potential of MICA. Findings show that MICA effectively reduces picking times and error rates. Consequentially, job training periods are shortened, while at the same time pressure put on the individual worker is reduced. This leads to lower costs for warehouse operators and an increased customer satisfaction.
DOI: 10.4018/978-1-60960-587-2.ch301
Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
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INTRODUCTION The four fundamental processes of a warehouse are (Tompkins & Smith, 1998): 1. To receive incoming goods for storing, 2. To store goods until they are required, 3. To prepare requested goods for shipping (picking), and 4. To ship the picked goods (sometimes called packing). Among all the processes of logistics, picking is the most problematic one because it is highly error-prone (Miller, 2004). Many different types of errors are known (Lolling, 2003): picking of wrong types or quantities of articles, complete omission of a type, and insufficient quality of delivered articles (see Figure 2). All these errors cause high costs for manufacturers and warehouse operators. Either because extra shipments and returns are necessary, or, in the worst case, because contract penalties have to be paid. In today’s lean production, where only small resource reserves are kept at the manufacturing site, the resources necessary for production are usually delivered to a customer just when he needs them. The orders are possibly known to the warehouse weeks before but delivery is expected exactly at the specified date. If an important item from the order is missing, this can mean that the whole production has to stop, incurring extra costs for the warehouse for courier delivery, and the customer who then lets the warehouse pay for the financial damage of the production halt. Besides causing huge costs, this certainly has potential to annoy customers. Accordingly, the primary goal for warehouses is to eliminate or at least reduce the number of errors. Especially warehouses with human workers are confronted with returns caused by incorrect delivery of items. But although humans constitute the soft spot in this process, completely automated solutions are not an option for most warehouses
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because human workers are much more flexible (see Figure 1). During economic peak times, warehouses are forced to employ unskilled workers in order to cope with the increased workload. These unexperienced workers are not familiar with the structure and organization of the warehouse, yet have to be operational in a short time. They do not have the time to learn from experienced workers where an ordered article can be found, what the fastest routes through the warehouse are, what the exact processes are, or what a certain article looks like. Nevertheless, work has to be completed without errors and under the same high time pressure that also skilled workers face. Picking errors and time pressure constitute the major problems for unskilled and skilled workers. Hence, there is a need for an intelligent assistance system that supports the workers. By preventing errors, such system also reduces the pressure put on each single warehouse worker. An assistance system for employees needs to support untrained workers as well as experienced workers in their usual way of working and not force them to change habits. Based on an initial requirement analysis, we propose the Interaction-by-Doing paradigm, which was realized in a first MICA prototype. Its success led to the development of the second MICA pilot for field testing in a productive environment. Figure 1. Worker in a non-automated warehouse
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Figure 2. Picking errors
In a field test we evaluated MICA’s usability, its effect on worker efficiency and estimated its world-wide sales potential. Finally, we present related work and conclude.
REQUIREMENTS AND CONCEPTS In collaboration with two medium-sized nonautomated warehouses, we initially collected requirements for our envisioned MICA system. Such system would reduce the pressure put on workers by assisting them with their tasks, and by preventing errors and the costly effects thereof.
For end-users and designers, design proposals can be understood as design probes to explore the characteristics and usefulness of a proposed system. When a prototype is available, end-users can try it and gain personal experience with it. The active involvement of users and a clear understanding of their tasks is the key for a successful system development. The ISO 13407 “Human-centred design processes for interactive systems” standard does not prescribe specific methods for how to achieve these goals; they are to be chosen according to what is state of the art and what is appropriate under the respective project circumstances. Based on practical experiences from other projects, we
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have devised a scenario-based approach, combined with user interviews, participatory observation and expert analysis, based on the structure proposed by Robertson and Robertson (1999) for mastering requirements. Their Volere process ensures that all important aspects of requirements are carefully addressed and that the methods applied have proven their value in practical work. The Volere process makes a distinction between global constraints affecting the project, functional requirements and non-functional requirements. Associated with this process is the Volere template. The template makes fine-grained distinctions between different types of requirements and requires that they are assessed in various categorizations. It also captures the rationale for each requirement as well as fit criteria. These criteria are used to evaluate customer satisfaction and dissatisfaction if a requirement is implemented or not. Hence, the Volere process ensures that all important aspects of requirements are carefully addressed.
REQUIREMENTS The requirements gathering process was directed by interviews with all stakeholders and focus groups at the two involved warehouses. These provided valuable insight into the work at the warehouse and contributed to a worthwhile understanding of the current and immanent problems, limits, tasks and benefits of a future support system. But much more important than the interviews and focus groups was the participative observation of the work in the warehouses for several days. Initially, the warehouse workers were quite cautious to work exactly to rule but soon they completely forgot the presence of the observers and reverted to their old habits. Quite remarkably this brought to light several important issues that would never have been discovered with interviews or focus groups: we could observe workers that were deliberately
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committing errors. For example, when an item was missing or broken they scanned in the correct bar code from the shelf and put another (wrong) item into the order box, thus producing two severe errors: an order with a wrong item (mix-up error) and removing another item from the warehouse that would leave the warehouse inventory in an inconsistent state, causing a missing article in a subsequent order. The reason for this observed behavior was the cumbersome process that had to be followed when an item of an order was missing or broken: the warehouse worker had to stop his picking and take the warehouse manager in. First he needed to find the warehouse manager in his office – usually on the other side of the warehouse – then inform him that an item was broken or missing. This could lead to some awkward situations due to the short-tempered nature of the warehouse manager. After that both had to go back to the location in the warehouse, so that the warehouse manager could investigate the situation. Then, mostly not without anew critique, the warehouse manager had to go back to his office, enter the error into the system and restart the picking order. Only now the worker could continue picking. This easily could consume more than 30 minutes. All in all we collected over 50 requirements that were prioritized by our own observation and by experienced workers and warehouse managers. The most important requirements can be summarized as follows: 1. Reduce error-rates. To be effective, MICA must reduce error-rates compared to existing assistance systems. Only this alleviates the workers’ fear of picking errors, while at the same time justifying the use of MICA from an economic point of view. 2. Provide the opportunity to process several picking orders at the same time. As experienced workers tend to process several orders at the same time to reduce walking distance.
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3. Support trained and untrained workers. MICA must support trained as well as untrained workers, because at peak times the permanent staff is reinforced with unskilled workers. Both groups have inherently different needs. Unskilled workers need a certain time to acquire the knowledge where to find an article. Navigation assistance should help to avoid making detours and to find articles on the picking list. At the same time, MICA should not interfere with habits of experienced workers. 4. Unobtrusive guidance. A novel technology gets rejected if people have to change their way of working or if they feel patronized. To achieve acceptance, a guidance system may not require much attention but should work in the background. It should only draw attention to prevent a picking error. 5. Usability. Interfaces should be intuitive, provide a good overview and be easy to learn because user training is expensive. Keeping the system responsive enables seamless user interaction and avoids idle time for workers. 6. Working hands-free. Simultaneous handling of mouse or keyboard would disrupt picking. Additionally, workers are usually unfamiliar with computer user interfaces. 7. Environmental conditions. Different environmental conditions play an important role for MICA. For example, the display should remain readable under unfavorable light conditions, while sound should remain hearable despite ambient noise.
in the sections below. Interaction-by-Doing is an enhancement of Interaction-by-Movement (Lorenz, Zimmermann, & Eisenhauer, 2005). Interaction-by-Movement means that moving towards a location is recognized by the system, which reacts with a proactive help. In Interactionby-Doing, interaction is not reduced to movement only but to multiple kinds of behavior. By this, no explicit interaction is necessary. A practical example is the picking process: when picking with support of a scanner, the worker passes articles by his scanner. The scanner confirms with an acoustical response. Not till then may the worker continue picking. In contrast, when the process is extended with an Interaction-by-Doing system, the worker just puts an article into the box. The Interaction-by-Doing system identifies the article in the background and interrupts the worker (using an appropriate modality) only in case of an error. Interaction-by-Doing eliminates the additional control process in picking and automatically helps with solving the problem by telling the user to remove the wrong article.
INTERACTION-BY-DOING
IMPLICIT INTERACTION
From above requirements, we derive MICA’s Interaction-by-Doing concept that builds on multi-modal and implicit interaction with a calm computing system that provides pro-active help to users with different experience levels. The different concepts’ implications are described
In explicit forms of interaction the user assertively communicates his wishes to the system via specific IT devices like mouse, keyboard or touch screen, and well-known interaction rules like clicking, dragging or typing. Other explicit interaction forms like gesture recognition can be socially
MULTI-MODALITY People’s interaction in a completely engineered environment relies on different modalities because a single modality may fail in a certain situation. For example, people in motion cannot focus their full attention on the interaction with a touch screen (Brewster, 2002). In contrast, noisy environments make speech less reasonable than other modalities.
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obtrusive if they involve sweeping gestures. When such gestures are required for interaction, the user might feel embarrassed because it looks strange to casual bystanders. Still, even if more subtle gestures (like a small tilting) are used, the user wants to explicitly and consciously communicate something to the machine. Implicit interaction is a passive form of formulating wishes. The idea is to analyze natural movement of the user and to derive reactions by the system. To be able to extract interaction information the system needs to know the tasks and intentions of the user in the specific context. Implicit interactions are unobtrusive but are also less reliable. Yet the success of a system is highly dependent on its usability because simple and intuitive interaction increases user acceptance. Natural interaction means multi-modal interaction with explicit and implicit interaction modalities. Therefore, the idea of MICA is to offer a suitable interaction modality to every particular situation.
CALM COMPUTING Weiser and Brown came up with the term of calm computing. They demanded that technology engages both the center and the periphery of our attention, and in fact moves back and forth between the two (Weiser & Brown, 1997). In MICA, the normal picking process remains the center of the worker’s attention. MICA stays in the periphery where additional information about the current task can be retrieved. It only moves to the center if an error occurs. A system based on the Interactionby-Doing principle beholds the workers’ actions with various sensors to detect problems.
PROACTIVE HELP Proactive applications want to give adequate help when the user is expected to need it (Kaufmann
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et al., 2007). A computer system offers proactive help if it deems that this could reduce a worker’s stress or if he is about to make an error. The intention is not to point out that the worker errs but to avoid errors. This saves time and reduces worker frustration. Because of that, help is presented as a non-binding offer. This is necessary so that the worker does not feel patronized. Furthermore, wrong reactions of the system – i.e., the worker’s intention was not predicted correctly and hence the system reacts in an undesired way – do not cause unnecessary disturbance as the worker is never explicitly interrupted in his work. One example is well-known from navigation systems: if the user leaves the proposed path, the route is silently recalculated accounting for the deviation. Hence, the proactive help assures that the optimal path is always displayed without interrupting the user with error messages or commandments. Similarly, MICA does not interrupt the current workflow when it recognizes a deviation. Instead, it just highlights the help button, so that appropriate help can be obtained with a single click. Concrete situations or problems are identified by observing the worker’s actions. Systems’ reactions rely on the analysis of the movement history. Hence, movement sensors and a positioning technology are necessary.
DIFFERENT EXPERIENCE LEVELS Calm computing makes it possible that experienced users are not interrupted by system alerts addressed to unskilled workers. They can work in the efficient ways they are familiar with. As Interaction-by-Doing facilitates implicit interaction, less explicit interaction forms have to be learned by users. This supports both, skilled and unskilled users. Proactive help is designed as a non-binding offer so that experienced workers are not disturbed. At the same time, unexperienced workers are thankful for the help when in need.
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DEVELOPMENT METHODOLOGY OF MICA
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The first MICA project started in 2004 running until 2006. The goal of the project was to prototypically explore the possibilities of supporting humans in their every-day working environment using technologies like context-awareness and user modeling with mobile devices. For this exploration it did not matter what working environment that was. The prototype served three purposes: firstly, it allowed us to gather first experiences with a variety of hardware and software technologies used in MICA. Secondly, it shows the technical feasibility of the concept. And thirdly, early feedback from potential users and customers can be collected. For example, it is possible to run user tests under laboratory conditions, or to show the prototype on trade fairs. This helps to review the general concept and shows opportunities for future development. Depending on success and reception of the prototype, a second project can be set up. For this successor the prototype is reworked, and a more mature pilot version is then tested in the field, i.e., in a productive environment.
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FIRST PROTOTYPE As a first setting for MICA, a warehouse scenario was chosen, where MICA would assist warehouse workers in the picking process. However, the MICA architecture was not meant to be constrained to this specific setting but to be a platform for realizing very different scenarios. The major challenges of the first MICA prototype are: • •
Workers need hands-free support, Interaction modalities for system input must fit the current situation and task,
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Volume levels of audio output must automatically adapt to environment noise levels, A display must react to rapidly changing lighting conditions, and The system must be highly responsive, never leaving the worker to wait for it.
MICA has to provide a combination of explicit and implicit interaction methods in blue-collar environments. It faces situations in which the spatial relations of objects change dynamically. Hence, the worker’s environment has to be monitored and interpreted in real time. On the one hand, this enables MICA to identify a worker’s need for help and to react on implicit interaction clues like stumbling or search behavior. On the other hand, workers interact explicitly with MICA, for example by pressing the “OK” button to confirm the execution of a proposed action after a warning message. In particular the combination of implicit and explicit interaction on various modalities leads to natural blended interaction (Eisenhauer, Lorenz, Zimmermann, Duong, & James, 2005). MICA guides the worker through the warehouse, keeps track of articles picked (see Figure 7 b) and pro-actively offers help. The following subsections give short descriptions of the different components of the original MICA system. At the same time, this section serves as a baseline for explaining the modifications of the MICA pilot in the next section. Both sections are therefore structured similarly, describing the necessary ingredients for Interaction-by-Doing like the MICA trolley, navigation, article identification, and the software design. This is followed by summaries of the realized concepts and the interaction experience. As a case study, the MICA prototype provided valuable lessons learned that were used to improve its successor, the second MICA (pilot).
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TROLLEY The multi-modal interaction in MICA relies on a wide range of different sensors for retrieving implicit interaction information, an input device for providing explicit interaction possibilities and devices to give feedback to the worker; among these is pen-touch display, RFID readers and antennas, a WLAN data connection, and a highperformance CPU for coordinating all interaction devices in the worker’s direct vicinity. Besides being heavy and bulky by themselves, the devices also need a power supply large enough to keep the system running during a complete workday. A device that workers use throughout the entire picking process is the trolley on which order boxes are placed. The trolley therefore became the heart of MICA hosting all the devices required, as one essential requirement is not to strain the worker in his work with heavy equipment.
ARTICLE IDENTIFICATION MICA receives picking orders from a server and lets workers select their next order. Workers – while always being connected to MICAvia the picking trolley – are presented a picking list, which is automatically synchronized with the articles already picked. For this, the MICA trolley is equipped with RFID technology which continuously monitors the items that are already picked. Articles and boxes (into which the articles are picked) are tagged with passive RFID tags. The floor of the MICA trolley is made up of a 4x4 array of RFID readers that read articles placed above them (see Figure 3). When an article or a box is placed on the trolley, MICA can determine if the article is correct and if it is placed in the right box. Hence, with MICA the worker is not constrained to work on one order at a time, but he may choose several orders and work on them simultaneously, while MICA makes sure that no article is wrong, forgotten or picked into a wrong shipping box.
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Figure 3. RFID antenna array for identifying articles and their location on the MICA trolley
Our RFID readers operate at High-frequency (approx. 14MHz, HFID) electromagnetic wave band, which has a limited reading range, but reveals good characteristics when used with conductive materials or liquids. This is important because the prototype is intended for office items (e.g., hole puncher) which occasionally contain metal or liquids. Diverting from the original plan, the MICA prototype only has a 1x2 array of RFID readers at the bottom. The reason is that the shape and diameter of an antenna affects the reach of the reader’s field above the antenna. So their large size enables an elongated vertical read area up to 30cm above the trolley loading area, while limiting the maximum number of simultaneous orders that can be processed at a time to two. In practice, it turns out that reading articles on a second layer above ground layer is unreliable. Articles randomly disappear or are attributed to the wrong box if an article is placed near the boundary of two adjacent RFID areas.
NAVIGATION MICA realizes an indoor navigation system to guide the worker to the next article on the picking list. Such navigation system essentially consists
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of two parts: A hardware part for determining the physical position of the worker, and a software part calculating and presenting a route. Drafts for tracking mechanisms in MICA combined Ekahau - a low precision WLAN tracking - with fine grained ultra-wide band (UWB) tracking (Eisenhauer, Lorenz, Zimmermann, Duong, & James, 2005). However, the actual realization of the MICA prototype completely relied on WLAN tracking leaving aside other tracking technologies because of the high cost associated with equipping large areas with UWB tracking systems. Given a list of articles the worker has to pick for his orders and storage locations of individual articles, the navigation system determines an optimal route for the worker through the warehouse. For this computation, the route calculation determines the distances between each pair of articles along valid paths in the warehouse with the A* algorithm (Hart et al., 1968). In the next step locations are ordered so that the round trip that visits all locations has an optimal length. This sorting – known as the Traveling Salesman Problem (TSP) (Menger, 1932) – is solved with a brute-force algorithm that finds the optimal solution. This is the most expensive computation step with a complexity of O(n!).
SOFTWARE MICA uses a bus concept for input and output data. The buses are based on a Jabber/XMPP (see Saint-Andre, 2004) instant messaging infrastructure. Collected data – for example, raw sensor data from pointing gestures – are refined into messages with MICA data – e.g., pointing direction and angle – and posted to a chat room, and thus forwarded to subscribed receivers in this room. Here, user modeling and dialog management servers pick up that data. Also connected to the bus are server components that provide databases, host navigation processing, manage users and trigger pro-active help. Having higher memory
and processor requirements, these components are placed on a stationary machine providing enough resources for the software. Responses from server components are then posted on the output bus for rendering on user interfaces (Schneider, Lorenz, Zimmermann, & Eisenhauer, 2006). A known problem with Jabber is that the amount of network traffic grows exponentially with the number of participants in a room. The common bus is therefore split into several rooms so that the number of participants and messages in each room is less than that in one common room for all. The XMPP protocol was chosen because of its openness and interoperability. Protocol implementations exist for different programming languages and platforms; even resource restricted mobile devices. For this resource thriftiness, Lorenz and Zimmermann (2006) embedded ARFF (http://www.cs.waikato.ac.nz/~ml/weka/ arff.html) messages (containing the data sent by MICA subsystems) into the XMPP messages. ARFF messages have their own header containing sender and receiver information, and data specific to the command. All components of the MICA server are implemented in a stand-alone Java application. On the client side, the GUI is implemented in C#. Originally the client included several intelligent functions, but due to high processor load and resulting low responsiveness of the GUI several functionalities were moved to the server. A light-weight client receiving detailed instructions remained.
PRO-ACTIVE HELP Kaufmann et al. (2007) interviewed and accompanied several workers and managers during their work in two non-automated warehouses. The aim was to get to know the authentic processes in a warehouse in order to identify situations where help was needed. Besides helping workers to avoid picking errors by observing picked articles, and
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helping them to find articles quicker by guiding them to the storage location, other stressing or time consuming activities were identified. Resulting from these, eight implicit interaction principles were developed that indicate if a worker is in need for help. These interaction principles are used as input to a finite state machine, which then triggers a means of pro-active help. For example, a common situation was that an article was damaged or missing. When this happened the worker had to fetch the warehouse manager to show to him the situation. During this time, the picking process is effectively on hold for up to 30 minutes (as described in Section 2). For such situations, the MICA prototype includes a wireless headset and video camera so that the worker can remotely consult the warehouse manager without having to walk to her office (see Figure 4). One of the indicators is that a worker is looking about or moving his head horizontally in a noticeable way (i.e., scanning for a specific item). The video stream continuously generated by the helmet-mounted video conference camera was re-purposed to detect horizontal movements between individual video frames. Other indicators used as input for the proactive help system included a worker standing still in the warehouse, the picking of a wrong item, or the worker walking too far away from his trolley in the wrong direction.
Figure 4. Warehouse worker with headset and a small video camera mounted on his hardhat
MULTI-MODAL INTERACTION Besides allowing graphical interaction with the worker, the client outputs speech like “Put two hole punchers into box A”. The voice output is composed from sampled partial sentences, hence providing high quality output at the cost of flexibility and a higher cost for hiring professional speakers to speak the partial sentences, quantities and article names. By offering several output modalities, the chance of misunderstanding due to inappropriate environmental conditions like loud noise is reduced. The MICA software architecture is a mix of centralized and distributed components. Input from different kinds of sensors is collected by MICA clients, fused with other sensor data on the same client, and filtered through a recognition mechanism. The pre-processed data is then published to a data bus on the local network that is used by MICA components (like sensors, servers, etc.) for their communication. Besides touchscreen interaction, Interactionby-Doing is offered as input modality. Each of the modalities is chosen for the correct situation. In the normal case of picking, the worker is situated beside the trolley, so that it is difficult to type on the touchscreen. Thus, Interaction-by-Doing is used. In cases where the worker has to go to the screen anyway, e.g., when video chatting with the overseer, touchscreen input is expected.
LESSONS LEARNED FROM THE FIRST PROTOTYPE The biggest problems we encountered were of physical nature. The batteries for power supply of the mobile components (e.g., RFID readers) have to be well proportioned. Long before the batteries are depleted, the readers’ reliability begins to degrade. This adds to an already existing problem with the article identification. The original assumption that every reader reads
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only the area above itself and not the area above another reader cannot be confirmed. The readers’ electromagnetic fields overlap or even twist around each other when objects are brought into the field. Though some modern antennas’ lobes have almost the desired shape in free space, it is impossible to prevent fields from getting distorted when there are obstacles. Similarly, the radiobased localization needed frequent recalibration in an ever-changing environment. On the software side, unreliabilities in the WLAN connection caused problems with the XMPP-based communication bus infrastructure on. A disruption of connection meant that either messages in chat rooms were lost or that messages were delivered twice. This could mean that first a lot of outdated messages were delivered before current messages were received. This led to some confusion for the test persons. Finally, there were some usability problems because the mobile PC used a pen input. Many people would have preferred to use their fingers and have larger buttons or active areas. However, much of the functionality in the prototype’s interface was not needed.
SECOND PROTOTYPE After the first prototype of MICA proved its feasibility, a follow-up pilot project started in 2008. The goal was to evaluate the road capability of MICA as well as its usability and market potential. A pilot allows testing a design and making adjustments in time. It also shows if anything is missing and provides quantitative proof that the system has potential to succeed on the larger (full) scale. For MICA, the new requirement of being suitable for productive use brought new challenges so that many aspects of the first prototype were re-engineered. Also, the scenario where MICA would be used (warehouse) was now fixed from the beginning.
With Antriebs- und Regeltechnik GmbH (ART), a medium-sized enterprise for testing MICA was found. Founded in 1955, 700 employees in Germany, Romania and Poland develop machinery supplies for the manufacturing industry. MICA ran at the headquarters’ central warehouse. ART faces the typical problems of non-automated warehouses, and at the same time is continuously looking for solutions that support their just-in-sequence and just-in-time services. ART actively supported and contributed to the pilot and assembled the new hand pallet truck at its workshop. Compared to the warehouses of the first MICA prototype, the requirements at ART are a bit different. They produce many of their articles specifically for their customers in small quantities (sometimes only one single unit). So for them, even one error in tens of thousands of picking items is too much. Their warehouse is smaller with fewer workers, and a much friendlier atmosphere. Environmental conditions like lighting and noise levels are rather constant. Importantly, ART’s products constitute a challenge for MICA’s original article identification and positioning: most items mainly consist of metal parts, are stocked in metal shelves and are handled in metal baskets. This is a conceivably bad situation for RFID and WLAN tracking. The typical order includes several baskets that are interchangeable but have to be prepared in a fixed order. These differences and the immanent productive use of MICA necessitated design changes that are discussed in the following sections.
THE MICA HAND PALLET TRUCK The working process at ART requires that two boxes stand side by side on a pallet, and can be stacked up to the fourth level at eye height. A finger touch enabled Tablet PC is mounted at common eye level. It is tiltable and turnable so that people can adjust it to their personal needs.
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Two batteries supply the Tablet PC and the RFID readers for article identification and positioning (see following sections). A standard power supply cable for charging ensures the easy recharge of batteries. Full charging takes four hours so that it fits well between two working shifts. A fully charged battery supplies energy for ten hours of MICA-enhanced work so that it lasts an entire shift without having to recharge. The MICA hand pallet truck is resistant against impact and scratches, electronic parts are protected. It is as easy to use as a normal hand pallet truck and fulfills safety at work guidelines. At the same time, hardware costs do not endanger profitability of the whole system.
NAVIGATION The positioning engine of the MICA pilot requires a higher accuracy. It needs to identify each single stockyard, situated no more than 30cm apart from each other. Ekahau cannot assure this accuracy, especially in a metal flooded and constantly changing environment. Hence, we changed to RFID-based tracking: RFID tags, working on another frequency range as the article tags, are placed on the floor of the storehouse. A RFID reader mounted underneath the trolley scans these tags and gets the corresponding location from a database. Floor RFID tags are usually placed in holes in the floor. This is not possible at ART because of a special anti-static and expensive ground. Using special adhesive labels which are resistant against physical force, we avoided drilling holes. As corridors are wider than the width of the hand pallet truck, we placed three tags in a row orthogonal to the corridor to guarantee reading a tag on any track the truck could move through the corridor. Each of these tags is associated with the same X/Y coordinates. The worker’s walking direction is derived from his current and previous positions. The
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new MICA system rotates the map so that viewing direction is always up as opposed to a fixed orientation with north always being up. Article locations are stored as their “true” location, which is not directly on the paths defined by corridors. Instead the articles are projected to the nearest path; the angle between projection vector and moving direction determines if an article is in the left or right hand shelf (see Figure 5). Additionally, now 3D map data may be annotated with individual path costs, therewith allowing to reduce traffic in selected corridors. The brute-force path length optimization with NP-complete TSP from the first MICA performs unsatisfactorily when applied to a picking list with 20 or more different locations. But an approximation algorithm (the “nearest neighbor” algorithm) usually provides good results with an average length of 1,25 times the shortest possible route. In the worst case, the route is at most O(log d) longer than the optimal route (Rosenkrantz, Stearns, & Lewis, 1977). Its computational complexity at any given time is O(n) for sweeping through all the remaining article locations to find the article with the shortest distance to the current location. With a normal PC this means that planning for thousands of locations is possible without a noticeable delay.
Figure 5. Picking article from right hand shelf
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ARTICLE IDENTIFICATION As the RFID readers of the first prototype were integrated in the trolley’s bottom they occasionally failed to read articles on the second level. In the pilot setting this detection ratio is even lower due to the fact that articles are metallic. This requested a change in RFID technology, from HF to Ultra High Frequency (UHF). UHF is prevalent in logistical applications: besides worldwide standardization in ISO 18000-6C (EPC global) (ISO 18000-6C), it features long reading ranges, bulk reading of several transponders at favorable prices, and compact chip design. Additionally, we need to be 100% sure that no article passes the scanner without being recognized. Picked articles appearing and disappearing randomly are obviously not acceptable. Also cross checking after picking is no option as it would entail no enhancement compared to the situation without MICA. Therefore, the RFID readers are mounted on a frame that is put on top of the boxes. These readers do not scan the contents of boxes, but register articles that are moved in and out of a box. The reading area is carefully calibrated to exactly cover the whole box opening. It thus assures that every passing article is read but nothing else from nearby shelves. This preserves a natural way of working and preserves valuable energy on the mobile device. In order to identify the direction of movement of a transponder through the box opening we analyze the RSSI value (Receive Signal Strength Indication (IEEE, 802.11)) of the tag. The obtained value qualifies the received field strength of wireless communication applications and is transmitted by the reader for every reading event of a transponder. Mathematical calculations yield the information if movement is upwards or downwards when two readers are placed on top of each other. For two boxes stand side by side on the pallet, two readers (for RSSI movement direction detection) cover each box opening. A frame carrying
one pair of readers slides up and down the truck’s mounting to rest on the rear stack of boxes. The second pair is attached to the front of the frame with its read area covering the front box opening (see Figure 6). The frame construction is quite heavy, but workers need to move it up to the fourth level of boxes (height of the head). Therefore, a bowden cable enables effortless moving. Maintaining a continuous electromagnetic RFID field consumes much energy. This is too much for a battery powered device, particularly if there are five such readers (four for article identification and one for positioning). A way to reduce energy consumption is to turn off the field while no article is potentially in range. Built-in ultrasonic (US) sensors that consume negligible amounts of electricity are coupled with the readers and automatically trigger a reading process. The US sensors detect moving objects within a range of up to 70cm. Any object passing the sensor immediately turns on the reader that creates the electromagnetic read field within milliseconds. Every transponder within reading range is then read. Configuration and placement of the rear readers’ triggers is carefully adjusted because US waves emitted by them would reflect from the back side of the front readers and trigger a read because the echo would mistakenly be interpreted as coming from an article. After a predefined period the reader switches back to standby. This method ensures that a reader only reads while an article is placed into a box or taken out of it. Thus the power consumption is reduced to a minimum, resulting in a higher operating time of the whole system. Besides saving energy the trigger has two additional advantages: 1. The already low probability of reading articles in the shelf is further reduced, because readers sleep most of the time, and 2. It is possible to identify if an article is not detected by RFID, in case of a broken RFID tag. In that case, the MICA system prompts
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Figure 6. Lifting truck with boxes and RFID mounting of the second MICA pilot
the worker to re-pick the article and initiates a multi-step error correction process.
PRO-ACTIVE HELP Several indicators that were used for the pro-active help of the first MICA are no longer available. For example, the video conferencing is no longer necessary due to the warehouse size, and therefore the head-mounted camera is not available. Similarly, persons are no longer tracked and it is therefore impossible to detect if they wander away from their trolley. As a consequence of this, we concentrated our efforts on the reliability of the remaining areas of pro-active help, navigation support, article identification through article pictures and picking error correction.
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MULTI-MODAL INTERACTION The constant environment in terms of lighting and noise within the warehouse makes a combination of auditive and visual output on the table PC most reasonable. Speech composition from partial sentences is not feasible anymore because there is an unlimited and dynamically changing space of possible wordings. The MICA pilot rather generates audio output with a text-tospeech engine allowing synthesizing any sentence from its written form. As ART has a complicated naming scheme for articles where each name is composed of 15 numbers and letters it makes no sense to spell this name. By referring to an article’s stockyard instead, there is no danger the text-tospeech engine generates incomprehensible article names. The visual interface has been re-factored to present less information at once.
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Figure 7. (a) Original design in English; (b) SAP design in German for ART
Menus and other complex explicit interaction constructs in the GUI have been removed because most workers have little computer experience. Instead, buttons and other active areas have been enlarged. The main interaction method, Interaction-by-Doing, remains: movement and picking still make up for most of the interaction between worker and MICA
SOFTWARE COMPONENTS Building a system that is used in a productive environment requires higher diligence than building an experimental prototype serving only as a proof of concept. The first prototype was implemented with an architecture for a wide and diffuse application domain reflecting personal research interests.
It was to be used under laboratory conditions. Implementation sprints with ad-hoc processes took place before trade fairs. Necessary cleaning-up and refactoring with reuse in mind would occur in the time in between, where deadlines were less troubled. This, however, did not happen. MICA was not suitable for field-testing. In preparation of the study, MICA’s software sources experienced a general overhaul and large portions of MICA’s code had to be rewritten from scratch by an all new team because scientists of the first prototype had changed to new projects. Differently from its predecessor, the new MICA system is much more focused, and no longer a platform for studying multi-modal interaction and user modeling under different conditions. Instead it is fully aimed at the warehouse scenario. Usability and understandability to the common warehouse worker are the primary objectives. Also a higher degree of reliability is necessary to not disrupt daily work of the productive environment. However, one design goal is still to keep the MICA software open for using different hardware devices and software components with the system. MICA’s backbone - instant messaging based communication - is replaced by the Java Message Service (JMS), which provides enterprise-class reliability in message oriented architectures. JMS guarantees message delivery for the publishsubscribe model, thus replacing the chat room mechanism, where messages could get lost if a client temporarily disconnects from the chat room. Also messages are sent with a time to live, which prevents a flood of messages that could occur if a component reconnected to the message bus. To save bandwidth low-priority messages (like position updates) are discarded earlier in case of a transport bottleneck. As JMS is capable of transporting entire Java objects, the ARFF message encoding was mostly removed, leaving it only as an interface to the.NET GUI. The original monolithic server part is broken up into distributable components that communicate with each other through JMS messages, thus fa-
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cilitating the relocation of individual components between different physical machines. The bus architecture is modified according to the observer design pattern: Every component (e. g., a worker location sensor) publishes its messages, while other components (e. g., navigation and route computation) subscribe to the update of components that they are interested in.
THE EFFECTS OF MICA ON ART The biggest change for ART resulted in the elimination of an explicit cross-check in their picking process: prior to the introduction of MICA, workers went through the repository with a shoppingcart-like trolley. They collected articles, brought them to the shipping area, cross checked the articles, and put them into a new box on a pallet. Afterwards, they repeated all steps until the order was completed. The manual cross checking process has now been replaced by MICA’s tag identification during the picking process. A box-by-box cross-check to keep an overview is no longer needed. The old MICA trolley is replaced by a hand pallet truck equipped with MICA technology (see Figure 6). Thus, picking onto a pallet on the hand pallet truck accomplished in one step. This safes time compared to the former multi-step process. One of MICA’s software modules connects it to the SAP Warehouse Management server of ART. This real-time data link keeps stock lists up to date. When picking starts, the items of the order are marked as “reserved”, and are immediately removed from stock when picking finishes. Formerly, there was no “reserved” state and updates would take hours. It was possible that the last item of a kind was picked in a previous order, so that the next one could not complete although started. Stock outage is a frequent problem and requires that picking starts early with enough reserve time before delivery, so that the missing piece can be-
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come available again. Hence, MICA reduces the time reserved for picking and packing.
USABILITY EVALUATION We put a considerable amount of effort into the design of the MICA GUI. It underwent several changes in the last years (see Figure 7a and Figure 7b): internal design reviews, customization to the SAP design guide, translation from English to German, and an adaptation to ART processes. Finally, a usability study was conducted with ART warehouse workers. A usability evaluation measures the extent to which users in their specific context can achieve their goals effectively, efficient and satisfactorily (ISO 9241, 1998b). Effectiveness is put on level with usability. A product, system or software supports effective processing of a task, if it provides all functions needed by a user to completely achieve his goals. Beyond that it can be rated as efficient if its functions are operated accurately and effortless. Satisfaction with the product, system or software necessarily (but not sufficiently) results from the perceived easiness and intuitiveness to operate the system. This unfolds in a model of stages, which stimulates the presentation of results. Effectiveness constitutes a measure of the usability potential. Results of a user test represent the efficiency, and satisfaction is measured with a questionnaire depending on the sample size of the usability study. Tests like the Software Usability Measurement Inventory (SUMI) (Kirakowski & Corbett, 1993) are recommended for sample sizes above twelve users. With lower sample sizes, like in our case, a shorter questionnaire provides a rough impression of the overall satisfaction. This, of course, is not statistically representative, but nevertheless delivers useful information for the usability assessment and suggestions for improvements. We first conducted a participatory expert evaluation of the interface with three experts – which
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meant that all experts were accompanied by two testers – one taking notes and the other in dialog with the expert taking care that no action on the interface is left uncommented and all relevant aspects of the system have been covered. That means that the tests were conducted in close collaboration with experts with the “thinking aloud”-method (e.g., Nielsen, Clemmensen, & Yssing, 2002) and subsequent discussions. In this test we identified 51 violations of requirements for the design of dialogs (according to ISO 9241-10 (ISO 9241, 1998a)). Most problems were related to violations of conformity with user expectations, error tolerance, or self-descriptiveness. Additionally, we identified and eliminated screens, which had lost functions, like the registration screen. The original plan arranged for testing eight workers. But due to time restrictions this evaluation had to be conducted prior to the full completion of the system. In particular tests with RFID-reader hardware and its interplay with the software were only partially completed. The evaluation of the MICA pilot was therefore conducted with a limited set of three more experienced workers. The main reason for this limitation was that the system still was not completely robust, and that there was a risk that it had to be rebooted. The participants were tested with real picking orders. Each usability test consisted of a short introduction of the worker into the nature of the test and to the method of “thinking aloud”. The tests were always conducted with three investigators: one that constantly stimulated the worker to comment each of his actions and two that took notes and pictures. All critical incidents were then collected and analyzed according to ISO 9241-10 and their specific violation of the dialog requirements. At the end of the test the workers were asked to complete a questionnaire measuring their satisfaction with the system. As expected this early testing revealed a potential for optimization. A series of critical incidents could be assigned to 69 violations of dialog requirements that limit the efficiency with respect to task completion (see Figure 8a).
In particular a high number (20) of malfunctions occurred that limit the effectiveness of the MICA System. However, the tests also revealed many positive aspects of MICA where the participants distinctively emphasized an unqualified success in conformance with dialog principles, as well as eight malfunctions that were directly eliminated during the test (see Figure 8b). The results of questionnaire and interview indicate a good satisfaction with MICA in spite of its malfunctions. Participants were confident that the system simplified their picking process, saved time and prevented errors. Specifically, they highlighted that search and identification of items in the picking process with the system was much easier, less error prone and much simpler than picking without MICA. The violations of dialog principles and identified malfunctions resulted in a revised version of MICA in the actual field-tests.
EVALUATION OF EFFICIENCY In this section we present results of the MICA evaluation based on (Gillmann, 2008). An economic evaluation of investments must always be based on solid investment appraisals. This in turn requires well evaluated data, describing the logistical process. Key economical measures of logistic systems are time, quality and cost. To evaluate these data, the MICA pilot is implemented and tested in the ART warehouse. To measure potential quality improvement and time reduction, as well as potential cost reduction, the paper based manual picking process is benchmarked against a MICA supported picking process. In particular, process times and failure rates are monitored. To evaluate the impact of MICA as a support system for (particularly unskilled) workers, both the manual picking process and the MICA supported picking process are tested with groups of skilled and unskilled workers. Skilled workers included all of the workers that worked in the respective ART warehouse (less than ten). A
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Figure 8. (a) Usability violations; (b) Usability conformance
similar number of unskilled workers were brought into the warehouse either from other departments of the company or by us. The workers in the evaluation worked on real orders that were finally shipped to customers. During the entire evaluation phase we accompanied workers in the warehouse, drawing maps of the paths they took and taking the picking times. In the MICA experimental groups, the warehouse’s paper-based quality control procedures were carried out in parallel by an experienced worker in order to detect problems that MICA might not have detected. In all experimental groups, the orders
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were finally (after picking was completed) crosschecked by an experienced worker to ensure the quality of the delivery. The results of this were also recorded to check for quality improvements through MICA. The duration of the evaluation phase was four months. The full time was sliced into multiple smaller time slots, each one to host one of the four variations (with MICA vs. without MICA, experienced vs. unexperienced). One major customer of the warehouse in our study produces large industrial machines (several meters in size), who receives electrical compo-
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nents and cables in various sizes from ART. In our study we included all orders for one series of machines from this customer. Hence, this study is highly representative for such orders. Due to the high number of orders from this customer, it can in turn also be considered as representative for all of the warehouse’s orders. To accurately determine the efficiency of MICA, we additionally need to take into account the cost of processes implied by MICA (e.g., tagging of articles before they are stored), the monetary cost of MICA hardware like RFID, and potential maintenance costs due to hardware wearout. We use common investment appraisal methods (Tucker, 1963) to calculate economic sense and an investment risk for this specific case. The overall picking process divides into four sub-processes: preparation, picking, inspection, and confirmation & hand over. Picking and inspection times depend on item quantities. Preparation and confirmation & hand over are independent of item quantities. Using MICA, the item dependent process time is reduced by 36%, when used by skilled workers, and by 75% when used by unskilled workers. A significant processing time reduction of 46%, for skilled workers and 61% for unskilled workers is demonstrated for the item
independent process time (see Figure 9. Picking times are hidden due to data confidentiality). The field trial focuses on two different error rates: error rate per order item (Ei) and error rate per picking order (Eo). Ei shows how many order items are picked mistakenly. Eo shows how many picking orders are processed mistakenly and in turn would result in a customer complaint. Without using MICA, the error rate per position is 0.48% / 4% (skilled / unskilled workers). More than this, a subsequent final cross-check of articles picked cannot detect all picking errors. Thus the error rate per order turns out to be 14.3% / 25% (skilled / unskilled workers). In contrast, with using MICA, all of the human errors are detected, thus the error rate per item and per order drops to 0%, for skilled and unskilled workers. The investment costs divide into one-time expenses and operating costs. One-time expenses are, for example, expenses for hardware, software, and infrastructure. Furthermore, assuming a good “confidence” in inventory data, according to correct and real time confirmations, dispatching can be organized more efficiently, thus “safety stock” can be reduced, yielding additional cost savings. Based on experimental data, investment in MICA reaches a ROI of 38% at a yearly picking
Figure 9. Average picking process times
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quantity of approximately 80,000 items. A typical amortization time of 18 months is reached at a yearly picking quantity of approximately 280,000 items. MICA demonstrates a substantial reduction of processing times, as well as a zero picking failure rate, both with a group of skilled and unskilled workers. Additionally, unskilled workers using MICA reached a picking performance almost as good as skilled workers. This shows very high potential of MICA for broad spread industrial use. In summary, the evaluation shows that MICA successfully supports complex picking processes. Potential customers are companies with small to medium sized goods, each of medium to high value, with inhomogeneous order structures and with high overall picking quantities.
ANALYSIS OF SALES POTENTIAL In order to find out the potential of MICA for the market, we finally present an analysis of sales potential based on (Brauner, 2009). The sales potential is defined as the portion of the market potential that a particular firm can reasonably expect to achieve (Lucas, 1975). With the analysis we address the question, how big the market is in the relevant industries. As MICA is a new system, no reviews of existing similar systems can be taken into account. Instead, a questionnaire was distributed to 300 companies, 25 completed questionnaires were sent back. The amount of companies for which MICA can be useful is too large to contact them all. Because of that, a mix of random and quota selection was conducted (Schnell & Kreuter, 2003). As only particular employees of a company can answer the questions, we tried to contact experts via already existing contacts. The questionnaire introduces the MICA systems and afterwards lets the probands reflect about their current picking system. Finally, the probands are asked if they consider buying a MICA-like system to determine the sales potential. About
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17% consider buying a MICA-like system, so we assume the sales potential to be 17%. According to the Bureau of Labor Statistics (2009) there are about 6,000 pickers in the US machinery industry. Hence, the sales potential for the US machinery industry is 17% of 6,000 = 1,020 MICA trolleys. We gathered the same information for the rest of the world and interpolated data where no data was available according to general economic performance data. In summary, we computed a sales potential of several ten thousand MICA-like trolleys for the whole world. Again concrete number are subject to data confidentiality but can be obtained from SAP on request.
RELATED WORK MICA combines in a single application contextawareness and RFID technology. On the one hand, its context-awareness is quite similar to that of systems like Oppermann and Specht (2000), Eckel (2001) or Long et al. (1996). These systems determine the physical context of the user from his location and orientation in order to provide him with useful information about his surrounding, i.e. exhibits in a museum or sights in tourism, respectively. In contrast, MICA is multi-modal, deals with a changing environment, and uses a set of different sensors to obtain context information. It does not only provide plain situational information but assists the worker with his current task. With respect to this, it is more like the context-aware assistants of Dey et al. (1999), Yan and Selker (2000) or Rhodes (1997). MICA, however, also serves a logistical assurance objective by guaranteeing that picking errors do not occur. MICA also has some aspects in common with smart shopping applications like that from Asthana et al. (1994) because it helps the user to locate items and guides him to their storage location. On the other hand, RFID is attracting more and more attention in business environments
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as it provides an interface between the physical world and an enterprise’s information infrastructure (Want, 20004). A major role in the business environment plays logistics, where the tracking of goods and their delivery status are traditional applications (Weinstein, 2005). Companies use huge RFID gates on the entrance and exit areas of their warehouses to automatically register incoming and outgoing goods while these are still loaded on trucks (Lefebvre, Lefebvre, Bendavid, Wamba, & Boeck, 2006). Historically, RFID technology and tags were too expensive to track individual items. As prices for tags have recently dropped significantly, even item level tracking of low-price goods becomes possible. Bendavid et al. (2006) present a study where a RFID-based single-item hand-over between customer and supplier is analyzed under laboratory conditions. Yet their system does not provide support or detect errors during the picking process. With this respect, RFID-enabled shopping carts are what comes closest to MICA’s article tracking (e.g., Kourouthanassis, 2003). For RFID-based locating Luimula et al. (2010) use a similar approach but as MICA is operated by humans, obstacle tagging is not necessary. Unlike other system like the IBM MAGIC system, which uses gaze tracking for the prediction of cursor movement (Zhai, 1999), in MICA a combination of speech and pen input with user movement in a physical environment was favored. MICA, as opposed to many other multi-modal applications, has prominent physical parts that have original practical reasons: the trolley is already there so that the worker does not need to carry the items himself. Only article and box identification are added but they do not change the natural way of working. Likewise, the worker would be moving in physical space also without MICA. This observation is the basis for Interaction-by-Doing.
CONCLUSION We presented a support system for warehouse workers: its requirements, the Interaction-byDoing design principle, its evolution through prototype and pilot, and evaluations of usability, effectiveness and sales potential. The MICA prototype is successful as a proof of concept. The reworked MICA pilot proves successful in field-tests, where it measurably supports warehouse workers in the picking process. Thanks to multi-modal interaction MICA is applicable to the changing environments of a warehouse. Calm computing principles and pro-active help make it usable for unskilled workers as well as for experienced workers without having to interrupt the familiar way of working. Intuitive handling as well as support for every worker’s experience level is assured by the Interaction-by-Doing concept. Pro-active help prevents errors before they occur. During its evaluation, several parts of MICA were adapted and improved. The positioning system is enhanced from WLAN-based to RFIDbased technology, thus increasing its accuracy when identifying a single stockyard. The new RFID-enabled hand pallet truck frame proves to scan 100% of the picked articles without interfering with the usual way of working. At the same time, no articles from the repository are accidentally read. The frame fulfills the picking process requirements of the ART warehouse and could be adapted to the needs of other warehouses. The usability evaluation reveals that search and identification of articles is much improved with MICA. The results already indicate a good satisfaction with MICA in spite of still existing malfunctions. Participants are confident that the system would simplify their picking process, save time and prevent errors. It can be expected that the new introduced interaction concepts and an improved MICA system that overcomes the detected malfunctions and violations of dialog principles will fully satisfy users’ needs.
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MICA’s potential to reduce the number of errors and to speed-up picking processes in nonautomated warehouses is shown in the economic evaluation. Enterprises with high picking quantities are offered a high potential to reduce costs. During economic peak times MICA helps as well unskilled workers to reduce picking errors even under high time pressure. The analysis of sales potential shows that there is a market for MICAlike systems. The future work consists of transforming the pilot into a productive system. For this, mainly stability must be enhanced and errors have to be found in high-pressure tests. Besides software errors, the reliability of the RFID reading has to be checked. Multi-modality can be advanced to more modalities as in the current status. However, MICA’s future also depends on economic decisions of companies that traditionally have conservative customers.
ACKNOWLEDGMENT Our thanks go to our designer Lars Zahl for the images, and to our former colleagues who helped realizing the MICA pilot: Oliver Kaufmann, Feras Nassaj, Rossen Rashev, Daniel Meckenstock and Kin Voong, as well as the teams of SAP Research, deister electronic and ART. Comments from the anonymous reviewers helped us very much to improve this paper.
REFERENCES Asthana, A., Cravatts, M., & Krzyzanowski, P. (1994). An Indoor Wireless System for Personalized Shopping Assistance. In Proceedings of the IEEE Workshop on Mobile Computing Systems and Applications, Santa Cruz, CA (pp. 69-74).
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Bendavid, Y., Wamba, S. F., & Lefebvre, L. A. (2006). Proof of concept of an RFID-enabled supply chain in a B2B e-commerce environment. In Proceedings of the 8th international Conference on Electronic Commerce: the New E-Commerce: innovations For Conquering Current Barriers, Obstacles and Limitations to Conducting Successful Business on the internet (ICEC ‘06) (Vol. 156, pp. 564-568). New York: ACM. Brauner, S. (2009). Untersuchung des internationalen Marktpotentials eines interaktiven, kontextsensitiven und multimodalen Kommissionierungstools für die SAPAG mit abschliessender Empfehlung für das weitere strategische Vorgehen [Investigation of the international market potential of an interactive, context-sensitive and multi-modal picking tool for SAP AG with final recommendation for further strategic proceeding]. Unpublished Master’s Thesis. Brewster, S. (2002). Overcoming the lack of screen space on mobile computers. Personal and Ubiquitous Computing, 6(3), 188–205. doi:10.1007/ s007790200019 Bureau of Labor Statistics. (2009). Packers and packagers, hand. National Employment Matrix. Dey, A. K., Futakawa, M., Salber, D., & Abowd, G. D. (1999). The Conference Assistant: Combining Context-Awareness with Wearable Computing. In Proceedings of the 3rd International Symposium on Wearable Computers (ISWC), San Francisco (pp. 21-28). Eckel, G. (2001). LISTEN - augmenting everyday environments with interactive soundscapes. In Proceedings of the I3 Spring Days Workshop Moving between the physical and the digital: exploring and developing new forms of mixed reality user experience, Porto, Portugal.
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Eisenhauer, M., Lorenz, A., Zimmermann, A., Duong, T., & James, F. (2005). Interaction by movement - one giant leap for natural interaction in mobile guides. In Proceedings of the International Workshop on Artificial Intelligence in Mobile Systems. Gillmann, L. (2008). Wirtschaftliche Evaluierung eines innovativen multimodal interaktiven Systems zur Unterstützung von Kommissionierprozessen [Economic evaluation of an innovative multi-modal interactive system in support of picking processes]. Unpublished Master’s Thesis. Hart, P. E., Nilsson, N. J., & Raphael, B. (1968). A formal basis for the heuristic determination of minimum cost paths. IEEE Transactions on Systems Science and Cybernetics, 4(2), 100–107. doi:10.1109/TSSC.1968.300136 IEEE802.11. (2007). IEEE Standard for Information technology-Telecommunications and information exchange between systems-Local and metropolitan area networks-Specific requirements: Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications. ISO 13407. (1999). Human-centred design processes for interactive systems. ISO 9241. (1998a). ISO 9241-10: Ergonomic requirements for the design of dialogs - part 10 guidance on usability. ISO 9241. (1998b). ISO 9241-11: Ergonomic requirements for office work with visual display terminals - part 11 guidance on usability. ISO/IEC 18000-6. (2004). Information technology - Radio frequency identification for item management - Part 6: Parameters for air interface communications at 860 MHz to 960 MHz.
Kaufmann, O., Lorenz, A., Oppermann, R., Schneider, A., Eisenhauer, M., & Zimmermann, A. (2007). Implicit interaction for pro-active assistance in a context-adaptive warehouse application. In Proceedings of the 4th international conference on mobile technology, applications, and systems and the 1st international symposium on Computer human interaction in mobile technology, Singapore. Kirakowski, J., & Corbett, M. (1993). SUMI: the software usability measurement inventory. British Journal of Educational Technology, 24(3), 210– 212. doi:10.1111/j.1467-8535.1993.tb00076.x Kourouthanassis, P., & Roussos, G. (2003). Developing Consumer-Friendly Pervasive Retail Systems. IEEE Pervasive Computing / IEEE Computer Society [and] IEEE Communications Society, 2(2), 32–39. doi:10.1109/MPRV.2003.1203751 Lefebvre, L. A., Lefebvre, E., Bendavid, Y., Wamba, S. F., & Boeck, H. (2006). RFID as an Enabler of B-to-B e-Commerce and Its Impact on Business Processes: A Pilot Study of a Supply Chain in the Retail Industry. In Proceedings of the 39th Annual Hawaii International Conference on System Sciences. Lolling, A. (2003). Analyse der menschlichen Zuverlässigkeit bei Kommissioniertätigkeiten [Analysis of human reliability in picking processes]. Shaker. Lorenz, A., & Zimmermann, A. (2006). User modelling in a distributed multi-modal application. In Proceedings of the Workshop on Ubiquitous User Modeling, Riva del Garda, Italy. Lorenz, A., Zimmermann, A., & Eisenhauer, M. (2005). Enabling natural interaction by approaching objects. In Proceedings of the Workshop on Adaptivity and User Modeling in Interactive Systems. DFKI.
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Lucas, H. C. Jr, Weinberg, C. B., & Clowes, K. W. (1975). Sales response as a function of territorial potential and sales representative workload. JMR, Journal of Marketing Research, 12, 298–305. doi:10.2307/3151228 Luimula, M., Sääskilahti, K., Partala, T., Pieskä, S., & Alaspää, J. (2010). Remote navigation of a mobile robot in an RFID-augmented environment. Personal and Ubiquitous Computing, 14(2), 125–136. doi:10.1007/s00779-009-0238-3 Menger, K. (1932). Botenproblem [Messenger Problem]. Ergebnisse eines Mathematischen Kolloquium, 2, 11-12. Miller, M. (2004). Technology: Cost per error and return on investment. Retrieved from http:// www.vocollect.com/np/documents/CostPerErrorWhitePaper.pdf Nielsen, J., Clemmensen, T., & Yssing, C. (2002). Getting access to what goes on in people’s heads?: reflections on the think-aloud technique. In Proceedings of the second Nordic conference on Human-computer interaction (NordiCHI ‘02) (pp. 101-110). New York: ACM. Oppermann, R., & Specht, M. (2000). A Contextsensitive Nomadic Information System as an Exhibition Guide. In Proceedings of the Second Symposium on Handheld and Ubiquitous Computing (LNCS, pp. 127-142). New York: Springer. Rhodes, B. J. (1997). The Wearable Remembrance Agent: A System for Augmented Memory. Personal Technologies Special Issue on Wearable Computing, 1(1), 218–224. Robertson, S., & Robertson, J. (1999). Mastering the requirements process. Reading, MA: Addison-Wesley. Rosenkrantz, D. J., Stearns, R. E., & Lewis, P. M. (1977). An analysis of several heuristics for the traveling salesman problem. Fundamental Problems in Computing, 45-69.
Saint-Andre, P. (2004). RFC 3920: Extensible messaging and presence protocol (xmpp): Core. Request for Comments, IETF. Retrieved from http://tools.ietf.org/html/rfc3920 Schneider, A., Lorenz, A., Zimmermann, A., & Eisenhauer, M. (2006). Multimodal Interaction in Context-Adaptive Systems. In Proceedings of the Second Workshop on Context Awareness for Proactive Systems (p. 101). Schnell, R., & Kreuter, F. (2003). Separating interviewer and sampling-point effects. In UC Los Angeles: Department of Statistics, UCLA. Retrieved from http://www.escholarship.org/uc/ item/7d48q754 Tompkins, J. A., & Smith, J. D. (1998). Warehouse Management Handbook (2nd ed.). New York: Tompkins Associates. Tucker, S. (1963). The Break-Even System: A Tool for Profit Planning. Upper Saddle River, NJ: Prentice Hall. Want, R. (2004). Enabling ubiquitous sensing with RFID. IEEE Computer, 37(4), 84–86. Weinstein, R. (2005). RFID: ATechnical Overview and Its Application to the Enterprise. IT Professional, 7(3), 27–33. doi:10.1109/MITP.2005.69 Weiser, M., & Brown, J. (1997). The coming age of calm technology. Beyond Calculation. The Next Fifty Years of Computing, 8, 75–85. Yan, H., & Selker, T. (2000). Context-Aware Office Assistant. In Proceedings of the 5th Infernational Conference on Intelligent User Interfaces, New Orleans, LA (pp. 276-279). New York: ACM. Zhai, S., Morimoto, C., & Ihde, S. (1999). Manual and gaze input cascaded (MAGIC) pointing. In Proceedings of the Conference on Human Factors in Computing Systems (CHI’99) (pp. 246-253). New York: ACM.
This work was previously published in International Journal of Handheld Computing Research (IJHCR), Volume 2, Issue 1, edited by Wen-Chen Hu, pp. 1-24, copyright 2011 by IGI Publishing (an imprint of IGI Global). 592
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Fuzzy Modelling for Integrated Strategic Planning for Information Systems and Business Process Design Dimitris K. Kardaras Athens University of Economics and Business, Greece Bill Karakostas City University, UK
ABSTRACT Strategic Information Systems Planning (SISP) has been a continuing top concern for IS/IT management, since the mid 1980’s. Responding to the increasing interest in SISP, researchers have developed a large number of SISP methodologies and models. However, when organisations embark on planning for their information systems, they face difficulties and usually fail to gain the expected benefits. Strategic alignment and the DOI: 10.4018/978-1-60960-587-2.ch302
identification of the business areas where the IT contribution is strategically important for the organisation are the most difficult problems in SISP. None of the existing SISP methodologies and models offers a complete solution. The approach presented in this chapter, utilises a Fuzzy Cognitive Map in order to align strategic objectives with IS opportunities that exist at the level of business processes. This chapter exemplifies fuzzy cognitive mapping in SISP, and illustrates how the strategic alignment between the business and IT domains can be realised.
Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
Fuzzy Modelling for Integrated Strategic Planning for Information Systems and Business Process Design
INTRODUCTION TO STRATEGIC INFORMATION SYSTEMS PLANNING Organisations experienced radical changes in their business and technological environment especially, during the 80’s and 90’s. The globalisation of the market and increased competition, in conjunction with a deep economic recession, and changes to the social and economic characteristics of the consumers, exert their pressure on companies. The struggle for further development, or even for survival in such an environment, has become increasingly difficult. However, during the same period an increasing number of research studies (Earl, 1989; O’Connor, 1993; Remenyi, 1991; Ward et. al., 1990) described successful IT initiatives that led companies to new ways of competing, and analysed the factors which led organisations to strategic planning for their IS. Briefly, the driving forces behind SISP are: • •
• • •
• •
Information technology is critical and strategically important to many organisations. The relative high growth in information systems budgets compared to that of other functions in organisations. Information technology is needed by our economic environment. Information technology is rapidly changing. Information technology infrastructure and architecture is critical for information systems integrity. Information technology involves many stakeholders. Top management support and user participation in IT-related decisions are needed.
It is high time that organisations begin to realise the potential of IT as the driving force to lead businesses out of the crisis and to improve organisational competitive performance. As a result, strategic planning for IS/IT has become a key activity which systematically addresses the
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IT issues in organisations, and can identify IT applications which exploit opportunities or counterthreats with substantial importance to business. Relevant literature argues that companies can not be competitive if their information systems strategies are not aligned with the business strategies (Avison et al. 2004). In (Lederer and Sethi, 1988, 1991) a dichotomous definition of Strategic Information Systems Planning (SISP) is provided. On one side of the dichotomy, SISP is a process of identifying computer-based applications that support certain business activities, strategic plans and objectives. On the other side of the dichotomy, SISP is a process of identifying computer-based applications which are characterised by their high potential to lead the organisation to competitive advantage. It is a process which results in innovative IT applications that may alter the competitive scene in an industrial sector, spawn new products, raise entry barriers to new competitors, etc. In both the above adopted views, SISP also covers the definition of the technological infrastructure, i.e. databases, communications, and other systems which are required for the implementation of the identified IT applications. It is argued however (Earl, 1989), that there exists a common confusion between the terminology which refers to information systems, information technology and their planning. Earl (1989) gives three definitions that delineate the concepts, and are adopted in this research work. These definitions are presented below: Information Systems (IS) Strategy is concerned primarily with aligning IS development with business needs and with identifying and exploiting competitive advantage opportunities from IT. IS strategy deals with what to do with the technology. Information Technology (IT) Strategy is concerned primarily with technology policies, such as the specification of analysis and development methods, security levels, technical standards, vendor policies, etc. The IT strategy is the architecture that drives, shapes and controls the IT infrastruc-
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ture. IT strategy designates how technology can be applied in order to implement the IS strategy. The IT infrastructure consists of four elements: computer systems, communication systems, data and databases, and applications. Information Management (IM) Strategy is concerned with the role and structure of IT activities in the organisation. It focuses on the relationships between users and specialists, decentralisation and centralisation, financing and appraising IT applications. IM strategy answers questions as to who does what, where regarding IT. According to a survey conducted by (Earl, 1993), the five dominant objectives of an SISP study are the following: • • • • •
Align IS with business needs. Seek competitive advantage from IT. Gain top management commitment. Forecast IS resource requirements. Establish technology plan and policies.
Five types of planning for information systems are presented below (Remenyi, 1991; Synnott, 1987). Each type of planning reflects how the role and contribution of IT is conceived by the business and IT management. The focus of this classification is on the degree of integration between the business and IT planning process. •
•
•
No Plan. No formal planning takes place for either business or information systems. Small companies often do not develop any plans and normally react to every day events as they occur. Stand-alone Planning. Companies following this type of planning usually develop a business plan without considering the capabilities of IT. If they do develop a plan for their information systems, this takes place in vacuum since there is no interaction with, or input from the business plan. Reactive Planning. Corporate managers develop their business plans and then ask
•
•
from IT management to deploy IT in order to support the business plans. However, there is no communication or collaboration among business and IT managers. Therefore, IT management decides on the priorities and kind of support that IT systems should offer. Linked Planning. In this kind of planning, after the business planning has been completed, business and IT managers prepare together the IT plans in order to reflect the business needs. Integrated Planning. When planning is integrated, there is no distinction between business and IT plans. Instead, there is close collaboration between business and IT managers, who prepare the integrated plan together. As an example, while the business part of the plan is being prepared, IT managers suggest opportunities on how to advance business objectives and plans, achieve competitive advantage with IT systems, or suggest alternatives on how to support businesses. As the information systems part of the corporate plan is being prepared, the business managers suggest priorities and evaluate support alternatives.
Relevant literature argues that companies can not be competitive if their information systems strategies are not aligned with the business strategies (Teo & Ang, 1999; Avison et al. 2004). In fact, strategic alignment has been expressed by many different terms in the literature. The term fit is used in (Porter, 1996), bridge is found in (Coborra, 1997), harmony is suggested in (Luftman et al., 1996), fusion is proposed in (Smaczny, 2001) and linkage is reported in (Henderson & Venkatraman, 1993). In all cases, alignment implies the integration of IS and business strategic planning. Many authors advocate the integrated planning as the most suitable for realising the impact of business to IT and vice versa (Earl, 1989; Ward, et al. 1990; Remenyi, 1991; Synnott, 1987;
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Chen and Nunmaker, 1989; Hayward, 1987; Weil & Broadbent, 1998). However, (Galliers, 1993; Luftman, 1996; Papp, 2001; Tallon & Kraemer, 2003; Trainor, 2003) argue that despite the general agreement about the need of such integration, it is still the case that in many organisations the links between business and IT strategic planning are loose and IS strategic alignment not a top management priority. This chapter uses the terms integration and alignment of IS strategic planning interchangeably. The research objectives of the approach described in this chapter follow: •
•
•
Develop a new model based on the theory of Cognitive Maps to facilitate SISP integrated planning. Integrate Fuzzy Cognitive Maps with business process models so that strategic IS alignment will be realised and strategic priorities will be translated into business process design options. Develop a methodology and associated models that draw on the principles of SISP, and Fuzzy Cognitive Maps.
The chapter continues with the discussion of the necessity of SISP, the problems pertaining to SISP and an introduction to fuzzy cognitive mapping. Then the chapter introduces and illustrates the proposed approach for integrated SISP and discusses the benefits from combining object-oriented and fuzzy cognitive mapping in aligning strategic objectives with process design suggestions.
THE NEED FOR INTEGRATED SISP Although (Jarvenpaa & Ives, 1994), argue that tight IS strategic alignment may reduce strategic flexibility, integrated SISP appears to be the answer to the organisational concerns on how to succeed in an uncertain and turbulent environment
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(Earl, 1989; Remenyi, 1991; Ward, et al. 1990). SISP provides tangible and intangible benefits (O’Connor, 1993; Hackathorn & Karimi, 1988; Kearns & Lederer, 2000; Choe, 2003; Avison, et. al., 2004; Bryd, et. al., 2006) and more specifically: •
•
•
•
• • •
Ensures that information systems are aligned with the corporate business and IT strategic objectives and considers possible opportunities for the company to employ IT to advance its strategic objectives and plans and when possible to gain competitive advantage, Provides for the assignment of the systems development priorities, built on a solid base that depends on the corporate business needs, Fosters the new vision of information systems as investments and ensures the efficient management of the scarce IT resources, Facilitates top management and users participation to IT decisions as it encourages organisational learning i.e. raises the awareness of business users and management of information systems potential through out the organisation, as well as the knowledge of the IT staff about the organisation, Provides a basis for IT performance assessment, Ensures the co-ordinated development of information systems, Provides for the establishment of standards and prevents the piecemeal development of information systems, thus eliminating problems such as data redundancy, inaccuracy and inconsistency and systems incompatibility.
In summary, integrated SISP allows an organisation to realise its opportunities, to influence the future, thus developing a favourable environment, to focus on the business areas where the actual
Fuzzy Modelling for Integrated Strategic Planning for Information Systems and Business Process Design
problem or opportunity is, and additionally provides top management and users’ commitment and participation while ensuring the efficient management of the IT resources.
MODELS FOR INTEGRATED SISP Researchers in their effort to improve SISP have developed several planning models which capture and formalise important aspects of the SISP process. (Earl, 1989) classified the planning models into three major categories namely: •
•
•
The Awareness frameworks, e.g. the Information Intensity Matrix (Porter & Millar, 1985), which demonstrate how IT can be used to inform executives for the potential impact of IT on their business and are more of a pedagogic nature. However, such models are generally of too high a level and too descriptive to guide the identification of specific IT opportunities (Earl, 1989). The Opportunity frameworks, e.g. the Value Chain Model (Porter & Millar, 1985), are explicitly designed to be analytical tools which can lead to firm-specific strategic advantage or clarify business strategies in order to demonstrate options for using IT strategically. However, there is need for tools used for searching for opportunities in particular application areas and for assessing specific technologies (Earl, 1989). The Positioning frameworks, e.g. the Strategic Grid by McFarlan and McKenney (Earl, 1989), are designed to help executives and planners to assess the strategic importance of the IT for a specific organisation and to show in quite general terms, how to manage the IT function. They indicate the nature of the management but they are not useful in searching for opportunities (Earl, 1989).
In the SISP literature the following models have been extensively presented: The Stage Model by Richard Nolan (Earl, 1989; Ward et al., 1990; (King & Kraemer, 1984), The Strategic Grid proposed by McFarlan and McKenney (Earl, 1989), The Growth Share Matrix introduced by Boston Consultancy Group (Synnott, 1987), The Information Intensity Matrix (Porter & Millar, 1985), The Information Weapon Model proposed by (Synnott, 1987), The Five Competitive Forces Model developed by (Porter, 1980), The Value Chain Model was introduced by (Porter & Millar 1985), the Strategic Option Generator presented by (Wiseman, 1985), The Customer Resource Life-Cycle Model of (Ives & Learmonth, 1984), (Beaumont & Walters, 1991) proposed a framework for developing information systems strategies in the services industry, The Strategic Alignment Model (SAM), has been proposed by (Henderson & Venkatraman, 1993; Luftman et al., 1993). A number of methodologies has also been discussed such as the Information Engineering, the BRG-Model, the B-SCP, (Bleistein, et al. 2006), the Business Systems Planning (BSP), etc. (Synnott, 1987; Earl, 1989).
PROBLEMS WITH ALIGNMENT AND SISP In order to carry out an SISP study, an organisation needs generally to embark on a major intensive study. It must apply one, or more of the several available methodologies or even invent its own, form committees of users and IS consultants and carry out the planning process for several weeks or months. While recognising the potential of SISP many organisations either fail to undertake planning or when they do so, planning fails. The literature provides little assistance on how to realise IS strategic alignment, how to evaluate the impact from alignment or misalignment on the business performance and what management can do to create an environment that fosters the
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culture for alignment (Hackathorn & Karimi, 1988, Lederer & Sethi, 1988; 1991; Mahmood & Soon, 1991; O’Connor, 1993; Henderson & Venkatraman, 1993; Luftman, 1996; Yetton, 1997; Hsaio & Ormerod, 1998; Burn, 1997). The main problems for integrated SISP are presented as follows: • •
• •
•
• •
• •
•
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Methodologies do not follow a specific theoretical model. Despite the large number of models available for SISP, none of them offers a complete answer. Methodologies fail to take into account the organisational goals and strategies. Methodologies fail to provide a statement of the IS organisational objectives and to identify specific new projects. Identification of IS projects with determination of the business area where IS are needed, clarification of information needs, and proposal for development IT system, are the most difficult problems to be tackled. There is difficulty in communicating organisational objectives and strategies to the SISP team, and hence difficulty in ensuring alignment between business and information systems. Methodologies fail to assess the current information systems situation. The output of the methodologies is not flexible enough to consider unanticipated changes in the organisation and its environment. Inadequate computer support for planning methodologies. The time and cost involved in performing the SISP study is often considered excessive. Planning is inaccurately viewed as an oneoff process rather as a continuous exercise. As a result SISP becomes outdated and inappropriate to the changing environment.
•
•
•
•
There is difficulty in securing top management commitment for the plan implementation. SISP methodologies fail to produce an overall organisational data, applications, communications and hardware architecture. SISP output fail to take into account issues related to plan implementation and accomplishing as plan requires further analysis. SISP groups fail to consider the political side of the planning, i.e. the power of the participants and the possible changes to the balance of the power.
INTRODUCTION TO FUZZY COGNITIVE MAPS Cognitive maps were first introduced by (Axelrod, 1976) in social sciences as signed oriented graphs, designed to capture the causal assertions of a person in a given area, in order to use them in the analysis of the effects of alternatives e.g. policies, business decisions etc. In a number of studies, they have been used to represent knowledge by presenting the cause – effect relationships that are comprehended to exist between the elements in a given context. Although the term “CM” is being used in various ways, all cognitive maps can be categorised depending on their world – objective (Hong & Han, 2002). One category is the physical and visible one. Another category includes the mental and invisible one (Zhang et al., 1992). The perception and understanding of a person about a problem may be presented on a cognitive map, comprising sets of elements associated with each other, representing the personal opinion of each individual about one’s interests and concerns (Lenz & Engledow, 1986). In other words, it captures the beliefs of an individual or of a group about their subjective world, regardless of objective reality. A cognitive map is also defined as “a representation of the relations that are perceived to exist between the attributes and the concepts
Fuzzy Modelling for Integrated Strategic Planning for Information Systems and Business Process Design
of a given environment” (Zhang et al., 1989). In another study (Eden et al., 1992), it is defined as “an oriented graph characterised by a hierarchical structure that is, most of the time, in the form of a means/ends graph”. Alternative names such as cognitive map, cause map, and influence map have also used to describe a CM (Kwahk & Kim, 1998a). The three structural elements of a CM are the nodes, representing concepts, the directed arrows, symbolising the causal relation between two concepts, and the causality coefficient, which is either positive or negative. (Kosko, 1986) introduced fuzzy cognitive maps (FCM) and substantially enhanced cognitive maps with fuzzy logic. Kosko used fuzzy values for cognitive map variables, in order to map causal relations. As people use fuzzy data, rules and sets, in a mathematical way, to represent fuzziness in their way of thinking (Bezdek, 1993), fuzzy cognitive maps can map human reasoning and model complex dynamic systems that are characterised by intense non linearity. FCMs are a combination of fuzzy logic and Neural Networks. They combine the heuristic and common sense rules of fuzzy logic with the heuristic learning capabilities of neural networks (Stylios & Groumpos, 1999). In essence, they constitute Artificial Neural Systems (ANS) (Hilton, 1992) that mimic how the human brain relates and deals with various input data and events. (Kosko, 1986) defines the fuzzy cognitive map as “a fuzzy signed oriented map with feedback that models the world as a collection of concepts (or factors) and causal relations between concepts”. In a subsequent study (Kosko, 1990) described a FCM as follows: “A FCM presents a causal picture. It maps events, things and processes with values, policies and objectives… allowing you to predict how complex events will impact on each other”. Typically, a FCM is a non hierarchical graph (Irani et al., 2002), where a change in a concept may result in a change throughout the network. Changes originate from a series of causal increases and decreases. These fluctuations are generally
in the form of a ruled weighted measure, from –1 to +1. A FCM is obtained from a CM by fuzzifying the strength of relations between concepts. In this way, fuzzy cognitive maps reflect most cases in a more logical manner. Therefore, a fuzzy cognitive map consists of nodes representing the factors that relate to the context being studied and of arrows indicating different fuzzy causal relations, whether positive or negative, between such factors (Figure 1). The FCM approach is, therefore, an inferential mechanism representing the existence of fuzzy causal relations between concepts and the monitoring of their effects (Lee & Han, 2000). In a similar way to CMs, if certain nodes are stimulated, the change will be conveyed through positive or negative weighted links throughout the map until equilibrium is reached. A FCM can also be represented by using an nxn table of links E, where n is the number of nodes-concepts contained in the graph. Every value of this table represents the strength and direction of causality between various concepts. As already stated, the value of causality eij is from the interval [-1, +1]. Thus, according to (Schneider et al., 1998): • •
eij > 0 indicates a causal increase or positive causality from node i to j. eij = 0 there is no causality from node i to j.
Figure 1. Part of a FCM
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•
eij < 0 indicates a causal decrease or negative causality from node i to j.
The representation of FCM with the use of a links’ table allows the study of the impact of a given causal effect D1 (Banini & Bearman, 1998), which can be represented with the aid of a vector. This impact is calculated through repeated multiplications: ΕxD1 = D2, ΕxD2 = D3 and so forth, that is, ΕxDi = Di+1, until a dynamic equilibrium is reached, which is the final result of the effect D1. Fuzzy cognitive maps have been used to model complex dynamic systems which are characterised by strong non linearity (Groumpos & Stylios, 2000). They have been used to capture the behaviour and reaction of virtual worlds by representing their needs such as “the search for food” or “the survival threat” (Dickerson & Kosko, 1994). Similar use is made in social systems, characterised by fuzzy causality grades (Taber, 1994). Another application of FCMs is in modeling dynamic systems with chaotic characteristics, such as social and psychological processes (Craiger & Coovert, 1994), as well as in the behaviour of organisations (Craiger et al., 1996). Moreover, they have been used for planning and decision making in the fields of international relations and political developments (Taber, 1991). From a different perspective, FCMs have been used in factory control (Gotoh et al., 1989), in modelling distributive systems’ supervisors (Stylios et al., 1997), in designing EDI (Lee & Han, 2000), in strategic planning (Kardaras & Karakostas, 1999a) and in the evaluation of information systems (Kardaras & Karakostas, 1999b). In addition, they have been used in managing relations in airline services (Kang et al., 2004), in supporting urban planning (Xirogiannis et al., 2004), in the differential diagnosis of specific speech disorders (Georgopoulos et al., 2002), as well as in many other fields.
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THE PROPOSED APPROACH: FUZZY MODELLING FOR INTEGRATED SISP AND BUSINESS PROCESSES DESIGN Overview of the Approach This chapter proposes an approach for integrating strategic planning for IS with business strategic planning and for translating the resulting strategic objectives into business processes improvement suggestions. FCMs represent the strategic priorities, which are expressed in terms of increase or decrease of business performance issues such as cost, customer satisfaction, market share, etc. FCMs also offer the modelling mechanism for linking the strategic objectives with the Object Oriented (OO) model that represent the business processes. The proposed approach advocates the integration of business and SISP planning that allows complex interrelationships between business and IT to be systematically identified and managed. The realisation of the integration in the planning process can be seen as the foremost objective of the methodology. The following diagram depicts how FCMs are linked with the OO business models. Figure 2 shows that strategic objectives (Si) are linked with each other, thus are forming a FCM that represents how the objectives impact on each other. Furthermore, the dotted arrows in Figure 2 represent relationships among strategic objectives and tasks (ti) of the OO business process model. The proposed modelling supports the simulation of planning at strategic level, as well as the simulation of the strategic impact at the process level. The following sections of this chapter illustrate in detail the proposed approach.
Fuzzy Modelling for Integrated Strategic Planning for Information Systems and Business Process Design
Figure 2. FCMs link strategies with business process tasks
Step 1: Modelling Strategic Objectives with the Strategic-FCM (S-FCM) Fuzzy cognitive mapping of strategic objectives starts with the identification of the concepts to be modelled. Such concepts belong to broad business and technological areas of strategic interest, for example, ‘Customers’, ‘Suppliers’, ‘Competition’, ‘IT Products and Services’. The variables of the S-FCM are therefore key concepts pertaining to the identified target areas and specifying the business and technological factors affected by IT affects and also how IT contributes to organisational performance improvement. A factor can be quite broad and therefore relevant to more than one target areas. The concepts of ‘cost’, ‘efficiency’, ‘quality’, ‘customer satisfaction’, ‘speed of service delivery’, etc. are some examples of variables. In fact, the S-FCM variable represent business performance factors as a series of increases or decreases to the values of the variable reflect the strategic choices of a company. Fuzzy cognitive mapping of strategic objectives continues with the identification of the Relationships of the S-FCM variables that show how a variable affects one or more other variables. The relationships are represented as the arrows in the S-FCM. Each relationship is assigned a (+) or a (-) sign that indicates the causal direction of
the impact that a variable exerts to another, and a fuzzy weight that indicates the perceived degree of the strength of the relationship (Kosko, 1986). The S-FCM is a tool for planners to be used in order to formulate the strategy and develop a consensus regarding the strategic choices. After the S-FCM is finalised and agreed by the strategic planners, it shows what is needed to be achieved. Figure 3 below, shows part of a S-FCM. The fuzzy weights shown in the figure in bold represent the strategic objective. Strategic objectives are defined in a subset of the S-FCM set of variables. The formulation of the strategy would not necessarily use all the variables in the model. Therefore, the strategic objectives (Si) shown in Figure 3 are: • • • •
S1: To increase customer satisfaction by (strong) S2: To decrease product price by (medium) S3: To increase individualised attention by (strong) and S4: To increase availability of products by (strong)
The rest of the variables that constitute the S-FCM do not represent a strategic objective. Each strategic objective is then defined by the following attributes:
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Fuzzy Modelling for Integrated Strategic Planning for Information Systems and Business Process Design
Figure 3. Part of the S-FCM and its linking with the process model
• • • •
Its current achievement (ca) its target (tr) its impact on other variables (im) its links with the tasks that are responsible for the realisation of the objective (lk).
Each attribute of an S(i) is a fuzzy set, taking values from the set of linguistic variables {little, medium, strong}, which, after defuzzification, take values from the [0,1] range (Kosko, 1986; Tanaka, 1997). Each strategy (SP) is also a fuzzy set, and is represented by a series of strategic objectives (Si), i.e. as: SP(i)=[S1(ca, tr, im, lk), S2(ca, tr, im, lk), S3(ca, tr, im, lk), …, Sn(ca, tr, im, lk)]. The above model of a strategy (SP), allows the planners to know the current level of achievement of each strategic performance variable, but also which business areas performance is critical and to what extent. The links between the S-FCM and the business model, provide the necessary modelling technique for IS alignment.
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Step 2: Aligning Strategies with Business Processes Drawing on Figure 3, each variable in the S-FCM is linked with one or more tasks in the business process models. Such links represent allow the alignment of strategies with business process design and IS applications development. Business processes are modelled as OO models. The performance of each process and each task of a process is assessed in terms of the S-FCM variables. For example, availability of products is a strategic target (S4) that needs a strong increase. The performance of this strategic objective depends, as shown in Figure 3, on the performance of task (T1). Because of this relationship, it is important not only to focus the attention for improvement on task T1, but also to measure and assess its performance in terms of the availability of products. Similarly, price of products needs a medium drop. The achievement of this objective depends on the performance of tasks (T2) and (T3). The performance metrics for each task constitute part of the tasks’ attributes.
Fuzzy Modelling for Integrated Strategic Planning for Information Systems and Business Process Design
The impact of the performance of each task to other tasks is propagated through the model by using the FCM relationships that link task attributes together. These relationships are shown in Figure 3 as solid arrows connecting tasks in the process model. The attributes that reflect the object’s performance are linked to attributes of the S-FCM. The S-FCM that supports the integrated business and SISP represents the organizational performance at a strategic level and is a FCM itself.
Step 3: Compare Current Business Performance and Strategic Objectives and Identify Areas of Improvement Consider the two vectors (Sca(i)) and (Str(i)) that represent for each (i), the current achievement and the target performance of strategic objectives respectively, where (i) is a strategic objective. The Gap (GP) in performance of a firm is defined as the distance (di) between two elements (vi) of the vectors i.e. as: (GP)=di = |χ1(Sca(i)) - χ2(Str(i))|, where χ1 and χ2 is the degree of membership for the (i) element of the vectors (Sca(i)) and (Str(i)) respectively. For a company to be competitive, it needs to minimise the distance between current achievement and strategic target. By looking at the value of gap in performance, the proposed approach locates the business areas where initiatives for improvement are needed. However, as our approach does not aim to manage differences in performance automatically; there is no need to specify a threshold for “accepted” or not differences. It rather encourages strategic decision makers to develop alternative scenarios based on their assumptions for the company. The differences indicate to strategic planners, the performance areas and subsequently the tasks they should focus on their attention. So, if there are areas that do not perform as expected,
the management can trace the business tasks that are responsible for delivering the required performance and decide the appropriate actions. Any changes or initiatives that they may propose, possibly altering the performance of tasks or changing the process design, can be fed back to the S-FCM and simulated.
STRATEGIC SIMULATION OF IS ALIGNMENT All concepts in S-FCM and tasks in business processes are interrelated. These interrelationships are implemented as a matrix (Strategy-Task Matrix), which has as columns and rows all strategic concepts and tasks performance measures, respectively. The following table shows the structure of this matrix. The numbers in the first row of Table 1 show how each concept affects or is affected by other concepts and task performance. The values are in the interval [-1, 1] and reflect the perception and beliefs of the IS planning team. New strategic initiatives can be modelled as a vector, Strategic Initiatives= [S1(tr), S2(tr), …, Sn(tr)], that is taking into consideration only the targets for each strategic objective. By considering the vector Strategic Initiatives, and its multiplication with the Strategy-Task Matrix, (i.e. strategic initiatives vector constitutes a row of the matrix), the above matrix indicates which tasks in which process(es) should change and in what direction (+ or –), in order to satisfy the strategic requirements. Several simulation runs will provide detailed examination of different strategic scenarios, as well as their evaluation in terms of required process design changes and performance improvements.
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Table 1. Strategy-task matrix that integrates strategy and tasks performance
S1
S1
S2…Sn
Task_1 performance
Task_2 performance…
Task_n performance
0
0.5
0.7
-0.4
0.8
S2, …, Sn Task_1 performance Task_2 performance… Task_n performance
CASE STUDY This section illustrates the applicability of the proposed approach for IS strategic alignment with a case study. For simplicity reasons, the complexity of the case is been kept to a minimum. Thus, only two strategic objectives and only two business tasks will be modelled. Let us consider company (X) which aims at realising the following two strategic objectives: • •
S1, from a medium current level of achievement increase market share to a high and S2 from a low current level of achievement increase customer satisfaction to a very high.
The defuzzification process (Ross 2004), depending on the technique, could assign for example values to the linguistic expression of the strategic objectives as follows: • • • •
Low=0.2 Medium=0.5 High=0.7 Very High=0.9
Then the gap of performance for S1= (0.7-0.5) = 0.2 and for S2= (0.9-0.2) = 0.7. S2 target is assigned a higher priority to S1, since the gap of performance for S2 is bigger than
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the gap of S1. The top priority for S2 indicates that all changes required at the process level and the IS that could be proposed for development in order to support S2, should have a higher priority from the changes and IS that would support S1. Company (X) then need to increase its customer satisfaction by 0.7 and to increase its market share by 0.2. The S-FCM for the above case is shown in Figure 4. Figure 4 shows that the realisation of target S1 depends on the performance of task T1, as measured in terms of task T1’s cost (T1-C) and time for completion (T1-t) as well as it depends on the cost (T2-C) of task T2. Similarly, the objective S2 depends on the cost (T2-C), time (T2-t) and friendliness (T2-F) of task T2 and the cost (T1-C) of task T1. The above figure also shows that target 2 affects target S1. Next consider the Strategy-Task matrix in the following table that represents the above FCM. The Strategic Initiatives (StrI) vector, which is shown below, is identical to a row of S-FCM and represents the strategic objectives that company (X) aims to achieve. Therefore company (X) aims at increasing S1 by 0.2 and S2 by 0.7 respectively. The multiplication of the StrI vector with the S-FCM indicates how strategic alignment can be achieved at the process and the IS level. The result
Fuzzy Modelling for Integrated Strategic Planning for Information Systems and Business Process Design
Figure 4. S-FCM for company (X)
Table 2. The strategy-task matrix for company (X) S1
S2
T1C
T1-t
T2C
T2-t
T2-F
S1
0
0.7
-0.3
0
-0.7
0
0
S2
0
0
-0.5
0
-0.8
-0.5
0.7
T1-C
0
0
0
0.6
0.2
0
0
T1-t
0
0
0
0
0
0.2
0
T2-C
0
0
0
0
0
0.3
0
T2-t
0
0
0
0
0
0
0
T2-F
0
0
0
0
0
-0.2
0
of the multiplication is the Strategic Alignment vector StrA, which is identical to the StrI vector. The results show that in order to achieve target S! and target S2, company (X) needs to reduce very strongly (-0.95) the time of completion of task T1, to strongly reduce the cost of task T2, to slightly reduce the time of task T2 and to increase the friendliness of task T2 by medium. The proposed approach then identifies the areas where changes are needed (e.g. tasks T1 and T2) as well as specifies what kind of changes are required thus indicating the information systems that are needed in order to implement the strategic targets and achieve strategic alignment. Multiplication continue with each resulting StrA vector with the S-FCM until all cells values equal
to (0), implying that there is no further impact to consider in the model. Several scenarios can be studied for alternative strategic objectives by changing the values in the StrI vector (thus changing the priorities for the objectives) or adding more objectives to be considered.
FUTURE TRENDS The proposed approach opens up new opportunities for research in IS strategic alignment. The intangible nature of strategic thinking as well as the different and many times contradicting views Table 3. The strategic initiatives (StrI) vector for company (X) S1 0.2
S2
T1-C
T1-t
T2-C
T2-t
T2-F
0.7
0
0
0
0
0
Table 4. The strategic alignment vector (StrA) vector for company (X) S1 0
S2
T1-C
T1-t
T2-C
T2-t
T2-F
0.14
-0.95
0
-0.7
-0.35
0.49
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of stakeholders can be represented using fuzzy logic models. Further research could focus in incorporating concepts from resource dependencies theory (Clemons & Row, 1991) into fuzzy models. Moreover, the resources dependencies theory is promising in investigating the resources necessary for the development of strategies and the realisation of competitive advantage. Another direction for future research may be towards the investigation and modelling of strategic thinking principles and guidelines that would improve knowledge on strategy formulation, integration and pre-development IS assessment. Finally, the development and use of IS evaluation metrics is an important research task; one that may change the way that IS is modelled and managed. Such a set of metrics could include the definition and measurement of concepts such as ‘compatibility’, ‘reusability’, ‘suitability’, ‘competitiveness’, etc.
CONCLUSION The proposed fuzzy causal strategic design model provides the means to consider the business objectives and to associate them with specific business areas, which can be benefited by IT. In contrast to other strategic design and management approaches, the proposed model is dynamic, exhibits flexibility and responsiveness to business environment changes, customisability to specific organisational context, and allows for the development of planning scenarios. The approach discussed in this chapter suggests that the introduction of fuzzy attributes and fuzzy associations to process models will facilitate the representation of inexact and soft concepts involved in SISP and process design. The proposed framework not only provides flexibility by accommodating non-financial measures, but it also allows the development of the systems and methods for representing, analysing, and communicating aspects of business performance
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information. Moreover, as it is argued in this chapter, integrated business and strategy FCM models allow the consideration of alternative business process re-design suggestions and their comprehensive evaluation in terms of organisational effectiveness related issues. This chapter discusses the importance of developing frameworks for the integrated SISP that can conceptually support business process design under different IT architectures. It suggests the use of fuzzy logic and its reasoning techniques in strategic planning and processes modelling techniques. Among the benefits of the approach is its potential •
• • •
to facilitate the development of a consensus among the planners and decision makers when developing strategies, to integrate business and IS planning, to translate strategic objectives into business processes design options, to suggest IT architecture options that would implement the suggested by the proposed model IS strategies.
The proposed methodology provides planners with the means to cope with the complex and turbulent external environment. In order to accomplish the required external consistency, it exhibits responsiveness and flexibility so that •
• •
environmental changes are adequately taken into consideration during the planning process, their impact on the organisation and its IS can be estimated and IS plans which reflect the latest development in the environment are produced.
With regard to the model’s internal consistency, the translation of the organisational strategic plans into specific IS plans, takes place through various levels of abstractions of business and IT concepts. The translation is achieved by linking
Fuzzy Modelling for Integrated Strategic Planning for Information Systems and Business Process Design
business and IT factors at the strategic level, with corresponding ones at specific business units and business functional areas. Scenarios can be developed during the planning session in order to: •
•
incorporate stakeholders’ differing viewpoints. This also facilitates the development of an organisational learning culture as business and IT experts, co-operatively develop the scenarios, get an insight on the organisational and technological matters and experience a multi-dimensional approach to planning and cope with the full availability of information and alleviate the drawbacks of the rational model adopted in the planning process.
The proposed approach provides the conceptual framework in order to accommodate the rather intangible and qualitative nature of the SISP process. Fuzzy linguistic terms are suggested to describe concept attributes and associations and add flexibility to the SISP and process models as well as facilitate the communication among planners.
REFERENCES Avison, D., Jones, J., Powell, P., & Wilson, D. (2004). Using and validating the strategic alignment model. The Journal of Strategic Information Systems, 13, 223–246. doi:10.1016/j. jsis.2004.08.002 Axelrod, R. (1976). Structure of Decision: The Cognitive Maps of Political Elites. Princeton, NJ: Princeton University Press. Banini, G. A., & Bearman, R. A. (1998). Application of fuzzy cognitive maps to factors affecting slurry rheology. International Journal of Mineral Processing, 52, 233–244. doi:10.1016/S03017516(97)00071-9
Beaumont, J. R., & Walters D. (1991). Information management in service industries: Towards a strategic framework. Journal of Information Systems, 1. Bezdek, J. (1993). Editorial, Fuzzy models - what they are, and why. IEEE transactions on Fuzzy Systems, 1. Bleistein, S., J., Cox, K., Verner, J., & Phalp, K.T. (2006). B-SCP: A requirements analysis framework for validating strategic alignment of organisational IT based on strategy, context, and process. Information and Software Technology, 48, 846–868. doi:10.1016/j.infsof.2005.12.001 Burn, J. (1997). Information systems strategies and the management of organizational change. Journal of Information Technology, 8, 205–216. doi:10.1057/jit.1993.32 Byrd, T. A., Lewis, B. R., & Bryan, R. W. (2006). The leveraging influence of strategic alignment on IT investment: An empirical examination. Information & Management, (43): 308–321. Chen, M., & Nunmaker, J. (1989). Integration of organisation and information systems modelling: An object-oriented approach. In Proceedings of the 22nd Hawaii International Conference on Systems Science, Jan. Choe, J. (2003). The effect of environmental uncertainty and strategic applications of IS on a firm’s performance. Information & Management, 40, 257–268. doi:10.1016/S0378-7206(02)00008-3 Ciborra, C. (1997). De Profundis? Deconstructing the concept of strategic alignment. IRIS conference (http://iris.informatik.gu.se/conference/ iris20/60.htm). Clemons E. K., & Row M. C. (1991). Sustaining IT advantage: The role of structural differences, MIS Quarterly, September.
607
Fuzzy Modelling for Integrated Strategic Planning for Information Systems and Business Process Design
Craiger, J. P., & Coovert, M. D. (1994). Modeling dynamic social and psychological processes with fuzzy cognitive maps. Proceedings of the IEEE International Conference on Fuzzy Systems, 1873 – 1877. Craiger, J. P., Goodman, D. F., Weiss, R. J., & Butler, A. B. (1996). Modeling organizational behavior with fuzzy cognitive maps. International Journal of Computational Intelligence and Organizations, 1, 120–123. Dickerson, & Kosko, B. (1994). Fuzzy virtual worlds. AI Experts, 25-31. Earl, M. J. (1989). Management Strategies for Information Technology. Prentice Hall. Earl, M. J. (1993). Experiences in strategic information systems planning. MIS Quarterly/March. Eden, C., Ackerman, F., & Cropper, S. (1992). The analysis of cause maps. Journal of Management Studies, 29(3), 309–324. Galliers R. D. (1993). Towards a flexible information architecture: integrating business strategies, information systems strategies and business process redesign. Journal of Information Systems, 3. Georgopoulos, V. C., Malandraki, G. A., & Stylios, C. D. (2002). A fuzzy cognitive map approach to differential diagnosis of specific language impairment. Artificial Intelligence in Medicine, 679, 1–18. Gotoh, K., Murakami, J., Yamaguchi, T., & Yamanaka, Y. (1989). Application of fuzzy cognitive maps to supporting for plant control. Proceedings of the SICE Joint Symposium of 15th Systems Symposium and 10th Knowledge Engineering Symposium, (pp. 99-104). Groumpos, P. P., & Stylios, C. D. (2000). Modeling supervisory control systems using fuzzy cognitive maps. Chaos, Solitons, and Fractals, 11, 329–336. doi:10.1016/S0960-0779(98)00303-8
608
Hackathorn R. C., & Karimi J. (1998). A framework for comparing information engineering methods. MIS Quarterly/June. Hayward, R. G. (1987). Developing an information systems strategy. Long Range Planning, 20(2). doi:10.1016/0024-6301(87)90012-4 Henderson, J. C., & Venkatraman, N. (1993). Strategic alignment: Leveraging information technology for transforming organisations. IBM Systems Journal, 32(1). Hilton, E. (1992). How neural networks learn from experience. Scientific American, 267, 144–151. Hong, T., & Han, I. (2002). Knowledge-based data mining of news information on the Internet using cognitive maps and neural networks. Expert Systems with Applications, 23, 1–8. doi:10.1016/ S0957-4174(02)00022-2 Hsaio, R., & Ormerod, R. (1998). A new perspective on the dynamic of IT-Enabled strategic change. Information Systems Journal, 8(1), 21–52. doi:10.1046/j.1365-2575.1998.00003.x Irani, Z., Sharif, A., Love, P. E. D., & Kahraman, C. (2002). Applying concepts of fuzzy cognitive mapping to model: The IT/IS investment evaluation process. International Journal of Production Economics, 75, 199–211. doi:10.1016/S09255273(01)00192-X Ives, B., & Learmonth, G. P. (1984). The information system as a competitive weapon. Communications of the ACM, 27(12). doi:10.1145/2135.2137 Jarvenpaa, S. L., & Ives, B. (1994). The global network organization of the future: Information management opportunities and challenges. Journal of Management Information Systems, 10(4), 25–57. Kang, S., & Choi, L. J. (2003). Using fuzzy cognitive map for the relationship management in airline service. Expert Systems with Applications, 26, 545–555. doi:10.1016/j.eswa.2003.10.012
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Kardaras, D., & Karakostas, B. (1999a). The use of fuzzy cognitive maps to stimulate the information systems strategic planning process. Information and Software Technology, 41(4), 197–210. doi:10.1016/S0950-5849(98)00125-6 Kardaras, D., & Karakostas, B. (1999b). A Modeling Approach for Information Systems Evaluation Based on Fuzzy Cognitive Map. Proceedings of the 5th International Conference of the Decision Sciences Institute. Integrating Technology and Human Decisions: Global Bridges into the 21st Century. Athens, Greece. Kearns, G. S., & Lederer, A. L. (2000). The effect of strategic alignment on the use of IS-based resources for competitive advantage. The Journal of Strategic Information Systems, 9, 265–293. doi:10.1016/S0963-8687(00)00049-4 King, J. L., & Kraemer, K. L. (1984). Evolution and organisational information systems: An assessment of Nolan’s stage model. Communications of the ACM, 27(5). doi:10.1145/358189.358074 Kosko, B. (1986). Fuzzy Cognitive Maps. International Journal of Man-Machine Studies, 24, 65–75. doi:10.1016/S0020-7373(86)80040-2 Kosko, B. (1990). Fuzzy Thinking: the New Science of Fuzzy Logic. Flamingo Press. Kwahk, K.-Y., & Kim, Y.-G. (1998). A Cognitive Model Based Approach for Organizational Conflict Resolution. International Journal of Information Management, 18(6), 443–456. doi:10.1016/ S0268-4012(98)00034-6 Lederer, A. L., & Sethi, V. (1991). Critical dimensions of strategic information systems planning. Decision Sciences, 22. Lederer A. L., & Sethi V. (1998). The implementation of strategic information systems planning methodologies. MIS Quarterly/September.
Lee, S., & Han, I. (2000). Fuzzy cognitive map for the design of EDI controls. Information & Management, 37, 37–50. doi:10.1016/S03787206(99)00033-6 Luftman, J. N., Papp, R., & Brier, T. (1996). Business and IT in harmony: Enablers and Inhibitors to alignment. (http://hsb.baylor.edu/ramsowner/ ais.ac.96/papers/papp.htm Oct 2000). Mahmood, M. A., & Soon, S. K. (1991). A comprehensive model for measuring the potential impact of information technology on organisational strategic variables. Decision Sciences, 22. O’Connor, A. D. (1993). Successful strategic information systems planning. Journal of Information Systems, 3. Papp, R. (2001). Strategic information technology: Opportunities for competitive advantage. IDEA publishing Group. Porter, M. E. (1980). Competitive Strategy. Free Press. Porter, M. E. (1996). What is strategy? Harvard Business Review, (Nov-Dec): 61–78. Porter, M. E., & Millar, V. E. (1985). How information gives you competitive advantage. Harvard Business Review, July-August. Remenyi, D. S. J. (1991). Strategic Information Systems Planning. NCC Blackwell. Ross, T. (2004). Fuzzy Logic with Engineering Applications. John Wiley, 2nd edition. Schneider, M., Shnaider, E., Kandel, A., & Chew, G. (1998). Automatic construction of FCMs. Fuzzy Sets and Systems, 93, 161–172. doi:10.1016/ S0165-0114(96)00218-7 Smaczny, T. (2001). IS an alignment between business and IT the appropriate paradigm to manage IT in today’s organization? Management Decision, 39(10), 797–802. doi:10.1108/ EUM0000000006521
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Fuzzy Modelling for Integrated Strategic Planning for Information Systems and Business Process Design
Stylios, C. C., & Groumpos, P. P. (1999). Fuzzy Cognitive Maps: a model for intelligent supervisory control systems. Computers in Industry, (39): 229–238. doi:10.1016/S0166-3615(98)00139-0 Synnott, W. R. (1987). The Information Weapon. Wiley. Taber, R. (1991). Knowledge processing with fuzzy cognitive maps. Expert Systems with Applications, 2(1), 83–87. doi:10.1016/09574174(91)90136-3 Taber, R. (1994). Fuzzy cognitive maps model social systems. AI Expert, 9, 18–23. Tallon, P., & Kraemer, K. (2003). Investigating the relationship between strategic alignment and business value. Hershy, PA: IDEA Publications (pp. 1-22).
Ward, J., Griffiths, P., & Whitmore, P. (1990). Strategic Planning for Information Systems. Wiley. Weill, P., & Broadbent, M. (1998). Leveraging the new Infrastructure. Harvard Business School Press. Wiseman, C. (1985). Strategy and Computers, Dow Jones Irwin. Xirogiannis, G., Stefanou, J., & Glykas, M. (2004). A fuzzy cognitive map approach to support urban design. Expert Systems with Applications, 26, 257–268. doi:10.1016/S0957-4174(03)00140-4 Yetton, P. (1997). False prophesies, successful practice, and future directions in IT management. In C. Sauer, P. Yetton, et al., (Eds), Steps to the Future. San Francisco: Jossey-Bass.
Tanaka, K. (1997). An introduction to fuzzy logic for practical applications. Springer Verlag.
Zhang, W. R., Chen, S. S., & Bezdek, J. C. (1989). Pool2: a generic system for cognitive map development and decision analysis, 19(1), 31-39.
Teo, T., & Ang, J. (1999). Critical success factors in the alignment of IS plans with business plans. International Journal of Information Management, 19, 173–185. doi:10.1016/S02684012(99)00007-9
Zhang, W. R., Chen, S. S., Wang, W., & King, R. S. (1992). A cognitive-map-based approach to the coordination of distributed cooperative agent. IEEE Transactions on Systems, Man, and Cybernetics, 22, 103–114. doi:10.1109/21.141315
Trainor, E. (2003). From the president’s desk. SIM Top Ten List (http://www.simnet.org).
This work was previously published in Strategic Information Technology and Portfolio Management, edited by Albert Wee Kwan Tan and Petros Theodorou, pp. 59-77, copyright 2009 by Information Science Reference (an imprint of IGI Global).
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Human Resources in the Balanced Scorecard System Juha Kettunen Turku University of Applied Sciences, Finland
INTRODUCTION Strategic planning is a matter of mapping the route between the perceived present circumstances and the desired future situation. Strategic management adapts higher education institutions (HEI) to their environment including educational policy, local demand for skilled labor, and other factors. The purpose of HEIs is to positively affect the development of society and the local community. The balanced scorecard approach developed by Kaplan and Norton (2001, 2004, 2006) is a framework for the communication and impleDOI: 10.4018/978-1-60960-587-2.ch303
mentation of the strategy. The approach creates a shared understanding of the strategic plan by describing the plan using strategy maps, strategic objectives, measures and target values for the planning period (Niven, 2005). The balanced scorecard approach can be combined with other approaches and management tools. The purpose of this article is to report on a development project where the balanced scorecard approach was applied in the management information system (MIS) of an HEI. The MIS integrates the different approaches of management into human resources (HR) planning. It is important that the balanced scorecard approach is supported by the MIS. This is especially criti-
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Human Resources in the Balanced Scorecard System
cal in large organizations. Many administrative units and organizational levels emphasize the importance of automation enabling management to consistently aggregate the scorecards of lower organizational levels to the overall scorecard. The MIS with a portal is a valuable communication channel, information processor, management tool and the joint memory of the organization. The empirical part of the article describes the MIS of the Turku University of Applied Sciences (TUAS), where the MIS is based on strategic management and the balanced scorecard approach. The system integrates budgeting, action plans, HR planning and quality management. The data warehouse approach is used to capture data from the diverse source systems and to store the data in an integrated database. An MIS portal was developed to support the management process and be open to the personnel of the institution. The portal supports the dialogue and commitment of the personnel to the strategic outlines. The portal is open to management and the personnel of the institution.
The balanced scorecard has been designed as a mechanism to make the strategic plan more understandable to management and personnel. The approach has been widely used in the private and public sectors. The experiences of many studies testify that the balanced scorecard approach is well suited to a higher education setting and allows the alignment of a wide variety of measures with the unique mission and strategy (Kettunen, 2004, 2006; Papenhause & Einstein, 2006; Self, 2003). The balanced scorecard is a useful tool, because it can be used to align the HR and many other management tools with strategic planning (Mouritsen, Thorsgaard Larsen, & Lumby, 2005; Rampersad, 2005). The balanced scorecard of the TUAS includes five perspectives: •
•
BACKGROUND Balanced Scorecard Translates the Strategy into Action The autonomy of HEIs has increased. The autonomy emphasizes stronger management and the increasing accountability of institutions to society and other stakeholders. The management of HEIs is acquiring more integrated and strict but at the same time loose forms (Meyer, 2002). Analyzes of autonomy and self-regulation in higher education do not, however, provide any specific tools for the management of HEI (Maassen & Stensaker, 2003). Strategic management is widely used in the Finnish HEIs (Kettunen & Kantola, 2006) and is also a strong candidate for the framework of the management system also in other countries (Bush & Coleman, 2000; Middlewood & Lumby, 1998).
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•
•
•
Societal impact: The societal impact perspective includes an objective which describes the institution’s outreach and engagement in society and the local community. Customer: The customer perspective includes the objectives of student and employer satisfaction. Customer satisfaction is what essentially all the organizations try to achieve. Finance: The financial perspective describes the objectives of public funding and external income. Internal processes: The internal processes perspective typically describes the sequential internal processes of an organization. Learning: The learning perspective describes the objectives of HR that are drivers for future performance. The achievement of these objectives is required to reach the objectives of the internal processes.
In many other organizations the societal impact and customer perspectives have been combined into one perspective.
Human Resources in the Balanced Scorecard System
The balanced scorecard helps management to communicate the important objectives to the personnel. The objectives are described by measures. Typically, the management of the organization sets the target values of the measures for the planning period. The HR must be aligned with all the strategic objectives. When the scorecards are planned for all the organizational units the personnel is able to understand the strategic plan and their own role in contributing to the plan.
MAIN FOCUS OF THE CHAPTER Balanced Scorecard in Higher Education Figure 1 describes the strategy map of the TUAS. The concept of the strategy map was introduced by Kaplan and Norton (2004). The societal impact perspective of the TUAS includes the objectives of regional development and the customer perspective includes the objectives of customer satisfaction. These objectives can be achieved as a result of the internal processes including research and development, support services and education.
The financial perspective includes funding from central government and external funding for research and development and continuing education. The financial objectives are aligned with the internal processes and structures in the budget of an organization. The learning perspective includes the objectives of capabilities for research and development and teacher capabilities. The linkages of the strategy map describe the relationships between the perspectives and strategic objectives. Table 1 describes the learning perspective of the balanced scorecard of the TUAS. The learning perspective includes two objectives describing the core capabilities of the personnel. The objective of the “capabilities for R&D” is described by the number of licentiate degrees and doctorates which are important for high quality research and education. The objective of “teacher capabilities” includes the measure describing the share of teachers having the required teacher education. The target values have been set for each year of the planning period. Even though there are many other important characteristics of HR, the balanced scorecard cannot include every important aspect, because the attention must be focused on achieving the most important targets.
Figure 1. Strategy map of the TUAS
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Table 1. Leaning perspective of the balanced scorecard at the TUAS Objectives R&D capabilities Education capabilities
Actual figures
Measures
2004
Target values
2005
2006
2007
2008
2009
No. of licentiate’s degrees
43
49
60
58
60
60
No. of doctorates
32
36
50
55
60
65
Share of teachers with teacher education, %
77
78
80
82
85
86
Table 2 describes the HR plan of the TUAS. It describes the actual and planned development of the labor force, vacancies and labor costs, which are aligned with the internal processes in the budgeting process. The HR plan has also been prepared for each administrative unit of the institution. The HR plan also includes information on the share of absence hours, measures to maintain working ability and the resources and days of in-house training. The HR plan also includes the timetable and plans for how permanent jobs will be created for temporary workers. Detailed plans including personnel development and qualitative indicators are made in the different administrative units. The HR plan includes diagnostic measures, which are vital for success, but are not drivers of strategic success. Diagnostic measures are necessary in the same way as the body temperature and blood pressure of individuals, but they are not the right ones to manage the transformations needed.
Development of the Management Information System The balanced scorecard approach was introduced at the TUAS in 2002. The maintenance of the balanced scorecards in the different administrative units turned out to be troublesome. The consistent aggregation of the balanced scorecards to the upper organizational levels and data collection needed automation. In large organizations automation of data processing is necessary. The planning of the MIS started in 2004 with the modeling of the entire management process. About 700 concepts were defined at the different organizational levels and a lot of process documents were written. It was obvious that the planned system would provide clear benefits as required generally for development projects of this kind (Galliers, Swatman, & Swatman, 1995). It is important that there is a rigorous planning methodology such as the balanced scorecard to communicate and implement the strategic plans
Table 2. HR plan of the TUAS Measures Labor force: • Labor force at work • Labor force, person-years • Permanent employees • Temporary employees • Substitute employees Vacancies: • Number of vacancies • Open vacancies Labor costs: • Labor cost / total cost, %
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Actual figures
Target values
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
173 173 128 27 18
175 198 119 38 18
175 206 126 30 19
178 185 122 54 9
172 172 136 27 9
172 173 139 24 9
172 173 141 23 9
172 173 141 23 9
172 173 141 23 9
172 173 141 23 9
171 173 141 21 9
171 173 141 21 9
139 3
143 3
145 3
126 4
127 1
130 1
134 1
134 0
134 0
134 0
134 0
134 0
59,3
59,7
61,7
64,7
52,4
52,4
52,4
52,4
52,4
52,4
52,4
52,4
Human Resources in the Balanced Scorecard System
as a basis of the management process, because an outstanding strategy is not a random collection of unit strategies but a carefully constructed system of interdependent plans (Collis & Montgomery, 1998). It is also important that the management process is developed and described in detail before the planning of the information system (Kettunen & Kantola, 2005). The management process includes a sequence of management activities, which includes the objectives, operations, resources and results. The strategic planning produces the objectives, which are placed in the different perspectives of the balanced scorecard. The operations of the internal processes are planned to achieve the desired objectives. The financial resources are allocated in the budgeting process for the operations of the internal processes. The achievement of results is monitored and ensured so that the desired objectives can be achieved within an agreed time and budget. The data warehouse approach proved to be useful to capture data from existing data sources and direct them to an integrated database (Inmon, 1996, Guan, Nunez & Welsh, 2002). The essential data that supports the management process are no longer acquired arduously from separate data sources or personal files. Before the introduction of the data warehouse, data collection was scattered, unreliable and to a large extent manual. A lot of overlapping data were collected on an ad hoc basis without the documentation of the data collection processes. A new MIS portal was developed to support the management process and for the use of different people in the organization. The portal takes advantage of data warehousing that makes efficient use of the data obtained from the various data systems. The members of the institution have diverse user rights and roles in the interactive tool, which allows different organizational units to draft their strategic plans, action plans, budgets, and HR plans. The action plan also integrates strategic and quality management. The portal is
also a communication tool that is used to make the strategic plan understandable to the personnel of the institution.
The MIS Integrates Different Approaches of Management The MIS is an electronic platform, which includes strategic plans, action plans, budgeting tools, and HR plans. The MIS also includes information on feedback from students and employers. The TUAS regularly collects course feedback from students and employers represented in the 26 advisory boards of the institution. The MIS also includes information on the internal evaluations of the institutions and the suggestions of external evaluation by the Finnish Higher Education Evaluation Council. The open MIS enables the administrators and the members of the personnel to see how the institution is implementing its strategy and continuously improving its operations. Budgeting is the primary management process in most organizations. The budget has traditionally helped managers with short-term tactical planning and operational details. Managers typically review the operating performance against the budget and take corrective action if necessary during the budget year. The budget should allocate resources to the strategic initiatives to achieve long-term strategic objectives. Operational management is not, however, divorced from strategic management, because the budget is aligned with the strategic objectives of the balanced scorecard. The action plan must identify the strategic initiatives, the units and individuals responsible for the implementation and timetable. The individuals responsible must drill the unit action plan down into more detailed plans and include the actions in their personal workload plans. Typically the workload plans are finalized with the line manager in Finnish educational institutions. The action plans of the operational units and the individual workload plans must be aligned with the internal processes perspective of the balanced scorecard.
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The HR plan should direct an increasing amount of investments in human capital, because the HR is critical to organizational success in a knowledge economy. If resources are not directed towards the drivers in the learning perspective of the balanced scorecard, the other objectives will remain distant goals to which the organization is not committed. The advantage of the balanced scorecard approach is that the personnel can see how investments in human capital can help the organization to achieve its strategic objectives.
FUTURE TRENDS The monitoring of the action plans and the budget is part of the periodic review process of management. The administrative units of the TUAS report on the achievements of the measures and targets three times a year. The TUAS has six educational departments, a continuing education centre and ten shared support units. All the administrative units have their own balanced scorecards, which directly contribute to the overall balanced scorecard of the institution. The achievement of the target values can be monitored using the MIS. The objectives include 37 measures with target values for the planning period. The measures and targets are updated annually and agreed on in the internal target discussions. Obvious future trends are that the number of data sources will increase in the data warehouse and more data will be collected from outside the organization. The information environments of the knowledge society will be open and dynamic. Networking with other organizations requires dynamic information environments which provide two-way access to shared information. Weak and strong signals are derived from the changes of the environment. The organization must match the resources of the organization to the changing environment in the strategic planning.
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CONCLUSION This article shows that a MIS with a portal can be used to integrate the different approaches and tools of management. An advantage of the electronic platform is that it supports the management process at all organizational levels and provides a framework for consistent future planning. HR planning can be aligned with strategic management, budgeting, action plans and quality management. It also turned out that the balanced scorecard approach is a useful tool when the different approaches of management are integrated into an information system. Management in a knowledge intensive organization requires software and controlled IT architecture. The data warehouse approach collects data from various data systems such as student administration, personnel management and financial management systems. The data warehouse provides a centralized database that integrates data from the diverse data sources. It integrates large amounts of data needed in the management process and statistical purposes. The integrated approaches of management and the open MIS create strategic awareness among the members of the organization and align the strategic objectives of the different administrative units. The integration and alignment of plans help management to create a shared understanding among the personnel about the efforts and steps needed for change. The MIS provides a system for the exchange of knowledge within the organization. It also stimulates dialogue encouraging innovations and reciprocal open discussion about strategic objectives.
REFERENCES Bush, T., & Coleman, M. (2000). Leadership and strategic management in education. London: Paul Chapman Publishing.
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Collis, D., & Montgomery, C. (1998, May/June). Creating corporate advantage. Harvard Business Review, 70–83. Galliers, R. D., Swatman, P. M. C., & Swatman, P. A. (1995). Strategic information systems planning: Deriving comparative advantage from EDI. Journal of Information Technology, 10(3), 149–157. doi:10.1057/jit.1995.19 Guan, J., Nunez, W., & Welsh, J. F. (2002). Institutional strategy and information support: The role of data warehousing in higher education. Campus-Wide Information Systems, 9(5), 168–174. doi:10.1108/10650740210452274 Inmon, W. H. (1996). Building the data warehouse. New York: John Wiley & Sons. Kaplan, R., & Norton, D. (2001). The strategyfocused organization. Boston: Harvard Business School Press. Kaplan, R., & Norton, D. (2004). Strategy maps. Boston: Harvard Business School Press. Kaplan, R., & Norton, D. (2006). Alignment: using the balanced scorecard to create corporate synergies. Boston: Harvard Business School Press. Kettunen, J. (2004). Bridge building to the future of Finnish polytechnics. Journal of Higher Education Outreach and Engagement, 9(2), 43–57. Kettunen, J. (2005). Implementation of strategies in continuing education. International Journal of Educational Management, 19(3), 207–217. doi:10.1108/09513540510590995 Kettunen, J., & Kantola, I. (2005). Management information system based on the balanced scorecard. Campus-Wide Information Systems, 22(5), 263–274. doi:10.1108/10650740510632181
Kettunen, J., & Kantola, M. (2006). Strategies for virtual learning and e-entrepreneurship. In F. Zhao (Ed.), Entrepreneurship and innovations in e-business: An integrative perspective (pp. 107123) Hershey, PA: Idea Group Publishing. Maassen, P., & Stensaker, B. (2003). Interpretations of self-regulation: The changing state-higher education relationship in Europe. In R. Begg (Ed.), The dialogue between higher education research and practice (pp. 86-95). Dordrecht: Kluwer Academic Publishers. Meyer, H. D. (2002). The new managerialism on education management: Corporatization or organizational learning? Journal of Educational Administration, 40(6), 534–551. doi:10.1108/09578230210446027 Meyer, M. W. (2002). Rethinking performance measurement:╯Beyond the balanced scorecard. Cambridge, UK:╯Cambridge University Press. Middlewood, D., & Lumby, J. (1998). Strategic management in schools and colleges. London: Paul Chapman Publishing. Mouritsen, J., Thorsgaard Larsen, H., & Bukh, P. N. (2005). Dealing with the knowledge economy: Intellectual capital versus balanced scorecard. Journal of Intellectual Capital, 6(1), 8–27. doi:10.1108/14691930510574636 Niven, P. R. (2005). Balanced Scorecard diagnostics: Maintaining maximum performance. Hoboken, NJ:╯Wiley. Papenhause, C., & Einstein, W. (2006). Implementing the balanced scorecard at a college of business. Measuring Business Excellence, 10(3), 15–22. doi:10.1108/13683040610685757 Rampersad, H. K. (2005). Total performance scorecard: The way to personal integrity and organizational effectiveness. Measuring Business Excellence, 9(3), 21–35. doi:10.1108/13683040510616943
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Self, J. (2003). From values to metrics: Implementation of the balanced scorecard at a university library. Performance Measurement and Metrics, 4(2), 57–63. doi:10.1108/14678040310486891
KEY TERMS AND DEFINITIONS Balanced Scorecard: A framework for the communication and implementation of the strategy. The balanced scorecard approach translates the strategy of an organization into tangible objectives and measures and balances them typically into four different perspectives: customers, financial outcomes, internal processes, and learning. Data Warehousing: The process of capturing data contained in the various operational systems of an organization. The data from external sources can optionally be added to the data warehouse and utilized for analysis and decision-making purposes. Diagnostic Measure: Signals about organizational health and represent the important dimensions of performance in the same way as body temperature and blood pressure of individuals. They are not strategic measures used to manage the transformations to achieve strategic objectives.
Management Information System: A proper management information system presupposes modeling the entire management process and tailoring all the necessary components of the information technology support system to meet the needs of the organization. The management information system should include a description and measures as to how the strategic objectives will be achieved. Management Portal: The management portal is a management tool to be used by managers and other members of the organization. Other stakeholders can have reports produced in the portal. Strategic Management: Strategic management is a matter of bridge building between the perceived present situation and the desired future situation. Strategy implies the movement of an organization from its present position, described by the mission, to a desirable but uncertain future position, described by the vision. Strategy Map: The concept of the strategy map is used to describe the strategy. The strategy map is a visual representation of the cause-and-effect relationships among the objectives of an organization’s strategy and a great insight for executives and stakeholders in understanding the strategy.
This work was previously published in Encyclopedia of Human Resources Information Systems: Challenges in e-HRM, edited by Teresa Torres-Coronas and Mario Arias-Oliva, pp. 464-470, copyright 2009 by Information Science Reference (an imprint of IGI Global).
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Chapter 3.4
The Role of HRIS in Crisis Response Planning Amy E. Hurley-Hanson Chapman University, USA
INTRODUCTION “On Sept. 11, 2001, terrorists attacked the World Trade Center, killing 2,749 people. The attack resulted in severe economic impact, especially to airlines, and a stock market loss of $1.2 trillion. On December 26, 2004, a tsunami from a 9.1 earthquake overran the shores of many countries along the vast rim of the Indian Ocean. Over 283,000 people died. On August 29, 2005, Katrina, a category-5 hurricane, knocked out electric and communication infrastructure over 90,000 square miles of Louisiana and Mississippi and displaced 1.5 million people.” (Denning, 2006,
p. 15). This past decade has been catastrophic, and there are still three more years to go. Many American businesses have not responded to the call for better human resource crisis planning, while a few corporations have risen to the challenge. It is necessary and extremely important for organizations to understand the importance of implementing crucial changes in the organizational structure of businesses, primarily in the human resource sector. The human resource sector is the area most responsible for the safety of personnel and therefore best equipped to foster the communication requirements any crisis will necessarily exact.
DOI: 10.4018/978-1-60960-587-2.ch304
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The Role of HRIS in Crisis Response Planning
BACKGROUND Since 9/11, the importance of human resource information systems (HRIS) has increased substantially. It has become important in all industries despite their differing business models, clienteles, or work forces. A key example of an affected industry is the complex and widely diverse health care industry. “Since 9/11, public health has seen a progressive culture change toward a 24/7 emergency response organizational model. This transition entails new expectations for pubic health workers, including (1) a readiness and willingness to report to duty in emergencies and (2) an ability to effectively communicate risk to an anxious public about terrorism or naturally occurring disasters” (Barnett et al., 2005, p. 35). What the surge in emphasis on human resource preparation indicates is that it is no longer financially viable or politically responsible to ignore the necessity of contingency planning. This knowledge has grown out of the climate of change based on the lessons learned from the terrorist acts of 9/11. “More importantly, the feedback and lessons learned from the September 11 disaster recovery process had a significant impact on optimizing the current processes, culture, and organizational model.” (De Tura, Reilly, Narasimhan, & Zhenhua, 2004, p. 160). It has become clearer that both customers and employees alike expect an emergency preparation model from the financial community to prevent disruptions of commerce so that business as usual can resume as soon as possible after a disaster. “Since the events of September 11, 2001 in New York, there is now world-wide awareness of the necessity of having trained and coordinated teams available to respond to such unexpected catastrophes” (Smith, Lees, & Clymo, 2003, p. 517). It is not difficult to understand this mentality, especially since this country has now witnessed examples of effective and ineffective corporate leadership in crisis. Even people previously inexperienced with emergency contingencies are now cogni-
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zant of what are the most basic steps a company must take to ensure its work place survival and competency. “These steps include preventative planning and training, responding competently during the event itself, and providing social support and post-event services” (Schouten, Callahan, & Bryant, 2004, p. 232). Prior to 9/11, the function of human resources was considerably different; previously it was reserved more for handling personnel issues in the company such as managing health benefits, attending to payroll, etc. That has changed. “Over the past two decades, the role of human resource management (HRM) in organizations has shifted from measuring individual productivity among the employees toward strategic management of the human resources, focusing on competence development, human learning management, knowledge management, and learning organizations” (Hustad & Munkvold, 2005, p. 82). An important reason for this change is the way in which information technology (IT) has shaped this organizational component of a company. It is not adequate for a competitive business to not be equipped with the latest in informational technology when dealing with a vast amount of data and personnel. “Computerized information systems have developed from a mere transaction processing function through a data accumulation period to a decision support role” (Beckers & Bsat, 2002, p. 41).
HRIS PREPAREDNESS BEFORE AND AFTER A CRISIS It is no longer viable for the top management of a functioning company to not utilize the capabilities of information technology. If one organization is not prepared to communicate with all levels of employees and make decisions quickly, a competitor will. Managers must be cognizant of incoming intelligence, be able to analyze trends they see coming, and predict crisis before they can occur,
The Role of HRIS in Crisis Response Planning
whether they be within an organization or outside of it. “An important part of management’s responsibility is related to giving and receiving critical feedback…. It comes with the territory if you are in IT management” (Hacker, 2003, p. 77). Part of this level of preparedness means sensing when key employees may be unhappy or dissatisfied with their current positions. This is an extremely valuable asset in organizations where your company’s productivity depends on possessing workers with specialized skills such as computer technology. “The survival of an organization may depend on its ability to deal with the issues of turnover and retention among its IT managers. In today’s business environment where IT is increasingly relied upon to create and sustain a competitive advantage, the loss of experienced and capable IT managers, can be profound” (Longenecker & Scazzero, 2003, p. 59). The level of company preparedness directly relates to its handling of crises. “Crisis management is broadly defined as an organization’s preestablished activities and guidelines for preparing and responding to significant catastrophic events or incidents (i.e., fires, earthquakes, severe storms, workplace violence, kidnappings, bomb threats, acts of terrorism, etc”) (Lockwood, 2005, p. 1). An organization needs to explore their preparedness for crises and explore if they are utilizing their HRIS to improve their disaster plans. After 9-11, many articles were written regarding how organizations needed to develop their HRIS systems to enable them to continue operations after a terrorist attack. In “A Look Back at a Disaster Plan: What Went Wrong—and Right,” Lawson (2005), an official from Tulane University, explains how he extrapolated from contingency planning he received from living through the 9/11 crisis to deal with Hurricane Katrina in New Orleans. “You also need a business-continuity plan for your institution. You’ve got to think about how you are going to function if a disaster happens. How long can you go without printing transcripts, how long without sending paychecks out, how long
without paying bills? How long can you tolerate not sending out accounts-receivable statements? You need to make those choices, so you’ll know how much money you’ll have to spend on disaster recovery.” (p. 20). It is also important to note that citizens of this country gravitated towards an expectation that national crisis preparation should be performed by the federal government after the 9/11 attacks. Their expectations were not met when Federal agencies failed to properly plan for the Katrina disaster. “People had not always looked to the federal government for help during disasters, but during the twentieth century the level of assistance expected from the federal government before and after a disaster ratcheted upwards….” (Roberts, 2006, p. 25). The level of security and safety that people felt towards their institutions, first challenged by the events of 9/11, was called into question by the planning incompetence exhibited by the Federal Emergency Relief Agency (FEMA). “We still have difficulty grasping the notion that we are not safe from disaster in our own country. We couldn’t imagine a foreign terrorist attack on our soil. It happened. We couldn’t imagine an entire city disappearing under water, its population evacuated — but too late. It happened. We must begin to imagine future disasters, perhaps multiple catastrophes, for they, too, may well occur” (Nussbaum, 2005, p. 36). What is of vital importance, then for business, is for every organization to be self-prepared through their own HRIS systems and other IS systems. That preparation extends to all areas of corporate functioning, but particularly to personnel considerations, as it is ultimately the people who run a company. In trying times, companies must be able to contact their employees and resume business after all types of crises, not just terrorist attacks or natural disasters such as Hurricane Katrina. Again, Lawson (2005) recounts his experiences at Tulane, particularly his HR failures: “And people were too dispersed for post-disaster activity, which was exacerbated by the communications failure.
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We couldn’t get hold of people to find out where they were. I had my director of administrative computing evacuating to one city; my director of networking, who was supposed to go with me, ended up in a different city because of traffic. We had people spread out all over.” (p. 20). Lawson’s human resource difficulties were not unique. Unfortunately, much of the knowledge corporations gained from dealing with the aftermath of the terrorist attacks was either forgotten or misused during the crisis following Hurricane Katrina. There are still many problems of organizational preparation in this country. During Hurricane Katrina we saw that many organizations’ HRIS systems or their IT systems were not prepared for this disaster. A study released in December 2005 by the nonprofit, Trust for America’s Health (TFAH), noted, “[Hurricane Katrina] provided a sharp indictment of America’s emergencyresponse capabilities as the gaps between plans and reality became strikingly evident. Parts of the public health system did not work, and while many did work as intended, those functions were often too limited and divorced from other response activities to match the real needs in a timely way,” (Young, 2006, p. 197). The report went on to give specific examples of ways in which some of the most basic infrastructural services are still woefully unprepared, months after Katrina and years after 9/11. “But, according to the report, hospitals in 15 states, including California, Florida, New York, Pennsylvania, Texas, and the District of Columbia, have not sufficiently planned to care for a surge of extra patients by using non-health care facilities, such as community centers, sports arenas, or hotels.” (p. 197). This poor planning that was exhibited by the Federal government in response to Katrina, highlights the need for strong leadership at all levels of an organization during both terrorist attacks and natural catastrophes. Also, the problems that subsequently occurred throughout FEMA and the federal response in wake of Hurricane Katrina were largely due to personnel failing to competently
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communicate with one another. “The various agencies had major difficulties in coordinating and FEMA did not deliver what people thought it had promised. At all levels there was a lot of finger pointing and wrangling over who would do what and who would pay for what” (Denning, 2006, p.17). We must learn from these examples of poor human resource allocation and preparation that organizations need to have a crisis response plan which enables them to initially know where all their employees are (since now so many employees do not just work at the corporate headquarters) and to be able to contact them and their families. Many of the problems and difficulties suffered by the people of Louisiana as a result of Hurricane Katrina were due to poor organizational communications. “At each level of government, leaders failed to hash out their differences beforehand. As a result, officials ran into communications roadblocks that should have been uncovered before the disaster struck.” (Roberts, 2006, p. 26). Another problem that contributed to the organizational breakdown after Katrina was the result of a decentralized command center that failed to hold civil employees accountable to the fulfillment of their obligations as administers of public services. “The report noted that in the days after Hurricane Katrina, more than 30% of the New Orleans Police Department did not report for duty, an indication that “planning must not only account for absences, but also seek to address worker concerns.” (Young, 2006, p. 197). It is evident, based on these incidents, that there is a great need for HRIS systems, which can help the organization, personnel, customers and family members respond quickly in a crisis. Using some of the successes and failures of both 9/11, and Hurricane Katrina as guides to what worked and what didn’t, HRIS can help organizations to begin to take the correct precautions to ensure that when a tragedy or a disaster does strike, an organization is as prepared as possible. In a comment on the state of technology and its implications today, Andrew Lippman, director of the MIT Media Lab,
The Role of HRIS in Crisis Response Planning
relates an unfortunate consequence of living in the wireless age. “The response to the 1906 San Francisco earthquake was more efficient than the emergency efforts that followed Katrina in New Orleans. At a time when communications technologies were limited, a single entity—the U.S. Army—quickly took control of emergency operations,” (Hamblen, 2006, p. 20). There are some good examples of companies employing their HRIS to implement crisis decisions. American Airlines is an excellent example. Directly after the attacks on 9/11 it took immediate steps to assist its personnel. “After American Airlines Flight 11 crashed into the North Tower of the World Trade Center, American Airlines’ most important public was the families of their passengers and crew. A crisis management plan called for the utilization of the Customer Assistance Relief Effort (CARE) program. CARE sent more than 350 specially trained volunteers from American to the departure and destination cities of the hijacked plane. They set up command centers to assist families of victims and helped them deal with such things as flight arrangements, hotel accommodations, and provided food if necessary. CARE volunteers, who speak a cumulative total of 50 languages, also escorted family members attending accident-related events, including memorials and funerals” (Feam-Banks, 2002, p. 30). The corporation of Coast Electric also learned valuable lessons from the tragedy of 9/11 and decided to implement an ad-hoc system of additional, part time employees to deal with the problems created by Hurricane Katrina. “During the storm, Coast Electric saw its 230 full-time employee population swell to 3,000 with contract crews” (Babcock, 2006, p. 37). The professional services organization firm, Ernst and Young, created a catastrophe communications network to account for its employees affected by disaster. “The [so-called] ‘Roll Call’ database allows emergency personnel to view which employees have checked in and compare them against the list of workers assigned or “hoteling” at the office facing the
emergency” (HR Focus, 2005). This roll call can be issued at anytime via an acting manager and it helps track where personnel are during a crisis. Important steps have been taken through management of HRIS of several companies to minimize the potential damage of a crisis of an entirely different nature—that of financial proportions. After the unparalleled disaster of the collapse of the gigantic Enron Corporation, which destroyed the income and assets of thousands of its employees in 2002, many forward-thinking industries have taken preventive measures to ensure its workers are protected through its HRIS. “While Congress and the Bush administration wrestle with how to alter the nature of defined contribution pension plans, savvy HR professionals are reacting to Enron by shoring up the administration of company 401(k) and employee stock ownership plans. They are also tending to employee relations issues that may have been caused by the negative publicity surrounding Enron” (IOMA’S REPORT, 2002, p.3). Finally, in what may be considered an extremely altruistic move or a very pragmatic one, some companies have taken the approach that during a time of crisis for their company, they will refer their own customers to their competitors if they are unable to meet their customers’ needs at the time; this is known as applying a continuity plan. “When Takata Corp.’s airbag plant in Mexico blew up in late March, it set off a supply-chain reaction that illustrates the sophisticated problem-solving capability of the auto industry” (Nussel, 2006, p.14). Instead of telling its customers to wait until the plant could be reopened, the HR department of Takata referred them to rival, Autoliv, while they were attempting to fix the problem at their airbag plant and get back on track.
FUTURE TRENDS Even in this era of cellular phones, the Internet, and fax machines, there is something reassuring about the idea of a central authority that is able
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to give and receive orders with competence that is worthy of emulation. It is the notion that someone, somewhere is in control and knows what to do. Our organizations could have authority on an even bigger and more efficient scale with the right kinds of human resource and information systems preparation. “Good crisis preparedness requires a culture shift,” says Kitty Porterfield, director of communications for Virginia’s Fairfax County Public Schools. “It requires leadership from the top, a critical mass of trained staff members, careful planning, and excellent communication” (Padgett, 2006, p.27). “Hastily developed networks,” is another way HRIS can help organizations in crises. It is very beneficial for firms and has the undeniable payoff of sound organizational planning ahead of time. “Hastily formed networks is an area where advanced networking technology and human organization issues meet…. The first priority after the precipitating event is for the responders to communicate. They want to pool their knowledge and interpretations of the situation, understand what resources are available, assess options, plan responses, decide, commit, act, and coordinate. Without communication, none of these things happens” (Denning, 2006, p.16).
CONCLUSION Ultimately, however, we cannot predict when a crisis is going to occur. This unpredictability is part of the reason that crises are so devastating. The best thing any organization can do to prepare for a crisis is to prepare its defense and that means planning and communicating, beginning with the HR department via information systems down to all levels of a company. It helps to practice by using safety drills. “Test your communications plan and have a backup. Make sure you’re as prepared as possible for your post-disaster activity. That means you need to know where your people are. You need to know how they can get back, and
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you need to have a place for them to get back to” (Lawson, 2005, p. 21). It is also important to make sure your organization is not overly dependent upon technology that could fail in an emergency. “Don’t rely upon cellular and pushto-talk networks. Have an old-fashioned radio system for backup communications on campus. Educate your key personnel on text messaging. We couldn’t make a voice phone call, but we could use text messaging on our phones, because that used so much less bandwidth. Again, put your key personnel in one location, out of harm’s way” (Lawson, 2006, p. 21). Organizations are very important to our lives. Our jobs help us determine who we are and they give us identity. When a catastrophe happens, we want to know that we are safe where we work and that can only occur with the right planning and early preparations put into place. “In addition to providing income, insurance, and other benefits, work imparts a sense of purpose, interrelatedness, and belonging. The workplace serves as a major organizing factor in the lives of most adults and as a source of social support; it is an essential part of the local community” (Schouten et al., 2004, p. 229).
REFERENCES Babcock, P. (2006). Lessons from Katrina: Make your plans now. HRMagazine, 51(8), 27–37. Beckers, A. M., & Bsat, M. Z. (2002). A DSS classification model for research in human resource information systems. Information Systems Management, 19(3), 41–50. doi:10.1201/1078/4 3201.19.3.20020601/37169.6 De Tura, N., Reilly, S. M., Narasimhan, S., & Zhenhua, J. Y. (2004). Disaster recovery preparedness through continuous process optimization. Bell Labs Technical Journal, 9(2), 147–162. doi:10.1002/bltj.20031
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Denning, P. J. (2006). The profession of IT. Communications of the ACM, 49(4), 15–20. doi:10.1145/1121949.1121966 Feam-Banks, K. (2002, September 30). A snapshot of how organizations responded to tragedy. Tactics. Hacker, C. A. (2003). Maintaining positive relationships when giving and receiving critical feedback. Information Systems Management, 20(4), 77–79. doi:10.1201/1078/43647.20.4.20 030901/77296.11 Hamblen, M. (2006, March 6). Disaster communications still lacking, panel says. Computerworld, 20. HR’s role in dealing with disaster. (2005). HR Focus, 82(11), 6-7. Hustad, E., & Munkvold, B. E. (2005). IT supported competence management: A case study at Ericsson, 22(2), 78-88. IOMA’S Report on Managing HR Information Systems. (2002). How your HRIS can help ease employees’ post-Enron concerns. 3-6. Kathleen, F. B. (2002, September). A snapshot of how organizations responded to tragedy. Tactics. Lawson, J. (2005). A look back at a disaster plan: what went wrong—and right. The Chronicle of Higher Education, 52(16), 20–22. Lockwood, N. R. (2005). Crisis management in today’s business environment: HR’s strategic role. HRMagazine, 50(12), 1–10. Longenecker, C. O., & Scazzero, J. A. (2003). The turnover and retention of IT managers in rapidly changing organizations. Information Systems Management, 19(4), 58–63. Nussbaum, B. (2005). The next big one. Business Week, 3851, 34–38. Nussel, P. (2006). What to do when the plant blows up. Automotive News, 80(6217), 14.
Padgett, R. (2006, May). Keeping cool in a crisis. Communicator. Education Digest, 27–28. Roberts, P. S. (2006, June/July). FEMA after Katrina. Policy Review, 15–33. Schouten, R., Callahan, M. V., & Bryant, S. (2004, July/August). Community response to disaster: The role of the workplace. Harvard Review of Psychiatry, 229–237. doi:10.1080/10673220490509624 Smith, M., Lees, D., & Clymo, K. (2003). The readiness is all. Planning and training for post-disaster support work. Social Work Education, 22(5), 517–528. doi:10.1080/0261547032000126452 Young, D. (2006, February 1). Nation still unprepared for health crisis. American Journal of Health-System Pharmacy, 63, 197. doi:10.2146/ news050047
KEY TERMS AND DEFINITIONS Ad-Hoc System: Strategy employed by an effective HRIS to improvise in time of crisis whether that means employing temporary employees to deal with a disaster or installing additional bases from which to continue to conduct business. Catastrophe Communications Network: A roll call system in which once an “incident” is reported, all assigned employees must check in to ensure personnel safety and accountability. Competence Management: The planning, implementation, and evaluation of initiatives to ensure sufficient competencies of the employees and the company to reach the objectives of the organization. Continuity Plan: The go-to plan you have set up in place when your alternatives have been minimized; one example is attending your customers via your competitors’ resources when you are unable to assist them in the same capacity you otherwise could when not in a crisis situation.
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Crisis Management: An organization’s preestablished activities and guidelines for preparing and responding to significant catastrophic events or incidents (i.e., fires, earthquakes, severe storms, workplace violence, kidnappings, bomb threats, acts of terrorism, etc.) Crisis Response Plan: From the point of view of a functioning HRIS, that strategy which enables a company to initially know where all their employees are (since now so many employees do not just work at the corporate headquarters) and that which allows them to able to contact them and their families. Decision Making: The processes of thought and action involving an irrevocable allocation of resources that culminates in choice behavior. Emergency Response Organizational Model: A new expectation of (health) workers
that includes (1) a readiness and willingness to report to duty in emergencies and (2) an ability to effectively communicate risk to an anxious public about terrorism or naturally occurring disasters. Hastily Formed Networks: A thrown-together community or organization designed to gather crucial information and deliver it to the most appropriate people in a crisis situation. Knowledge Management Systems: A broad range of information systems supporting the creation, transfer, and application of individual and organizational knowledge. Roll Call: An interactive database whereby acting managers can keep track of (key) employees in time of crisis by having them check in once an alert has been issued (usually via e-mail).
This work was previously published in Encyclopedia of Human Resources Information Systems: Challenges in e-HRM, edited by Teresa Torres-Coronas and Mario Arias-Oliva, pp. 764-769, copyright 2009 by Information Science Reference (an imprint of IGI Global).
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Chapter 3.5
Concepts, Technology, and Applications in E-Mentoring Ricardo Colomo-Palacios Universidad de Carlos III, Spain Juan Miguel Gómez-Berbís Universidad de Carlos III, Spain Angel Garcia-Crespo Universidad de Carlos III, Spain Cristina Casado-Lumbreras Universidad Complutense, Spain
INTRODUCTION The so-called “Internet revolution” has dramatically changed the way people communicate and work nowadays. Attending to The Word Factbook developed by the U.S. Central Intelligence Agency (CIA), there are 1,018,057,389 Internet users in the world by 2005 (CIA, 2006). Fostering of the Internet revolution from a business perspective is out of question and the ever-growing number of Web functionalities has implied a significant and dramatic change in all business management DOI: 10.4018/978-1-60960-587-2.ch305
areas. Within these areas, this revolution has not gone unnoticed, particularly for human resources management. Mentoring, which has been used as a tool for human capital development leverage in organizations has also been deeply impacted by the emergence and generalized use of Internet technologies giving birth to the so-called “ementoring.” The origins of the term must be looked for in Ancient Greece. In the Homer masterwork “Odyssey,” Ulysses, king of Ithaca, recommends mentor Alcímida his house, properties, and his son, Telemachus, education on leaving for the Troy War (traditionally dated from 1193 BC-1183 BC).
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Concepts, Technology, and Applications in E-Mentoring
Apart from the word ethimology, several modern disciplines literature (such as management, social psychology, sociology, or knowledge management) have provided with mentoring studies from the late seventies of the XX century, particularly, from the mid-nineties. As a consequence of the growing interest of the topic and its broad application in business ecosystems, thousands of definitions have popped up, trying to cover the semantics of the concept. Due to the aforementioned popularity of the concept, Friday and Green (2004) accomplish a re-conceptualization of the term stemming from a deep and detailed study about existing literature definitions. Subsequently, a definition for the mentoring concept is provided, aiming at being universal, following the authors goal: Mentoring is a guidance process that takes place between a mentor and a protégé (also known as mentee). Authors define similarly the mentor term as “wise and trusted counselor or teacher.” Hence, mentoring is an improvement process in a number of aspects related to the professional career, but it is also the improvement of the individual integrating two sides: a senior advisor and a junior protégé. The established relationship is a win-win situation, having mutual benefits for both sides. On the one hand, the protégé, following the empirical studies about the topic, benefits from improvements in his professional career mainly related to promotions (Dreher & Ash, 1990; Scandura, 1992), a higher income (Dreher & Ash, 1990; Whitely, Dougherty, & Dreher, 1991), more satisfactions in the work environment, and socialization in the workplace (Chao, Walz, & Gardner, 1992). On the other hand, mentors benefit from faster promotions, reputation, and personal satisfaction (Scandura, Tejeda, Werther, & Lankau, 1996). Finally, organizations also benefit, given a highest motivation of the employees, lower working mobility rates, and the improvement of leadership and development skills (Levesque, O’Neill, Nelson, & Dumas, 2005), relying on more adaptable employees, willing to share knowledge and ready to face a decision
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making process with more trust and confidence (Ragins & Scandura, 1999).
BACKGROUND Due to technology capability of setting up new communication means and paradigm among people, the envisagement of electronic communication as a means for mentoring relationships was immediate. E-mentoring refers to the process of using electronic means as the primary channel of communication between mentors and protégés (Hamilton & Scandura, 2003). The key distinction between electronic mentoring and traditional mentoring (t-mentoring) is reflected in the face-time between mentors and protégés. The communication means used by both sides is absolutely different in the two mentoring types. While traditional mentoring uses face-to-face relationships, e-mentoring, which also harness face to face relationships, particularly at the beginning of the relationship, is mostly based on e-mail, chat, instant messaging, and several other Internet applications. As it was previously outlined, e-mentoring is a kind of mentoring, based total or partially on electronic communication. Due to the great amount of electronic communication instruments, a remarkable number of different names for the concept e-mentoring have been provided. According to Perren (2003), e-mentoring can be seen to encompass a range of terms: computer-mediated mentoring, tele-mentoring, e-mail mentoring, Internet mentoring, online mentoring, and virtual mentoring. In this section, we will describe the most relevant e-mentoring features through a review of advantages and disadvantages of e-mentoring faced to t-mentoring, the phases in the mentoring cycle, and the description of e-Mentoring mentoring styles, to end up with the main and most widely used e-mentoring implementations.
Concepts, Technology, and Applications in E-Mentoring
Advantages and Disadvantages of E-Mentoring Face to T-Mentoring Although Evans and Volery (2001) suggested from their survey of experts that e-mentoring is “secondbest” and should only be seen as a supplement to face-to-face mentoring, there are many other studies in which e-mentoring is pointed out as a valid vehicle to overcome some of the t-mentoring barriers. E-mentoring provides flexibility and easy access which is highly beneficial to those who may face barriers to being mentored, because of their gender, ethnicity, disability, or geographical location (Bierema & Hill, 2005). Hamilton and Scandura (2003) also analyze the advantages of e-mentoring in comparison with t-mentoring. These advantages are classified in mainly three groups: • • •
Organizational structure Individual and interpersonal factors Flexible/alternative work arrangements
Firstly, regarding the organizational structure, e-mentoring takes out geographical barriers carried by face-to-face interactions, smoothes status differences within the organization, and increases the pool of available mentors. Secondly, in what concerns individual and interpersonal factors, the absence of face-to-face interactions decreases and minimizes gender or ethnical issues impact by increasing the effectiveness of mentors with a lack of social skills. Finally and to sum up, in what concerns flexible or alternative work arrangements, the ability and actual capability of performing asynchronous communications implies clearing out temporal barriers or caveats. In addition, communication is not geographically bounded. Some studies provide further arguments to the statements from Hamilton and Scandura (2003). Hence, following this trend, Warren and HeadlamWells (2002) observed that t-mentoring, typically operating in large organizations tends to cast the
mentee as a passive recipient of structured formal provision. On the other hand, the use of the Web as a communication means between the mentor and the mentee improves access and creates a larger pool of potential mentors and mentees (Packard, 2003). In addition, as with other e-learning programmes, a major advantage of an e-mentoring system is its cost effectiveness (Headlam-Wells, Gosland, & Craig, 2005). There are high start-up costs, but once established, the operational costs are relatively low. Costs related to travel or time away from the job and costs of updating learning resources can be reduced. At last, a record of the ‘‘discussion’’ usually exists for later reflection and learning (Hunt, 2005). To summarize, it is possible to state, as it is discussed by Clutterbuck and Cox (2005), that e-mentoring will be able to overcome many of the problems involved in t-mentoring. Nevertheless, not all e-mentoring features are win-win for the mentor-mentee relationship. Eby, McManus, Simon, and Russell (2000) conducted empirical work in this area that further examined the dark side of mentoring and developed a useful taxonomy of negative experiences from the mentee perspective using qualitative data. These authors make important distinctions between what is considered negative and how that might be different from the mentee and mentor perspective. A latter study conducted by Ensher, Heun, and Blanchard (2003) uses Eby et al.’s (2000) findings to identify five major challenges in e-mentoring: (1) likelihood of miscommunication, (2) slower development of relationship online than in face to face, (3) requires competency in written communication and technical skills, (4) computer malfunctions, and (5) issues of privacy and confidentiality.
Phases in the Mentoring Cycle Salmon (2004) suggests a five-stage model to provide a valuable guide for e-mentoring programme designers. Central to this model is the role of the e-moderator, who acts as a mentoring resource to
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Table 1. Matching criteria proposed by Headlam-Wells et al. (2006) for automatic pair matching Criterion
Explanation
Age
Mentee matched with older mentor
Number of years work experience
Mentee matched with mentor with more work experience
Level of qualification
Mentee matched with mentor with higher qualification level
Marital status
Mentee matched with mentor with same marital status
Children
Mentee matched with mentor in a similar situation to themselves (having/had children)
Dependant care
Mentee matched with mentor in a similar situation
Life/career history
Identify similarities in life/career experiences, fro example, having experienced barriers to progression
Personal skills
Mentee matched with mentor who could help them develop the personal skills they need to improve
Professional skills
Mentee matched with mentor who could help them develop the professional skills they need to improve
Vocational sector
Mentee matched with mentor who worked/had worked in a similar occupational area
Personal values
Mentee matched with mentor who shared similar core values
both mentors and mentees. Purcell (2004) suggests that “even mentors need mentors at times,” or at least someone with whom they can talk about mentoring issues. Salmon’s first stage is “access and motivation” where both mentor and mentee access the system, and are welcomed, encouraged, and motivated by their e-moderator. In the second stage, “online socialization,” participants establish their online identities and build bridges with their partner, the e-moderator, and the wider group. “Information exchange” is the stage in which participants explore the site and are encouraged to carry out learning tasks using online learning materials. At stage four, “knowledge construction” discussions on career development take place between the pair and among the group. This fourth stage can be considered as the core of the learning process. At stage five, “development,” participants focus in greater depth on achieving their personal goals and reflect on the learning process. Notwithstanding, as it was previously stressed, the general approach of the model for e-learning activities avoids relying on one of the fundamental aspects of e-mentoring relationships: pair matching criteria. This concept is based on the assignment of a mentor to a mentee depending of a number of parameters defined with the purpose
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of harnessing the mentorship. Such parameters might include values, gender coincidences, related professional experience, and so on. Despite it being a key issue of concern for mentoring, crucial in words of Hunt (2005), there is little research concerning the matching of pairs (Headlam-Wells et al., 2005). Cohen and Light (2000) argue that matching solely on the basis of mentees needs and mentors’ skills may not be enough to ensure successful matches, and suggest that personality factors may also be significant. Indeed, successful mentoring relationships are often reported as those where mentees felt they shared their mentors’ personal values (Headlam-Wells et al., 2005). With the exception of a small number of mentoring programmes which use a formal matching system, most tend to use a ‘hand-sift’ method, whereby mentees are matched with a mentor who suits their needs (Headlam-Wells, Gosland & Craig, 2006). However, if a number of people of remarkable size is faced, that kind of features can unfortunately not be applied. Therefore, HeadlamWells et al. (2006) suggest a set of eleven criteria that allow the automation of the process, together with application criteria:
Concepts, Technology, and Applications in E-Mentoring
E-Mentoring Styles
FUTURE TRENDS
According to Ensher et al. (2003) there are three e-mentoring styles. The first type is computer mediated communication (CMC)-only in which mentoring is done only by electronic means. The second type is CMC-primary, in which the majority of mentoring interactions are conducted online but may also be supplemented by telephone calls and face-to-face interactions. Usually the first contact is made face to face. The third type is CMC-supplemental in which the majority of mentoring is done in person, yet the relationship is supplemented via e-mails, instant messaging, chat-rooms, Web sites, and so forth. This can be the case of a mentor and mentee who work for the same organization, yet because of different schedules or difficulty in scheduling meetings, may use e-mail in place of face-to-face meetings and to communicate information.
The ever-growing social adoption of IT is fostering an unstoppable “virtualization” process of most of our daily experiences. Virtual world overlaps the physical world and fits its constraints. Thus, most e-mentoring relationships have attained significant progress in the CMC-supplemental in a remarkable percentage. In addition, the boom of the so-called Web 2.0 brings into the arena an interesting innovation and research field where ementoring is a perfect guinea pig. This new social Web is a further evolution of the Web, whereby a number of social software tools are hoarding communication, sharing, and cooperation among Web users. This new upcoming communication paradigm is depicting a challenging scenario featured by infinite learning relationships and informal mentoring. These will be based on the concept of “collective intelligence” implemented by a number of crowd-oriented sites such as Digg® (www.digg.com) or the ever-increasing blogs being born each and every day. The blogosphere, an abstraction to name this new phenomenon, allows bi-directional interaction by means of comments and have subsequently subverted the consumerproducer equation on the Web. Nonetheless, e-mentoring, despite its obvious advantages, presents some caveats such as those related to communication (Ensher et al., 2003). Presently, most of the mentor-mentee interactions happen in a textual form, using e-mail, instant messaging (IM), or discussion forums. An increasing number of functionalities, networks bandwidth capabilities, and server storage outperform previous technologies and present a great chance for the application of visual technologies reducing the disadvantages of writing communication, namely miscommunication or slowness, by allowing communication storage for its further review. One of the technological applications that can be envisaged as highly recommendable for e-mentoring processes is the so-called “virtual worlds.” These are computer-generated graphi-
E-Mentoring Implementations There are a number of Web sites that allow the creation of relationships among mentors and mentees. As a mere example, we can point at: Electronic Emissary® (http://emissary.wm.edu/), Professional Mentoring® (http://www.promentoring.com/), Mighty Mentors® (http:// www.mightymentors.com/), Academos® (http:// www.academos.qc.ca/), Advanced Mentoring® (http://www.advancementoring.com), iMentor® (http://www.imentor.org), and the one which has undergone probably most impact and acceptance: MentorNet® (http://www.mentornet.net/). MentorNet® offers one-on-one e-mentoring programs for students of engineering and related sciences (freshmen through postdocs) with professionals in industry, government, and higher education for 8 month-long, structured mentoring relationships conducted via e-mail. According to the company, since its birth in 1998, MentorNet® has matched over 25,000 individuals and created a community of more than 15,000 members.
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cal representations of environments (imagined or reality-driven). The most well-known and widely visited is Second Life®. It is inhabited by 13,874,040 people (June 2008) from around the globe that perform 19,060,161 economic transactions per month (April 2008). Second Life® offers its users to show evolving behaviors related to the changes undergone in its environment via their avatar-shape representation. Currently, virtual worlds are used in a variety of domains, particularly those related with simulation, entertainment, or even politics (U.S. politician Mark Warned showed up in Second Life® on August 31, 2006 to discuss several points of his campaign). Thanks to the digital features of virtual reality, this kind of environments benefit from the possibility of integrating human perception in the system and emulate behaviors in the avatars, even adding non-verbal communication. This circumstance can drop down some of the CMC barriers and leverage the potential of e-mentoring sessions.
CONCLUSION The e-mentoring domain offers an open field both for research and for business environments application in the human resources area. Nowadays, if compared with the t-mentoring research field, studies related to the concept and its applications are quite rare or scarce. On the other hand, e-mentoring spreading capabilities seem only limited by the possibilities offered by the technology to the users. Inherent features of e-mentoring may break down a number of barriers for the application of t-mentoring, broadening its impact significantly. The downside of e-mentoring application is focused on technological limitations and technology access. The evolution of technology and the emergence of new Web-based communication paradigms will foster their enrichment and harnessing of mentoring communities, avoiding these to become a simple set of peers, creating synergies for the bi-directional
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learning of mentor and mentees. Furthermore, outside the technological scope, negative aspects of online relationships can be greatly reduced with training and education (Wallace, 1999). In what concerns to barriers for technology adoption, on the one hand, platforms ease of use and, on the other hand, ever-growing acceptance of technology by world wide population might attain critical changes in the situation, fostering virtual and physical world integration. To sum up, despite the knowledge gap in ementoring research, the growing acceptance of CMC in significant everyday life aspects opens a challenging application field which academia and organizations must harness.
REFERENCES Bierema, L., & Hill, J. (2005). Virtual mentoring and HRD. Advances in Developing Human Resources, 7(4), 556–568. doi:10.1177/1523422305279688 Chao, G. T., Walz, P. M., & Gardner, P. D. (1992). Formal and informal mentorships: A comparison on mentoring functions and contrast with nonmentored counterparts. Personnel Psychology, 45, 619–636. CIA, Central Intelligence Agency. (2006). The World FactBook. Rank order Internet users. Retrieved September 19, 2006, from https://www.cia.gov/cia/publications/factbook/ rankorder/2153rank.html Clutterbuck, D., & Cox, T. (2005, November). Mentoring by wire. Training Journal, 35-39. Cohen, K. J., & Light, J. C. (2000). Use of electronic communication to develop mentor-protégé relationships between adolescent and adult AAC users: Pilot study. Augmentative and Alternative Communication, 16, 227–238. doi:10.1080/0743 4610012331279084
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Dreher, G. F., & Ash, R. A. (1990). A comparative study of mentoring among men and women in managerial, professional, and technological positions. The Journal of Applied Psychology, 75, 539–546. doi:10.1037/0021-9010.75.5.539 Eby, L. T., McManus, S. E., Simon, S. A., & Russell, J. E. (2000). The Protégés perspective regarding negative mentoring experiences: the development of a taxonomy. Journal of Vocational Behavior, 57, 1–21. doi:10.1006/jvbe.1999.1726 Ensher, E. A., Heun, C., & Blanchard, A. (2003). Online mentoring and computer-mediated communication: New directions in research. Journal of Vocational Behavior, 63(2), 264–288. doi:10.1016/S0001-8791(03)00044-7 Evans, D., & Volery, T. (2001). Online business development services for entrepreneurs: An exploratory study. Entrepreneurship and Regional Development, 13(4), 333–350. doi:10.1080/08985620110052274 Friday, E., Friday, S. S., & Green, A. L. (2004). A reconceptualization of mentoring and sponsoring. Management Decision, 42(5), 628–644. doi:10.1108/00251740410538488 Hamilton, B. A., & Scandura, T. A. (2003). E-mentoring: Implications for organizational learning and development in a wired world. Organizational Dynamics, 31, 388–402. doi:10.1016/ S0090-2616(02)00128-6 Headlam-Wells, J., Gosland, J., & Craig, L. (2005). There’s magic in the Web: E-mentoring for women’s career development. Career Development International, 10(6/7), 444–459. doi:10.1108/13620430510620548 Headlam-Wells, J., Gosland, J., & Craig, L. (2006). Beyond the organization: The design and management of e-mentoring systems. International Journal of Information Management, 26, 372–385. doi:10.1016/j.ijinfomgt.2006.04.001
Hunt, K. (2005). E-mentoring: Solving the issue of mentoring across distances. Development and learning in organization, 19(5), 7-10. Levesque, L. L., O’Neill, R. M., Nelson, T., & Dumas, C. (2005). Sex differences in the perceived importance of mentoring functions. Career Development International, 10(6), 429–443. doi:10.1108/13620430510620539 Packard, B. W. (2003). Web-based mentoring: Challenges traditional models to increase women’s access. Mentoring & Tutoring, 11(1), 53–65. doi:10.1080/1361126032000054808 Perren, L. (2003). The role of e-mentoring in entrepreneurial education & support: A meta-review of academic literature. Education & Training, 45(8/9), 517–525. doi:10.1108/00400910310508900 Purcell, K. (2004). Making e-mentoring more effective. American Journal of Health-System Pharmacists, 61, 284–286. Ragins, B., & Scandura, T. (1999). Burden or blessing? Expected costs and benefits of being a mentor. Journal of Organizational Behavior, 20(4), 493–510. doi:10.1002/ (SICI)1099-1379(199907)20:43.0.CO;2-T Salmon, G. (2004). E-moderating: The key to teaching and learning online (2nd ed.). London: RoutledgeFalmer. Scandura, T., Tejeda, M., Werther, W., & Lankau, M. (1996). Perspectives on mentoring. Leadership and Organization Development Journal, 17(3), 50–58. doi:10.1108/01437739610117019 Scandura, T. A. (1992). Mentorship and career mobility: An empirical investigation. Journal of Organizational Behavior, 13, 169–174. doi:10.1002/job.4030130206 Wallace, P. (1999). The psychology of the Internet. Cambridge, UK: Cambridge University Press.
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Warren, L., & Headlam-Wells, J. (2002). Mentoring women entrepreneurs: A better approach. Organizations and People, 9(2), 11–17. Whitely, W. T., Dougherty, T. W., & Dreher, G. F. (1991). Relationship of career mentoring and socioeconomic origin to managers’and professionals’ early career progress. Academy of Management Journal, 34, 331–351. doi:10.2307/256445
KEY TERMS AND DEFINITIONS E-Mentoring: The process of using electronic means as the primary channel of communication between mentors and protégés. Mentor: Trusted friend, counselor, or teacher. Usually a more experienced person.
Pair Matching: Process in which a mentor is assigned to a mentee regarding upfront pre-defined parameters with the aim of attaining a higher benefit from the mentoring process. Peer Mentoring: Form of mentoring that takes place in learning environments such schools, usually between an older more experienced student and a new student(s). Protégé/Mentee: More junior individual who is paired with a mentor based on shared interests in order to provide him/her career and psychosocial developmental support. T-Mentoring/Mentoring: Relationship between a more experienced person, mentor, and a less experienced partner referred to as a mentee or protégé.
This work was previously published in Encyclopedia of Human Resources Information Systems: Challenges in e-HRM, edited by Teresa Torres-Coronas and Mario Arias-Oliva, pp. 166-171, copyright 2009 by Information Science Reference (an imprint of IGI Global).
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E-Recruitment in Emerging Economies Pramila Rao Marymount University, USA
INTRODUCTION Electronic human resource management (eHRM) is the process of using online technology for human resource management activities, such as recruitment, training, performance appraisal and benefits (Rudich, 2000). The goal of this article is to discuss the origins of e-recruitment and address some challenges of e-recruitment in emerging economies like India and Mexico as multinationals seeks to establish strong presence in these countries. DOI: 10.4018/978-1-60960-587-2.ch306
E-recruitment originated in the form of independent job sites called bulletin board systems in the 1980s. Initially only the U.S. universities and military had access to Internet facilities. However, the PC revolution that embraced the world in the early 1990s changed the corporate landscape completely (Rudich, 2000). Today more than three-fourths of the Fortune 500 companies use online recruiting and approximately about 18 million people are posting their resumes on Internet portals such as Monster.com (Feldman & Klaas, 2002). Corporations are aggressively seeking the best talent worldwide. Internet recruiting allows
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organizations to tap a huge talent beyond their own national boundaries (Birchfield, 2002). Erecruitment has several advantages such as its low cost (Galanaki, 2002; Rudich, 2000), quick response time (Hays, 1999), wide range of applicants (Sessa & Taylor, 2000), and worldwide accessibility (Galanaki, 2002; Vinutha, 2005). Specifically to recruitment, it has demonstrated a shorter recruitment cycle and lower cost-per-hire (Jasrotia, 2001; Pollitt, 2005; Sridhar, 2005). For instance, Nike has demonstrated with the use of e-recruitment the average time to fill job positions reduced from 62 to 42 days and the recruitment costs reduced by 54% (Pollitt, 2005). From the employees’ perspective, is that it has made the recruitment process a very proactive one—now passive applicants post their resumes online in anticipation of an interview (Mollison, 2001). Further, online recruitment allows applicants the luxury of accessing jobs online at their own convenience 24 hours 7 days a week. It provides the comfort of scrutinizing jobs without physically going through the stress of an interview. Finally, it allows applicants to get a thorough understanding of the organization and its culture before joining the organization (Vinutha, 2005).
BACKGROUND The United States started the global trend of erecruitment when Taylor launched Monster.com in 1994 (Murray, 2001) with 20 clients and 200 job openings (Anonymous, 2007). Monster.com pioneered e-recruitment in the U.S. and today is the leading Internet recruitment portal globally. Monster.com launched the concept of posting and storing resumes online (Mollison, 2001). The name Monster.com was used to suggest “a big idea or a monster idea” (Mollison, 2001) and the company has definitely lived up to its name. The word monster translates well into other languages, an important point, as the company has global operations in 19 countries. On an average,
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the company has about 6 million visitors a month and about 804 of the Fortune 1000 companies use Monster.com as one of their recruitment portals (Mollison, 2001). The beginning of e-recruitment coincided with a business culture that was becoming increasingly global with the introduction of new trade reforms such as the NAFTA and the breaking down of political barriers such as the Berlin Wall (Friedman, 2005). However, it was not just political and economic transitions that lead to the Internet Revolution that we see today. It was the concept of making the Internet accessible to all and sundry that brought e-recruitment to it forefront. A British scientist Tim Berners Lee introduced the World Wide Web to academic scientists in 1991. This was a harbinger to Internet recruiting. Netscape revolutionized the concept of Web browsing by making the Internet accessible “to the public, from five-year olds to eighty-five year olds” (Friedman, 2005, p. 56). The United States was ahead of the game in e-recruitment because of increased Internet penetration compared to other countries even a decade ago (Murray, 2001). The national average for Internet penetration is 59%, with the Pacific states of Washington and Oregon boasting of a high average of 68% (Anonymous, 2003). Further, the US culture promotes sharing work experiences more openly than many other cultures- hence posting resumes on Web sites was not a difficult choice for applicants (Mollison, 2001). E-recruitment can be either in the form of corporate recruiters or third-party recruiters. Corporate recruiters allow potential job applicants to post their resumes directly on their job sites without using any other intermediaries. Statistics reveal that 80% of the world’s Fortune 500 companies use corporate Web sites for recruiting (Epstein & Singh, 2003). Third-party recruiters, such as Monster.com are synonymous with the job advertisement pages of the newspapers identifying thousands of employment vacancies (Epstein et al., 2003). They usually charge employers a fee
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for posting their advertisements for certain duration of time (Tong & Sivanand, 2005). Usually third party recruiters and corporate recruiters collaborate together to provide best recruitment and career solutions to candidates (Mollsion, 2001; Pollit, 2005). The major e-recruitment portals in the U.S. are Monster.com, CareerBuilder.com, and Yahoo® that are growing phenomenally at an average rate of about 32%. Online recruiting seems to flourish with some chronic problems of Corporate America such as employees who are persistently dissatisfied, having a lack of “knowledge” workers, and supervisory workforce. Statistics suggest that a typical American employee has at least eight different jobs between the ages of 18-32 (Anonymous, 2007). The online revolution pioneered by Monster. com in the U.S. in 1994 (Murray, 2001) set the stage for emerging economies like India and Mexico to experience the flattening of the world (Friedman, 2005).
E-RECRUITMENT IN INDIA India has become a very important economic power ever since it liberalized its economy in 1991. Over the past two years, the Indian economy has been growing at about 8% per annum. Economists suggest that it will be the third largest economy in 2040. Today 125 Fortune 500 companies have their R &D centers in India (Zakaria, 2006). However, this phenomenal growth in multinational investment and economic boom has brought its own recruitment challenges in terms of a workforce that is plagued with attrition and is very brand-conscious. For instance, the attrition rate in the IT industry is usually 25-40% (Mitra, 2006). Applicants are job-hopping constantly for better jobs and challenging work in the IT industry that is growing at a phenomenal rate of 30%. Potential applicants usually have two to three job
offers and spend considerable time deciding which best offer they should accept (Smerd, 2006). Organizations are never certain about the employee’s acceptance of the job offer till the employee reports for the first day of work (Grossman, 2006). HR professionals spend about 80% of their time on recruitment (Grossman, 2006). Indian employees have a very strong addiction to brands and would prefer to work for multinationals such as Google™, Microsoft®, or IBM® rather than a top Indian company. This can be attributed to the masculine cultural dimension of being very statusconscious and openly displaying the privileges such increased status brings (Grossman, 2006). With this current economic prosperity, traditional recruitment has become a nightmare (Smerd, 2006). Traditional recruitment, which includes advertising costs, hiring time, and administrative expenses costs 80% more than Internet recruiting in India (Vinuta, 2005). In March 1997, an Indian company, Naukri. com, began its first Internet portal operation with basic HTML operation. At that time India had only 14,000 Internet connections with most of them being only text-only connections. However, today Naukri.com is India’s largest e-recruitment portal with 3.5 million users and 15,000 corporate clients (Srinivasan, Babu, & Sahad, 2005). The main players of the e-recruitment industry in India today are naukri.com, timesjob, careerindia.com, and jobstreet.com (Sridhar, 2005). Job.street is the only “truste certified e- recruitment” site in India. Such a certification ensures absolute privacy about applicant’s employment details (Suryanarayanan, 2001), which is very important in the Indian organizational culture that values qualities such as loyalty and trust (Chokkar et al., 2007).
Challenges of E-Recruitment in India The predominant challenges of e-recruitment in India are the sheer magnitude and size of recruitment. On an average, large companies recruit about 10,000 entry-level positions annu-
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ally (Sachitanand & Sheth, 2007). The process of screening resumes for authenticity and relevance is quite a challenge even for online recruiters as the population of India staggers over a million (Sridhar, 2005; Vinuta, 2005). For instance, India’s leading software company, Infosys, hires almost an average of about 40 entry-level employees a day (Schlosser, 2006). Second, a strange paradox is that though India is widely known as the IT leader of the world (Friedman, 2005), the high disparity in income levels creates a “digital divide” (Curry & Kenney, 2006) where the rich have the benefits of the technological revolution and poor are left behind. Apart from economic costs, poor telecommunications infrastructure and undependable power shortages are the norm for rural villages in India. India’s population of a staggering one billion has only 3.7% Internet penetration with approximately about thirty-seven million Internet users (Lath, 2006). While the big metropolitan cities of Mumbai, Bangalore, Chennai, Delhi, and Hyderabad are very well-connected, Internet connection in inner cities are not to global standards. The low Internet penetration can be a challenge for U.S. multinationals where a laptop at every desk is so ubiquitous (Lath, 2006). However, to bridge this “digital divide” Internet cafés or cyber cafés have been introduced by the government to provide the benefits of the Internet to each and every citizen. Ivan Pope pioneered the concept of Internet café in 1994. This first cafe was introduced in London to enjoy Web-surfing and having something to munch on the side (http://www.encyclocentral.com/684Internet_Cafes.html). In India, such Internet cafes provide a low-cost access to the Internet to people from different economic backgrounds. It also provides opportunities for young people to become entrepreneurial, such as starting a lowcost Internet business (Lancaster, 2003). Third, the Indian culture places a strong emphasis on personal interaction because of their collectivist ties (Chokkar et al., 2007). Collectivist
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cultures are characterized by a very tight social framework where members distinguish themselves from in-groups and out-groups. Therefore employers in Indian companies tend to select employees known to them through social connections, regardless whether employees are qualified for the job (Awasty & Gupta, 2004).
E-RECRUITMENT IN MEXICO Mexico opened it doors to foreign policy when it changed it trade policy from an import-substitution to an export strategy. With the NAFTA opening the doors to increased trade, Mexico has become the 15th largest exporter economy of the world. In the IT sector, the Mexican government is heavily investing in the Information Technology (IT) industry as it realizes that it lags behind several Asian economies in the IT field. The government has announced an incentive program called Prosoft to achieve $5 billion worth of Mexican software by 2013 and also make Mexico a software leader in the Latin American region (Emmond, 2005; Navarrete & Pick, 2002). Initially the government focused on the business triangle of the Federal District, Monterrey, and Guadalajara, but now it extended to provide online facilities to other business areas, such as Tapachula, Cancun, and Tijuana. Infact, Guadalajara is known as the Mexican Silicon Valley (Urteaga-Trani, 2003). Organizations in Mexico are embracing this new digital culture and its impact on human resource practices. Several organizations are adopting e-training and online services for staffing and compensation practices (Emmond, 2005). The origins of Internet in Mexico began in the late 1980s with the universities of ITESM (Instituto Technologico y de Estudios Superiores of Monterrey) and UNAM (Universidad Nacional Autonoma de Mexico) providing email communication between the two universities. As in the US, the engineering departments in Mexico adopted
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Internet usage earlier than other departments in the colleges (Curry et al., 2006). However, since then the Mexican government has taken aggressive initiatives to provide an Internet economy for its people (Emmond, 2005). It is interesting to note that the major online employment Web sites in Mexico are held by non-Mexican firms. The pioneers of online recruitment in Mexico are bumeran.com and laborum. com, both launched around 1999. Bumeran has its corporate office in Argentina while Laborum has its corporate office in Chile (Anonymous, 2001; Fitzgerald & Liburt, 1999; Peterson, 2000). Scholars suggest barriers in Mexico such as high business costs, complicated ownership laws for new firms, and a lack of capitalist culture prompts non-Mexicans to dominate the e-commerce business (Curry, Contreras, & Kenney, 2001).
Challenges of E-Recruitment in Mexico The predominant challenges are that there is a “digital divide” or “digital inequality,” just like as in India (Curry et al., 2006; Olivas-Luján, Ramírez, & Zapatu-Cantu, 2007). There is a stark distinction between those who can afford access to the Internet and those who cannot. Such digital disparity is widely prevalent because of poor telecommunications infrastructure, very distinct economic classes of the rich and poor, and also high costs associated with Internet usage. To overcome such digital disparity, the government has introduced the concept of Internet cafes in Mexico. Internet usage at these cafes is very affordable and cost an average about 8 pesos an hour (Curry et al., 2006). On an average, about 37% of the households in Mexico have Internet access (Anonymous, 2005), while in the corporate world only 28.6% firms have Internet connection while 71.4% do not have Internet access (OlivasLuján et al., 2007). U.S. multinationals have to be cognizant that in emerging economies Internet
connectivity is still a challenge (Olivas-Luján et al., 2007). The second challenge for e-recruitment in the Mexican culture is employees fear loss of confidentiality in submitting their resumes to the Internet (Mejias, 2000). Loyalty is a very important cultural trait (Davila & Elvira, 2005) and applicants fear their employers (bosses) might see their resumes online (Mejias, 2000). Finally, several online fraud activities, such as credit card transactions, have made Mexican cautious of the credibility of Internet communications (Peterson, 2000). Further, the Mexican culture (Davila et al., 2005; Olivas-Luján et al., 2007) strongly relies on personal relationships and networking due to cultural dimensions of collectivism and uncertainty-avoidance. Mexicans feel intimidated by recruitment practices that do not allow them to get to know the applicants personally. In a case study of four Mexican companies, the HR departments reported a sense of alienation with the applicants with the use of e-recruitment (Olivas-Luján et al., 2007). An observation by Laborum.com, the online recruitment company, was that Mexico had the lowest number of online applicants (80) compared to Argentina which had the highest (150), emphasizing the significance of personal interactions in the Mexican recruitment culture. Further it was also observed that online recruitment is hardly done at the upper-managerial level in Latin American countries, where trust and loyalty dictate hiring practices (Anonymous, 2001). However, in contrast, Rao (2005) identified, in a recent study in US-Mexican joint ventures, Internet recruiting was ranked as the third most important method (35%) in recruiting executive candidates. Multinationals are also known to transcend local human resource practices (Friedman, 2005).The increased presence of multinationals (Urteaga-Trani, 2003) has put a premium of getting quality executive talent worldwide.
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FUTURE TRENDS Internet recruiting will definitely continue to play a very prominent role as the world becomes more digitized. Multinationals are going to rely increasingly on this method of recruitment as it proven to bring high-caliber worldwide talent to your doorstep. Diverse applicants from New Delhi to Nairobi to New York can be leveraged across to provide organizations with best solutions and therefore a sustainable completive advantage (Epstein et al., 2003). Emerging economies will be major business players in tomorrow’s corporate world (Friedman, 2005).
CONCLUSION E-recruitment has proven definite advantages to the recruitment process such as specifically reducing cost and having a shorter time in hiring applicants. Internet recruiting will to play a huge role in the global war for talent seeking cognitive diversity from every corner of this world. The world is becoming flat with the digital revolution of laptops, ipods, and flash drives (Friedman, 2005). While economies like India and Mexico will strive to be at the top of this race with multinationals seeking global opportunities, multinational companies should be cognizant of economic and cultural pitfalls for this method of recruitment in emerging economies like India and Mexico.
REFERENCES Anonymous,. (2001). Headhunters hit by slowdown. Country Monitor, 9(22), 5. Anonymous,. (2003). Internet penetration mainly a coastal thing. Chain Store Age, 79(10), 80. Anonymous,. (2007). The coming crisis in employee turnover. Growth Strategies, 1004, 1–3.
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Anonymous. (2007). Career crisis: Monster. com has choices to make as it approaches “Middle Age.” Retrieved October, 15, 2007, from http://knowledge.wharton.upenn.edu/article. cfm?articleid=1817 Awasty, R., & Gupta, R. (2004). An Indo-Japanese MNC operating in India. South Asian Journal of Management, 11(3), 94–113. Chokkar, J., Brodbeck, F., & House, R. (2007). Culture and leadership across the world. The GLOBE book of in-depth studies of 25 societies. Mahwah, NJ: Lawrence Erlbaum Associates. Curry, J., Contreras, O., & Kenney, M. (2001). The Internet and e-commerce development in Mexico. Working Paper 144. The Berkely Roundtable on the International Economy. Curry, J., & Kenney, M. (2006). Digital divide or digital development? The Internet in Mexico. First Monday, 11(3), 1–21. Davila, A., & Elvira, M. (2005). Culture and human resources management. In M. Elvira & A. Davila (Eds.), Managing human resources in Latin America: An agenda for international leaders. London: Routledge Emmond, K. (2005). Investing in IT. Business Mexico, 15(5), 22–28. Epstein, R., & Singh, G. (2003). Internet recruiting effectiveness: Evidence from a biomedical device firm. International Journal of Human Resources Development and Management, 3(3), 216–225. doi:10.1504/IJHRDM.2003.003662 Feldman, D., & Klass, B. (2002). Internet job hunting: A field study of applicant experiences with on-line recruiting. Human Resource Management, 41(2), 175. doi:10.1002/hrm.10030 Fitzgerald, M., & Liburt, E. (1999). Spanishlanguage job site launches. Editor & Publisher, 132(48), 3.
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Friedman, T. (2005). The world is flat. New York: Farrar, Straus, and Giroux. Galanaki, E. (2002). The decision to recruit online. Career Development International, 7(4), 243–250. doi:10.1108/13620430210431325 Grossman, R. (2006). HR’s rising star in India. HRMagazine, 51(9), 46–53. Jasrotia, P. (2001). E-recruitment market registers major growth. Express Computer. Retrieved October, 15, 2007, from http://www.itpeopleindia. com/20011008/cover1.htm Lancaster, J. (2003, October 12). Village Kiosks Bridge India’s Digital Divide. Washington Post, AO1. Lath, S. (2006). The battle of two portals: Yahoo and MSN are getting ready to fight it out in the Indian market, which may still be small but promises a lot. Business Today, 128. Mitra, K. (2006). The new dotcom millionaire. Business Today, 124. Mollison, C. (2001). The Internet world interview. Internet World Magazine. Retrieved October, 15, 2007, from http://www.iw.com/magazine.php?in c=050101/05.01.01interview.html Murray, S. (2001). From tiny job boards into mighty career networks. A brief history of online recruitment. Financial Times, 04. Navarrete, C., & Pick, J. (2002). Information technology expenditure and industry performance: The case of the Mexican Banking Industry. Journal of Global Information Technology Management, 5(2), 7–29. Olivas-Luján, M., Ramírez, J., & Zapata-Cantu, L. (2007). E-HRM in Mexico: Adapting innovativeness for global competitiveness. International Journal of Manpower, 28(5), 418–434. doi:10.1108/01437720710778402
Peterson, A. (2000). Opening a portal: E-Commerce apostle target Latin America. Wall Street Journal (Eastern Edition), A1. Pollitt, D. (2005). E-recruitment gets the Nike tick of approval. Human Resource Management International Digest, 13(2), 33–36. doi:10.1108/09670730510586995 Rao, P. (2005). Executive recruitment practices in US-Mexican joint ventures. Doctoral Dissertation. Proquest International. Schlosser, J. (2006). Infosys. Fortune, 153(5), 41–43. Singh, A. (2005). The e jobs dust-up. Even as they fight each other, online recruitment biggies Naukri and MonsterIndia are going after their print rivals. At stake: A market that could be worth over Rs 1,000 crore by 2008. Business Today, 110. Smerd, J. (2006). Indian firms tap benefits, brand in talent battle. Workforce Management, 85(4), 6–8. Sridhar, B. (2005). E-recruitment, the right way. The Hindu. Retrieved October, 15, 2007, from http://www.hinduonnet.com/ jobs/0503/2005030900350600.htm Srinivasan, P., Babu, V., & Sahad, P. (2005). Durable dotcoms. Business Today, 60. Suryanarayanan, M. (2001). A guide to better positions and better performance. The Hindu. Retrieved October, 15, 2007, from http://www. hinduonnet.com/jobs/0105/05230014.htm Taylor, J. (2003). Decisions. Jeff Taylor founder and chairman, Monster. Management Today, 26. Tong, D., & Sivanand, C. (2005). E-recruitment service providers review. International and Malaysian. Employee Relations, 27(1/2), 103–118. doi:10.1108/01425450510569337
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Vinuta, V. (2005). E-recruitment is here to stay. Express Online Computer. Retrieved October, 15, 2007, from http://www.expresscomputeronline. com/20050418/technologylife01.shtml Zakaria, F. (2006). India Rising. Newsweek, CXLVII(10), 34-43.
KEY TERMS AND DEFINITIONS Bulletin Boards: An electronic message center. Digital Divide: A split between people who have access to the Internet and people who do not have access to the Internet due to economical and technological reasons.
E-HRM: This is a method of implementing HR strategies, policies, and practices in organizations with the direct support of webWeb-technology. E-Recruitment: The complete automation of the recruitment process. Internet Café or Cyber Café: A public place where people can use a computer and internetInternet facility by paying fees for the services. Naukri.com: An employment webWebsite in India that means “job” in the Indian language, Hindi. Recruiting Portals: Internet recruiting organizations that provide links to jobs and corporate webWeb sites. Recruitment: The process of generating a pool of qualified applicants for organizational jobs. Selection: The process of choosing the most qualified individuals from the pool of qualified applicants.
This work was previously published in Encyclopedia of Human Resources Information Systems: Challenges in e-HRM, edited by Teresa Torres-Coronas and Mario Arias-Oliva, pp. 357-362, copyright 2009 by Information Science Reference (an imprint of IGI Global).
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Chapter 3.7
E-Logistics:
The Slowly Evolving Platform Undrepinning E-Business Kim Hassall University of Melbourne, Australia
INTRODUCTION By 1998, arguably some four years after the Internet’s general user beginnings, many commentators did not doubt that Internet based home shopping was on its way to revolutionize our lives. At the margin, it certainly allowed us another purchasing channel and for many retailers some 5% to 12% of differing goods is now done through an “e-store” or “e-marketplace”. (Visser & Hassall, 2005). However, by 2001 a range of major e-business summits, perhaps very notable being the 44 nation OECD hosted e-transport and e-logistics summit DOI: 10.4018/978-1-60960-587-2.ch307
in Paris (June, 2001), was beginning to demolish the euphoria of B2C. In its basic state, B2C was a very marginal business. But what of B2B? Yes, it is a bigger sector but how were the business rules and logistics strategies shaping up for network design, e-marketplace use, and logistic fulfilment changing when compared to the rapidly evolving B2C environment? The ICT sector rapidly began to assemble a host of B2B applications for Supply Chain Management and despite the “tech wreck” occurring towards the end of 2001, these highly expensive suites of products found some traction over the next three to four years. So, initially, the development of large logistics software packages such as I2, Baan, Descartes, and so forth, were
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offerings that the B2B sectors availed themselves of. However, besides the ICT developments in the B2B space, the evolution of new logistics strategies would prove themselves to be good, bad, and various shades in between, when examining the full end to end (E2E) e-business operations. Since 2001, a tide of interest has turned towards the adoption of fit for purpose e-logistic models to support the end to end functionality of e-business. Hassall (2003) describes a detailed survey for the international Postal Authorities as to what new e-logistics and e-business strategies should be developed. These ranged from new householder delivery choices, to global e-marketplaces being developed. Why this survey was important was because the global postal authorities are the largest combined B2C operator and also a growing B2B logistics supplier.
The Tools of E-Logistics The staple of the world’s logistics is activated by orders generated by the use of the phone and the fax machine. This is true for small/medium enterprises (SMEs), small office/home office (SOHOs) and Medium Enterprises (MEs) involved in B2C, b2b (small business to small business) or b2B (small business to large business). In many ways it will be the customer requirements that eventually force the smaller enterprises into adopting the use of further enhanced Web based products so that the information flow and reporting of their product orders or dispatches can feed customer or client information systems. B2B logistic contracts will often have a predefined set of software systems in place for reporting, monitoring, and accounting. Usually these will be more expensive than the suite of systems that the SMEs, SOHOs, and so forth, will have at their disposal. The above list of e-logistic options is a list of capabilities that either the customer may require, or the logistics supplier offers. It would be quite unusual for many major 3PLs (Third Party Logistic Providers) to supply all of these capabilities un-
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less directed to, usually by the decree of a major client. However, a subset of these strategies ought to be examined by the supplier or the e-logistics provider fulfilling the service.
The Evolution in B2C Logistics The evolution of B2C from the Christmas mishaps in 1999 to now has been to achieve a cheap and successful delivery by the delivery agent. This statement is true but another dimension to the home delivery is trying to minimize the problems associated with product returns, and products being taken back to the delivery depot. That is, home delivery is also aware of the problems of “reverse logistics,” which range from 2% returns for household chemicals to 50% returns for magazines. (Bayles, 2001). Reverse logistics is a large cost burden and, in fact, integral to the physical and environmental cost of the B2C operation. (Sarkis, Meade, & Talluri, 2004). Generally, the full planning and operational capability required for reverse logistics has even spawned several specialist providers in this area. (Poirier & Bauer, 2001). However, is a better way to minimize the reverse logistic operations to have the customer pick up the item? This may minimize some aspects of reverse logistics, but it may not be a winner in the area of customer satisfaction. Certainly delivering to a retail agent is a large cost benefit for the delivery agent. One drop of a hundred parcels to a retail agent is a lot cheaper than attempting delivery to one hundred households. But perhaps the delivery dump at the retail partner is not the choicest alternative for the majority of customers. New strategies outlined in Table 1 are, for example, the electronic home parcel box (Number 2) which is just progressing beyond the R&D stage. In Europe this method of delivery is being discussed in regard to new planning regulations and this strategy may be a significant strategy within ten years. One way retailers are experimenting with loading for household delivery is directly out of their normal retail premises, not from a distribution
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centre. This Strategy (Number 8) is employed by such retailers as Tesco. This strategy may negate the need for a separate loading centre but what happens when 100 commercial vehicles arrive to load at the same time slot? Answer: Severe queuing and a valuable loss of time for the delivery agents. However, for a wholesaler with a diverse enough range of products, an entire retail operation could, in theory, be by-passed in a home shopping environment. The wholesaler takes orders, picks the orders from a central warehouse, then undertakes the delivery of these orders directly to households from the warehouse. The benefits to customers could see a substitute to a retail price which would be now made up of a wholesale price, plus a transport cost, and a small margin. This could be cheaper than the retail purchase price. Many major retailers, however, offer both services to span both the customer shopping and home delivery requirements.
Customer Fit in the New B2C Pairwise Strategy Models Some of these new strategies, listed in Table 2, are geared towards a high degree of cost minimi-
zation for the delivery operator. This inherently may not be a bad thing, however, where does the customer rate in the strategy? More importantly, customer response surveys may indicate exactly what proportion of the customers are happy and unhappy with the offered delivery strategies. If the surveyed service response rating exceeds 85% or 90%, then that one strategy may be worth keeping for that delivery agent for that class of home-shopping products. One survey conducted in 1998 (Hassall, 2000) suggested that about 12% of electronic order forms allowed for alternative delivery instructions. Limiting alternative delivery strategies will hardly reflect a high level of customer satisfaction. However, allowing a limited set of delivery options may add significantly to the home shoppers’ level of satisfaction. Figure 1 suggests that the combination of “hypothetical generic pairs” of strategies will give at least an equivalent level of cumulative satisfaction. Seven pairs of strategies are hypothetically displayed. For any particular retailer and delivery agent it is a matter of examining what pairwise options are feasible and customer friendly. It may only be that two single and two pairwise options are feasible. Perhaps even one direct hop strategy
Table 1. The tools for e-logistics €€€€€E-logistics Tool €€€€€e-ordering
€€€€€Description Via Web, e-market, auction, collaborative system, etc.
€€€€€€EDI Requirements
Optional – dependent on contract requirement
€€€€€Activated order/Shipment number
Usually an imperative requirement. Various Generators
€€€€€Activation of Logistics services €€€€€-order/pick/pack €€€€€-despatch €€€€€-transport, etc.
Activation of a specific set or single operation from warehouse, transport operator, delivery agent etc through shipper, broker, customs agent, and/or sub-contractor or own fleet
€€€€€Barcode or RFID scan
Optional – dependent on requirement
€€€€€Track and Trace capability
Optional – dependent on requirement
€€€€€Call Centre CRM ability
Optional – dependent on requirement
€€€€€Automatic Logistic Performance calculator
A rare but powerful tool. Can save many hours per week in evaluating if functionality is available.
€€€€€Client Accounting
Commonly an e-market and portal offering,
€€€€€Quarterly reporting
Specified financials/service performance or customers, etc.
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Table 2. B2C householder delivery strategies 13 STRATEGIES for Household delivery 1. Attempt 1st delivery, phone follow up for 2nd attempt. 2. Attempt delivery to a home parcel box. 3. Attempt home delivery, failure redirected to retail agent for customer pick up. 4. Continual household attempt at delivery. 5. Customer pick up from retail key-hole or kiosk site. 6. Customer pick up from secure depot storage or common parcel box. 7. Delivery agent to retail agent by direct drop. 8. Delivery agents loads orders direct from retail site not a specialized distribution hub. 9. Delivery to public provider parcel delivery box. 10. Initial delivery to preferred post office of choice. 11. Optional flexible delivery strategies as stated on the customer order form. 12. Phone booking for initial delivery slot. 13. Slotted after hours delivery. (Source: Hassall, 2002, revised.)
and one pairwise strategy is feasible for the particular commodity purchased, but it is certainly part of the operation that the retailer is aware of the customers’ highest preferences for the particular delivery options either offered or not offered. For example, the delivery of backyard furniture may very much limit the feasibility of
selecting from at most a small number of the 13 options listed in Table 2. Why are pairwise delivery strategies important? As stated above pairwise strategies can reflect higher levels of customer satisfaction, but also they can be used to lower the marginal delivery cost of a single strategy. Another benefit for pairwise delivery strategies is that they can add a considerable level of security for particular commodities. For example, a business consultant takes advantage of a discount sale on a new desktop computer model. Instructions are to attempt after hours home delivery on a particular evening. If a computer agent sent the computer to the domestic householder upon nobody at home it will be returned to a safe storage site for customer pickup. For small items, a return to a local 24-hour convenience retail agent, or to a retail agent near a day office may be an alternative. However, boxed computers are not a small item, they are valuable as well, and a small retail agent may not wish to store such a large single cubic consignment. This pairwise strategy, therefore, is performed at smaller cost than attempting second delivery, or telephoning to arrange a second delivery. One recent international survey of B2C delivery strategies across 16 countries suggested that the offering of a diversity of delivery options was
Figure 1. Pairwise home delivery strategies and satisfaction ratings
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the second most important strategic issue facing incumbent B2C operators (Hassall, 2003). Reynolds (2004) describes six e-fulfilment models, however, when compared to Table 2, these are somewhat more macro in their descriptions.
B2B Fulfillment and the Appropriate E-Logistic Solutions B2B is simple in concept but the sub-classifications of B2B are quite large. Many B2B transactions do not generate freight per se and this is why generally e-logistics is far more relevant to e-business generating physical product. At the OECD/ECMT e-transport and elogistics Summit (Paris, 2001), Nemoto, Visser, & Yoshimoto (2001) described B2B as “too big” a concept for the logistical requirements of B2B. Instead classifications such a G=Government, S=Shippers, L=Logistics Operators should be subsets of the B2B space. The only classification to have become recognized in its own rite is the Governmental category G. In fact the e-business of Government has become a specialist study area in its own rite. Figure 2. The proposed expanded B2B and B2C environments
The logistic fulfilment for B2B is most often performed as a well defined set of pre-arranged business rules that are implemented between the customer and the 3PL or fulfilment agent. That is, the software requirements, service performance level, reporting levels, and invoicing are all covered by contractual arrangements. Enterprise Requirements Planning systems have been designed for the B2B space (Reynolds, 2001) but many are exceedingly costly. It will be interesting as to whether smaller “best of breed” technologies will replace these mega ERP systems that were being developed some five years ago. This is especially true as the requirement for many e-logistic applications such as Radio Frequency Identification (RFID), Track and Trace, Barcode reading, vehicle routing optimization and fleet management were often not part of these mega systems. In fact, the build to scale E2E (end–to-end) solutions, or assembly of a suite of smaller “best of breed” solutions for MEs (Medium Enterprises), will be an attractive applications business space over the next five years for logistics operators to buy from. Figure 3 depicts the several of the dozen or more end-to-end logistics and supply chain functions that can be streamlined through either individual or aggregated Web based e-logistic applications and platforms, through which e-business can be supported and fulfilled.
E-Logistics: Is it all about Visibility, Validation, and Verification? The New Question What makes the difference between traditional logistics and e-logistics? This is a crucial question which may be better understood from examining the several definitions of e-logistics. Current definitions refer to logistics support for Web ordering. However, it may be suggested that true “e-logistics” operations are generated from Web based/electronic applications that are activated by the order, guided through the process stages until fulfilment, invoic-
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Figure 3. Potential operational components of e-logistics
ing, payment, and reporting occurs. If one or more electronic logistic tools are invoked across the order to delivery, then there are the three properties of visibility, validation, and verification that can be seen as the electronic “value adds” for the e-logistics chain as opposed to the “phone/fax” orders and delivery used by traditional logistics. In fact the property of Visibility is the most significant difference between e-logistics and traditional logistics, at least according to this author.
What Does the Crystal Ball Hold? Around June 2001, somewhat coincidentally, when the OECD hosted a 44 country summit on “e-transport and e-logistics”, a wave of reality was emerging such that the business models for the fulfilment of e-business had to be rethought. E-stores and e-markets were proving that they were not very “logistics savvy.” The area of Business to Consumer (B2C) was very much a high focal point and is arguably still, in France, the Netherlands, Germany, Italy, and many other European countries. B2C was “doing it tough with very low, or negative, profit margins” even though over a dozen fulfilment strategies had evolved in the B2C space. The bigger Business to Business
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(B2B) brother, although it was seen as being several factors larger in volume and value than B2C operations, when viewed from an e-logistics perspective, it was somewhat harder to enunciate the generalised logistics activities. However, B2B in one perspective looks after itself. If the customer requires specific levels of service, reporting, software collaboration, and so forth, then the logistics supplier has a choice, either develop, or link into the capability, or risk losing the contract. The customer needs also to be aware what, specifically, the logistical services from a third party, or own fulfilment divisions, involve, and at what cost they can be provided. Many B2B relationships may just be coming to grips with a few of the available e-logistic tools and how to both price and leverage off their use. However, many major B2B relationships are still totally supported phone and facsimile machines. It is more than possible that the future evolution of very cheap public domain software for planning, routing, reporting, and for performing even “track and trace” through various mechanisms, will encourage not only the Medium Enterprise (ME) logistics operators, but even quite large 3PLs, the opportunity to offer a much larger suite of e-logistic functionality to their clients at very cheap prices.
E-Logistics
CONCLUSION The absolute difference between e-logistics and traditional logistics is the electronic “visibility” of particular steps in the chain, from order to confirmation of delivery and onward to invoice payment. The electronic logistic audit trail also lends itself to “verification and validation” of orders, pick pack instructions, standards of delivery services, and any alternative delivery instructions. In fact, the full range of services taken up in the e-logistics chain can be a very powerful input activity subset into the Activity Based Costing models (ABC) for that particular chain. This also assists what many logistic companies, B2C or B2B, are not fully cogniscent of, and that is their full attributable activity-based chain costs. A comprehensive knowledge of impact of these operationally based costs can very much make the difference between profit and failure. This difference between traditional and elogistics has not been widely examined in any a more meaningful way than by suggesting that e-logistics “may” be highly Web and applications enabled, unlike traditional logistics. But traditional logistics offerings that might only depend on the phone and facsimile machine may also be supported by very good databases, service response teams, and accounting and business systems. These systems may be very functional and successful. The differences between the streams of e-logistics and traditional logistics, is a fertile ground for future research which should also canvass the opinions of the actual logistic and transport operators.
REFERENCES Bayles, D. L. (2001). E-Commerce Logistics & Fulfillment, Prentice Hall PTR, New Jersey.
Hassall, K. (2001a). Trends and Hindrances in elogistics: An Australian Perspective. Proceeding of the OECD conference on e-Transport, Paris, 2001. Hassall, K. (2001b). The Evolution of B2C. [Publishing Services Australia, Brisbane.]. Supply Chain Review, 10(4), 42–50. Hassall, K. (2003). The E-Logistics Challenge for the Post Office: A Phoenix egg or an Ostrich Egg? Universal Postal Union (United Nations), Postal Technology Branch, Bern. http://www.ethematic.org/download/The%20e-Logistics%20 Challenge%20for%20the%20Post%20Office.pdf Hassall, K. (2005). Smart Supply Chain Conference, Technical Seminars, Sydney. (presentation) http://www.smartsupplychain.com.au/seminars. cfm Nemoto, T., Visser, J., & Yoshimoto, Y. (2001). Impacts of Information and Communication Technology on Urban Logistics Systems. Proceedings of the OECD Summit on e-Transport and e-Logistics, OECD. Paris 2001. Http://www1. oecd.org/cem/online/ecom01/Nemoto.pdf Poirier, C. C., & Bauer, M. J. (2001). E-Supply Chain. Berrett-Koehler Publishers Inc., San Francisco. Reynolds, J. (2001). Logistics and Fulfillment for e-Business. CMP Books, New York. Reynolds, J. (2004). The Complete E-Commerce Book, 2nd Edition, CMP Books, New York. Rowlands, P. (Ed.). (2000). E-logistics: Magazine. Spice Court Publications. Sarkis, J., Meade, L. M., & Talluri, S. (2004). E-logistics and the Natural Environment. Supply Chain Management. [Emerald Group Publishing Limited.]. International Journal (Toronto, Ont.), 9(4), 303–312.
Hassall, K. (2000). The B2C revolution. [Publishing Services Australia, Brisbane.]. Supply Chain Review, 9(4), 41–44. 649
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Visser, J., & Hassall, K. (2005). The Future of City Logistics: Estimating the Demand for Home Delivery in Urban Areas. Proceedings of the 4th City Logistics Conference Langkawi: Kyoto University. www.elogmag.com www.fulfilmentonline.ac.uk
KEY TERMS AND DEFINITIONS 3PL (IIIPL): Third party logistics provider. A diversified provider of logistics services that may include: warehousing, freight forwarding, longhaul and shorthaul transport, storage, inventory management, returns, tracking, performance monitoring, selected documentation, and so forth. Electronic Data Interchange (EDI): Computer to computer interchange between two or more companies so such entities can enter a range of standard forms such as purchase orders, bills of lading, invoices, forward orders, stock replenishment, and so forth. E-Logistics: The following definitions are variations on the theme that e-logistics utilises Web based tools in the support of e-business. Some definitions are fuller than others. The timing in the emergence of these definitions is also relevant. 1. Finnish (translation), E-logistics can be defined as the application of Internet based technologies to traditional logistics processes.2. German: (Translation) E-Logistics, Web based applications and services dealing with the efficient transport, distribution, and storage of products along the supply and demand chain.3. French: (Translation): E-Logistics A collection of the new logistic management practices for the Internet.4. Forbes, “E-logistics” describes three core backend processes required to get an order from the
“buy” button to the bottom line: warehousing, delivery, and transportation, and customer interaction (usually handled through a call center where customers can ask questions, place orders, check on order status, and arrange for returns). In many cases, a different vendor handles each of these three separate functions. Managing them all successfully and simultaneously requires an indepth understanding of each discipline. Integrating them with one another and with a corporation’s existing systems is even tougher. Source: www. forbes.com/specialsections/elogistics.5. “The electronic activation of a set of physical logistic activities with associated electronic information flows that support e-Business.” (Hassall, 2005) (presentation) http://www.smartsupplychain.com. au/seminars.cfm. ICT: Information and Communication Technology. IV PL (4PLTM): Fourth Party Logistics Provider. The operation of end-to-end coordination and management of a logistics chain by direction to 3PL operators and often including the use of large scale IT systems that drive management, reporting, and scheduling activities. IV PL operators need not operate any 3PL activities themselves. Radio Frequency Identification: Active or passive tag or print based “label” that can be preprogrammed with specific data input fields. These fields emit data from active tags or can reflect embedded data for inactive tags when pulsed with specific electronic signals. Reverse Logistics: The process of collecting, moving, storing used, damaged, or outdated products and/or packaging from end users. Tecso Model: Strategy for replenishment of grocery orders for delivery from existing supermarket stores rather than from a specialized, non retain pick/pack urban depots. Used by Tesco stores.
This work was previously published in Encyclopedia of Information Science and Technology, Second Edition, edited by Mehdi Khosrow-Pour, pp. 1354-1360, copyright 2009 by Information Science Reference (an imprint of IGI Global). 650
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Chapter 3.8
E-Business Perspectives through Social Networks Mahesh Raisinghani Texas Women’s University, USA Elon Marques University of Dallas, USA
ABSTRACT This chapter is focused on some of the current research being conducted in the field of social network theory. The importance of studying the social network concepts is attached to a better understanding of individuals and how and why people interact with each other, as well as how technology and the Internet can affect this interaction. The social network theory field has grown significantly in the last years, and the use of the Internet and advanced computing technology has contributed to new research in this growing
area. The first aspect to be covered is the social network theory and some applications for social networks. Also virtual communities, as well as the control over communications tools through social networks will be discussed. Finally, the technology side of social networks will be presented, as mobile social networks, internet social networking systems and e-business correlation, social network software and future trends of social networks. The main objective of this research is to illustrate the correlation between electronic (e-) business (of which e-government is a subset) and social networking.
DOI: 10.4018/978-1-60960-587-2.ch308
Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
E-Business Perspectives through Social Networks
INTRODUCTION: SOCIAL NETWORK THEORY A network is a set of objects or nodes mapped according to the relationship between these objects. For social networks, the objects refer to people or groups of people. A social network is a map representing the relationships among individuals, indicating the ways in which they are connected according to their social familiarities. The networks of communication and interpersonal relationships that develop naturally within an organization form channels for the flow of organizational knowledge and can promote organizational learning, innovation and change management (Smith and McKeen, 2007). According to the Organization for Economic Co-operation and Development (OECD, 2008a), broadband plays a critical role in the workings of the economy and society. It connects consumers, businesses, and governments and facilitates social interaction. Hence, broadband policies are now a vital instrument to ensure the competitiveness of OECD countries and to address pressing societal concerns. The following OECD broadband statistics serve as a rationale for examining Internet based social networks and e-government readiness (OECD, 2008b): The United States is the largest broadband market in the OECD with 75 million subscribers. US broadband subscribers consistently represent 30% of all broadband connections in the OECD. The number of broadband subscribers in the OECD reached 251 million by June 2008, an increase of 14% from June 2007. This growth increased broadband penetration rates to 21.3 subscriptions per 100 inhabitants, up from 20% in December 2007. Denmark, the Netherlands, Norway, Switzerland, Iceland, Sweden, Korea and Finland lead the OECD with broadband penetration well above the OECD average, each surpassing the 30 subscribers per 100 inhabitants threshold.
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The strongest per-capita subscriber growth over the year was in Luxembourg and Germany. Each country added more than 5 subscribers per 100 inhabitants during the past year. On average, the OECD area increased 2.7 subscribers per 100 inhabitants over the year.
Table 1 illustrates the developments in egovernment from1996-2008 versus 2008-2020. Social networks operate at many levels, such as youth, families, students, organizations, and are represented by some small groups of people, as well as by entire nations. Their importance varies with problem solving scenarios, achievement of individual success and the way organizations run. Internet social networks is a category of the social network field in which individuals through a variety of internet application tools connect to other individuals, group of friends and business partners. [Wikipedia, 2005a].
BACKGROUND According to the social network theory social relationships are mapped by nodes and ties. Nodes are the individuals who act within the network and ties are the relationship between the individuals. In a network diagram the nodes are displayed as points and ties as lines, linking the nodes. Two nodes in the network are connected if they are directly linked to each other, or interact in some way. For instance, in the network from Figure 1, there is a connection between mikedinner and Bijan and between Mike-dinner and Ronwalf, but no direct connection exists between Ronwalf and Bijan. Analyzing the shape of the network helps to determine the network’s usefulness to its individuals. The network shape illustrated in Figure 1 shows the distinction between the three most popular individual network measures: Degree Centrality,
E-Business Perspectives through Social Networks
Table 1. 1996
2008
2020
Infrastructure
€€€€€• Secure private networks (SWIFT) €€€€€• BitNet €€€€€• Infancy of the www
€€€€€• Convergence €€€€€• Mobile/ubiquitous internet €€€€€• Broadband €€€€€• Digital divide issues remain
€€€€€• Ubiquitous broadband ? €€€€€• Commoditized network ?
Information exchange
€€€€€• EDI €€€€€• ‘unsecured’ packet switching
€€€€€• Web-based secured (https) €€€€€• Open networks €€€€€• Web 2.0 ?
€€€€€• Two-tier internet ? €€€€€(security, pricing)
E-government purposes
€€€€€• Public spending €€€€€• Shared data bases
€€€€€• Public spending €€€€€• Public sector reform €€€€€• Better government €€€€€• Governance €€€€€• Economic development
€€€€€• Public spending €€€€€• Local vs central govt €€€€€• Socio-economic efficiency €€€€€• The death of e-govt ?
E-government drivers
€€€€€• Public sector €€€€€• IT departments €€€€€• Finance/accounting
€€€€€• Public sector (+ PPPs) €€€€€• Reform/change agents €€€€€• Government as a whole €€€€€• Local governments
€€€€€• Mostly PPPs and ‘franchise’ models €€€€€• Internationalized €€€€€• Localized
E-government concerns
€€€€€• Security €€€€€• Sharing of info resources and equipment
€€€€€• Security/privacy €€€€€• Institutions/enterprise architecture €€€€€• Standards/interoperability €€€€€• ROI
€€€€€• Security/privacy €€€€€• Innovation/change mangt €€€€€• Transparency/Governance €€€€€• Democracy/empowerment €€€€€• Democracy/empowerment €€€€€• Inclusion (worldwide) €€€€€• Skills (worldwide)
Adopted from: http://www.oecd.org/dataoecd/42/57/40304889.pdf, e-leaders conference 2008 The Hague -6-7 March 2008, Where is egovernment going in 2020?, Bruno Lanvin, eLab, INSEAD
Betweenness Centrality, and Closeness Centrality as will be discussed next (Orgnet, 2005). Degree Centrality is the measurement of the network activity using the concept of degree, or the number of direct connections a node has to other nodes. In figure 1 the nodes represented by Golbeck and Ronwalf have the most direct connections in the network, making them the most active nodes. They are called the ‘connectors’ or ‘hubs’. A common impression of networks is the more connections, the better. This assumption is not true and what really matters is where the connections lead and how they connect nodes which are otherwise unconnected. Betweenness Centrality has great influence on the flows of the network. According to the network from Figure 1, while Ronwalf has many direct ties, Mike-dinner has few direct connections, even fewer than the average in the network. However, Mike-dinner has one of the best locations
Figure 1. Social network diagram [Adopted from PieSpy, 2005]
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or highest betweenness centrality in the network because he is between two important constituencies. Mike-dinner plays an important role in the network, linking clusters of nodes, and also he is a point of failure because without him, Mhgrove and Bijan would be cut off from information and knowledge from Ronwalf’s cluster. Closeness Centrality measures the best visibility into what is happening in the network. Jordan has fewer connections than Golbeck, however the pattern of his direct and indirect ties allows him to access all the nodes in the network faster than anyone else. Jordan’s high closeness centrality gives him the shortest path to all other nodes and he is in an excellent position to monitor the information flow in the network. Many studies have been done about social networks and are being applied to many different fields (e.g., Acquaah, 2007; Christ et al., 2007; Golbeck and Hendler, 2006; Ioannides and Soetevent, 2007). The volume of researchers has considerably increased in this area and many corporations are realizing the importance of social networks as a powerful marketing tool and a strong way of communication between people and within corporations.
Applications of Social Network Theory The evaluation of the social capital of an individual connected on a social network to other individuals is an application of the Social Network theory. Social capital refers to the position of the node in the network and this member can draw resources contained by other members of the network. According to the French sociologist Pierre Bourdieu in “The Forms of Capital” (1986), there are three forms of capital: economic capital, cultural capital and social capital. He defines social capital as “the aggregate of the actual or potential resources which are linked to possession of a durable network of more or less institutionalized relation-
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ships of mutual acquaintance and recognition.” (Wikipedia, 2005b) Social capital has a considerable influence on a person’s life, and can affect aspects such as job searches, potential for promotions, knowledge in general, channels of consumption and public opinion. The more mappings a person has, the more social resources his contacts can be extended to, and the more influence, knowledge and power the original person will control [Ethier, 2005]. Social network theory also has an important role in the social sciences. Sociometry is one of the methods of socio-psychology developed by the psychiatrist Jacob Levi Moreno and analyzes the interpersonal emotive relationships within groups. His methods can be used to identify informal leaders, social rankings and isolated individuals [Adit Software, 2005].
Virtual Communities on the Internet People wonder whether communities will persist in these stressful modern times, in a society of loneliness where people walk or drive by themselves. News about terrorist attacks and violence are guiding humanity to fear these patterns of isolation. Communities have existed throughout history and cooperation among individuals has always been fundamental for human evolution. In some way, individuals are always seeking communities in order to escape loneliness. Despite this universal behavior, the same people think that they are exceptions and that all the individuals around them are isolated and lonely. [Wellman, 2005] Virtual communities are groups of people or nodes on the network that come together through the internet to exchange ideas, knowledge and information. Basically there are four effective ways of building virtual communities on the internet and they are: web-based communities, email groups, newsgroups and real-time discussions forums. Social networks represented by Web-based communities are the most sophisticated mechanisms for building on-line communities, and are
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often the simplest for end users. Web communities allow some kind of advertisement and visual presentation of material which are typically omitted from email groups, newsgroups and discussion forums. [Dobney.com, 2005]
Control over Communication Tools through Social Networks Google acquired the social networking site Dodgeball.com as a strategy to improve its own social networking efforts. The idea was to gain more control over communication tools, including the mobile world, and to strengthen its ambition of being more of a Web portal than a search engine. Dodgeball (www.dodgeball.com) is a social network which enables the connection of its users to other nodes through their mobile phones, sending text messages that are relayed through a broadcast hub to multiple recipients. Google’s attempt to invest in social networking is not new and started with the Orkut web site (www.orkut.com). Orkut is a web-based social network which was designed by a Google engineer and currently Orkut has more then seven million people connected through thousands of communities. [Regan, 2005]
Mobile Social Networks The mobile phones or wireless PDAs (Personal Digital Assistants) are naturally ideal vehicles to study individuals and organizations. Habitually individuals carry a mobile phone and use it as main tollway for communication. Currently many manufacturers are opening their handset platforms to developers and the devices can be harnessed as networked wearable sensors. The information available from today’s wireless devices includes the cell phone user’s location by the cell tower ID, people’s closeness through repeated Bluetooth scans, regular communication calls and SMS, as well as application usage and phone status like idle, charging, and so on.
Considering the phones as networked, their functionality is no longer solely related to logging devices for social surveys, but phones can also be used as a means of social network involvement, supplying introductions between two proximate people who don’t know each other. Massachusetts Institute of Technology is working on researches of a new infrastructure of devices which are not only aware of each other, but also have a sense of social curiosity. The concept is based on the assumption that the devices may be used to figure out what is being said by people, and even to discover the type of relationship between two individuals. According to Nathan Eagle from the Reality Mining project, underway at MIT’s Media Lab, “The mobile device of tomorrow will see what the user sees, hear what the user hears, and learn patterns in the user’s behavior. This will enable the device to make inferences regarding whom the user knows, whom the user likes, and even what the user may do next.” [Nathan, 2005] Within this context, the research being done by MIT emphasizes the social network aspects of the mobile devices. People through wireless devices will be able to be part of social networks more efficiently, creating new relationships with anyone carrying a mobile device. According to Search Engine Lowdown and search consultant Andy Beal, there are potential social network benefits of using mobile devices: “Can you imagine being able to tell your friends that you are at a local bar, provide them with a map -- or even a satellite view of the premises -- take a photo of your group and then add it to your mobile blog? All from your cell phone.” [Regan, 2005]
YASNs: Internet Social Networking Systems and E-Business Correlation The term “circle of friends” in online social networks started appearing in 2002, and became popular in 2003. An online circle of friends is a
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virtual community in which an initial set of founders send out messages inviting other members of their own personal networks to join the network represented by a website. New members repeat the process, increasing the total number of nodes and links in the network. Websites then offer features such as automatic address book updates, photo galleries, viewable profiles, the ability to form new communities and many forms of online social connections. Using the circle of friends technique, some internet social networking systems, also known as YASNS (Yet Another Social Networking Service), have been launched lately. Some examples are Friendster, Tribe.net, MySpace and LinkedIn. Currently there are over 200 social networking websites, and Friendster is one of the most successful examples of the circle of friends technique [Wikipedia, 2005a]. These tools are used for information gathering, meeting people, and/or finding services. The development of these sites has primarily been funded by private investment. As the popularity of these websites grew substantially, companies started to look closer and enter into the internet social networking arena, as in the case of Google launching Orkut and acquiring the Dodgeball mobile social network company. If Ebay goes in the same direction, social networks could be a possibility for expanding the horizon of e-commerce in the online auction web-sites. The benefits of social networks to marketing have been proven by many researchers. The patterns of relationships of social networks are fundamental to consumer behavior and can be used effectively for marketing strategies. As a major challenge, market strategists are looking for increases in the effectiveness of marketing strategies based on social networks. In order to reach the goal of effectiveness increase in the marketing strategies, scientists and researchers are collecting social network related data for further analyzing, and the study of social networks is beginning to be broadly used in marketing.
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One example of using social networks for the purpose of marketing is when the distribution of products and services is done through a network of independent business people who take care of the distribution themselves or cause others to do it. It is important to notice that marketing strategists not only look to members of the network with the most social capital, but also to nodes which have access to others with a vast amount of social capital. Internet social networks have expanded the channels of integrated marketing communications, advertisement and public relations, as well as the marketing distribution strategy. Within social networks, the communication and relationship between the nodes has attracted the attention of marketing strategists as a niche to be explored. Many people in the network have relationships tied by common interests and behaviors. For example, when a group of members join a community at Orkut social network they have common ideas and thoughts. Within the community, a node with high capital social and betweenness centrality can influence other members to purchase goods or services from specific brands, using specific channels according to his/her marketing strategy. The power of influence is important in social networks and can lead to individuals or groups succeeding in some e-commerce activities.
Internet Social Network Software The “cc:” in the emails can be considered a start point for social software, when individuals send a message to a group of people within a network relationship. People are willing to use social software to advance personal interests and primarily to interact socially. Internet social software must include at least three basic features: support for conversational interaction between individuals or groups, support for social feedback and support for social networks. The conversational interaction between individuals is usually represented by instant
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messaging, discussion chats and collaborative teamwork spaces. When a member of a group in the network starts a discussion with a group, other members must be able to react and participate in the discussion. Support for feedback allows individuals or groups to rate the contributions of other members, in order to build digital reputations for the nodes of the network. Nodes with high digital reputations as well as high social capital have a great power of influence on other nodes. As example, sellers from eBay depend on feedback to maintain a good reputation and increase sales. Social software needs to support the circle of friends. For example, the proposed standard Friend Of A Friend (FOAF), is represented by an XMLbased approach to define the member interests, phone numbers, e-mails and degree and type of relationship this member has with other members from the network. The social software should be able to represent the map with all the ties between the nodes in the network. For example, Golbeck and Hendler (2006) present TrustMail, a prototype email client that uses variations on algorithms for inferring trust relationships between individuals that are not directly connected in the network to score email messages in the user’s inbox based on the user’s participation and ratings in a trust network.
beginning, then a slow death. According to the on-line communication and community specialist Lee Bryant, one of the reasons for the problem with knowledge management was the hijacking by software vendors. Bryant’s position regarding Social Network is that “Social Software tries to remove obstacles in the path of interaction to let people communicate and collaborate more effectively. In other words, to let people do what they do naturally, but in a better way” (Kaplan, 2005). Although Web-based tools offer various opportunities for advertising, distribution, marketing, and even direct payment, the companies are still trying to find the perfect magic recipe for reaching profits and some doubts still remain about the longterm value of social networking from a revenue perspective [Regan, 2005]. As all technologies and concepts evolve, social networking will fit new technologies which will be introduced to the society, and the internet will allow and contribute to the expansion of social networks in ways that were previously not possible.
CONCLUSION AND RECOMMENDATIONS
FUTURE TRENDS OF SOCIAL NETWORK AND E-BUSINESS
Today, forward-thinking executives are using information technology to streamline and synchronize operating and management processes. Looking forward, some potential elements of the next-generation service agenda are as follows (Marson, 2007):
One of the future trends of YASNs is the emergence of hybrid web-based social networks and instant messaging technologies. The idea is to allow users to share blogs (weblogs), files and instant messages, creating a social network dynamically in real time, depending on where the users are currently located. Some arguments state the fear of social software following the same way of knowledge management software: much excitement at the
1. Listening to and Engaging Citizens and Clients: Government service strategies are based on regular research and consultation with citizens and clients, and on citizens’ priorities for improvement 2. Next-generation Service Policy: embodies a results-based approach to: external service; internal service; integrated, one-stop service; cost-effective channel management, and strikes a balance between excellence
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3.
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8.
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in service outcomes for clients and costeffectiveness for citizens Improving Access for Citizens and Business: “No wrong door” across the public sector, underpinned by an e-data base (311, 211 etc) and N11-integration Integrated Service Delivery and Integrated Channel Management: expanded one stop shopping, both “department stores” and “boutiques”. Focus on improving telephone service and on integrating T-service with E-service; Web 2.0 applications are applied to internal management, external service, and citizen engagement Personalization and Customization: the Internet is used to personalize and customize service to individual client needs Horizontal Governance and Service Collaboration: collaborative platforms and new governance arrangements are developed within and across governments Internal Service Transformation: focused on cost-effective e-solutions, and on measuring and improving internal client satisfaction The Service Value Chain: public organizations use the SVC concept to link, measure and improve employee engagement, service outcomes and public trust and confidence Results Measurement and Benchmarking: shared ways of measuring service performance emerge internationally and benchmarking occurs across the public sector (e.g the CMT& MAF) Training and Development: Public sector service delivery becomes a profession based on a growing empirical body of service management knowledge.
Overall, the academic community and business practitioners can no longer ignore the consequences of the rapid “flattening” of the world due to IT facilitated globalization. E-Government is a burgeoning phenomenon across the globe with substantial investment being made to sup-
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port improvements to infrastructures as well as services to the citizen. Many of the emerging challenges facing its adoption are not technical or developmental but in fact center around political, managerial, and cultural information and communication technology issues, which are of course accentuated in the public sector. When they are successful, organizational transformation and change initiatives can be exciting and engaging experiences that achieve extraordinary outcomes. Such change efforts can lead to innovation and renewal in many areas. Better utilization of technology, more efficient process flow, and enhanced individual and team productivity are all potential benefits of positive change.
REFERENCES Acquaah, M. (2007). Managerial social capital, strategic orientation, and organizational performance in an emerging economy. [Chichester.]. Strategic Management Journal, 28(12), 1235– 1242. doi:10.1002/smj.632 Adit Software. (2005). Adit software–sociometry. Retrieved on July 9, 2007, from http://www.adit. co.uk/html/sociometry.html Boyd, S. (2003). Are you ready for social software? Darwin Magazine Web site. Retrieved on July 9, 2007, from http://www.darwinmag.com/ read/050103/social.html Christ, R. E., Berges, J. S., & Trevino, S. C. (2007). Social networking sites: To monitor or not to monitor users and their content? [Clifton.]. Intellectual Property & Technology Law Journal, 19(7), 13–17. Dobney.com. (2005). Online virtual communities. Retrieved on July 10, 2007, from http://www.dobney.com/Technology/virtual_communities.htm
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Epstein, D. (2004). Fast approximation of centrality. Journal of Graph Algorithms and Applications, 39-45.
Orgnet. (2005). An introduction to social network analyzes. Retrieved on June 25, 2007, from http:// www.orgnet.com/sna.html
Ethier, J. (2005). Current research in social network theory. Retrieved on July 9, 2007, from http://www.ccs.neu.edu/home/perrolle/archive/ Ethier-SocialNetworks.html
PieSpy. (2005). PieSpy social network by jibble Web page. Retrieved on May 26, 2007, from http:// www.jibble.org/piespy/
Golbeck, J., & Hendler, J. (2006). Inferring binary trust relationships in Web-based social networks. [New York.]. ACM Transactions on Internet Technology, 6(4), 497–504. doi:10.1145/1183463.1183470 Ioannides, Y. M., & Soetevent, A. R. (2007). Social networking and individual outcomes beyond the mean field case. [Amsterdam.]. Journal of Economic Behavior & Organization, 64(3/4), 369–380. doi:10.1016/j.jebo.2006.06.017 Kaplan, E. (2005). Social software and e-learning. Retrieved on July 10, 2007, from http://www. learningcircuits.org/2003/dec2003/kaplan.htm Marson, B. (2007). The future of e-governmenta citizen-centred perspective. Treasury Board of Canada Secretariat, Canada. Retrieved on October 18, 2008, from http://www.oecd.org/ dataoecd/42/39/40305179.pdf Nathan, E. (2005). Using mobile phones to model complex social systems. Retrieved on June 26, 2007, from http://www.oreillynet.com/pub/a/ network/2005/06/20/MITmedialab.html OECD. (2008a). OECD broadband statistics. Retrieved on November 6, 2008, from http://www.oecd.org/document/54/0,3343, en_2649_34225_39575670_1_1_1_1,00.html OECD. (2008b). Broadband growth and development in OECD countries. Retrieved on November 6, 2008, from http://www.egov.vic.gov.au/index. php?env=-categories:m11-1-1-8-s-0&reset=1
Regan, K. (2005). Google boosts its social network with dodgeball.com buy. Retrieved on June 25, 2007, from http://www.macnewsworld.com/ story/43099.html Smith, H. A., & McKeen, J. D. (2007). Developments in practice XXVI: Social networks: Knowledge management’s “killer app”? [Atlanta.]. Communications of the Association for Information Systems, 19, 35. Wellman, B. (2005). “The network community” an introduction to networks in the global village. Retrieved on May 26, 2007, from http:// www.chass.utoronto.ca/~wellman/publications/ globalvillage/in.htm Wikipedia. (2005a). Social network. Retrieved on May 22, 2007, from http://en.wikipedia. org/wiki/Social_network#Introduction_to_social_networks Wikipedia. (2005b). Social capital. Retrieved on July 9, 2007, from http://en.wikipedia.org/wiki/ Social_capital
KEY TERMS AND DEFINITIONS Betweenness Centrality: This has great influence on the flows of the social network. It is one of the best locations or highest betweenness centrality in the network because it is between two important constituencies and is a point of failure because without it, the others would be cut off from information and knowledge from the cluster.
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Closeness Centrality: This measures the best visibility into what is happening in the social network. Social Network: A map representing the relationships among individuals, indicating the ways in which they are connected according to their social familiarities. The networks of communication and interpersonal relationships that develop naturally within an organization form channels for the flow of organizational knowledge and can promote organizational learning, innovation and change management. Sociometry: One of the methods of sociopsychology developed by the psychiatrist Jacob Levi Moreno that analyzes the interpersonal emotive relationships within groups.
Social Networking Sites: Online communities for expanding users’ business or social contacts by making connections through their mutual business or personal connections. Socio-Technical Design: Design to produce information systems that blend technical efficiency with sensitivity to organizational and human needs. Virtual Organization: An organization that uses networks to link people, assets and ideas to create and distribute products and services without being limited to traditional organizational boundaries or physical locations.
This work was previously published in Handbook of Research on E-Government Readiness for Information and Service Exchange: Utilizing Progressive Information Communication Technologies, edited by Hakikur Rahman, pp. 324-333, copyright 2010 by Information Science Reference (an imprint of IGI Global).
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Chapter 3.9
Designing E-Business Applications with Patterns for Computer-Mediated Interaction Stephan Lukosch Delft University of Technology, The Netherlands Till Schümmer FernUniversität in Hagen, Germany
INTRODUCTION Probably the most important aspect of e-Business and e-Commerce is that it mediates the interaction between various stakeholders in a business setting. New organizational forms such as virtual organizations emerged in which independent companies form a strategic alliance for a close collaboration towards a shared goal (e.g., shared product development). New forms of B2C (business-to-customer) interaction argue for the importance of hearing the customer’s voice e.g., by providing means for customization (Piller, DOI: 10.4018/978-1-60960-587-2.ch309
2006) or by collecting the customers’ feedback (Levine, Locke, Searls, & Weinberger, 2000). And in some cases, C2C (customer-to-customer) interaction has become an integrated part of the business (in settings where customers also act as providers of goods or services). Closely related to these trends is the emergence of the Web 2.0 as “a set of economic, social, and technology trends that collectively form the basis for the next generation of the Internet – a more mature, distinctive medium characterized by user participation, openness, and network effects.” (Musser, O’Reilly et al., 2006, p. 4). Again, collaboration and user participation is one of the most important terms in this definition and it is what makes
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Designing E-Business Applications with Patterns for Computer-Mediated Interaction
Web 2.0 different from traditional web sites that have mainly focused on content delivery rather than interaction and collaboration among users of content. Considered from an e-business perspective, there are important analogies, especially the shift from mass delivery to customized goods and services that are co-created by traditional sellers and customers. Interestingly, this analogy is not yet widely reflected in the technology support. If business would move from traditional provider-customer interaction to the so-called c-business, the respective support technologies need to be designed so that the social processes of collaboration become an integral part. First examples of web-based collaborative applications provide hints towards the future of c-business: Google Docs (http:// google.docs.com), Yahoo Groups (http://groups. yahoo.com/), the Amazon bookstore (http:// amazon.com/), or Google Earth (http://earth. google.com/) are all instances with comparable characteristics. They activate the users to create and share information instead of only consuming information created by a single owning company. At Google Earth, users, e.g., tag the map of the earth with points of interest or photography that is shared among all users. The information provider (Google) transfers parts of his business to the customers and acts as an enabler for information creation done by customers. Through the efforts of the user community, the map becomes a reflection of what the inhabitants of the different places on the map consider as relevant. The same is true for the Amazon book store: by allowing users to comment on books and to comment on comments, the bookstore becomes a place for exchanging thoughts rather than just consuming. Considered from a B2C e-commerce perspective, this increases the stickiness of the store (Schümmer, 2001a). Once customers are involved in an interaction with other customers, they have additional incentives for returning to the store. Instead of having a community of circumstances that brings together all users who want to buy books, the site evolves
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to a community of interest for books of a specific topic (Schümmer, 2001a). Yahoo groups support users in creating places for discussion and exchanging ideas and content. The shared manipulation of files is one of the core ideas of Google Docs where users can interact synchronously on a shared document using just their web browser as client infrastructure. Again, such tools open up new opportunities for e-business. They are the enabling technology that allows organizations to create goal-oriented distributed project teams that collaborate intensively in order to reach a shared objective. The remaining part of this article discusses aspects common to these e-business applications and presents an approach to capture the best practices within these applications by means of patterns. Then, we describe how patterns for end-users can look like, outline the structure of a pattern language for computer-mediated interaction and explain how the different patterns of this language form a holistic pattern catalogue for computer-mediated interaction. The pattern language is illustrated by means of an example pattern. Finally, we give a conclusion and discuss questions for future work.
BACKGROUND Several core aspects that make collaborative e-business applications like the ones described above compelling: • •
• •
Users can create and share content. Users can get in contact with other users whom they in most cases have not met before. Users can express their opinion on content and on users. Users become aware of other users’ presence and actions, which transforms the usage experience from a single-user experience to a group experience.
Designing E-Business Applications with Patterns for Computer-Mediated Interaction
Looking more closely at these aspects, all of them have been subject of research and development in the area of computer supported collaborative work (CSCW) and groupware. Peter and Trudy Johnson-Lenz defined groupware systems as “intentional group processes plus software to support them”. (Johnson-Lenz and Johnson-Lenz, 1981) Often this definition is extended by considering not only group processes but also community processes. Users interacting in a community follow a common global goal but may have different sub-goals. They contribute to the community in order to satisfy both personal and shared goals. Tim Berners-Lee commented on the Web 2.0 hype that “Web 2.0 for some people means moving some of the thinking client side so making it more immediate, but the idea of the Web as interaction between people is really what the Web is. That was what it was designed to be as a collaborative space where people can interact.” (Berners-Lee, 2006) Thus, the challenges imposed by the Web 2.0 hype are anything else but new. However, the Web 2.0 hype has the positive effect that the aspects of collaboration and human-human interaction that were often ignored by current applications now move back to the focus of many system developers. And, as we see from the examples mentioned above, collaboration opens new potentials that change the way how we can interact over computer networks and move e-business to c-business applications.
A PATTERN LANGUAGE FOR COMPUTER-MEDIATED INTERACTION The development of such collaborative applications a challenging task. Apart from the actual task of the application, e.g. editing texts or spreadsheets, developers have to consider various aspects ranging from low-level technical issues up to high-level application usage. Among others, network connections between the collaborating
users have to be established to enable communication, parallel input from the collaborating users has to be handled, specific group functions have to be included to provide group awareness, and the data has to be shared and kept consistent to allow users to work on common task at all (Ellis, Gibbs, & Rein, 1991). Nevertheless, the last twenty years of research and development in the area of computer-supported collaborative work have identified various good practices for the design of such applications. A widely accepted approach to capture and communicate good practice knowledge from experts to novices is to use design patterns. Design patterns are considered as a lingua franca for design (Erickson, 2000). The concept of patterns has its roots in architecture where the architect Christopher Alexander collected a large collection of patterns for designing towns and buildings (Alexander et al., 1977). The core of a pattern description is that it describes a solution to a recurring problem in a specific context. A collection of interrelated patterns forms a pattern language. The pattern language for computer-mediated interaction consists of 71 patterns and captures best practices for the collaborative applications (Schümmer & Lukosch, 2007).
An End-User Friendly Pattern Structure When developing collaborative applications not only the interaction of one user with the tool but also the interaction among a number of users has to be taken into account. For a successful application, it is crucial to involve end-users in the development process (Schümmer et al., 2006). Involving end-users in the development process requires that end-users and developers can communicate using a common language. This language has to allow end-users and developers to identify and specify social and technical requirements as well as best practices for a solution. As result, the patterns for computer-mediated interaction
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always address a socio-technical problem. They describe the technology that supports the group process and therefore include a technical and a social aspect. Patterns for computer-mediated interaction are thus socio-technical patterns. Development processes like the Oregon Software Development Process (OSDP) (Schümmer, Lukosch, & Slagter, 2006) rely on such patterns to foster end-user involvement and enable communication as well as interaction among developers and future end-users. The socio-technical perspective on groupware design has to be aware of three key aspects: •
•
•
It is difficult to predict the reciprocal effect of changes to either the social or the technical system. The process used to create the socio-technical system will affect the acceptance of the system. Both social and technical systems change over time.
Patterns are a good means for empowering the user and the groupware developer so that they can react to the changing requirements during the group process. Besides the standard elements of a design pattern, i.e., a context description, a problem statement, a solution statement, and a collection of examples where the solution is in place, the patterns for computer-mediated interaction include several further aspects to address the socio-technical problems. The structure oft the patterns for computer-mediated interaction is shaped to meet both end-user’s and developer’s needs for detail and illustration. The pattern name is followed by the intent, and the context of the pattern. All these sections help the reader to decide, whether or not the following pattern may fit into his current situation. Then follows the core of the pattern composed of the problem and the solution statement separated by a scenario and a symptoms section. The scenario is a concrete description of a situation
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where the pattern could be used, which makes the tension of the problem statement tangible. The symptoms section helps to identify the need for the pattern by describing aspects of the situation more abstract again. After the solution section, the solution is explained in more detail and indications for further improvement after applying the pattern are provided. The participants section explains the main components or actors that interact in the pattern and explains how they relate to each other. The rationale section explains, why the forces are resolved by the pattern. The check section lists a number of questions, one has to answer before applying the pattern in a development context. Unfortunately, the application of a pattern can in some cases raise new unbalanced forces. These counter forces are described in the section labeled danger spots. The solution presented in a pattern represents a proven solution to a recurring problem, so the known uses section provides well-known examples where this pattern is applied. Finally, the related patterns section states what patterns are closely related to this one, and with which other patterns this one should be used. The pattern language for computer-mediated interaction (Schümmer & Lukosch, 2007) identifies 11 categories that group the 71 patterns according to the patterns’ most important forces. In addition, different abstraction levels show which patterns will be used by whom in the development process. Patterns at a high abstraction level have their main focus on the social process (like the Welcome Area pattern) while patterns on a low abstraction level have their main focus on the technical support (such as the Centralized Objects pattern that describes how shared objects can be accessed from a common location). Figure 1 shows the different clusters of our language as shaded boxes. Top level clusters address issues at a community level. The clusters in the middle layer address issues on a group level. Finally, the clusters on the lower levels ad-
Designing E-Business Applications with Patterns for Computer-Mediated Interaction
dress technical issues. The white boxes represent complementary pattern languages. We will explain the clusters of our pattern language in this section providing a tour through some prominent patterns of the pattern language (Coplien and Harrison, 2004, Manns and Rising, 2005, Tidwell, 2006, Duyne, Landay, & Hong, 2002, Völter, Kircher, & Zdun, 2004, Völter, Schmid, & Wolff, 2002, Gamma, Helm, Johnson, & Vlissides, 1995, Schumacher, Fernandez-Buglioni, Hybertson, Buschmann, & Sommerlad, 2005). When establishing a community, the community owner, i.e., the user interested in the community’s topic, will have to think about the relation of community with the surrounding environment. Once, the community is established, it becomes important to deal with quality. Protecting users is especially important in larger communities where not all users know one another. All the patterns in these clusters can be implemented on top of most collaboration infrastructures. With minimal support, e.g., when basing the interaction on e-mail, most of the pattern’s implementation will be the design of a social
process. However, the processes can also be implemented as part of the groupware application which will provide a better guidance for the users. The next lower layers describe technical solutions for a better group support. The basic assumption for these patterns is that the members have found peers in a community and now want to better support their tasks in the community. Most importantly, the designer has to think about how to modify shared artifacts together. Users need to be able to access shared information. This rather tool-oriented view on collaboration is complemented with a place-oriented view. The group shapes places for collaboration. Most collaboration support tools offer some means for textual communication. Awareness is an important aspect of computer-mediated interaction. It describes how users can understand the actions of other users in order to situate their own actions in the group context. The synchronous awareness cluster shows ways how this understanding can be achieved if a group of users collaborates at the same time. The cluster of asynchronous awareness complements the patterns from the above cluster with patterns
Figure 1. Layers in the pattern language for computer-mediated interaction
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that help to stay aware of collaboration partners over longer times. All the patterns in these clusters rely on a technical collaboration infrastructure. The infrastructure can again be described on two layers. On a higher level, session management has to be considered and on the lower level, shared objects and concurrent access to these objects needs to be handled. The cluster on session management assumes that collaboration episodes are embedded in a technical representation of users, the computer systems on which they act, and the used artifacts. Sessions are modeled as shared objects. Finally, data consistency support becomes important when users change shared objects at the same time.
AN EXAMPLE PATTERN: SHARED BROWSING This section illustrates the concept of the design pattern for computer-mediated interaction by presenting selected parts of the Shared Browsing pattern (Schümmer and Lukosch, 2007). The Shared Browsing pattern can especially be used in B2C e-commerce contexts where customers should interact in the process of product selection. •
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Context: Users of your application have different degrees of knowledge about the data or the virtual environment that is presented in the application. Now you are thinking about ways to ease their orientation in the environment. Problem: Users have problems finding relevant information in a collaboration space. They often get lost. Symptoms: You should consider applying this pattern when... ◦⊦ Users take a long time to find the information that they are looking for. ◦⊦ The goal is to find the information as a group, but several group members duplicate efforts to reach this goal.
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•
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Users want to talk about shared artifacts, but do not know how to ensure that their peer user sees the same artifact. Solution: Browse through the information space together. Provide a means for communication, and collaborative browsers that show the same information at each client’s site. Dynamics: Users collaborate in a shared information space. When interacting with a specific chunk of information, users position themselves at this chunk. The position of each user can be described as a location.
The collaborative browser communicates and shares the location of each user in the group. How this information is processed depends on the navigation strategy of the collaborative browser. Examples of different navigation strategies in collaborative browsing are: •
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Master-slave browsing in which one user ‘‘drives’’ and the other users follow. Whenever the master user updates the position, this position is also set for all slave users. Anarchistic browsing that does not have any roles. Whenever one user moves to a new location, all other users follow. Democratic browsing in which the group has to form a collaborative opinion before its members move on to the next artifact. Rationale: In a study of traditional libraries, Twidale, Nichols, & Paice (1997) showed that browsing should be a collaborative action. Although many searches for information is carried out alone in such places, Twidale et al. (1997) show that interaction between users also takes place.
Since collaborative browsers always show the same artifacts, their users will be able to commu-
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nicate about the content shown. This helps them to understand the artifacts better. •
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Check: When applying this pattern, you should answer these questions: ◦⊦ How should you represent the view location? Can you use a URL or a coordinate? ◦⊦ Which browsing strategies will you offer the users? Known Uses: TUKAN (Schümmer, 2001b), CobWeb (Stotts, Prins, Nyland, & Fan, 1998), and GroupScape (Graham, 1997). Related Patterns: Application Sharing, Shared Editing, Remote Field of Vision, Collaborative Session, Floor Control, Vote, Embedded Chat, Replay.
An e-business application scenario for this pattern could be an event-management system where buyers can shop, e.g., for movie tickets. Such a system could be enhanced by the Shared Browsing pattern in order to support a group of friends in the movie selection process. Group members would select relevant movies independently and store references to these movies on a shared wish list. After this phase of independent browsing, they would review the relevant movies together using a master-slave browsing approach.
CONCLUSION AND FUTURE RESEARCH In this article, we presented a pattern language for computer-mediated interaction. We discussed the pattern language in the context of other well-known pattern languages and described an example pattern for the use in e-business settings. The pattern language presents a first step towards a better understanding of computer-mediated interaction in a networked environment and offers best practices for designing applications in
the emerging c-business domain. Case studies (Schümmer & Lukosch, 2007) on prominent groupware applications, like, e.g., BSCW (http:// www.bscw.de) or CoWord (http://cooffice.ntu/ edu.sg/coword), as well as the application of the patterns to design groupware (Lukosch & Schümmer, 2006) show that the most important patterns are captured within the pattern language for computer-mediated interaction. Still, there is a large potential for mining additional patterns in order to complement the pattern language for computer-mediated interaction in the area of workflow management, computer-mediated collaborative learning, gaming and entertainment, media use in collaboration, or mobile and other new computing devices.
REFERENCES Alexander, C., Ishikawa, S., Silverstein, M., Jacobson, M., Fiksdahl-King, I., & Angel, S. (1977). A pattern language. New York: Oxford University Press. Berners-Lee, T. (2006). developerworks interviews. Retrieved June 1, 2009, from http:// www-128.ibm.com/developerworks/podcast/ dwi/cm-int082206.txt Coplien, J. O., & Harrison, N. B. (2004). Organizational Patterns of Agile Software Development. Upper Saddle River, NJ: Prentice Hall. Duyne, D. K. V., Landay, J., & Hong, J. I. (2002). The Design of Sites: Patterns, Principles, and Processes for Crafting a Customer-Centered Web Experience. Reading, MA: Addison-Wesley Longman Publishing Co., Inc. Ellis, C., Gibbs, S., & Rein, G. (1991). Groupware some issues and experiences. Communications of the ACM, 34(1), 38–58. doi:10.1145/99977.99987
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Erickson, T. (2000). Lingua francas for design: sacred places and pattern languages. In Proceedings of the conference on Designing interactive systems, (pp. 357–368). New York: ACM Press.
Schumacher, M., Fernandez-Buglioni, E., Hybertson, D., Buschmann, F., & Sommerlad, P. (2005). Security Patterns. Chichester, UK: John Wiley & Sons, Ltd.
Gamma, E., Helm, R., Johnson, R., & Vlissides, J. (1995). Design Patterns. Reading, MA: AddisonWesley.
Schümmer, T. (2001a). GAMA-Mall – shopping in communities. In L. Fiege, G. Mühl, & U. Wilhelm, (Eds.), Proceedings of the Second International Workshop on Electronic Commerce (WELCOM’01), (pp. 51-62). Heidelberg, Germany: Springer.
Graham, T. C. N. (1997). Groupscape: Integrating synchronous groupware and the world wide web. In S. Howard, J. Hammond, & G. Lindgaard, (Eds.), Human-Computer Interaction, INTERACT ‘97, IFIP TC13 Interantional Conference on Human-Computer Interaction, Vol. 96 of IFIP Conference Proceedings, (pp. 547–554), Sydney, Australia. Boca Raton, FL: Chapman & Hall. Johnson-Lenz, P., & Johnson-Lenz, T. (1981). Consider the groupware: Design and group process impacts on communication in the electronic medium. In S. Hiltz & E. Kerr, (Eds.), Studies of Computer-Mediated Communications Systems: A Synthesis of the Findings, (Vol. 16). Newark, NJ: Computerized Conferencing and Communications Center, New Jersey Institute of Technology. Levine, R., Locke, C., Searls, D., & Weinberger, D. (2000). The cluetrain manifesto. Cambridge, MA: Perseus Publishing. Lukosch, S. & Schümmer, T. (2006). Groupware development support with technology patterns. International Journal of Human Computer Studies, Special Issue on ‘Theoretical and Empirical Advances in Groupware Research’, 64(7), 599–610. Manns, M. L., & Rising, L. (2005). Fearless Change: Patterns for Introducing New Ideas. Reading, MA: Addison-Wesley. Musser, J., O’Reilly, T., & the O’Reilly Radar Team (2006). Web 2.0 Principles and Best Practices. Sebastopol, CA: O’Reilly Radar. Piller, F. (2006). Mass Customization. Wiesbaden, Germany: Gabler Verlag.
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Schümmer, T. (2001b). Lost and found in software space. In Proceedings of the 34th Hawaii International Conference on System Sciences (HICSS-34), Collaboration Systems and Technology, Maui, HI. Washington, DC: IEEE-Press. Schümmer, T., & Lukosch, S. (2007). Patterns for Computer-Mediated Interaction. Chichester, UK: John Wiley & Sons, Ltd. Schümmer, T., Lukosch, S., & Slagter, R. (2006). Using patterns to empower end-users – The Oregon software development process for groupware. International Journal of Cooperative Information Systems, Special Issue on ‘11th International Workshop on Groupware (CRIWG’05)’, 15(2), 259–288. Stotts, D., Prins, J., Nyland, L., & Fan, T. (1998). Cobweb: Tailorable, analyzable rules for collaborative web use. Technical report, Dept. of Computer Science, University of North Carolina, Chapel Hill. Tidwell, J. (2006). Designing Interfaces. Sebastopol, CA: O’Reilly. Twidale, M. M., Nichols, D. M., & Paice, C. D. (1997). Browsing is a collaborative process. Information Processing & Management, 33(6), 761–783. doi:10.1016/S0306-4573(97)00040-X Völter, M., Kircher, M., & Zdun, U. (2004). Remoting Patterns – Foundations of Enterprise, Internet, and Realtime Distributed Object Middleware. Chichester, UK: John Wiley & Sons, Ltd.
Designing E-Business Applications with Patterns for Computer-Mediated Interaction
Völter, M., Schmid, A., & Wolff, E. (2002). Server Component Patterns: Component Infrastructures Illustrated with EJB. Chichester, UK: John Wiley & Sons, Ltd.
KEY TERMS AND DEFINITIONS Design Pattern: Description of a solution to a recurring problem in a specific context. Electronic Collaboration: Process of collaborating by means of electronic tool support. Groupware Systems: Intentional group or community process plus computer support.
Patterns for Computer-Mediated Interaction: Design patterns that address the design of groupware systems. Pattern Language: Collection of interrelated patterns for a problem domain. Socio-Technical System: A system that recognizes the interaction between people and technology. Socio-Technical Pattern: A design patterns that combines a technical and a social solution. User-Centered Design: Design process which gives attention to the needs of the end-user.
This work was previously published in Encyclopedia of E-Business Development and Management in the Global Economy, edited by In Lee, pp. 1002-1010, copyright 2010 by Business Science Reference (an imprint of IGI Global).
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Business Artifacts for E-Business Interoperability Youakim Badr INSA-Lyon, France Nanjangud C. Narendra IBM Research India, India Zakaria Maamar Zayed University, UAE
ABSTRACT Traditional solutions to address interoperability issues are mainly process-centric so that consistent interactions among collaborating enterprises are ensured. These solutions examine interoperability from a technological perspective with focus on exchanging information messages between distributed and heterogeneous applications. However, interoperability from a business perspective has been overlooked in the past due to the complexity of reconciling diverse business strategies, organizational constraints, and IT infrastructures. DOI: 10.4018/978-1-60960-587-2.ch310
Business interoperability denotes the ability of diverse enterprises to collaborate together to coproduce added-value products and services. In this chapter, a new line of thinking is promoted whereby interoperability is data-centric instead of process-centric. Business interoperability is dealt with by adopting business artifacts that are able to cross organizational boundaries, and by introducing a stack of three layers - strategy, service, and resource. Artifacts are self-contained business records that include attributes, states, and life cycles that reflect the changes in these states. The artifact concept not only describes a business entity, but also encompasses knowledge about what to process without explaining how to
Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
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do it. The shift from processes to artifacts makes business interoperability “quite simple’’ to deploy and renders collaboration easy to manage and analyze. The chapter also introduces several interaction patterns that regulate the exchange of artifacts between enterprises. The ideas and proposals in this chapter are discussed via a realistic case-study to demonstrate how business people can seamlessly manage their day-to-day activities and intuitively construct interoperable and sustainable collaborations at the business and technological levels.
INTRODUCTION To face today’s challenges such as competition and market volatility; enterprises must adapt their business operations and even, sometimes, modify their organizational structures. Existing information and communication technologies attempt to make this happen by integrating diverse entities including people, applications, processes, and information into the same common working space (Nandi & Kumaran, 2005). In this space, people use applications that trigger processes that themselves make use of the available information to answer their needs. Despite the collaborative tools that render the integration possible, the main challenge remains the ability of these entities to effectively interoperate together to accomplish their business goals. In a broad sense, interoperability refers to “the ability of a system or a product
to work with other systems or products without special effort” (Touzi et al., 2007). Interoperability is a recurring challenge that surfaces each time either physically or morally independent enterprises decide to collaborate (Norta et al., 2006). Differences in terminologies, backgrounds, requirements, priorities—just to cite a few examples—offer a glimpse of the interoperability challenges. Despite the large number of initiatives, standards, and specifications to deal with interoperability (Arsanjani, 2002; ETSI, 2006; Gailly & Poels, 2009; Peristeras & Tarabanis, 2006; Ma, 2009), enterprises have been struggling over the years with almost the same set of issues: lack of common semantics and ways of doing businesses, reduced access to external resources, data inconsistencies, and policy incompatibilities. These initiatives have, to a certain extent, focused on technical issues while neglecting the need of examining interoperability from a business perspective. Extending Cimander and Kubicek’s work (Cimander and Kubicek, 2009), we distinguish five interoperability levels (Table 1): technical, syntactic, semantic, organizational, and business. Regardless of any of these interoperability levels, the main purpose remains business collaboration where different systems not only have to communicate and consolidate their data but also semantically understand business practices to meet customers’ expectations and increase enterprises’ profits. Considering the success factors of some today’s technologies such as the Internet, the eXtensible
Table 1. Interoperability levels Business
Ability of diverse enterprises to collaborate together to coproduce added-value despite their different business strategies, organizational constraints, and IT infrastructures
Organizational
Ability to seamlessly interoperate pre-existing organizational structures and their business processes in response to different types of business collaborations
Semantic
Ability to automatically interpret the data exchanged meaningfully and accurately in order to produce useful results
Syntactic
Ability to integrate and exchange data by using specified data formats
Technical
Ability of systems to technically provide data transfer protocols to communicate with other systems and operate effectively together
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Markup Language (XML), and Web services, in this chapter we demonstrate how these technologies could contribute to overcome the interoperability challenge. In this context, the Internet is a support platform for e-business applications, XML is a platform-independent communication format to exchange data, and Web services are a computing technology that allows business processes across organizational boundaries (Baldoni et al., 2009; Maamar et al., 2006; Mocan et al. 2009). The composition of Web services offers another advantage to set up new business scenarios obtained by combining available Web services. Although Web services stand as an inevitable solution to interoperability at the technical level, examining interoperability at the business level remains almost “untouched”. Interoperability is not restricted to business process integration to ensure consistent data flow and smooth interactions between applications, but strengthens the importance of revisiting the way business processes are understood by all the people in an enterprise with emphasis on those at the business level. The people at the business level – primarily business managers or analysts - prefer to manage the evolution of their business records or data instead of spending time following-up the execution progress of business processes. These people are typically not IT savvy, and would prefer to evaluate the progress of their business processes via inspections of business records and data, rather than the low-level details of the individual business process implementations. Needs and concerns of the people at the business level are quite different from those at the middle (e.g., supervisors) or lower (e.g., programmers) levels. Taking this into account, we adopt the concept of business artifact (Nandi & Kumaran, 2005; Bhattacharya et al., 2005; Bhattacharya et al., 2007; Kumaran et al., 2008) to provide appropriate interoperability mechanisms at the business level. According to (Nigam & Caswell, 2003), artifacts are concrete, identifiable, selfdescribing records of information that can be
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easily identified by business people. In (Cohn & Hull, 2009), the added value of the use of business artifacts to model business operations and processes is reported. Typical artifacts include purchase order, bills, invoices, loan approvals, and car registrations. Simply put, business artifacts are “business-relevant objects that are created, evolved, and (typically) archived as they pass through a business” (Cohn & Hull, 2009). In this chapter we introduce our interoperability stack and adopt business artifacts as exchange means that can first, traverse organizational boundaries and second, flow within organizations (Figure 1). In this stack, three layers are identified: strategy, service, and resource. All these layers have access to a repository of business artifacts for different needs and purposes. In the context of the interoperability stack, the artifact passes through the stack layers in a top-down manner before it is sent over the network and reaches its recipient for further processing. The objective of this passing through is to enrich the artifact with additional elements related to semantics, update/ access rights, or business constraints. Our contributions in this chapter are threefold. 1. The interoperability stack demonstrates the interactions between enterprises using the strategy, service, and resource layers. The strategy layer provides an artifact-based collaboration model to ensure enterprise interoperability and automatically instantiates spontaneous and synchronous group collaboration in a modular and transparent manner. The service layer supports the collaboration that is set by the strategy layer by composing Web services. Finally, the resource layer provides the necessary means upon which the Web services are executed according to the collaboration model defined by the strategy layer. In this chapter, we primarily focus on the strategy layer, with some minor emphasis on the service layer.
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Figure 1. Interoperability stack
This is due to the chapter’s focus, which is modeling interactions at the business layer. 2. The interaction patterns that regulate the collaboration schemas between enterprises. 3. The repository of business artifacts and mechanisms of artifact exchange between enterprises. This chapter is organized as follows. We first review the existing state of the art in the area of interoperability and point out its shortcomings. We then illustrate our proposed solution via a simple yet realistic running example in the purchase order domain. Prior to concluding and listing some future research directions, we present the details of our proposed stack and demonstrate its usefulness via the running example.
LITERATURE REVIEW Because of the multiple topics that our research work addresses, we decompose the literature review section into three parts. The first part reviews some solutions for e-business interoperability (Hall & Koukoulas, 2008; Liang et al., 2005; Silva et al., 2003; Janner et al., 2008). The second part reviews some initiatives concerning artifacts (Hull, 2008; Muller et al., 2008; Kumaran et al., 2008; Nandi & Kumaran, 2005; Narendra et al., 2009; Nigam & Caswell, 2003). The last section
discusses the expected added-value of artifacts to e-business interoperability.
E-Business Interoperability In (Liang et al., 2005), Liang et al. discuss the interoperability between different e-business specifications with emphasis on the Connections Markup Language (cnXML) and the Electronic Business using eXtensible Markup Language (ebXML). An architecture that consists of data, semantic, and process layers is proposed. This architecture is in line with our interoperability stack where the separation of concerns per level is necessary. In the architecture of Liang et al., the data layer corresponds to messaging service specifications in terms of the basic format and delivery mechanisms of business messages. The semantic layer corresponds to commonly used business terms and vocabulary. Finally, the process layer corresponds to business process specification in terms of defining the frequently used business processes, which are a set of message sequences in a predefined order. Liang et al. argue that interoperability assurance between different e-business specifications is necessary for e-business technology to become widespread. In (Hall & Koukoulas, 2008), Hall and Koukoulas discuss semantic interoperability for e-business in the particular service domain of Internet Service Providers (ISPs). An accurate understanding of the information that collaborating partners exchange
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is critical. Hall and Koukoulas selected small ISPs because of their capacity to target niche markets, but at the same time for their limited capacity to offer (i) a wide range of services that are nowadays required by increasingly demanding business customers and (ii) a proper geographical coverage that is necessary in a globalized marketplace. Hall and Koukoulas stress the importance of knowledge management and ontology development for enterprise interoperability. This importance is highlighted in the Enterprise Interoperability Research Roadmap (Li et al., 2006). A group of ISPs can work efficiently only if all the partners have the same view, not only of what a service is and what it offers, but also of relationships and constraints between services, service characteristics, and characteristic values. In (Silva et al., 2003), Silva et al. stress the role of ontologies to achieve e-business interoperability. This role is illustrated with the possibility of annotating Web resources with machine-processable meta-data. Thanks to these meta-data, automatic tools can analyze meaning and semantic relations between the Web resources. Silva et al. suggest that an ontology should be built in three distinct layers: model, axiomatic, and lexical. Again, the representation of this layer is in line with our stack interoperability and the separation of concerns principle. The model layer specifies domain and/or application entities, their inter-relations, and properties. The axiomatic layer constrains the interpretation and application of entities through axioms and rules. Finally, the lexical layer characterizes entities and their properties with natural language lexicons, giving them a real word meaning. In (Norta et al., 2006), a repository of patterns for storing already-designed and used interorganizational business processes is proposed. Each process is modeled via a combination of predefined process patterns, where each pattern is a technology-independent model for process representation. Each pattern is itself defined as per a pattern meta-model: management of the pattern
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in the repository follows a lifecycle comprising pattern submission, pattern review, and pattern acceptance or rejection. Developing business process models for a new requirement therefore consists of selecting the appropriate process patterns from the pattern repository and combining them to form the desired process model. Collaboration, which is a visible form of interoperability, is examined in different European projects. In the ECOSPACE project (www.ipecospace.org/), the vision is that “by 2010 every Professional in Europe is empowered for seamless, dynamic and creative collaboration across teams, organisations and communities through a personalised collaborative working environment’’. The design and development of an open-standard, service-oriented architecture along with a usercentric platform are among the objectives of this project. In the InContext project (www.in-context. eu/page.asp?PageRef=1), the aim is to develop “a novel scientific approach to the problem of enabling diverse individual knowledge workers in separate organizations to facilitate effective team work among individual knowledge workers, harnessing the latest developments in new technology’’. A semantic agent-based framework to facilitate business process collaboration is developed in this project. In another project known as COIN for Enterprise COllaboration & INteroperability (www.coin-ip.eu), enterprise interoperability is defined as “the ability of two or more systems or components to exchange information and to use the information that has been exchanged’’. The interoperability services developed in COIN are meant for information, knowledge, and business. Generally speaking, these approaches tend to solve the interoperability problem by addressing the semantics of exchanged business objects and data. They also seek to solve the interoperability problem due to the integration of different and distributed business processes, and their activities. The interoperability in e-business applications remains a challenging problem due to the evolution of partner business processes. In fact, all
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partners continuously improve their businesses and update their business process activities. Thus, changes require an entire revision of the underlying collaborative approach. As for data semantic interoperability, some of the aforementioned related works propose ontology-based solutions but still depend on the interoperability of business processes. The challenge remains how to ensure the interoperability at the business level independently from activity-centric business processes.
Business Artifacts A business artifact is a mechanism used to record chunks of information that can be used by a business person to manage a business. The value of an artifact relies on its representation model that is manageable, analyzable, and flexible from the perspective of a business person. Changes in an artifact are usually reflected on an Artifact LifeCycle (ALC). These changes are the result of executing one or more tasks in business processes. In (Kumaran et al., 2008), Kumaran et al. stress the importance of developing guidelines to identify artifacts from business processes. A business process complies with a business model that prescribes the activities to be performed as part of a business operation, the sequencing of these activities, and the inputs and outputs of these data. According to Kumaran et al., business artifacts have been successfully used in different information-centric process modeling exercises, but several problems remain. One of these problems is how to discover the right artifacts that best describe a business process. The current discovery technique is based on intense consulting sessions that are time consuming and require special consulting skills. To address this problem, Kumaran et al. propose an algorithm along with an approach that transforms activity-centric process models into information-centric models. In (Nigam & Caswell, 2003), Nigam and Caswell present a comprehensive discussion of using business artifacts and their life-cycles in business
modeling. An artifact is a formal structure that is suitable for use by business people to manage, analyze, and control their daily business operations. In another work, Nandi and Kumaran introduce the concept of Adaptive Business Objects (ABO) to integrate people, processes, information, and applications (Nandi & Kumaran, 2005) into the same working space. The ability to quickly and easily change the underlying application behaviors in response to ever-changing business conditions remains a crucial problem in business integration. An ABO constitutes an abstraction of a business entity with explicitly managed states and an associated programming model. It is similar in spirit to the artifact and tends to define a holistic view of integration. In (Muller et al., 2008), Muller et al. present data-driven process structures in which Object Life Cycles (OLC) of different objects are linked through OLC dependencies. Based on objects and relations between them, process structures are specified at the model level and then automatically instantiated as per a given data structure. This approach enables adaptations of data-driven process structures at both design and runtime. In (Narendra et al., 2009), Narendra et al. introduce a unified approach for business process modeling using context-based artifacts and Web services. They note that Service-Oriented Architecture (SOA) is a promising paradigm upon which enterprises could develop looselycoupled, interoperable business processes made up of distributed components for instance Web services. However, Narendra et al. recommend that prior to implementation it is critical to abstract business processes using models that are simultaneously expressive for non-IT specialists. A unified process- and data-centric approach seems to offer the right means for this recommendation. In that work, a business process is derived from a combination of interacting business artifacts. Modifications in an artifact are reflected on its life cycle that is represented as a state transition system. Transitions between successive states
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in an artifact life-cycle are the result of executing tasks in a business process, tasks that in fact correspond to Web service’s operations. Hence a complete business process is now modeled as a set of interacting artifact life-cycles. Artifacts progress through their respective life-cycles upon Web services’ approvals.
Artifacts’ Expected Added-Value to E-Business Interoperability Prior to concluding this section, we compare between process- and artifact-centric approaches and discuss the expected added-value of artifacts to e-business interoperability. For the first point, Table 2 summarizes this comparison (Kumaran et al., 2008). As per the aforementioned initiative where the focus is always technological, artifacts could prove useful means to address some interoperability issues. Artifacts are mainly data-centric instead of process-centric. Data passing from one partner to another is a core activity in any interoperability scenario. Partners always struggle with identifying the data they require from their peers due to lack of common understanding and restricted access to data resources. In our approach, interoperability scenarios can be built upon artifacts (that all organizations agree upon) that can cross organizational boundaries and whose life cycles can be split into parts, each part associated with a partner in compliance with some access rights.
Each artifact is associated with a life cycle that shows all the changes in states that the artifact goes through. Through artifact use, it is possible to make interoperability focus on the needs of the business itself rather than on the needs of integrating business processes. This will allow business people to seamlessly manage their day-to-day activities and intuitively construct sustainable collaborations with partners. Internal changes in organizational structures, activities, and functional services should not impact existing collaborations. Our objectives are to: •
• •
•
Promote a new line of thinking whereby interoperability should be data-centric instead of process-centric. Reduce interoperability reliance on standards and technologies. Establish sustainable business collaboration regardless of current business processes and their future evolution. Increase the ability of business people to easily adapt their businesses in response to strategy changes.
CASE STUDY Business process models are used to represent processes in terms of tasks to execute, messages to exchange, data to update, among other things.
Table 2. Comparison between process- and artifact-centric approaches Requirement
Process-centric approach
Artifact-centric approach
Modeling
Enumerates all process activities via hierarchical process representation of control and data flow – not conducive to in-depth analysis and prediction of process behavior.
Helps to analyze and predict system behavior using the lifecycle models of a few business artifacts in a flat structure.
Flexibility
Once defined, the process-centric approach fixes a particular process flow, which needs to be changed in order to accommodate exceptions or requirement changes
Provides business people with the flexibility to choose/ modify the appropriate sub-sequence of steps in the business process, as long as the lifecycles of the artifacts are adhered to, thereby enhancing flexibility.
Tracking
Due to hierarchical representation, tracking at various levels becomes quite cumbersome
Tracking based on states in the flat artifact-centric structure – can provide a quick “bird’s eye view” without unnecessary details.
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In Figure 2, we identify the accounting, sales, and stock departments that belong to the same enterprise. Additional external departments are also shown in this figure for instance bank, supplier, and shipper. At the technological level, each department or enterprise runs various applications on different platforms. Some of these applications are depicted in Figure 3. In Figure 2, dashed rectangles represent business partners, arrows represent collaboration flow, and circles represent applications. Figure 3 illustrates inter-enterprise collaboration through an online purchase-order scenario. Initially a customer places an order for a variety of products via Customer-App. Based on this order, Customer-App obtains details on the customer’s previous purchase history from the CRMApp (standing for Customer Relationship Management). Then Customer-App forwards these details to Billing-App, which first calculates the customer’s bill based on her history details (e.g., whether eligible for reward points or discounts)
that Credit-App provides, and then sends the bill out to CRM-App. The latter prepares the detailed purchase order based on the bill and sends it out to Inventory-App (standing for Inventory Management) for order fulfillment. For those products that are in stock, Inventory-App sends a shipment request out to Shipper-App, which is now in charge of delivering the products to the customer. For those products that are out-of-stock, InventoryApp sends a supply message out to the requisite Supplier-App, which provides the products to Shipper-App for subsequent shipments to the customer. The above scenario, albeit highly simplified, shows the need of different departments or enterprises collaborate in order to fulfill their customers’ needs. When mapping this scenario onto the elements of our interoperability stack, the following points are raised: •
At the strategy layer, enterprises need to express their willingness to participate
Figure 2. Collaboration at the enterprise level
Figure 3. Collaboration at the application level
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•
•
in joint operations by reviewing some of their internal business processes or making some of their internal business processes accessible to other peers. For example, suppliers let some businesses check their inventories. At the service layer, enterprises need to develop combined operations (or services) that will involve their own applications as well as those of their peers. These operations will spread over organizational boundaries at run-time. For example, Inventory-App needs to coordinate with Supplier-App and Shipper-App to ensure that the products are delivered to the customer. At the resource layer, enterprises need to ensure that data flow between their respective applications regardless of the implementation technologies that each enterprise uses. For example, customerrelated data that flow between CRM-App and Customer-App need to be understandable by their respective applications. Additionally, interface protocols used by these applications should be compatible with one another. For example, if CRMApp requires an acknowledgement for every outgoing message, then Customer-App should have acknowledgement transmission as part of its own interface protocol.
INTEROPERABILITY BASED ON ARTIFACTS Overview In a decentralized environment, collaboration refers to a process that lets two or more enterprises work together to achieve common goals. Although these enterprises agree to engage in this process, they continue functioning in an independent way by taking actions, making decisions, and
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developing new strategies so they can sustain their growth and maximize their benefits. All this happens without violating the collaboration agreements with other enterprises. Enterprise interoperability offers an opportunity to abstract any potential collaboration opportunity and overcome its complexity by helping business managers understand complex situations and address them properly. The collaboration models as shown in Figure 4 describe the most popular and commonly used ways to understand how business people see various interactions taking place with their partners without paying attention to constraints such as technologies, regulations, semantics, and business strategies (Baudin, 2004). Nowadays, various collaboration models deploy process-centric workflows to exchange messages and accomplish joint activities. Each process may involve Web services responsible for executing some of this process’s activities. Despite the costs and efforts of deploying such collaboration models and monitoring the execution progress of all the individual Web services, business analysts and managers would be overwhelmed with too many low-level details, which in turn would require specialized implementations to condense and present these details in a summarized way. Artifacts provide an appropriate, uniform picture of each collaboration model by enabling business analysts and managers to answer different questions related for example to the verification and finalization of customer bills, the current order fulfillment stage, and the fulfillment of particular order types and delivery time. In this context, a simple collaboration can take place between two enterprises where artifacts are sent from one side to another (i.e., unidirectional). Collaboration may also include several enterprises where artifacts can be sent and received by all partners (i.e., bidirectional). In some situations, partners can be involved in several disjoint collaborations and can concurrently exchange various artifacts (i.e., coordination). As a result, we define collaboration in terms of flows of exchanged ar-
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Figure 4. Types of collaboration models
tifacts between senders and receivers. Complex collaboration scenarios can be built upon atomic collaboration flows. Unlike traditional approaches that attempt to ensure interoperability by integrating business processes through Web services, we use here what we refer to as a “generic” Web service whose role is limited to receiving and sending artifacts as in Figure 5. Since artifacts are self-contained, each partner can select an appropriate Web service to update the artifact’s attributes and make this artifact transition from its current state to a new state with respect to this artifact’s lifecycle. In such a way, the partners do not reveal their internal applications or Web services. They only guarantee that they will process the artifacts based on the current attribute values and current states of these artifacts.
Interoperability Stack Description 1. Strategy layer: it enables business interaction using various collaboration models as depicted in Figure 4. This is done via the definition of artifacts by each business partner and artifact exchanges between the partners. The artifact exchanges are defined by their lifecycles. The service layer includes all necessary services or applications required to manipulate these artifacts. 2. Service layer: from a business perspective, a service represents a unit of work constrained by the business rules in a business process. It can be fully automated or performed by people who make the service completion non-deterministic. Technically speaking, a service updates artifact attributes and changes artifact states with respect to the artifact lifecycle. When the service is automated, Web services can be used to
Figure 5. Enterprise interoperability using artifacts and generic Web services
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implement loosely-coupled and platformindependent applications. These applications are especially relevant as collaboration is increasingly distributed across multiple independent enterprises. 3. Resource layer: it is decomposed into logical and physical parts. The logical part concerns the data that a business owns and manages as part of its day-to-day activities. The logical part in the resource layer includes also software resources such as operating systems, database management systems, etc. Finally, the physical part in the resource layer is about the hardware platforms that are deployed and connected through networks such as terminals, servers, routers, etc.
Artifact Definition In a manner consistent with (Nigam & Caswell, 2003), we define an artifact as a container of a set of related data items that define an information entity. Formally, an artifact is recursively defined as A = {di}, where di is either a data variable or itself an artifact. Since an artifact is considered as a chunk of potentially usable business data, its
types are not always conventional and are usually specified in unstructured form (http://ikt.hia.no/ perep/eipind.pdf, accessed April 2009). Unstructured data does not have a data model or one that is easily stored in databases. Data variables in an artifact can be ordered, unordered, simple objects, complex objects, finite, or infinite data through a recursive definition. The data models in artifacts can be represented as nested name-value pairs, Entity-Relationship schemas, or might be based on RDF or some Description Logic. We define the artifact life-cycle of artifact A as ALCA = (S, s0, Sf, L, T), where S is the set of states, s0 is the initial state, Sf is the set of final states, L is a set of transition labels, and T is a set of transitions. A label l in L consists of three components (event E, condition C, and action A) and is written as E[C]/A. A transition is defined from a state to another as t = (si, l, sj) where si and sj are in the same ALC. The order artifact from Figure 3 and its lifecycle details are in Table 3. The transitions between states are associated with Web services such as Estimate, RoutineApproval, ExecApproval, and Schedule. Each Web service is specified by a formal logical expression; if precondition then effect.
Table 3. Representation of artifact “order” Artifact: order Associated Attributes: ProdName: string prodType: string bid: integer profitMargin: [0..100] scheduleDate: date States: Created: boolean Updated: boolean Approved: boolean Fulfilled: boolean Archived: boolean
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Transition rules: Estimate: profitMargin PRE: DEF(ProdName) ^ DEF(prodType) ^ DEF(bid) EFF: Bid ≤ 400 → profitMargin ≤ 25% Bid > 350 → profitMargin > 20% RoutineApproval: approved PRE: DEF(bid) ^ DEF(profitMargin) EFF: Bid ≤ 100 → approved = true prodType = “sw” → approved = true prodType = “hw” ^ profitMargin > 10% → approved = true “else” → approved = false ExecApproval: Approved PRE: approved = false EFF: true → DEF(Approved) Schedule: scheduleDate PRE: DEF(ProdName)
Lifecycle
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In general, the specification of services can be expressed in terms of inputs, outputs, pre-conditions, and post-conditions using OWL-S and semantic Web services (Martin et al., 2003; McIlraith et al., 2001; Fritz et al., 2008; Deutsch et al., 2009). Together, these are defined as IOPE rules, standing for Inputs, Outputs, Preconditions and Effects. The precondition and effects may refer to artifacts and artifact attributes. In our context, artifact transitions correspond to OWLS descriptions. The conditional effects typically create new attribute values or change states. They are usually defined using logical formulas describing the artifact states before and after the service execution. In Table 3, we express some transition rules in terms of IOPE expressions that include artifact states and attributes.
Artifacts Exchange Mechanism Enterprise interoperability based on artifacts attempts to help enterprises set up collaboration with partners. The artifact concept not only describes a business entity, but also encompasses the knowledge about what to do without explaining how to do it. The exchanged artifact includes the attribute value pairs, the artifact lifecycle, and the current state with its potential transition. The capacity of including attributes, states, and lifecycle in a single entity called artifact conveys business intent and serves as a basis to propose an abstraction for any type of collaboration scenario. However, two partners can exchange many artifacts and sometimes wish to partially or totally hide their artifact contents. This typically leads to the proposal of a dedicated flow in which a specific artifact can be exchanged back and forth between two partners. In this context, we differentiate between public and private artifacts to protect the privacy of each partner. Public artifacts are exchanged between partners whereas private artifacts are managed internally by each partner. Each enterprise has relevant and complete definitions of artifact attributes and lifecycles that do not wish to reveal
to partners. Public artifacts are considered as reduced views of private artifacts. Consequently, partners should agree in advance on public artifact structures and their lifecycles. In this case, a mapping mechanism is required to specify how both public and private artifacts are mapped. In our earlier work (Hull, et. al., 2009) we had specified how this mapper can be developed by specifying appropriate access control-based restriction rules that limit access of certain states and transitions in a private artifact to external parties, thereby generating the public artifact. To illustrate, in our running example (Figure 2), the accounting department could select some artifacts, e.g., order and bill, to be sent to the bank department. This selection happens at the strategy layer. The values of some attributes are updated, and some states could be changed as well. The strategy layer then passes these artifacts to the service layer where additional actions are taken, e.g., preparing the private portions of these artifacts. Once this is done, the private portions of the artifacts are sent to the resource layer where they are encrypted so as to maintain security. The architecture of artifact-based interoperability is depicted in Figure 6 and includes the following elements. •
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Generic Web services are used only to establish collaboration between partners. They facilitate the exchange of business artifacts expressed in terms of input and output messages. Business artifacts are self-described business records. They can be modeled using any suitable information modeling approach such as Entity-Relationship diagrams in order to facilitate their understanding by business people. At the technical level, artifacts can be modeled as XML schema to describe exchanged input and output messages. Notice that the messages can take full advantages of WS-* standards to enable security (e.g., WS-Policy, http://
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Figure 6. Illustration of artifact exchange and processing
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www.w3.org/Submission/WS-Policy) and establish an agreement between two parties (e.g., WS-Agreement, http://www.ogf.org/ documents/GFD.107.pdf). All exchanged artifacts are considered public artifacts. Interceptor: Upon reception of a public artifact, the generic Web service invokes the interceptor which analyzes the received artifact. The interceptor enables security authentication and checks for business constraints and requirements. All required information is stored in databases (i.e., business rules, security credentials, etc). Artifact mappers: ensure mapping between public and private artifacts. Each partner has to define rules to specify how the mapping should occur. The private artifact is a generalization of the public artifact and supports the privacy of the partners. IOPE databases: enable separation between services and artifacts by using IOPE rules.
•
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Inference engine: transitions between artifact states are described in their artifact lifecycles. Each transition can be realized by the execution of one or more business web services. The IOPE rules specify how Web services should change the artifact states. In this context, the inference engine reads IOPE rules, reasons over these rules, and chooses the appropriate Web service. Artifact manager: invokes the selected Web services and updates artifact attributes and states, and sets up the current state.
We assume that the interceptor and the artifact mappers are optional components in the case that the collaboration does not consider private artifacts and there are no constraints to check when receiving an artifact.
Business Artifacts for E-Business Interoperability
ARTIFACT INTERACTION PATTERNS We define artifact interactions between partners as consisting of the following patterns: 1. Interactions between artifact lifecycles where each partner manages its artifacts separately. 2. Partners share a common artifact and potentially different ECA rules. 3. Subcontract interactions such as when one partner’s artifact is partially or completely processed by subcontractors. In the following figures, dashed lines represent the exchange of messages between the artifact life cycles, and plain lines represent the transitions within the life cycles.
Interactions Between Partner Artifacts Where Each Partner Manages Its Artifact Separated In this type of interaction, artifacts from separate business partners communicate by sending messages to each other. When an artifact A receives
a message from artifact B, it is treated by artifact A as an event under the ECA rule formation. Depending on the current state of artifact A, and other conditions, the artifact A makes transitions to the next state as described in its lifecycle. The artifact A may respond by sending a reply message to the artifact B which may treat the message reception as an event to make transitions in its lifecycle – this request-response pattern should be agreed upon in advance by both partners. This interaction pattern is illustrated in Figure 7. Although this figure shows only two interacting partners, this pattern can be extended to multiple interacting partners. In our running example, if artifact A and B are the client’s orders and the bill that the client has to pay, respectively, then artifact A could move from Updated to Approved states upon receipt of a message from artifact B that the customer’s bill has been paid. This is illustrated in Table 4. Such an approach can be used in situations that demand a high level of autonomy among interacting partners. Neither party is aware of each other’s artifacts – agreement is only about
Figure 7. Direct interactions between partner artifacts
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Table 4. ECA rules for order and bill artifacts if Bill receives a “Request of transition message” from Order and Order has the current state Updated and Bill has the current state Unpaid then Bill moves from state Unpaid state to Paid state and sends a “Confirmation of transition message” to Order if Order receives a “Confirmation of transition message” from Bill and Order has the current state Updated and Bill has the current state Paid then Order moves from state Updated state to Approved state
is illustrated in Figure 8. Although this figure only shows two interacting partners, this pattern can be extended to multiple interacting partners. This pattern can be used when the partners have full trust in each other, and can work together to solve a common business goal. In our running example, the Customer artifact could be jointly updated by the Sales and Bank enterprises such as in Figure 2, to ensure that the customer’s purchase and credit history are regularly maintained.
the messages to exchange and the conditions under which the message exchanges take place.
One Common Public Artifact and Private ECA Rules
One Common Public Artifact and Shared ECA Rules
This is a variant of the previous type of interaction, whereby the trust level among the partners is not high enough to share ECA rules. This involves the modeling of a public artifact, which is shared among the business partners along with private artifacts for each partner. The private artifacts are hidden from other partners (Figure 9). The ECA rules that govern public artifact updates based on information from a partner’s private artifacts are not revealed outside the partner’s organization. In Figure 9, the public artifact is Artifact C, which is governed by state changes
In this type of interaction, two partners agree to share a common artifact and contribute towards its lifecycle. The ECA rules that govern the behavior of each partner as part of this common artifact are also shared, that is to say that each partner is aware of the other’s ECA rules. Each partner, therefore, provides the appropriate Web services that help in implementing the appropriate state transitions of the common artifact’s lifecycle. This pattern Figure 8. One common artifact and shared ECA rules
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Figure 9. One common artifact and private ECA rules
in the private artifacts A and B.↜Here too, for example the Sales and Bank organizations could independently update the Customer artifact, while ensuring privacy for their respective ECA rules.
Subcontract Artifact Interactions In this type of interaction, there is only one artifact (artifact A in Figure 10). Some states of this artifact are executed by the partners of the business organization that owns artifact A. In other words, this is a typical interaction between a prime contractor and its subcontractors. Such an interaction can be employed when the prime
contractor trusts its subcontractors, and there is a well-defined working relationship among them.
IMPLEMENTATION In order to demonstrate the feasibility of our approach, we have developed a primary release of a prototype illustrating the benefits of an artifactbased modeling. The prototype aims to be a frontend interface for each partner in a distributed collaboration. It implements the architecture in Figure 6 to manipulate data entities as artifact records and artifact life-cycle interactions through
Figure 10. Subcontract artifacts
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generic Web services. It also deploys and executes the mapping rules between public and private artifacts depending on the collaboration patterns and by using mapping rules triggered with respect to the current states of public and private Web services. The prototype architecture is extensible and modular to allow effortless business integration with legacy systems and provides tools amenable to business people and intuitive for business communications. The prototype’s architecture consists of three independent modules: Artifact Manager, Web Service Manager, and Rule Base Manager. Each module is self-contained and implemented as a set of reusable plug-in in the Eclipse 3.4 3.5.1 runtime platform. As illustrated in Figure 11, the prototype offers user-friendly interfaces based on SWT/JFace components to define several collaboration projects including appropriate artifacts, states, generic Web services, and mapping rules. A graphical editor built on GEF/EMF Frameworks helps business people to graphically construct artifact life-cycles and establish interactions between their states. However, dedicated editors Figure 11. Prototype snapshot
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allow linking public and private artifacts through messages, transitions and triggering conditions. The deployment and execution of web services are ensured by the integration of ActiveBPEL plug-in which takes care of persistence, queues, alarms, and many other execution details. The prototype includes SWT Web Brower features to send or receive public artifacts manually or automatically. In the prototype, we also pay attention to the exchange format and the storage of business artifacts. We thus developed an XML Schema to represent artifact data, states and lifecycles. As depicted in Figure 12, the schema enables the representation of semi-structured data which allows the addition of attribute-value pairs without a prior predefined data structure. Moreover, the artifact data can evolve to satisfy new business requirements or changes. In this context, the generic web services remains intact and the business rules should only be updated by each partner to internally specify how to handle the new data. That is to say, the change in the public artifact is managed individually and independently by each
Business Artifacts for E-Business Interoperability
partner. As depicted in the Figure 12, the lifecycle, which is a graph of states, is presented by the GraphML (Brandes et al., 2002) to allow various operations such us graph processing, drawing and reporting. The prototype primary release has been successfully tested to exchange public artifacts and applying mapping rules to synchronize public and private artifact lifecycles. The application of the artifact-based collaboration requires the substitution of activity-centric processes with data-centric processes to get full benefits of our proposed approach.
CONCLUSION AND FUTURE RESEARCH DIRECTIONS In this chapter, we examined some key issues related to ensuring a smooth enterprise interoperability. Interoperability raises several issues such as lack of common semantics for inter-business
interaction, data inconsistencies, and policy incompatibilities. Traditional approaches have promoted process-centric solutions, which have not been enough to address these issues at the business level. Additionally, enterprises should be able to quickly adapt their e-business interactions in response to changing market conditions. A low-level process-centric modeling approach makes it difficult for enterprises to achieve this dynamism. Enterprises, therefore, need to view and control their operations at a higher level of abstraction than process implementations. In order to address these shortcomings, we proposed an artifact-centric solution that can manage e-business interactions at a level of abstraction that is meaningful for business managers and analysts. Through our interoperability stack comprising strategic, service and resource layers, we demonstrated how e-business interactions can be modeled and implemented via artifact exchanges among enterprises. We, also, introduced several interaction patterns that is to say several ways in
Figure 12. Artifact representation along with its lifecycle
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which enterprises can interact with each other by exchanging artifacts. Expressing e-business interactions as combinations of these patterns also enables them to become more flexible and reusable. For future work, we seek to implement and test our approach through real-life examples. Since interactions among autonomous organizations typically involve conflicts due to differing agendas, we will also extend our earlier work on B2B conflict resolution at the service layer (Maamar et al., 2008) to incorporate artifact-based interactions.
REFERENCES Arsanjani, A. (2002). Developing and integrating enterprise components and services. Communications of the ACM, 45(10). Baldoni, M., Baroglio, C., Chopra, A. K., Desai, N., Patti, V., & Singh, M. P. (2009). Choice, interoperability, and conformance in interaction protocols and service choreographies. In Proceedings of the 8th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS’2009), Budapest, Hungary. Baudin, V., Drira, K., Villemur, T., & Tazi, S. (2004). A model-driven approach for synchronous dynamic collaborative e-learning. In Ghaoui, C. (Ed.), E-education applications: Human factors and innovative approaches (pp. 44–65). Information Science Publishing. Bhattacharya, K., Gerede, C. E., Hull, R., Liu, R., & Su, J. (2007). Towards formal analysis of artifact-centric business process models. In Proceedings of International Conference on Business Process Management (BPM’2007), (pp. 288-304). Bhattacharya, K., Guttman, R., Lyman, K., Heath, F. F. III, Kumaran, S., & Nandi, P. (2005). A model-driven approach to industrializing discovery processes in pharmaceutical research. IBM Systems Journal, 44(1), 145–162.
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Brandes, U., Eiglsperger, M., Herman, I., Himsolt, M., & Marshall, M. S. (2002). GraphML progress report: Structural layer proposal. Proceedings of the 9th International Symposium Graph Drawing (GD ‘01). LNCS 2265, (pp. 501-512). SpringerVerlag. Cimander, R., & Kubicek, H. (2009). Organizational interoperability and organizing for interoperability in e-government. In Second European Summit on Interoperability in the iGovernment, (pp. 109–122). Cohn, D., & Hull, R. (2009). Business artifacts: A data-centric approach to modeling business operations and processes. Bulletin of the IEEE Computer Society Technical Committee on Data Engineering, 32(3). Deutsch, A., Hull, R., Patrizi, F., & Vianu, V. (2009). Automatic verification of data-centric business processes. In Proceedings of the 12th International Conference on Database Theory (ICDT), St. Petersburg, Russia, (pp. 252-267). ETSI. (2006). Achieving technical interoperability–the ETSI approach. ETSI White Paper No. 3. Retrieved on December 24, 2009, from http:// etsi.org/WebSite/document/whitepapers/IOP%20 whitepaper%20Edition%203%20final.pdf Fritz, C., Hull, R., & Su, J. (2009). Automatic construction of simple artifact-based workflows. In Proceedings of the 12th International Conference on Database Theory (ICDT’2009), St. Petersburg, Russia, (pp. 252-267). Gailly, F., & Poels, G. (2009). Using the REA ontology to create interoperability between e-collaboration modeling standards. In The Proceedings of the 21st International Conference on Advanced Information Systems Engineering (CAiSE’2009), Amsterdam, The Netherlands, (pp. 395-409).
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Hall, J., & Koukoulas, K. (2008). Semantic interoperability for e-business in the ISP service domain. In Proceedings of the International Conference on e-Business (ICE-B’2008), Porto, Portugal. Hull, R. (2008). Artifact-centric business process models: Brief survey of research results and challenges. In Proceedings of OTM Conferences’2008, Monterrey, Mexico. Hull, R., Narendra, N. C., & Nigam, A. (2009) Facilitating workflow interoperation using artifact-centric hubs. In Proceedings of The Seventh International Conference on Service-Oriented Computing (ICSOC/ServiceWave’2009), Stockholm, Sweeden. Janner, T., Lampathaki, F., Hoyer, V., Mouzakitis, S., Charalabidis, Y., & Schroth, C. (2008). A core component-based modeling approach for achieving e-business semantics interoperability. Journal of Theoretical and Applied Electronic Commerce Research, 3(3). Kumaran, S., Liu, R., & Wu, F. Y. (2008). On the duality of information-centric and activity-centric models of business processes. In The Proceedings of the 20th International Conference on Advanced Information Systems Engineering (CAiSE’2008), Montpellier, France. Li, M.-S., Cabral, R., Doumeingts, G., & Popplewell, K. (2006). Enterprise interoperability research roadmap, final version (Version 4.0). European Commission. Liang, P., He, K., & Liu, J. (2005). The interoperability between different e-business specifications. In The Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC’2005), Las Vegas, Nevada, USA.
Maamar, Z., Benslimane, D., Kouadri Mostéfaoui, G., Sattanathan, S., & Ghedira, C. (2006). Developing interoperable business processes using Web services and policies. In The Proceedings of the 2nd International Conference on Interoperability for Enterprise Software and Applications (I-ESA’2006), Bordeaux, France. Maamar, Z., Thiran, P., Narendra, N. C., & Sattanathan, S. (2008). A Web services-based framework for modeling B2B applications. In The Proceedings of the 22nd International Conference on Advanced Information Networking and Applications (AINA’2008), Okinawa, Japan. Martin D. (2003). OWL-S semantic markup for Web services. W3C Member Submission, November 2003. McIlraith, S. A., Son, T. C., & Zeng, H. (2001). Semantic Web services. IEEE Intelligent Systems, 16(2), 46–53. Mocan, A., Facca, F. M., Loutas, N., Peristeras, V., Goudos, S. K., & Tarabanis, K. A. (2009). Solving semantic interoperability conflicts in cross-border e-government service. International Journal on Semantic Web and Information Systems, 5(1), 1–47. Muller, D., Reichert, M., & Herbst, J. (2008). A new paradigm for the enactment and dynamic adaptation of data-driven process structures. In Proceedings of the 20th International Conference on Advanced Information Systems Engineering (CAiSE’2008), (pp. 48-63). Montpellier, France. Nandi, P., & Kumaran, S. (2005). Adaptive business objects-a new component model for business integration. In Proceedings of the International Conference on Enterprise Information Systems (ICEIS’2005), Miami, Florida.
Ma, Y.S. (2009). Towards semantic interoperability of collaborative engineering in oil production industry. Concurrent Engineering: R &A, 17(2).
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Narendra, N. C., Badr, Y., Thiran, P., & Maamar, Z. (2009). Towards a unified approach for business process modeling using context-based artifacts and Web services. In Proceedings of the IEEE International Conference on Services Computing (SCC’2009), (pp. 332-339). Bangalore, India. Nigam, A., & Caswell, N. S. (2003). Business artifacts: An approach to operational specification. IBM Systems Journal, 42(3), 428–445. Norta, A., Hendrix, M., & Grefen, P. (2006). A pattern repository for establishing inter-organizational business processes. Beta Working Papers, Vol. 175. Eindhoven University of Technology. Peristeras, V., & Tarabanis, K. (2006). The connection, communication, consolidation, collaboration interoperability. International Journal of Interoperability in Business Information Systems, 1(1), 61–72. Silva, N., Rocha, J., & Cardoso, J. (2003). E-business interoperability through ontology semantic mapping. In Proceedings of the Processes and Foundations for Virtual Organizations, IFIP TC5/ WG5.5 Fourth Working Conference on Virtual Enterprises (PRO-VE’2003), Lugano, Switzerland. Touzi, J., Lorre, J.P., Benaben, F. & Pingaud, H. (2007). Interoperability through model-based generation: The case of the Collaborative Information System (CIS). Enterprise Interoperability, 407-416.
KEY TERMS AND DEFINITIONS Artifact: It is a self-describing collection of closely related data that represents a business record, which describes details of goods and services provided or used by the business. Composite Web Service: Composition targets users’ requests that cannot be satisfied by any single, available Web service, whereas a composite Web service obtained by combining available Web services may be used. Interoperability: It is the ability of systems to collaborate despite distribution and heterogeneous obstacles. Ontology: It is the conceptualization of the knowledge of a certain domain. Pattern: It identifies a set of recurring events/ objects that arise/appear constantly. Process: It is a set of activities that are connected together according to a certain execution chronology. Web Service: It is “a software application identified by a URI, whose interfaces and binding are capable of being defined, described, and discovered by XML artifacts, and supports direct interactions with other software applications using XML-based messages via Internet-based applications’’ (W3C).
This work was previously published in Electronic Business Interoperability: Concepts, Opportunities and Challenges, edited by Ejub Kajan, pp. 15-36, copyright 2011 by Business Science Reference (an imprint of IGI Global).
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Adaptive Web Presence and Evolution through Web Log Analysis Xueping Li University of Tennessee, USA
INTRODUCTION The Internet has become a popular medium to disseminate information and a new platform to conduct electronic business (e-business) and electronic commerce (e-commerce). With the rapid growth of the WWW and the intensified competition among the businesses, effective web presence is critical to attract potential customers and retain current customer thus the success of the business. This poses a significant challenge DOI: 10.4018/978-1-60960-587-2.ch311
because the web is inherently dynamic and web data is more sophisticated, diverse, and dynamic than traditional well-structured data. Web mining is one method to gain insights into how to evolve the web presence and to ultimately produce a predictive model such that the evolution of a given web site can be categorized under its particular context for strategic planning. In particular, web logs contain potentially useful information and the analysis of web log data have opened new avenues to assist the web administrators and designers to establish adaptive web presence and evolution to fit user requirements.
Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
Adaptive Web Presence and Evolution through Web Log Analysis
BACKGROUND
MAIN FOCUS
People have realized that web access logs are a valuable resource for discovering various characteristics of customer behaviors. Various data mining or machine learning techniques are applied to model and understand the web user activities (Borges and Levene, 1999; Cooley et al., 1999; Kosala et al., 2000; Srivastava et al., 2000; Nasraoui and Krishnapuram, 2002). The authors in (Kohavi, 2001; Mobasher et al., 2000) discuss the pros and cons of mining the e-commerce log data. Lee and Shiu (Lee and Shiu, 2004) propose an adaptive website system to automatically change the website architecture according to user browsing activities and to improve website usability from the viewpoint of efficiency. Recommendation systems are used by an ever-increasing number of e-commerce sites to help consumers find products to purchase (Schafer et al, 2001). Specifically, recommendation systems analyze the users’ and communities’ opinions and transaction history in order to help individuals identify products that are most likely to be relevant to their preferences (e.g. Amazon. com, eBay.com). Besides web mining technology, some researches investigate on Markov chain to model the web user access behavior (Xing et al., 2002; Dhyani et al., 2003; Wu et al., 2005). Web log analysis is used to extract terms to build web page index, which is further combined with text-based and anchor-based indices to improve the performance of the web site search (Ding and Zhou, 2007). A genetic algorithm is introduced in a model-driven decision-support system for web site optimization (Asllani and Lari, 2007). A web forensic framework as an alternative structure for clickstream data analysis is introduced for customer segmentation development and loyal customer identification; and some trends in web data analysis are discussed (Sen et al., 2006).
Broadly speaking, web log analysis falls into the range of web usage mining, one of the three categories of web mining (Kosala and Blockeel, 2000; Srivastava et al., 2002). There are several steps involved in web log analysis: web log acquisition, cleansing and preprocessing, and pattern discovery and analysis.
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Web Log Data Acquisition Web logs contain potentially useful information for the study of the effectiveness of web presence. Most websites enable logs to be created to collect the server and client activities such as access log, agent log, error log, and referrer log. Access logs contain the bulk of data including the date and time, users’ IP addresses, requested URL, and so on. Agent logs provide the information of the users’ browser type, browser version, and operating system. Error logs provide problematic and erroneous links on the server such as “file not found”, “forbidden to access”, et al. Referrer logs provide information about web pages that contain the links to documents on the server. Because of the stateless characteristic of the Hyper Text Transfer Protocol (HTTP), the underlying protocol used by the WWW, each request in the web log seems independent of each other. The identification of user sessions, in which all pages that a user requests during a single visit, becomes very difficulty (Cooley et al., 1999). Pitkow (1995, 1997, 1998) pointed out that local caching and proxy servers are two main obstacles to get reliable web usage data. Most browsers will cache the recently pages to improve the response time. When a user clicks the “back” button in a browser, the cached document is displayed instead of retrieving the page from the web server. This process can not be recorded by the web log. The existence of proxy servers makes it even harder
Adaptive Web Presence and Evolution through Web Log Analysis
to identify the user session. In the web server log, requests from a proxy server will have the same identifier although the requests may come from several different users. Because of the cache ability of proxy servers, one requested page in web server logs may actually be viewed by several users. Besides the above two obstacles, the dynamic content pages such as Active Server Pages (ASP) and Java Server Pages (JSP) will also create problems for web logging. For example, although the same Uniform Resource Locator (URL) appears in a web server log, the content that is requested by users might be totally different. To overcome the above obstacles of inaccuracy web log resulting from caching, proxy server and dynamic web pages, specialized logging techniques are needed. One way is to configure the web server to customize the web logging. Another is to integrate the web logging function into the design of the web pages. For example, it is beneficial to an e-commerce web site to log the customer shopping cart information which can be implemented using ASP or JSP. This specialized log can record the details that the users add items to or remove items from their shopping carts thus to gain insights into the user behavior patterns with regard to shopping carts. Besides web server logging, package sniffers and cookies can be used to further collection web log data. Packet sniffers can collect more detailed information than web server log by looking into the data packets transferred on the wire or air (wireless connections). However, it suffers from several drawbacks. First, packet sniffers can not read the information of encrypted data. Second, it is expensive because each server needs a separate packet sniffer. It would be difficult to manage all the sniffers if the servers are located in different geographic locations. Finally, because the packets need to be processed by the sniffers first, the usage of packet sniffers may reduce the performance of the web servers. For these reasons, packet sniffing is not widely used as web log analysis and other data collecting techniques.
A cookie is a small piece of information generated by the web server and stored at the client side. The client first sends a request to a web server. After the web server processes the request, the web server will send back a response containing the requested page. The cookie information is sent with the response at the same time. The cookie typically contains the session id, expiration date, user name and password and so on. This information will be stored at the client machine. The cookie information will be sent to the web server every time the client sends a request. By assigning each visitor a unique session id, it becomes easy to identify the sessions. However, some users prefer to disable the usage of cookies on their computers which limits the wide application of cookies.
Web Log Data Cleansing and Preprocessing Web log data cleansing and preprocessing is critical to the success of the web log analysis. Even though most of the web logs are collected electronically, serious data quality issues may arise from a variety of sources such as system configuration, software bugs, implementation, data collection process, and so on. For example, one common mistake is that the web logs collected from different sites use different time zone. One may use Greenwich Mean Time (GMT) while the other uses Eastern Standard Time (EST). It is necessary to cleanse the data before analysis. There are some significant challenges related to web log data cleansing. One of them is to differentiate the web traffic data generated by web bots from that generated by “real” web visitors. Web bots, including web robots and spiders/ crawlers, are automated programs that browse websites. Examples of web bots include Google Crawler (Brin and Page, 1998), Ubicrawler (Boldi et al. 2004), and Keynote (www.keynote.com). The traffic from the web bots may tamper the visiting statistics, especially in the e-commerce domain. Madsen (Madsen, 2002) proposes a page
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tagging method of clickstream collection through the execution of JavaScript at the client’s browsers. Other challenges include the identification of sessions and unique customers. Importing the web log into traditional database is another way to preprocess the web log and to allow further structural queries. For example, web access log data can be exported to a database. Each line in the access log represents a single request for a document on the web server. The typical form of an access log of a request is as follows:hostname - - [dd/Mon/yyyy:hh24:mm:ss tz] request status bytes An example is:uplherc.upl.com - - [01/ Aug/1995:00:00:07 -0400] “GET / HTTP/1.0” 304 0which is from the classical data collected from the web server at the NASA’s Kennedy Space Center. Each entry of the access log consists of several fields. The meaning of each field is as following: •
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Host name: A hostname when possible; otherwise, the IP address if the host name could not be looked up. Timestamp: In the format “ dd/Mon/ yyyy:hh24:mm:ss tz “, where dd is the day of the month, Mon is the abbreviation name of the month, yyyy is the year, hh24:mm:ss is the time of day using a 24-hour clock, and tz stands for time zone as shown in the example “[01/Aug/1995:00:00:07 -0400]”. For consistency, hereinafter we use “day/month/year” date format. Request: Requests are given in quotes, for example “GET / HTTP/1.0”. Inside the quotes, “GET” is the HTTP service name, “/” is the request object, and “HTTP/1.0” is the HTTP protocol version. HTTP reply code: The status code replied by the web server. For example, a reply code “200” means the request is successfully processed. The detailed description about HTTP reply codes refers to RFC (http://www.ietf.org/rfc).
•
Reply Bytes: This field shows the number of bytes replied.
In the above example, the request came from the host “uplherc.upl.com” at 01/Aug/1995:00:00:07. The requested document was the root homepage “/”. The status code was “304” which meant that the client copy of document was up to date and thus “0” bytes were responded to the client. Then, each entry in the access log can be mapped into a field of a table in a database for query and pattern discovery.
Pattern Discovery and Analysis A variety of methods and algorithms have been developed in the fields of statistics, pattern recognition, machine learning and data mining (Fayyad et al., 1994; Duda et al., 2000). This section describes the techniques that can be applied in the web log analysis domain. 1. Statistical Analysis: It is the most common and simple yet effective method to explore the web log data and extract knowledge of user access patterns which can be used to improve the design of the web site. Different descriptive statistical analyses, such as mean, standard deviation, median, frequency, and so on, can be performed on variables including number of requests from hosts, size of the documents, server reply code, requested size from a domain, and so forth. There are a few interesting discoveries about web log data through statistical analysis. Recently, the power law distribution has been shown to apply to the web traffic data in which the probability P(x) that a performance measure x decays as a power law, following P(x) ~ x–α. A few power law distributions have been discovered: the number of visits to a site (Adamic et al., 1999), the number of page within a site (Huberman et al., 1999), and
Adaptive Web Presence and Evolution through Web Log Analysis
the number of links to a page (Albert et al., 1999; Barabási et al., 1999). Given the highly uneven distribution of the documents request, the e-commerce websites should adjust the caching policy to improve the visitor’s experience. C. Cunha (1997) point out that small images account for the majority of the traffic. It would be beneficial if the website can cache these small size documents in memory. For e-commerce websites, the highly populated items should be arranged to allow fast access because these items will compose over 50% of the total requests. These insights are helpful for the better design and adaptive evolution of the web sites. 2. Clustering and Classification: Techniques to group a set of items with similar characteristics and/or to map them into predefined classes. In the web log analysis domain, there are two major clusters of interest to discover: web usage clustering and web pages clustering. Clustering of web usage can establish the groups of users that exhibit similar browsing behaviors and infer user demographic information. Such knowledge is especially useful for marketing campaign in e-commerce applications and personalized web presence. On the other hand, clustering analysis of the web pages can discover the web pages with related content. This is useful for the development of Internet search engine. Classification can be accomplished through well developed data mining algorithms including Bayesian classifier, k-nearest neighbor classifier, support vector machines, and so on (Duda et al., 2000). 3. Associative Rules: Associative rules mining is to find interesting associations or correlations among large data sets. In the web log mining domain, one is interested in discovering the implications or correlations of user access patterns. For example, users who access page A also visit page B; customers who purchase product C also
purchase product D. A typical associative rule application is market basket analysis. This knowledge is useful for effective web presence and evolution by laying out user friendly hyper links for easier access. It can help for e-commerce web site to promote products as well. 4. Sequential Patterns: The sequential patterns mining attempts to find inter-transaction patterns such that the presence of one event is followed by another (Mannila et al., 1995, Srikant and Agrawal, 1996). In the context of web log analysis, the discovery of sequential patterns helps to predict user visit patterns and to target certain groups based on these patterns.
FUTURE TRENDS With the explosive growth of the Internet and ever increasing popularity of e-commerce, privacy is becoming a sensitive topic that attracts many research efforts. How to make sure the identity of an individual is not compromised while effective web log analysis can be conducted is a big challenge. An initiative called Platform for Privacy Preference (P3P) is ongoing at the World Wide Web Consortium (W3C). How to analyze the web log online and make timely decision to update and evolve the web sites is another promising topic.
CONCLUSION An effective web presence is crucial to enhance the image of a company, increase the brand and product awareness, provide customer services, and gather information. The better understanding of the web’s topology and user access patterns, along with modeling and designing efforts, can help to develop search engines and strategies to evolve the web sites. Web logs contain potentially useful information for the study of the effective-
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ness of web presence. The components of web log analysis are described in this chapter. The approaches and challenges of acquisition and preprocessing of web logs are presented. Pattern discovery techniques including statistical analysis, clustering and classification, associative rules and sequential pattern are discussed in the context of web log analysis towards adaptive web presence and evolution.
REFERENCES Adamic, L.A. and Huberman, B.A. (1999). The Nature of Markets in the World Wide Web. Computing in Economics and Finance, no. 521. Albert, R., Jeong, H., & Barabási, A. L. (1999). The Diameter of the World Wide Web. Nature, 401, 130–130. doi:10.1038/43601 Asllani, A., & Lari, A. (2007). Using genetic algorithm for dynamic and multiple criteria web-site optimizations. European Journal of Operational Research, 176(3), 1767–1777. doi:10.1016/j. ejor.2004.03.049
Cooley, R., Mobashar, B., & Shrivastava, J. (1999). Data Preparation for Mining World Wide Web Browsing Patterns. Knowledge and Information Systems, 1(1), 5–32. Cunha, C. (1997). Trace Analysis and Its Application to Performance Enhancements of Distributed Information Systems. Doctoral thesis, Department of Computer Science, Boston University. Dhyani, D., & Bhowmick, S. and Ng, Wee-Kong (2003). Modeling and Predicting Web Page Accesses Using Markov Processes. 14th International Workshop on Database and Expert Systems Applications (DEXA’03), p.332. Ding, C., & Zhou, J. (2007). Information access and retrieval: Log-based indexing to improve web site search. Proceedings of the 2007 ACM symposium on Applied computing SAC ‘07, 829-833. Duda, R. O., Hart, P. E., & Stork, D. G. (2000). Pattern Classification. John Wiley & Sons, Inc. Fayyad, U., Piatetsky-Shaprio, G., & Smyth, P. (1994) From data mining to knowledge discovery: an overview. In Proc. ACM KDD.
Barabási, A., & Albert, R. (1999). Emergence of Scaling in Random Networks. Science, 286(5439), 509–512. doi:10.1126/science.286.5439.509
Huberman, B. A., & Adamic, L. A. (1999). Growth Dynamics of the World Wide Web. Nature, 401, 131.
Boldi, P., Codenotti, B., Santini, M., & Vigna, S. (2004a). UbiCrawler: a scalable fully distributed Web crawler. Software, Practice & Experience, 34(8), 711–726. doi:10.1002/spe.587
Kohavi, R. (2001). Mining E-Commerce Data: The Good, the Bad, and the Ugly. KDD’ 2001 Industrial Track, San Francisco, CA.
Borges, J., & Levene, M. (1999). Data mining of user navigation patterns, in: H.A. Abbass, R.A. Sarker, C. Newton (Eds.). Web Usage Analysis and User Profiling, Lecture Notes in Computer Science, Springer-Verlag, pp: 92–111. Brin, S. and Page, L. (1998). The anatomy of a large-scale hypertextual Web search engine. Computer Networks and ISDN Systems, 30(17):107–117.
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Kosala, R. and Blockeel H. (2000). Web Mining Research: A Survey. SIGKDD: SIGKDD Explorations: Newsletter of the Special Interest Group (SIG) on Knowledge Discovery & Data Mining, 2(1): 1- 15. Lee, J. H., & Shiu, W. K. (2004). An adaptive website system to improve efficiency with web mining techniques. Advanced Engineering Informatics, 18, 129–142. doi:10.1016/j.aei.2004.09.007
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Madsen, M.R. (2002). Integrating Web-based Clickstream Data into the Data Warehouse. DM Review Magazine, August, 2002. Mannila, H., Toivonen, H., & Verkamo, A. I. (1995). Discovering frequent episodes in sequences. In Proc. of the First Int’l Conference on Knowledge Discovery and Data Mining, pp. 210-215, Montreal, Quebec.
Srivastava, J., Cooley, R., Deshpande, M., & Tan, P.-N. (2000). Web usage mining: discovery and applications of usage patterns from web data. SIGKDD Explorations, 1(2), 12–23. doi:10.1145/846183.846188 Srivastava, J., Desikan, P., & Kumar, V. (2002). Web Mining: Accomplishments and Future Directions. Proc. US Nat’l Science Foundation Workshop on Next-Generation Data Mining (NGDM).
Nasraoui, O., & Krishnapuram, R. (2002). One step evolutionary mining of context sensitive associations and web navigation patterns. SIAM Conference on Data Mining, Arlington, VA, pp: 531–547.
Wu, F., Chiu, I., & Lin, J. (2005). Prediction of the Intention of Purchase of the user Surfing on the Web Using Hidden Markov Model. Proceedings of ICSSSM, 1, 387–390.
Pitkow, J. E. (1995). Characterizing browsing strategies in the World Wide Web. Computer Networks and ISDN Systems, 27(6), 1065–1073. doi:10.1016/0169-7552(95)00043-7
Xing, D., & Shen, J. (2002). A New Markov Model For Web Access Prediction. Computing in Science & Engineering, 4(6), 34–39. doi:10.1109/ MCISE.2002.1046594
Pitkow, J. E. (1997). In search of reliable usage data on the WWW. Computer Networks and ISDN Systems, 29(8), 1343–1355. doi:10.1016/S01697552(97)00021-4 Pitkow, J.E. (1998). Summary of WWW characterizations. Computer Networks and ISDN Systems, 30(1-7): 551-558. Schafer, J. B., Konstan, A. K., & Riedl, J. (2001). E-Commerce Recommendation Applications. Data Mining and Knowledge Discovery, 5(1-2), 115–153. doi:10.1023/A:1009804230409 Sen, A., Dacin, P. A., & Pattichis, C. (2006). Current trends in web data analysis. Communications of the ACM, 49(11), 85–91. doi:10.1145/1167838.1167842 Srikant, R., & Agrawal, R. (1996). Mining sequential patterns: Generalizations and performance improvements. In Proc. of the Fifth Int’l Conference on Extending Database Technology, Avignon, France.
KEY TERMS AND DEFINITIONS Web Access Log: Access logs contain the bulk of data including the date and time, users’ IP addresses, requested URL, and so on. The format of the web log varies depending on the configuration of the web server. Web Agent Log: Agent logs provide the information of the users’ browser type, browser version, and operating system. Web Error Log: Error logs provide problematic and erroneous links on the server such as “file not found”, “forbidden to access”, et al. and can be used to diagnose the errors that the web serve encounters in processing the requests. Web Log Acquisition: The process of obtaining the web log information. The web logs can be recorded through the configuration of the web server. Web Log Analysis: The process of parsing the log files from a web server to derive information about the user access patterns and how the server processes the requests. It helps to assist the web
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administrators to establish effective web presence, assess marketing promotional campaigns, and attract customers. Web Log Pattern Discovery: The process of application of data mining techniques to discover the interesting patterns from the web log data. Web Log Preprocessing and Cleansing: The process of detecting and removing inaccurate web log records that arise from a variety of sources such as system configuration, software bugs, implementation, data collection process, and so on.
Web Presence: A collection of web files focusing on a particular subject that is presented on a web server on the World Wide Web. Web Referrer Log: Referrer logs provide information about web pages that contain the links to documents on the server. Web Usage Mining: The subfield of web mining that aims at analyzing and discovering interesting patterns of web server log data.
This work was previously published in Encyclopedia of Data Warehousing and Mining, Second Edition, edited by John Wang, pp. 12-17, copyright 2009 by Information Science Reference (an imprint of IGI Global).
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On-Line Credit Card Payment Processing and Fraud Prevention for E-Business James G. Williams University of Pittsburgh, USA Wichian Premchaiswadi Siam University, Thailand
ABSTRACT As the volume of purchases for products and services on the Internet has increased and the chosen method of payment is a credit or debit card, e-commerce merchants must be capable of accepting such payment methods. Unfortunately, cyber-criminals have found ways to steal personal information found on credit cards and debit cards and fraudulently use this information to purchase products and services which costs merchants lost revenue and fees for chargebacks. DOI: 10.4018/978-1-60960-587-2.ch312
This article discusses the process by which credit card payments are processed beginning with the e-commerce merchant’s web site to a credit card processor or service gateway to the credit card company’s network to the issuing bank’s network with an accept or decline response being returned to the merchant’s shopping cart system via the same networks. The article addresses the issue of credit card fraud in terms of how the cybercriminals function and the potential solutions used to deter these attempts by the cybercriminals. A list of preventive measures that should be used by e-commerce merchants is provided.
Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
On-Line Credit Card Payment Processing and Fraud Prevention for E-Business
INTRODUCTION Consumers in the United States spend nearly 1 trillion dollars each year using a credit card over the internet (Woolsey and Schulz, 2009). Accepting credit cards is essential for any e-commerce Web site. Processing credit cards over the Internet is one of the fastest growing segments of business transactions today. This type of transaction or “card-not-present” transaction requires a special type of merchant account. In the early days of credit card usage, to accept credit cards, a merchant needed a merchant account through a bank. But today there are a number of services, generally referred to as credit card processors or merchant account services, which will permit a merchant to accept credit card payments online without their own merchant account. There are actually three different methods for processing credit card payments using a merchant account service. These are: 1. Real-Time Processing: Real-time processing allows e-commerce merchants to link their e-commerce shopping cart with a gateway merchant service which will automatically process credit card payments. 2. Virtual Terminal (Online Interface): An e-commerce merchant can also process credit card transactions, manually, 24 hours a day by logging in online and submitting a secure form through a merchant account interface. A merchant can use this to process credit card payments while taking the customer’s information over the phone if the merchant is able to access the Internet at high speed while talking to the customer. 3. Automated Recurring Billing (ARB): Some e-commerce merchant services need to charge customers on a monthly or account threshold basis. Some merchant account services allow the merchant to set the time interval or account threshold level and some services allow a merchant to upload multiple
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subscriptions using a batch file like Microsoft Excel. PayPal is generally accepted as the most widely used online merchant account service with more than 150 million users across the world. VeriSign operates a competing service called Payflow that is typically used by merchants with a high volume of transactions each month. Although the number of merchant account service providers continues to increase, some of the more popular one are listed below (TopTenReviews, 2009): Flagship Merchant Services Gomerchant Merchant Accounts Merchant Accounts Express MerchantWarehouse Electronic Transfer Inc. E-Commerce Exchange NorthAmericanBancard Total Merchant Services Charge Merchant Credit Card Free AuthNet Merchant Credit Card Companies that sell merchandise and services over the Internet are referred to as e-tailers or ecommerce merchants. These credit card processing services make it easy for e-tailers to start accepting credit cards for purchases of their products and services.
BACKGROUND Who Are the Participants in OnLine Credit Card Purchases? Consumers and Merchants The consumer is an individual or organization that has the intent of making a purchase. They have money or credit and they desire goods
On-Line Credit Card Payment Processing and Fraud Prevention for E-Business
and services. The merchant is the one with the goods and services and is looking to sell them to consumers. Consumers are motivated to select a particular merchant by things such as price, service, selection or preference. But the merchant’s primary motivation is to make money by selling the goods or services for more money than they paid for them. This money between what they bought it for and what they sold it for is called their margin. There are several different methods to exchange money for products and services such as bartering, cash, checks, debit cards, installment payments or credit cards. When credit cards are used, the consumer and the merchant both have banks that they are working with that process the credit card payment transactions.
Issuing Bank Consumers get their credit cards from a bank or credit union, called the “issuing bank.” Sometimes an issuing bank is simply called an “issuer.” An issuing bank may not just be associated with major credit card brands such as American Express, MasterCard and Visa, but also with credit cards called “private label credit cards.” These are the ones that department stores or shops offer, such as Sears and Target credit cards. Issuing banks are lending institutions that support these credit cards by granting and managing extended credit. Some examples of these are Bank of America, Citibank, MBNA, Household Financial, GE and Wells Fargo. The purpose of the issuing bank is to grant credit directly to a consumer. They, typically, have a consumer fill out an application, check the applicant’s credit history and maintain their account. The issuing bank is the one that decides what a consumer’s credit limit is, based on credit history and current debt load. There are thousands of issuing banks in the United States. In Canada and the United Kingdom as well as most other countries in the world there are far fewer banks, so the number of issuing banks is much smaller. Issuing banks make money on the interest
the consumer pays on outstanding balances from previous purchases, and they get a portion of every purchase a consumer makes with the credit card from a merchant.
Acquiring Bank The acquiring bank represents the e-commerce merchant. The acquiring bank processes all of the merchant’s credit card payments with the associations (American Express, MasterCard, Visa, etc.), and provide the merchant with reconciliation data and other financial tools. The acquiring bank also makes money on every transaction a merchant processes. There are many acquiring banks in the United States and abroad, and merchants are free to move from one acquirer to another. Merchants typically select their acquiring bank based on the amount of money, called basis points, they charge per transaction.
Payment Processors and Gateway Services In theory, e-commerce merchants can connect directly to their acquiring bank, but there are a number of reasons why they may not want, or be able, to do so. There are technical and business requirements for conducting the payment process for credit cards and most merchants don’t want to deal with these requirements. As an alternative, they use a third party to process credit card payments for them and their acquiring bank. These third parties are called credit card payment processors and gateway services. Credit card payment processors offer the physical infrastructure for the merchant to communicate with the acquiring banks and the credit card associations. They connect all the credit card payment participants together. This permits even very small banks to offer merchant services that they could not provide otherwise. Credit card payment processors make their money by charging a flat transaction fee or by charging basis points to the e-commerce
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merchant. Some credit card payment processors also provide acquiring bank services directly to the merchant. Gateway services provide merchants physical infrastructure as well. They generally offer technology and integration services among all the participants. The gateway service providers charge the merchant a transaction fee or basis points for their services. These fees are in addition to the credit card payment processor fees the merchant is already paying. If a merchant decides to use a gateway service provider they have to set up accounts with an acquirer. The acquirer can be an acquiring bank or a credit card payment processor that offers acquiring bank services.
Credit Card Associations The credit card associations such as Visa, MasterCard International, American Express, Discover, etc. are responsible for establishing the procedures and policies for how credit card transactions, services and disputes are handled. They are bound by national banking laws and provide the money that covers some of the fraud that occurs within their membership. Each of the credit card associations operate somewhat differently and even within the same association they may operate differently in different parts of the world. For example, Visa has regions that operate somewhat autonomously. There is Visa U.S.A., Visa Europe, Visa Asia, etc. Each of these regions has slightly different rules, tools and services. Visa does not actually issue credit cards to consumers; they use issuing banks to issue credit cards that are branded as “Visa.” MasterCard International is somewhat different from Visa in that there is one association for the entire world with all regions using the same basic structure, policies, and management procedures. MasterCard International also uses issuing banks to issue credit cards to consumers that are branded as “MasterCard.” American Express differs by acting as the issuer for all American Express branded credit cards.
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American Express is one global organization with regional coverage. American Express also differs from Visa and MasterCard in permitting merchants to set up direct connections for performing the acquiring functions. Each of these credit card associations has their own network of systems, policies for use and payment processing. Each of these associations also develops fraud-prevention tools and attempt to get merchants to utilize them.
HOW THE ON-LINE CREDIT CARD PAYMENT PROCESS WORKS When a merchant makes a sale over the internet; the card number, the amount of the sale, and the merchant identification (ID) are transmitted from the merchant’s establishment or the internet Web site over the credit card processor’s computer network. The credit card processor can either be a bank or a merchant account service company called a credit card processor that does nothing but provide credit card processing services as discussed above (Quick Start GA Dept. of Technical and Adult Education, 1996). From the credit card processor’s network the transaction is transmitted to the credit card company’s computer network. If the customer is using MasterCard, for example, the transaction will go to MasterCard’s computer network. Then, the electronic transaction is sent to the bank that issued the credit card to the customer. The bank’s computer system checks the account and verifies that the customer has adequate credit to cover the purchase. The bank’s computer system then sends the merchant an authorization over these same networks. Although the sale is complete, the transaction is not complete since no actual money has been exchanged. At the end of the business day the merchant account service (credit card processor) sends that day’s charges to the credit card network, e.g. MasterCard, for processing. The transactions are transmitted via the merchant’s credit
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card processor service to the credit card network, e.g. MasterCard. Individual transactions are then extracted and sent back to the individual cardholders’ banks. The issuing banks then debit the cardholders’ accounts and make appropriate payments to the merchant’s credit card processor through the Federal Reserve Bank’s Automated Clearing House. The credit card processor then credits the merchant’s bank account for the transaction amount, minus its fees for the transaction. Those fees are also used for paying transaction fees to the issuing bank and the credit card network. Despite the use of computers, it can take two business days before the merchant’s account is credited (Bank of America, 2009).
Opening a Merchant Account In order to accept credit cards, a merchant can open a merchant account with a bank. However, many banks have gotten out of the credit card processing business, and those that remain are often reluctant to service small businesses, particularly ones with limited operating histories. Many small businesses must therefore go through a specialized credit card processor or an independent sales organization, commonly referred to as an “ISO.” Whether a merchant uses a bans, ISO or a credit card processor, they need a merchant account before they can accept credit card payments. An ISO or an Independent Sales Organization is an entity that acts more or less as a middle man, helping formulate a Bank or Bank/Credit Card Processor alliance. Within such an arrangement, an ISO has an agreement to sell the services of the Bank or Bank/ Credit Card Processor alliance, and is allowed to mark up the Fees and sign up merchants. ISOs are also known as Member Service Providers (MSP). ISOs solicit new merchant relationships for a specific bank. Most merchants buy their processing services from an ISO and the ISOs buy their processing services from a backend credit card processor. However, depending on
the situation there can be significant differences between the responsibilities of the ISO and the backend processor. Each ISO is classified depending on how much of the responsibility they take for covering risk: Tier I - ISO: Also known as a Super ISO, Wholesale ISO, Full Liability ISO, and a Full Service ISO, a Tier I - ISO always does their own underwriting and risk-assessment and assumes full chargeback liability for their merchants and provide full technical support. Tier II - ISO: These are shared liability ISOs. Usually, they do not do their own underwriting, or require underwriting approval from the ISO or credit card processor with which they are contracted. They provide technical support capabilities and they also have the support from the ISO or credit card processor with which they are contracted. They are referred to as a shared-risk ISO because they usually are responsible for a portion of the chargeback risk of their merchants. Tier III - ISO: These are usually comprised of a few salespeople with no technical support to provide to their merchants, Tier III - ISOs also do take any responsibility for any chargeback risk. Since they do not assume any chargeback risk, they are subject to the underwriting guidelines of the ISO or credit card processor with which they have contracted Although businesses can contact credit card processors directly for a merchant account, banks unable or unwilling to process credit card transactions often refer customers to an ISO to help them find a credit card processor and get the necessary equipment and training to begin accepting credit cards
Typical Information Required for a Merchant Account Getting the required information together before applying for a merchant account can save time during the application process. Although different merchant account providers have different
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requirements typically what follows are required in order to obtain a merchant account: 1. Business checking account (some providers will create one for the merchant) 2. A copy of a voided check (if merchants use their own business checking account for funds to be deposited in) 3. A copy of the company’s Articles of incorporation, business license or reseller license. (A ‘Certificate of Assumed Name’ from the county’s Register of Deeds office may be all that is required and are relatively inexpensive, e.g. under $10.00) The purpose of this is to prove the applicant is a legitimate business. 4. Pictures of business office and location (this may save the merchant money in credit card processing costs) 5. Have a web site and URL (for real-time processing) 6. Photocopy of the merchant’s return policy 7. Provide business references 8. Photocopy of recent tax returns (depends on monthly sales volume expected through the merchant account) 9. Site inspection (pictures of your inventory). Only a few providers require this. 10. A photocopy of the applicant’s drivers license (Secondary verification of ID)
TECHNOLOGY REQUIREMENTS FOR PROCESSING CREDIT CARDS ON WEB SITES The following are considered to be the technology requirements and best practices for e-commerce Web Sites that accept credit card payments (Authorize.com, 2009). Create a Secure Payment Web Site. This is needed to protect credit card data and other sensitive information from hackers during the credit card transaction process. Identity theft and credit
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card fraud are occurring more frequently on the Internet, and merchants must ensure that their customers are protected from internet criminals. Many consumers will not buy from a site that does not provide secure transactions. Merchants can help secure their site by having a secure socket layer certificate, or SSL. SSL encrypts information being entered on the merchant site as it is sent across the Internet. Merchants can purchase their own SSL certificate, or the merchant’s Web host may allow a merchant to use their SSL certificate as a part of its service. Utilize a compatible shopping cart application. This is required to make sure the merchant’s shopping cart application can communicate with the merchant’s credit card payment-processing gateway. There are several different types of credit card payment gateways, and each has a set of standards that must be followed. Many of the free shopping cart application software packages do not support all of the available credit card payment gateways. A merchant should check with their merchant account provider or their shopping cart documentation to make sure that all the components will work together. Shopping cart applications fall into two basic categories namely: Local shopping carts that merchants can install on their own Web servers, and third-party shopping carts that run on a provider’s site. If a merchant decides to install his own shopping cart software, he will have a variety of software packages from which to choose. Three of the more popular ones are Miva Merchant, OSCommerce, and Agoracart. Miva Merchant is a shopping cart that many Web hosting companies include with their hosting packages. If a merchant’s host doesn’t offer it, the merchant will be required to pay a licensing fee before the package can be installed. Miva offers a variety of different options for small businesses, and the application is considered highly user-friendly. OSCommerce is a free, open source shopping cart program that contains many features and a reputable development community. It is con-
On-Line Credit Card Payment Processing and Fraud Prevention for E-Business
sidered relatively easy to install and customize. Because OSCommerce is open source, support and improvements are readily available. Agoracart is a simple, free, and basic functionality shopping cart application. If a merchant doesn’t require a lot of features, this is a useful package to be utilized on a merchant’s shopping cart site. If a merchant would rather not install shopping cart software on his own web site, there are a number of third-party options available. When a merchant utilizes third-party shopping cart software, the merchant must place a link on his web site to the third party’s web site where the application exists. This link takes customers to the merchant’s offsite shopping cart software. Microsoft’s BCentral is one of the more popular third-party shopping cart software. Yahoo! offers a similar third-party shopping cart software package. Storefront.net and 1shoppingcart.com both offer services that include shopping carts as well as advanced tools like email list management, affiliate program integration, etc. Provide E-mail Message Encryptions. If a merchant plans on accepting orders and sending or receiving credit card information via email, the merchant will need to encrypt the information that is transmitted. PGP, which stands for “Pretty Good Privacy,” is the most common form of email encryption. PGP encrypts an email when it is sent and decrypts the email when it has reached the intended recipient. If e-commerce merchants plan to use PGP, they will also need to make sure that their email clients support it. Merchants must keep the PGP security key in a location where it cannot be accessed by others. Utilize a Firewall. If a merchant stores customer credit card numbers or other personal information on his server, it is necessary to have a site-wide firewall to protect this information. Many merchants expose their customers to hackers by neglecting to implement a proper firewall. Use Anti-Virus Software and Update It Frequently. Anti-virus software will prevent most
of the hacker’s attempts to invade the merchant’s Web site and steal personal information such as credit card numbers. This software should be updated on a regular basis. Regularly Download and Install Security Updates: Software performance and security can be optimized by installing all service and security updates when they become available. After merchants have implemented these basic technology requirements, they are ready to offer their customers an easy way to purchase their merchandise or services. Merchants can also give their customers comfort in knowing that they are providing a safe and secure environment for making credit card payments and providing other personal information.
HOW CREDIT CARDS PAYMENTS ARE ACCEPTED AND PROCESSED ONLINE If most of a merchant’s business is conducted on the Internet, Real-Time processing is the appropriate solution. When a customer who is using a merchant’s Web site is finished shopping and is ready to pay, typically the customer simply clicks on a “Check Out” button which is a link to a secure page where customers type in their credit card information. After a few seconds, a message will then appear showing whether the credit card has been accept or declined. Two days later the money will be transferred into the merchant’s business checking account. Real-Time credit card processor or merchant account service providers will have an online database containing all of the credit card transactions for a merchant which makes month-end accounting and balancing simple. Real-Time processing is the best solution for those who plan on having a high volume of daily transactions. Real-Time processing helps to automate the payment acceptance process, unlike in retail establishments where entering credit card information must be done manually. Most
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Real-Time solutions are coupled with a “Virtual Terminal” that allows a merchant to process Mail Order/Telephone Order (MOTO) orders manually via a web browser from any location that has access to the Internet. The process a credit card transaction goes through is fairly complicated; however it generally only takes a few seconds. The steps below illustrate how credit card transactions are typically processed using a Real-Time credit card processing service (Smith, 2009; Murdock, 2006). 1. Using the merchant’s shopping cart Web interface, customers select “check out” with the items they placed into their shopping cart or selected from an order form on a merchant’s Website. 2. Customer then selects “credit card” as their method of payment. 3. The customer’s Web browser then connects to the Merchant’s website host’s secure server, and brings up the secure payment form. 4. Customer enter their credit card information on the secure payment form, and authorize the transaction by clicking a “Complete Order” or “Continue” type of button. 5. The credit card transaction information is transmitted to the Website host’s secure server using SSL encryption. 6. The merchant’s secure server connects to the merchant’s processing bank either via a secure payment gateway (a third party which provides the connection to the processing bank), or directly (some credit card processors have their own proprietary secure payment gateway and therefore do not require a third party to provide this service). 7. The credit card processor service sends the transaction to the credit card association network, such as Visa or MasterCard, directly, and the validity of the card and availability of funds is confirmed.
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8. If the credit card transaction is approved, an authorization code is returned to the credit card processor service, or to the Secure Payment Gateway from the credit card association network. 9. The authorization is encrypted by the Payment Gateway or credit card processor and transmitted in encrypted form to the secure Web server of the merchant, which permits fulfillment of the order. 10. The merchant’s secure Web server then sends the customer’s Web browser a confirmation receipt. 11. The amount due for the credit card transaction is moved from the card holder’s bank to the merchant’s credit card processing bank. The merchant’s credit card processing bank transfers the money to the merchant’s local bank within 2 to 3 business days. Figure 1, illustrates the technological components of a typical credit card processing system.
MINIMIZING INTERNET CREDIT CARD FRAUD Although there are no verifiable global figures on losses from credit card fraud, an FBI report issued in 2005 indicated that credit cards represented the majority of the total $315 billion U.S. financial fraud loss for that year. A recent European study found that more than 22 million adults were victims of credit card fraud in 2006. Figures from the Banque de France, the country’s central bank, showed a credit card fraud loss of $319 million, for 2005 (Conlin, (2007). For US buyers, credit card fraud does not pose a significant problem, as their loss is limited to $50. But, for merchants who shoulder the burden of the losses that is not the situation. Between November 1999 and February 2000, travel site Expedia.com lost 12% to 18% of sales through fraudulent card purchases. Visa and MasterCard claim a fraud rate of 0.08% to
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Figure 1. Typical credit card processing system
0.09%, and have stated that there is little difference between Internet sales fraud and other type of credit card sales fraud, but they have invoked serious penalties for excessive chargebacks for on-line credit card fraud. When a consumer reports an instance of fraud, the disputed amount is removed from the merchant’s account and credited back to the customer. This “chargeback” typically comes with a standard fee of $15 per instance. The Internet Fraud Prevention Advisory Council has established online transaction fraud rates at 2% to 40%, depending upon the product category. At highest risk are downloadable software and entertainment, and high ticket items such as airline tickets, computers, and diamonds. Payment gateways in the US have developed sophisticated fraud checking techniques, but it has not halted credit card fraud. To protect themselves, merchants can capture the IP address of purchasers, carefully examine purchases made from free e-mail addresses, those with different shipping and billing addresses, bounced e-mail order confirmations, no-existent telephone numbers, and large middle-of-the-night transactions. Merchants must also be cautious about shipping to Eastern European and other countries with a history of fraudulent transactions and telephone the buyer before shipping high ticket items (Faughnan, 2007).
Sophisticated Security Required to Prevent Credit Card Fraud Online merchants have been forced to develop sophisticated security protections that far exceed the normal security approval process by the credit card companies (Wilson, 2008). In 2005, an estimated 13.5 percent of U.S. adults (30.2 million consumers) were victims of one or more cases of identity fraud in the previous year. There were an estimated 48.7 million incidents of fraud during this one year period (Woolsey & Schulz, (2009). Currently, credit card companies only verify whether a credit card number is correct and then match the number against the customer’s billing address but cyber-criminals can make sure the address is correct and that the addresses match. Cybercrime, in all forms, shows no signs of decreasing in the near future. For example, MSNBC reported that Visa quietly informed select merchants that 485,000 credit card numbers were stolen from a major e-tailer in January 1999 and in 2008 the Bank of America notified thousand of card holders that their MasterCard information had been compromised. E-tailers (Web Merchants) find themselves in a difficult position regarding credit card fraud (MasterCard Worldwide, 2009; Montague, 2004).
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Credit Card Fraud Solution Approaches While there does not appear to be any simple solutions, experts believe that potential cybercriminals will soon begin to reconsider committing credit card fraud. This type of criminal activity has, for a long time, been considered too small to bother with, but using credit cards fraudulently is quickly becoming “identity theft”; which has been defined as a serious federal felony. Cybercriminals do leave digital fingerprints and can get caught. There are a number of approaches used by criminals to commit credit card fraud and there are a number of procedures implemented to deter their attempts at credit card fraud. These are discussed below.
Security Codes An important Internet security feature that now appears on the back of most Visa/MasterCard and Discover cards, and on the front of American Express cards is a security code. This code is generally a three or four-digit number which provides a cryptographic check of the information embossed on the card. The security code helps validate that the customer placing an online order actually has the credit card in his/her possession, and that the credit/debit card account is legitimate. The security code is only printed on the card and it is not contained in the magnetic stripe information nor does it appear on sales receipts or billing statements. The goal is to make certain that the customer must have the card in his/her possession in order to use this code. Since Card Security Codes are not scanned into standard credit card readers, in theory, these numbers are only visible to the customer. When customers give their Card Security Code to merchants, they assist merchants in verifying that the orders being placed are being placed by the credit card holder. Visa, MasterCard, Discover and American Express now require Internet commerce sites to obtain the
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security code for all cards that have a code printed on them. In order for a credit card transaction to be accepted and processed, this code is required as part of the transaction data. Unfortunately, the cyber-thieves are also using advanced techniques to ascertain critical information about stolen card numbers. They have developed software that can determine which bank issued a card, harvest the three-digit card verification number and determine the available credit-card limit. They can check a card number’s validity and personal information such as address and telephone number about the owner as well.
Credit Card “Skimming” Criminal gangs recruit individuals who work within restaurants, hotels and retail outlets. The recruits are given battery powered electronic devices known as “skimmers” that read and capture all of the credit or debit cards details in the few seconds that it takes to swipe the card through the credit card reader machine. When customers pay their bill, their card is first swiped through the legitimate credit card machine, but then it is also swiped through the “skimmer” reader. The recruits then pass the “skimmer” machines onto counterfeiters, who pay the recruits for their part in the crime. Once the “skimmer” machines have been given to the counterfeiters, they download the information onto a computer and produce a fake clone of the credit card. The “cloned” card is embossed with the details of the victim’s credit card and passed on to gang members who may sell it for between $400 and $700, depending on the perceived credit limit. The buyer then uses the “cloned” credit card to illegally purchase products and services. Skimming is costing credit card users worldwide millions of dollars in phony charges, as stolen clones are sold and used in the United States and elsewhere around the world. Often skimming is done at gas stations or restaurants, since those are the places that hire people who work for minimum wage and are businesses that
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don’t bother with background checks, especially since many employees are part-time workers (Fraud Guides, 2009).
Skimming Prevention The following are measures merchants can use to avoid credit card fraud by skimmers: 1. Subscribe to stolen credit card checking systems 2. Verify the address 3. Verify the telephone number 4. Call the credit card issuing bank 5. Examine the email address - hotmail and yahoo mail can be easily faked 6. Call the cardholder 7. Be cautious of bulk orders 8. Shipping and billing address should match 9. Single-use credit card numbers 10. Smart Cards
Single Use Credit Card Numbers Some credit card companies have a new security and privacy offering which utilizes the concept of disposable credit card numbers. With this system, customers can get unique credit card numbers linked to their credit card account each time they make a purchase online. This allows the customer to avoid transmitting their “real” credit card numbers. The single-use numbers don’t work for recurring charges but they also don’t work for cyber-thieves who try to make multiple purchases. The utilization of single-use credit card numbers can help reduce the risk posed by hackers who steal and reuse numbers
Smart Card Technology for On-Line Purchasing Newer “smart cards” are embedded with a computer chip containing a digital certificate. A digital certificate consists of basic information about the
cardholder’s digital identity. It contains elementary personal information such as the cardholder’s name, e-mail address and digital signature. The digital signature is nothing more than a series of numbers called a public key which forms the basis of encryption algorithms. Unlike a written signature, a digital signature has two purposes. It authenticates who the cardholder is legally and it also allows the cardholder’s messages to be encrypted. Because the smart card chips are programmable, “smart chip technology” is flexible, and designed for multiple applications. These cards are inserted into a, typically free, smart card reader plugged into the user’s computer. The card, together with a PIN number, allows consumers to buy on the Internet using their digital certificate. The card allows access to an online wallet, which contains information such as shipping and ordering information. This information is automatically transmitted to the merchant’s online order forms. The current problem with digital certificates is a lack of standardization. Almost anyone can establish themselves as a digital certificate issuing authority (CA). Currently, the major players include retail-oriented certificate authorities such as Entrust, VeriSign, Thawte and Cybertrust although there are many others. Consumers are becoming increasingly aware of the role played by digital certificates. Many consumers will only buy from a merchant who displays a digital certificate issued by one of these certificate authorities. Secure communications generally requires five key elements to work correctly, namely: Confidentiality, authorization, authentication, integrity and non-repudiation. Confidentiality and authorization are supplied by encryption systems. The others, namely: authentication, integrity and non-repudiation depend on a digital signature.
Address Verification System (AVS) E-commerce merchants can utilize an Address Verification System (AVS) for consumers from
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the United States. An AVS takes the consumer’s ZIP code and the numbers in the street address, and compares them with the numbers in the credit card billing address. If they agree, the transaction is authorized; if they do not agree, the transaction is flagged as suspicious or in some cases not allowed, depending upon the merchant’s preference. Using AVS lowers the merchant’s discount rate, and can protect against stolen credit cards where the thief has the credit card number, but not a correct address.
Telephone Number Authentication A Telephone authentication service can provide a decrease in the number of fraudulent transactions that pass through an on-line ecommerce web site. Most cyber-criminals are not willing to provide their real telephone number to complete a transaction and many, if asked for a telephone number will simply exit the transaction. There are a number of services that will provide real time telephone number authentication. These services can determine whether a telephone number is real, no longer in service, stolen or a legitimate working number at the address given by the user.
Telephone Verification Telephone Verification works by automatically calling an online end-user’s telephone number at the same time the end-user is making a transaction on a website. The user while on the website answers the phone and is provided a one-time personal identification number (PIN) presented via the web interface; an otherwise anonymous online end-user will be able to confirm that the person who received the phone call and the person who is interacting on the website are the same person. If the consumer, or end user, cannot verify through the phone, they should asked to try again with another phone number. If they cannot pass on the second attempt; assume the consumer or end user is high risk and do not allow the transaction.
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Customer Transaction and IP History Databases Checks Another approach for detecting online fraud is to compare a transaction with previous transactions made for a given credit card number and make sure it fits the pattern of use. There are companies that provide real time checks of credit cards with databases of millions and, in some cases billions, of records to detect anomalies (Wilson, 2008). This type of service will score a credit card transaction based on all the intelligence it has gathered both about the transaction and former purchases. In addition, online fraud detection solutions based on a combination of IP reputation analysis and a mutual collaboration network has proved successful. IP reputation uses geolocation and proxy detection by providing relevant information about the IP’s historic behavior, both legitimate and suspicious (MaxMind Inc., 2008).
Intelligent Credit Card Fraud Detection An intelligent credit card detection system monitors card transactions as they occur by gathering data from the current and previous transactions and uses this data to compute a transaction score for the current transaction. The algorithms used to compute such a score are called classifiers. Typically, high scores for transactions are more likely to be fraudulent than low scores thus transaction scores are compared to a threshold and the score is classified as normal or fraudulent. Credit card fraud detection is a complicated problem involving many input variables such as time, transaction amount, merchant, merchant category code, country, etc) acquired from multiple transactions in a sequence. A classifier computes a fraud score based on a number of these variables. Two basic approaches have been used in developing classifiers, namely, neural networks and Bayesian decision methods. A neural network is a nonlinear function which takes multiple input
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variables and computes a score from them. A neural network consists of a series of interconnected neurons similar to the structure of the brain. The interconnections have weights assigned to them and the input neurons (input nodes) to a network represent each continuous variable and every value that a categorical variable can take. Since the weights in a neural network need to be optimized, a learning or training process iteratively passes through a database of card transactions containing both fraudulent and legitimate transactions and systematically adjusts the weights so that the resulting scores discriminates between fraudulent and legitimate transactions. The Bayesian approach to card fraud detection is based on probability theory. Research has identified a number of characteristics derived from credit card transactions which tend to be predictive of fraud. A Bayesian approach computes the probability distributions for each of these credit card transaction characteristics using a process called evidence integration to compute a fraud probability from the individual characteristic probabilities. Therefore, in a Bayesian approach the classifier consists of credit card transactions characteristics, their probability distributions and an evidence integrator (Alaric Inc., 2008).
REGULATORY AND LEGISLATIVE ISSUES Management of information risk is now tied to regulatory mandates. Since 1999, laws enacted at the federal and state levels have forced companies to be extremely careful in protecting the confidentiality and reliability of medical, financial and other sensitive information stored on their computer systems. Failure to comply with these mandates can lead to civil and criminal penalties, lawsuits and related litigation costs and, of course, damage to reputations. Although the earlier laws focused on financial and healthcare companies, two of the most recent
laws, namely, the 2002 Sarbanes-Oxley Act and the California Data Protection Law (SB 1386), broadened the scope of companies that are required to comply. The Gramm-Leach-Bliley Act (GLB), also known as the Gramm-Leach-Bliley Financial Services Modernization Act, is an Act of the United States Congress that stipulates that every financial institution must protect the security and confidentiality of its customers’ personal information. The Federal Trade Commission in conjunction with several other federal and state agencies along with the Federal Bureau of Investigation (FBI) is the federal agency responsible for enforcement of these laws and mandates (United States Department of Justice, 2009).
FEDERAL TRADE COMMISSION (FTC) The FTC deals with issues that are related to the economic life of every American citizen and business. It is the only federal agency with both consumer protection and competition jurisdiction across all sectors of the economy including e-commerce. The FTC is charged with law enforcement and protecting consumers’ as well as business’ interests by sharing its expertise with federal and state legislatures and U.S. and international government agencies; developing policy and research tools through hearings, workshops, and conferences; and creating practical educational programs for consumers and businesses in a global marketplace with constantly changing technologies. The FTC has also been directed to administer a wide variety of other consumer protection laws, including the Telemarketing Sales Rule, the Pay-Per-Call Rule and the Equal Credit Opportunity Act. In 1975, Congress gave the FTC the authority to adopt industry-wide trade regulation rules. The FTC’s work is performed by the Bureaus of Consumer Protection, Competition and Economics. That work is aided by the Office of General Counsel and seven regional offices.
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Credit card fraud is within the FTC’s domain of responsibility and this responsibility is shared with the Federal Bureau of Investigation (FBI) (Federal Trade Commission, 2009).
MANAGING INFORMATION RISK Managing information risk must be integrated with a merchant’s overall risk management strategy. The technology infrastructure; including servers, network monitors, and firewalls, needs to be assessed and managed in terms of its relation to people, operations, supply chains and other business drivers. Some of the steps involved with information technology (IT) risk management include paying attention to human factors, putting proper security policies in place, identifying critical assets and fostering better communication and an enterprise-wide perspective among IT managers and risk managers. Bringing together IT, risk management, internal audit, legal and human resources to address information management risk issues produce a consensus to the identification of threats, the areas of operation (ranked in order of most critical and sensitive) that could be affected by a threat, potential financial or reputational loss, and the most cost-effective way to reduce the risk (Stoneburner; Goguen; Feringa; Alexis, 2009).
An Information Risk Assessment A risk assessment should be performed by any merchant accepting credit card payments and this assessment should examine the following risk factors (Cooney, 2007; Frank, 2004): System Characteristics: Assess and identify the resources and information that constitute the systems used for financial purposes and identify the business systems jointly with management personnel, IT personnel and users. Threat Identification: Conduct interviews and utilize work-group sessions with key management team members, technology administrators and
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system users to uncover potential threat agents that may impact the confidentiality, integrity and availability of information stored in databases and files. Vulnerability Identification: Conduct a technical assessment to detect vulnerabilities and to assess how effective the controls are for preventing unauthorized access, Control Analysis: Assess countermeasures regarding items such as firewalls, encryption, web server access policies, password policies, backup and recovery procedures, change-management procedures, currency of software, hardware maintenance and the physical environment. Insurance Gap Analysis: Assess current insurance policies in terms of coverage for financial loss arising out of unauthorized access or use of confidential information, damage to third-party software or data as well as damage to the business network or databases and files. The risk assessment can not only help identify the critical areas of risk to be addressed, but can also be used to recommend best practices to remedy the risk. Creating a more secure environment can help produce and maintain consumer confidence and deter financial loss, which could, in turn, give a merchant a competitive edge (United States General Accounting Office- Accounting and Information Management Division, 1988).
CREDIT CARD FRAUD PREVENTIVE STEPS FOR ONLINE BUSINESS OWNERS When a merchant physically accepts a credit card, and the charge is authorized, and the merchant has conformed to credit card regulation, the merchant will get paid, even if a stolen card is used. But, the liability for fraud shifts from the card issuer to the merchant for ‘Card Not Present’ sales (Internet sales, mail order, and telephone/fax order). After a credit card processor or registration service approves a credit card transaction, the merchant
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should perform additional checks, as fraudulent orders are sometimes approved. The following methods and techniques can be utilized to protect an e-commerce merchant against credit card fraud (Wilson, 2000; Jepson, 2009; Authorize.com, 2009; Federal Trade Commission, 2009). Typically, a combination of methods is the best approach. •
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Follow the procedures recommended by your credit card processor and the credit card companies. Authorization approval - make sure you get it from the issuing bank. Address Verification System (AVS) AVS is only available for the U.S. and partially available in four European countries to verify the address matches. Card Verification Methods (CVM) Security Codes: VISA = CVV2, MasterCard = CVC2, and American Express = CID use a security code of 3 or 4 extra digits. Payer Authentification Programs Authentification programs (Verified by Visa and MasterCard’s SecureCode) use personal passwords to ensure the identity of the online card user. Real-Time Authorization - Credit card information is sent to the processor for immediate approval. Bin Check - The first 6 digits of the credit card are called the Bank Identification Number (BIN). Calling The Card-Issuing Bank - Call the card-issuing bank, to verify the charge. Different Bill And Ship To Addresses – Use a search engine such as Google to search for the street address number, street name, and zip code. Negative Historical File - Keep a database or other electronic record of prior fraud attempts, problem customers, charge back records, and customers receiving refunds.
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Shared Negative Historical File – Combine negative historical databases/ files from several e-commerce merchants. Positive Database File – Maintain a file that contains a list of good customers Credit Service Database – Use a credit database service, such as Equifax (www. equfax.com), Experian (www.experian. com), and Trans Union (www.tuc.com) for high-dollar value items. Customizable Merchant Rules - A merchant should establish rules to stop or flag specific orders for review. Fraud Scoring Systems – Assign weights, points or probabilities to different components of a transaction (IP Address, freeemail account, time of day, AVS results, amount of sale, type of products ordered, shipment method, different shipping/billing addresses, certain zip codes, etc) to generate a fraud score to indicate the likelihood of fraud. Pattern Detection - Check if multiple orders are placed shipping to the same address, but different credit cards were used. Check orders for an unusually high quantity of a single item. Alternate Thank You Page - If an order is being shipped to a non-English speaking country, display an alternate thank you page. Require the customer to fax either a photo of the credit card or a scanned copy of his/her credit card bill. Preventative Data Checking Measures Check the data fields entered by the buyer to determine if the buyer actually exists based on data entered on the order. Check to see if the ZIP Code the customer listed actually exists. Make sure the customer’s e-mail address is formatted properly. Check for incomplete names or an address like 100 Elm Street. Free Email Accounts - There is a much higher incidence of fraud from free email
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services. Many fraudsters use free email addresses to remain anonymous. Reverse IP Address Checks – Make sure the user’s IP address matches the email address and physical billing address of the customer. The IP address identifies the location of the server where the order was placed. Numerical IP addresses can be checked through programs such as WsPing32. Anonymous And Open Proxy IP Addresses - IP addresses can be falsified thus hiding the falsified IP addresses true location of the criminal. Organized credit card fraud rings often use anonymous proxies. Checking Telephone Numbers - The web sites at http://www.freeality.com/finde. htm, http://www.theultimates.com/, http:// www.anywho.com, http://nt.jcsm.com/ ziproundacx.asp, and http://nt.jcsm.com/ ziproundacx.asp provide tools to match a telephone area code to a postal zip code, reverse telephone directories, search for email addresses, maps, directions, etc. A merchant can call directory assistance to determine if the phone number on the order matches the customer’s phone number based on their name and address. Fax Orders - When a credit card order is received by fax, require the customer to also fax copies of both sides of their credit card and a copy of their state-issued ID, or driver’s license International Orders - Some countries have a bad reputation as a source of fraud transactions. Banks or credit card processors can provide a list of high-risk countries. High risk countries include developing nations like Indonesia, Malaysia, Benin, Nigeria, Pakistan, Israel, Egypt, and Eastern European countries. Placing an international phone call to the issuing bank may be worth the cost for large orders
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and/or ask the customer to contact the merchant by phone or email for shipping costs. A cyber-criminal may consider this too much contact, and decide to go elsewhere. Calling The Customer - Calling customers is not only an excellent way to detect fraud, but it can also be a valuable part of your customer service Web Site Information – Make sure the order form includes fields to enter the CVV2 verification code imprinted on the credit card, the name of the card-issuing bank, and the bank’s toll-free telephone number, the customer’s telephone number and email address. Processing Orders – Do not ship any order until the charge can be verified by additional checks. Use Temporary Activation Codes - If the merchant wants to process orders immediately, issue thirty-day temporary validation keys for downloaded software Anti-Fraud Groups – Become educated about fraud prevention by attending seminars offered by credit card companies and card processors. Organizations such as www.antifraud.com and www.wiscocomputing.com offer help. These groups also offer tips, databases of stolen credit cards, and web lookup tools. File a Complaint with the FTC and the FBI – If you detect fraud or have been a victim of fraud, file a complaint with the FTC at https://www.ftccomplaintassistant.gov/ and the FBI’s Internet Crime Complaint Center or IC3, a partnership of the FBI and the National White Collar Crime Center at http://www.fbi.gov/majcases/fraud/internetschemes.htm (Internet Crime Complaint Center (IC3), 2009).
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CONCLUSION Based on past performance and predictions for the future, it seems safe to say that purchasing goods and services over the internet will continue to increase. This is because it is more efficient for the merchants and they can reach a much larger audience than using the face-to-face, instore methods of the past. But like most uses of technology, there are individuals who find ways to use the technology for criminal purposes. This has been the case when utilizing credit or debit cards for purchasing goods and services over the internet. Thus, a sort of battleground has evolved between the e-commerce merchants along with their customers and the cyber-criminals. As new technological security methods are implemented by merchants to protect themselves and their customers, the cyber-criminals attempt to find ways through or around these technological barriers. If past events are any indication of the future, this battle is not over and merchants and their customers must continue to find secure methods to combat the criminals attempting to fraudulently steal financial and other personal information for their own financial gain.
REFERENCES Alaric, Inc. (2008). Card fraud detection - Comparison of Detection Technologies. Retrieved December 28, 2008 from http://www.alaric.com/ public/products/fractals?gclid=CI20ofLAnZgCF QpxHgodKmPDmg Authorize.com. (2009). Security Best Practices (2009). Retrieved January 21, 2009 from http://www.authorize.net/upload/images/Files/ White%20Papers/Security_0604.pdf
Bank of America. (2009). Card Processing Basics (2009). Retrieved January 21, 2009 from http://www.bankofamerica.com/small_ business/merchant_card_processing/index. cfm?template=card_processing_basics Conlin, J. (2007, May 11). Credit card fraud keeps growing on the Net. Retrieved December 28, 2008 from http://www.iht.com/articles/2007/05/11/ news/mcredit.php Cooney, M. (2007, November 11). Credit card transaction security fortified by new risk assessment system. Retrieved from http://www.networkworld.com/community/node/21731 Dept, G. A. of Technical and Adult Education (Ed.). (1996). Credit Card Processing Overview. GA Dept of Tech & Adult Education, Quick Start. Faughnan, J. G. (2007, November 23). International Net-Based Credit Card/Check Card Fraud with Small Charges. Retrieved from http://www. faughnan.com/ccfraud.html Federal Trade Commission. (2009a). Avoiding Credit and Charge Card Fraud. Retrieved April 24, 2009, from http://www.ftc.gov/bcp/edu/pubs/ consumer/credit/cre07.shtm Federal Trade Commission. (2009b). About the Federal Trade Commission (2009). Retrieved January 22, 2009 from http://www.ftc.gov/ftc/ about.shtm Frank, J. (2004). Fraud risk assessments: audits focused on identifying fraud-related exposures can serve as the cornerstone of an effective antifraud program. Retrieved from http://findarticles. com/p/articles/mi_m4153/is_2_61/ai_n6152654/ Fraud Guides. (2009). Credit Card Skimming. Retrieved from http://www.fraudguides.com/ business-credit-card-skimming.asp Internet Crime Complaint Center (IC3). (2009). Retrieved January 21, 2009 from http://www.ic3. gov/default.aspx
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Jepson, T. (2009). Merchant Credit Card Fraud: 31 Ways to Minimize Credit Card Fraud. Retrieved from January 17, 2009 from http://www.wiscocomputing.com/articles/ccfraud.htm MasterCard Worldwide. (2009). Site Data Reflections The top five Web intrusions. Retrieved January 21, 2009, from http://www.northamericanbancard.com/google/smart_templates/default/ web/MC_SECURITY.pdf MaxMind, Inc. (2008). IP Address Reputation and a Mutual Collaboration Network. Retrieved December 28, 2008, from http://www.maxmind. com/minFraudWhitePaper.pdf Montague, D. A. (2004). Fraud Prevention Techniques for Credit Card Fraud. Victoria, Canada: Trafford Publishing. Murdock, K. (2006). Credit Card Processing: How It All Works. Retrieved January 21, 2009, from http://www.practicalecommerce.com/ articles/168-Credit-Card-Processing-How-ItAll-Works Smith, R. (2009). How Credit Card Processing Works. Review. Retrieved January 21, 2009 from http://www.smithfam.com/news/nov99d.html Stoneburner, G., Goguen, A., & Feringa, A. (2009). Risk Management Guide for Information Technology Systems Recommendations of the National Institute of Standards and Technology. Retrieved January 22, 2009, from http://csrc.nist. gov/publications/nistpubs/800-30/sp800-30.pdf TopTenReviews. (2009). Credit Card Processing Services Review. Retrieved January 21, 2009 from http://credit-card-processing-review.toptenreviews.com/ United States Department of Justice. (2009). Internet and Telemarketing Fraud. Retrieved April 28, 2009, from http://www.usdoj.gov/criminal/ fraud/internet/
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United States General Accounting Office- Accounting and Information Management Division. (1988). Information Security Risk Assessment, Practices of Leading Organizations. GAO, May, 1988. Wilson, R. F. (2000, March 15a). Sophisticated Fraud Protection Systems. Web Commerce Today, 32. Retrieved January 12, 2008 from http://www. wilsonweb.com/wct3/fraud-systems.cfm Wilson, R. F. (2000, March 15b). Inexpensive Techniques to Protect Merchants against Credit Card Fraud. Web Commerce Today, 32. Retrieved from January 15, 2009 from http://www.wilsonweb.com/wct3/fraud-lowcost.cfm Woolsey, B., & Schulz, M. (2009). Credit Card Industry Facts, Debt Statistics 2006-2009. Retrieved January 12, 2009 from http://www.creditcards. com/credit-card-news/credit-card-industry-factspersonal-debt-statistics-1276.php
KEY TERMS AND DEFINITIONS Acquiring Bank: The bank that represents the e-commerce merchant and processes all of the merchant’s credit card payments with the credit card associations Credit Card Processor: A third party utilized to process credit card payments for merchants and their acquiring bank Credit Card: A card issued by banks, savings and loans, retail stores, and other businesses that can be used to borrow money or buy products and services on credit. Cyber-Criminal: An individual who commits a crime using a computer and the internet to steal a person’s identity such as credit card information. E-Commerce: The buying and selling of goods and services on the Internet. Fraud: An act of deception for the purpose of unlawful financial gain using stolen credit card information.
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Issuing Bank: The bank that issues consumers their credit cards. Merchant Account: A legally binding contract wherein an acquiring bank extends a line of credit to a merchant who desires to accept payment using credit cards. Service Gateway: This is another name for a credit card processor.
Skimming: This is a type of fraud wherein the numbers on a credit card are recorded and transferred to a duplicate card. SSL: SSL is an abbreviation for Secure Sockets Layer, a protocol developed for transmitting documents over the Internet using a cryptographic system that uses two keys to encrypt data; namely a public key known to everyone and a private or secret key known only to the recipient of the document.
This work was previously published in Encyclopedia of E-Business Development and Management in the Global Economy, edited by In Lee, pp. 455-473, copyright 2010 by Business Science Reference (an imprint of IGI Global).
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Chapter 3.13
Achieving Electric Restoration Logistical Efficiencies During Critical Infrastructure Crisis Response: A Knowledge Management Analysis Teresa Durbin San Diego Gas and Electric, USA Murray E. Jennex San Diego State University, USA Eric Frost San Diego State University, USA Robert Judge San Diego State University, USA
ABSTRACT After the 2007 Southern California wildfire events, event-assessment of the efficacy of spreadsheets and paper forms raised the question of whether alternative tools could have achieved greater efficiencies in the logistical support of command centers, the sites from which the local utility’s electric restoration personnel were deployed. In
this paper, the authors examine what approach would have enabled personnel working on the logistics of the command center effort to have easier-to-use, faster-to-access, command center data stored in, and provided via, a catastrophe resilient platform other than the traditional company computer network. Additionally, the capability to store basic command center requirements from previous emergency responses, thereby saving time during the next emergency, was examined.
DOI: 10.4018/978-1-60960-587-2.ch313
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Achieving Electric Restoration Logistical Efficiencies During Critical Infrastructure Crisis Response
INTRODUCTION Gas and electric services in the County of San Diego are provided by San Diego Gas & Electric Company (SDG&E), an investor-owned public utility. Many useful issues can be analyzed from the wildfires that damaged SDG&E’s electric system in 2003 and 2007 and certain activities that supported efficient service restoration can be examined and used for comparative analysis for a terrorist attack scenario, earthquakes, wildfires, or any other event that might impact service delivery. This paper analyzes the logistics support provided during the wild fires to determine what could be improved. This is an important topic as there is little research literature addressing crisis response logistics. Whybark et al. (2010) discuss disaster relief supply chains but only propose a research agenda. We agree there needs to be research in this area and start with this case study. Logistics/supply chains ensure that responders are able to sustain disaster relief. Their importance is illustrated by the response to the 2009 Haiti earthquake where ships and supplies stood empty or unused off the coast because of an inability to deliver supplies and evacuate injured. Keeping responders in the field is critical for long term disaster relief. Providing relief is critical for affected persons and societies to recover. This paper hopes to start this important research area by exploring alternatives to the spreadsheet approach used in the 2007 wild fires. Finally, the research question for this paper was what alternatives could be used in lieu of paper forms and spreadsheets to achieve more accurate, timely logistics data and solutions?
METHODOLOGY This paper is a case study using action research to assess whether future activities by the command center support teams can be influenced to convert from paper forms and spreadsheets to
something more real-time, as a new solution for crisis response. The working definition of action research (Zuber-Skerrit & Fletcher, 2007, p. 413) incorporated situations where people reflect and improve (or develop) their own work and their own situations by tightly interlinking their reflection and action; and also making their experience public not only to other participants but also to other persons interested in and concerned about the work and the situation, i.e. their public theories and practices of the work and the situation, and in which the situation is increasingly: data-gathering by participants themselves (or with the help of others) in relation to their own questions; participation (in problem-posing and in answering questions) in decision-making, self-reflection, self-evaluation and self-management by autonomous and responsible persons and groups. This study is action research as the lead author is a team lead of the SDG&E supply chain systems team tasked with assessing logistics performance. Reflection for this study was done using knowledge management, KM as the reflective lens. Jennex (2005) summarized KM definitions to conclude that KM is about capturing knowledge created in an organization and making it available to those who need it to make decisions and improve organizational performance. Jennex (2007) discussed the role of KM in crisis response and included the role of post event evaluation of lessons learned as a way of capturing knowledge generated during an event and ensuring that knowledge is shared and incorporated into crisis response activities. This implies that KM is a good reflective lens for crisis response research. The ability to apply KM to the 2007 command center logistical effort and how it can benefit future emergency responders corresponds to KM in support of crisis response as expanded upon by Jennex and Raman (2009). The underlying KM principle upon which this study is constructed are that experience gained from one emergency can be
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applied as knowledge when shared with others to improve performance during a subsequent emergency. Additionally, improved performance will help an organization meet its goals or mandated objectives acceptably. Comparing how the basic computer tools used in the 2007 command center set-ups performed against how an alternative process would perform should demonstrate the need to move towards tools that are multi-user, require no consolidation of data, and which can be used with little to no training in the fast-paced environment of an emergency. Improving an existing business process draws justification from the theory of action research as discussed in the Technology Acceptance Model (TAM) of perceived usefulness (Venkatesh et al., 2003). TAM addresses the realm of computer technology and validation of the usefulness of employees’ outputs. Davis (1989) verifies the usefulness of the employees’ outputs based on their belief of how they performed in that activity. Additionally, Bandura (1982) reiterated the general concept with his self-efficacy model of people’s response and reaction being based on their perception of their competency in face of new technologies resulting from the computer and internet evolution. Bandura (1982, p. 122) stated, “A capability is only as good as its execution.” Based on this, converting the paper forms and spreadsheets used for the command center logistical effort in 2007 to an alternative tool might be indicated. The action research of this paper is using lessons learned to convert the information tracked in the spreadsheets to a more technological format for easier and faster access in emergency response. This serves as the impetus for improving the existing emergency response process via a technology tool (Bandura, 1982; Davis, 1989; Venkatesh et al., 2003). The data used in this paper is from the 2007 Firestorm responses of San Diego Gas & Electric’s command center support. Their spreadsheets,
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emails, phone calls, including the personal observations of the lead author, who participated in the effort, provided the data for this study. The action research format is appropriate for this paper because the research process involved manipulating outputs containing the command center logistical details and their role in the activities in the organization’s response to emergency situations. The data that were analyzed related solely to the support of the command center camps and what it took to sustain their mission as bases from which to deploy the electric restoration personnel during the power outages. The details surrounding the ordering, receiving, inventorying, handling, staging, and deployment of construction materials, such as poles and wires, were not the purview of BSLs’ work in support of the command centers. Material handling was the responsibility of the Logistics and Warehousing groups. The spreadsheet listed 25 categories of information that included the following column headings: Region, Need for Site: Yes/Pending, Site Name, Command Center/Staging Area, Site Coordinator & Phone #, Thomas Brothers page, Address, Start Date, Estimated End Date, Total # of People, Food Counts, #B, #L, #D, water buffalo Y/N or 5 gal H2o, # of Porta Potties, Trash bin type: trash/cable/metal/treated wood/recyclables, # of hand-wash stands, Portable Office Trailer, Copier, Lights, Generator(s), Parking Space Reqmnts (Requirements), Material Laydown Space Reqmnts (Requirements), Security, # of Vehicles, Phone /Data/Radio/Printer, BMP Materials, Notes/Comments. The data that were examined were three versions of the spreadsheet, Firestorm 2007 - Command Centers and Staging Areas, during the time frame of October 24, 2007 through November 10, 2007, to demonstrate the progression of the command centers’ expansion and contraction over time. The spreadsheet also displayed the types of items being tracked at a consolidated level.
Achieving Electric Restoration Logistical Efficiencies During Critical Infrastructure Crisis Response
WILD FIRE LOGISTICS During the week of October 21, 2007, wind-driven wildfires raged across San Diego County burning more than 360,000 acres and destroying at least 1,700 homes. As soon as the fires had moved through an area, SDG&E crews were on-site to assess damage to the utility’s assets. As a result, 750 SDG&E employees, along with 203 neighborstate mutual-aid personnel and, at peak periods, 78 contract electric crews and 129 digging crews, were deployed to perform the service restoration efforts. Service was restored for approximately 83,000 customers affected by the fire and SDG&E eventually replaced more than 2,170 utility poles, 338 transformers, and at least 35 miles of overhead electrical wire (Geier, 2009). Four years earlier, after San Diego County’s 2003 wildfires, SDG&E had refined a model for supporting the logistical components of establishing and supporting command centers. This model was ready for implementation during the October 21, 2007. SDG&E’s electric restoration response to the 2007 fires was supported by teams of employees from the Fleet, Facilities, Environmental, Supply Management, Logistics & Warehousing, Fleet Services, Facilities, Real Estate/Land, Environmental, and Safety departments (Dulgeroff, 2009). These teams were tasked with supporting the logistical needs for electric construction crews allowing the construction foremen and supervisors to be available to perform their core competency of repairing or rebuilding the electric system. Working in teams of approximately three people per shift, the support team employees were consumed for 10-15 hours a day for the first 10 days of the emergency. They had to respond to central points near the fire-damaged areas where they set-up command center camps to serve three meals a day. The command center sites included restrooms, shaded rest areas, water, ice, and snacks to all the crews who were working 16-hour shifts (Dulgeroff, 2009). In addition, the command center sites needed mobile offices with internet
connectivity (often via satellite due to the remote locations and/or damage to on-site power and telecommunications connections). Also required were helicopter landing areas for hard-to-access, power pole replacements, water trucks for dust mitigation in the rural settings, mobile radio repeaters, and dedicated space for all the materials to be staged for the crews’ use. Preventative environmental checklists had to be followed at the rural sites. Straw wattle to prevent run-off, steel shaker plates to keep the vehicles from tracking loose dirt out onto the streets, and traffic control where the extra traffic related to the command center made an impact to normal traffic flow at the entrance were all required. Sites that were designated just as material lay-down locations, still needed restrooms and trash containers (Dulgeroff, 2009). The region’s basic communications infrastructure was not impacted by the fires, therefore alternate communications systems were not needed in the 2007 firestorm. It is timely to note however that emerging technologies leveraging communications devices already being used are being tested for response to emergencies impacting infrastructure. This new type of infrastructure-less wireless network, such as Georgia Tech’s LifeNet model (Wilson, 2005), which is formed out of consumer electronic devices such as laptops or smart phones could have great utility in disaster scenarios impacting the traditional means of communications. Using consumer devices such as smart phones and laptops to remove dependence on a company’s local network infrastructure and data center could also be addressed by cloud computing. In SDG&E’s 2007 response, the team members used cell phones and laptops with air cards to track all the support activities and items for command centers, on spreadsheets that were emailed back and forth to the manager leading the command center efforts. This enabled them to track the logistics of all command center sites in a consolidated manner. Each day the team
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members participated in two conference calls with their counterparts, during which they were given updates from other SDG&E departments supporting the logistical efforts.
OBSERVED ISSUES The SDG&E team members who were serving as business solutions liaisons (BSLs) between the construction supervisors leading the restoration and rebuilding efforts of the crews, and the departments that procure and oversee delivery of the material and services used to set-up the command centers, reported occasions when their requests for items needed for the command centers were not conveyed exactly, or delivery was late. Other times requests were duplicated, or second and third calls were received from the providers to confirm if materials or meals were still needed, when the items had already been received. The BSLs’ daily submittal of the tracking spreadsheet to the manager’s administrative support required a significant consolidation chore and lacked real-time status. For example, an impact of the spreadsheet’s lack of timeliness was that if the BSLs needed to track something more timely than information from the afternoon before, they would have to participate in both conference calls each day, despite other tasks they might have been performing. Additionally, the BSLs needed to take their own notes as to what each command center team was reporting during the calls. Then, the spreadsheet combined with their handwritten notes provided them with more detailed information, but resulted in an abundance of paper. Further, the daily consolidation of spreadsheets from 17 different command centers contributed to the chance of errors being made. The possibility of achieving efficiencies through a more real-time method, rather than paper forms, repeated consolidation of emailed spreadsheets, and email requests first arose during the type of miscommunication reported above. This sug-
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gested an opportunity for investigation of a more real-time approach to handling the logistics related to the emergency response. The rush to procure water, meals, tents, lights, portable bathrooms, and mobile offices is all performed in competition with other responding agencies in the region, public and private-sector. Any lag in response time could present the loss of the opportunity to obtain what is essential. Because of that competition for scarce resources, the first five days of a response are the most timesensitive. Consequently, the potential for errors in the spreadsheets could have represented a loss of needed resources. Research discusses the range of spreadsheet errors from calculation errors, to one that is more germane to this study, errors in data quality. Caulkins et al. (2005) cite these errors in data quality as one of three typical reasons that contribute to undetected errors in an alarming “91 percent of spreadsheets” (p. 22). These authors contend that a simple task such as a “bad sort can destroy the integrity of a row, or a mismatch of units” (p. 23). This is supported by Panko’s research in which he estimated 94 percent of spreadsheets contain errors (Panko, 2007). Therefore, it is clear that any solution must need no manual manipulation of the data such as is needed when using spreadsheets for database functions. An alternate solution must also have virtually no training-time requirements, since the employees assigned to the task in subsequent emergencies will likely have no experience with the solution, nor would they have the luxury of time to learn it. The possibility of SDG&E changing its approach to command center logistics tracking as Commonwealth Edison and Duke Energy were able to do, merits further study. After the 2007 fires, event-assessment and debrief of the command center support personnel included the subject being raised of the efficacy of spreadsheets and paper forms and the question of whether an alternate approach could have achieved greater efficiencies, especially in
Achieving Electric Restoration Logistical Efficiencies During Critical Infrastructure Crisis Response
the areas where duplications and problems were encountered was posed. This study addresses the following research questions: •
•
•
What alternative approach would have enabled the teams working on the command center effort of emergency response to have easier-to-use, faster-to-access data? What solution would include the capability to store basic command center requirements from previous emergency responses to save time in addressing the first or most crucial items needed during the next emergency? What resiliency could be built into command center logistics tracking in case the company’s network was rendered inaccessible at the same time as command centers were needed for service restoration activities?
Therefore, if SDG&E’s electric or gas system was damaged by terrorist activity or another natural disaster with equal or greater severity than the firestorms of 2003 and 2007, tracking the command center logistics could become exponentially more difficult proportionate to the severity of the disaster. An alternative solution designed for easy access by users in multiple areas could enhance the support of the logistical efforts to bring the region’s critical infrastructure back to normalcy in the most effective manner possible. This study is designed to investigate the possibility of an alternate, multi-user approach, in order to improve accessibility or timeliness of information in a further refinement of disaster response tools. Results could aid decision-makers in their planning for subsequent emergencies. The present body of knowledge will be expanded by the study of converting from spreadsheets and paper forms currently used for some emergency management activities to more effective tools of response.
POST WILD FIRE ANALYSIS After the Southern California fires of 2003, the Sempra Energy utilities’ vice president of Business Solutions, and Directors leading the support-type departments of Supply Management/Logistics, Fleet Services, Facilities, Real Estate/Land, Environmental, and Safety, formulated a program to further enhance their support to field operations areas in their response to emergencies. That new program was enacted for the first time during the 2007 Southern California fires. Under a dotted line reporting relationship to a manager responsible for all command center and staging area sites, “Business Solutions Liaisons” (BSLs) fulfilled a strategy that was designed to provide them as central points of contact. They were to interface between the operating centers’ field operations and SDG&E’s high-level central coordination and communications Emergency Operations Center (EOC), during emergencies that necessitated the set-up of staging areas and/or crew deployment areas. The BSLs were selected from a qualified pool of employees from the support departments, and based on their availability to respond to remote locations for ten-hour shifts. The BSLs were to be a visible presence in the field to facilitate proper two-way communications between field operations groups, the support departments, and the EOC, where requests would be received and dispatched to the proper responding support departments. The BSLs were intended to be the “one-stop-shop” for all requests instead of field supervisors having to make requests of many areas for their needs (Dulgeroff, 2009). The BSLs are not examined in this paper as a population. Their data output, however, is the sample examined. The BSL program would be activated under certain conditions including: • •
The utility experiences a major event The EOC is activated
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Achieving Electric Restoration Logistical Efficiencies During Critical Infrastructure Crisis Response
• •
One or more off-property staging areas are needed It is requested by EOC staff
The BSLs had to be ready to mobilize at the beginning of an event through response and recovery. They were to engage with operating groups and coordinate with existing emergency response systems. In addition, the BSLs were to be familiar with field operations activities, be prepared for inclement weather, and be field-ready. Teams of two BSLs were assigned to each location to cover two shifts per day. Sites were determined by identifying areas where the utility’s system had sustained significant damage, for economies of adjacency in location decisions. If there was suitable land, and the area met strategic placement guidelines, a command center was located there (Dulgeroff, 2009). In the first three days of the emergency, the Facilities department was activating its baseline set of plans, to achieve the earliest response to the expected need for some type of field command centers or staging areas. Therefore, they already had contingency plans in place for rapid procurement of several large tents to house the resting and dining functions for the emergency response, generators, lighting, drinking water, catering, and portable sanitation services. As soon as they reported to their assigned command center locations with their laptops and air cards, cell phones, and personal protective equipment, BSLs checked-in with the construction supervisors to receive any logistical requests and support them in their core mission of directing system repair for service restoration of the utility system. As the emergency unfolded, appropriate numbers of utility personnel, mutual assistance crews, and contract construction company crews were deployed to repair damaged segments of the system (Dulgeroff, 2009) The BSLs were apprised by the construction supervisors, of the crew size increases or decreases, as work progressed across the damaged areas, and as mutual assis-
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tance crews arrived. The command center needs were adjusted depending on that crew movement (Dulgeroff, 2009). In order of priority, meals, water, ice, and sanitation facilities were the most important of the many things needed at the command centers. Shelter (tents), electricity, portable offices, internet connectivity, and garbage containers and garbage collection were next in order of priority. Following in priority were a fuel tanker to refuel the crew trucks and a pad for a helicopter to land, including a water truck to mitigate dust from the helicopter and the vehicle traffic. As soon as the BSLs reported to their assignments, they were to review the template documents in their binders, time permitting. There were often requests and/or people waiting for the BSLs as soon as they got to their locations, and the BSLs provided rapid response and follow-up on all requests. The One-Stop-Shop was an exceptionally successful response model because the construction supervisors’ needs were continuous and the BSLs execution of the ordering and tracking was a better use of company resources. It quickly became apparent that the paper request forms in the binder were unworkable, for two main reasons. The forms were meant to be handwritten, then faxed to the EOC representative for that request category, however, there were no fax machines available, at least in the first several days of the emergency. Further, the forms required name, date, and time information. The natural inclination of the BSLs was to call the EOC representative and initiate the request via cell phone call, then complete an email note with the same information as a written confirmation, and for ease of follow-up. The email notes automatically recorded name, date, and time information, and the BSL added the other shift’s BSL in the carbon copy line. Early in the process, the paper request forms served as helpful visual cues for the details that needed to be included in the phone and email requests, but beyond that were hardly used.
Achieving Electric Restoration Logistical Efficiencies During Critical Infrastructure Crisis Response
Similarly, the paper BSL Service Request Log was viewed as inconvenient given the Sent Items feature which saves sent-email in a folder in the sender’s Outlook program. Not all of the BSLs used this paper Log knowing their Outlook Sent Items function captured and archived them automatically and more permanently in case the information was needed at a later time. Given that the other shift’s BSL had been copied on any emails that alternate shift BSL did not need to review the paper Service Request Log to ensure smooth transition of information.
FINDINGS AND DATA ANALYSIS What alternative approach would have enabled the teams working on the command center effort for emergency response to have easier-to-use, faster-to-access data? What solution would include the capability to store basic command center requirements from previous emergency responses to save time in addressing the first or most crucial items needed during the next emergency? What resiliency could be built into command center logistics tracking in case the company’s network was rendered inaccessible at the same time as command centers were needed for service restoration activities? The 2007 Southern California fires damaged a large amount of San Diego County’s territory including, in some areas, SDG&E’s means of delivery of electric service, its poles, wires, cable, and transformers (Dulgeroff, 2009). SDG&E coordinated a full-scale effort to restore service for its customers as soon as possible. “To provide forward support closer to the actual field locations where the bulk of the repair and restoration work was occurring, SDG&E established ‘command centers’ and ‘staging areas’ in strategic locations” (Geier, 2009, p. 14). Establishing and maintaining the command centers and staging areas to support the crews in their restoration efforts, and ultimately closing them down, involved approximately 56
employees from supporting departments, for approximately three weeks in a significant logistical exercise (Dulgeroff, 2009). The process began with: (1) baseline requirements needed for a command center or staging area, (2) personnel assigned to the location to be the points of contact, called BSLs, and (3) the BSLs’ laptop computers with air cards for internet connectivity, the BSLs’ cell phones, a master spreadsheet to track all the details of all the command centers and consolidate them into one view, and paper forms on which BSLs could make requests for items needed at the sites. The spreadsheets did not look at the causes of the emergency, but helped manage the responses. The lead author, a team lead of the SDG&E supply chain systems team, served in the BSL capacity. The people who received the requests and information from the BSLs and fulfilled them were support department representatives manning their specific EOC positions. Each EOC position was staffed around the clock at the beginning of the emergency, and as appropriate later in the response, was reduced to 16 hours per day of coverage. The BSLs received all the requests associated with taking the command centers from their baseline configuration to fully-functioning field operations support, by working as the interface between the construction supervisors, the EOC representatives, and on occasion, directly with the vendors. The defined method for initiating a request for materials or services was in the library of paper forms. In practice however, instead of using the paper forms to initiate requests, there were two preferred methods by which BSLs sent requests to the EOC representatives. The first method was via cell phone call. The second method was via company email which was available via air card internet connectivity and VPN computer network access. These emails were often written followup to the initiating phone call. Also, since they were accessing the network via VPN, all internal
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Achieving Electric Restoration Logistical Efficiencies During Critical Infrastructure Crisis Response
drives and intranet pages and systems normally available to BSLs were accessible. The EOC representatives were on-site at SDG&E’s company headquarters location, and had the full company network available to them and received BSL email communications in that manner. The main tool used to handle the command center logistics effort was a spreadsheet. The spreadsheets used for this study are three samples of the daily iterations of the 2007 Firestorm command center and staging area consolidated information. All of the categories represented essential items needed to support response to the emergency. Many of the BSLs’ actual practices did not include filling-in the paper forms, which meant the paper forms provided in the binder went unused. The service request log in the binder was also not used by the BSLs as they preferred the daily-updated spreadsheets that conveyed the entire command center landscape. The spreadsheet in its consolidated form was the most significant tracking output of that effort. The main benefit of the spreadsheet was the ability to track, albeit a day later, the logistical details of the command center, which included upward reporting to and by the manager. This information was kept current by the BSLs completing and emailing the spreadsheets back to the manager after the afternoon conference call, for his administrative support’s updating. The inherent inefficiency of its manual consolidation prompted the research questions. A consideration of efficiencies to be gained and opportunities to track more categories of information, if needed, might reveal a new structure for the process, using an alternative approach to the paper forms and the spreadsheet. Consequently, the analysis of efficiency of the spreadsheets compared to real-time access to data, might include a new technology or a combination of several. An examination of the details of forms on smart phones, dashboards, blogs and wikis, and cloud computing would be timely, as SDG&E continuously strives for improvement of its crisis response.
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DISCUSSION Based on the data resulting from SDG&E’s 2007 Firestorm command center support response analysis, two hours a day of conference call attendance, paper form requirements, and editing of the spreadsheet by each BSL team, indicates opportunities to improve efficiency exist. Several possibilities for alternative approaches to command center logistics tracking are growing in use and popularity. To address the first research question on what alternative approach to emergency response logistics tracking would be easier-to-use and provide faster access to data, rendering forms on smart phones in replacement of paper forms, blogs for BSLs to convey new situations or information they encounter, via a posting on a webpage, making it readily searchable for the next crisis, wikis, which can capture blog information of a more formal or permanent nature to document processes or procedures, and dashboards as a means to display the real-time, consolidated, command center information, links, and metrics are suggested. The use of a database as the backend data repository supporting what is displayed in dashboards related to the second question, and the concept of cloud computing related to the third research question will be discussed later. This combination of alternatives incorporates the concept of building resiliency into a company’s activities supporting critical infrastructure response work, as well as reducing duplicative or outdated methods. It also can be viewed through the lens of the expanded crisis response system model (Jennex, 2004). The expanded system encompasses more than the basic components of database, data analysis, normative models, and interface. Enhancing the model includes the addition of trained users (where users are personnel using the system to respond to or communicate about the emergency and consist of first responders, long term responders, the emergency response team, and experts), dynamic, integrated, and collabora-
Achieving Electric Restoration Logistical Efficiencies During Critical Infrastructure Crisis Response
tive (yet possibly physically distributed) methods to communicate between users and data sources, protocols to facilitate communication, and processes and procedures used to guide the response to and improve decision making during the crisis. This expanded crisis response system model is applicable to the discussion of combining alternatives in order to better respond to the logistics tracking activities of SDG&E’s emergency response. Specifically, the dashboards fulfill the model’s condition for a dynamic method of communication, based on the real-time nature of the information received and displayed. The potentially constantly updated information supports the optimum display to users of what is residing in the underlying data sources and, further, to non-users such as executive teams, and decision-makers. The dashboards also fulfill the model’s component of integrated and collaborative protocols by their attribute of displaying multiple types of information from multiple sources or contributors that would not normally be displayed together in a single view, or viewable by so many different parties. Additionally, the nature of the field operations and the EOC functions being physically separated conforms to the model’s almost-certain distributed teams, sites, and means of communications. The sometimes duplicative activities associated with the BSLs’ use of paper forms and follow-up phone calls, and the time-consuming consolidation of that information in a spreadsheet with limited visual display characteristics, implied one or all of these alternatives may have efficacy in improving BSL-related data output in subsequent emergency efforts, as supported by the Jennex expanded crisis response system model. The result of analyzing enhanced concepts to the command center tracking needs, suggests further study of forms on smart phones, and dashboards connected to a robust back-end database already populated with baseline data as a starting template to save time, residing on remote servers in a private cloud. A site linked to the dashboard on which any participant in the command center effort could
blog about any special experience for sharing with the other team members would be timely as well as easy to access. Problems or issues discussed in the blogs and successfully addressed, could be elaborated upon or documented in a more formal and thoroughly developed way and posted as a wiki, as a more permanent and searchable archive. The need for resiliency in case of unforeseen inaccessibility, suggests the use of private cloud computing, which would result in a virtual, secure, remote location for SDG&E-related command center activities to be developed, housed, and delivered. That need for secure software and data is important because of the proprietary nature of the information. Therefore, a practical solution to help the utility in case of a catastrophic loss of its computer network might include private cloud computing. Possibilities of technological alternatives other than these may be suited for transforming the spreadsheets and the paper forms, and displaying command center logistics however, the intricacies of the related technology need to be addressed as further suggestions. The viability of these technologies in support of alternative systems for crisis response is derived from Jennex and Raman (2009). The forms on smart phones, blogs and wikis, cloud computing, and the dashboards similar to those developed by SDSU’s Visualization Center for flu tracking in San Diego County when implemented together, can all be considered components in the fusion of KM systems (Jennex & Raman, 2009). Filling out paper forms and completing the spreadsheets was actually just the manual assembling of a list of data in columns and rows. It was not a meaningful transfer of ideas, needs, and information. When ideas, needs, and information are assembled without further requirement for consolidation or user adaption, and then easily rendered visually, it results in expedient crisis response through impactful visual cues and a more efficient transfer of knowledge. The implication is the tacit knowledge from BSLs’ previous experiences can not be appropri-
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Achieving Electric Restoration Logistical Efficiencies During Critical Infrastructure Crisis Response
ately conveyed in a single file when the information is simply housed in a spreadsheet’s columns and rows format. However, the multi-dimensional, graphical layering, and photographic images displayed in a dashboard format heralds the emergence of knowledge transfer that would benefit the evolution of SDG&E’s emergency response model. Blogs to capture BSLs special experiences or issues, and wikis to more permanently archive the blog posts that lend themselves to formal processes and procedures, provide a searchable, easy to access forum for command center participants’ specific information, and should be included as links in the dashboard. Handling the knowledge in support of crisis response in this manner substantiates the Jennex and Raman (2009) assertion that, decision makers, when under stress, need systems that do more than just provide data, they need systems that can quickly find and display knowledge relevant to the situation in a format that facilitates the decision maker in making decisions.
IMPLICATIONS AND RECOMMENDATIONS The research related to the spreadsheets revealed that they performed in an adequate manner based on the fact that the command center logistics tracking was generally accurate and the consensus among the interfacing groups was that the command center model performed very well. However, the lag time in displaying updated information on the distribution of the crews across the command center landscape during a day, and how that impacted meal counts which, potentially dramatically affected the crews’ perception of well being, can be surmised due to the manual consolidation effort necessary to keep spreadsheet data current. The literature validates the significance of the crews’ perceived well being as having substantial importance. Relative to the discussion of the crews’ well being, a tangent factor of the BSLs’ efforts in the
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command center support was their stated feelings of satisfaction related to their accomplishments, as discussed in a BSL debrief meeting in November 2007. The perceived usefulness of their efforts and their feelings of self-efficacy gave an indication of how likely BSLs would be to embrace alternative approaches to the work if it meant further improvement in their response to a crisis. While this relates to implementing knowledge management systems in support of crisis response (Jennex & Raman, 2009) it must be acknowledged that the responsibility for efficient and timely restoration of essential services is still a mandate from the federal government as codified in HSPD7. Despite SDG&E’s culture of dedicated restoration activities, the BSLs’ satisfaction in support of the company mission, or the opportunity to leverage computer technology and knowledge management systems to enhance the logistical support, the restoration activities would still be required by the federal government even in the absence of those company requirements and employee satisfaction drivers. It also should be recognized that there could be a scenario when the normal network systems for achieving compliance with HSPD 7’s requirements would be completely interrupted. In the event of a loss of SDG&E’s computer network infrastructure, an alternative to the company network would be needed to handle the on-going restoration tracking efforts. One alternative to the traditional and local company network would be via cloud computing. In the event SDG&E’s computer network was rendered unusable, whatever applications were needed for the command center response could be housed on virtual servers in the cloud, and accessed via the internet, likely through wireless connectivity such as the BSLs’ air cards. The implication is SDG&E could continuously access its disaster response support tools if they were housed and delivered outside the company network. The security aspect would be addressed by using the cloud computing model known as
Achieving Electric Restoration Logistical Efficiencies During Critical Infrastructure Crisis Response
the private cloud, in which processing, storage, networking, and the application, are via an intranet, allowing for user authentication, and encryption of the company’s proprietary data. Computing via the cloud also allows for applications to be used on a pay-as-you-go pricing schedule (Vanmechelen et al., 2006). This would allow the cost of an important emergency response tool, after its initial development costs, to be borne only at the time the company is experiencing an emergency. Responding to emergencies often carries great costs, some of which can be recovered in rates if SDG&E’s governing regulatory agency grants such a request. Matching the costs of a paywhen-used type of emergency response support tool to the infrequent occasions of emergencies impacting SDG&E’s critical infrastructure, supports a position of careful stewardship of costs the company will eventually request to recover. Further, using cloud-based tools to house an emergency response logistics tracking application securely outside SDG&E’s territory and having it be accessible via any internet-based connection along with VPN, provides a resilience to catastrophic wildfire- or earthquake-caused network destruction that would interfere with tracking of, although not halt, SDG&E’s restoration activities in the field. Analysis of the manual, and not-well-used paper forms for BSLs to send requests to the EOC, demonstrated the need for an alternate request method. As was demonstrated by actual practice, phone calls and follow-up emails were preferred to the paper forms. However, the email was duplicative to the phone call, which suggests a less-than-optimal use of the BSLs’ time. The rendering of a paper form for display and user input on a smart phone has potential utility as the technology to replace the paper forms for command center logistics requests. Data initiated by the request is needed to execute the activity and provides the EOC recipient with record of the exact details needed for accurate fulfillment, almost always better than a phone call
request, but usually not faster. Yet the BSLs all had cell phones and continuously made requests initiated by phone calls then followed-up with emails for solid confirmation. An alternative is using a smart phone with a form accessed from the phone’s embedded memory. The efficiency of using the hand-held portability and instant communications of a cell phone, while having the accuracy and full detail inherent in a form, can both be achieved with this technology. The electronic forms housed in the smart phones’ memory could also be available in a library of request forms linked on the dashboard, as a secondary and back-up location to the smart phones. The practices of the BSLs in the field imply this alternative merits further investigation and possible piloting during future SDG&E emergency drills. Another implication for future research addresses the need to experiment with the dashboard as a more informative alternative for the current spreadsheet data and to house links to other BSLneeded information. A test model would include a dashboard being provided to the BSLs, their decision-makers, and related support departments for further determination of the efficacy of the technology. The user requirements of both dashboard and cloud computing would be structured by the technical staff at SDG&E to determine whether cloud computing and dashboards are viable alternatives to replace the current emailed spreadsheet. The spreadsheet as the most significant tracking output of the BSLs’ 2007 efforts is important when considering how such a single, relatively simple file was the source for tracking a great deal of valuable SDG&E-owned or rented assets, providing the manager with the ability to report to the EOC and the Executive team, the extent of the command center support of field operations and his decision-making related to consolidations of sites, or needed geographical changes, particularly while the fires were still burning. Considering those substantive uses of the spreadsheet, the lag time in the data’s accuracy
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due to the need for consolidation, indicates the audiences could be better served as more realtime technologies become achievable for this specific purpose. Furthermore, the recognition of the potential need of other categories and/or sources of information implies the spreadsheet format was already at the limit of its utility. The need for a tool with the ability to display data in a visual, real-time format, with links to additional helpful or related sources of information such as BSL-related blogs and wikis, seems a likely area for future study, since dashboards provides internet-browser display of many categories of data from potentially many sources. Dashboards also provide for understanding of performance indicators of importance to a specific audience, by summarizing them and often displaying them by graphical icon. The summarized data displayed in a dashboard can be the starting point to drill down to their detail. Conveying the data in a summarized, graphical way represents a significant, behind-the-scenes effort of collection, consolidation, and presentation of the data that starts to transfer tacit knowledge when the consolidation allows for decision-making based on the whole picture that is drawn by the dashboard. Dashboards support two important points made by Turoff, supplying the best possible up-to-date information is critical to those whose action may risk lives and resources and that an emergency response information system must be an integrated electronic library of external data and information sources (Turoff, 2002). The data in SDG&E’s command center tracking spreadsheet has the potential to become enhanced decision-making information and therefore knowledge that can be applied by its users through the use of baseline data from past command center experiences to respond to a present emergency. Using a dashboard displaying data taken from the spreadsheet categories in a more actionable manner could enhance decision-making or at the least, readability and timeliness. The summarization and display of all of these types of information
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sources in a single dashboard enables viewers to drill down to access other websites, company intranet pages, participant blogs, related wikis, detailed data from maps and databases, and have it all accessible real-time. It would be a significant enhancement to the ways this information was available to SDG&E’s emergency response support teams in previous emergencies. This practice of selectively applying knowledge from previous experiences during turbulent moments of decision making, to current and future decision making activities with the express purpose of improving the organization’s effectiveness, would be possible via a KM system (Jennex & Raman, 2009) such as a dashboard along with its underlying means of delivery.
CONCLUSION This paper proposes using knowledge to drive an alternative to SDG&E’s paper request forms for command center needs, and suggests the use of request forms rendered on smart phones assigned to the BSLs for the duration of the effort. In addition, the development of dashboards, including links to command center participant blogs and wikis, is suggested as an effective alternative to spreadsheets to track the command center logistics, and provide easy to access information by means of links. Finally, the use of cloud computing as the development platform and host of an SDG&E dashboard application is recommended as a timely evolution to a KM system approach to achieve logistical tracking efficiencies.
REFERENCES Bandura, A. (1982). Self-efficacy mechanism in human agency. The American Psychologist, 37(2), 122–147. doi:10.1037/0003-066X.37.2.122
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Caulkins, J. P., Morrison, E. L., & Weidemann, T. (2005). Spreadsheet errors: Are they undermining decision making in your organization? Public Management, 34(1), 22–27.
Jennex, M. E., & Raman, M. (2009). Knowledge Management is Support of Crisis Response. International Journal of Information Systems for Crisis Response and Management, 1(3), 69–82.
Davis, F. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. Management Information Systems Quarterly, 13(3), 319–340. doi:10.2307/249008
Panko, R. P. (2007). Two experiments in reducing overconfidence in spreadsheet development. Journal of Organizational and End User Computing, 19(1), 1–23.
Dulgeroff, A. (2009). Application of San Diego Gas & Electric Company (U 902 M) for authorization to recover costs related to the 2007 Southern California wildfires recorded in the Catastrophic Event Memorandum Account (CEMA). Retrieved from http://www.sdge.com/regulatory/ documents/a-09-03-011/testimony-dulgeroff.pdf
Turoff, M. (2002). Past and future emergency response information systems. Communications of the ACM, 45(4), 29–32. doi:10.1145/505248.505265
Geier, D. L.(2009). Investigation on the Commission’s own motion into the operations and practices of Cox Communications and San Diego Gas & Electric Company regarding the utility facilities linked to the Guejito Fire of October 2007. Jennex, M. E. (2004). Emergency Response Systems: The Utility Y2K Experience. Journal of Information Technology Theory and Application, 6(3), 85–102. Jennex, M. E. (2005). What is knowledge management? International Journal of Knowledge Management, 1(4), i–iv. Jennex, M. E. (2007, August 25). Knowledge Management in Support of Crisis Response. Paper presented at the ISCRAM China Workshop.
Vanmechelen, K., Stuer, G., & Broeckhove, J. (2006). Pricing substitutable grid resources using commodity market models. Retrieved from http://www.coms.ua.ac.be/publications/files/ KVM_GECON_2006.pdf Venkatesh, V., Morris, M., Davis, G., & Davis, F. (2003). User acceptance of information technology: Toward a unified view. Management Information Systems Quarterly, 27(3), 425–478. Whybark, D. C., Melnyk, S. A., Day, J., & Davis, E. (2010). Disaster Relief Supply Chain Management: New Realities, Management Challenges, Emerging Opportunities. Decision Line, 4-7. Wilson, S. (2010). Next generation disaster communications technology now a reality with LifeNet. Retrieved September 25, 2010, from http://www. scs.gatech.edu/news/next-generation-disastercommunications-technology-now-reality-lifenet Zuber-Skerrit, O., & Fletcher, M. (2007). The quality of an action research thesis in the social sciences. Quality Assurance in Education, 15(4), 413.
This work was previously published in International Journal of Information Systems for Crisis Response and Management (IJISCRAM), Volume 2, Issue 3, edited by Murray E. Jennex, and Bartel Van de Walle, pp. 36-50, copyright 2010 by IGI Publishing (an imprint of IGI Global).
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Chapter 3.14
Assessing the Impact of Mobile Technologies on Work-Life Balance Sharon Cox Birmingham City University, UK
INTRODUCTION Mobile technologies such as laptops and mobile phones enable work to be conducted remotely, away from the normal working environment. Removing the geographical boundaries between work life and home life poses new challenges within the context of maintaining a healthy worklife balance. This article proposes a multidimensional model for assessing the impact of mobile technologies on work-life balance considering DOI: 10.4018/978-1-60960-587-2.ch314
social, organizational, legal, technological, and ethical issues to inform the development of human resource strategies.
BACKGROUND ‘Work’ and ‘life’ are traditionally viewed as separate spheres which need to balance such that one does not adversely affect the other (MacInnes, 2005). Stress occurs when the spheres are out of balance (Rotondo, Carlson, & Kincaid, 2003). Improving work-life balance can help:
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Organizations to work effectively and efficiently; and Individuals manage their time and reduce pressures that encroach on their life outside the workplace.
The notion of balance implies the need to establish clear boundaries between work and home lives. This is expressed as “being able to come to work and not worry about my life outside of work and going home without having to worry about work.” Work-family interference (WFI) occurs when work issues adversely impact family life and family-work interference (FWI) occurs when the pressures from non-work issues adversely impact the work sphere (Greenhaus & Beutell, 1985). The employers for work-life balance (EfWLB) define work-life balance as being about giving people control of when, where, and how they work such that they can be fulfilled and enjoy an optimum quality of life, whilst being respected in the workplace (McIntosh, 2003). It should not be assumed that work-life balance policies are only of interest to employees with children; having time for taking part in learning, the community, and social activities are important factors for a healthy lifestyle (MacInnes, 2005). Traditionally, studies focus on the tension of needing to be in two places at the same time: the workplace and the home. This has led to a central theme in work-life balance being that of control; control is often expressed in terms of ‘flexibility,’ the ability to make choices and having the freedom to prioritize in accordance with personal values and maintain an equilibrium between multiple roles. Mobile technologies, such as wireless Internet access, laptop computers, mobile telephones, PDAs (personal data assistants), and other handheld devices, increasingly enable ease of access to data, applications, and people that was previously restricted to the workplace. This provides the opportunity for employees to work away from a regular workplace and changes the significance of the location factor in the work-life dyad. How-
ever, easing the ability to ‘bring work home’ also introduces tension by enabling work to (further) encroach on family life. Work-life is now recognized as being bidirectional and multidimensional (Rotondo et al., 2003). This is supported by Warren (2004) who suggests that discussion should be repositioned as work-life integration. It includes time-based conflict where time in one role affects participation in the other; strain-based conflict where the demands of one role affect participation in the other and behavior-based conflict where behavior appropriate in one role is used in the other role (Greenhaus & Beutell, 1985). The following sections discuss the impact of mobile technologies on work-life balance.
ASSESSING THE IMPACT OF TECHNOLOGY ON WORK-LIFE BALANCE The impact of technology can be seen both as positive and negative (Berg, Mörtberg, & Jansson, 2005). Technology facilitates working arrangements such as teleworking (Tietze, 2005) and mobile working (Prasopoulou, Pouloudi, & Panteli, 2006) which can benefit both employers and employees. These benefits are summarized in Table 1. Technology can make communication easier but it can also be an intrusion. Addressing location issues resolves some problems in work-life balance, for example, being able to work at home to be with a poorly child, but blurs the boundary between work and home (Prasopoulou et al., 2006) making it harder to balance work and home life. Flexible working can become abused when the normal expectation is that someone can be contacted anywhere anytime about work related issues. The work-life battle moves from location-based issues to demands for attention; reflected in the need to be available to respond to work issues at home.
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Table 1. Benefits and issues of mobile and teleworking
Issues
Benefits
Employees Flexible scheduling to work around family situations. Reduced commuting time and travel expenses. Greater geographic flexibility. Remote working is practical and cost-effective. Enables people with illness, disability, or lack of access to transportation to join the workforce.
Reduced overheads. Improved staff retention as employees can live remotely. Improved productivity as employees are more productive at home and work longer hours. Reduced impact of traffic delays and bad weather. Increased market of potential employees to recruit. Benefits local economies by helping people to stay/return to remote rural areas.
Costs incurred (e.g., heating, lighting, electricity). Discipline needed as the structure of ‘going to work’ is removed. Create a workspace and develop strategies for working effectively at home. How to separate work from home life and control the number of hours worked. Avoiding becoming isolated and disconnected from the company’s culture.
More difficult for managers to understand the skills of people reporting to them which affects performance reviews. Lack of organizational learning if performance is focused on deliverables rather than the processes used. Some managers feel that they have little control over staff working at a distance and that employees will abuse this privilege. Ensuring that remote workers do not become disconnected from the company’s culture and ensure effective communication. Changing processes to ensure that remote workers are appropriately supported.
Organizational Culture and Individual Empowerment The work-home culture is a key element of the workplace that impacts work-home interference (Beauregard, 2006). Mobile technologies impact the temporal boundaries between work and social activities (Prasopoulou et al., 2006) as information sharing and communication activities can be performed irrespective of time and location. Mobile phones are at the interface of the private and public spheres of life (Prasopoulou et al., 2006). They provide a fixed point of reference for connectivity and communication enabling a person to remain accessible (Srivastava, 2005). However, the ease with which a person can be contacted via a mobile phone can be a double-edged sword (Townsend & Batchelor, 2005). Prasopoulou et al. (2006) report examples of organizations where standard working hours are in place and it is not acceptable to call colleagues on their home landline (as this is perceived as intrusion into personal life), yet it has become acceptable to contact colleagues at home on their mobile phone after hours. Institutionalization of ‘anytime anywhere’ availability is exasperated as
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Organization
mobile phone numbers tend to be more widely distributed to colleagues who would not have access to home phone numbers (Prasopoulou et al., 2006). Some employees are unwilling to turn off their mobile phones at home as the organizational culture favors the prioritization of work over family and employees perceive that failing to respond to work requests ‘after hours’ would result in negative career repercussions (Beauregard, 2006). Other employees are aware of the risks of increasing stress caused by mobile telephones and switch them off at the end of the day (Berg et al., 2005). The growing acceptability of this work-family interference establishes new organizational norms and raises social issues. Context-sensitive computing technology incorporates features to help moderate the ‘anytime anywhere availability’ situation. Devices can be programmed according to organizational policies and individual preferences. For example, a mobile phone can be set not to ring if the electronic schedule indicates that a person is in a meeting (Colbert & Livingstone, 2006) or has finished work for the day. Hill, Miller, Weiner, and Colihan (1998) emphasize that training should not only include instruction on how to use the mobile technology
Assessing the Impact of Mobile Technologies on Work-Life Balance
but also include the social and psychological changes that are required in teleworking and mobile working. This requires the repositioning of organizational culture and personal empowerment.
Social Issues of Community and Occupational Identity Working away from the workplace requires employees to develop self-efficacy and recognize their responsibility to adhere to organizational codes of conduct and procedures. Beauregard (2006) proposes that personal, as well as organizational factors may influence the work-home interface. For example, personality may influence the amount of work taken home and the strategies for dealing with the interference. The work sphere contributes to how an individual forms their occupational identity (Tietze, 2005) and social contact requires a community setting with established norms. Working in one or more locations at a distance from colleagues challenges occupational identity and the manner in which communities evolve. When the work and life spheres are geographically separated, roles and behaviors are easier to define and separate, reducing behavior-based conflict.
Ethical Issues Teleworking blurs the boundaries between the work and home-life spheres and the cultural boundaries around them need to be redrawn (Tietze, 2005). This may involve designating spaces in the home for work tasks and developing rituals to disengage and separate work from home life (Hill et al., 1998). Strain-based work-family interference is of particular concern in professions such as healthcare, involving surface acting and emotional labor. Schulz, Cowan, Pape Cowan, and Brennan (2004) define emotional labor as the emotional suppression needed in order to accomplish tasks or protect relationship boundaries and the emotional regulation, such as surface acting (exhibiting emotions
that are not felt), required for social interaction. The commute between work and home facilitates the transition between the two spheres of life, providing the time, space, and routine to re-adjust. Montgomery, Panagopolou, and Benos (2005) use the metaphor of scuba-diving decompression to reflect the transition from work to home. People working in emotional environments need to “decompress” before returning into their home life. This may take the form of structured or informal debriefing procedures. Where ‘work’ is conducted in the ‘home’ environment, this decompression is more difficult to facilitate and can increase workfamily interference. Montgomery et al. (2005) suggest that emotional management training and opportunities for emotional decompression for health-care professionals should be explored. The strain of the work undertaken is increased by the isolation and separation from colleagues who can provide an informal support network. Debriefing and support mechanisms therefore need to be established to assist mobile and teleworkers in managing the strains of emotional labor.
Technology and Organizational Processes Technology enables remote working but the productivity gains from such practices can be limited by not having the right technology and business processes. The design of the technology also needs to be considered. Lee (2006) identifies the following device issues that can affect the ease with which tasks can be conducted remotely: design of menu structures, accessibility factors, battery duration, screen size, and weight. Remote working can reduce costs, increase staff motivation, and improve operational flexibility (Tietze, 2005), but requires the redesign of business processes and working practices (Clear & Dickson, 2005). This is particularly relevant to support processes requiring physical signatures or physical attendance at regular meetings (Pearlson & Saunders, 2004). Attention also needs to be given to the manner in
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which other central services, such as IT support, are delivered (Hill et al., 1998). Mobile technology poses security risks to the organization, including the physical security of the device and the person using it, the security of data held and transmitted and the risk of data corruption and virus infection when the device is returned to the workplace. Organizations need to revise their technical security policies to include for example, the standard use of data encryption and the disabling of infrared ports. Guidelines are needed to advise staff on how to transport and use the devices safely, for example, not to send data via infrared in public places. Pearlson and Saunders (2004) point to a ‘flexibility paradox;’ organizations need procedures in place to ensure that the organization continues to work effectively therefore flexible working requires structured approaches to business processes.
Legal Issues Legislation requires that organizations investigate the provision of flexible working policies. The impact of such policies on other areas of legislation such as software licensing (Lee, 2006), data protection, and health and safety policies needs to be considered. Guidelines exist surrounding, for example, the acceptable length of time spent using a computer without taking a break and the organization of workstations to reduce the risk of back problems and conditions such as repetitive strain injury. These guidelines need to be extended to include for example, the safe and appropriate use of laptop computers and the organization of workstations in the home.
MEASURING THE IMPACT OF MOBILE TECHNOLOGY Technology changes the way work is conducted including the skills required, communication patterns, collaboration patterns (how people work
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together and the degree to which they need to), the way people are managed, and the manner in which their performance is assessed (Pearlson & Saunders, 2004). Figure 1 presents a model of the factors to be considered within work-life balance. Hyman, Baldry, Scholarios, and Bunzel (2003) define a number of measures of work-family interference; tangible measures include the frequency of: work at weekends, paid and unpaid overtime, and the extent to which work is taken home; intangible measures include the degrees to which employees perceive that work has adversely affected health, they think about work in ‘family time,’ they feel exhausted after work, they are kept awake at night by problems at work, work prevents them spending time with family/friends and the frequency of feeling stressed. Previous measures of family-work interference and workfamily interference are extended in Table 2 which proposes parameters for measuring the issues identified in Figure 1. This provides a tool for assessing the impact of mobile technology on work-life balance in an organization which can be used to inform the development of human resource strategies.
Figure 1. Model of impact of mobile technologies on work-life balance
Assessing the Impact of Mobile Technologies on Work-Life Balance
Table 2. Parameters for assessing the impact of mobile technologies on work-life balance Factors Affecting Work-Life Balance
Parameters for Measuring the Impact of Technology on Work-Life Balance
Areas to Inform the Development of Human Resource Strategy
Social
Frequency of interruptions during social time. Duration of interruptions. Significance/importance of the interruption. Additional work generated by the interruption.
Agreement on normal hours of availability. Prepare ‘etiquette’ guidelines for contacting staff out of hours and for managing the expectations of availability. Develop training programme to raise awareness of impact on work-life balance.
Organizational
Percentage of time spent working off site. Number of trips to main company site. Number of calls out of hours. Number of calls to mobile phone. Opportunities for flexible working. Clarity and equality of policies about opportunities for, and availability of, flexible working and procedures for flexible working. Cultural acceptance of flexible working. Availability of processes for working outside the office. Ease with which equipment can be removed. Accessibility of systems outside the workplace. Processes to manage remote staff. Processes for evaluating performance. Processes for career development. Availability of support services for remote workers.
Develop policies for facilitating and supporting flexible working. Prepare policies to support the management, performance evaluation, and career development of remote staff. Establish broad training programme encompassing social and technical issues. Emphasize greater importance of communication and participation opportunities.
Legal
Total number of hours worked. Number of hours worked outside ‘normal’ office hours. Number of hours worked at evenings/weekends. Number of holiday days taken. Time spent ‘working’ whilst on holiday (e.g., checking e-mail). Time spent using technology between breaks. Length of breaks. Policies on staff conduct. Fair procedures for monitoring staff so that evidence can be attained on those that abuse the system. Procedures for holiday and sickness. Security of data. Number of software licenses for off-site working.
Clear guidelines and monitoring procedures for staff performance. Software licensing. Data protection.
Technological
Availability of required technology (and system access). Percentage of time spent on data access and transmission. Accessibility of technology. Availability of technical support. Ease of use of systems. Security of data and equipment. Availability of safe working conditions (e.g., appropriate furniture).
Health and safety of mobile working. Ethical use of technology. Data security. Technical support. Training in safe use of technology. Risk assessment procedures.
Ethical
Opportunities and support for emotional labor decompression. Opportunities for mobile and flexible working. Perceptions that 24x7 availability of staff is expected. Degree of involvement in decision making and organizational culture. Openness of availability of flexible working opportunities.
Develop policies for facilitating flexible working. Establish clear policies for communication and participation opportunities. Guidelines on expectations of staff conduct. Support mechanisms for mobile staff. Incorporate mobile working policy in vacancy adverts. Advertise vacancies widely.
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FUTURE TRENDS
CONCLUSION
Mobile technology has improved the communication processes within the work sphere, facilitating flexible working patterns enabling organizations to meet the demands of the 24x7 digital economy whilst empowering staff with the flexibility to control their work-life integration. The previous discussion highlights how expected availability adversely affects the home sphere by increasing work-family interference. Emerging technological trends will continue to blur the work-life boundary, paradoxically perhaps, improving aspects of the home sphere at the expense of the work sphere. It is claimed that ubiquitous technologies, such as processors and Internet connections embedded in domestic appliances will improve the home sphere. For example, a refrigerator connected to the Internet can reorder produce consumed. However, this may adversely affect the work sphere by increasing the demands placed upon staff to be available 24x7 and increasing the demand for electronic communication whilst reducing social interaction. As technology drives electronic business and mobile working, organizations need to take responsibility for managing the social aspects of work practices. Drucker’s (1988) prediction of organizations of orchestrated knowledge-workers can be reduced to organizations of disparate remote automatons unless actions are taken to protect and enhance the lives of teleworkers. Drew and Murtagh (2005) propose that trends in the over, and often inappropriate, use of technology need to be countered by guidelines to reduce the intrusion of technology by, for example, restricting contact to staff outside office hours. However, such guidelines need to consider the communication needs of mobile workers who choose to work outside office hours.
Mobile technologies increasingly enable ease of access to data, applications, and people that was previously restricted to the workplace and empower individuals with greater freedom to choose when, where, and how to balance the demands of their work and home lives. Although employees can work at home, they should not be expected to do so. Human resource strategy needs to address the impact of mobile technology on employees and adopt appropriate guidelines to maximize the benefits offered by the technology whilst protecting the employee from inappropriate demands being made on them; protecting the customer from lack of service availability and protecting the organization from risks such as misappropriation of resources and data protection issues. This article presented a model and parameters with which to assess the impact of mobile technology on work-life balance and assist the development of human resource strategies to address the opportunities and challenges offered by mobile technology.
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REFERENCES Beauregard, T. A. (2006). Predicting interference between work and home. Journal of Managerial Psychology, 21(3), 244–264. doi:10.1108/02683940610659588 Berg, E., Mörtberg, C., & Jansson, M. (2005). Emphasizing technology: socio-technical implications. Information Technology & People, 18(4), 343–358. doi:10.1108/09593840510633310 Clear, F., & Dickson, K. (2005). Teleworking practice in small and medium-sized firms: Management style and worker autonomy. New Technology, Work and Employment, 20(3), 218–233. doi:10.1111/j.1468-005X.2005.00155.x
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Colbert, M., & Livingstone, D. (2006). Important context changes for talking and text messaging during homeward commutes. Behaviour & Information Technology, 25(5), 433–441. doi:10.1080/01449290500330240
Montgomery, A. J., Panagopolou, E., & Benos, A. (2005). Emotional labor at work and at home among Greek health-care professionals. Journal of Health Organization and Management, 19(4/5), 395–408. doi:10.1108/14777260510615413
Drew, E., & Murtagh, E. M. (2005). Work/life balance: Senior management champions or laggards? Women in Management Review, 20(4), 262–278. doi:10.1108/09649420510599089
Pearlson, K. E., & Saunders, C. S. (2004). Managing and using information systems: A strategic approach. Chichester: Wiley.
Drucker, P. F. (1988). The coming of the new organization. In Havard Business School. Havard Business Review on Knowledge Management (pp. 1-19), Harvard Business School Press.
Prasopoulou, E., Pouloudi, A., & Panteli, N. (2006). Enacting new temporal boundaries: The role of mobile phones. European Journal of Information Systems, 15(3), 277–284. doi:10.1057/ palgrave.ejis.3000617
Greenhaus, J. H., & Beutell, N. J. (1985). Sources of conflict between work and family roles. Academy of Management Review, 10(1), 76–88. doi:10.2307/258214
Rotondo, D. M., Carlson, D. S., & Kincaid, J. F. (2003). Coping with multiple dimensions of work-family conflict. Personnel Review, 32(3), 275–296. doi:10.1108/00483480310467606
Hill, E., Miller, B., Weiner, S., & Colihan, J. (1998). Influences of the virtual office on aspects of work and work/life balance. Personnel Psychology, 51(3), 667–684. doi:10.1111/j.1744-6570.1998. tb00256.x
Schulz, M. S., Cowan, P. A., Pape Cowan, C., & Brennan, R. T. (2004). Coming home upset: Gender, marital satisfaction and the daily spillover of workday experience into couple interactions. Journal of Family Psychology, 18(1), 250–263. doi:10.1037/0893-3200.18.1.250
Hyman, J., Baldry, C., Scholarios, D., & Bunzel, D. (2003). Work-life imbalance in call centers and software development. British Journal of Industrial Relations, 41(2), 215–239. doi:10.1111/14678543.00270 Lee, T.-T. (2006). Adopting a personal digital assistant system: Application of Lewin’s change theory. Journal of Advanced Nursing, 55(4), 487–496. doi:10.1111/j.1365-2648.2006.03935.x MacInnes, J. (2005). Work-life balance and the demand for reduction in working hours: Evidence from the British social attitudes survey 2002. British Journal of Industrial Relations, 43(2), 273–295. McIntosh, S. (2003). Work-life balance: How life coaching can help. Business Information Review, 20(4), 181–189. doi:10.1177/0266382103204003
Srivastava, L. (2005). Mobile phones and the evolution of social behavior. Behaviour & Information Technology, 24(2), 111–129. doi:10.108 0/01449290512331321910 Tietze, S. (2005). Discourse as strategic coping resource: Managing the interface between “home” and “work.”. Journal of Organizational Change Management, 18(1), 48–62. doi:10.1108/09534810510579841 Townsend, K., & Batchelor, L. (2005). Managing mobile phones: a work/non-work collision in small business. New Technology, Work and Employment, 20(3), 259–267. doi:10.1111/j.1468005X.2005.00158.x
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Warren, T. (2004). Working part-time: Achieving a successful ‘work-life’ balance. The British Journal of Sociology, 55(1), 99–122. doi:10.1111/j.14684446.2004.00008.x
KEY TERMS AND DEFINITIONS Emotional Labor: The suppression or regulation of emotions needed in order to accomplish tasks or protect relationship boundaries. Family-Work Interference: The inability to carry out work activities due to the pressures and responsibilities arising from home or family life. Flexible Working: Policies to allow work activities to be carried out in different ways, including practices such as part-time working, flexi-time, annualized hours, compressed hours, staggered hours, job sharing, home working, teleworking, and mobile working. Mobile Technology: Electronic devices and the underlying infrastructure (e.g., wireless Internet access) that enable communication and remote access to data and information. It includes devices such as mobile telephones, laptop computers, and hand-held equipment (such as personal data assistants).
Mobile Working: Work arrangements that allow employees to freely conduct work at any location away from the main employer’s workplace, with full access to the information, people, and systems they need in order to complete their work (e.g., community nurse). Occupational Identity: The organizational context and the role(s) an individual adopts in the work environment contribute to an individual’s perception of who they are, what they do, and where they come from. Surface Acting: Pretending to feel emotions that are not felt in order to conform to social expectations. Teleworking: Work arrangements that allow employees to work at one location, away from the main employer’s workplace (literally ‘at a distance’ from the workplace, e.g., homeworking). Work-Life Balance: The empowerment and responsibility of a person to control activities in work and family/social spheres according to their own values and priorities such that one aspect does not adversely affect their contribution in the other sphere. Work-Family Interference: The inability to carry out family/social activities freely due to the pressures and responsibilities arising from work situations.
This work was previously published in Encyclopedia of Human Resources Information Systems: Challenges in e-HRM, edited by Teresa Torres-Coronas and Mario Arias-Oliva, pp. 63-69, copyright 2009 by Information Science Reference (an imprint of IGI Global).
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Migration of Legacy Information Systems Teta Stamati National and Kapodistrian University of Athens, Greece Panagiotis Kanellis National and Kapodistrian University of Athens, Greece Konstantina Stamati National and Kapodistrian University of Athens, Greece Drakoulis Martakos National and Kapodistrian University of Athens, Greece
INTRODUCTION In recent years, the accelerated competition in the global marketplace rendered the corporate environment more volatile than ever. The businesses are heavily relying on technological advancements to deliver a vast array of initiatives across a variety of industries. The firms’ main partner in this increasingly complex and unpredictable journey is considered to be their information systems. Although the relevant industry offers an unprecedented rate of technological innovations, nevertheless there are cases where the information DOI: 10.4018/978-1-60960-587-2.ch315
systems carry significant baggage from the past (Kelly, Gibson, Holland, & Light, 1999). There are aged systems that often form the central hub of the information flow within the organisation and are responsible for consolidating information about the business (Bisbal, Lawless, Wu, & Grimson, 1999; Sommerville, 2001) and thus they are called mission-critical legacy information systems. The term “Legacy”, according to the Oxford Dictionary, refers to any long-lasting effect of an event or process. The Legacy System describes an old system that remains in operation within an organisation. These systems often represent a massive, long-term business investment. Ulrich (1994) defined them as “stand-alone applications
Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
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built during a prior era’s technology, but they are perhaps more widely understood as software systems whose plans and documentation are either poor or non-existent” (Connall & Burns, 1993). Bennett (1995) referred to the legacy systems as, “large software systems that we do not know how to cope with but that are vital to the organisation”, while Brodie and Stonebraker (1995) as “any information system that significantly resists modification and evolution to meet new and constantly changing business requirements”. Finally, O’Callaghan (1999), drawing on the characteristics of legacy systems, described them as “a large system delivering significant business value today from a substantial pre-investment in hardware and software that may be many years old. Characteristically, it will have a long maintenance tail. It is, therefore, by definition a successful system and is likely to be one that is, in its own terms, well engineered. It is a business critical system which has an architecture which makes it insufficiently flexible to meet the challenges of anticipated future change requirements.” Legacy systems as a subject area is often overlooked in favour of areas such as new technology developments and strategic planning of information technology. In this context, the following sections present an overview of the legacy information systems problems in terms of their scale and definition. The legacy system issues include the required man-effort and costs of maintaining and evolving existing systems and the current methods of migrating complex legacy systems to new technology. It is shown that legacy systems present a critical area of study in both software engineering and business information systems. Taking into account that the role of technology is not merely supportive but affects the way enterprises conduct their business, it is shown that it is outdated to consider the migration process as the simple replacement of aged or problematic hardware and software. Thus, the migration should be approached as a planned change process that first and foremost requires an understanding and
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a methodology that covers the range of issues and organisational entities involved.
BACKGROUND Legacy Information Systems O’Callaghan (1999) refers to the adoption of an informational culture within the organisations in which “point solutions” were developed due to the widespread use of computer technology over several decades. There are cases where different divisions of the same organisation have developed individual applications in order to meet their perceived needs in an application-by-application basis (O’Callaghan, 1999). In a similar way, there are applications in the same company that are running on different operating systems. Subsequently, such “point solutions”, according to O’Callaghan (1999), became subject to localised optimisation, and uncontrolled maintenance, exacerbating the position further (Zou & Kontogiannis, 2002). These applications are unambiguously hard to maintain, improve, and expand because there is a general lack in their understanding. In addition, integration with newer systems may also be difficult because new business software may use completely different technologies (Wu, Lawless, Bisbal, Grimson, Wade, O’Sullivan, & Richardson, 1997). Due to the aforementioned reasons, there is a significant number of software engineers and practicing managers that consider the legacy systems to be potentially problematic (Bisbal et al., 1999). On the other hand, according to Brodie and Stonebraker (1995), legacy systems do not always fit this stereotype. They propose that if a system was recently developed but cannot be readily modified to adapt to the constantly changing business requirements, then such a system can be regarded as a legacy system. Similarly, Randall (1999) stresses that “Legacy” is not just a problem encountered by organisations with aging main-
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frames and dated software, it is an issue from the moment a computer system becomes an integral part of any organisation’s work (Randall, 1999). The common rule is that if the legacy systems cannot support the business requirements, the business will not be able to remain competitive for long (Brodie & Stonebraker, 1995). Both a significant budget and person-hours will be monopolised by legacy systems maintenance. De Palma and Woodring (1993) referred to over 40% of the IT costs within an organisation being spent on maintaining its legacy systems, while Brodie and Stonebraker (1995) considered that the process of keeping these systems running takes 80-90% of the IT budget. Slee and Slovin (1997) gave an estimation in the area of 80% just for the routine maintenance activities.
Migration of Legacy Information Systems The common sense solution to the legacy problem is migration. The definition of a successful information system migration according to Brodie and Stonebraker (1995) is as follows: “it begins with a mission-critical legacy system of a significant size in full operation and it ends with a fully operational, mission critical target application (or applications components) that replaces the essential aspects of the original legacy system.” This involves replacing the problematic hardware and software, including the interfaces, applications, and databases that compose an information system infrastructure. Brodie and Stonebraker (1995) claim that legacy information system migration involves starting with a legacy information system and ending with a comparable target information system. This target system is significantly different from the original, but it contains substantial functionality and data from the legacy system. The target system must be built using technological advancements in place of the legacy technology. For practical reasons, the target system may contain legacy components for
which there is no adequate justification for their migration. According to Bisbal et al. (1999) the essence of legacy system migration is to allow the organisations to move their legacy systems to new environments, retaining the functionality of existing information systems without having to completely redevelop them. In recent years, a significant number of organisations have initiated large-scale migration projects in order to improve their operations performance and to be compatible with the latest technological advancements. Particularly, the introduction of the Web browser technology, the so-called first-wave of the Internet (Dreyfus, 1998), forced the organisations to undertake migration projects in order to exploit the benefits of the shared information resources (Zou & Kontogiannis, 2002). Afterwards, the convergence of the Web and the distributed-object technologies extended the information Web-based applications to the services-based worldwide applications which was referred to as the Internet’s secondwave (Dreyfus, 1998), and where the provided services and the content were distributed over the Internet (Zou & Kontogiannis, 2002). Moreover, the object-oriented technologies provided some valuable tools for the realisation of the servicesbased Web due to their inherent properties of encapsulation, polymorphism, and specialisation. In addition to the object orientation as a design paradigm, n-tier object computing was gradually being adopted by organisations as the preferred architecture for distributed applications because it allowed for the clear separation of business logic, representation logic, and back-end services (Zou & Kontogiannis, 2002). Considering the case where the stakeholders of a large organisation (for instance, in the banking sector) have decided to maintain organisation’s competitive edge and achieve conformation to the requirements posed by the need for flexibility and the minimization of time to market, the migration of company’s legacy systems towards a new operating Web-based environment will be a
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considerably effective system evolution strategy. The strategic objectives will focus on leveraging the existing legacy software assets while minimising the risks involved in implementing from scratch its large scale mission-critical legacy applications (Umar, 1997). Thus, following the new era of distributed component-based applications, the organisation will face pressures to evolve its existing system (for instance, a large mainframe) in response to its customer expectations. The transformation from the mainframe computer to a multi-tier architecture will force the migration engineers to separate the integration logic and the legacy services to be stored in the middle-tier and the back-end tier, respectively. This architecture will enable lightweight and thin clients to interact with servers in a fully customisable way. The component-based development will be based on the concepts of modularity, structured design, and object-orientation. The migration engineers and the practicing managers will emphasise on the design of the information systems in terms of well-defined modules that will be accessible to other modules through well-defined interfaces. (see Figure 1)
Current Migration Approaches Each migration project could address the areas of reverse engineering, business reengineering, data transformation application development, human computer interaction, and testing (Ulrich, 2002).
A generic process of legacy systems migration may include distinct phases (Bisbal et al., 1999) such as the Justification of the Migration process; the Understanding of the Legacy System; the Development of the Target System; the Testing and the Cut-Over (actual Migration). Within each task, general software and system engineering techniques can be applied. Regarding the crucial phase of the actual migration process, various software engineers propose different methodological approaches. Brodie and Stonebraker (1995) describe two strategies for migration: Cold Turkey and Chicken Little. The main drawback of the Cold Turkey strategy is the probable failure because the system will be written essentially from scratch. In that case, the risk level is high due to the fact that the development and evolution of the new system usually last for many years, in which the factors that affect the system may change. Chicken Little is a better strategy, according to Brodie and Stonebraker (1995), as it separates the migration process into step, and faces each one with a different aspect. Gateways play a significant role in the Chicken Little process. The Butterfly methodology is being developed as part of the MILESTONE project (Wu et al., 1997). During the migration, the methodology eliminates the need for system users to simultaneously access both the legacy and target systems and, therefore, to keep consistency between these two heterogeneous information systems. The But-
Figure 1. Major activities in legacy system migration (Bisbal et al., 1999)
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Figure 2. Chicken Little 11-step1 strategy (Brodie & Stonebraker, 1995)
terfly methodology is based on the assumption that the data of the legacy system is logically the most important part of the system and that, from the viewpoint of the target system development, it is not the ever-changing legacy data that is crucial, but rather its semantics or schema(s). Thus, the Butterfly methodology separates the target system development and data migration phases, thereby eliminating the need for gateways. (see Figure 2)
BUSINESS “LEGACY” AND MIGRATION AS A BUSINESS CHANGE PROCESS According to Laudon and Laudon (1998), today’s business environment has been altered by the three powerful worldwide changes, namely, the emergence of globalisation; the transformation of industrial societies and economies into knowledge and information-based economies; and the transformation of the business enterprise whereby organisations are moving away from a hierarchical, centralised structure to become decentralised. The presence of business legacy within organisations can be identified by examining how they operate in their environment (Kelly et al., 1999). Kelly et al. (1999) refer to the typical components of “business legacy” as the way firms perceive their business, their organisational structure, and the way that they perceive the market within which they operate. Moreover, the business objectives and the organisational strategy can be part of this “business legacy” as well as the way
work is organised such as workflows and business processes (Kelly et al., 1999). In this context, the “business legacy” is embedded in the legacy information systems, and it is the inter-relatedness of business and information systems legacy that makes either business or systems change a very complex process. In this context, Stamati, Kanellis, Stamati, and Martakos (2004) consider the fact that although the legacy migration is being viewed as the replacement of aged or problematic hardware and software, including applications, interfaces, and databases that compose an information system infrastructure, it does not take into account the role of technology today which is not merely supportive but pervades every aspect of the way enterprises conduct their business. Their position is that migration must be implemented as a planned change process that first and foremost requires an understanding of the range of issues and organisational entities involved (Stamati et al., 2004). In this case, the main underlined hypothesis is that migration is a process which entails business change, and it is more than just the movement or reorganisation of database systems, application programs, and program interfaces. The consideration of these physical systems is only the informational view of migration. However, from a business perspective, migration must also account for the broader impact to business change which occurs from the organisational and operational viewpoints.
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The motivation for any migration process is the transition from an initial organisation situation A, which is unsatisfactory in some aspect, to a desired situation B where the problem is treated. Possible causes to such change include perceived opportunities, threats, or strategic decisions, including for example the opportunities offered by new technologies, the treatment of inefficient business processes, the increased customer demands, the globalisation of markets, or the decision to move to a different operating platform (Kavakli & Loucopoulos, 2004). (see Figure 3)
FUTURE TRENDS Recent methodologies consider business requirements as “the process of transforming the need for organisational change into a requirements specification which can then serve as a framework for making the necessary change into the organisational domain” (Pohl, 1996). Considering the aforementioned hypothesis for a migration process, it should be stressed that the actual business structures and practices should be considered as a domain of potential change and new design. Thus, business requirements should be considered as a central part of any migration Figure 3. The Butterfly methodology (Wu et al., 1997)
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activity within a business environment (Kavakli & Loucopoulos, 2004). Migration requires cooperation and understanding between the business management and technology management. Once business management has determined its goals, technology management must seek ways to modify the technology to support these goals. Migration, therefore, should not be an undirected process but a purposive activity driven by organisational change goals. Its effectiveness should depend on being able to make good decisions about what migration goals to pursue, on selecting the appropriate strategies for achieving the desired goals, and on guiding the application of the chosen strategies.
CONCLUSION The concept of migration has shifted in order to include both organisational change as well as change in computer systems that enable such enterprise change. Such a movement has led to the emergence of new definitions that put emphasis on a broader process of migration, and include the cognitive, social, and technical context of migration. These definitions are based on the premise that the replacement of a software system
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in the organisation inevitably brings change in the way work is organised. In a similar manner, any organisational change should be reflected in the software system requirements. Therefore, migration is concerned both with the design and implementation of a new software system and the management of change in the business systems that might be supported by it.
REFERENCES Bateman, A., & Murphy, J. (1994). Migrating of legacy systems. Working Paper CA-2894, School of Computer Applications, Dublin City University. Bennett, K. H. (1995). Legacy systems: Coping with success. IEEE Software, 12(1), 19–23. doi:10.1109/52.363157 Bisbal, J., Lawless, D., Wu, B., & Grimson, J. (1999). Legacy information system migration: A brief review of problems, solutions and research issues. IEEE Software, 16, 103–111. doi:10.1109/52.795108 Brodie, M. L., & Stonebraker, M. (1995). Migrating legacy systems. Morgan Kaufmann Publishers. Connall, D., & Burns, D. (1993). Reverse engineering: Getting a grip on legacy systems. Data Management Review. De Palma, D. A., & Woodring, S. D. (1993). Breaking legacy gridlock. Software Strategies, 4(9), 1–16. Dreyfus, D. (1998). The second wave: Netscape on usability in the services-based internet. IEEE Internet Computing, 2(2). doi:10.1109/4236.670681 Ganti, N., & Brayman, W. (1995). Transition of legacy systems to a distributed architecture. John Wiley & Sons.
Holland, C. P., & Light, B. (1999). Focus issue on legacy information systems and business process change: Introduction. Communications of AIS, 2(9), 98–120. Kavakli, E., & Loucopoulos, P. (2004). Goal modeling in requirements engineering: Analysis and critique of current methods. In J. Krogstie, T. Halpin, & K. Siau (Eds.), Information modelling methods and methodologies (pp. 102-124). Hershey, PA: Idea Group Publishing. Kelly, S., Gibson, N., Holland, C. P., & Light, B. (1999). A business perspective of legacy information systems. Communications of the Association for Information Systems, 2(7). Laudon, K. C., & Laudon, J. P. (1998). Management information systems, new approaches to organisation and technology (5th ed.). New York: Prentice Hall. Light, B., Holland, C., & Gibson, N. (1998). The influence of legacy information systems on business process change strategies. Proceedings of the 4th American Conference on Information Systems Association for Information Systems, 2(1), 527-529. O’ Challaghan, A. J. (1999). Migrating large-scale legacy systems to component-based and object technology: The Evolution of a pattern language. Communications of the Association for Information Systems, 2(3), 104–121. Pohl, K. (1996). Process-centered requirements engineering. Research Studies Press Ltd. Randall, D. (1999). Banking on the old technology: Understanding the organisational context of the “legacy” issues. Communications of the Association for Information Systems, 2(8), 208–221. Slee, C., & Slovin, M. (1997). Legacy asset management. Information Systems Management, 14(1), 12–21. doi:10.1080/10580539708907024
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Sommerville, I. (2001). Software engineering (6th ed.). Pearson Education. Stamati, T., Kanellis, P., Stamati, K., & Martakos, D. (2004) Legacy migration as planned organizational change. Sixth International Conference on Enterprise Information Systems (ICEIS), 3, 501-508. Ulrich, W. (1994). From legacy systems to strategic architectures. Software Engineering Strategies, 2(1), 18–30. Ulrich, W. M. (2002). Legacy systems: Transformation strategies. Prentice Hall PTR. Umar, A. (1997). Application (re)engineering: Building Web-based applications and dealing with legacies. Englewood Cliffs, NJ: Prentice Hall. Wu, B., Lawless, D., Bisbal, J., Grimson, J., Wade, V., O’Sullivan, D., & Richardson, R. (1997). Legacy system migration. Proceedings of the 17th International Database Conference (pp. 129-138). Zou, Y., & Kontogiannis, K. (2002). Migration to object oriented platforms: A state transformation approach. 19th IEEE International Conference on Software Maintenance (ICSM) (pp. 530-539).
KEY TERMS AND DEFINITIONS Component Architecture: A notion in object oriented programming where components of a program are completely generic. Instead of having a specialised set of methods and fields they have generic methods through which the component can advertise the functionality it supports to the system into which it is loaded. Distributed Programming: The kind of programming that supports objects distributed across a network.
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Gateway: A software module that is placed between other software modules. One of its roles for instance, is to simulate the old information system, while it is migrated, so it is still visible to the old user interfaces and application modules. Another role may be the transformation of the target information system in order for it to be visible to the old user interfaces, and the old legacy information system to be visible to the new user interfaces. Mainframe: A machine designed for batch rather than interactive use, though possibly with an interactive time-sharing operating system retrofitted onto it. N-Tier (or Multi-Tier) Architecture: This means splitting a system into more than just a client layer and a database layer. The server in this case refers to a custom written thing. The server then takes care of the business logic, and gets and returns the raw data to one or more database servers. Object-Oriented Programming: The use of a class of programming languages and techniques based on the concept of an object which is a data structure encapsulated with a set of routines, called methods, which operate on the data. Operations on the data can only be performed via the methods, which are common to all objects that are instances of a particular class. Reengineering: The examination and modification of a system to reconstitute it in a new form and the subsequent implementation of the new form. Web Services Definition Language: An XML format for describing network services as a set of endpoints operating on messages containing either document oriented or procedure-oriented information. The operations and messages are described abstractly and then bound to a concrete network protocol and message format to define an endpoint. Related concrete endpoints are combined into abstract endpoints (services).
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ENDNOTE 1
S1: analyse the legacy information system, S2: decompose the legacy information system structure, S3: design the target interfaces, S4: design the target applications, S5: design
the target database, S6: install the target environment, S7: create and install the necessary gateways, S8: migrate the legacy database, S9: migrate the legacy applications, S10: migrate the legacy interfaces, S11: cut over to the target information system.
This work was previously published in Encyclopedia of Information Science and Technology, Second Edition, edited by Mehdi Khosrow-Pour, pp. 2551-2556, copyright 2009 by Information Science Reference (an imprint of IGI Global).
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Policy Technologies for Security Management in Coalition Networks Seraphin B. Calo IBM Research, USA
Emil Lupu Imperial College, UK
Clare-Marie Karat IBM Research, USA
Jiefei Ma Imperial College, UK
John Karat IBM Research, USA
Alessandra Russo Imperial College, UK
Jorge Lobo IBM Research, USA
Morris Sloman Imperial College, UK
Robert Craven Imperial College, UK
Arosha Bandara The Open University, UK
ABSTRACT The goal of policy-based security management is to enable military personnel to specify security requirements in terms of simple, intuitive goals. These goals are translated into the concrete system settings in a way that the system behaves in a consistent and desirable way. This technology minimizes the technical expertise required by military personnel and automates security management while allowing a high level control by DOI: 10.4018/978-1-60960-587-2.ch316
the human in the loop. This chapter describes a framework for managing security policies, and an overview of two prototypes that simplify different aspects of policy management in the context of coalition operations.
INTRODUCTION Secure, reliable and adaptable communications is needed to support dynamic mission-based coalitions of partners from different military and
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Policy Technologies for Security Management in Coalition Networks
non-military organizations. If sensitive information is communicated to the wrong person/device, it could cost the lives of the personnel involved in the mission. Likewise, if necessary information is not communicated and shared with the right people, it could also lead to loss of lives. Policy-based security management should enable military personnel to specify security requirements in terms of simple, intuitive goals that are translated into the concrete system settings in such a way that the system behaves in a consistent and desirable way. The objective is to minimize the technical expertise required by military personnel, and to automate policy management as far as possible. This is dependent on being able to specify and analyze policies to ensure that they prescribe correct and desirable behavior. For example, inconsistencies should not arise because the available communication devices cannot support the specified policies. We assume that military personnel specify goals using a structured natural language aimed at non-technical people. Goals are automatically translated into a formal, logic-based abstract language for refinement and analysis. Our past experience has indicated that logic languages, while good for reasoning, are not amenable to efficient implementation, particularly on small hand-held devices. Thus abstract policies must be translated into concrete implementable policies described in languages such as Ponder2 (Twidle et al, 2008), XACML (OASIS XACML TC, 2005), or CIM-SPL (Agrawal et al, 2007). We start with the presentation of a policy-based security management framework for complex, dynamic, ad hoc systems. This provides the platform supporting mechanisms for adapting system behaviors to meet high-level user-specified security policies through the enforcement of low-level controls in coalition networks. To accomplish this, end-to-end policy mechanisms are described that capture the security requirements of the system, transform them into constraints on the system resources and executable policies, which are then disseminated to and executed upon the appropriate
distributed entities within the coalition network. Yet without analysis much of the benefit of using policy-based techniques and declarative policy languages may be lost. Arguably, the lack of effective analysis tools accounts in part for the lack of wider adoption of policy-based techniques. In order to perform analysis, policies must be expressed unambiguously in a manner that captures their semantic meaning. We describe an approach based upon a logical construct for the specification and analysis of security policies. This construct is developed over a very expressive policy language that may be used to represent policies and systems at many different levels of abstraction and stages during the refinement process. In order to bring together and demonstrate the various policy technologies for security management, two concept prototypes are discussed. These served to integrate some capabilities and provided an end-to-end view of the policy lifecycle for coalition systems. They were based on user scenarios. The purpose of a user scenario is to provide sufficient context about a problem-space being investigated so that researchers can identify the scientific, technical, and feasibility questions they must address in the research. A user scenario can be a valuable research and design tool for scientists to employ to understand the trade-offs about different options in the context of the targeted end user. Details of these prototype demonstrations are presented, as are a number of research questions that arose during their development.
FRAMEWORK FOR SECURITY POLICIES Our framework for policy analysis and refinement captures policies at various levels of abstraction (or layers), which identify the key stages in the process of refining policies from goals to implementations. The layered architecture is useful in identifying the architectural elements, software components, and system models that are needed
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to support the refinement and analysis processes, and to facilitate the management of policies. In this section we describe and illustrate the framework, identifying the levels comprising it and the services that we expect to be able to perform at each level.
DESCRIPTION OF THE LAYERS We can identify four key stages, or layers, in the process of refining policies: Specification, Abstract, Concrete, and Executable. Policies are defined with respect to a system model, which is a formal representation (or description) of the system within which the policies are enforced. Given that policies exist at multiple levels of abstraction, it is natural that each layer of policy specification should exist in the context of system models at that layer. These models are elaborated at the appropriate level of abstraction, so that they become more detailed at the lower layers (Figure 1). Policy Specification Layer. This is the most abstract level of policy specification; it is at this layer that we would expect the military user to have the most interaction. Typically, the military Figure 1. Description of layers
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user would define the mission security goals, in some intuitive format at this layer. We would not expect policies specified at this layer to make any reference to security mechanisms, or any other concrete system features. However, it should still be possible to assign formal semantics to the specified policies. The system model at this layer should only refer to high-level operations and services which are meaningful to a nontechnical military user. Policies defined at this level can be referred to simply as security goals, or end-user goals. These policies must be interpreted in context. Ontologies are being developed for capturing the semantics of the battle space. These can be used in establishing semantics for transforming the policies at the specification layer into the abstract policies described below. The sets of information relating the various aspects of the military environment, including policies, constitute a semantic backplane. This consists of the set of concepts and relationships that are used by the military in carrying out coalition missions. Abstract Policies. To implement a policy we need candidates for the system entities and actions that will be used to enforce the policy. The
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abstract policy models are possible refinements of the end-user goals but enriched with suitable information about candidates for implementation. Descriptions of these candidates will, of course, reside in the system models. Note that there may be multiple abstract policies with respect to corresponding system models in support of a single security goal. Concrete Policies. Inherent in the notion of refinement is the resolution of choices. The abstract policies capture the range of choices that may be available in implementing an end-user goal. These are refined to concrete policies when the candidates from the abstract layer have been restricted to singletons. The system model at this layer refers directly to objects and services which are to be found in the target system. The system model at this layer may also include classes of user, types of risk, and so forth. Executable Policies. This layer contains the policies which will actually be deployed. It may further refine the policies from the concrete layer by setting low level system parameters, expressing policies in a format so that they can be used conveniently by mechanisms in the system. As an example of the refinement process, we consider policies for Intelligence, Surveillance, and Reconnaissance (ISR) assets being used in a coalition operation. One high level goal defined at the specification layer can lead to a number of policies at the lower layers. •
•
Policy Goal: ◦⊦ High quality sensor information is reserved for US use only Abstract Policies: ◦⊦ For coalition members, video sensor output will be degraded to reduce image resolution. ◦⊦ For coalition members, location sensor output will be degraded so that coordinates only identify a proximity region.
•
Concrete Policies: ◦⊦ If a UK control asset requests an image from a US camera then it will be set to a resolution of.8 times its native resolution ◦⊦ If a UK control asset requests the location of a US asset then the GPS data will be transformed into data identifying a region of 10 square meters
The executable policies would be in whatever form is required by the mechanisms in the system that would enforce them. They would identify specific assets with specific characteristics.
DESCRIPTION OF THE FUNCTIONALITY AT EACH LAYER The layers are intended as a means of identifying key milestones in the refinement process; but, in addition, they also underpin effective solutions to the broader challenges of policy management. For instance, policy analysis is a crucial part of policy management, and, as a rule, it highly desirable to analyze policies at as high a level of abstraction as possible, because abstract policies are simpler and therefore more tractable. Furthermore, should a given type of analysis detect a violation, then it is easier to remedy that violation at a more abstract level, than at a more concrete level. For example, the conflict detection problem is more tractable for abstract policies, and should two policies be found to conflict, the remedy for the conflict is easier to identify and implement when the policies are more abstract. There are various policy management services which are expected to be supported by the layers; and, in general, implementing these services will require interaction between the layers. The services, and their interactions, are as follows:
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Policy Specification Layer 1. Policy authoring 2. Translating/mapping policies into formal semantics. 3. Basic analysis: tools such as model-checkers or logic programs can be adapted to analyze security goals in the goal specification language for detection of conflict and other policy properties. In addition it may be possible, using the semantics developed, to analyze sets of end-user goals for coverage – in other words does this set of end-user goals capture the complete range of security variables that need to be controlled. 4. Conflict resolution: if conflicts can be identified, it may also be possible to perform conflict resolution.
Abstract Policies 1. The information added at this layer should enable substantial conflict (and inconsistency) detection services to be provided. There are interesting problems arising from attempting to check a policy that is being refined, and so is rather abstract, against one that is executable and so rather concrete. 2. Conflict resolution is the complementary service to conflict detection, but it may be necessary to coordinate conflict resolution with the layer above. In other words, for some conflicts it may make more sense for the resolution to be provided by the specification layer. 3. It may be necessary to perform coverage analysis at this layer as well. In general it is desirable to perform as much coverage analysis at the specification layer as possible; however, the layers below this layer may yield negative results about validity, which may obligate modification of policies at this layer (or above), and that in turn may require coverage checking at this layer.
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4. Incorporating user preferences or accommodating risk-based decisions from the user would happen at this level. While the ultimate objective is that polices are managed automatically (and specifically their refinement is automatic), in reality full automation is probably not possible. The compromise to is to provide users with an interface to the refinement (and management) services; this will allow users to insert their preferences (either preemptively or on-demand), and it will also be the means for enabling users to make risk-based policy decisions. 5. Mappings to and from the formal semantics are likely to be necessary here.
Concrete Policies 1. While we would hope that most conflict detection is done above this layer, so that the concrete policies derived here are known to be conflict free, it may be necessary for some types of conflict and inconsistency detection to be done here. 2. Validity checking is done most naturally at this layer, since we expect the system model at this layer to refer directly to objects in the system. 3. Compliance checking is done either at this layer, or the layer below. 4. Refinement checking. We would hope that the policies generated would, by construction, be a correct refinement of the security goals. However, in practice there may be changes to policies, or violations of policies, at runtime (it is most likely that manual override must be permitted). In this case it makes sense to be able to check that modified policies, or indeed, system behavior, still constitutes a refinement of the original security goal. 5. Mapping to and from the formal semantics is a basic service, required here as well, especially to support refinement checking.
Policy Technologies for Security Management in Coalition Networks
Executable Policies 1. 2. 3. 4.
Validity checking. Compliance checking. Refinement checking. Mapping to and from the semantics; we would expect that at this layer the results of the refinement algorithms, which operate on the formal semantics, are translated into executable policies; however, it may also be necessary to be able to map from the policies back to the formal semantics in order to perform the indicated analyses.
As indicated in the above, various forms of analysis must be performed at each of the refinement layers. The ability to carry out the required analyses is thus a basic consideration in the management of policies within the system. An in depth discussion of analysis mechanisms and the underlying policy representations that are required to support them is undertaken in the next section.
ABSTRACT POLICIES AND POLICY ANALYSIS The selection of an abstract policy language will determine the quality and scope possible during analysis. The goal is to be able to have an expressive abstract language that captures the intuitive understanding of security descriptions expected by the end user and at the same time a language that is amenable to efficient implementations. Hence, we need to balance expressiveness with efficiency of policy evaluation. We also need a powerful analysis component. In this section we describe a formal framework for representing and analyzing authorization and obligation policies. Policies are represented in an expressive logical language, which can capture complex dependencies amongst policy rules. These policy rules are then joined to a specification of the behavior of the system which the policies regulate, and many
different types of analysis and verification may then be performed on the joint system. We have designed an abstract language which we hope to be expressive enough that policies written in many different formalisms (such as Ponder2 (Twidle et al, 2008), XACML (OASIS XACML TC, 2005), or Cassandra (Becker & Sewell, 2004)) can be translated into it, where they can then be analyzed for the presence of modality conflicts, coverage gaps, and other properties. A crucial component of our framework is the representation of dynamic system behavior. Policies have constraints on their applicability that often depend on the local system state. Therefore, a model of the system is required as a component of an analysis framework, both in order to determine whether policies conflict, and to be able to analyze a given set of policies for properties that the system would satisfy when they are enforced. An analysis framework should also represent policies and the systems they regulate in a separable way, so that the behavior of a policy on different systems, and the implementation of different policies in the same system, can easily be studied. The properties for which we can perform analyses include both foundational, policy focused principles, and also application specific features, dependent on the particular system to which the policy applies and its structure. Specifically (though not exhaustively) these include: •
•
•
Modality conflicts, such as the joint authorization and denial to perform some action, or the presence of an obligation to act without the permissions necessary for its fulfillment. Separation of duty clashes, including static separation of duty, dynamic, and many other classes (see (Simon & Zurko, 1997) for terminology and instances). Coverage gaps, where no policy exists to dictate what the correct response to a request should be.
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•
•
Policy comparison, including the question of whether two policies are equivalent or one is contained in the other. Behavioral simulation, where specific sequences of requests and events in the policy regulated system are entered, to see the policy decisions that would arise during in the actual system.
LANGUAGE Our operational model broadly follows the architecture and principles of operation of XACML (OASIS XACML TC, 2005), PolicyMaker, and KeyNote (Blaze et al, 1999). There is a policy component, consisting of policy decision and enforcement points (PDP/PEP), and the system to which policies refer and which they modify. The PDP has access to a policy repository. Authorization decisions are made in response to requests for a subject to perform an action on a target, using the policies, and these decisions are then enforced by the PEP. The PDP also monitors whether obligations of subjects to perform actions have been met or not. We distinguish between regulatory predicates, used to describe the state of the PDP/PEP, and non-regulatory predicates that express the state of the policy-governed system. Regulatory predicates are subdivided into input regulatory, state regulatory, and output regulatory; similarly, for nonregulatory predicates. In general, a system moves between states depending on the occurrences of actions and events. Non-regulatory state predicates represent properties of states, and non-regulatory event predicates describe the occurrence of events. (The need for event predicates arises because, in general, not all occurrences which modify the state of a system are controllable by the policy mechanism.) We use many-sorted first-order predicate logic as our base language, and clearly distinguish the policy representation language from the domain
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description language. This allows us to detach policy representations from system representations, and compare the implementation of a policy in different systems. The policy representation language, Lπ, includes at least the sorts Subject, Target, Action, the sets of subjects, targets and actions, respectively, and the sort Time, given as R+, the set of non-negative Real numbers, with constants including numerical constant symbols (0, 1,...) and variables such as T, with super- and subscripts as needed. Standard arithmetical functions (+, −, /, ∗) and relations (=, =, [3]
RT
3.34 (0.49)
3.11 (0.62)
3.13 (0.80)
7.91**
[1]>>[2]>>[3]
*p t 1 ≤ t ≤T t
Figure 12. Determination of milestone specific NPV cost targets
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provides the needed time adjustment. In the introductory example of Figure 10 and Figure 12 τ = t was assumed, but affecting payment time differences may likely occur as well as price variances of input factors over time. In contrast to the introductory example, both cause the need for a differentiation of iteration cost rates over time in a more realistic modelling, hence rt. Therefore, the ∈ ℜJ+ of fixed values has to vector a := (a j ) 1 ≤ j ≤J
be determined by complex tensor multiplications. Once more assuming τ = t and only focusing on a specific discipline k ∈ {1, 2, …, J}, the variance contribution Δak already consists of seven partial variances, one of them of third degree, three of second degree and three of first degree. With Δ as marker for a variance of the respective variable, Δak results with := (b + ∆b ) B ∈ ℜ +ΤxH , t ,h t ,h 1 ≤ t ≤ Τ, 1≤h ≤ H
:= (p + ∆p ) P ∈ ℜ+ΤxH and t ,h t ,h 1 ≤ t ≤ Τ, 1≤h ≤ H
q ' := (qt + ∆qt )
1 ≤ t ≤T
−− −− −−
∈ ℜ +Τ in
−
∆ak := q '⋅ B ⋅ P − q'⋅ B ⋅ P
(4)
Figure 13 illustrates these partial variances for of a given input factor and period, hence indexes h and τ are neglected. The second-degree variances are shaded grey, the third-degree variance is shaded dark grey. Since productivity control has to be restricted to variances influenced by responsible managers (principle of controllability), partial variances no. 1, 2, 4, and 6 have to be eliminated in either case when controlling a development team leader who is not responsible for procurement. This is due to the fact that these variances are at least partially price-driven, e.g. by increased official wages. The elimination of variances (3), and (7) depend on whether they have been triggered by changes of interest rates or not. Changes of the interest rate contrary to time shifts cannot be attributed to a development team leader. In general, for responsibility accounting it is important that Δdpac consists of different variances. To avoid misleading incentive-effects, performance control has to separate controllable and non-controllable partial variances for the controlled person in charge using a differentiated variance analysis. Figure 14 summarizes possible causes of partial variances on a highly aggregated level.
and more descriptive in Box 1. Box 1. ∆ak = (1) ∆bt ,h ⋅ ∆pt ,h ⋅ ∆q t ,h + third degree variance 4) 3) 2) ( ( ( − − − T H bt ,h ⋅ ∆pt ,h ⋅ ∆ q t ,h + ∆bt ,h ⋅ pt ,h ⋅ ∆ q t ,h + bt ,h ⋅ ∆pt ,h ⋅ ∆ q t,h + ∑ ∑ ∆ t =0 h= =1 second degree variances 6) 5) 7) ( ( ( _ − − ∆b ⋅ p ⋅ q b ⋅ ∆p ⋅ q b ⋅ p ⋅ ∆ q t ,h t ,h t ,h t ,h t ,h t,h t ,h t ,h t ,h first degree variaance
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(5)
Performance Management in Software Engineering
Figure 13. Partial variances of the fixed value ak for a given input factor and period
Figure 14. Possible causes of partial variances of iteration cost rate variances
Case Study for Responsibility Accounting in Performance Management To illustrate the necessary steps in responsibility accounting of cost performance targets, we will discuss a very simplified case with only a few changes compared to the numerous changes in the introductory example.
•
•
•
There is a change in the iteration signature of iteration type c2 (see Figure 6): the new signature is 137.794.631. The fixed cost values a8 and a9 for project management and environment are 0.8 instead of 0.2 totally due to increases in prices of underlying activities. The interest rate is constant 6% per year.
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•
There is a slight change in the project time signature because two iterations of type e3 instead of e2 are used.
Figure 15 illustrates the determination of actual milestone-specific dpac values. Changes in input factors are highlighted grey. Since we often see different managers in charge of the respective milestones, incentive-driven performance management requires rolling target adjustments after having finalised each milestone. Only this clarifies the different performance of responsible managers for milestones. The IOC and PR milestones illustrate, that comparing actual values to original targets is misleading. Instead of a reduced contribution to dpac there are cost overruns. Hence the manager responsible for the LCA milestone is the only one who met and even undercut the target. Before giving a bonus to the manager in charge of LCA and calling the others over the coals, a closer look at partial variances is inevitable. Doing so, it becomes obvious that, for instance, the manager responsible for milestone PR is unburdened: the dpac variance in this area is totally due to higher input factor prices in project management and environment and a discounting-driven effect of – 0.5 due to higher interest rates. Both influencing variables are not under the control of this manager. On the other hand, the manager responsible for milestone IOC can be discharged at least partially: separatedly, the increase of input prices accounts for a dpacincrease of 12.3 and the increase of interest rates
for a dpac-reduction of 5.6. Together, taking variances of higher degree into account, they explain the dpac-increase of 6.7. Therefore, the manager still has to take responsibility for 31.3.
CONCLUSION Due to its structural similarity to the Unified Process, activity based costing may be employed for cost management tasks in all phases of software development. Compared to conventional approaches numerous improvements can be expected. The presented approach is strictly focused on data that are specific to the developers’ business. At the same time it is simple, because it relies on the widely used software development model of the Unified Process and allows the detailed planning and control of costs at the level of short and time-boxed iterations. Additionally, in many companies activity based costing is already being used, which facilitates the successful adaptation of activity based cost management for software developments based on the Unified Process. Furthermore, the financial aspects considered clearly suggest using this approach to manage long lasting and complex software projects. However, the quality of similarity estimations needed to gain the quantity structure of the projects will be crucial for its success. Adopting the new concept of iteration and project signatures will simplify the identification of similar iteration types, at the same time reducing technical requirements
Figure 15. Variance analysis with rolling NPV target adjustments
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of the similarity approach considerably. Finally, the development of an effective and powerful variance analysis will give the project manager the performance measurement tools needed to discover problems in software development at an early stage.
Boehm, B., Abts, C., & Chulani, S. (2000). Software development cost estimation approaches – a survey. Annals of Software Engineering, 10(1-4), 177–205. doi:10.1023/A:1018991717352
REFERENCES
Brealey, R. A., Myers, S. C., & Franklin, A. (2007). Principles of corporate finance (9th ed.). New York: McGraw-Hill.
Abernethy, M. A., Bouwens, J., & van Lent, L. (2010). Leadership and control system design. Management Accounting Research, 21(1), 2–16. doi:10.1016/j.mar.2009.10.002 André Ampuero, M., Baldoquín de la Peña, M. G., & Acuña Castillo, S. T. (2010). Identification of patterns for the formation of software development projects teams. International Journal of Human Capital and Information Technology Professionals, 1(3). Anseimo, D., & Ledgard, H. (2003). Measuring productivity in the software industry. Communications of the ACM, 46(1), 121–125. doi:10.1145/948383.948391 Atkinson, A. A., Kaplan, R. S., Matsumara, E. M., & Young, S. M. (2007). Management accounting. Upper Saddle River, NJ: Prentice Hall.
Booch, G., Rumbaugh, J., & Jacobson, I. (2005). The unified modelling language user guide. Reading, MA: Addison-Wesley.
Chiu, N.-H., & Huang, S.-J. (2006). The adjusted analogy-based software effort estimation based on similarity distances. Journal of Systems and Software, 80(4), 628–640. doi:10.1016/j. jss.2006.06.006 Choi, D. O., & Kim, J. S. (2005). Productivity measurement and evaluation models with application to a military R&D organization. International Journal of Technology Management, 32(3-4), 408–436. doi:10.1504/IJTM.2005.007339 Choudhury, N. (1986). Responsibility accounting and controllability. Accounting and Business Review, 16(63), 189–198.
Baker, G. (1992). Incentive contracts and performance measurement. The Journal of Political Economy, 100(3), 598–614. doi:10.1086/261831
Colomo-Palacios, R., Tovar-Caro, E., Garcia-Crespo, A., & Gomez-Berbis, M. J. (2010). Identifying technical competences of IT professionals. The case of software engineers. International Journal of Human Capital and Information Technology Professionals, 1(1), 31–43.
Baker, G. (2002). Distortion and risk in optimal incentive contracts. The Journal of Human Resources, 37(4), 728–751. doi:10.2307/3069615
Emblemsvåg, J. (2003). Using activity-based costing and Monte Carlo methods to manage future costs and risks. New York: Wiley.
Baumeister, A., & Ilg, M. (2004). Cost management of software developments – an activity based approach. In Proceedings of the IFSAM/ SAM VIIth World Congress 2004.
Farooquie, P., & Farooquie, J. A. (2009). Project planning and performance: An empirical study. International Journal of Project Organisation and Management, 1(4), 408–421. doi:10.1504/ IJPOM.2009.029109
Boehm, B., (Eds.). (2000). Software cost estimation with COCOMO II. Upper Saddle River, NJ: Prentice Hall.
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Foulds, L. R., & West, M. (2007). The productivity of large business information system development. International Journal of Business Information Systems, 2(2), 162–181. doi:10.1504/ IJBIS.2007.011617
Krishnan, M. S., Kriebel, C. H., Kekre, S., & Mukhopadhyay, T. (2000). An empirical analysis of productivity and quality in software products. Management Science, 46(6), 745–759. doi:10.1287/mnsc.46.6.745.11941
Han, W.-M., & Huang, S.-J. (2006). An empirical analysis of risk components and performance on software projects. Journal of Systems and Software, 80(1), 42–50. doi:10.1016/j.jss.2006.04.030
Kroll, P., & Kruchten, P. (2003). The rational unified process made easy. Reading, MA: AddisonWesley.
Hicks, D. T. (2002). Activity based costing. New York: Wiley. Horngren, C. T., Foster, G., Datar, S. M., Rajan, M. V., & Ittner, C. (2008). Cost accounting: A managerial emphasis. Upper Saddle River, NJ: Prentice Hall. Jacobson, I., Booch, G., & Rumbaugh, J. (1999). The unified software development process. Boston: Addison-Wesley. Kadefors, A., & Badenfelt, U. (2009). The roles and risks of incentives in construction projects. International Journal of Project Organisation and Management, 1(3), 268–284. doi:10.1504/ IJPOM.2009.027539 Kaplan, R. S., & Anderson, S. R. (2007). Timedriven activity-based costing: A simpler and more powerful path to higher profits. Boston: Harvard Business School Publishing. Kitchenham, B. (2010). What’s up with software metrics? – A preliminary mapping study. Journal of Systems and Software, 83(1), 37–51. doi:10.1016/j.jss.2009.06.041 Kitchenham, B., & Mendes, E. (2004). Software productivity measurement using multiple size measures. IEEE Transactions on Software Engineering, 30(12), 1023–1035. doi:10.1109/ TSE.2004.104
1660
Kruchten, P. (2003). The rational unified process. An introduction. Reading, MA: Addison-Wesley. Larman, C. (2002). Applying UML and patterns. An introduction to object-oriented analysis and design and the unified process. Upper Saddle River, NJ: Prentice Hall. Leung, H., & Fan, Z. (2002). Software cost estimation. In S. K. Chang (Ed.), Handbook of software engineering & knowledge engineering (Em2, pp. 307-324). River Edge, NJ: Word Scientific. Lum, K., Bramble, M., Hihn, J., Hackney, J., Khorrami, M., & Monson, E. (2003). Handbook for software cost estimation. Pasadena, CA: Jet Propulsion Laboratory. Maxwell, K. D., & Forselius, P. (2000). Benchmarking software-development productivity. IEEE Software, 17(1), 80–88. doi:10.1109/52.820015 Na, K.-S., Simpson, J. T., Li, X., Singh, T., & KiYoon, K. (2007). Software development risk and project performance measurement: Evidence in Korea. Journal of Systems and Software, 80(4), 596–605. doi:10.1016/j.jss.2006.06.018 Otley, D. (1999). Performance management: A framework for management control systems research. Management Accounting Research, 10(4), 363–382. doi:10.1006/mare.1999.0115 Pfleeger, S. L. (2008). Software metrics: Progress after 25 Years? IEEE Software, 25(6), 32–34. doi:10.1109/MS.2008.160
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Tan, T., Li, Q., Boehm, B., Yang, Y., He, M., & Moazeni, R. (2009). Productivity trends in incremental and iterative software development. In Proceedings of the 2009 3rd International Symposium on Empirical Software Engineering and Measurement (pp. 1-10). Wallace, L., Keil, M., & Rai, A. (2004). How software project risk affects project performance: An investigation of the dimensions of risk and an exploratory model. Decision Sciences, 35(2), 289–321. doi:10.1111/j.00117315.2004.02059.x
Yu, A. G. (2010). Questioning the key techniques underlying the iterative and incremental approach to information systems development. International Journal of Information Technology Project Management, 1(1), 15–29. Zardari, S. (2009). Software risk management. In Proceedings of the 2009 International Conference on Information Management and Engineering (ICIME) (pp. 375-379). Zimmerman, J. L. (2003). Accounting for decision making and control. New York: McGraw-Hill.
This work was previously published in International Journal of Information Technology Project Management (IJITPM), Volume 2, Issue 1, edited by John Wang, pp. 1-18, copyright 2011 by IGI Publishing (an imprint of IGI Global).
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Strategy and Structure in a Virtual Organization Nazim Ahmed Ball State University, USA Ray Montagno Ball State University, USA Sushil Sharma Ball State University, USA
ABSTRACT The business environment of the 21st century require organizations to respond quickly to market demands and thus traditional organization structures and strategy are no longer capable of sustaining the needs of this relentless pace. New forms of organizations in the form of virtual organization (VO) hold promise in the network world. Several organizations worldwide have already been experimenting virtual organizations’ structures and processes. These new virtual structures and processes, however, will require newer strategies to succeed. This paper attempts to highlight some DOI: 10.4018/978-1-60960-587-2.ch606
strategy and structural issues of a VO. The study is conceptual in nature and inferences have been drawn from existing literature and practices.
INTRODUCTION Advances in internet and communication technologies are mandating organizations to experiment newer forms of organizations structures such as; distributed structures, network structures and virtual organizations for their business. A virtual organization is a network of companies which support each other around a product and or a service idea. The companies in the network should be seamlessly integrated by information
Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
Strategy and Structure in a Virtual Organization
and communication technologies so that to the customer it is not apparent that the different processes are handled by separate companies. With the availability of internet and other communication technologies a VO is a viable option for many innovative entrepreneurs. According to Lipnack and Stamps (1997), virtual team is “a group of people who interact through interdependent tasks guided by common purpose” that “works across space, time, and organizational boundaries with links strengthened by webs of communication technologies” (p. 7). We are using the same definition for our study. (Mowshowitz, 1986, 1994) used the term Virtual Organization for the first time in 1986. Since then, literature on virtual organizations has grown. There have been numerous definitions of virtual organizations (Dubinskas, 1993). “In a virtual organization, complementary resources existing in a number of co-operating companies are left in place, but are integrated to support a particular product effort for as long as it is justifiable to do so.” (Goldman et al., 1995) “Virtual organizations are distributed ‘business processes’. These processes may be ‘owned’ by one or more organizations acting in partnership. For a specific project, resources are assembled to perform a business process on behalf of the project owner(s), and then disassembled on completion of the contract.” (Wolff, 1995) A virtual organization (VO) is an alliance of companies formed for the purpose of delivering specific products and or services. According to Porter (1990) “A virtual organization is a collection of business units in which people and work processes from the business units interact intensively in order to perform work which benefits all” (Skyrme, 1999). The literature suggests that virtual organizations tend to be non-hierarchical (Beyerlein & Johnson, 1994; Goldman et al., 1995) and decentralized (Baker, 1992). The company who is
responsible for the products and services may be called the “core” company. The core company is linked together by information and communication technologies (ICT) with other companies called “satellite” companies or VO partners. Core company and satellite companies share information, resources and skills in a seamless way so that the core company can deliver products and services to the customer and can create an impression to the customer that they have control over every aspect of the business process (Townsend et al., 1998). With the availability and ubiquitous nature of networked based information technology, a company’s business processes theoretically can span across the entire globe. Opportunity exists for organizations to deliver goods and services to the customer efficiently without the need to have physical control and ownership of many of the businesses processes. So the viability of VO’s is a present reality rather than a distant possibility (Kotorov, 2000; Coulson & Kantamneni, 2000). Nature of a VO varies in terms of its longevity and complexity. Figure 1 depicts several types of VO from very transient to somewhat permanent. A virtual corporation may arise out of some interesting product and/or service idea. The originator of this product and/or service idea may succeed to actually market the product through entrepreneurial initiative using the virtual organization framework. Over time a successful VO may achieve some sort of permanency and may grow to be a traditional company (Pang, 2001). The research on virtual companies can be categorized roughly into three broad categories: 1) the conceptual description and definition, 2) empirical studies, 3) issues related to managerial implications. The concept of virtual organization was evolving in the early 90’s as the internet and e-commerce was gaining momentum (Barnatt, 1995; Flaig, 1992). Davidow and Malone (1992) described virtual corporation as “edgeless, permeable and continuously changing interfaces, among company, supplier, and customer”. Blau
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Figure 1. Typology of virtual organizations (Palmer & Speier, 1997, 2001)
(1997) Concluded that virtual company has little need for physical capital and can be formed anywhere around a market opportunity by deploying intellectual capital and forming alliances based on core competencies of some existing companies. Goldman et al. (1995) defined VO’s as one where, complementary resources exist in several companies which can be profitability utilized by sharing with others. Expert talent is recruited for the duration of the project and profit is shared among the companies. Some recent empirical studies concluded that the many advantages of virtual organizations include flexibility, responsiveness, improved resource utilization in ever changing global business environment (Grabowski & Roberts, 1998; Jarvenpaa & Leidner, 1998; Cascio, 1999; McDonough, Kahn, & Barczak, 2001). Researchers also concluded there are several disadvantages such as low individual commitment, role overload, role ambiguity, absenteeism, customers find a lack of permanency, consistency and reliability in virtual firms (Jarvenpaa & Leidner, 1998; Cascio, 1999). 1664
Potocan and Dabic (2002) describe that virtual organizations enable organizations to bring their core competencies together to tightly coordinate the transactions and activities across a value chain. Snow et al. (1999) suggested that lack of influence and autonomy for the members may be a barrier to the functioning of virtual organizations. They also suggested that lack of human communication, inertia to change, and complexity of still evolving information and communication technologies and cultural differences can affect the performance of virtual organizations. Some authors suggest that virtual organizations may not be suitable for all businesses. Ahuja and Carley (1998) expertise and competence based tasks which is communication intensive can utilize distributed resources to form a virtual organization. It may not be easy for the start-up virtual company to stay competitive in the market place. There are so many competitive forces working in a business environment, it is even hard for a regular company which has all the functional areas within itself to stay competitive. We see even big
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corporations becoming stagnant and losing market share for failing to come up with right product and services that will be competitive in the market place. The strategy of being competitive is an ongoing effort (McDonugh et al., 2001). As the product life-cycle shortens, it is imperative that a company must always be on its guard to bring out the right product at the right time to hold and build market share. So if a start up VO wants to mature to a permanent VO should focus on right strategy and structure and continuously update its strategy and structure. This paper investigates some structural and strategy related issues in a VO. A virtual organization adopts different structures depending upon different internal and external uncertainties. Several studies have also supported the argument that the virtual organizations structure also depends upon level of adoption of technology (Ahuja & Carley, 1998). Baker (1992) suggests that all known virtual organizations structures evolved based on their needs. These structures vary by the nature of the task being performed. Few authors suggest that virtual organization structures evolve in three different stages known as establishment, virtualization and institutionalization (Hedberg et al., 1997).
Methodology The literature study constitutes the major part of this study. The research examined a large sample of literature on virtual organization that has been published in information systems journals books, web pages between 1990 and 2006. The study is conceptual in nature and inferences have been drawn from existing literature and practices.
VO STRATEGY In a traditional organization, strategy selection and formulation process involves first formulating the firm’s corporate strategy by analyzing; customers, core competencies, which include workforce,
facilities, market and financial know-how, systems and technology (Sharma et al., 2006). The firm also has to evaluate the changing nature of business environment especially the competitor’s strength. After analyzing the above items the firm comes up with its corporate strategy. Then the corporate strategy is exploded into functional area strategies for functions such as operations, marketing, finance, and accounting. For example if an US auto company decides to go for Chinese market as a part of their corporate strategy, the operations function should design cars specific to that market. Also, they may have to find suppliers in China or setup plants there. Marketing department may have to find a Chinese auto dealership to market their car. Finance department may have to raise money from Chinese banks or investment companies. For a VO which is usually resource constrained, strategy selection may not be that complicated. The basic strategy selection process for VO may be two step decisions. First and foremost, a VO to succeed must have a good product strategy. Then they have to also decide about their competitive priority. Once the product strategy and competitive priorities are decided, then the VO can deal with structure and infrastructure issues. The firm also has to evaluate the changing nature of business environment especially the competitor’s strength. For a VO, a traditional core competency may not exist in the sense that a VO may lack most of the functional components such as design, sales/marketing, manufacturing, distribution and so on. To setup their corporate strategy they have to rely on the core competencies of the companies in the network.
Product Strategy Here in this article our focus is on a company which will actually come up with an actual product or service idea and then market and sell the product to the customers. There are a host of companies which sells products and services from other companies using internet. An example will be a
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phone card company which sells phone different phone cards through their websites. We would not consider them as VO for our purpose as they do not sell their own products. Understanding customer demand is the first step in formulating the firm strategy. For an established traditional company the customer base is already there, however, for a VO the customers are usually new. A VO has to spend a lot of time trying to understand the nature of customer demand and also viability of the product. For developing a corporate strategy, a traditional firm will look at its core competencies in terms of workforce, facilities, market and financial know-how, systems and technology to evaluate whether a certain firm strategy is in line with its capabilities. For a VO, a traditional core competency may not exist in the sense that a VO may lack most of the functional components such as design, sales/marketing, manufacturing, distribution and so on. To setup their company strategy they have to rely on the core competencies of the companies in the network. So it is imperative that the Core company understands the relevant capabilities of the satellite companies. If the core company and the satellite companies do not have established relationship already then the core company should try to get as much information about them using whatever sources available. The main impetus for a VO is the product idea. If one comes up with a brilliant product idea, the next thing is to make that idea succeed. If the product idea is promising, one may investigate into the possibility of using or forming a VO around the product idea. The product idea needs to be thoroughly evaluated analyzing all the related aspects. For a traditional company the feasibility of a product is evaluated by analyzing markets, competition, pricing etc. assuming that operational and supply chain issues will be handled by the organizations and its suppliers and distributors. However, for a VO, apart from analyzing marketability, competition etc., the operational issues
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such as marketing, manufacturing, sales, distribution issues should also have to be evaluated. It may be advisable to come up with a product and or service idea which is not complex. For example, if one has to produce a new automobile or cell phone or a lawn mower, the degree of complexity in manufacturing, distributing and servicing the products could probably render a VO not an attractive option. Here are some strategies for product selection for a startup VO: 1. Products/service itself should be innovative but not complex. The product should be such that there will be a demand for it and at the same time in terms of complexity, the manufacturing and after sales service etc. should be easy to manage. An example of this may be a VO which wants to sell tailor made clothing. They can setup a web-site where they may advertise different kinds of clothing products, including design, style, coloring etc. For each product, there should be clear-cut instructions as to how to make measurements. The customers can select the design, color and give their measurements and find out the price. Once the order has been received, the order will go to a tailoring company in Thailand. When the order will be done it will be sent to a distribution company in U.S. The orders will be shipped by the distribution company to the customers. Complaints will be handled by a customer service company and if there is any re-do it will be handled by a tailoring company inside U.S.A. 2. Concurrent engineering approach should be used for product selection and the idea of concurrent engineering is that all the aspects of manufacturing, supplier issues, pricing, etc. should be resolved while the product is being designed. In a traditional company it is easy to team up with people from different functional area because they all belong to the
Strategy and Structure in a Virtual Organization
same organization and all have stake in the company. However, concurrent engineering is not as easy in VO setting. Never the less it is very important to sort out details before the product is selected. It is important that the core company has interactions and communication with the entire all the satellite company’s which will be ultimately involved in different processes in the supply chain for delivering the product to the customers.
Competitive Priorities Competitive priorities are critical dimension that a process or value chain must focus on to satisfy both the current and future customers. There are four basic competitive priorities:
Cost In most business environment cost is the important competitive priority as lowering price will facilitate gaining customers and increasing market share. To reduce cost, operations strategy should focus on achieving efficiency by redesigning the product, reengineering the processes, addressing supply chain issues and exploring global opportunities.
Quality Competing on the basis of quality imply that company wants to sell products and services to a niche market. For example, a small private airline has a fleet of luxury planes to serve corporate CEOs. If a company uses quality as a competitive priority, then it should focus on two aspects of quality 1): Top quality and 2) Consistent quality. Top quality is those characteristics of a product and or service that create an impression of superiority. This may need superior product with grater tolerances, demanding requirements, high aesthetics and personal attention. Consistent quality is producing products and or services which meet customer
requirement and expectations on continual basis. For example, a luxury private airline will be always punctual in picking up the clients, flying the plane and arriving at the destination.
Time For many firms time is a competitive priority. Especially as the product life-cycle is becoming short it is imperative to bring out products and service ahead of your competition. There are three approaches to time-based competition, 1) delivery speed, 2) On-time delivery and 3) development speed. Delivery speed is how quick a customer’s order can be filled. The time between the receipt of a customer’s order and the filling it is called lead time. To compete on delivery speed one must try to design the order fulfillment process so that the lead time can be reduced. Sometimes companies may keep inventory or cushion or back-up capacities to compete on delivery speed. On-time delivery is meeting the promised schedule. This could be important for an airline. Also it is important for customers who are working on Just-in-time inventory basis. Development speed is important for those companies where it is important to bring in new products or new version of products before the competition. For example Intel and AMD use this competitive priority. Whoever can introduce the newest computer chip in the market gains market share.
Flexibility Competitive priority based on flexibility allows a company to react to changing customer needs quickly and efficiently. A company may compete based on flexibility using one or more of the following strategies, 1) customization, 2) Variety, 3) Volume flexibility. Customization is catering to individual customers needs. For example a custom home builder builds different houses for different customers. Customization generally implies that the products and or service are produced in low
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volume and has a higher degree of complexity. This requires that organization has people have higher skills and should be able to work closely with customers. Variety is producing products and or services with wide array of choices. Variety is different from customization, in the sense that customization is unique to each customer, while variety could entail different features in the product but the product is not unique. Volume flexibility is ability to produce in smaller or larger volumes within the confines of production parameters. The companies who use volume flexibility as a competitive priority must design their processes so that set-up cost is minimal.
panies. So for a VO design seamless integration of the partner companies is very important. This integration has two major aspects. First, there is a need for technological integration so that all the companies in the network can work as one entity. Second, for management purposes there should be interaction among people from the companies in the network so that all the management issues can be handled effectively and promptly (Green & Inman, 2006). For a successful design of a VO, the following issues should be considered: 1) Selection of VO partners; 2) Understanding the nature of communication requirements; 3) Developing E- infrastructure; 4) Simulation and trial run
Selecting Competitive Priority
Selecting VO Partners
Strategy selection process would dictate the firm strategy that will drive firm’s effort in the areas of product design, process design, supply chain management and customer relationship process. Strategy selection would also include selecting a competitive priority which later is used design the structure of the VO. For example, if the VO wants to compete on the basis of cost, then all the satellite company strategy will have to use processes which will minimize cost at the same time providing implied quality. Or else, if the competitive priority selected is superior quality, then the companies in the VO network should gear their processes to provide superior quality and cost may not be the major consideration (Camillus, 1993).
Once the core company has decided about the product and or service, and the competitive priority, the next step is to form the VO. It was mentioned earlier that, the product strategy should involve concurrent engineering, which means that the potential partners in the network should have input in the very beginning of the venture. However, it may be very much likely that, these relationships may be informal. Now is the time to select the partners in the network and design and work out the details of this partnership (Sommer, 2009). One of the driving forces for selecting VO partners is the competitive priority of the core company. If the core company selects cost as it’s core competency, the VO partners should have a similar competitive priority. That means that their processes should be geared towards providing cost savings maintaining expected quality. If the competitive priority is flexibility, the VO partners should have the similar competitive priority and their processes are developed to accommodate variety and customizations. Once, the issues of matching competitive priorities are resolved, a VO partner should be evaluated based on some other performance criteria such as: 1) capability; 2) reputation; 3) Reliability; 4) cost; 5) Technology integration; 6) Experience as a VO partner.
STRUCTURAL DESIGN ISSUES To be successful a VO should have all the responsibilities and attributes of a traditional company from customer point of view. For an ideal VO customer should not be able to know or at the very least feel inconvenienced by the fact that different processes such as order entry, billing, customer service and support are handled by different com-
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A VO partner should have the required capability in it’s area of expertise. For example, a customer service company should have all the resources and people and expertise and technical know to provide customer support. Reputation of the company is very important. If the company does not have good reputation, which means one can expect trouble down the road. A VO partner should be reliable in the sense that it should repeatedly and consistently provide quality performance. For anew VO it is probably hard to judge the reliability of the partners. Some of the information may be obtained from secondary sources using internet resources. Cost can also be an important factor for selecting a VO partner, It is not true that one has to select the lowest cost partner, on the other hand negotiation for cost and prices should be done to the mutual benefits of the core company and the VO partners. Technology integration is an important issue in selecting VO partners. It is imperative that most of the companies now have access to internet and e-mails. Apart from these basic technologies, A VO may need other knowledge management technologies such as: virtual reality, portals, Extensive markup language (XML), personal devices, intranets and extranets etc. It is also important that all the appropriate technologies are seamlessly integrated across the VO so the customer will not have any idea that the VO is a combination of several organizations (Davidrajuh, 2003). So it is important to understand the technology integration issues before selecting a VO partner. Last but not the least, if a company has already have experienced as a VO, then the implementation issues can be taken care of easily (Stough et al., 2000).
Understanding the Nature of Communication Requirements
the VO partners, but also the customer. Table 1 inventories the nature of communication between different entities such as customers, marketing sales, production/operations, accounting and billing and maintenance and customer support. The core company is called the hub company. For, example the nature of communications between the customer and the hub company may be through phone, e-mail and company web-site. There will be probably no communication between customer and production and operations company. The nature of communications between hub company and marketing and sales company may be faceto-face, e-mail, video, work group and phone (Klueber et al., 1999).
Creating E-Infrastructure Once communications requirements between the different entities in the network are established, the next step is to map appropriate information and communication technology to support those requirements. Table 2 shows the information and communication technologies required to support different communication interfaces. Communications between a customer and other customers can be facilitated by online blog or company portal. Communications between hub company and the marketing and sales company can be accomplished by electronic meeting room, phone, internet, intranet, portal for both the companies. Apart from phone, many of the common information and communication technologies such as internet, intranet, video conferencing, portal may already exist among the VO partners. Some other technologies such as electronic meeting room and video conferencing may not be available to some of the partners. So it may be necessary to negotiate cost and other managerial and technical issues which are relevant for use of those technologies.
To develop the e-infrastructure, it is important to understand the nature of communications between different entities in the VO. This not only includes
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Strategy and Structure in a Virtual Organization
Table 1. Nature of communication Entities
Customer
Customer
Remote Information Exchange
Hub Company
Hub Company
Marketing and Sales Company
Productions/ Operations Company
Accounting and Billing Company
Maintenance and Customer Support
Phone e-mail Portal
Phone e-mail mobile
No communication
Phone e-mail Mobile
Phone e-mail Mobile
E-mail Face-to Face Phone Work Group
Face-to face e-mail, Video, Work group Phone
Face-to face e-mail, Video, Work group Phone
Face-to face e-mail, Video, Work group Phone
Face-to face e-mail, Video, Work group Phone
Phone E-mail
e-mail, Video, Work group Phone
E-mail Phone
E-mail Phone
Phone E-mail
Phone E-mail
Phone E-mail
Phone E-mail
Phone E-mail
Marketing and Sales Company Productions/Operations Company Accounting and Billing Company Maintenance and Customer Support Company
Phone E-mail
Table 2. Mapping information and communication technology Entities
Customer
Customer
Marketing and Sales Company
Productions/ Operations Company
Accounting and Billing Company
Maintenance and Customer Support
Portal Phone Mobile technology Internet
Phone Mobile technology Internet Portal
No communication
Phone Mobile technology Internet
Phone Mobile technology Internet
Electronic Meeting Room, Phone, Internet, Intranet
Electronic Meeting Room, Phone, Internet, Intranet, Portal
Electronic Meeting Room, Phone, Internet, Intranet, Portal
Electronic Meeting Room, Phone, Internet, Intranet, Portal
Electronic Meeting Room, Phone, Internet, Intranet, Portal
Intranet Phone E-mail
Electronic Meeting Room, Phone, Internet, Intranet, Portal
Electronic Meeting Room, Phone, Internet, Intranet, Portal
Internet Phone
Productions/ Operations Company
Phone Internet
Phone Internet
Accounting and Billing Company
Phone Intranet
Phone Internet
Hub Company
Marketing and Sales Company
Maintenance and Customer Support Company
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Online Blog Portal
Hub Company
Phone Intranet
Strategy and Structure in a Virtual Organization
Simulation and Trial Run
appearance of physical boundaries have enabled the emergence of virtual organizations from a “futuristic “concept to reality (Greiner & Metes, 1995). Virtual organizations consist of independent companies networked together for providing product and services to the customer on behalf of the core company. VO provides entrepreneurial opportunities for a company with limited resources. However, the implementation of a VO has a lot of challenges which must be overcome (Christie & Levary, 1998). This study augments the existing literature on virtual organizations. The literature research indicate that though virtual organizations suggest network structures in theory but in practice, structural dimensions have been of hierarchy and centralization nature (Black & Edwards, 2000). The relationship between task routineness and structure has been well established in the literature for virtual organizations (Stough et al., 2000). The study is limited to the number of information systems and management journals that were used for virtual organization literature search. The authors recommend that further studies need to be conducted widening the literature survey set on virtual organizations in larger set of journals. Also the conceptual framework needs to be tested for its empirical evidence. In this paper we have discussed issues related to strategy and structure for a VO. Main focus of a VO should be the product strategy. Also, a product
To have a better understanding of how the whole VO works, a simulation may be performed incorporating all the processes starting from placing a customer order, billing process, communicating the information to the operations company, making a prototype, shipping the prototype to the distribution company, sending the product to the customer, handling customer complaints for billing, handling customer returns and so on. Before the trial run or simulation it is important to devise a performance matrix for all the important processes. Table 3 shows example of some of the performance criteria for different processes. All of the performance criteria may not be evaluated during the simulation. The ones which could evaluate, such as time between order and delivery, production lead time, time to answer customer complaint, time for refund etc. may generate valuable information which will help in redesigning the processes (Vakola & Wilson, 2004).
DISCUSSION AND SUMMARY Rapid advancement, availability and affordability of internet-based technologies have changed the way the companies do business to stay competitive. Rapid growth of e-commerce and the disTable 3. Performance criteria for important processes Marketing and Sales and Customer relationship process
Percent of wrong orders Time between order and delivery Percent of delayed order Time to take an order Time to re-do
Productions and Operations
Production lead time Percent of returned order Percent of re-do
Accounting and Billing
Percent of wrong billing Time for refund
Maintenance and customer support
Time to answer customer complaints Percent of customers complaining Types of customer complaint
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Strategy and Structure in a Virtual Organization
strategy should be established in conjunction with competitive priority such as cost, quality, time and flexibility. The competitive priority is important for designing important processes in the VO. For example, if a VO chooses to focus on the competitive priority of cost, then the VO partners should design their processes to be cost efficient at the same time maintaining expected quality. Structural design issues for a VO includes selecting the VO partners, understanding the communication requirements, mapping the information and communication technology and simulating the processes. Simulation of the VO may resolve some technical and managerial issues before the actual operation and enable the company to achieve customer satisfaction from the very start (Vakola, & Wilson, 2004).
Blau, J. (1997). Global networking process management challenges. Technology Management, 40(1), 4–5.
REFERENCES
Coulson, K. R., & Kantamneni, S. P. (2000). Virtual corporations: The promise and the peril. Retrieved March 23, 2005, from http://www. dcpress.com/jmb/virtual.htm
Ahuja, M., & Carley, K. (1998). Network Structure in Virtual Organizations. Journal of ComputerMediated Communication, 3(4), 10(6), 741-757. Baker, W. (1992). The network organization in theory and practice. In Nohria, N., & Eccles, R. (Eds.), Networks and Organizations (pp. 327–429). Cambridge, MA: Harvard Business School Press. Barnatt, C. (1995). Office space, cyberspace and virtual organizations. Journal of General Management, 21(4), 78–91. Beyerlein, M., & Johnson, D. (1994). Theories of self-managing work teams. Stamford, CT: JAI Press. Black, J. A., & Edwards, S. (2000). Emergence of virtual or network organizations: fad or feature? Journal of Organizational Change Management, 13(6), 567–576. doi:10.1108/09534810010378588
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Camillus, J. (1993). Crafting the competitive corporation: Management systems for future organizations. In Lorange, P., Chakravarthy, B., Roos, J., & Van De Ven, A. (Eds.), Implementing strategic process: Change, learning, and cooperation (pp. 313–328). Oxford, UK: Blackwell. Cascio, W. F. (1999). Virtual work places: Implications for organizational behavior. In Cooper, C. L., & Rousseau, D. M. (Eds.), The Virtual Organization (Vol. 6, pp. 1–14). Trends in Organizational Behavior. Christie, P. M. J., & Levary, R. R. (1998). Virtual corporations: Recipe for success. Industrial Management (Des Plaines), 40(4), 7–11.
Davidow, W. H., & Malone, M. S. (1992). The Virtual Corporation: Structuring and Revitalizing the Corporation for the 21st Century. New York: Harper Collins Publishers. Davidrajuh, D. (2003). Realizing a new e-commerce tool for formation of a virtual enterprise. Industrial Management & Data Systems, 103(6), 434–445. doi:10.1108/02635570310480006 Dubinskas, F. A. (1993). Virtual Organizations: Computer Conferencing and Organizational Design. Journal of Organizational Computing, 3(4), 389–416. doi:10.1080/10919399309540210 Flaig, S. (1992). Virtual enterprise: Your new model for success. Electronic Business, 153-155. Goldman, S., Nagel, R., & Preiss, K. (1995). Agile Competitors and Virtual Organizations. New York: Van Nostrand Reinhold.
Strategy and Structure in a Virtual Organization
Grabowski, M., & Roberts, K. H. (1998). Risk mitigation in virtual organizations. Journal of Computer-Mediated Communication, 3(4), 49–65. Green, K., & Inman, R. (2006). Does implementation of a JIT-with-customers strategy change an organization’s structure? Industrial Management & Data Systems, 106(8), 1077–1094. doi:10.1108/02635570610710764 Greiner, R., & Metes, G. (1995). Going Virtual: Moving Your Organization into the 21st Century. Upper Saddle River, NJ: Prentice Hall. Hedberg, B., Dahlgren, G., Hansson, J., & Olve, N. (1997). Virtual Organizations and Beyond. New York: Wiley. Jarvenpaa, S. L., & Leidner, D. E. (1998). Communication and trust in global teams. Journal of Computer-Mediated Communication, 3(4), 18–37. Klueber, R., Alt, R., & Oesterle, H. (1999). Emerging electronic services for virtual organizations - concepts and framework. In P. Sieber & J. Griese (Eds.), Workshop on Organizational Virtualness and Electronic Commerce (pp. 183-204). Zurich, Switzerland: Simowa. Kotorov, R. P. (2000). Virtual Organization: Conceptual Analysis of the Limits of its Decentralization. Journal of Modern Business. Retrieved from http://www.dcpress.com/jmb/jmb.htm Lipnack, J., & Stamps, J. (1997). Virtual Teams: Reaching Across Space, Time, and Organizations with Technology. New York: John Wiley & Sons. McDonugh, E. F. III, Kahn, K. B., & Barczak, G. (2001). An investigation of the use of global, virtual, and collocated new product development teams. Journal of Product Innovation Management, 18(2), 110–120. doi:10.1016/S07376782(00)00073-4 Mowshowitz, A. (1986). Social dimensions of office automation. In Myovitz (Ed.), Advances in computers (pp. 335-404).
Mowshowitz, A. (1994). Virtual Organization: A Vision of Management in the Information Age. The Information Society, 10, 267–288. doi:10.1 080/01972243.1994.9960172 Palmer, J. W., & Speier, C. (1997). A Typology of Virtual Organizations: An Empirical Study. In Proceedings of the Association for Information Systems 1997 Americas Conference, Indianapolis, IN. Palmer, J. W., & Speier, C. (2001). A Typology Virtual Organizations: An Empirical Study. Retrieved from http://hsb.baylor.edu/ramsower/ais. ac97/papers/palm_spe.htm Pang, L. (2001). Understanding Virtual Organizations. Information Systems Control Journal, 6, 42–47. Porter, M. (1990). Competitive Advantage of Nations. New York: Free Press. Potocan, V., & Dabic, M. (2002). The Virtual Organization from the Viewpoint of Informing. In Proceedings of the Informing Science (pp. 1267-1275). Sharma, S. K., Chen, C., & Sundaram, S. (2006). Implementation Problems with ERP Systems in Virtual Enterprises/Virtual Organizations. International Journal of Management and Enterprise Development, 3(5), 491–509. doi:10.1504/ IJMED.2006.009572 Skyrme, D. (1999). Virtual Teaming and Virtual Organizations: 25 Principles of Proven Practice. In Lloyd, P., & Boyle, P. (Eds.), Web-Weaving: intranets, extranets and strategic alliances. Oxford, UK: Butterworth-Heinemann. Snow, C. C., Lipnack, J., & Stamps, J. (1999). The virtual organization: promises and pay-offs, large and small. In Cooper, C. L., & Rousseau, D. M. (Eds.), The Virtual Organization (Vol. 6, pp. 15–30). Trends in Organizational Behavior.
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Sommer, R. (2009). A planning solution for virtual business relationships. Industrial Management & Data Systems, 109(4), 463–476. doi:10.1108/02635570910948614 Stough, S., Eom, S., & Buckenmyer, J. (2000). Virtual teaming: a strategy for moving your organization into the new millennium. Industrial Management & Data Systems, 100(8), 370–378. doi:10.1108/02635570010353857
Vakola, M., & Wilson, I. E. (2004). The Challenge of Virtual Organization: Critical Success Factors in Dealing with Constant Change. Team Performance Management, 10(5-6), 112–120. doi:10.1108/13527590410556836 Wolff, M. (1995). New Organizational Structures for Engineering Design Commissioned Report. Retrieved from http://www.worldserver.pipex. com/ki-net/content.html
Townsend, A. M., DeMarie, S. M., & Hendrickson, A. R. (1998). Virtual teams: Technology and the workplace of the future. The Academy of Management Executive, 12(3), 17–29.
This work was previously published in International Journal of E-Adoption (IJEA), Volume 2, Issue 4, edited by Sushil Sharma, pp. 48-60, copyright 2010 by IGI Publishing (an imprint of IGI Global).
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Chapter 6.7
Assessment Strategies for Servant Leadership Practice and Training in the Virtual Organization Darin R. Molnar eXcolo Research Group, USA
ABSTRACT Leadership in the virtual organization presents unique opportunities and challenges for the manager. Some researchers consider management in the virtual organization to be comprised mainly of challenges while others see it as the opportunity to realize competitive advantage in the global marketplace. Several leadership approaches offer interesting options for the manager within the DOI: 10.4018/978-1-60960-587-2.ch607
context of the virtual organization. One standout approach that has gained increasing popularity over the last 30 years is servant leadership in which the leader is servant first. Those managers in virtual organizations who have committed to a practice of servant leadership recognize the need for assessment instruments to help them understand the level of perceived servant leadership characteristics among organizational members under their guidance. This understanding acts as a foundation for training within this context. With this in mind, Laub’s Organizational Leader-
Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
Assessment Strategies for Servant Leadership Practice and Training in the Virtual Organization
ship Assessment (OLA) offers a reliable survey instrument accepted by the servant leadership practice community. The OLA is easily administered to virtual organization members as a set of Web pages and can be used in conjunction with complementary, third-party data sets such as the World Values Survey database. Future directions for the assessment of servant leadership in the virtual organization include the potential modification of the OLA, as well as the creation of survey instruments to be used in conjunction with it.
INTRODUCTION The practice and training of organizational members as servant leaders in the virtual organization is conducted under the same constraints as any other leadership approach (Bass & Stogdill, 1990; Burns, 1982). An important aspect of any leadership practice is the efficient and effective administration of survey tools to gauge the perceptions of organizational members. This helps managers hone their practice in ways that increase its efficacy in order to serve the organizational members under their guidance. In the case of the virtual organization, servant leaders are presented with the logistical challenge of assessing the perceptions of members in a widely distributed organization. Laub’s (1999) Organizational Leadership Assessment (OLA) instrument offers a reliable tool that is widely accepted by the servant leadership research community. As an introduction to ways in which a servant leader may enhance her practice by using the OLA, this chapter introduces servant leadership and its practice, covers the opportunities and challenges of practicing servant leadership in the virtual organization. It discusses the OLA in greater depth and explains how the OLA might be used in the virtual organization with original and third-party data sets to assess the perceptions of organizational members regarding the level of servant leadership practiced by organizational members. This will help managers better under-
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stand the groups they manage and allow them to tailor training programs as necessary. As a forward-looking conclusion, future directions for the assessment of servant leadership in the virtual organization using the OLA, along with complementary instruments, are offered.
SERVANT LEADERSHIP Greenleaf’s (1970) publication of The Servant as Leader represents a Kuhnian paradigm shift in the truest sense of the term. Kuhn (1996) presents the notion that new ideas arise not from a single prophet in the wilderness, but rather from a groundswell of knowledge and research which most often culminates in a seminal publication, or publications, representing both a consolidation of knowledge and the opening of a new knowledge gateway through which others may pass. The creator of the seminal publication is often quite new to the discipline. This is where the Greenleaf story diverges from the Kuhnian concept of paradigm shift, though paradigm shift it most certainly was. Robert K. Greenleaf presented the idea of servant leadership after he had retired from AT&T where he held various leadership positions for forty years (Frick, 2004). Greenleaf claims to have come upon the idea of servant leadership after reading Hesse’s (2003) Journey to the East in which one of the characters, Leo, plays a central role as guide to a group of Europeans traveling in Asia. After a long and arduous journey in which several characters lose their lives, the main character of the book discovers that Leo, the seemingly insignificant servant of the troupe, is actually “the titular head of the Order, its guiding spirit, a great and noble leader” (Greenleaf, 1977/2002, p. 58). At the time of Greenleaf’s epiphany, the United States was still in the throes of the social discord and violence created by the Vietnam War. Greenleaf eventually published what has become the seminal book on servant leadership, Servant Leadership: A Journey
Assessment Strategies for Servant Leadership Practice and Training in the Virtual Organization
into the Nature of Legitimate Power and Greatness (Greenleaf, 1977/2002). One of Greenleaf’s fundamental goals was to create a better society by asking the rhetorical question of students he taught at Dartmouth, Harvard, and MIT: “Who is standing in the way of a larger consensus on the definition of the better society and paths to reaching it?” (Greenleaf, 1977/2002, p. 58). In the intervening years between the publication of The Servant Leader: A Journey into Legitimate Power and Greatness and now, we have seen an explosion of servant leadership publications, seminars, conferences, and university programs in the United States and abroad. Servant leadership has finally become a positive force in making our society more patient, understanding, and compassionate by transforming how leaders and managers in all sectors perform their duties and train their followers. At the foundation of this burgeoning shift is an understanding of the importance of values and the role they play in shaping the behaviors of leaders and organizational members whose initial desire is to serve others. At the very heart of servant leadership praxis is a willingness to lead by first serving others: It begins with the natural feeling that one wants to serve, to serve first. Then conscious choice brings one to aspire to lead. The person is sharply different from one who is leader first, perhaps because of the need to assuage an unusual power drive or to acquire material possessions. For such, it will be a later choice to serve-after leadership is established. The leader-first and the servant-first are two extreme types. Between them are shadings and blends that are part of the infinite variety of human nature (Greenleaf, 1977/2002, p. 27). This quote from Greenleaf speaks to the personal values of the servant leader and how those values affect his or her view of what it means to lead others. Fortunately, the principles of servant leadership have been constructed upon a solid foundation of virtue ethics that extends from the
works of Aristotle (1911/1998) to contemporary times (Annas, 2003; Hookway, 2003; Murphy, 1999; Slote, 2003, Solomon, 2003; Whetstone, 2001). An ethic based upon principles of virtue emphasizes the moralistic character and personal comportment of the agent. In the case of servant leader as agent, the practitioner is required to ask, “What sort of person am I?” whenever confronted with a situation requiring an ethical decision. This stands in contrast to various other normative ethics which prompt the agent to ask questions such as, “How should I behave in this situation in order to maximize the good and minimize the harm for all parties involved?” The servant leader will rely upon intrinsic and deep-seated moral characteristics to make decisions in an ethical manner. In this way, servant leadership is a way of being in which the practitioner is constantly monitoring and adjusting his own functional leadership attributes and behaviors (i.e., ways of doing) with the goal of fulfilling the role of true servant leader. For every way of being there exists one or more ways of doing, and servant leadership is no exception. Before construction of practice guidelines may begin, a measurement strategy should be created to capture and quantify outcomes. Such a strategy must be highly reliable with solid internal consistency and verifiability for researchers while offering a stable standard, or set of standards, that is repeatable within multiple, competing research contexts. The first step in this construction process is the identification and definition of characteristics that are capable of informing the theory, hypotheses, discipline, field, or study. Several good efforts have been made within quantitative and qualitative methodics to identify fundamental behavioral and character attributes of servant leaders (Dennis & Bocarnea, 2005; Dennis & Winston, 2003; Laub, 1999; Page & Wong, 2000; Russell, 2000; 2001; Russell & Stone, 2002; Spears, 2004). The most notable of these efforts at this time are those by Spears (2004), Dennis and Bocarnea (2005), Page
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and Wong (2005), Russell and Stone (2002), and Laub (1999). The assessment of servant leadership has been problematic since its introduction into the leadership and management literatures. This stems from two facts: (a) servant leadership is a relatively new approach to leading and managing people and an assortment of assessment instruments has not yet amassed and (b) to this point in time servant leadership has been an inherently qualitative approach. The first factor is an understandable dynamic of a new field of study while the second presents a unique challenge. Because servant leadership is a way of being, the practitioner is constantly considering and honing her own functional leadership attributes. When combined with assessment in the context of the virtual organization, the task of assessing servant leadership practice can become daunting. Fortunately, assessment approaches exist that make this task easier for managers.
SERVANT LEADERSHIP IN THE VIRTUAL ORGANIZATION Organizational leadership has been a vigorously discussed topic within the academic community since the early part of the 20th century (Taylor, 1918/1998; Weber, 1947). As the emphasis on the organization as a hierarchical, bureaucratic structure shifted to more flexible forms with less centralized control structures within the leadership literature, new ways of thinking about and analyzing the roles and activities of leaders emerged (Bass & Stogdill, 1990; Burns, 1982). Granted, these new approaches to leadership research were not created exclusively by new organizational forms, yet they were certainly influenced by the need to study organizational leadership and management in a new light. Now, in the early part of the 21st century, these new forms are often heavily influenced by innovative economic forms and technologies available for the analysis of both the structure and management of
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organizations. Argandoña (2003, p. 3) recognizes three basic features of the new economy: “(1) a knowledge- and information-based change, (2) which is taking place in real time on a planetary scale (globalization), and (3) which entails a new, flexible, network –based business organization.” One of these new change-driven forms is the virtual organization. A popular assumption about the virtual organization per se is that it is composed only of geographically dispersed members. As organizations have adapted to new work environments, virtual teams have gained increasing importance as a management structure at the local level. Arnison and Miller (2002) remind us virtual organizations as dispersed teams “could include any team that uses technology to collaborate for a common purpose with the support of the organisation and with the necessary technology to enable the team to reach its goals” (p. 169). This flexible definition speaks to the often transient nature of this type of organization. Temporary virtual project work teams fall under this definition and represent a nimble approach to product development, yet this chapter is concerned with the more stable form of the virtual organization, one that lasts longer than the duration of a project and whose lifetime is considered theoretically perpetual. Hence, the virtual organization under consideration here may range in size from the few members who comprise a startup company to a global virtual powerhouse with hundreds of thousands of members scattered across the globe. Regardless of its size, the virtual organization is now an accepted organizational form. This makes the assessment of servant leadership practice in the context of the virtual organization an important part of ensuring its continued success. Like any innovation, the virtual organization presents opportunities and challenges for managers. Minimal personal interaction, group member accountability and accessibility issues, lack of traditional control mechanisms, performance management logistics, and cross-cultural contexts
Assessment Strategies for Servant Leadership Practice and Training in the Virtual Organization
Table 1. Spears’ ten servant leadership characteristics Listening
Listening, coupled with regular periods of reflection, is essential to the growth of the servant-leader.
Empathy
The servant-leader strives to understand and empathize with others.
Healing
Learning to heal is a powerful force for transformation and integration.
Awareness
General awareness, and especially self-awareness, strengthens the servant-leader.
Persuasion
The servant-leader seeks to persuade others rather than to coerce compliance.
Conceptualization
The ability to look at a problem (or an organization) from a conceptualizing perspective means that one must think beyond day-to-day realities.
Foresight
Foresight is a characteristic that enables the servant-leader to understand the lessons from the past, the realities of the present, and the likely consequences of a decision for the future.
Stewardship
Servant-leadership, like stewardship, assumes first and foremost a commitment to serving the needs of others.
Commitment to the growth of people
Servant-leaders believe that people have an intrinsic value beyond their tangible contributions as workers.
Building community
Servant-leadership suggests that true community can be created among those who work in businesses and other institutions.
Note: Adapted from Spears, L. C. (2004). The understanding and practice of servant-leadership. In L. C. Spears & M. Lawrence (Eds.), Practicing servant leadership: Succeeding through trust, bravery, and forgiveness (pp. 9-24). San Francisco: Jossey-Bass.
are just a few of the challenges leaders face in this new world. Personal qualities typically reinforced through daily contact and by example are much harder for leaders to effect in a virtual environment. This makes it vastly more difficult for managers to establish the trust relationships so necessary for the creation and ongoing maintenance of successful training programs. On the other hand, Silbergh and Lennon (2006) and Shekhar (2006) see member perception of the effectiveness of virtual organizations and the highly dispersed nature of the form as grounds for competitive advantage on a global scale. Ultimately, the success of the virtual organization is based upon outcomes realized from leadership characteristics, behaviors, and practices such as strategic thinking, goal setting, positive motivation, and general ethical environment. One particularly effective approach which relies upon all of these, as well as virtue ethics and the personal ethical comportment of the leader, is servant leadership. The distributed nature of the virtual organization requires an ethic that is transparent and trusting, rather than opaque and controlling, and servant leadership answers such a call.
QUALITATIVE APPROACHES TO SERVANT LEADERSHIP PRACTICE ASSESSMENT As the former director of The Greenleaf Center for Servant-Leadership and now the Spears Center for Servant-Leadership, Larry Spears carries considerable weight whenever addressing servant leadership topics, of which he is an expert acknowledged across the world. He identifies 10 characteristics of servant leadership in Table 1 below. These characteristics have been widely accepted within the servant leadership academic and practice communities. In a similar vein, Russell and Stone (2002) offer two complementary lists of servant leadership attributes. These two lists are described by Russell and Stone as (a) functional because their classification “primarily results from their repetitive prominence in the literature” (2002, p. 146) and (b) supporting with regard to the functional attributes. The two lists are presented in Table 2 below. The functional attributions are “operative qualities, characteristics, and distinctive features belonging to leaders and observed through specific leader behaviors in the work-
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Table 2. Russell and Stone’s servant leadership functional and accompanying attributes Functional Attributes
Accompanying Attributes
Vision
Communication
Honesty
Credibility
Integrity
Competence
Trust
Stewardship
Service
Visibility
Modeling
Influence
Pioneering
Persuasion
Appreciation of others
Listening
Empowerment
Encouragement Teaching Delegation
Note: Adapted from Russell, R. F., & Stone, A. G. (2002). A review of servant leadership attributes: Developing a practical model. Leadership and Organization Development Journal, 23(3), 145-157.
place” (Russell & Stone, 2002, p. 146). The accompanying attributes are secondary characteristics intended to complement the functional list. There exists no correlation between the functional and accompanying attributes; they are merely counterparts which Russell and Stone consider fundamental parts of two basic servant leadership models. In a summary to their literature review, Russell and Stone assert that “since values are the core beliefs that determine an individual’s principles, they are the independent variables in a model of servant leadership. The dependent variable is manifest servant leadership” (2002, p. 153). They suggest two models of servant leadership. Model 1 describes “the relationship between leader attributes and manifest servant leadership” (p. 153) while Model 2 “is a more encompassing model for servant leadership” (p. 153). Model 2 includes considerations of organizational culture, behaviors, and performance in a systemic loop structure. The accompanying attributes act as intervening variables in both models which serve to raise and modify the functional attributes. Regardless of the model, the primary goal of Russell and Stone
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is to construct the groundwork for further discussion and dialogue centered on the establishment of additional servant leadership theoretical and practice frameworks, not for training program development.
PAGE AND WONG’S SERVANT LEADERSHIP MEASUREMENT INSTRUMENTS Page and Wong have developed several servant leadership measurement instruments aimed at self-assessment and the measurement of both positive and negative leadership characteristics (Page, 2004; Page & Wong, 2005; Wong & Page, 2003; Wong & Page, 2005; Wong, Page, & Rude, 2005). The research at the core of these instruments is a qualitative literature review combined with their own experience putting servant leadership principles into practice (Page & Wong, 2000). Their efforts have resulted in 12 servant leadership categories: integrity, humility, servanthood, caring for others, empowering others, developing others, visioning, goal setting, leading, modeling, team building, and shared decision-making. Other researchers (Dennis & Winston, 2003) have taken pains to apply quantitative statistical techniques to Page and Wong’s work in the interest of creating a tractable servant leadership measurement scale. Dennis and Winston’s (2003) principal component factor analysis “indicates that Page and Wong’s instrument measures three of the 12 purported factors and while it did not represent all 12, this scale represents a potential tool with positive implications for training new and existing leaders” (Dennis & Winston, 2003, p. 456). This instrument clearly holds promise, yet lacks the maturity and quantitative methodological rigor sought by so many practicing managers, especially those hoping to use the tool as a training aid.
Assessment Strategies for Servant Leadership Practice and Training in the Virtual Organization
QUANTITATIVE APPROACHES TO SERVANT LEADERSHIP PRACTICE ASSESSMENT While qualitative approaches to assessing servant leadership are an important part of constructing a viable practice, many managers are more comfortable with quantifying results. A popular approach involves the administration of a survey instrument to a sample population followed by application of statistical methods and procedures to attempt hypothesis disproof. Such instruments already exist with more in development. Here, we will examine Dennis and Bocarnea’s (2005) and Laub’s (1999) instruments in greater depth, paying special attention to the utility of Laub’s Organizational Leadership Assessment (OLA) instrument as a way to understand the level of servant leadership in the interest of refining servant leadership training strategies and tactics within the virtual organization context.
DENNIS AND BOCARNEA’S SERVANT LEADERSHIP ASSESSMENT INSTRUMENT Dennis and Bocarnea (2005) build upon Dennis’ (2004) study to create a servant leadership assessment instrument based upon Patterson’s (2003) theory of servant leadership. Dennis and Bocarnea base their instrument solely upon Patterson’s (2003) “component constructs underlying the practice of servant leadership” (p. 15) detailed in Table 3 below. Dennis and Bocarnea’s study constructs a proposed servant leadership characteristic set; it uses the Delphi (i.e., panel-of-experts) method for settling upon a final survey item list gathered from follower data. By conducting a factor analysis with Oblimin rotation, Dennis and Bocarnea (2005) “sought to answer the following question: Can the presence of Patterson’s servant leadership concept be assessed through a written
Table 3. Patterson’s servant leadership constructs Construct
Description
Agapao Love
To love in a social or moral sense
Humility
The ability to keep one’s accomplishments and successes in perspective
Altruism
Helping others selflessly just for the sake of helping
Vision
Necessary to good leadership
Trust
Speaks to leader morality and competence
Service
A mission of responsibility to others
Empowerment
Entrusting power to others
Note. Adapted from Patterson, K. A. (2003). Servant leadership: A theoretical model. Dissertation Abstracts International, 64 (02), 570. (UMI No. 3082719).
instrument?” (p. 610). In the end, they are only able to verify five of Patterson’s seven servant leadership constructs, eliminating the altruism and service factors.
THE ORGANIZATIONAL LEADERSHIP ASSESSMENT INSTRUMENT Laub’s creation of the OLA1 marks a significant contribution to the development of a reliable, internally consistent, and quantifiable servant leadership characteristics scale. Several researchers have utilized the OLA in a range of disciplines from school effectiveness to law enforcement to job satisfaction (Braye, 2001; Drury, 2004; Hebert, 2003; Herbst, 2004; Irving, 2005; Ledbetter, 2004; Miears, 2005; Molnar, 2007; Thompson, 2004). Laub recognizes within the servant leadership scholarly community “a significant lack of quantitative research, as we are still in the early stages of study in this new field; and there is a need for tools to assist in ongoing research” (1999, p. 34). This was an accurate statement in 1999 and still rings true today. Laub’s response to the recognition of the need for more quantitative servant leadership research
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is to develop a three-phase study composed of a Delphi panel, a pilot study, and a cross-sectional survey consisting of a sample drawn from 41 organizations distributed throughout the world. The Delphi panel is composed of 14 recognized experts in the field. Factor analysis of Laub’s study results produced six categories of servant leadership: (a) values people, (b) develops people, (c) builds community, (d) displays authenticity, (e) provides leadership, and (f) shares leadership. The discovery of these factors is important for several reasons and will be more fully explored later. In his doctoral dissertation study, Laub (1999) initially develops 74 survey questions using the Delphi panel technique. This technique ensures qualitative research design rigor (Malterud, 2001; Morgan & Smircich, 1980; Munck, 1998, Tobin & Begley, 2004), which is important during the early design phase of a survey instrument. The origins of this method lie in the Rand Corporation’s early efforts at forecasting military probabilities covering scenarios such as large-scale bombing attacks against the United States (Helmer, 1975, p. xix). Linstone and Turoff (1975) offer a concise definition of the method: “Delphi may be characterized as a method for structuring a group communication process so that the process is effective in allowing a group of individuals, as a whole, to deal with a complex problem” (p. 3). Thus, the Delphi technique is considered an iterative, facilitated, expert group communication process that is, at its heart, a qualitative effort. In this way, Laub’s initial efforts at creating a quantitative servant leadership assessment instrument are grounded in the qualitative realm. This is not the last time we will observe the qualitative and quantitative domains engaged in a relationship in which one needs the other and vice versa. The OLA uses a Likert-type scale that ranges from one for “Strongly Disagree” to five for “Strongly Agree” (see Figure 1 for organization level examples) with six additional questions designed to assess job satisfaction for a total of 80 survey questions. After deciding the survey took
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too much time to complete, Laub settled upon 60 servant leadership characteristic questions plus the job satisfaction questions for a total of 66 questions (Laub, 1999). Seven demographic, or control variable, questions are included. These questions are intended to assess respondents’ categorical responses under gender, age, level of education, type of organization, number of years with the organization, present position with the company, and ethnic origin. These variables are important for researchers because they allow research question and hypothesis testing based upon statements such as, “Gender affects a participant’s view of his/her role within the organization.” Such statements are important because they tie more general statements about servant leadership at the organizational level to organizational members. Laub is able to use the factor analysis statistical technique with his study data to discover the six sub-scores mentioned above: (a) values people, (b) develops people, (c) builds community, (d) display authenticity, (e) provides leadership, and (f) shares leadership. By creating an instrument that “has been developed in such a way that it can be taken by anyone, at any level, within an organization, work group or team” (Laub, 1999, p. 49), the resulting instrument effectively and accurately measures the servant leadership characteristics of respondents at three levels: (a) top management, (b) management, and (c) workforce/ staff. As a quantitative approach, Laub’s OLA is an instrument of high quality and reliability that
Figure 1. Example items from the organizational leadership assessment instrument
Assessment Strategies for Servant Leadership Practice and Training in the Virtual Organization
is quickly becoming the de facto standard among servant leadership researchers for measuring servant leadership characteristics in a quantitative way.
PUTTING THE OLA TO USE Laub’s OLA is an effective instrument in the context of the virtual organization in which a researcher administers it to a sample population drawn from that organization. Several researchers have conducted similar studies with great success (Braye, 2001; Hebert, 2003; Ledbetter, 2004; Miears, 2005; Molnar, 2007; Thompson, 2004), and more continue to incorporate the OLA into their work every day. Because the OLA is comprised of 60 items using a Likert-type scale with an upper bound of five, the measure of the quintessential servant leader is 300 (60x5). This allows a researcher several opportunities for good, solid statistical analyses. For instance, the mean, median, and mode and total counts by category are easily accomplished. A good researcher will make use of the OLA’s demographic (control) variables to run the Analysis of Variance (ANOVA) technique with the goal of determining whether any of the demographic variables might influence the servant leadership scores of the respondents. As an example, one may discover whether gender influences the group’s servant leadership practice. This is accomplished using a statistics software package such as SPSS. In such a scenario, the researcher would use the ANOVA function of SPSS to include the gender variable with the mean servant leadership scores for the entire sample. The result would be the discovery of possible influence by one of the genders (for humans, male and female) upon the practice of servant leadership in that particular sample. This example assumes the researcher has the time and resources to pursue such a data collection regimen. In the likely event that time and money act as study constraints, the researcher may use the
OLA and Laub’s (1999) doctoral dissertation study as guides for creation of their own servant leadership index from a secondary data set. Such a data set might come from the researcher’s own organization (e.g., a prior study/human resources department) or from a third-party. Useful for such a study is Hebert’s (2004) doctoral dissertation. Her study includes a factor analysis of Laub’s six sub-scores in which she produces a single factor, servant leadership. This finding is important for two reasons: (a) it compresses multiple servant leadership meta-characteristics into a single factor and (b) it allows other researchers to rely upon her work to define servant leadership characteristics within foreign datasets. An example of this might involve the creative use of Hebert’s compression technique in conjunction with the World Values Survey (World Values Survey, 2008) database. In some ways, the World Values Survey (WVS) represents the ultimate virtual organization. This longitudinal study is comprised of demographic and values data from 80 countries located on all six inhabited continents of the world. It has been conducted in waves starting in 1981, the last taking place over the course of 2005 and 2006. The point is well taken when the WVS Web site states that “the most important product of this project may be the insight that it produces concerning changes at the individual level that are transforming social, economic and political life” (World Values Survey, 2008). Along with plentiful demographic information, the values data points of the WVS consist of survey items such as, “For each of the following, indicate how important it is in your life. Would you say it is…” The values choices for this item are family, friends, leisure time, politics, work, and religion with Likert-type scale answers that include very important, rather important, not very important, and not important at all. Hundreds of similar items exist in the survey and can vary from wave to wave. Though some items may be included in the survey for all of the waves, not all of the questions are asked by interviewers during
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the administration of each wave. This can create interesting gaps for the researcher interested in discovering how values change over time for a particular country or group of countries (e.g., region of the world), yet this is not uncommon for a study of this scope and size. As a way of building a unique “servant leadership index” over several of the WVS items, a researcher will decide which items to include in their fabricated index. This is where the relationship between quantitative and qualitative data decisions rises again. In this case, the researcher will use Laub’s OLA sub-scores, (a) values people, (b) develops people, (c) builds community, (d) displays authenticity, (e) provides leadership, and (f) share leadership, combined with Hebert’s compression of them into the single “servant leadership” factor to make determinations about which WVS variables to include in their own, unique servant leadership index. Once several variables are chosen and a determination regarding which of the five data sets to use is made, the researcher will use a statistical package such as SPSS to run the Cronbach’s Alpha statistical technique to decide whether the chosen variables measure the same construct (i.e., internal reliability), servant leadership. In this way, the researcher has made a qualitative determination about which quantitative values to use. He has also then used a quantitative technique to establish the reliability of the new “instrument” before using other quantitative techniques such as ANOVA and Pearson’s Correlation Coefficient (Pearson’s r) to determine correlations between variables. In the context of a virtual organization, a survey instrument such as the OLA can be created as a set of Web pages that capture the item answers to a database. Since the OLA covers three levels of an organization, (a) top management, (b) management/supervisory, and (c) workforce/ staff, it would be instructive to administer the survey over time to see if and how member views of the level of organizational servant leadership have changed. Such recognition in organizational member perceptions is an important part of main-
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taining a vibrant servant leadership practice. As the mean OLA score for the virtual organization shifts up or down, it will become the task of the leader-manager to understand why such a shift is taking place and create a plan for how to modify organizational dynamics to correct or enhance it. Regardless of the direction of the shift, it will have been the careful and conscientious administration of the OLA that made its recognition possible.
FUTURE DIRECTIONS The ideas presented here regarding the use of Laub’s (1999) OLA constitute a short introduction to the use of such an instrument as a training assessment and program preparation tool in the context of the virtual organization. Laub originally administered the OLA to traditional organizations, yet there is nothing inherently “traditional” in the tool that prevents its use by servant leadership practitioners in virtual organizations. The OLA is an excellent resource for the preparation of training programs by providing clear understanding of the level of servant leadership within the organization. One opportunity for further refinement of the OLA might involve the reduction of the number of items presented by the instrument. Reducing the number of items while retaining its practical efficacy would make the OLA more attractive to organizational members and managers alike. Research into the creation of complementary instruments that consider an individual organizational member’s servant leadership practice would hold enormous utility for managers, as well. Finally, a comparison study of OLA results from traditional and virtual organizations would provide information about servant leadership practice in the virtual organization, as well as valuable research details about differences that might exist between administering such a tool in the two environments. Regardless of the context in which the OLA is used, it is a valuable tool for
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managers to conduct both pre- and post-training assessments of the virtual organization.
REFERENCES Annas, J. (2003). The structure of virtue. In M. DePaul & L. Zagzebski (Eds.), Intellectual virtue: Perspectives from ethics and epistemology (pp. 15-33). New York: Oxford University Press, Inc. Argandoña, A. (2003). The new economy: Ethical issues. Journal of Business Ethics, 44, 3–22. doi:10.1023/A:1023226105869
Drury, S. L. (2005). Employee perceptions of servant leadership: Comparisons by level and with job satisfaction and organizational commitment. Dissertation Abstracts International, 65(09), 3457. (UMI No. 3146724). Frick, D. M. (2004). Robert K. Greenleaf: A life of servant leadership. San Francisco: BerrettKohler Publishers. Greenleaf, R. K. (1970). The servant as leader. Indianapolis, IN: The Greenleaf Center for Servant Leadership.
Aristotle. (1998). Nicomachean ethics (D. P. Chase, Trans.). Mineola, NY: Dover Publications, Inc.
Greenleaf, R. K. (2002). Servant leadership: A journey into the nature of legitimate power and greatness (25th anniversary ed.). New York: Paulist Press.
Arnison, L., & Miller, P. (2002). Virtual teams: A virtue for the conventional team. Journal of Workplace Learning, 14(4), 166–173. doi:10.1108/13665620210427294
Hebert, S. C. (2004). The relationship of perceived servant leadership and job satisfaction from the follower’s perspective. Dissertation Abstracts International, 64(11), 4118. (UMI No. 3112981).
Bass, B. M., & Stogdill, R. M. (1990). Bass and Stogdill’s handbook of leadership: Theory, research, and managerial applications (3rd ed.). New York: Simon & Schuster.
Helmer, O. (1975). Foreword. In H. A. Linstone & M. Turoff (Eds.), The Delphi method: Techniques and applications. Reading, MA: Addison-Wesley Publishing Company.
Braye, R. H. (2001). Servant-leadership: Belief and practice in women-led businesses. Dissertation Abstracts International, 61(07), 2799. (UMI No. 9981536).
Herbst, J. D. (2004). Organizational servant leadership and its relationship to secondary school effectiveness. Dissertation Abstracts International, 64(11), 4001. (UMI No. 3110574).
Burns, J. M. (1982). Leadership. New York: HarperCollins Publishers.
Hesse, H. (2003). Journey to the east (H. Rosner, Trans.). New York: Picador USA.
Dennis, R. S., & Bocarnea, M. (2005). Development of the servant leadership assessment instrument. Leadership and Organization Development Journal, 26(8), 600–615. doi:10.1108/01437730510633692
Hookway, C. (2003). How to be a virtue epistemologist. In M. DePaul & L. Zagzebski (Eds.), Intellectual virtue: Perspectives from ethics and epistemology. New York: Oxford University Press.
Dennis, R. S., & Winston, B. E. (2003). A factor analysis of Page and Wong’s servant leadership instrument. Leadership and Organization Development Journal, 24(8), 455–459. doi:10.1108/01437730310505885
Irving, J. A. (2005). Servant leadership and the effectiveness of teams. Dissertation Abstracts International, 66(04), 1421. (UMI No. 3173207). Kuhn, T. S. (1996). The structure of scientific revolutions (3rd ed.). Chicago: Chicago University Press.
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Assessment Strategies for Servant Leadership Practice and Training in the Virtual Organization
Laub, J. A. (1999). Assessing the servant leadership organization: Development of the Servant Organizational Leadership Assessment (OLA) instrument. Dissertation Abstracts International, 62(02), 308. (UMI No. 9921922).
Page, D., & Wong, P. T. (2000). A conceptual framework for measuring servant-leadership. In S. B.-S. K. Adjibolosoo (Ed.), The human factor in shaping the course of history and development (pp. 1-16). Latham, MD: University Press of America.
Ledbetter, D. S. (2004). Law enforcement leaders and servant leadership: A reliability study of the organizational leadership assessment. Dissertation Abstracts International, 64(11), 4200. (UMI No. 3110778).
Popper, K. (2002). The logic of scientific discovery (J. Fried & L. Fried, Trans.). New York: Routledge.
Linstone, H. A., & Turoff, M. (Eds.). (1975). The Delphi method: Techniques and applications. Reading, MA: Addison-Wesley Publishing Company. Malterud, K. (2001). Qualitative research: Standards, challenges, and guidelines. Lancet, 358, 483–488. doi:10.1016/S0140-6736(01)05627-6 Miears, L. D. (2005). Servant-leadership and job satisfaction: A correlational study in Texas Education Agency Region X public schools. Dissertation Abstracts International, 65(09), 3237. (UMI No. 3148083). Molnar, D. R. (2007). Serving the world: A crosscultural study of national culture dimensions and servant leadership. Dissertation Abstracts International, 68/05, 139. (UMI No. AAT 3266277). Morgan, G., & Smircich, L. (1980). The case for qualitative research. Academy of Management Review, 5(4), 491–500. doi:10.2307/257453
Russell, R. F. (2001). The role of values in servant leadership. Leadership and Organization Development Journal, 22(2), 76–89. doi:10.1108/01437730110382631 Russell, R. F., & Stone, A. G. (2002). A review of servant leadership attributes: Developing a practical model. Leadership and Organization Development Journal, 23(3), 145–157. doi:10.1108/01437730210424 Shekhar, S. (2006). Understanding the virtuality of virtual organizations. Leadership and Organization Development Journal, 27(6), 465–483. doi:10.1108/01437730610687755 Silbergh, D., & Lennon, K. (2006). Developing leadership skills: Online versus face-to-face. Journal of European Industrial Training, 30(7), 498–511. doi:10.1108/03090590610704376 Slote, M. (2003). Agent-based virtue ethics. In S. Darwall (Ed.), Blackwell readings in philosophy: Virtue ethics (pp. 203-226). New York: Oxford University Press.
Munck, G. L. (1998). Canons of research design in qualitative analysis. Studies in Comparative International Development, 33(3), 18–45. doi:10.1007/BF02687490
Solomon, D. (2003). Virtue ethics: Radical or routine? In M. DePaul & L. Zagzebski (Eds.), Intellectual virtue: Perspectives from ethics and epistemology (pp. 57-80). New York: Oxford University Press.
Murphy, P. E. (1999). Character and virtue ethics in international marketing: An agenda for managers, researchers, and educators. Journal of Business Ethics, 18(1), 107–124. doi:10.1023/A:1006072413165
Spears, L. C. (2004). The understanding and practice of servant-leadership. In L. C. Spears & M. Lawrence, Practicing servant leadership: Succeeding through trust, bravery, and forgiveness (pp. 9-24). San Francisco: Jossey-Bass.
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Taylor, F. W. (1998). The principles of scientific management. New York: Dover Publications. Thompson, C. H. (2006). The public school superintendent and servant leadership. Dissertation Abstracts International, 66(09). (UMI No. 3190501). Tobin, G. A., & Begley, C. M. (2004). Methodological rigor within a qualitative framework. Methodological Issues in Nursing Research, 48(4), 388–396. Weber, M. (1947). The theory of economic organization (A. Henderson & T. Parsons, Trans., T. Parsons, Ed.). New York: The Free Press.
World Values Survey. (2008). World values survey: The world’s most comprehensive investigation of political and sociocultural change. Retrieved June 25, 2008, from http://www.worldvaluessurvey.org/
ENDNOTE 1
You may find complete information about obtaining and using the instrument at Dr. Jim Laub’s OLAgroup Web site at http:// www.OLAgroup.com.
Whetstone, J. T. (2001). How virtue fits with business ethics. Journal of Business Ethics, 33, 101–114. doi:10.1023/A:1017554318867
This work was previously published in Leadership in the Digital Enterprise: Issues and Challenges, edited by Pak Yoong, pp. 181-193, copyright 2010 by Business Science Reference (an imprint of IGI Global).
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Chapter 6.8
E-Leadership Styles for Global Virtual Teams Petros Chamakiotis University of Bath, UK Niki Panteli University of Bath, UK
ABSTRACT With time, an increasing number of organizations deploy global virtual teams (GVTs) in an effort to respond to the demands and the competitive nature of the global business arena. Leadership, a factor that is arguably central to the successful functioning of collocated teams, is much altered in view of the virtual backdrop, and thus, management practices, when referring to GVTs’ operation and effectiveness, have to be re-addressed. This chapter explores the contribution of a leader-coordinator in GVTs and – by drawing upon interviews with staff that participate in intra-organizational virtual DOI: 10.4018/978-1-60960-587-2.ch608
teams of an eminent global operator – it discusses leadership approaches suitable for those teams. In addition, this chapter attempts to unveil and discuss the personal values that drive ordinary virtual actors to emergently lead their teams. Ultimately, the chapter suggests e-leadership styles which could be of foremost value to current and future virtual teams and virtual organizations.
INTRODUCTION Global Virtual Teams (GVTs) have attracted an overwhelming attention and popularity among both academics and practitioners. GVTs are often viewed as a means to accomplish an or-
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E-Leadership Styles for Global Virtual Teams
ganizational task by breaking any geographical or time constraints (Lipnack & Stamps, 1997), whilst enabling organizations to gain advantage of globally dispersed expertise and knowledge (Bell & Kozlowski, 2002; Hargrove, 1998). The forenamed consider GVTs to be organizing units of work which stem from technological advances, respond to the need for product and service differentiation, and create horizontal organizational structures due to their far-flung nature. In spite of the numerous advantages that the virtual milieu can implicitly offer, researchers and practitioners posit an oxymoron when virtual team working comes into practice (Handy, 1995; Kaboli et al., 2006). Goodbody (2005), for instance, argues that less than 30% of virtual teams are led successfully, and this could be attributed to virtual actors considering themselves a substitute, rather than an evolution of face-to-face communication (Caulat, 2006). Not surprisingly, cultural diversity, lack of trust and face-to-face communication, insufficient training and time difference represent some of the novel hurdles that companies have to deal with. Therefore, while exploring GVTs’ nature, potential and efficiency, one needs to question what constitutes the role of a leader is within a virtual arrangement, and what their contribution to the success of these teams could be. Though as we argue – virtual leadership, or e-leadership as we will refer to it here, has attracted a lot of attention in the literature – it still necessitates investigation. This study questions the use of traditional leadership styles and explores new models of shared leadership, while identifying the values which may motivate virtual team members to emerge as leaders. In doing so, we discuss the gaps in the existing literature and, with the use of an empirical study, we explore different e-leadership styles that may be appropriate for GVTs. Specifically, the study commences with a definition of GVTs and a brief description of their challenges and opportunities, while thereafter we continue with
a synopsis of leadership approaches and styles employed in collocated or virtual settings. What makes this issue topical and interesting for study lies in the fact that information technology is continuously transforming organizational arrangements by adding new variables, and affecting the way people work, the tools they use, the relationships amongst themselves, and ultimately the quality of their performance. Therefore, our aim here is to bridge the lacuna between traditional and virtual leadership, and produce a number of applicable recommendations that will amplify GVTs’ potency and effectiveness. Overall, this chapter discusses different emergent e-leadership styles in GVTs, which could be of foremost value to current and future virtual organizations that operate internationally and wish to improve their management styles. Finally, the implications for research and practice will be explored in the chapter.
BACKGROUND Global Virtual Teams Virtual teams comprise individuals who are geographically, organizationally and time dispersed, and are brought together via technological means of communication in order to accomplish a certain organizational task (Alavi & Yoo, 1997; DeSanctis & Poole, 1997; Jarvenpaa & Leidner, 1999; Townsend et al., 1998). In the literature, it is unanimously acknowledged that virtual teams are different from normal teams in that they are flatter environments with high degree of physical separability – in other words they are intact workgroups – guided by a common purpose and facilitated by technologically advanced communication channels (Duarte & Snyder, 1999; Henry & Hartzler, 1998; Lipnack & Stamps, 1997). In addition, Bal et al. (2000) summarized some common characteristics assembled in GVTs, such as goal orientation, geographical dispersion, deployment
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of computer-supported networks, coordination of interrelated activities, mutual accountability in terms of the outcome, joint decision making and problem solving, and finite duration. GVTs are anticipated to play a prominent role in the structural design of organizations in the future, as they offer several advantages to both the employer and the employee (Alavi & Yoo, 1997; Townsend et al., 1998). Bell and Kozlowski (2002) argue that GVTs offer organizations the chance to access the best-qualified people from every field irrespective of geographical limitations, while providing a high degree of flexibility to the employee by enabling them to work remotely. Presently, though, researchers and practitioners have pinpointed opportunities afforded by GVTs, while several studies have emphasized implicit challenges and problems. Powell et al. (2004), for instance, attempted to discern what is known about GVTs from what is not known and urged researchers to investigate the proneness of certain virtual tasks to generate problems and conflicts. In what follows, we discuss, based on current literature, the key issues that are related to leading GVTs in an effort to better explore this theme.
E-LEADERSHIP: STYLES AND CHALLENGES In the traditional organizational literature, leadership is considered to be a process whereby one member influences and controls the behaviour of the other members toward a common goal (Burns, 1978). Leadership in virtual teams refers to the ability of one person to influence the behaviour of others in a virtual, computer-mediated environment; thus e-leadership. Although e-leadership has been discussed both as a theme in and of itself, and in terms of its effect upon team processes and outcomes (Jarvenpaa et al., 1998; Jarvenpaa & Leidner, 1999; Kayworth & Leidner, 2002; Malhotra,et al. 2007, Tyran et al., 2003; Yoo &
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Alavi, 2004), little is known about its different styles. Different leadership styles exist in the traditional leadership literature. In addition to transformational (which motivates team-members to pass from an individual to a collective level) and transactional leadership (which is based on exchange theory, namely on relationships that are seen as having two-way benefits) (Bass, 1998), attention has been paid to several other styles. For example, there are occasions when outstanding personalities steer others (people, companies and nations) to safety during a crisis (Collins, 1998), and this is known as heroic leadership. Likewise, there are people who possess a magnetic presence and are known as charismatic leaders, while other leaders require obedience and conformity and are known as authoritarian leaders. Those leaders base their behaviours on their view of people being incapable of mastering their forces and lacking personal ambitions (Senge, 1990). Further, situational leadership is centrally dependant upon all variables that make one environment different from another, such as organizational culture (MacBeath, 1998), and learning-centred or instructional leadership is premised on the desire to learn and become better (Fidler, 1997). As opposed to the majority of leadership styles, distributed leadership, which can be also phrased as dispersed, shared or collaborative, represents a newly but an increasingly popular idea within the leadership literature (Mehra et al., 2006). In general, there is some agreement that traditional leadership styles are not suitable to emergent types of organizational arrangements, including GVTs. For example, Shamir (1999) discusses the inappropriateness of current leadership theories and practices for the newly emergent organizations. He argues that as organizations increasingly become boundaryless, flattened, flexible, projectbased and team-based, the need for coordination becomes vital and this can be achieved through shared meanings and values. Therefore, as he puts it, “the main function of organization leaders
E-Leadership Styles for Global Virtual Teams
becomes that of being ‘centres of gravity’ in the midst of weakening frameworks, and balancing the centrifugal forces exerted by loosely coupled structures, fragmented cultures, temporary membership and technologies that increase the distance between leaders and members” (p. 59). Snow et al. (1992) argued that GVTs stand in need of caretakers, or else ad hoc managers who will be responsible for the successful functioning of the teams, including coordination at different levels. Subsequently, Vogel et al. (2001) explained that such caretakers contribute to the team by supporting regular, detailed, and prompt communication, and by identifying individual role relationship and responsibilities. According to Kerber and Buono (2004), virtual leaders should pull together their subordinates’ strengths, and act against the centrifugal forces such as local priorities or time differences. Not surprisingly, they relate the e-leader to the collocated one, placing them in the absolute centre of any activity or responsibility. Virtuality prevents leaders from reaching consensus with their teams, due to the novel hurdles, such as cultural diversity, time difference, insufficient training and technophobia. In view of those problems, Lipnack & Stamps (2000) introduced the term polycephalous which originates from the Greek language and means ‘to have multiple leaders’. This idea relates back to distributed leadership which disproves any leadership styles used in the past. Advocates of this style find that emergent types of work teams which are primarily based around networks depend on the availability of multiple leaders within the team, rather than the traditional top-down approach between the leader and team members (Mehra et al., 2006). Indeed, Zigurs (2003) agreed that in GVTs the leadership role shifts from one individual to the other, as the wide breadth of leadership attributes needed while a team accomplishes its tasks is unlikely to be covered by a single person. This argument is also congener to the functional approach to leadership which focuses on individual
behaviours within a group, in which all serve leadership functions towards the aimed goals (Pavitt, 2004). The functional approach is also supportive of the views that, on the one hand, leadership behaviours are performed by more than one people, and on the other hand, that different players present similar leadership behaviours at different times. Further to different players involved, GVTs also experience the use of different computermediated communication channels. Thus, depending on the channels used, each leader has to deal with different degrees of virtualness (Staples et al., 1999); with some media revealing more social cues and therefore more richness than others. According to the media richness theory, the higher the degree of richness in the channels used in virtual teams, the more synchronous and effective the communication becomes (Daft & Lengel, 1986; DeRosa et al., 2004). Though this theory has been criticized for ignoring social and contextual variables (Markus, 1994; Panteli, 2002), it has significant importance in our understanding of communication patterns in GVTs and affects the relationships among virtual team members and their leaders. Motivation is an issue that has not seen much attention within this topic. McClelland and Burnham (1976), for example, introduced the Leadership Motive Profile in an effort to connect a successful leader’s profile with various types of motivation. On the other hand, a sense of personal growth, a sense of being worthwhile and a feeling of achievement represent some key factors that may motivate team leaders (McKee, 2004). Still, there is the fear that the achievement motivation (which entails personal success motivation), however beneficial it could be, could also have as a result that leaders concentrate more on retaining their leadership position, thus aiming at personal rather than collective success (De Hoogh et al., 2005).
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WHEN LEADING GVTS COMES INTO PRACTICE: THE ‘ALPHA’ CASE STUDY Issues, Controversies, Problems Following the discussion so-far, we decided to focus on a specific case study in order to respond to our research questions and provide pragmatic solutions. In this section, we present the results of our empirical study that aimed to uncover the emergence of e-leadership in GVTs. In what follows, we briefly describe the research approach adopted and present the results of the study.
Research Approach Our empirical study is exploratory in nature, aiming to gain insight into an issue that has seen limited research and focuses on human beings and behaviours. Case studies generally represent the most appropriate research strategy for investigations at the exploratory phase (Yin, 2003). Our single case study approach involved semi-structured interviews with five individuals. The laddering method, which “elicits the higher level abstractions of the constructs that people use to organize their world” (Bourne & Jenkins, 2005), is hereby employed to extract the consequences that originate from the employees’ virtual activities and, by extension, the values that drive them to take control and lead their teams, with or without realizing it. Though it has been used in psychology (Wright, 1970), consumer research (Gutman, 1982), and in human resources management (Jolly et al., 1988), laddering has not been extensively used in management research (Bourne & Jenkins, 2005). Laddering represents a semi-structured interviewing technique which can be the richest single source of data (Gillham, 2000), while it involves a series of direct probes, typified by the ‘Why is that important to you?’ question, with the goal of determining sets of linkages between
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the key perceptual elements across the range of attributes (A), consequences (C) and values (V) (Reynolds & Gutman, 1988). Attributes are the functional benefits of a product. In the case of GVTs, participation in GVTs can be seen as an initial attribute. Consequences are the benefits that flow from these attributes. They explain how they affect the individual or rather emotional benefits. Finally, values are the motivations underlying consequences and attributes of participating in GVTs. A simple ladder will be of the following form (Figure 1).
The Selected Organization In consideration of the aims and the limitations of this study, we decided to take a focus on a distinguished high-tech company in the computer and office equipment industry, a Fortune 500 company. The company, which we call Alpha for confidentiality, operates at a global level, and increasingly depends on permanent and temporary intra-organizational virtual arrangements consisting of people who work for the same company, but live in different geographical areas across the globe. According to the company’s mission statement, Alpha views its employees as the most valuable assets, and encourages everyone to produce innovative ideas and take initiatives before Figure 1. Simple ladder
E-Leadership Styles for Global Virtual Teams
their higher-ups tell them to do so. Further, being a prominent global operator, Alpha provides its employees with cutting-edge technologies and modern communication tools, and is committed to providing a pleasant working atmosphere, while knowledge-sharing, learning from the past, and motivation are importantly promoted through its organizational philosophy. Lastly, Alpha’s senior employees base rewards on performance, they engage their staff in lifelong learning, and they develop leaders who are responsible for exemplifying the company’s values and achieving the anticipated goals. Overall, Alpha’s culture is reflected in its fluid hierarchical structures, the staff’s continuing education, and the fact that everyone is stimulated to innovate and become a leader.
Data Collection Procedure and Analysis The study was carried out between June and August 2007 and it drew upon interviews with several members based in the UK, some of whom have acted as emergent GVT leaders. In-depth interviews are preferably conducted in non-threatening and quite environments which help interviewees to be introspective and elaborate on their experiences (Saunders et al., 2007). The personal contact with each of them also provided an overall image of their personality, as in-depth interviews afford perceptions that cannot be recorded or measured. The interviews were recorded using a digital recorder, while hand-written notes were also taken in case the recorder was damaged. Each interviewee was asked to provide an insight into the day-to-day problems and challenges faced not only by e-leaders, but also by other staff who often participate in GVTs. Interviews lasted approximately 45 minutes each and were listened to twice in order not to miss important elements, and to remove bias. The laddering technique helped us unveil the personal values that drive people to lead their
teams. The ‘why’ probe continued until no further insight was possible, and it was assumed that we had reached the level of values. After identifying performed leadership behaviours, a second set of questions – which was very important in formulating the ladders – was initiated. This phase brought forth the functional and emotional benefits, and self-expressive values the virtual actor seeks whilst leading a GVT. The last set consisted of follow-up questions in order to re-analyze the answers previously given and to cover implicit vagueness. Only three of the interviewees have performed as emergent leaders in current and past GVTs, and consequently, only three ladders where formulated. Lastly, a diagrammatical representation of each interview was formulated, in which all the ladders of the interviewee were combined. Besides, visual displays such as diagrams and matrixes are helpful in analyzing data and drawing conclusions (Gengler & Reynolds, 1995). Due to space limitations, the tables classify both consequences and values into certain broad categories. In these tables, we only refer to consequences and values with frequency of 2 or above, as frequency of just 1 is considered to be insignificant.
Results and Analysis Here, we present a summary of the characteristics of the five employees who were interviewed (Table 1). All five of them are referred to as Persons A, B, C, D and E, preserving their confidentiality. There is homogeneity in terms of age, nationality and other variables, but all have different personalities, different experiences and different approaches. Subsequent to this summarizing table is the analysis of the interviewees, classified by person. Each of the five employees first describes the framework of their GVT experience, and then we critically present their views and stories about the issues that concern this study.
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Table 1. Presentation of interviewees Gender Nationality
Person A
Person B
Person C
Person D
Person E
F
F
M
M
M
British
British
British
British
British
Field
Production
Commodity Management
Development
Management
Procurement
Role
Line Operator
Procurement Specialist
Technical Specialist
Leader
Manager
Virtual Experience
7 years
9 years
10 years
More than 10 years
More than 10 years
Assigned Leader
No
Yes
No
Yes
No
Emerged Leader
Yes
Yes
No
Yes
No
Leadership Realization
No
Yes
-
Yes
-
Leader’s Acceptance
Yes
Yes
Yes
Yes
No
Perceived Outcome Success
99%
80-90%
88%
99%
100% plus risks
Person A Person A represents an open character, and this perhaps contributes to her being a successful leader. She gives the impression of a professional who knows how to be effective and efficient in terms of the company’s productivity, yet she approaches virtuality with anxiety, as “working from different physical locations can be scary.” The UK branch, being a Global Business Unit (GBU), plays a central role in guiding and advising, and therefore, every employee assumes leadership responsibilities somehow. Typically, she collaborates with the USA, and the main body of the GVTs she works in remains stable and does not exceed 10 partners. She uses teleconferencing, phone calls, net-meetings, share rooms, and she believes that “email is the best and the worst thing ever; when a [email] response becomes unprofessional, I always pick up the phone.” Regarding technology expertise, she considers that “if everyone had the skills to fully exploit what technology offers, we would be unstoppable and more productive.”
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She has experienced cultural diversity problems such as different sense of humour, which can easily create misunderstandings. Hence, each time a problem arises, she starts an escalation as diligently as possible. Her role is to ensure that a product maintains a high standard throughout the production process and reaches its end destination on time. Her responsibilities are well-defined and she sees herself as “… a vehicle that initiates a call for a virtual meeting, knows the right people, and has the ability to pull everyone together.” According to her, when a colleague’s voice becomes the one most heard, then they are usually accepted as emergent leaders.
Person B Person B promotes an image of a leader who will not hesitate to act differently and take the initiative. As manufacturing is outsourced at Alpha, Person B’s task it to ensure that quality remains high. Thus, she interacts with suppliers over the phone, via email (continuously), by teleconferencing (twice a week), by videoconferencing (once a month), while she also has face-to-face meetings
E-Leadership Styles for Global Virtual Teams
Figure 2. An example of e-leadership: case of shared leadership
(quarterly). She often posits lack of agreement and coordination as symptoms of diversity. Figure 2 represents a product development process as described by Person B. Person B is often the one to set and finalize a meeting, whilst she also assumes the pay-back analysis, and intervenes when a decision cannot be reached. She has observed situations where “there is a gap and someone steps in and expresses their opinion. When I do this, I speak to people individually first and then I am confident I represent everyone.” She believes that there is always a leader, because, as she puts it, “there’s always a checkpoint;” let alone that “in China, they might say ‘yes’, and you think they replied to your question, even though they mean ‘yes, I’m listening.’” As a leader, she has to “be inclusive and pull people back from wanting to go into the details, although sometimes it’s of value to let the conversation flow and then pull it together.” She argues that “people cannot put their head over the fence and see, because communication is not good enough” and that GVTs require more though than traditional teams, since separation hinders relationship building. For her, an e-leader should meet the following criteria:
• • • • • • • •
One should not be blinked with the target, as they can become dictatorial to have the desire for efficiency to be learnt from and listened to have experience in both leading, and the scientific field to take value from leading and move forward work before the meetings make your team willing to engage with the tasks by affecting the dynamics adapting the leading style according to the circumstances
Person C Person C, a technical specialist within a development group, works with the same virtual people for a number of years, which connotes established relationships with his virtual colleagues and guaranties high level of collaboration in the long-term. Person C appreciates Alpha’s culture that allows fluid structures. Development tasks are classified into three stages: early stage, physical development, and post-development support; Person C is involved in the two latter development processes and he collaborates with five employees from the USA. He mainly uses telephone, email and file sharing, and he travels at least twice a year
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to the USA in order to attend face-to-face meetings, though he also does individual meetings. He generally prefers voice, but “the technical stuff has to be written, so you end up with pictures and graphs”. Additionally, he observes the “absence of coming to one’s office and saying: ‘hey, have a look at this’; in GVTs you don’t get the body language, only the voice language.” When their old manager retired, a new employee took over this managerial role in order to build their team’s framework only, since they “… are all sufficiently experienced and self-driven to need guidance; but in virtual working you don’t always understand the situation correctly.” Judging by his 10-year experience, he defines a set of qualities for a successful e-leader: • • • • •
combination of both technical and managerial skills to be reflected in the results excellent inter-personal relationships ability to re-establish lines of communication and levels of trust ability to pull all different strengths together
Sometimes, one leader from one area is matched by a leader in another area and therefore co-leadership is indicated. Separation in time also requires co-ordination between different leaders, whereby when one leader is unavailable, they hand over to the co-leader and vice versa, and this can be easily delineated in Figure 3.
Person D “Electronic management is wonderful if it doesn’t have to work, if it’s a yes or no answer; for complicated things, you just cannot do it.” Person D represents an experienced leader who is simultaneously engaged in multiple virtual projects and whose job “goes across all technologies”. He is a centred leader who supervises projects lasting from 1 to 15 years. He believes
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that “there’s nothing like speaking to someone; Even if they speak a different language; the next step would be: come over to see me.” Emails are also continual, while he uses video-conferencing 3 or 4 times per week. He is positive that “Without a leader, the project will definitely fall”, though many times a member of staff who is in expert automatically becomes the emergent leader. Equally important Person D views the role of all sub-leaders of a project while a project unfolds, since often “… I might be the leader and then hand on to somebody that takes the next stage.” Moreover, he sees relationship establishment as paramount and he argues that one has to understand personally their subordinates, since “… maybe they have a disabled mother; the leader must understand that.” The grey area in GVTs is owed to language barriers, different working practices and cultural differences. He explains that “… the idea of a product might be born in the USA and the actual implementation of it could be in China; the actual testing of it could be in Germany; people perceive the same procedures differently and this impacts cost and time.” Thus, he adjusts his leadership style according to each GVT. Further, he notes that “… the Japanese will not make a decision, unless everyone agrees on that; that’s a generalization, but they like to be able to agree; they don’t like to say ‘no’ to your face; so they’ll find all sorts of
Figure 3. An example of e-leadership: case of co-leadership
E-Leadership Styles for Global Virtual Teams
ways around it; but when they make a decision, they stick to it.”
Person E As opposed to Person D, Person E prefers the term leader over manager, because the former is about motivating people, whereas the latter is about telling people what to do. Person E gives the impression of a systematic manager, with his level of experience being reflected by the leisure with which he narrates events. In the projects that he is accountable for, they always hit the deadline which indicates a high degree of achievement, yet they take risks and make compromises in order for the product to punctually reach its final destination, the customer. Person E prioritized the communication media his team uses, according to their efficiency, as follows: • •
face-to-face is the best Beta (a pseudonym) is a wonderful full size proprietary video-conferencing system produced by Alpha. One can see a number of TV screens opposite them and then have up to 3 groups talking to each other, and there is a table that joins the screen.
“It’s like you’re all sitting in the same room physically; it’s full size, so you see one person at each frame with high quality and no delays.” •
• •
•
Traditional video-conferencing, where the camera faces the table, is regarded as the next best. Audio conferencing Delta (a pseudonym) is a proprietary type of instant messaging similar to MSN, which offers security and can be used between two people while a meeting is going on. Email is only used to confirm what has been agreed or to pass on information. It
is not used as a debating tool, because it creates misunderstandings and people get offended. “… people perceive sense of humour differently, and emoticons play a role; you don’t see what is serious or not; a joke is really risky, it requires a good relationship, otherwise we don’t make jokes; if it’s a tricky subject and I don’t make jokes in writing.” •
Telephone is often better than emails for conversations
Big product programme meetings use videoconferences twice per week, while the senior management staff attend video-conferences once per week for approximately two hours. Still, emails are only used for confirmation and passing on data, or rarely for peer-to-peer debates. From his experience, when all virtual team members feel ownership of the team’s objectives, a good relationship is developed, and the chance of achieving the target is increased. They have “… both centred and shared leadership, because as a management chain we have matrix organizational structures.” Along with shared leadership though, they also try to maintain clear accountability. Nonetheless, they often break each project down and they “… assign different leaders for each stage.” In Person E’s view, a good e-leader needs a toolbox of skills, a combination of hard and soft skills, and he also argues that, “behaviour is far more important, though you have to adjust to the personality of your team”. Further, an e-leader has to • • • • •
check whether the continuously changing established procedures are followed replay what has just been said emphasize the learning outcome build relationships remotely ensure messages have been received
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• • •
measure the outcome optimize things for next time ask for feedback (not in the form of criticism or calibration)
Person E narrated a current story where one e-leader is not being fully accepted by the rest of his group, as the group comprises very high-level people who do not agree with the leader’s practices, and thus, the project is slowing down. Similarly, he currently faces a second situation where three e-leaders are responsible for one project and “… roles are not clear and issues start to appear.” Therefore, as he states, “… we’ll sit together in two-week time [using Beta video-conferencing] and discuss the roles; if there are personal issues, then face-to-face is always the best way; if there are constraints, we’ll try voice-to-voice, but if it’s not resolved, we’ll approach the local manager.”
Leaders’ Motivation The elicited ladders are cited in the Appendix and the results in terms of the emergent leaders’ motivation are synopsized in Tables 2 and 3. The reasons why people were urged to undertake a leadership position are presented in the first table. All three of them responded to the question “why did you feel that you had to become the leader.” One representative respond was: “It’s the desire for efficiency actually” (Person B). Notably, Person D stated that “there is never any certainty, you make the certainty; and it’s the thrill of getting things done.” Another prominent reason was that the company should thrive in the future and that employees should share knowledge (Person A), learn from their mistakes (Persons A and B), contribute to the commonweal and to Alpha’s promotion (Person B), and improve their everyday lives (Person D). However, it is found that it is not the above reasons per se that actually drive virtual actors to partially or fully lead their GVTs. The interviewees valued those reasons because they linked them
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to the concepts summarized in Table 3. It is therefore evident that more abstract and fundamental motives exist when adopting leadership behaviours. The interviewees reached the values-level via a variety of different ladders, despite the time limitations. They linked this level with the knowledge they gained, with personal comfort, family moments, society’s improvement, and collaboration. These words represent the upper layer of the consequences which resulted in the display of their personal values. The cases of the three emergent leaders’ behaviours being analyzed here disclosed that they are all strong personalities who share prominent principles, self-awareness, and they value their personal integrity high. Furthermore, they all anticipate a high degree of security that Alpha is willing to provide them. Following this, the three emergent leaders also considered satisfaction, happiness, protection of the environment, improvement, and trust building as major personal values. Considering the high results throughout their experience, their high appreciation towards Alpha, and the Table 2. Hierarchical classification of consequences Consequences
Frequency
Understanding / Learning / Contributing
3
Thrill / Desire / Interest
3
Collaboration and Sharing
2
Uncertainty / Problems
2
Everyday life and Society
2
Becoming Better / Comfortable
2
Table 3. Hierarchical classification of values Values
Frequency
Personal Integrity
2
Security
2
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comparison made in terms of financial rewards, it seems that the company covers the majority of their personal values.
Solutions and Recommendations In this section, we discuss the results of our empirical study and present a set of distinct recommendations which will enhance team coherence and will thereby improve team efficiency, whilst considering the limitations which arise from the working context and the research methods employed. These recommendations will be informed by the literature review and our research findings.
DISCUSSION Alpha is an organization with a global presence; its product ideas are generated in the USA, where research and innovation thrive, while manufacturing is outsourced to Asian countries where labour costs are low. Thus, GVTs are a common phenomenon within this organization. In this study, we interviewed managers with substantial virtual team experience. The laddering technique revealed the interviewees’ personal values and justified their preferred leadership styles. Some of the values emerged can be associated with theories on charismatic leadership (Conger & Kanungo, 1987; Shamir et al., 1993). Charismatic leaders engage in proactive social influence (Person D) and share ideological values such as promotion of the company (Person B), the protection of the environment (Person B), family happiness (Person D) or personal integrity (Person A). The interviewees typically follow a transactional leadership style, whereby they seek to develop a two-way beneficial relationship (Bass, 1998), and this is justified by the fact that they aim for rewards upon completion of a project. Most importantly, Alpha e-leaders make use of multiple leadership styles, as they try to adjust to each group (situational leadership), be authorita-
tive (with reference to the Japanese – Person D), and learn from the outcome (learning-centred leadership – Persons A, B and E). We also find that Alpha e-leaders combine different leadership styles simultaneously. Person D, for instance, being engaged in numerous GVTs, endeavours to adjust his leadership style to the idiosyncrasy of each group, while he suggestively notes that Japanese employees work better under authoritarian practices. Overall, however, there seems to be an agreement that leadership should be shared as the project unfolds, and therefore, it is inevitable that multiple leaders are accountable for the same project. The findings indicate different instances where leadership could be shared; this could be, for example, shared among the different countries where members are based (e.g. example given by Person A) or by different sub-group leaders (e.g. Person B). A critical parameter that allows them to reach their objectives is the opportunities they have in drawing upon different communication media to choose from for their virtual interactions. Several communication channels have been mentioned and, in some instances, these have been categorized based on their efficiency and level of interactivity. For example, e-meetings are held via pioneering interactive technologies such as the Beta or the Delta systems, and we therefore argue that these technologies importantly contribute to the GVTs achieving their goals. Despite that, there seems to be a type of technophobia or lack of technological expertise (Persons A, D), and they still consider important face-to-face meetings, especially when personal issues arise (Person E). Cultural diversity is also an issue in Alpha, albeit the fact that they communicate with Anglophone virtual colleagues (mostly from the USA) heavily reduces culture-related hurdles. Nonetheless, they have developed ways to overcome such difficulties, for example by sending emails for confirmation of what has been already said or agreed (Person E). Alpha e-leaders are usually
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accepted by the rest of the team, while emergent e-leaders make sure they represent their team’s views in order to be fully accepted (Person B). Yet, there are instances where the leader has not been accepted, and for this, Persons C and E suggest that an e-leader has to be managerially and technically skilful.
IMPLICATIONS FOR PRACTICE This project is restricted to the idiosyncrasy of the examined case study, and this would partially prevent us from drawing general recommendations that would apply to each virtual organization. However, we set out a number of points that would be of considerable value to managers and organizations: •
•
•
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By following a pragmatic approach, beneficial changes will be brought about, both for the individual employee’s expectations and the company’s macro-economic objectives. Thus, by embracing the appropriate strategies and adjusting them to situational variables (such as company culture, etc.) an e-leader can achieve high quality results. The research showed that computer-mediated communication cannot be effectively utilized in GVTs, unless members have been adequately trained. Therefore, organizations – regardless of industry and content – should not only invest in the infrastructure per se, but they should equally invest in their human assets (e.g. employee selection and training). Given the qualities that describe the successful e-leader and despite the severe limitation of the context of the paper, virtual organizations should engage in recruiting and promoting the right people who are capable to handle geographical dispersion; in other words, there is a certain set of criteria that a person has to satisfy in order to
overcome virtual hurdles, and companies should filter out future e-leaders, based not on stereotypes, but rather on empirical studies.
FUTURE TRENDS While our goal here is to inform the modern business arena on how to improve their leadership styles and practices, the future seems rather unpredictable due to the constant technological advances and the exigency for efficiency at global level. Leadership is much changed with the advent of instant communication technologies that operate globally, and this chapter could prove useful to a number of organizations, when appropriately studied. Subsequent to our recommendations, we cite the following limitations in order to measure the viability and the degree of applicability and implementation of our models. •
•
The examined sample, in the main, recurrently participates in projects with the same virtual partners; this connotes a high degree of intimacy which leads to the development of trust and well-established relationships. Short-term GVTs have not been explored here. The small sample size importantly limits the generalizability and applicability of our models. Also, because of the nature of the research, the outcome relied upon subjective interpretation of the results. Further research is needed, and we discuss this below.
From our empirical study, several research opportunities, which could expand the academic and working knowledge of virtual leadership, emerge. On the other hand, leadership is not the one and only variable that impacts GVTs’ potency and operation, and thus, the future of the book’s theme could expand to a wider exploration of issues
E-Leadership Styles for Global Virtual Teams
that affect the modern digital enterprise. Concerning our chapter’s future, researchers could move on and provide solutions applicable to a wider spectrum of GVTs. The research opportunities we have identified can be summed up as follows: •
•
•
Future researchers could focus on the plethora of different types of GVTs, varying in length and project types, as well as on different industries and departments. Employment of longitudinal research methodology, for example, could offer a better insight and could shift knowledge on e-leadership from the exploratory to the descriptive and explanatory phases. This would critically aid in understanding the phenomenon of e-leadership and in suggesting new avenues concerning a very wide range of virtual activities. This study initiated an exploration of the factors that motivate virtual actors to spearhead their teams, either a priori or emergently. However, only three of the interviewees have experienced the role of an emergent leader, and thusly, only three ladders were formulated here (Appendix). Therefore, research should examine a larger sample of leaders and should not only expand on the leaders who have acted emergently, but also on the values that determine a priori assigned leaders’ behaviours. Lastly, e-leadership was here studied by looking at two parameters – distribution and motivation. This by no means embraces every single aspect of the phenomenon, and as a result, this chapter is unable to provide successful recommendations in isolation. Considering the relative immaturity of the topic, future research should seek to adapt the majority of the theories on collocated leadership to the uniqueness of the digital enterprise, and form a set of principles which organizations will be
able to follow in order to deploy successful GVTs.
CONCLUSION Drawing on Alpha’s experiences, we agree with existing literature that traditional leadership practices are not always suitable to GVTs, though our data also indicated that these may be seen as appropriate, depending on the situation. Shared leadership was found as the most popular e-leadership style, though the way this is adopted seems to vary. Finally, as our dataset has been limited, we would encourage researchers to extend research in this field, by juxtaposing the theme as entailed in the ‘Future Trends’ section of our chapter.
ACKNOWLEDGMENT We are grateful to Alpha and its employees for their participation in this study.
REFERENCES Alavi, M., & Yoo, Y. (1997). Is learning in virtual teams real? (working paper). Boston, MA: Harvard Business School. Bal, D. J., Wilding, R., & Gundry, J. (2000). Virtual teaming in the agile supply chain. The International Journal of Logistics Management, 10(2), 71–82. doi:10.1108/09574099910806003 Bell, B. S., & Kozlowski, S. W. J. (2002). A typology of virtual teams: Implications for effective leadership. Group & Organization Management, 27(1), 14–49. doi:10.1177/1059601102027001003 Bourne, H., & Jenkins, M. (2005). Eliciting managers’ personal values: An adaptation of the laddering interview method. Organizational Research Methods, 8(4), 410–428. doi:10.1177/1094428105280118 1701
E-Leadership Styles for Global Virtual Teams
Burns, J. M. (1978). Leadership. New York, NY: Harper and Row. Caulat, G. (2006). Virtual leadership. The Ashridge Journal. Retrieved June 20, 2007, from http:// www.ashridge.com/360 Collins, J. (1998). Level five leadership: The triumph of humility and fierce resolve. Harvard Business Review, (January): 66–79. Conger, J. A., & Kanungo, R. N. (1987). Toward a behavioral theory of charismatic leadership in organizational settings. Academy of Management Review, 12(4), 637–647. doi:10.2307/258069 Daft, R. L., & Lengel, R. H. (1986). Organizational information requirements, media richness, and structural design. Management Science, 32(5), 554–571. doi:10.1287/mnsc.32.5.554 De Hoogh, A. H. B., Den Hartog, D. N., Koopman, P. L., Thierry, H., Van den Berg, P. T., Van der Weide, J. G., & Wilderom, C. P. M. (2005). Leader motives, charismatic leadership, and subordinates’ work attitude in the profit and voluntary sector. The Leadership Quarterly, 16, 17–38. doi:10.1016/j.leaqua.2004.10.001 DeRosa, D. M., Hantula, D. A., Kock, N. F., & D’Arcy, J. (2004). Trust and leadership in virtual teamwork: A media naturalness perspective. Human Resource Management, 43(2-3), 219–232. doi:10.1002/hrm.20016 DeSanctis, G., & Poole, M. S. (1997). Transitions in teamwork in new organizational forms. Advances in Group Processes, 14, 157–176. Duarte, D. L., & Snyder, N. T. (1999). Mastering virtual teams: Strategies, tools, and techniques that succeed. San Francisco, CA: Jossey-Bass. Fidler, B. (1997). School leadership: Some key ideas. School Leadership & Management, 17(1), 23–27. doi:10.1080/13632439770140
1702
Gengler, C. E., & Reynolds, T. J. (1995). Consumer understanding and advertising strategy: Analysis and strategic translation of laddering data. Journal of Advertising Research, 35(4), 19–33. Gillham, B. (2000). The research interview. London: Continuum. Goodbody, J. (2005). Critical success factors of global virtual teams. Strategic Communication Management, 9, 18–21. Gutman, J. (1982). A means-end chain model based on consumer categorization processes. Journal of Marketing, 46(2), 60–72. doi:10.2307/3203341 Handy, C. (1995). Trust and the virtual organization: How do you manage people whom you do not see? Harvard Business Review, 73, 40–48. Hargrove, R. (1998). Mastering the art of creative collaboration. New York: McGraw-Hill Companies. Henry, J. R., & Hartzler, M. (1998). Tools for virtual teams. Milwaukee, WI: ASQ Quality Press. Jarvenpaa, S. L., Knoll, K. A., & Leidner, D. E. (1998). Is anybody out there? Antecedents of trust in global virtual teams. Journal of Management Information Systems, 14(4), 29–64. Jarvenpaa, S. L., & Leidner, D. E. (1999). Communication and trust in global virtual teams. Organization Science, 10(6), 791–815. doi:10.1287/ orsc.10.6.791 Jolly, J. P., Reynolds, T. J., & Slocum, J. W. (1988). Application of the means-end theoretic for understanding the cognitive bases of performance appraisal. Organizational Behavior and Human Decision Processes, 41, 153–179. doi:10.1016/0749-5978(88)90024-6 Kaboli, A., Tabari, M., & Kaboli, E. (2006). Leadership in virtual teams. Paper presented at the Sixth International Symposium on Operations Research and Its Applications, Xinjiang, China.
E-Leadership Styles for Global Virtual Teams
Kayworth, T. R., & Leidner, D. E. (2002). Leadership effectiveness in global virtual teams. Journal of Management Information Systems, 18(3), 7–40.
Panteli, N. (2002). Richness, power cues and email text. Information & Management, 40, 75–86. doi:10.1016/S0378-7206(01)00136-7
Kerber, K. W., & Buono, A. F. (2004). Leading a team of change agents in a global corporation: Leadership challenges in a virtual world [white paper]. Adapted from K. W. Kerber & A. F. Buono, Intervening in virtual teams: Lessons from practice. In A. F. Buono (Ed.), Creative consulting: Innovative perspectives on management consulting. Greenwich, CT: Information Age Publishing.
Pavitt, C. (2004). Small group communication: A theoretical approach (3rd ed.). Retrieved June 15, 2004, from http://www.udel.edu/communication/ pavitt/bookindex.htm
Lipnack, J., & Stamps, J. (1997). Virtual teams: Reaching across space, time and organizations with technology. New York: John Wiley and Sons. Lipnack, J., & Stamps, J. (2000). Virtual teams: People working across boundaries with technology (2nd ed.). New York: John Wiley and Sons. Macbeath, J. (1998). Effective school leadership: Responding to change. London: Paul Chapman. Malhotra, A., Majchrzak, A., & Rosen, B. (2007). Leading virtual teams. The Academy of Management Perspectives, 21, 60–70. Markus, M. L. (1994). Electronic mail as the medium of managerial choice. Organization Science, 5(4), 502–527. doi:10.1287/orsc.5.4.502
Powell, A., Piccoli, G., & Ives, B. (2004). Virtual teams: A review of current literature and directions for future research. The Data Base for Advances in Information Systems, 35(1), 6–36. Reynolds, T. J., & Gutmann, J. (1988). Laddering theory, method, analysis, and interpretation. Journal of Advertising Research, 18(1), 11–31. Saunders, M., Lewis, P., & Thornhill, A. (2007). Research methods for business students (4th ed.). Essex, UK: FT Prentice Hall. Senge, P. (1990). The fifth discipline: The art and practice of the learning organisation. New York: Doubleday. Shamir, B. (1999). Leadership in boundaryless organizations: Disposable or indispensable? European Journal of Work and Organizational Psychology, 8(1), 49–71. doi:10.1080/135943299398438
McClelland, D. C., & Burnham, D. (1976). Power is the great motivator. Harvard Business Review, 54, 100–110, 159–166.
Shamir, B., House, R. J., & Arthur, M. B. (1993). The motivational effects of charismatic leadership: A self-concept based theory. Organization Science, 4(4), 577–594. doi:10.1287/orsc.4.4.577
McKee, T. W. (2004). Motivating your very busy volunteers. Retrieved September 2, 2007, from http://www.worldvolunteerweb.org/getnews/ news2.cfm?ArticlesID=572
Snow, C. C., Miles, R. E., & Coleman, H. J. (1992). Managing 21st century network organizations. Organizational Dynamics, 20(3), 5–20. doi:10.1016/0090-2616(92)90021-E
Mehra, A., Smith, B. R., Dixon, A. L., & Robertson, B. (2006). Distributed leadership in teams: The network of leadership perceptions and team performance. The Leadership Quarterly, 17, 232–245. doi:10.1016/j.leaqua.2006.02.003
Staples, D. S., Hulland, J. S., & Higgins, C. A. (1999). A self-efficacy theory explanation for the management of remote workers in virtual organizations. Organization Science, 10(6), 758–776. doi:10.1287/orsc.10.6.758
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E-Leadership Styles for Global Virtual Teams
Townsend, A. M., DeMarie, S. M., & Hendrickson, A. R. (1998). Virtual teams: Technology and the workplace of the future. The Academy of Management Executive, 12(3), 17–29. Tyran, K. L., Tyran, C. K., & Shepherd, M. (2003). Exploring emergent leadership in virtual teams. In C. B. Gibson & S. G. Cohen (Eds.), Virtual teams that work: Creating conditions for virtual team effectiveness (pp. 183-195). San Francisco, CA: Jossey-Bass. Vogel, D., van Genuchten, M. L. D., Verveen, S., van Eekout, M., & Adams, A. (2001). Exploratory research on the role of national and professional cultures in a distributed learning project. IEE Transactions on Professional Communication, 44(2), 114–125. doi:10.1109/47.925514
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Wright, K. J. T. (1970). Exploring the uniqueness of common complaints. The British Journal of Medical Psychology, 41, 221–232. Yin, R. K. (2003). Case study research: Design and methods (3rd ed.). London: Sage. Yoo, Y., & Alavi, M. (2004). Emergent leadership in virtual teams: What do emergent leaders do? Information and Organization, 14, 27–58. doi:10.1016/j.infoandorg.2003.11.001 Zigurs, I. (2003). Leadership in virtual teams: Oxymoron or opportunity? Organizational Dynamics, 31(4), 339–351. doi:10.1016/S00902616(02)00132-8
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APPENDIX Figure 4.
Figure 5.
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Figure 6.
This work was previously published in Leadership in the Digital Enterprise: Issues and Challenges, edited by Pak Yoong, pp. 143-161, copyright 2010 by Business Science Reference (an imprint of IGI Global).
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Chapter 6.9
Strategising Impression Management in Corporations: Cultural Knowledge as Capital Caroline Kamau Southampton Solent University, UK
ABSTRACT Impression management is a powerful psychological phenomenon with much unexplored potential in corporate settings. Employees or corporations can deploy impression management strategies in order to manipulate others’ perceptions of them. Cultural knowledge is powerful capital in impression management, yet this has not been sufficiently explored in previous literature. This chapter argues that impression-motivated employees or corporations need to perform a three-step knowledge
audit: (i) knowing what their impression deficits are; (ii) knowing what impression management strategy is needed to address that deficit, based on the taxonomy of impression management strategies tabulated here; (iii) knowing what societal (e.g. collectivist culture or individualist culture) or organization-specific cultural adjustments are needed. A cultural knowledge base can thus be created through cross-cultural training of and knowledge transfer by expatriates. Multinational corporations can also benefit from utilising the knowledge presented in this chapter in their international public relations efforts.
DOI: 10.4018/978-1-60960-587-2.ch609
Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
Strategising Impression Management in Corporations
INTRODUCTION The success of knowledge transfer often depends on incidental or subsidiary information accompanying the knowledge itself. Communication between humans usually involves nonverbal cues such as facial expressions, gestures, body posture, tone of voice, gaze, clothing style and use of props. Nonverbal cues therefore have an important communicative function (DePaulo, 1992), such as in terms of conveying information on emotional states (Ekman & Friesen, 1971). An individual can strategically manipulate the nonverbal signals that they transmit through a process known as impression management or self presentation (Leary & Kowalski, 1990). Impression management is the strategic attempt to control how one is perceived by others in order to fulfil a deeper aim (Rosenfeld, Giacalone & Riordan, 1995), such as exuding competence in a particular knowledge field or being taken seriously as an expert. There is considerable evidence in organizational settings that impression management by employees can influence supervisors’ ratings of them (Wayne & Liden, 1995; Vilela et al, 2007), increase chances of promotion (Westphal & Stern, 2007) and increase others’ perceptions of ones credibility (Leigh & Summers, 2002). Individuals with knowledge on impression management strategies may therefore successfully utilise this knowledge to, for example, maximise their capacity to influence their organization’s policies and practices. The success of impression management strategies depends on both societal cultural norms on appropriate social behaviour (DePaulo, 1992) and on organizationspecific culture (Drory & Zaidman, 2007), as well as individual characteristics (Snyder, 1974). Impression management in corporate settings has a lot of unexplored potential. This chapter begins by discussing nonverbal communication and compiling a taxonomy of impression management strategies typically used in corporate settings. Cultural knowledge relevant to impres-
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sion management is an invaluable resource to individuals in corporate settings. This chapter explores the impact of societal cultural norms on workers’ choices of impression management strategies, focussing on the contrast between collectivist cultures (e.g. the Far East) and individualist cultures (e.g. Western Europe and North America). The impact of organization-specific culture on employees’ impression management strategies is then discussed. This chapter therefore argues that employees need to acquire a tacit or explicit knowledge base on impression management, and to perform an audit of their impression deficits, the impression management strategies required to resolve these deficits, and the adjustment in strategy needed to accommodate society or organizational cultural norms or individual difference variables. The benefits of cross-cultural adaptation by expatriates, based on fact-finding and the accumulation of knowledge through interactions, and cross-cultural training of expatriate employees, will then be discussed. Having explored impression management from the perspective of employees as individuals, this chapter then goes on to argue that multinational corporations should utilise the kind of knowledge presented in this chapter in their international public relations efforts. Ethical considerations for employees or corporations (concerning their choice of impression management strategy) are then discussed, after which further research questions will be outlined.
Theoretical Background: What is Impression Management? Imagine that Gary, a new systems analyst at an IT department, wants to suggest a major restructuring of a large database. However, his seniors have a reputation for being resistant to change and they are usually hostile towards ideas generated by newcomers. Gary therefore needs to find a way of making his seniors more receptive towards him
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as a potential agent for change. Soon after joining the corporation, Gary frequently indicates that he agrees with his seniors’ policies, he laughs generously at their jokes, he frequently does favours for them, and he regularly drops hints that he really admires them. Weeks later, Gary approaches his seniors and casually asks what they think about restructuring the database. Are his seniors likely to say no? Probably not – at least much less so than if Gary had not deployed the impression management strategy of ingratiation. Impression management is therefore a strategic attempt to influence others’ perceptions or reactions in order to fulfil a personal objective (Leary & Kowalski, 1990), a social objective (Baumeister and Tice, 1986) or a material objective (Leary & Kowalski, 1990). Based on Rosenfeld, Giacalone & Riordan’s (1995) wide scale literature review, Table 1 presents a taxonomy of impression management strategies that are widely used in corporate settings. Impression management begins with “impression motivation” (Leary & Kowalski, 1990, pp 35), whereby a person tries to gauge what others think of them and they develop a desire to control this. Impression management therefore begins with the gathering of information that enables an individual to determine what strategy is needed and why. Leary & Kowalski (1990) suggest that “People deliberately search for cues regarding others’ impressions of them and attend selectively to information that is relevant to making the right impression.” (pp 36). An individual then needs to establish what their motive is. For instance, their desire may be personal – to fulfil an ambition or to construct or maintain a public identity, which is said by Baumeister & Tice (1986) to be a major motive behind impression management. Alternatively, the motive may be purely social – e.g. wanting to be liked or respected (Baumeister & Tice, 1986). Some employee ranks may be predisposed towards such social motives. For example, Palmer, Welker, Campbell & Magner’s (2001) study of 95 middle/upper-level
managers suggests that managers are predisposed towards impression management tactics that are concerned with gaining approval from employees. Another possible motive behind impression management is the quest for material gains (Leary & Kowalski, 1990) such as receiving a pay increase through promotion. Strategies such as ingratiation have been shown to successfully impact on liking (Vonk, 2002) and on employees’ promotional chances Westphal & Stern, 2007, 2006). For instance, Westphal & Stern (2007) surveyed managers and CEOs at some of the Forbes 500 companies, and they found that deployment of ingratiatory tactics such as opinion conformity, doing favours and flattery increased the managers/ CEOs’ chances of being recommended for board appointments. After the impression motivation stage is the “impression construction” stage (Leary & Kowalski, 1990, pp 35), whereby an individual deploys an impression management strategy (see Table 1). This involves the enactment of behaviours that fulfil the motive behind wanting to control others’ impressions. People often use nonverbal behaviour in their impression management strategies, since much of human communication occurs without words (DePaulo, 1992). Such behaviour may be subtle, such as the use of gait and walking style to convey information on age, power and mood (Montepare & Zebrowitz-McArthur, 1988), or it may be more overt. For instance, a data clerk who has made many mistakes with data entry one afternoon may yawn a lot and drink coffee in order to give the impression that fatigue is the reason for the errors. However, not all impression management is exclusively nonverbal. In the previous example, fictitious Gary used both nonverbal behaviour (e.g. doing favours for his seniors) and verbal impression management tactics (e.g. saying that he agrees with them).
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Table 1. Taxonomy of impression management strategies commonly used in organizational settings* Impression management strategy
Ingratiation through opinion conformity
Ingratiation: colloquially referred to as “sucking up to” or “buttering up” someone with the expectation that one will be liked more
Ingratiation through doing favours
Example
Agreement with some disagreement
Mary tells her dissertation supervisor how fantastic his recent article was, how original his thinking is and how similar it is to her own opinion, except for one minor detail.
Transformation of disagreement into agreement
Samson’s says that he disagrees with his project manager’s new marketing plan but later in the meeting he starts nodding and saying that he now sees how wonderful the plan is.
Ordinary favours
Matt offers to walk across town daily to collect his department director’s favourite takeaway lunch.
Favours that cannot be directly repaid
Lucy offers to baby-sit her manager’s pets for a week during her vacation leave.
Flattery via third-parties
During an office party, Thomas tells his supervisor’s husband that she has a fantastic, remarkable leadership style.
Timely flattery
Several weeks before a promotions review, Myra tells her office manager how much she wishes that he could run the entire organization because he does such a great job.
Ingratiation through flattery
Self-promotion to show competence
Patrick often talks to his workmates about what he learned during his student days at the prestigious Harvard University.
Self-promotion with some self-criticism
Betty tells her colleagues how lousy she is at golf but how quickly she can clinch a sale with any type of buyer.
Self-promotion to compensate for weakness
After finding a new software package difficult to use, Henry tells workmates what a whiz he usually is with most computer programmes.
Intimidation: behaving in a threatening or cold manner in the hope that doing so will instil fear in others
Intimidation for downward influence
Rachel, the head chef, shouts and uses bad language at junior chefs who make a mistake.
Intimidation for counter-power
Peter is a union activist and he threatens to get his union to alert the press about practices at the company if his supervisor makes him work on weekends.
Exemplification: behaving like a highly conscientious person, with the intention of making onlookers think highly of oneself
Exemplification through model behaviour
Her colleagues and supervisors always find Gertrude working at her desk, no matter how early they arrive in the morning.
Exemplification through self-sacrifice
Charlie, a hotel worker, takes the shifts that other workers dislike and he does not take any days off during high season.
Supplication: belittling or criticising oneself in the hope of evoking liking from others
Supplication to evoke compassion
Melissa, who has just joined a theatre company, criticises herself often and says that she does not feel good enough to be an actor.
Supplication through exchange
Oscar, a university researcher, talks about how bad he is at writing reports but offers to show a colleague how to analyse the data.
Self-promotion: emphasising ones strong points with the expectation that listeners will have a high opinion of oneself
continues on following page
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Table 1. continued Impression management strategy Indirectness: use of third parties to help one enact an impression management tactic (e.g. ingratiation, exemplification) or to increase ones own social standing
Acclamation: making a false or exaggerated positive claim to enhance ones image
Showing group loyalty: behaving in ways that display ones group identity so as to increase other group members’ liking of oneself
Other nonverbal: Use of other nonverbal strategies or the manipulation of ones nonverbal behaviour to help fulfil an impression management aim.
Example
Indirect impression management through associations with others
Drew, a new associate professor of literature, talks often about his good friend the Pulitzer Prize winner.
Indirect impression management through ‘basking in reflected glory’
The day after their firm won a coveted regional award, employees wore t-shirts with the firm’s name during weekends and non-working hours.
Indirect impression management through boosting
Estate agents working at a company that was severely fined for malpractices tell people that their company is actually one of the best estate agents in the country.
Acclamation through claiming entitlement for positive outcomes
When sales of her company’s newspaper trebled, writer Martha says that her articles contributed to the increase in copies bought.
Acclamation through enhancement
When her marketing team received a commission from a successful local company, Frieda tells colleagues that the company is one of the most successful companies in the country.
Showing group loyalty through slating the disloyal
Esther, who works for a supermarket chain, shows dislike for employees who do not buy groceries at that supermarket chain.
Showing group loyalty through perpetuating norms
Morris always carefully checks with colleagues what the organization’s traditional policies and practices are, before doing anything.
Use of nonverbal status symbols
On his desk, stockbroker Stuart has a photo of himself holding a sports trophy, sailing on a yacht, and he wears expensive-looking clothing.
Use of exaggerated nonverbal behaviour
Edna shows that she likes her new workplace by grinning a lot and laughing indulgently at any joke made by a colleague.
Use of nonverbal behaviour to conform
Workers at a creative consultancy firm have a certain unspoken fashion code, which Ian mimics when he becomes an employee.
*This taxonomy of impression management strategies is based on the comprehensive literature review by Rosenfeld, Giacalone & Riordan (1995)
Overarching Argument: The Need for Integrated Knowledge about Impression Management in Corporate Settings This chapter argues that knowing what impression management strategies there are, however, is not enough. Employees and/or corporations wishing to deploy impression management strategies must gain knowledge on a number of other important factors: cultural factors and individual difference variables. This is because the success of impression management attempts depends on general cultural norms (DePaulo, 1992), the culture of
an organization (Drory & Zaidman, 2007) and on interpersonal or individual characteristics (Wayne & Liden, 1995). To date, literature integrating all these concepts (impression management in corporate settings, societal culture, organizational culture, individual differences) is lacking. For instance, relevant literature published in management journals (e.g. Liden & Mitchell, 1988; Westphal & Stern, 2007) tends to focus on workplace impression management strategies per se (particularly ingratiation). Relevant literature published in cross-cultural management journals (e.g. Richardson & McKenna, 2006) tends to focus on the role of societal culture per se in
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workplace impression management. Relevant literature published in human resources journals (e.g. Drory & Zaidman, 2007) tends to focus on the impact of organizational culture on choice of impression management strategies. Relevant literature published in psychological journals (e.g. DePaulo, 1992) tends to focus on the impact of individual difference variables on impression formation and impression management. This chapter therefore integrates these facets of knowledge about impression management in corporate settings, also presenting (later on in this chapter) an impression management knowledge audit model for impression-motivated employees or corporations to use.
Knowledge about Societal Culture and Impression Management Firstly, let us explore the role of societal culture. The cultural norms of the target audience determine the appropriateness of particular impression management tactics particularly when employees are operating in new cultural settings. This is particularly evident if we consider the impact of cultural norms on the appropriateness of different impression management strategies when used in Far Eastern cultures, compared to Western cultures. The kinds of nonverbal communication that can be acceptably utilised vary from culture to culture, according to culturally-specific norms known as ‘display rules’ (Ekman & Davidson, 1994). Culturally-specific display rules determine the appropriateness of particular nonverbal behaviours and people therefore needs to know what a given culture’s norms and display rules are: “To use nonverbal behaviours successfully for self presentation, people need to have some basic knowledge… of the kinds of nonverbal behaviours that are appropriate to use at particular times and in particular situations, and of the kinds of reactions and interpretations that particular nonverbal behaviours are likely to elicit from others.
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…The abstract understanding of display rules … is important.” (DePaulo, 1992, pp 214) In Far Eastern cultures, impression management in many social situations is governed by the notion of “face” or “saving face”, which can be defined as the avoidance of social embarrassment or loss of dignity (Ting-Toomey, 1994). In Chinese culture, ‘saving face’ is termed mien-tzu, which denotes having propriety/respectability, social prestige and keeping a good reputation (Chang & Holt, 1994). The central role of the notion of ‘face’ in impression management in Far-Eastern cultures is likely to be due to the collectivistic nature of such cultures. Collectivism involves emphasis on group identity, group norms and group harmony over personal needs/identity (Triandis, 1989; Hofstede, 1980), with Far Eastern cultures being examples of collectivistic cultures (Markus & Kitayama, 1991). The notion of ‘saving face’ may thus be closely linked to the desire to be seen as someone who represents the prototypical group member, who does not violate group norms and who contributes well to the wellbeing/stability of the group. For instance, Jackson et al (2006) found that collectivism is a significant predictor of group productivity. This altogether leads us to expect that the impression management tactics of exemplification and supplication are commonplace in Far Eastern corporate settings, and that the tactics of self-promotion or acclamation are relatively rare in the Far East, compared to the West. Another characteristic of collectivism is reverence for authority figures (Triandis & Gelfand, 1998), which ties in well with the idea that ingratiation in the Far East is based on acquiescence to the group’s existing structure and the desire to show that one is not challenging that structure. In corporate settings in Far Eastern countries such as China, collectivism is also likely to be prevalent because many businesses are family owned (Silverthorne, 2005). A qualitative study of Chinese people by Chang & Holt (1994) found that placing high importance
Strategising Impression Management in Corporations
on mien-tzu often led to employees not wanting to own up to being wrong about something, especially to someone of lower ‘status’ (such as in terms of age or employment rank). In addition, they found that mien-tzu is often used as a social bargaining tool, such that someone with a high amount of mien-tzu is likely to exact strong influence over other people. For example, if two neighbours have a dispute, a third neighbour with a lot of mien-tzu because he/she is a respected teacher in the local school has the capability to intervene and help the neighbours resolve their dispute. Chang & Holt write that “Work on ones mien-tzu, therefore, involves attempts to manipulate degrees of relationship so as to augment ones social resources” (pp 122). Concurrently, a person interacting with someone of higher mien-tzu would therefore act deferential, self-abasing in acknowledgement of the other person’s higher status. We would therefore expect that impression management in Chinese corporate settings is governed by the concept of mien-tzu, with high-ranking employees manipulating their own prestige to exact influence or power over their subordinates, and with subordinates playing up to senior employees’ mien-tzu and using ingratiating tactics that signal their respect. The impression management strategy of ingratiation (see Table 1) might thus be commonplace in Chinese workplaces. Therefore, based on collectivist norms, Far Eastern cultures may deem some impression management strategies in Table 1 appropriate or desirable, whereas other strategies may be deemed unacceptable. Likewise, some impression management strategies may lead to successful outcomes in Western European/ North American societies, whereas other strategies are likely to be unsuccessful because of individualist norms. Individualism involves emphasis on personal needs and personal identity over group needs/ identity (Triandis, 1989). Impression management through self-promotion or acclamation is likely to be a regular feature in Western corporate settings because Western European and North
American cultures are regarded as prime examples of individualistic cultures (Markus & Kitayama, 1991). Furthermore, in individualistic cultures, impression management strategies such as exemplification, supplication and ingratiation are likely to be motivated by individual ambitions, rather than concerns about the group. Particular impression management strategies may therefore either be deemed socially inappropriate because they violate collectivist or individualist cultural norms, or they may evoke suspicion or cynicism about the actor’s motives. Vonk’s (1998) studies, conducted in the Netherlands, suggest that people in individualist cultures dislike and are suspicious of colleagues who behave in an ingratiatory manner towards seniors. In a study of supervisor/subordinate pairs from Spain, Vilela et al (2007) found a weak, albeit significant, correlation between ingratiation by employees and liking by supervisors. On the contrary, it is possible that employees in Far Eastern corporate settings have different attitudes to ingratiation, viewing it less cynically than Western workers would, and overt ingratiation might be more effective in collectivist cultures than in individualist cultures. Likewise, whereas norms of ‘face’ in the Far East may necessitate strategies such as supplication, a study conducted in France by Chambon (2005) suggests that supplication by employees in individualist settings is not well received by supervisors and it does not produce favourable impressions. Vilela et al’s (2007) Spanish findings suggest that exemplification by employees has virtually no correlation with supervisors’ liking of employees, whereas the tactic of exemplification is likely to be effective in the Far East. In addition, the strategy of self-promotion is likely to be rare in the Far East and the strategy of showing group loyalty is likely to be commonplace. Granose (2007) found that Chinese managers were likely to use collectivist tactics such as contributing to the organization; Shahnawaz & Bala (2007) found that Indian workers in IT/fast food companies were more likely to use collectiv-
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ist tactics than individualist ones; Chang & Lu’s (2007) Taiwanese study found that organizational loyalty was a key feature of corporate culture there. Similarly, Parkes, Bochner & Schneider (2001) found that collectivism amongst workers in South East Asia led to positive outcomes such as tenure, whereas collectivism did not have such an effect in Australia. Kurman (2001) similarly found that the strategy of self-promotion was less prevalent amongst people in Singapore and China than people in Israel. It is therefore in the interests of Western people working in Far-Eastern corporations (or vice versa) to be aware of cultural norms on impression management strategies when establishing themselves. In addition to cross-cultural variation, some impression management strategies are appropriate in some types of organizations but not others, because of the nature of an organization’s culture.
Knowledge about Organizational Culture and Impression Management When choosing impression management strategies, employees should take into account not only their surrounding culture but also the specific culture of their organization. Drory & Zaidman (2007) argue that: “In the context of their work environment, individuals choose their impression management strategies to maximize their personal gain, [but employees] adopt the functional and appropriate impression management tactics, which will best serve their interests under the existing organizational system.” (Drory & Zaidman, 2007, pp 291) Drory & Zaidman (2007) hypothesised that the types of impression management strategies used by employees in the military (as a ‘mechanistic’ organization) would differ from those used by civilian organizations in Israel. Mechanistic organizations are defined by Drory & Zaidman as those with a rigid hierarchy, high levels of formality,
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emphasis on employee obedience to seniors and minimum opportunities for innovative input by employees. On the other hand, organic organizations are defined by Drory & Zaidman as having a high level of informality, with frequent contact between seniors/juniors, many opportunities for employees to make innovative changes, and so on. Drory & Zaidman found that the Israeli army officers made more impression management attempts than employees in non-military Israeli organizations, and that army officers made more ingratiation attempts than employees in less mechanistic organizations. This supports Liden & Mitchell’s (1988) argument that one of the causes of ingratiatory behaviour in organizational settings is the nature of the organization’s culture, such as in terms of the level of inter-dependence within it. The influence of organizational culture can therefore mean that there are variations in the use of impression management strategies even within a wider cultural setting, such as an individualistic one. Rao, Schmidt & Murray (1995) investigated whether the amount of “formalization and routinization” (pp 153) within an organization would correspond with the use of ingratiation as an impression management tactic. Rao et al surveyed 134 manager-subordinate pairs from British manufacturing firms, government bodies and educational institutions. They determined the organizations’ culture using a measure with items such as: the degree of written work schedules, emphasis on written documents, standard operating procedures, defined job responsibilities, and so on. Unlike Drory & Zaidman (whose study was conducted in Israel), Rao et al’s British study found no significant correlation between the use of ingratiation by employees and the degree of formality/ routine in the organizations surveyed. Organization culture may thus create variations within one wider cultural context (individualist or collectivist), especially for some impression management strategies. Rao et al (1995) suggested that the use of ingratiation may be less typical or effective in British workplaces than in
Strategising Impression Management in Corporations
some other Western countries, such as the United States, – a difference which may be due to organization culture. Wayne & Liden (1995) surveyed pairs of US supervisors/subordinates and found a significant positive correlation between use of ingratiatory impression management tactics and liking by supervisors. Schmidt & Kipnis’s (1984) and Westphal & Stern’s (2007) US studies found similar results. There is therefore an interaction between national culture and organizational culture, as Parkes, Bochner & Schneider (2001) found in their study of workers from Australia and South-East Asia. The extent to which national culture takes precedence over organizational culture (or vice versa) may depend on a number of factors – such as the degree of similarity between the two or the cultural diversity of employees in an organization. Therefore, successful impression management in corporate settings requires that an individual gains important knowledge about both societal and organization-specific culture, and that an individual then uses that knowledge to strategise their impression management.
Knowledge about Individual Differences and Impression Management Irrespective of the culture of the actor or target(s), a person planning an impression management strategy should consider the individual characteristics of each target. Leary & Kowalski (1990) show that the individual attributes of the target audience determine the nature/intensity of impression management strategies chosen. Furthermore, a person’s individual characteristics may make them more competent at impression management or their individual characteristics may influence others’ receptiveness to them. Let us now explore some of the individual differences variables to consider in step three of the impression management knowledge audit model in Table 2. One important individual difference variable to consider is the status or power of the targets or the actor. Generally speaking, people exert more impression management efforts if the target people possess attributes such as high status, power or attractiveness (Schlenker, 1980). Individuals/ corporations may also need to adjust their impression management strategy to accommodate
Table 2. 3-step knowledge audit model for impression management Knowledge audit step 1 Impression deficit = desired impression minus actual impression
Knowledge audit step 2
Knowledge audit step 3
Impression management strategy needed
Adjustment in strategy required? Adjustment required by culture? Collectivist culture
Individualist culture
Organizational culture
=Acceptance deficit
=Show group loyalty
No
Yes
Analyse
=Compassion deficit
=Supplication
No
Yes
Analyse
=Competence deficit
=Exemplification
No
Yes
Analyse
=Credibility deficit
=Indirect tactic
No
No
Analyse
=Liking deficit
=Ingratiation
No
Yes
Analyse
=Power deficit
=Intimidation
Yes
No
Analyse
=Respect deficit
=Self-promotion
Yes
No
Analyse
=Reward deficit
=Acclamation
Yes
No
Analyse
=Status deficit
=Other nonverbal behaviour
No
No
Analyse
Other adjustments required? Case-bycase basis: Individual differences variables – e.g. high status of targets; selfmonitoring trait in self
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their own characteristics. High status, power and/ or attractiveness are likely to make them more successful at impression management (DePaulo, 1992; Schlenker, 1980). At the same time, some characteristics, such as high status, may make some impression management strategies inappropriate or even counter-productive (e.g. ingratiation, supplication), and other strategies may backfire, especially when made public (e.g. intimidation). Another important individual difference variable to consider is the level of ‘self-monitoring’ of the actor. Synder (1974) showed that some individuals are more adept at impression management because they possess high levels of a trait called self monitoring – a trait associated with high need for approval (Paulhus, 1982). Such individuals are also more successful at monitoring the success of their impression management attempts (Gangestad & Snyder, 2000) because of their level of attentiveness to situation cues (Snyder, 1974). People who score highly on the Self Monitoring Scale were found to be able to facially/vocally act out random emotions more successfully than low self monitors, as well as being able to decode others’ facial/vocal emotional expressions (Snyder, 1974). The other important individual difference variable to consider is the gender of the actor or the target(s). Despite advances in gender equality in many countries, sex-role stereotyping still has a pervasive effect on impression formation and on the success of particular impression management strategies. For instance, in their study of 760 US directors, Westphal & Stern (2007) found that male directors who deployed the strategy of ingratiation were more likely to be promoted than female directors who deployed the same strategy. Impression management strategies such as selfpromotion are more frequently used by males than females (Thornton et al, 2006), and women who engage in the strategy of self-promotion may receive hostility because they are viewed as having violated gender stereotypes. Shimanoff
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(1994) reviewed studies on gender differences in face-saving behaviour and concluded that women in many cultures behave in a more polite, subservient way, than men. Supplication has likewise been found to be more prevalent amongst females than males, (Thornton et al, 2006), perhaps because of gender-role stereotypes. At the same time, it is sensible for impression motivated individuals to avoid using tactics (e.g. flattery as part of ingratiation) that targets of an opposite gender could construe as sexual harassment. Timmerman & Bajema’s (1999) review of numerous studies concluded that definitions of sexual harassment vary, but may include such behaviour as unwanted compliments about clothing or appearance. Another important individual difference variable to consider in impression management is based on the concept of ‘idiosyncrasy credits.’ Hollander (1958) postulates that “…by conforming to group norms, people accumulate “idiosyncrasy credits” that allow them to deviate from norms in the future” (see Leary & Kowalski, 1990, pp 42). This suggests that, for example, an individual who usually engages in supplication in conformity to a societal or organizational cultural norm accumulates ‘credits’ that allow him/her to deviate from that supplication without jeopardising his/ her acceptance by the group. Therefore, impression-motivated individuals or corporations need to know about the role of individual difference variables, as well as knowing about the benefits of both society- and organization-specific cultural knowledge.
Integrating and Auditing Impression Management Knowledge: A 3-Step Knowledge Audit Model The first thing that an impression-motivated individual needs to do is to acquire knowledge about other peoples existing impressions of them. An individual who wants to manage others’ impressions of them will need to seek information about what these impressions are in the first place.
Strategising Impression Management in Corporations
Individuals then need to have explicit knowledge of their desired impressions, and to then find out whether there is a deficit between their desired impressions and the actual impressions that people have of them. Overall, there is often a “degree of discrepancy between the image one would like others to hold of oneself and the image one believes others already hold.” (Leary & Kowalski, 1990, pp 39). An impression-motivated individual may find out that there is a deficit in the extent to which they are perceived as competent, powerful, respected, and so on. Secondly, after identifying the nature of the impression deficit, an individual needs to identify the most appropriate strategy to rectify this deficit – something which requires the kind of knowledge that has been presented in this chapter. Table 2 pairs each type of impression deficit with the strategy most likely to rectify that deficit. Of course, more than one impression management strategy may be deployed to attempt to correct a particular deficit. For example, a meta-analytic study by Gordon (1996) of ingratiation studies found that ingratiatory tactics have a significant effect on both performance evaluations and liking. Thirdly, individuals need to find out what the local cultural norms are, as well as finding out about their organizational culture. This will determine the appropriateness of each potential impression management strategy. Individuals or corporations would therefore need to adjust the nature (see Table 1) of their impression management strategy or its intensity, depending on the cultural context. For example, in a Western context, a liking deficit may be solved with an indirect, rather than direct, ingratiation strategy. Therefore, rather than issuing overt flattery, an individual may indicate their flattery through imitation or through a third party. In an Eastern context, rather than engaging in overt self-promotion, an individual may couple their self-promotion with self-criticism, or they may emphasise the contribution of others to their achievements. Furthermore, individuals may need to adjust the nature or intensity of their strategy
to suit the specific culture of their organization, and they may also need to adjust their strategies according to their own individual characteristics or those of their target audience. How can employees – in particular those about to embark on international assignments – acquire this knowledge? Let us now consider the knowledge-enhancing role of cross-cultural training.
Creating an Impression Management Knowledge Base through Cross-Cultural Training Learning a language, reading a travel guide book or watching television programmes of films from a prospective host country is something that some expatriates are likely to do before commencing their jobs abroad. However, more formal cultural knowledge than this is needed. Prior familiarity with a prospective host culture is beneficial to cultural adaptation (Selmer, Chiu & Shenkar, 2007), but familiarity alone cannot sufficiently prepare expatriates for cultural adaptation. Selmer et al found that German expatriates in the USA were better culturally adjusted than American expatriates in Germany, perhaps because of the Germans’ prior familiarity with American culture (through, say, American television programmes or films). Nevertheless, Selmer et al recommended formal cross-cultural training for expatriates before they begin working in new cultural settings. In particular, would-be expatriate workers need to acquire in-depth knowledge about the host country’s cultural norms on interpersonal behaviour and on behaviour in workplaces. Organizations can devise formal cross-cultural training programmes for would-be expatriates, in order to increase their cultural knowledge base. In fact, a cultural knowledge deficit can lead to unreceptive behaviour towards people in the host culture. Richardson & McKenna (2006) conducted a qualitative study of 30 British expatriate academics in the United Arab Emirates, New Zealand, Singapore and Turkey and found that some
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participants discussed a “lack of local knowledge, not being able to relate to people, not having interactions with locals” (pp 13). Cross-cultural training of expatriates should therefore be useful in giving employees knowledge that they can utilise in the new cultural setting, also focussing on giving expatriates knowledge on workplace norms specific to the culture in question. Having prior cultural knowledge would prevent misunderstandings based on a lack of awareness about impression management behaviour in the new culture. Consider Peltokorpi’s (2006) qualitative study of 30 Nordic managers working in Japan from Denmark, Norway, Sweden and Finland. Peltokorpi asked the Nordic managers about their views of Japanese employees’ workplace behaviour. The Nordic managers commented on the prestige associated with age in Japan, such that seniority in rank was often associated with age, rather than competence, and such that “fresh ideas presented by young employees were often shot down before they reached the expatriate managers” (Peltokorpi, 2006, pp 110) because it was considered inappropriate for those of junior rank to present ideas directly to seniors. The Nordic managers also commented on the passiveness of Japanese employees in meetings, with the expatriate managers expressing frustration that the employees did not articulate their own feelings or ideas. The Nordic managers found all these cultural differences problematic. However, prior crosscultural training would have provided knowledge about impression management in workplaces and the impact of Japanese cultural norms on this. For example, junior Japanese employees’ shyness in meetings was probably part of their impression management strategies of supplication and conformity to the concept of ‘face’ – whereby Japanese juniors might not have wanted to risk embarrassing a senior by contradicting his/her ideas in a meeting. The Nordic managers found it problematic that junior Japanese employees sought guidance when asked to complete a task. Again, the Nordic managers appeared to have misinterpreted that as
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a lack of independence when in fact the junior Japanese employees were probably deploying the impression management strategy of supplication, a strategy which was probably usually rewarded by Japanese seniors. The Nordic managers appeared to have recognised the central role of collectivist cultural norms because they pointed out that “… virtually nothing [in the Japanese workplaces] was indicated to occur as a result of individual effort… Individualist and opportunistic behaviour can lead to social sanctions, such as exclusion from the principle social unit” (Peltokorpi’s, 2006, pp 112). However, despite recognising this, the expatriate Nordic managers found it problematic that the Japanese employees worked very well in teams but not so well if alone. Cross-cultural training could have enabled the expatriate managers to recognise the extent to which the impression management strategy of showing group loyalty, based on strong collectivist norms, explains the Japanese employees’ focus on team work, as opposed to individual output. Therefore, cross-cultural training should equip expatriates with knowledge about impression management strategies prevalent in the host culture. Why is this important? Cultural knowledge can make expatriates more culturally adaptive to their new work environment which, as we will now see, has positive effects on their work performance and adjustment.
The Benefits of Cultural Adaptation by Expatriates Cross-cultural adaptation or flexibility by expatriates has many benefits. Before exploring those benefits, it is important to note that adaptation to a new culture need not be assimilation. Pires, Stanton & Ostenfeld (2006) suggest that “adjustment strategies based on immersion in a foreign culture” (pp 156) can be beneficial to expatriates, but this fits the definition of assimilation. Assimilation involves a total immersion into a new culture and the abandonment of ones old culture (Berry, 2001),
Strategising Impression Management in Corporations
whereas cultural adaptation suggests a much more temporary or context-dependent kind of cultural flexibility. Yamazaki & Kayes’ (2007) study of Japanese expatriate managers in the US suggested that they devised ways of adapting to their new culture without actually assimilating in it, suggesting that expatriates do not need to change their cultural practices or beliefs. Therefore, cultural adaptation by expatriates is so called because it involves a dynamic process that ideally begins with fact-finding (such as from cross-cultural training) and continues through interactions with locals that allow further acquisition of knowledge about the impression management tactics that work in that culture. Cultural adaptation by expatriates has been found to have a positive impact on their work performance and/ or adjustment. For example, Shaffer et al (2006) conducted a study of Japanese expatriates working in or soon to be working in the US, as well as Korean expatriates working in other parts of Asia, the Americas and Europe. They found significant, albeit moderate, correlations between cultural flexibility, interaction adjustment (e.g. socializing with locals) and work adjustment (e.g. performing well in ones role). In a separate study of Western expatriates (mainly from the US, UK and Australia) working in Hong Kong, Shaffer et al found significant correlations amongst cultural adjustment, adjustment in interactions (such as socialising with Hong Kong nationals on a daily basis) and cultural adjustment. Likewise, Selmer (2006) conducted a study of 165 expatriate managers working in China from Western countries such as the US, Germany, Britain and Australia. Selmer found that the participants’ adjustment to working in a new cultural setting was positively correlated with their adjustment to interacting with the people in their host country. Similarly, Liu & Shaffer’s (2005) study of expatriate managers working in Hong Kong and China found that the extent to which the expatriates had Hong Kong/ Chinese interpersonal skills was significantly correlated with both work adjustment and inter-
action adjustment. This altogether suggests that expatriates’ work performance is related to their cultural flexibility, their adjustment to their host culture, and their interactions with local people. This is an empirically robust finding. There is also widespread evidence that adjustment to work, adjustment to social interactions, and adjustment to the environment/culture are three distinct variables (e.g. see Shimoni, Ronen & Rozimer’s, 2005, factor analysis using data from expatriates working in Israel). This means that an expatriate’s adjustment to a new workplace is not the same as adjusting to a new culture, and therefore he/ she needs to pay attention to both factors. There is evidence that some expatriates are aware of the benefits cultural adjustment. Stahl & Caligiuri (2005) found that, of 116 German expatriates working in the US and Japan, 18% of the expatriates adopted the strategy of interaction adjustment (e.g. inviting locals to visit their home), and 17% adopted the strategy of behaving in ways that save others’ face. However, the remaining percentage of expatriates that did not demonstrate cultural adaptation was still substantially large. Stahl & Caligiuri found that 25% of the expatriates adopted the strategy of intentionally violating local cultural norms and 21% adopted the strategy of negatively comparing the host culture with their own home culture. This suggests that a small but significant number of expatriates do the opposite of cultural adaptation – something which may have an unfavourable impact on the impressions that they form and the failure of their impression management attempts. This is likely, in turn, to have a negative impact on their work performance and it may harm their employers’ interests because the cultural adjustment process can be beneficial to business negotiations. Moore’s (2006) qualitative study of German expatriates working in the London branch of a German multinational bank found that the participants deployed impression management strategies that enabled them to be effective negotiators between the London branch and the head office. These strategies included
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variously showing group loyalty to the London office or to the German headquarters, playing on their London identity, or assuming an AngloGerman identity. There is also evidence suggesting that cultural adaptation enhances knowledge transfer by expatriates. Liu & Shaffer’s (2005) study of expatriate managers working in Hong Kong and China found a significant correlation between knowledge transfer performance (in terms of e.g. transferring information from the host organization to the home country or vice versa) and work performance, with this being significantly correlated with interaction adjustment. The knowledge gained through cultural adjustment by an expatriate can itself be a beneficial part of the knowledge transferred. Hocking, Brown & Harzing (2007) conducted a case study of a transnational firm and found that the learning of local knowledge by expatriates could be transferred to the home headquarters and therefore increase the latter’s global capabilities. Expatriates should thus be seen as useful fact-finders who can transfer their new cultural/ social knowledge to their home organization, which should in turn incorporate this knowledge into a formal cross-cultural training programme for other employees. What about multinational corporations? Although most impression management in workplace settings occurs at the individual level (that is to say, the actor is an individual rather than a group or organization), this is not to say that corporations cannot deploy impression management strategies. In fact, it can be argued that corporations operating in other cultures should gain knowledge about impression management strategies and use this in their public relations efforts.
Future Trends: Utilising Impression Management Knowledge in Corporate Public Relations Impression management by organizations is what is conventionally known as public relations. If
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organizational impression management is concerned with creating favourable impressions in other countries, it is known as international public relations (see Curtin & Gaither, 2007; Sriramesh & Vercic, 2001). However, corporate public relations are often concerned with that kind of organizational impression management that produces increases in, for example, product sales. In fact, as is evident with individual impression management, the goals of organizational impression management in new contexts should be more than simply marketing a product/service or increasing sales. In fact, it can be argued that – especially when a corporation is operating in a new culture – other impression management goals must necessarily be fulfilled before secondary goals such as increasing sales can be fulfilled. For example, ‘green’ (i.e. eco-friendly) values have become very popular in British culture, to such an extent that some social commentators argue that the green movement has been appropriated by mainstream society (e.g. Giddens, 2006), with increasing demand for products such as ecofriendly property (Telegraph, 2004). Many British companies now incorporate a ‘green’ message in their marketing material and websites, irrespective of whether these messages are relevant to their products or services. For example, a 2008 conference entitled ‘Green Marketing’ targeted themes such as making marketing more eco-friendly, recognising the marketing benefits of eco-friendly values, and so on, with scheduled speakers from mainstream organizations such as the Advertising Standards Authority (a regulatory body), Marks & Spencers, the BBC and British Telecom. Many companies in the UK now conform to eco-friendly values such as use of recycled paper, minimization of energy waste, and so on, integrating them into their corporate ethics. For example, HSBC, British Airways, British Gas, ITV, and many other major UK corporations coalesce with the Carbon Neutral Company, which runs a “carbon offset scheme” (Adam, 2006) that involves planting trees and creating eco-parks to compensate for the
Strategising Impression Management in Corporations
corporations’ negative impact on the environment. Many UK companies and public institutions also promote Fairtrade-certified produce and about 300 towns across the UK refer to themselves as “Fairtrade towns” (Fairtrade Foundation, 2008). Eco-friendly values have thus become so prevalent in the UK that contrary corporate behaviour is often considered a scandal and is ostracised in the media. For example, corporate executives or major politicians/ public figures using a private jet or driving so called ‘gas guzzling’ cars are often strongly criticised for having a large ‘carbon footprint’ (see e.g. BBC, 2006; Reuters, 2007). All this would mean that a new company wishing to fulfil the goal of gaining customers in the UK might first have to fulfil the goal of being viewed as an eco-responsible company. Likewise, in other cultures, there are particular important social values that new corporations need to learn about if they wish to manage the impressions that others have of them in those cultures. Therefore, firstly, organizations operating in other countries need to engage in a considerable amount of fact-finding in order to determine what their impression management goals are. Secondly, having determined their goals, corporations operating in foreign cultures, should – like individuals working in cross-cultural settings – perform the kind of impression management knowledge audit depicted in Table 2. Organizational impression management falls into the realm of public relations, and therefore it would fall upon public relations and marketing staff to seek and utilise knowledge on the appropriateness of different impression management strategies in the new culture. Therefore, such an impression management knowledge audit should establish: what a corporation’s goals are, what strategies are feasible or appropriate in a given culture, and how those strategies can be varied to accommodate successful public relations tactics used in that culture. Adapting impression management strategies to different cultural contexts is something which Coca Cola has often attempted. With regards to the
US market, Curtin & Gaither (2007) point out that: “For almost 100 years… the company [Coca Cola] had spent millions of dollars developing an image steeped in nostalgia and small town America” (pp 46), with Coke succeeding in being viewed as a product that is as American as ‘baseball or hamburgers’ (pp 47). At the same time, in India, Coca Cola adapted its public relations tactics, emphasising its commitment to the community: “…we are deeply involved in the life of the local communities in which we operate” (Coca Cola India; cited in Curtin & Gaither, 2007, pp 22). This resulted in many Indians – particularly those living close to Coca Cola factories – emphatically describing Coke as an Indian product (Curtin & Gaither, 2007). In Africa, the corporation created the Coca Cola Africa Foundation, an organization for “social investment” that addresses both “individual and collective needs” (Coca Cola website, 2008), perhaps in recognition of the likelihood that African cultures have both collectivist and individualist characteristics. Coca Cola’s African mission statement is notably different from the corporation’s Spain Foundation, which focuses on promoting fine arts amongst youths, or the corporation’s Nordic Environmental Foundation, which promotes eco-friendly projects (Coca Cola website, 2008). In Japan and China, Tian (2006) similarly argues that “… Coca Cola has been integrating local traditional cultural factors into its strategies” (pp 16) and on its China website the corporation shows its identification with Chinese culture. It can therefore be argued that Coca Cola’s public relations (or impression management) attempts involve localised cultural adaptation. Nevertheless, these attempts are sometimes undermined by other factors and Coca Cola therefore has to make a continuing effort to maintain its desired impressions. For example, Coca Cola in India has faced widespread criticisms, boycotts and demonstrations because of allegedly emitting toxic sludge (BBC News, 2003a), depleting local water sources (BBC News, 2005) and because
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coke drinks there allegedly contain pesticide pollutions (BBC News 2003b). In the UK, Coca Cola miscalculated the nature of the market for bottled water when it launched a brand of bottled purified tap water (called ‘Dasani’) that received heavy criticism for not only being ‘mere’ tap water but for also containing levels of bromate that contravened UK limits (BBC News, 2004). Dasani was subsequently withdrawn from the UK market. In Belgium, there was a temporary ban on Coca Cola drinks after some consumers complained of shivering, nausea and other symptoms and the corporation embarked on an ‘aggressive’campaign to rebuild its image (Johnson & Peppas, 2003). Therefore, Coca Cola needs to regularly monitor and update its impression management strategies because its public image is itself not static. Similarly, McDonalds recognises the need for cultural adaptation, such as by including meal variations based on local customs. For instance, McDonald’s sells falafel burgers in Egypt and Morocco, burrito breakfasts in the US, kosher meals in countries such as Israel, halal meat in countries such as Malaysia, serving coffee in china cups in Portugal, spicy chicken burgers in Singapore and so on. McDonalds has also learned to adapt itself to suit the needs that are of high importance in a given culture – such as studious behaviour by children and youths. In China and Singapore, McDonald’s has gained fame as a place where children can do their homework (Zukin & Maguire, 2004). However, there are ways in which McDonald’s can further adapt itself to suit local cultural norms. For example, Eckhardt & Houston (2002) found that Chinese participants described seating arrangements at McDonald’s restaurants as “too public” (pp 72) because of their open-plan nature, compared to the cubicle-style of many Chinese restaurants. Eckhardt & Houston report that Chinese couples on dates in McDonald’s restaurants felt more exposed and uncomfortable than they would have felt if seating arrangements were similar to those found in traditional Chinese res-
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taurants or noodle bars. In addition, McDonald’s was slow to adapt to the eco-friendly culture that has been gaining popularity in Britain and other Western countries, governing negative attitudes towards artificial ingredients in food, genetically modified produce and crops not grown organically. The bestselling film “Supersize Me” (Spurlock, 2004), which was a case-study of the effects of McDonald’s meals on health, was arguably a product of this growing cultural phenomenon. McDonald’s sales that year were affected; for example, in the UK, the companies profits fell from £83.8 million in 2003 to £23.5 million in 2004 (see Oliver, 2005). McDonald’s refuted the film’s claims but it then discontinued ‘supersize’ meal options and introduced a ‘Premium’ line in North America, parts of Europe and Australia/ New Zealand. This meant that salads and healthy options such as deli sandwiches were introduced in these parts of the world, although they are may not be financially successful. The fact that this menu continues to be offered in the West and is not available worldwide suggests that the move by McDonald’s was strategic and that it was an example of adjustment to cultural values of growing importance in the West. Furthermore, McDonald’s is often associated with the standardization of eating habits, the elimination of culinary variety and with emphasis on cheap, quick food. This has spawned regional movements such as the European/ North American Slow Food Movement (see slowfood.com), which is against the notion of fast food and supports the more traditional restaurant format. In addition to being associated with the standardization of eating habits, McDonald’s is also often associated with American culture, meaning that some regions of the world resist “McDonaldization” because they associate it with “Americanization” (Illouz & John, 2003, pp 202; see also Bryman, 2003). This has led to regular global protests (such as during the Worldwide Anti-McDonald’s Day) as well as perceptions of conflict between other national identities and consumption at McDonald’s (see
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e.g. Illouz & John, 2003, who discuss attitudes towards McDonald’s in Israel). Therefore, global corporations such as McDonald’s often struggle to maintain the impression that they are truly global and not merely expansions of a corporation from one nation. Some corporations seem to recognise the difficulty of attaining a truly global identity, and they capitalise on their exoticism as representatives of particular cultures, viewing this as a more achievable primary impression management goal. For example, KFC (Kentucky Fried Chicken) emphasises its roots in American cuisine, giving customers in other countries the impression that they are participating in an authentic American eating experience (see Friedman, 1999). Other corporations – rather than emphasising a global identity that downplays national differences – focus on the impression management goal of appearing diverse. For example, it can be argued that the multinational bank HSBC (Hong Kong & Shanghai Banking Corporation) has recognised the benefits of possessing an image of national diversity, and its public relations attempts often revolve around the slogan “The world’s local bank” (HSBC, 2008). Another example is provided by two members of HSBC, Gakovic & Yardley (2007), who discuss “global talent management” (pp 201), which emphasises national diversity of recruits, as the bank’s “organizational development solution” (pp 201). Nevertheless, the impression management aim of appearing global and diverse may be difficult for HSBC to fulfil because its business is unlikely to be equally distributed across all countries with a HSBC presence. As we have seen, some multinational corporations have recognised the benefits of cultural adjustment and strategic international public relations. However, such corporations are arguably in the minority. For example, in terms of advertising in other countries, many corporations use the same television commercials (albeit for dubbing voices in other languages or adding subtitles), believing that the commercials’ success will be replicated in
new countries. In fact, what corporations should do is to regard television commercials or other publicity platforms as important opportunities for impression management, and to therefore begin by performing the knowledge audit in Table 2 before creating or editing commercials to suit each cultural context. Let us consider some hypothetical examples of this in Table 3. In each example, we see how the same impression management goal can be fulfilled in different, culturally-specific ways. The examples in this table illustrate the differences between collectivist and individualist cultures, and they demonstrate ways in which a primary cultural theme (e.g. individualism or collectivism) can be reinforced even whilst trying to meet secondary impression management goals such as being viewed as efficient, polite, popular, down-to-earth, and so on. In addition, as Curtin & Gaither argue, global corporations need to recognise the potentially diverse forms that public relations could take in other countries – and to realize that these forms can be radically different from their own public relations activities at home. For example, Curtin & Gaither report that public relations in India often takes the form of dance, skits and plays; in Ghana, storytelling is often used as a public relations method; poetry is often used in Saudi Arabian public gatherings as part of public relations, and so on. At the same time, corporations need to evaluate the ethics of their chosen impression management tactics, ensuring that their cultural adaptation is not based on harmful over-generalisation (i.e. stereotyping) of their targets’ culture. The need for ethical standards also applies to impression management by individuals.
Controversies: The Ethics of Impression Management In the example provided in Table 1, if Gertrude (who turns up to work at her desk very early in the morning in order to give her supervisors the
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Table 3. Examples of how corporations can deploy impression management strategies Impressionmanagementgoal (multinational corporation)
Known strategy to fulfil goal
Culture-specific example (corporate)
Imagine if Microsoft, a software company, wants to give the impression that it offers the most efficient software.
Acclamation
In a Chinese commercial, Microsoft could claim that it’s anti-virus software enable people to collectively defend China’s computer networks.
In an American commercial, Microsoft could claim that it’s anti-virus software enable each individual subscriber to have the best defended computer.
Imagine if Phillips, an electric appliance company, wants to give the impression that its employees are conscientious.
Exemplification
In a Chinese version of its website, Phillips could depict its factory employees working over-time to ensure that all households are well equipped.
In an American version of its website, Phillips could depict its factory employees working over-time to ensure that hard-working individuals the best equipped homes.
Imagine if CNN, a cable/ satellite television channel, wants to give the impression that prototypical local people watch it.
Indirect tactic
In a broadcast to China, CNN could depict a well-known Chinese family organising a gathering to watch CNN together.
In a broadcast to USA, CNN could depict a wealthy American celebrity watching CNN and benefiting materially from doing so.
Imagine if Ford, an automobile company, wants to give the impression that it its employees are immensely polite.
Ingratiation
In a Chinese commercial, Ford could depict employees in a Ford showroom being very polite to clients whose qualities (e.g. age) are typically accorded respect.
In an American commercial, Ford could depict employees in a Ford showroom being very polite to clients whose qualities (e.g. success) are typically accorded respect.
Imagine if HSBC, a banking company sternly wants to give the impression that it offers authoritative advice.
Intimidation
During a feature on a Chinese discussion programme, community leaders could warn viewers to listen to HSBC’s advice or risk their financial future.
During a feature on an American discussion programme, a well-known entrepreneur could warn viewers to listen to HSBC’s advice or risk financial ruin.
Imagine if Emirates, an airline, wants to give the impression that it has international experts recommend it.
Self-promotion
In a press release in China, Emirates could report that travel experts gave it a star rating, and suggest that this indicates that the international community is pleased with it.
In a press release in the USA, Emirates could report that renown travel experts gave it a star rating, and suggest that this is benefits the image of travellers who use it.
Imagine if Hilton, a hotel chain, wants to give the impression that it is a member or supporter of a given cultural group.
Show group loyalty
In brochures to be distributed in China, Hilton could depict itself as a long-standing host of Chinese cultural events and a hotel chain that upholds Chinese traditional décor and cuisine.
In brochures to be distributed in the USA, Hilton could depict itself as a hotel chain that respects the individuality of guests in the USA, varying the menu and décor of rooms to suit various tastes.
Imagine if Fedex, a courier company, wants to give the impression that it is an unpretentious company.
Supplication
In a documentary to be broadcast in China, Fedex could depict its courier staff as people who make humorous, self-abasing gaffs in their attempt to deliver a package to a community organization in China.
In a documentary to be broadcast in the USA, Fedex could depict a member of its courier staff as a person who makes humorous, self-abasing gaffs in his/ her attempt to deliver a package to a prototypical American.
Collectivist culture
impression that she is conscientious) actually spends the extra time writing a blog, her impression management behaviour seems deceptive. If Samson actually thinks that his project manager’s new marketing plan is awful, but he starts saying that it is wonderful in order to ingratiate himself, this would be deceptive. The head chef Rachel,
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Individualist culture
who shouts and uses bad language at junior chefs as part of the strategy of intimidation may succeed in gaining her juniors’ respect but at a considerable cost to their mental wellbeing. If Martha erroneously believes that her articles contributed to the increase in newspaper copies sold and tells people this, it might be more beneficial to her professional
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ambitions if she objectively evaluates the quality of her articles instead. Therefore, strategies such as ingratiation, exemplification, acclamation, self promotion, and others, might sometimes seem to involve deception of others, self-deception, an exaggeration of the truth, the omission of the truth or harm to others’ wellbeing. James Westphal, in an interview by Capos (2008), discussed the ethical costs of impression management strategies to corporations. In particular, Westphal discussed the ethics of ingratiation, which he argued is not frowned upon and very much the norm in US corporations. Westphal argued that “Ingratiation can have adverse consequences, depending upon the company’s situation… Our research suggests that if directors are appointed on the basis of their ingratiatory behaviour, they are less likely to [question or monitor the decision made at board level].” (cited in Capos, 2008). Westphal reported that managers who lack high-level management experience are most likely to engage in ingratiation, thus gaining access to positions that they otherwise would not have qualified for. Although this may seem beneficial to both the promoted managers and those doing the promoting (whose self esteem would be boosted by ingratiation from former), Westphal pointed out that it is not beneficial to the company as a whole or its shareholders. For example, a company’s performance could suffer if it is led by someone without the appropriate level of competence. Westphal thus recommends that board recruitment is done by outsiders such as head-hunting firms, rather than through informal networks, because the most ingratiatory internal employee or the most ingratiatory external candidate known via social circles (rather than necessarily the most competent) is otherwise likely to be promoted. What about ingratiation through favours (see Table 1)? Westphal (cited in Capos, 2008, who interviewed him for an article) reported that favour-doing is quite common on the US Wall Street, with favours often being market-oriented,
such as in terms of recommending someone for a job or as a supplier. However, Westphal argued that “favour-rendering” is not bribery or fraud. Perhaps the ethics of ingratiation through doing favours depends on whether an individual’s competitors (e.g. their co-workers) have the opportunity or the capability to do similar favours. If Matt (see Table 1) volunteers to collect his department director’s favourite takeaway lunch, this does not seem unethical since his co-workers could volunteer to do the same. If Matt chose to give his department director a $50 gift voucher for Christmas, this might not be bribery since the sum is one which co-workers can afford and the occasion is one which all co-workers have the opportunity to give gifts. If, however, Matt decides to give his director $1000 – even if as a Christmas gift – then this might seem like bribery, especially if Matt is secretive about his gift and if the circumstance suggests that it is a bribe (say, if, the director is in the process of deciding who gets a large bonus or pay rise). In addition, Westphal pointed out that long-term shareholders could lose out if the favour-rendering affects their long-term investments. Therefore, some instances of impression management are ethically questionable. However, does this necessarily have to be the case: do these strategies necessarily have to be deployed in an unethical manner? In the Table 1 examples, Gertrude could spend the extra time actually working, and therefore deploy the strategy of exemplification without deceiving her supervisors. Samson could deal with his situation by using a different type of ingratiation. Rather than choosing the deceptive strategy of transforming disagreement into agreement (when in fact he strongly disagrees with his project manager’s plan), he can choose the strategy of ingratiation through flattery whilst sticking to his disagreement. Samson can therefore think of genuine compliments to relay to his project manager, relay them, and then thoughtfully explain why he disagrees with the marketing plan. Head chef Rachel could fulfil
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her impression management goal of gaining her juniors’ respect without deploying the strategy of intimidation in the way that she did. Instead, Rachel could still adapt an aloof, formal demeanour, sternly criticising the food rather than criticising a junior chef’s character, and therefore adapting the strategy of intimidation without putting her staff’s mental wellbeing in jeopardy. Likewise, rather than deceiving herself about the impact of her articles on her newspaper’s sales, Martha could solicit genuine feedback about her articles and base an impression management strategy on that feedback.
Further Research Questions Having integrated knowledge from different disciplines (e.g. applied psychology, management, human resources), it is important for this knowledge to be utilised in generating empirical research on impression management in corporate settings. Firstly, during the process of researching this chapter, the author found that most published research articles focus on one or a few of the impression management strategies presented in Table 2. A single psychometric scale measuring all of the strategies (and sub-strategies) presented in Table 2 therefore needs to be developed. Secondly, considering that a new impression management knowledge audit model has been presented in this chapter, it is important to empirically test this model, also ensuring that cross-cultural samples and samples from different types of organizations are used. Thirdly, it is argued that individuals or corporations need to regularly re-run the three steps of the audit in Table 2, based on new knowledge that they acquire, and therefore the process of impression management should be a dynamic process using the audit model as a guidance tool rather than as a prescriptive one. It is argued that employees or corporations that run this knowledge audit should be more successful at impression management than individuals or corporations who do not do so. Therefore, the third important
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further research question should investigate this hypothesis. For instance, it is predicted that expatriates who obtain relevant cross-cultural training should be more successful (in terms of impression management) in their host cultures than expatriates who do not obtain such training. Research should also explore the benefits of cross-cultural training in impression management processes within organizations with employees from different cultures, as well as exploring the interaction between organizational culture and national culture. Empirical investigations of these research questions will be of great value.
CONCLUSION Having compiled a taxonomy of impression management strategies typically used in corporate settings, this chapter explored the role of cultural knowledge on impression management. Cultural knowledge was discussed as something which serves as powerful capital in impression management and as something which concerns both the specific culture of a given organization and the surrounding societal culture. For instance, would-be expatriates wishing to deploy impression management strategies can benefit from establishing a knowledge base about their prospective host culture through attending cross-cultural training. In addition to adjusting for culture, employees or corporations need to adjust their impression management strategy to accommodate the individual characteristics of their target person(s). Therefore, an impression management knowledge audit by employees or corporations should be concerned with acquiring knowledge about not just the psychology of impression management but also cultural adaptation/ flexibility as well as individual differences. Corporations can likewise utilise the knowledge presented in this chapter to maximise their international public relations attempts. Both individual employees and corporations as a whole should consider the ethics of
Strategising Impression Management in Corporations
their chosen impression management tactics and realise that impression management strategies can and should be deployed ethically. One of the further research questions outlined highlighted the need for cross-cultural research testing the benefits of the presented knowledge audit model for employees or corporations using it.
Chang, K., & Lu, L. (2007). Characteristics of organizational culture, stressors and wellbeing: The case of Taiwanese organizations. Journal of Managerial Psychology, 22(6), 549–598. doi:10.1108/02683940710778431
REFERENCES
DePaulo, B. (1992). Nonverbal behaviour and self-presentation. Psychological Bulletin, 111, 203–243. doi:10.1037/0033-2909.111.2.203
Adam, D. (2006). Can planting trees really give you a clear carbon conscience? The Guardian. Retrieved from http://www.guardian.co.uk/ environment/ 2006/oct/07/climatechange.climatechangeenvironment Baumeister, R. F., & Tice, D. M. (1986). Four selves, two motives, and a substitute process self-regulation model. In R. F. Baumeister (Ed.), Public self and private self (pp. 63-74). New York: Springer-Verlag. BBC. (2006). Hypocrisy claim over Cameron bike. Retrieved from http://news.bbc.co.uk/2/hi/ uk_news/politics/4953922.stm Berry, J. W. (2001). A psychology of immigration. The Journal of Social Issues, 57(3), 615–631. doi:10.1111/0022-4537.00231 Capos, C. (2008). The currency of favours (James Westphal interview). Retrieved from http://www. bus.umich.edu/NewsRoom/ArticleDisplay. asp?news_id=12754 Chambon, M. (2005). How to look modest in an organization: Supervisors’ perceptions of subordinates’ account for success. Psychologie du Travail et des Organisations, 11(3), 151–164. doi:10.1016/j.pto.2005.07.003 Chang, H.-C., & Holt, R. (1994). A Chinese perspective on face as inter-relational concern. In S. Ting-Toomey (Ed.), The challenge of facework: Cross-cultural and interpersonal issues. Albany, NY: State University of New York.
Coca Cola. (2008). Regional and local foundations. Retrieved from http://www.thecoca-colacompany.com/citizenship/foundation_local.html
Drory, A., & Zaidman, N. (2007). Impression management behaviour: Effects of the organizational system. Journal of Managerial Psychology, 22(3), 290–308. doi:10.1108/02683940710733106 Eckhardt, G. M., & Houston, M. J. (2002). Cultural paradoxes reflected in brand meaning: McDonald’s in Shanghai, China. Journal of International Marketing, 10(2), 68–82. doi:10.1509/ jimk.10.2.68.19532 Ekman, P., & Davidson, J. (Eds.). (1994). The nature of emotion: Fundamental questions. New York: Oxford University Press. Ekman, P., & Friesen, W. V. (1971). Constants across cultures in the face and emotion. Journal of Personality and Social Psychology, 17, 124–129. doi:10.1037/h0030377 Fairtrade Foundation. (2008). About fairtrade towns. Retrieved from http://www.fairtrade.org. uk/get_involved/campaigns/fairtrade_towns/ about_fairtrade_towns.aspx Friedman, T. L. (1999). The Lexus and the olive tree. New York: Farrar, Straus and Giroux. Gangestad, S. W., & Snyder, M. (2000). Selfmonitoring: Appraisal and reappraisal. Psychological Bulletin, 126, 530–555. doi:10.1037/00332909.126.4.530
1727
Strategising Impression Management in Corporations
Giddens, A. (2006). We should ditch the green movement: The climate change debate is too important to be left in the hands of those who are hostile to science and technology. The Guardian. Retrieved from http://www.guardian.co.uk/commentisfree/2006/nov/01/post561 Gordon, R. A. (1996). Impact of ingratiation on judgments and evaluations: A meta-analytic investigation. Journal of Personality and Social Psychology, 71(1), 54–70. doi:10.1037/00223514.71.1.54 Granose, C. S. (2007). Gender differences in career perceptions in the people’s republic of China. Career Development International, 12(1), 9–14. doi:10.1108/13620430710724802 Green Marketing Conference. (2008). Grange City Hotel. Retrieved from http://www.haymarketevents.com/conferenceDetail/278 Hocking, J. B., Brown, M., & Harzing, A. (2007). Balancing global and local strategic contexts: Expatriate knowledge transfer, applications, and learning within a transnational organization. Human Resource Management, 46(4), 513–533. doi:10.1002/hrm.20180 Hofstede, G. (1980). Culture’s consequences: International differences in work-related values. Beverly Hills, CA: Sage Publications. Hollander, E. P. (1958). Conformity, status, and idiosyncrasy credit. Psychological Review, 65, 117–127. doi:10.1037/h0042501 HSBC. (2008). Global website. Retrieved from http://www.hsbc.com Jackson, C., Colquitt, J. A., Wesson, M., & ZapataPhelan, C. (2006). Psychological collectivism: A measurement validation and linkage to group member performance. The Journal of Applied Psychology, 91(4), 884–899. doi:10.1037/00219010.91.4.884
1728
Johnson, V., & Peppas, S. C. (2003). Crisis management in Belgium: The case of Coca Cola. Corporate Communications: An International Journal, 8(1), 18–22. doi:10.1108/13563280310458885 Kurman, J. (2001). Self-enhancement: Is it restricted to individualistic cultures? Personality and Social Psychology Bulletin, 27(12), 1705–1716. doi:10.1177/01461672012712013 Leary, M. R., & Kowalski, R. M. (1990). Impression management: A literature review and two-component model. Psychological Bulletin, 107(1), 34–47. doi:10.1037/0033-2909.107.1.34 Leigh, T. W., & Summers, J. O. (2002). An initial evaluation of industrial buyers’ impressions of salespersons’ nonverbal cues. Journal of Personal Selling & Sales Management, 22(1), 41–53. Liden, R. C., & Mitchell, T. R. (1988). Ingratiatory behaviour in organizational settings. Academy of Management Review, 13, 572–587. doi:10.2307/258376 Liu, X., & Shaffer, M. (2005). An investigation of expatriate adjustment and performance: a social capital perspective. International Journal of Cross Cultural Management, 5(3), 235–254. doi:10.1177/1470595805058411 Markus, H. R., & Kitayama, S. (1991). Culture and the self: Implications for cognition, emotion, and motivation. Psychological Review, 98, 224–253. doi:10.1037/0033-295X.98.2.224 Montepare, J. M., & Zebrowitz-McArthur, L. A. (1988). Impressions of people created by age-related qualities of their gaits. Journal of Personality and Social Psychology, 55, 547–556. doi:10.1037/0022-3514.55.4.547 Moore, F. (2006). Strategy, power and negotiation: Social control and expatriate managers in a German multinational corporation. International Journal of Human Resource Management, 17(3), 399–413. doi:10.1080/09585190500521359
Strategising Impression Management in Corporations
News, B. B. C. (2003a). India to test Coca-Cola sludge. Retrieved from http://news.bbc.co.uk/2/ hi/south_asia/3133259.stm News, B. B. C. (2003b). Indian colas ‘not unsafe’. Retrieved from http://news.bbc.co.uk/2/hi/ south_asia/3126519.stm News, B. B. C. (2004). Coke recalls controversial water. Retrieved from http://news.bbc.co.uk/1/hi/ business/3550063.stm News, B. B. C. (2005). Indian Coca-Cola protest to go on. Retrieved from http://news.bbc.co.uk/1/ hi/world/south_asia/4603511.stm Oliver, M. (2005). McLibel. The Guardian. Retrieved from http://www.guardian.co.uk/ news/2005/feb/15/food.foodanddrink Palmer, R. J., Welker, R. B., Campbell, T. L., & Magner, N. R. (2001). Examining the impression management orientation of managers. Journal of Managerial Psychology, 16(1), 35–49. doi:10.1108/02683940110366588 Parkes, L. P., Bochner, S., & Schneider, S. K. (2001). Person-organisation fit across cultures: An empirical investigation of individualism and collectivism. Applied Psychology: An International Review, 50(1), 81–108. doi:10.1111/14640597.00049 Paulhus, D. (1982). Individual differences, self presentation and cognitive dissonance: Their concurrent operation in forced compliance. Journal of Personality and Social Psychology, 43(4), 838–852. doi:10.1037/0022-3514.43.4.838 Peltokorpi, V. (2006). Japanese organizational behaviour in Nordic subsidiaries: A Nordic expatriate perspective. Employee Relations, 28(2), 103–118. doi:10.1108/01425450610639347 Pires, G., Stanton, J., & Ostenfeld, S. (2006). Improving expatriate adjustment and effectiveness in ethnically diverse countries: Marketing insights. Cross Cultural Management, 13(2), 156–170. doi:10.1108/13527600610662339
Rao, A., Schmidt, S. M., & Murray, L. H. (1995). Upward impression management: Goals, influence strategies, and consequences. Human Relations, 48, 147–167. doi:10.1177/001872679504800203 Reuters. (2007). Prince Charles shows of smaller carbon footprint. Retrieved from http:// www.reuters.com/article/environmentNews/ idUSL2691546320070626 Richardson, J., & McKenna, S. (2006). Exploring relationships with home and host countries: A study of self-directed expatriates. Cross Cultural Management, 13(1), 6–22. doi:10.1108/13527600610643448 Rosenfeld, P., Giacalone, R. A., & Riordan, C. A. (1995). Impression management in organizations: Theory, measurement, practice. London: Routledge. Schlenker, B. R. (1980). Impression management: The self-concept, social identity, and interpersonal relations. Monterey, CA: Brooks/Cole. Schmidt, S. M., & Kipnis, D. (1984). Managers’ pursuit of individual and organizational goals. Human Relations, 37, 781–794. doi:10.1177/001872678403701001 Selmer, J. (2006). Adjustment of business expatriates in greater China: A strategic perspective. International Journal of Human Resource Management, 17(12), 1994–2008. Selmer, J., Chiu, R. K., & Shenkar, O. (2007). Cultural distance asymmetry in expatriate adjustment. Cross Cultural Management, 14(2), 150–160. doi:10.1108/13527600710745750 Shaffer, M. A., Harrison, D. A., Gregersen, H., Black, J. S., & Ferzandi, L. A. (2006). You can take it with you: Individual differences and expatriate effectiveness. The Journal of Applied Psychology, 91(1), 109–125. doi:10.1037/0021-9010.91.1.109
1729
Strategising Impression Management in Corporations
Shahnawaz, M. G., & Bala, M. (2007). Exploring individualism-collectivism in young employees of new organizations. Journal of Indian Psychology, 25(1-2), 24–40.
Thornton, B., Audesse, R. J., Ryckman, R. M., & Burckle, M. J. (2006). Playing dumb and knowing it all: Two sides of an impression management coin. Individual Differences Research, 4(1), 37–45.
Shimanoff, S. B. (1994). Gender perspectives on facework: Simplistic stereotypes vs. complex realities. In S. Ting-Toomey (Ed.), The challenge of facework: Cross-cultural and interpersonal issues (pp. 159-207). Albany, NY: State University of New York Press.
Tian, Y. (2006). Communicating with local publics: A case study of Coca Cola’s Chinese website. Corporate Communications: An International Journal, 11(1), 13–22. doi:10.1108/13563280610643516
Shimoni, T., Ronen, S., & Roziner, I. (2005). Predicting expatriate adjustment: Israel as a host country. International Journal of Cross Cultural Management, 5(3), 293–312. doi:10.1177/1470595805060812 Silverthorne, C. P. (2005). Organizational psychology in cross-cultural perspective. New York: New York University Press. Snyder, M. (1974). Self-monitoring of expressive behaviour. Journal of Personality and Social Psychology, 30(4), 526–537. doi:10.1037/h0037039 Spurlock, M. (Director). (2004). Supersize me [Motion picture]. USA: Samuel Goldwyn Films. Sriramesh, K., & Vercic, D. (2001). International public relations: A framework for future research. Journal of Communication Management, 6(2), 103–117. doi:10.1108/13632540210806973 Stahl, G. K., & Caligiuri, P. (2005). The effectiveness of expatriate coping strategies: The moderating role of cultural distance, position level, and time on the international assignment. The Journal of Applied Psychology, 90(4), 603–615. doi:10.1037/0021-9010.90.4.603 Telegraph. (2008). Green grows the value so when you go eco-friendly. Retrieved from http:// www.telegraph.co.uk/property/main.jhtml?xml=/ property/2004/06/26/prgre26.xml
1730
Timmerman, G., & Bajema, C. (1999). Incidence and methodology in sexual harassment research in northwest Europe. Women’s Studies International Forum, 22(6), 673–681. doi:10.1016/S02775395(99)00076-X Ting-Toomey, S. (Ed.). (1994). The challenge of facework: Cross-cultural and interpersonal issues. Albany, NY: State University of New York. Triandis, H. C. (1989). The self and social behaviour in differing cultural contexts. Psychological Review, 96, 506–520. doi:10.1037/0033295X.96.3.506 Triandis, H. C., & Gelfand, M. (1998). Converging measurement of horizontal and vertical individualism and collectivism. Journal of Personality and Social Psychology, 74, 118–128. doi:10.1037/0022-3514.74.1.118 Vilela, B. B., González, J. A. V., Ferrín, P. F., & del Río Araújo, M. L. (2007). Impression management tactics and affective context: Influence on sales performance appraisal. European Journal of Marketing, 41(5-6), 624–639. doi:10.1108/03090560710737651 Vonk, R. (1998). The slime effect: Suspicion and dislike of likeable behaviour toward superiors. Journal of Personality and Social Psychology, 74(4), 849–864. doi:10.1037/0022-3514.74.4.849 Vonk, R. (2002). Self-serving interpretations of flattery: Why ingratiation works. Journal of Personality and Social Psychology, 82(4), 515–526. doi:10.1037/0022-3514.82.4.515
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Wayne, S. J., & Liden, R. C. (1995). Effects of impression management on performance ratings: A longitudinal study. Academy of Management Journal. Special Issue: Intra- and Interorganizational Cooperation, 38(1), 232-260. Westphal, J. D., & Stern, I. (2006). The other pathway to the boardroom: Interpersonal influence behaviour as a substitute for elite credentials and majority status in obtaining board appointments. Administrative Science Quarterly, 51(2), 169–204. doi:10.2189/asqu.51.2.169
Westphal, J. D., & Stern, I. (2007). Flattery will get you everywhere (especially if you are a male Caucasian): How ingratiation, boardroom behaviour, and demographic minority status affect additional board appointments at U.S. companies. Academy of Management Journal, 50(2), 267–288. Yamazaki, Y., & Kayes, D. C. (2007). Expatriate learning: Exploring how Japanese managers adapt in the United States. International Journal of Human Resource Management, 18(8), 1373–1395. Zukin, S., & Maguire, J. S. (2004). Consumers and consumption. Annual Review of Sociology, 30, 173–197. doi:10.1146/annurev. soc.30.012703.110553
This work was previously published in Cultural Implications of Knowledge Sharing, Management and Transfer: Identifying Competitive Advantage, edited by Deogratias Harorimana, pp. 60-83, copyright 2010 by Information Science Reference (an imprint of IGI Global).
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Chapter 6.10
Agile Alignment of Enterprise Execution Capabilities with Strategy Daniel Worden RuleSmith Corporation, Canada
ABSTRACT Emergent strategy provides for both planned and reactive aspects of strategic planning. It also identifies that strategy as implemented will often have different characteristics than originally anticipated. Today, even traditional, non-knowledge based organizations have adopted comparatively high levels of computerization compared to a decade ago. Enterprises now rely extensively on digital systems for data handling across operational and administrative processes. This chapter DOI: 10.4018/978-1-60960-587-2.ch610
maintains that detection and reporting capabilities inherent in information technology (IT) can themselves be exploited as a strategy for managing knowledge. Using feedback loops to describe the dynamics of systems lets an organization capture and communicate intended strategy and emergent characteristics of the actual strategy along with changes in the execution environment. The role of IT as an execution capability required for both business strategy and knowledge management is examined, along with the need to more quickly align the business processes that use IT services to changes in business strategies or priorities. Advances in IT assisting in requirements discovery,
Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
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system design and development- including use cases, patterns, decision modeling, and aspectoriented software-are discussed. Techniques to capture and communicate knowledge vital for aligning organizational capabilities with emerging strategies and competing priorities are evaluated. A predicted emergent business pattern as a tool for managing the capture and communication of organizational knowledge is proposed. This includes techniques for defining strategy and decision elements as data about processes that can be used during execution to trigger notification and appropriate handling of exceptional events.
INTRODUCTION Knowledge management strategies require effective execution to be successful. Over time, information technology has become a de facto repository for organization knowledge, in the form of business rules and data integrity constraints expressed as computer programs. IT is a requirement for successful execution of a knowledge management strategy. Even while information systems have become increasingly pervasive across organizations of all sizes and types, their ability to capture and convey knowledge elements has generally been secondary to their intended utility in processing data. In many cases, these systems are deemed inflexible, expensive to enhance or worse. As much as organizations have come to rely on information technology to enable their knowledge strategies, change to the computing infrastructure, or the introduction of new systems to support knowledge management carries significant risk. Many enterprises have launched IT initiatives that have failed completely (Santa, Ferrer & Pun, 2007). Recent innovations in information technology and techniques offer valuable new ways to use information technology to collect and communi-
cate knowledge across organizational lines and functions, while reducing that risk. The Predicted-Emergent pattern captures a context and motivation for any organizational endeavor, describing both the planned for and actual events that occur. Advanced separation of concerns is used to define relevant scope for each activity. These activities include strategic planning and course correction, and progress through levels of detail down to business process definition and decision management. These in turn can be implemented as adaptive software, which establish thresholds for action and notification through operational parameters. This approach pulls the discussion of IT solution elements into earlier phases in the organizational planning process. Incorporating a predictedemergent knowledge management strategy allows the enterprise to more accurately assess events as the plan unfolds, and to communicate priorities more quickly. The net effect is faster reaction and shorter implementation times with the ability to capture significant new knowledge as it arises from organizational experience. The predicted-emergent approach to knowledge management strategy seeks to enable an agile alignment between enterprise planning and operational systems. The legacy of traditional systems has given rise to hardened silos of computing, with inflexible data structures, complex program logic, scattered business rules and standard reports designed to serve a fixed set of organizational requirements. This gap between expectations for and delivery of information system affects and is affected by knowledge management practices. Given that IT frequently fails to deliver basic business operations support, it should come as no surprise that a gap exists between implemented systems and their capabilities for the management of institutional knowledge. That there is a lack of alignment between information technology departments and enterprise strategies is not a new observation (Chan, Huff &
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Copeland, 1998). Nor is the notion that IT can and should be an integral part of realized corporate business and knowledge management strategies (Henderson & Venkatraman, 1992). Achieving the goal of pulling those systems into tighter alignment with needs for knowledge management and adaptive organizational strategies lies in the first part with those responsible for defining system requirements. If the lack of alignment between operational information systems and business strategy is the problem, a solution can be found in creating a faster, more accurate feedback loop between planning and execution. Many IT practitioners have already identified this as an area of focus for their own strategies. That community often refers to the process by the jargon term - agility. This chapter introduces several techniques that have emerged as part of research and practice of information technology and computer science. These practices have relevance to knowledge management strategies; particularly in support of capture and communication of both requirements and capabilities.
The discussion of techniques and approaches begins with the gathering of requirements to describe the problem domain. Enterprise business and knowledge management strategies are considered included in those requirements. As part of the expression of business requirements, however, several innovative architectural notions from software development will be introduced. The value of expressing the problem within the framework of how the solutions are developed will be considered. This chapter will describe the linkage of business processes with their operational context as well as how meta-data about the process can be defined, collected and acted upon as part of a dynamic loop, as shown in Figure 1. The goal is to outline a set of steps for containing business planning and process models into descriptions grouped by relevant level of detail for both business process owners and solution developers.
Strategic Feedback Every strategy admits of both assumptions and a lack of certain foreknowledge of events yet to
Figure 1. A predicted-emergent feedback loop for business strategies
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occur. Plans have within them the seeds of achievement and disappointment in similar measure. In keeping with this reality is the need to continually inform business development strategies with events as they actually unfold and the situation as actually exists. Knowledge of these things is a strategic advantage, as it allows an organization to change, refine or bolster a given plan based on how well the assumptions are validated and the ability of the organization to address unanticipated issues that arise. This combination of top-down strategy and bottom-up status reporting creates a feedback loop and represents a dynamic between the planned and the discovered. A systems dynamics model of the overall flow is shown in Figure 1. The diagram depicts the role of the knowledgebase (KB) as central to deriving predictions or making strategic assumptions as well as collecting event information to populate the knowledge base with data. Predictions are essentially known unknowns, with probabilistic values supplied for purposes of decision-making. Detected events are added to the KB as either predicted or unpredicted. Additionally, the diagram shows that there is a class of event that goes undetected and correspondingly uncollected within the knowledgebase. Unpredicted events may occur but remain undetected for some period of time. Agile alignment as a strategy emphasizes the role of event detection to improve predictions or expose areas for strategic evaluation. Ranges for probable values defined as part of predictions is a key way to ensure the pattern translates into a specification for usable systems dynamics model. By setting minimum and maximum ranges various scenarios can be simulated to determine the effect on other elements in the system.
Describing the Problem to be Solved There are few truly ‘green field’ opportunities to define business strategies, plans and projects from scratch. Generally, some version of the activity or
system is already in use. In keeping with this reality, assume that some knowledge about the systems and processes will already exist. What is needed then is a strategy for capturing this knowledge in a manner that will make it more suitable for inclusion in enterprise planning and operation. Use cases have become a commonly used mechanism to capture business requirements and describe systems behaviors. Arising from early software development methodology efforts, they are an example of the practical value IT innovators can provide to business users and management through systems tools and techniques. Clearly, use case models are not in and of themselves sufficient to define a given organizational problem, but in combination with process models, business plans and budgets, the user view of the problem can be explained this way. Use case descriptions typically incorporate step-by-step flows of user-system interaction through ‘as-is’ and ‘to-be’ versions of the organizations behavior. Use cases are a vitally important tool for the capture of knowledge management, though some care must be paid in how the use cases narratives are structured in order to optimize their applicability to knowledge management in practice. With the formulation of a use case based approach to requirements gathering, many software project members believe they are effectively capturing ‘real’ business requirements. However, too often the effort bogs down in degree of detail – either too high or too light – and in an attempt to capture every scenario imaginable. Employing use case descriptions supports the agile, iterative development process, allowing the design and development to flesh out detail as it is discovered. More important, the focus is on defining what is known and how to handle all other events – whatever they may be- as they arise. Accordingly, capturing all possible scenarios is less important than defining the foreseeable (predictable) states of a process, and identifying
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the acceptable parameters within which it may operate effectively. Once the business defines these parameterized processes, the exception handling procedures of an emergent event means that software developers can reasonably rely on coding only those cases that are explicitly specified. They can also ensure those parameters are accessible and modifiable by business users of the software rather than requiring re-coding. By pulling the definition of exception handling up into the earliest efforts of the requirements gathering, processes can be formalized, reviewed and revised as needed. Test cases that reflect exception handling can be derived concurrently with the use case effort. Programmers can then focus their efforts on automating well-defined scenarios, while throwing all others, predicted or not, into the exception handling processes defined as acceptable to the business. This offers the promise of increased quality of the delivered product (by alleviating programmers requirement to guess at how the system should behave) as well as making the system more responsive to changes in thresholds, which are administered by those closest to the systems use, specifically the business (Alexander, 2004).
A Strategic Context Use cases are a relatively low-level artifact within an enterprise knowledge system. Frequently they deal with detail at the process and function level. The motivation of the business for the project or process sponsoring the use cases will be taken as an input or an assumption. However, as a function of their ability to convey ‘as-is and ‘to-be’states, Use cases provide a vehicle to capture current capabilities (or challenges) of the current environment to planners, and also to communicate strategic goals or priorities to mid level operations resources.
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EMERGENT STRATEGY Organizational strategies may be deliberate or emergent (Mintzberg & Waters, 1985). The classic vision of the senior leader devising a brilliant plan for the way ahead is the epitome of a deliberate strategy. In contrast the emergent strategy is one that arises out of experience. It is this capture and dissemination of experience that is most relevant to knowledge management. Decision makers and business planners are a key user and constituency of knowledge management systems. They depend on the collection and communication of relevant, timely information that describes the status of the organization and changes in the environment in which it operates. That information can be aggregated into repeatable patterns that form the basis for organizational knowledge. However, this tends not to happen effectively when relied on to occur spontaneously. Part of the difficulty in creating a learning organization that adapts to its environment as changed circumstances or incorrect assumptions are encountered is the human tendency to avoid communicating ‘bad news.’ The recommended approach to defining exceptions and notification parameters as part of use cases definitions is one way to de-politicize that communication. Where intended strategy is the deliberate plan, emergent strategy is the plan as realized or implemented. Success is a function of how well and how quickly variances between the two can be identified and reconciled. The intent of this chapter is to provide specific techniques that can be used to better employ use cases and emergent strategy in knowledge management efforts. One of the techniques that support overlaying business process definition and use cases with strategies for enhancing institutional knowledge management is to separate the concerns.
Agile Alignment of Enterprise Execution Capabilities with Strategy
Advanced Separation of Concerns In software engineering, the separation of concerns is a principle that allows complexity to be restricted to a certain number of elements related by a given context or purpose (Dijkstra, 1976). The problem and solution domains represented by the business users and IT solution providers can be taken as one example of two separate concerns. Integrating those two is another concern in its own right. Concerns may be separated into level of detail, for instance where both the problem and solution definitions are being addressed within a single iteration during an agile development project, or along a chain of related processes, as part of an operational or planning exercise. The separation may also occur dynamically as a concern arises, from an audit for example or as non-compliance with a new regulation. One of the knowledge management strategies advocated in this chapter is to identify knowledge management concerns. Each of these can be rooted in current practice or systems, from which the realized strategy may emerge for validation or review. Alternately, a change in overall direction or priority may be a deliberate strategy that requires implementation to be made effective. The technique for defining specific processes to be handled by a system and raising exceptions is another example of applying the principle of separation of concerns. By doing so deliberately, the requirements express not only precisely what the process is intended to achieve, but also a mechanism for handling all exceptions that occur outside those pre-defined thresholds. These are the parameterized processes set by the business. Use cases that reflect these requirements capture the business intent and also better enable the allocation of implementation work to specialists. One resource with suitable background and knowledge to handle the active process can be assigned to requirements, design or programming as appropriate. Others may be given the task of detecting and handling the exceptions.
While business focused practitioners will not be burdened with having to understand the solution design internals, software architects will realize this promotes both agile, iterative development and also sets the stage for an aspect oriented (Kiczales, et al., 1997) solution to be developed.
Knowledge Management Aspects To this point communication has run from leadership to operational resources and back, and from business users to coders, however, knowledge management concerns are not necessarily hierarchical. In identifying separate concerns, it is also possible to intersect those concerns with an additional concern. A learning organization may identify a concern for knowledge capture and consolidation into a specified knowledgebase. Given that exception handling is its own concern, so too would this acquisition of knowledge elements. But where an exception handling process might be common to some number, or unique to a single process, knowledge acquisition will cut across a number of processes and domains. It becomes a crosscutting concern or aspect of the system. Put another way, a knowledge system may not simply exist separate and apart from an operational system. Knowledge systems can also be constructed as aspects of all other systems, with their own unique set of elements included as part of its own knowledge management concern, co-existing with the operational systems in use within the enterprise. The useful computer science innovation that applies here is AOSD, Aspect Oriented Software Development. Building on the use case definition technique described in this chapter, a knowledge management aspect could be considered to be the requirement for a KM practitioner to be notified of previously un-encountered exceptions, so they can be reviewed for severity, catalogued and handled as predicted scenarios as appropriate.
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This approach may prove less technically demanding than might be feared. Trends in software development have been leading towards an emphasis on discovery over rigidly defined specifications. This is consistent with the needs of emergent strategy, as it reflects the reality that environments change, as does knowledge of that change, and it can be used to support organizational learning. Agility in IT terms can become synonymous with enterprise adaptability, enabled by an aspect oriented knowledge management strategy.
ADVICE FOR UN-TANGLING AND UN-SCATTERING Using aspects as a fundamental approach to segregating systems concerns was intended to solve a particular problem that arises in object-oriented approaches to software development. As objects are defined as methods or operations that occur on specific data, those operations can be required on many different data sets throughout an information system. As a result, the operations become scattered across the code and the business models used to depict the processes and software solution. Additionally, certain concerns, such as exception handling, cut across many other concerns and so become tangled up with other concerns such as business logic and operational rules. Where a use case involves several systems components it can be considered to be subject to scattering, and where a component is invoked by several use cases it may be considered to be entangled. The mechanism used in AOSD to encapsulate crosscutting aspects is called ‘advice’. Advice is of particular interest in the context of knowledge management practice. As described earlier, to achieve separation of concerns in software solutions, it is a great benefit to define them as part of requirements. Use cases support this defined separation, but do not force it. By defining and naming certain functions, such as exception handling, or notification as Advice, use cases may
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simply refer to the function to be called without bogging the effort down in explaining the detailed implementation of the procedure. Emergent strategy provides a way to capture the differences between strategy and plans as implemented when compared to their original intent. Use cases provide a way to document business requirements that can be used to describe systems to implement solutions for meeting those requirements. Aspects provide a way to separate the concerns into manageable modules and to navigate both the requirements and software solutions along the path relevant to a given purpose.
RE-USE THROUGH PATTERN LANGUAGE With their 1995 book Design Patterns: Elements of Reusable Object-Oriented Software by Erich Gamma, Richard Helm, Ralph Johnson, and John Vlissides (the famous Gang of Four or GoF) translated the architectural concept of Patterns to software design. Their work was inspired by another book, that of an Architect Christopher Alexander – Towns, Buildings, Construction – A Pattern Language. Through their combined insight, design problems and aspects of their solutions can be more efficiently abstracted and communicated from one setting to another. Design patterns are by definition constituent elements of a solution. These patterns inform the construction of a software solution. The extent to which that solution addresses specific problems depends on how well the design pattern fits within the target problem domain. The solutions as built will only accidentally address the problem better than it was designed to do. As well as introducing design patterns to the software industry, the GoF went on to create the Unified Modeling Language (UML) and the Rational Unified Process (RUP) for requirements discovery and software development. Their original focus was primarily on the optimal engineering
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of software solutions. There was somewhat less emphasis on establishing the context in which the solution fits until Jacobson brought his use case emphasis with him when he joined the group in 1995. A subset of these tools and techniques are applicable to knowledge management systems, particularly some of the patterns for describing problems and solutions.
PATTERNS USAGE IN KNOWLEDGE MANAGEMENT Design patterns and pattern language have influenced the Information Technology community for more than a decade. The applicability of these concepts, approaches and tools to a knowledge management environment may be less common (Hughes, 2006). One dictionary definition of the work ‘Pattern’ is as follows: Anything used as a model or guide for something to be fashioned or made (Dictionary.com, n.d.).As an information or knowledge management system is something to be fashioned or made, it would seem to follow that patterns for the creation of effective solutions should be available. This general definition of the term has been made much more specific as applied to the creation of software solutions. However, the emphasis in this chapter is not solely on the construction of solutions, but rather on the setting of the overall and on-going context in which software solutions must fit. A pattern language for business concepts, including an enterprise architecture that encompasses its requirements and IT services, is delineated as part of the IBM Enterprise Solutions Structure (McDavid, n.d.). This approach uses patterns to describe situations where IT solutions fill a role. One benefit of this approach is apportioning of the business functions with human and computing resources are intertwined but still contained within discrete blocks. Consistent with advanced
separation of concerns, this approach segregates the functions allowing detailed design for both the problem and solution domains while containing the scope into a discrete and manageable size. The intent behind pattern language was to communicate applicable considerations from one environment to another. As such it is highly suited to adoption as part of a knowledge management strategy. This chapter advocates that pattern descriptions for software solutions be pulled into the requirements definition phase of information systems projects, through the vehicle of use case descriptions. By applying aspect-oriented labels to organizational functions within business processes described during use case development, an optimized level of modularization can be achieved. This modularization contains both requirements and systems support and lends itself to agile and iterative implementation. In turn, this agile approach supports emergent strategies for knowledge management. The key to successfully applying these patterns is defining the controlling context.
ESTABLISHING CONTEXT The purpose or goal of any given effort informs all aspects and subsequent implications arising from the endeavor. Decisions regarding priority, resource allocation, scheduling, approval or deferment are frequently the result of comparing the purpose and impact of one endeavor against another. Every initiative, product, project, campaign or event, has presumably only been launched after at least an informal cost-benefit analysis to define its operating parameters. The initiators often understand the desired outcomes but that definition can become lost to the downstream operators and managers of the tasks required to accomplish it. Additionally, the initiators are aware of the factors under which the endeavor is viable. The states of these factors may change over time.
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Knowledge management systems seek to capture and communicate these descriptors but the challenge remains to present a complete subset of data associated with the descriptors that is relevant to a given audience at the point in time they seek it. Meta-data, often summed up as data about data, includes the descriptions of factors and their states. Here the interest is in capturing those factors and states as they were when the endeavor was evaluated and determined to be viable. At the highest level, the context for an organization can be defined by its mission and boundaries which consist of resources and constraints (Wernerfelt, 1984). The predictive aspect is expressed in strategies, plans, budgets and other forms of defining direction. Environmental issues, such as regulatory compliance requirements or market conditions represent additional constraints on any viable effort. The IT definition of pattern languages for systems solutions is a necessary part but insuffi-
cient to completely describe all of the concerns an organization must address as part of its on-going existence. Similarly, there is no one modeling technique, unified or otherwise, that fully describes the environment, financial implications, business strategy, priorities and other aspects of the problem domain as used by members of any given enterprise. An overlapping, intersecting and collaborating set of concerns is depicted in Figure 2. Where IT may maintain object and data models, data dictionaries and flows, operations might be the owner of business process models. Finance views the enterprise in terms of dollars and cents, balance sheets, income statements and cash flow models while leadership often expresses its direction through narrative business plans. The artifacts generated by each of these constituents are valid within the confines of their own purposes, and frequently might be inputs, outputs or both to the other organizational members.
Figure 2. Dimensions of organizational concerns (Ossher & Tarr, n.d.)
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When attempting to create a catalog or model for knowledge of both problems and solutions across the enterprise as a whole, the difficulty of managing dynamic changes with static models arises. It is here that a pattern for depicting predictedemergent events offers assistance.
BOXING UP THE MODELS The first step in aligning the systems solution to a given organizational problem is to isolate what is known. The key consideration for relevance is defined by the endeavor under evaluation. It may be as far-reaching as reorganization or a five-year plan. Alternatively, it may be a departmental initiative. The approach to application of the predicted-emergent pattern related to knowledge management scales in either direction. As the scope of the endeavor moves towards operational and focused efforts, only the level of detail needs to change. Implementation of a new Financial System (for example) may be only mildly informed by the enterprise mission statement, but to be successful the project requires a plan that addresses the applicable constraints. The relationship of these elements is depicted in Figure 3. This simple diagram is a visual reminder that, for any initiative, both the plan and constraints must be identified. While the diagram is static, it should be noted that not all constraints are known Figure 3. Endeavor context step with predictive and emergent elements
at the time of initiation, accordingly constraints may emerge and the plan must be updated to reflect those constraints. This is a usual function of project management, but attention should be paid to how emerging constraints will be captured and communicated. At this stage, it is sufficient to ensure that for the particular endeavor, all planning artifacts and known constraints have been identified. Where knowledge management systems provide a catalog of knowledge assets to their internal users, endeavor contexts for particular projects or initiatives could be linked by name to the published plans, budgets and risk assessment documents. Such referencing of models across organizational functions can be promoted as a knowledge management specific service, providing clear value to all participants. Equally valuable is the assignment of responsibility for updating the catalog to reflect emergent constraints and potential impact on plans.
BUSINESS MOTIVATION From a Predicted/Emergent perspective, the business motivation expresses the goals of the plan and incorporates the priorities already set. Of course, business motivation can cut across a number of areas, depending on the nature of the initiative. For that reason, motivation depends on establishing the context for the endeavor. This is shown in Figure 4. In this slightly more complex depiction, the business motivation applies to a specific endeavor. As already discussed, the endeavor might be as large as the organizations existence or a much smaller, focused initiative. In either case, the predictive aspect includes a plan with specific objectives, and an emergent aspect that allows for priorities to be realigned as the constraints that apply to the endeavor become apparent as the plan unfolds.
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Figure 4. The relationship between endeavor context and business motivation
A useful methodology and notation neutral definition of business motivation has been adopted by the Object Management Group (OMG) as a standard for Business Motivation Modeling (Object Management Group, 2008).
BUSINESS PROCESSES The work of any organization is typically conducted through processes. These may be formal or informal, approved or unapproved. They may be aligned with the organizations overall plan and constraints, or they may operate independently. From a knowledge management perspective, the more clearly understood and consistently operated processes are, the better. The predictive aspects of business processes are the models developed to show them. The emergent aspects are contained in the resources using and used as part of the process. This is shown in relationship with the business motivation and endeavor context in Figure 5. The diagram now shows the relationship between the plan, its objectives and models. These are all related predictive elements for a given
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Figure 5. Business process in context
endeavor. Additionally, we can see that the constraints and priorities that affect resources within processes are all informed by the applicable context and motivation for the larger endeavor the processes support.
DECISIONS With the introduction of The Decision Model (Von Halle, et al., 2009), a compelling case has been made for the segregation of decisions and processes. Similar to the isolation of data from business logic and user interfaces in systems design, decisions are discrete elements of processes that can be reused and shared. Decisions are comprised of rule families that in turn are made up of sets of business rules. From a predicted-emergent perspective, decisions also identify thresholds at which the rules may be triggered. These are set as parameters that are modifiable over time, set by the business to
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Figure 6. Decisions related to their endeavor context, business motivation and processes
Similar to the way in which AOSD supports a reduction in tangling and scattering of software operations, the use of decision modeling allows segregation of decisions from the processes that invoke and consume them. Decisions may be combined with Advice to perform notifications, or they may themselves be invoked as a named Advice where process owners need not have visibility into the rules that makes up the decision.
SEGREGATING DECISION RESOURCES
reflect the constraints and priorities of the current state. The decision definition step is depicted in Figure 6. In this multi-dimensional block diagram, it follows that plans define objectives described in models specifying thresholds. An alternate traversal of the graph describes constraints that result in priorities affecting resources through rules. The most basic set of steps described in the figure show that every endeavor exists in its own context. The motivation for achieving specific outcomes as part of that endeavor informs the processes within the endeavors context, and that decisions taken as part of a process exist as discrete concerns.
It should be noted that some organizational decision models exist in the form of deployed application code. The expertise may not have been formalized as process models or rule diagrams. In some cases, those decisions access other data or processing resources, such as calls to external systems to validate a credit card, for example. One of the advantages of detailing decisions separately from process models is the ability to simplify process models. The decision is not represented as part of the process flow; it can be merely shown as an intrinsic part of the process. The decision becomes, in an aspect-oriented sense, a crosscutting concern. Figure 7 shows how a process diagram could contain decision points without modeling the decision itself. The black diamond inside the process indicates a named decision. Using a software tool, rather than a printed page, the decision resources details can be accessed when relevant. Since the decision might be used by any number of processes, consolidating the depiction this way reduces visual complexity in the process model and also ensures that decisions are not scattered and tangled within the process model. Additionally, decisions for notification or exception handling can be treated as advice during the requirements definition phase. Where such decisions are not well understood, the name can
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Figure 7. A Process containing a named decision (Worden, 2009)
be used as a stub or placeholder and fleshed out later during a subsequent iteration. This technique supports the treatment of knowledge management strategy as a crosscutting concern while enabling an iterative approach to defining requirements, processes and software solutions to address them.
PREDICTED EMERGENT FORCES AND RELATED PATTERNS One of the principal premises of the predicted-emergent pattern is that the quality of delivered software is a direct function of the quality of the requirements definition; too often those who don’t understand what they are building are doing so for those who don’t understand what is needed. The chunking of discrete stages of a project frequently termed ‘the waterfall approach’ to requirements definition and solution specification has long been identified as a major culprit and cause of disappointment (Royce, 1970). While Agile, iterative and spiral methodologies have been proposed as a viable alternative, they have hardly proved the cure-all solution.
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These forces – requirements to integrate computing and business operations more effectively, at less cost and support on-going changes – are not new, but neither have they been resolved. Organizations continue to face these problems regardless of the technologies, hardware or software, and the methodologies, rapid or traditional, they employ. The predicted-emergent pattern addresses these problems by beginning with what is known, and capturing new events so they can be analyzed, classified and converted into new knowledge. This is in stark contrast to a traditional approach to requirements definition, which emphasizes identification of every possible outcome before deeming the requirements ‘complete. With the strategies recommended here, the focus is on decisions, not merely process, on information not data and on usage over technology. The differences are subtle but the implications are remarkable. The predicted-emergent pattern is more a business architecture and an integration pattern than a design pattern. However, as part of the definition of how the predicted-emergent pattern is properly used, other patterns, specifically software design patterns are incorporated. In this
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way, the predicted-emergent pattern allows the linkage of problem definitions and organizational requirements to solution descriptions in the form of software design artifacts. The key to successfully achieving this integration is to focus on detection of emergent events.
DETECTION OF EMERGENT EVENTS Given that the predicted-emergent pattern is a business architecture and integration pattern, it is necessarily described at a higher level of abstraction than a design pattern, such as those put forward by the GoF. The purpose of applying the predicted-emergent technique is to set a context with a contained scope for the application of design patterns as part of a given solution. One such useful design pattern is the Observer pattern. This pattern describes how a resource may identify an interest in a particular state or states of a subject. When that states changes, the observer is notified and subsequent action may be triggered by that notification. A real world example of information as a strategic asset and where the observer pattern is applied can be found in credit history data services. Data aggregators receive notifications of events from credit issuers such as banks and retailers. These transactions report payment amounts and dates, as well as balance and query information to arrive at a credit score. For business decisions that are affected by financial considerations these services often integrate with and form part of the knowledge management systems on which an organization relies.
OBSERVER PATTERN AND THE REPORT BY EXCEPTION PRINCIPLE Within a predicted-emergent approach for knowledge systems, a best practice to be applied when using the observer pattern is to report by excep-
tion. The difference between a report periodically and report only exceptions is relatively slight, but carries significant implications when the requirements are supported by software. A real world example of a report by exception approach to an observed situation can be found when considering the subject of a credit report. As integral as credit ratings are to many transactions, studies have shown 79% of the records have errors of some kind, with 25% of them significant enough to result in a denial of a credit-based application (National Association of State PIRGs, 2004). Even with such a high percentage of error, many people and business do not actively monitor their scores and data on a periodic basis. When an application for credit is denied, however, that exception can trigger a review and correction. Clearly, the traditional approach generates a great deal of data. While it may be relevant if fluctuations of recorded credit scores are the subject of investigation, it can generally be taken to simply be a record of data of no particular relevance where the only consideration is whether the score falls below or above a certain set range. For someone with a good credit rating they may range considerably above the floor level of 720 with no effect on their status. The observer pattern as applied to credit ratings describes the secondary communication of the individuals financial transactions to a third party, in this example, the credit bureaus. As implemented the pattern requires the identification of a triggering event and the third party must be prepared to receive notifications subsequent to activation of the trigger. A report by exception would apply to organizations that decline to share all transaction data, opting instead to report only certain exceptions, such as a closed account. Whether report by exception presents a strategic opportunity to improve data integrity for credit reporting agencies is a matter for experts in that domain to determine. Instances of the observer pattern can be found in many organizations, and
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it is predictable that some of those will benefit from applying the report by exception principle.
OBSERVER PERFORMANCE AND RESOURCE CONSUMPTION The implication to systems people of trapping a value and comparing it to a range is quite different than maintaining an on-going log of values. IT considerations such as file sizes, systems performance and so on are dramatically affected. By opting for the report by exception approach, the parameters representing the acceptable values can be changed without resorting to programming alterations. This means that software so designed is more easily maintained and operated by ‘the business’ where things like the temperature values may need adjustment. Use case definitions for gathering system requirements and describing business-systems interaction have become a common practice under many methodologies. Expressing use cases using the report-by-exception technique becomes a vital component of capturing emergent events at the requirements level and lends itself particularly well to the definition of exception handling concern.
Anti-Patterns in PredictedEmergent Environments Anti-patterns can be thought of as reasonable, attractive approaches to problems that tend to yield poor solutions. Assigning more people to a project that is behind schedule is one example. New people require support to be effective and this tends to take away time available to the project members already assigned. It seems reasonable that more people will result in more work being accomplished in the same period, but overlooking the increased cost of coordination makes this an anti-pattern. The predicted-emergent approach to defining business process parameters and decision ele-
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ments such as rules, exceptions and notifications is one way to structure responses to unanticipated events. This becomes especially valuable when systems automate responses and the elapsed time between encountering the new business situation and responding is immediate. Where the predicted-emergent pattern is applied as a knowledge management strategy, there are two key anti-patterns to avoid. Ascertainment bias describes the tendency for experienced practitioners to discover only what they expect to find. An unwarranted influence describes factors that generate a disproportionate impact during the realization of a strategy. The use of a knowledge base in a predictedemergent context provides opportunities to assess and correct for either ascertainment bias or unwarranted influence. A business process or use case may elect to name a decision or call advice at a particular point in its flow. As a distinct procedure, that decision or advice can include provisions to evaluate its context, constraints, motivation or priorities. That evaluation may or may not be automated. In fact, many decision points in new processes may require human intervention before control is returned to the calling software and its execution resumed. Unwarranted influences are those that have a higher than desired impact on a business process or resource. As shown in the examples, these influences can range from course of dealings and customary practice, to abrupt price changes of inputs. It is neither necessary nor desirable to attempt to predict all influences in advance. Overlaying a predicted-emergent structure on business processes can result in specification of solutions that appropriately trap and handle ANY event that falls outside acceptable predicted ranges. Ascertainment bias refers to the tendency for investigators or analysts to find supporting correlations in data or results consistent with their expectations. Organizational anti-patterns such as GroupThink (Janis, 1972) can create ascertainment bias, where critical appraisal is not raised as a
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direct result of the group dynamic. The predictedemergent loop allows events and actual experience to notify pre-defined monitors as the existence of an anomalous occurrence. Not all ascertainment bias is a result of a failure to speak up or overlooking the obvious. It can also result from a lack of aggregation of knowledge over time.
RESULTS The Business Motivation model of the Object Management Group (OMG1), calls out initiation of any action because of internal or external influence. One pressing problem of business today is to identify acceptable or desirable behaviors as they apply to emergent situations. The key benefit of a quick turnaround in communication to senior managers of relevant new experience and efficiently returned direction is the mitigation of risk. This is an attractive consequence of good knowledge management strategies, effectively implemented and used within an organization. The application of emergent strategy, defined as separate concerns in both requirements and software solutions, accessing named decisions and notifications as explicit aspects of either manual or automated processes, taken as a whole these represent the predicted-emergent pattern for knowledge management. By beginning with what is known, and identifying suitable processes for dealing with any unknown event that arises (as opposed to trying to imagine them all), knowledge management sets the operational context for all business processes. Separation of decisions from processes yields the advantages of specialization. Decisions are not scattered and tangled in the process flows, they are called by name, and the parameters of the decisions can be changed to suit the environment of the day as it emerges. This yields the agility and responsiveness decision makers are looking for in their operations
SUMMARY As this is merely a single chapter, the treatment of emergent strategy, aspect oriented software design, use case development, the rational unified process, pattern language, and decision modeling is necessarily spare. Nevertheless, building on these cornerstone concepts provides a solid basis for an adaptive knowledge management strategy. As a discipline, knowledge management has a pivotal role in assisting practitioners when aligning operations with business goals and priorities. There are several key underpinning contributors to realizing that alignment. Emergent strategy supports the definition of organizational plans in a way that does not rely on omniscience or having all required data in advance. Knowledge management can leverage emergent strategy by encapsulating processes, data and rules into decisions for what is known, and by handling exceptional events appropriately as they arise. Business and design patterns offer a vocabulary and description of reusable practices that can be successfully applied in various settings. These patterns describe effective ways of partitioning the problem and solution domains, as well as the services that link them, into manageable pieces. Agile and adaptive development methodologies use these patterns to support discovery and allow IT to address changes in requirements in a flexible and responsive way. Use cases are an effective way to collect and express both requirements and solution design, especially where wellunderstood scenarios are spelled out in detail, and others are relegated to a separate exception handling process, whether manual or automated. The models and depictions of each concern consume, inform and extend the others. Taken as a whole, the integrated set of models represents an actual knowledgebase of an organization encompassing its operations in all their contexts. Explicit responsibility for creating and maintaining a catalog of these models is a key role for knowledge
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management practitioners and an effective way to provide value across the organization as a whole. Aspect oriented software development capabilities enable IT resources to capture and collect data relevant to an identified set of concerns, as well as to automate business operations to the optimum extent and increase productivity through appropriate specialization. The goal of this chapter was to introduce these approaches and to provide a context for evaluating knowledge acquisition and communication by better exploiting information systems resources. In a predicted-emergent sense, each of these initiatives within information and organizational management has developed from its own impetus. The constructs were predicted as academic exercises to address unexpected problems, and the modeling techniques have emerged in their current forms from actual practice and experience. By taking stock of these capabilities and using them to more fully express business plans, processes, rules and decisions, knowledge management can take an active role in creating adaptive enterprises. It can be predicted that those who do, will emerge the better for it.
REFERENCES Alexander, R. (2004). Aspect-oriented technology and software. Software Quality Journal, 12(2). doi:10.1023/B:SQJO.0000024109.11544.65 Chan, Y. E., Huff, S. L., & Copeland, D. G. (1998). Assessing realized information systems strategy. Strategic Information Systems, 6(4), 273–298. doi:10.1016/S0963-8687(97)00005-X Dictionary.com. (n.d.). Pattern. In Dictionary.com unabridged (v 1.1). Random House, Inc. Retrieved on June 11, 2007, from http://dictionary.reference. com/browse/pattern
Dijkstra, E. W. (1976). A discipline of programming. Prentice Hall. Henderson, J. C., & Venkatraman, N. (1992). Strategic alignment: A model for organizational transformation through information technology. In T.A. Kocham & M. Useem (Eds.), Transforming organizations. New York: Oxford University Press. Hughes. (2006, February). Journal of Usability, 1(2), 76-90. Janis, I. (1972). Victims of GroupThink. Houghton Mifflin. Kiczales, G., Lamping, J., Mendhekar, A., Maeda, C., Lopes, C., Loingtier, J.-M., & Irwin, J. (1997). Aspect-oriented programming. Proceedings of the European Conference on Object-Oriented Programming, 1241, 220–242. McDavid, D. W.(n.d.). A standard for business architecture. IBM Systems Journal, 38(1). Mintzberg, H., & Waters, J. A. (1985). Of strategies, deliberate and emergent. Strategic Management Journal, 6, 257–272. doi:10.1002/ smj.4250060306 National Association of State PIRGs. (2004). Mistakes do happen. Object Management Group. (2008). Business motivation model. OMG document number formal/2008-08-02. Standard document. Retrieved from http://www.omg.org/spec/BMM/1.0/PDF Ossher, H., & Tarr, P. (n.d.). Multi-dimensional separation of concerns and the hyperspace approach. IBM, T.J. Watson Research Center. Royce, W. K. (1970, August). In Proceedings of IEEE Wescon. Santa, R., Ferrer, M., & Pun, D. (2007). Why do enterprise information systems fail to match the reality? USA: ISRST. Von Halle, B., et al. (2009). In Auerbach (Ed.), The decision model.
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Wernerfelt, B. (1984). A resource-based view of the firm. Strategic Management Journal, 5(2), 171–180. doi:10.1002/smj.4250050207 Worden (2009). Making the case for the physical decision. In Auerbach (Ed.), The decision model.
ENDNOTE 1
OMG has been an international, open membership, not-for-profit computer industry consortium since 1989.
This work was previously published in Knowledge Management Strategies for Business Development, edited by Meir Russ, pp. 45-62, copyright 2010 by Business Science Reference (an imprint of IGI Global).
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Governance of Virtual Networks: Case of Living and Virtual Laboratories Brane Semolic University of Maribor, Slovenia Jure Kovac University of Maribor, Slovenia
ABSTRACT Technological and organizational excellence is the key element for business success in a modern business environment. In contemporary business environments, companies will restore and keep their competition capability not only by optimizing their own potentials, but mainly by utilizing capability of foreign resources and their connection to complete business process in the so called network organizations. Virtual organizations are a special form of network organizations. Among virtual organizations the so called Living Laboratory takes place. This chapter presents the findings DOI: 10.4018/978-1-60960-587-2.ch611
of the research regarding the state of development and application of laser living laboratory management and governance system in Toolmakers Cluster of Slovenia.
INTRODUCTION Modern companies are permanently analyzing their business activities and the global market, and are searching for business opportunities to improve the competitive capacities of their own company. New forms of network organization of companies’ business activities are coming to the fore, which organize individual business activities in the regions that from the business viewpoint
Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
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seem favourable with respect to the prices of manpower, special know-how, raw materials etc. Trans-national research, development and production networks are being formed. Their formation and development is influenced by the scope of business environment development of the involved countries, regions, national and regional government rules and regulations, social and cultural conditions etc. The world is becoming a more and more intertwined network consisting of a series of different trans-national networks and specialized economic entities, working in different parts of the world. The urge for the concentration of resources resulted in the creation of network-structured integrations as one of the most appropriate solutions. One of the major features of creating network organizational structures is the integration based on rather loose and temporary association of particular resources in order to obtain the objective of competitive advantage. Virtual network organizations are a special form of network organizations based on the use of modern information and communication technologies and collaboration between different organizations that has similar research and development interests. The mission and concern of the proposed chapter is to present the concepts of the living and virtual laboratories design. Within this framework the problems and theoretical solutions will be presented: •
•
How to design governance and management model for the specific needs of living and virtual laboratories clients; How to start architecture design of living and virtual laboratories.
Described theories are partly illustrated using the case studies from Toolmakers Cluster of Slovenia.
VIRTUAL ORGANIZATION, VIRTUAL LABORATORIES AND LIVING LAB? Most of the existing studies point out that virtual organizations are a temporary consortium of partners from different organizations establishes to fulfill a value-adding task, for example a product or service to a customer (Duin, 2008, p.26). According to Rabelo and Pereira-Klen (2004) virtual organizations are temporary alliances between organizations to share skills or core competencies and resources in order to better respond to new collaboration opportunities (Loss et al., 2008, p.77). This way, virtual organizations represent cooperation between formally non-connected organizations or persons who establish vertical or horizontal links and present themselves to the customers of their products or services as a single association. Apart from the professional literature concerning virtual organizations emphasis is also given to the information and communication technology as well as to the absence of the central control functions. (Mohrman, Galbraith & Lawler III., 1998, p.77; Dessler, 2001, p. 230; Pettigrew et al., 2003, p. 8; Vahs, 2005, p. 507). As indispensable precondition for the functioning of the above mentioned organizational connectedness the authors quote timely adjusted cooperative processes, organizational development, space dispersion and use of modern communication technology to master the processes of cooperation (Rohde, Rittenbuch, & Wulf, 2001. p. 2). In the literature, the companies are often described as a network of companies (i.e. organizations – boundary-less firms or boundless organizations). These are dynamic, i.e. virtual companies, linked together at the base of the interorganizational information systems, pursuing the aim to be successful in the area of given projects. Virtual laboratories are a special form of network organizations. A virtual laboratory is an interactive online environment established so as to create and channel simulations and experiments
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in a certain science field. It is an environment designed for working in teams from different locations and creates opportunities for cooperation in research and development. One of its important tasks is also the remote access to expensive laboratory and other equipment. Virtual laboratories further include the so called living labs. The basic concept of the living lab was developed at the American MIT Institute in Boston, USA. It was first used for designing and planning urban area architecture. A living lab is an R&D methodology for identifying, validating and finding solutions to complex problems by including a real-life environment. In such an environment, product and service innovation is carried out, tested and introduced.
GOVERNANCE OF VIRTUAL ORGANIZATIONS AND LIVING LABORATORIES Recent years have seen an increased interest in corporate governance. There are several reasons for that, resulting from individual business scandals to increasingly complex environments that require close cooperation between owners and management. Corporate governance can be defined as a system by which companies are directed and controlled. Boards of directors are responsible for the governance of their companies. The stockholders’ role in governance is to appoint directors and auditors and to make sure that an appropriate governance structure is in place. The responsibilities of the board include setting the company’s strategic goals, providing the leadership to put them into effect, supervising the management of the business, and reporting to stockholders on their stewardship. The board’s actions are subject to laws, regulations, and the wishes of the stockholders in the general meeting (Bnet Business Dictionary, Mallin, 2007, p.12). The area of governance and that of management are closely connected. In the area of net-
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work organizations with special focus on virtual organizations, the connection of the processes of governance and management is even more expressive. For this purpose, we will ensue from the term governance as explained by the author Hilb, when we present the models of governance and management in a virtual organization and living laboratories. Hilb defines corporate governance as s system “by which companies are strategically directed, integratively managed and holistically controlled in an entrepreneurial and ethical way in a manner appropriate to each particular context” (Hilb, 2006, p. 9-10). Processes of governance take place at virtual connections on the level of connection and in individual associations. The complexity of governance processes demands a clear distinction and mutual adjustment. For the purpose of easier recognition and understanding of governance processes, we can divide them in: • •
Governance processes of forming interorganizational virtual connections and Governance processes of ensuring development and operations of inter-organizational virtual connections.
The key aspects of governance processes in forming inter-organizational virtual network organizations are: • •
Goals and Forms of virtual network organization.
Definition of the strategy behind virtual network organizations must stem from the organization’s strategy (Mohrman, Galbraith & Lawler III., 1998, p.79). The other set of governance processes embodies: • •
Forms of virtual network organization Assignment of the role that individual organizations assume.
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The form of virtual network organizations is closely related to the goal definition of virtual network organizations. When joining into a virtual network organization the owners and management must ask themselves the following questions: •
• • •
•
What are the primary goals, purposes, and strategy of forming a virtual network organization? What advantages and dangers does it imply to the company? What are the advantages of a virtual network as a whole? What place will our company have in a virtual network (specialist or integrating of the entire network)? What are the alternatives?
When forming a virtual network special attention must be paid to the selection of partners. The first step in this process is to know and understand the strategic goals of partners. Good knowledge and understanding of partner’s reasons for the involvement in virtual networking can spare us from future unpleasant surprises. In practice, we have cases where certain organizations are closely connected in a network for the sole reason of acquiring information on its partners. This enables them greater control, price pressure, etc. That is why the key to partner selection is to know their strategic implications for joining (Mohrman, Galbraith & Lawler III., 1998, p. 86). Having chosen the partner, the company must then select forms of virtual network organizations and reach an agreement on the role of the organizations (conclusion of a contract). The role that an organization assumes depends on the ability, purpose, and goals for joining a network. Primarily, we speak of the decision on the form of the legal status and ways of implementing an integrative role as well as a definition of the place and role of other companies in the network. Basic criteria for the selection of a coordinating role in a virtual
network are (Mohrman, Galbraith & Lawler III., 1998, p.101): • • • • • • • •
Knowledge of the entire process or the chain of added value Experience Ability to gain the necessary resources for the operation of a virtual network. Disposable resources Credibility of the organization Key factors or abilities of individual organizations Management resources with the required expertise and experience. Readiness to assume the role.
It is appropriate to stress that many times the required managerial effort for the implementation of integrative processes is underestimated (Schräder, 1996, p.83). Therefore, the selection of managers and other personnel that work in inter-organizational virtual networks is especially important. Managers, who control, organize and guide integrative processes in virtual networks must posses the following expertise and skills (Krystek, Rede & Reppegather, 1997, p.174): • • • • • • • • •
Integrative abilities Goal-oriented management control Sensitivity to various organizational cultures Expertise in the field of virtual networking Participation Ability to motivate Restriction of constructive conflict management Communicative and representative skills Controlling of information management
In addition, it is crucial that individuals that assume key positions in virtual network organizations have the following expertise and skills
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(Krystek, Rede & Reppegather, 1997, p. 178, Reiß, 2000, p. 30): • • • • • • • •
Professional and functional knowledge Communication skills Cultural adaptability Adaptable and constructive conflict management A desire to participate A need for horizontal and lateral professional and personal development Entrepreneurship Independence and a sense of responsibility
Selection of individuals that hold key positions in a virtual network reduces conflicts, which are one of the most sensitive areas of management. There are many conflicting areas in virtual networking. This is why one of the most important managerial goals is to lay the principles, means, and instruments to resolve any possible future conflicts while forming a virtual network. One must clearly set the procedures and levels of conflict solving.
MANAGERIAL PROCESSES INSIDE VIRTUAL ORGANIZATIONS AND LIVING LABORATORIES Every virtual network organization must establish a management system that assumes the coordinating role within a network. Managerial system of coordination involves management at a classical level. Without a doubt, there are differences between the implementation of managerial tasks in a classical organization and the operation of management with a coordinating role in a virtual network organization. The differences are as follows: •
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Management system for the needs of coordination within a virtual network exists for the time that the network is operational.
•
•
Management jurisdictions responsible for coordination in a virtual network are not comparable with management jurisdictions in a classical organization. Management processes for coordination purposes within a virtual network can be distributed among several institutions.
Despite the noted aspects, we must emphasize that management processes are linked to a certain form of organization that must form itself for the operational needs of a virtual network as a whole. In principle, we differentiate three forms of a management system in coordination (Mohrman, Galbraith & Lawler III., 1998, p. 88-91): • • •
One partner carries out coordinating processes There is a division of coordinating processes among partners and Self-sustaining model of coordination.
Without a doubt, the first form is most common in implementing coordinating processes. The latter, self-sustaining, is appropriate in the first stage of forming a virtual network organization. The central place at ensuring development and virtual networking belongs to strategy. Strategy is the starting point for management operations as all individual management activities derive from it. Up to a certain point strategy of a virtual network can stem from strategies of individual organizations included in a network. Figure 1 clearly shows that it is the strategy at the level of virtual networking which represents the key connection between strategies of organizations and their business strategies. The making of key strategic starting points is by no means simple. We must first look for common ground and points and then form the key strategic goals. The common strategy is guidance for management operation in a network at key tasks such as:
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Figure 1. Strategic levels in a virtual network organization (Krystek, Rede & Reppegather, 1997, p. 304)
• •
Allocation of resources within a virtual network and Evaluation of the achieved business results.
In classical companies, the role of the managers is to – among other tasks – allocate the financial, material resources and personnel abilities. One of the primary management tasks lies also in virtual network organizations. The difference is that management in virtual network organizations predominantly deals with personnel abilities, technology, self-sustainment and support to individual tasks (Schräder, 1996, p.80). One particularly sensitive area of management activity in virtual network organizations is the area of forming unified elements or organizational culture. The process of forming a virtual network organizational culture is different from that of the classical organizations. Virtual network organizations have a high degree of differentiation of organizational culture with explicit presence of individual subcultures (Krystek, Rede & Reppegather, 1997, p.159).
This implies that we cannot expect a formation of a unified virtual network organizational culture that all organizations in the network will embrace. We can speak only of common elements of organizational culture. The basis for identification and strengthening of common elements of organizational culture are the joint starting points of organizations, where unification can be achieved. In most cases, these are openness and customer orientation. Virtual network organizations form basic outlines of a common organizational culture only through joint projects, products, or services. The common elements of organizational culture can greatly contribute to achieving set goals of the network, and above all facilitate conflict resolution, which is one of the most sensitive areas of management activities. There are many conflict areas in virtual networks; therefore, the foundation of principles, means, and instruments of their resolution is one of the important tasks of management when forming a virtual network.
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HOW TO START ARCHITECTURE DESIGN OF LIVING LABORATORIES The value chain links of the organization are represented by the individual business functions which the organization needs to perform its activity. The individual business function defines the logical frame of professional tasks the organization has to perform. It relates to research, development, marketing, supply, procurement, production, sales, finances etc. The organization’s management is responsible to identify and define all business functions, which the organization needs, and to ensure their proper performance (Figure 2). The contents, organizing and organization of functioning of the individual function and related tasks must be subject of constant innovation, just like the organization’s products and related technologies.
The sole problem is not only to set forth correct contents, organization and organizing of functioning of individual business functions, but also to set forth the interconnecting of the individual function (e.g. connection between research, development, production, finances etc.). Primary and supporting business areas are distinguished. Primary business functions represent the elements of the basic business process ranging from research and development of the product to its sale on the market. On the other hand, the supporting businesses areas actually make that happen. The supporting business activities include business planning, organizing, financing, managing and supervising. In any organization two simultaneous, closely connected processes are going on (Figure 3):
Figure 2. The organization’s management is responsible to identify and define all necessary business functions (Semolic, 2004, p. 136)
Figure 3. In any organization two simultaneous, closely connected processes taking place (Semolic, 2004, p. 137)
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• •
Technical process, Entrepreneurial process.
The technical process comprises of the sequence of all tasks which have to be performed in order to make the product. The result of the technical process is the “finished product”. The entrepreneurial process makes the first process possible; its result is the sold product and realized profit or other organization’s business benefits. The first process represents the technical part, whereas the second process represents the business part of the organization’s value chain.
MATRIX OF VALUE CHAIN OF LIVING LABORATORY The value chain of the living laboratory refers to defining the interconnected specialized activities with which the organizations enter into business connections with other virtual laboratory entities taking part in completion of the product. Figure 3 illustrates the example of an organization without external business connections (Classical approach
to make a business), performing all research, development and testing activities inside an own organization, and a highly specialized organization performing only certain business activities at home, while the others are performed through outsourcing with the living laboratory organizations. Figure 4 shows the types and content of business connections between the partners of living laboratory. Also in living laboratory the following connections are distinguished: • •
primary and supporting connections.
Presentation of practical example of the links of chain of primary connections in LENS Living Laboratory: • • • • • •
development of new materials and alloys, material surface treatment, conceiving and designing, computer analyses and simulations, special testing or production services, etc.
Figure 4. Classic and outsourcing approach to the company’s value chain set-up (Semolic, 2004, p. 139)
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Figure 5. Organizations outsourcing and clustering cube (Semolic, 2004, p. 139)
The individual link of the primary value chain represents specialization of involved organizations. The value chains of primary connections between the organizations of the living laboratory are formed in accordance with the living laboratory development strategy. The support and orientation of the development of living laboratories value chains are assured by supporting value chain links, thus creating conditions for successful connecting of business companies and organizations, by orienting the value chain primary links formed by companies and organizations of the living laboratory. The supporting value chain links consist of the following business activities: • • • • • •
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living lab digital eco-system development and maintenance, living lab e-collaboration platform development and maintenance, living lab professional virtual communities social networking support, living lab governance and management systems development maintenance, living lab e-program and project management, living lab marketing etc.
In conjunction with the participating organizations, the leading companies – organizers of business networks within the living laboratory organize the business chains, hence assuring optimum value of products and services offered to the clients and their end users. The organization of Living Laboratory’s (virtual organization) Breeding Environment (ECOLEAD, 2004) represents the living laboratory management. The living laboratory management must take care of orienting, stimulating and supporting the business cooperation and connecting. Accordingly, they must provide and develop a suitable supporting value chain of specialized services, required for this purpose. The basic driving force of each work in any participating organizations of the living laboratory must be “client’s value”.
TOOL MAKING INDUSTRY CASE STUDY Tool and Die Industrial Sector Tool and Die-making workshops (Figure 14) are facing the challenges how to enhance performance of project-oriented production in multi-project and multi-organizational environment. Each customer order presents the project charter (see Figure 6) for
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Figure 6. Examples of metal products for automotive industry with example of progressive tool for production of parts from metal plates (EMO, 2002)
the project of development and construction of a unique new tool. As illustration of the size of its market we can say that automotive producer needs more that 1000 tools and dies for production of a new car. In the project of a new tool development and construction companies outsourcing capacities from different partners and creating a different modalities of production network organizations. In this context in project we developed reference business model. It provides a framework, including all relevant main business process applications. Next, the practical example of the technical and entrepreneurial value chain in tool-making industry will be presented. Tool-making industry consists of SMEs, producing special purposed (unique) machines and tools for clients from manufacturing industries (ex. automotive etc.). Elements of the technical value chain of a tool-making company: • • •
researches and development of new technical knowledge, development of new production technologies, design of tools,
• • • • • •
tool manufacturing technology development, tool manufacture, tool tests, start-up of tools, tool maintenance, tool recycling (after expiration of the tool service life).
Elements of the entrepreneurial value chain of a tool-making company: • • • • • • •
researches and development of new business knowledge, development of new business technologies, marketing and sales, supplies for production,, production, client’s taking-over of tool, after-sales activities.
The technical and entrepreneurial value chain must be coordinated and subject to constant introducing of novelties and innovative solutions which are a prerequisite for maintaining or increasing the company’s competitiveness
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What is LENS Living Lab? LENS Living Lab is organized by coordination of Slovenian Toolmakers Cluster (TCS). Laser Engineered Net Shaping (LENS) Living Laboratory (LENS Living lab) is a real-life research and operational laboratory with the focus on a LENS new technology applications development and operational use (Figure 7). The LENS Living Lab creates a base for inventing, testing, prototyping and marketing of new LENS technology applications. The major advantage of virtual organization is the creation of pools of innovative organizations and experts from different research and end user areas who are collaborating and cooperating in this virtual environment.
The LENS Living Lab core members are business partners (users, researchers, developers etc.) who have long-term interest in such cooperation and collaboration. Those organizations and individuals are from research and industrial sector. LENS living lab creates open “value space” for researchers, developers and end users who have professional interest in collaboration in this field. They can be innovators, researchers, developers or advanced users. Figure 8 shows phases in the process of a technology life cycle (TLC) and LENS Living lab areas of support. LENS Living Lab supports three major TLC phases: new design and manufacturing concepts development; testing of new developed technologies and connected “early birds” and support to phase of new technologies implementation and
Figure 7. The basic concept of LENS technology and examples of products (OPTOMEC, 2006, p.15)
Figure 8. TLC phases and LENS Living Lab areas of support (Semolic, 2009)
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its operations support. The horizontal supporting services are related to functionalities of LENS Living Lab project office and LENS Living Lab general collaboration platform (Tool East Platform). The customers of LENS Living Lab application research and operations are SMEs who are working in different industries, like tool-making and niche machines production, automotive, aeronautics, medicine etc. The participating organizations are divided in different open research groups like material scientists, mechanical engineers, laser and electronics experts, end users, ICT experts, business design developers etc. They have been involving in three operational and research frameworks as follows: • • •
Technological and Innovative Centre, LENS Living Lab and Open Laser Collaboration Platform
Governance and Management in LENS Living Lab The LENS Living Lab is an open network organization with three levels of inter-organizational governance and coordination (see Figure 9). The
first level deals with strategic business issues. At this level, the participating partners sign a longterm cooperation agreement. This agreement defines areas of cooperation and management of LENS Living Lab. The second level deals with the inter-organizational issues (joint and support operation and project management). This level is related to the coordination of agreed business activities and connected organizational processes. The third level of coordination is related to the definition of IT and telecommunication platform of cooperation. The organizational architecture of the second level which deals with the inter-organizational issues is based on the principles of open project based matrix organization (see Figure 10). One side of this matrix organization is composed by independent open international R&D groups (R&D organizations, SMEs, independent researchers and developers etc.) which represent LENS Living lab research and development capacities. Another side comprises of a list of agreed R&D programs and projects. In the cross-sections of this matrix we are identifying demanded R&D resources and creating temporary collaborative virtual project teams.
Figure 9. Levels of coordination in LENS Living Lab (Semolic & Kovac, 2008, p. 413)
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Governance of Virtual Networks
Figure 10. LENS Living lab – open project based matrix organization (Semolic, 2009)
Strategic level of LENS Living lab governance is performed by the support of strategic annual conferences, by collaboration between coordinators of open international R&D groups, by collaborative program management, by collaborative project management, by management of collaborative virtual project teams etc.
CONCLUSION If we want to develop a competitive strength of our company, it often turns out that despite using our knowledge, capacities and other resources we are still not able to reach the desired goal. In the modern business environment, the companies will establish and maintain their competitiveness not solely by optimizing their own potentials, but more often by being able to use the resources of others and by interconnecting them into an overall process of creating new value. New forms of network organization appear which organize individual business activities in the regions favorable from the business viewpoint with respect to the prices of manpower, special know-how, raw materials
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etc. Methods and forms of organizing network virtual organizations are based on modern and flexible business models. Living Laboratory represents one of many forms of virtual network organizations. The article presents some basic theories related to this subject. A Living Lab is an environment in which researchers, developers and users cooperate with the common objective of delivering a tested product, solution or service respecting users’ requirements and in a shortest time possible. We illustrated the creation of virtual organizations and living laboratories on the case study of tool and die making industry. By illustrating the governance and coordination of LENS Living lab we presented the discussed theories in praxis.
REFERENCES Dessler, G. (2001). Management. NJ: Prentice Hall, Inc. Dictionary, B. B. (n.d.). Retrieved October 10, 2008, from http://www.bnet.com
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Duin, H. (2008). Systemic strategic management for VBEs in the manufacturing sector. In L.M. Camarinba-Matos, & W. Picard (Eds.), Pervasive Collaborative Networks, IFIP TC 5 WG 5.5. Ninth Working Conference on Virtual Enterprises, Sept. 2008, Poznan, Poland. NewYork: Springer. EMO (2000). Internal project documentation. Celje: EMO Orodjarna. Hilb, M. (2006). New corporate governance. New York: Springer Verlag. Knez, M., Cedilnik, M., & Semolic, B. (2007). Logistika in poslovanje logističnih podjetij. Celje: Fakulteta za logistiko UM Krystek, U., Redel, W., & Reppegather, S. (1997). Grundzüge virtueller organisation. Wiesbaden: Gabler. Loss, L., Pereira-Klen, A. A., & Rabelo, R. J. (2008).Value creation elements in learning collaborative networked organizations. In L.M. Camarinba-Matos, & W. Picard (Eds.), Pervasive Collaborative Networks, IFIP TC 5 WG 5.5. Ninth Working Conference on Virtual Enterprises, Sept. 2008, Poznan, Poland. NewYork: Springer Mallin, C. A. (2007). Corporate governance. Oxford: Oxford University Press. Mohrman, A. S., Galbraith, J. R., & Lawler, E., III. (1998). Tomorrow’s Organization, San Francisco: Jossey-Bass. Pettigrew, A., Whittington, R., Melin, L., Runde, C. S., & Bosch, F. A. J. den, Ruigrok, W., & Numagami, T. (2003). Innovative forms of organizing, London: Sage Publications. Peyton, R. (2004). Toolmakers cluster of Slovenia, feasibility study. Los Alamos, World Tech, Inc. Rohde, M., Rittenbuch, M., & Wulf, V. (2001). Auf dem Weg zur virtuellen Organisation. Heidelberg: Physica-Verlag.
Schraeder, A. (1996). Management virtueller Unternehmungen. Frankfurt/Main: Campus Verlag. Semolic, B., & Dworatschek (2004). Project management in the new geo-economy and the power of project organization. Maribor: IPMA Expert Seminar Series, University of Maribor. Semolic, B. (2007). LENS Living Laboratory – Project documentation. Celje: INOVA Consulting; Project & Technology Management Institute, Faculty of Logistics, University of Maribor. Semolic, B. (2009). TA Platform, LENS Living Lab. Vojnik, INOVA Consulting, TCS. Semolic, B., & Kovac, J. (2008). Strategic information system of virtual organization. Pervasive Collaborative Networks. Poznan: IFIP, Springer. Vahs, D. (2005). Organisation. Stuttgart: SchafferPoeschel Verlag.
KEY TERMS AND DEFINITIONS Corporate Governance: Corporate governance can be defined as s system by which companies are strategically directed, integratively managed and holistically controlled in an entrepreneurial and ethical way in a manner appropriate to each particular context. Living Lab: A living lab is an R&D methodology for identifying, validating and finding solutions to complex problems by including a real-life environment. In such an environment, product and service innovation is carried out, tested and introduced. Network Organizations: Network organizations (i.e. organizations – boundary-less firms or boundless organizations). These are dynamic, i.e. virtual companies, linked together at the base of the inter-organizational information systems, pursuing the aim to be successful in the area of given projects.
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Virtual Laboratory: A virtual laboratory is an interactive online environment established so as to create and channel simulations and experiments in a certain science field. It is an environment designed for working in teams from different locations and creates opportunities for cooperation in research and development.
Virtual Organizations: Virtual organizations are a temporary consortium of partners from different organizations establishes to fulfill a valueadding task, for example a product or service to a customer
This work was previously published in Infonomics for Distributed Business and Decision-Making Environments: Creating Information System Ecology, edited by Malgorzata Pankowska, pp. 262-276, copyright 2010 by Business Science Reference (an imprint of IGI Global).
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Chapter 6.12
Decision-Making for Location of New Knowledge Intensive Businesses on ICT Sector: Portuguese Evidences João J. Ferreira University of Beira Interior, Portugal Carla S. Marques University of Trás-os-Montes e Alto Douro, Portugal Cristina Fernandes University of Beira Interior, Portugal
ABSTRACT Technological innovation associated with ebusiness is seen as one of the key drivers of the knowledge economy and innovation performance and is a considerable test of a region’s or nation’s capacity to generate e-entrepreneurship and sustain competitiveness. The importance of the knowledge intensive business services (KIBS) sector to economic growth will increase signifiDOI: 10.4018/978-1-60960-587-2.ch612
cantly with the development of the knowledge economy and the rise of e-entrepreneurship. This article identifies different types of new KIBS and recognizes factors influencing their location. A conceptual research model based on the link between KIBS and location attributes is proposed and tested, and a survey was carried out in the Region Centro of Portugal to test a multidimensional approach at the location decision level. The authors’ found many different factors associated with the location of new KIBS, and their findings highlight two profiles of KIBS.
Copyright © 2011, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
Decision-Making for Location of New Knowledge Intensive Businesses on ICT Sector
1. INTRODUCTION The Lisbon European Council adopted, in March 2000, an economic reform programme with the aim of making the EU the most competitive and dynamic knowledge-based economy in the world by 2010. In that connection the European Council highlighted the key role of services in the economy and their potential for growth and employment. Services are the main motor of growth in the EU, accounting for 54% of GDP (Eurostat, 2002) and for 67% of those in employment. However, interest on economic information services goes back to 1980, at a time when regional development in Europe and North America was concerned with de-industrialization. Until then, those services were seen as mere subsidiaries of transforming activities. Over the last 20 years, special attention has been paid to the roles performed by those services. De-industrialization has continued, yet, some services’ sectors have shown a progressive rise (Wood, 2005). Despite growing awareness that innovation is not confined to sheer technical processes and products, some recent research on innovative activities has focused its attention only on technical innovation and, in particular, on the transforming industries sector (Becker & Dietz, 2004; Huergo & Jaumandreu, 2004; Lynskey, 2004; Nieto & Santamaria, 2005). Technological innovation associated with e-business is now broadly appreciated as one of the key drivers of positive economic change and innovation performance and gives a potentially considerable test of a region or nations capacity to generate an e-entrepreneurship process (a multistage process which is influenced by both the exogenous as well as endogenous factors) and sustain competitiveness (Ramsey et al., 2005). Particularly the importance of the Knowledge Intensive Business Services (KIBS) sector to economic growth will increase significantly with fast development of the knowledge economy and the rise of e-entrepreneurship.
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According to McCole and Ramsey (2004) e-business is the integration of Information and Communication Technologies (ICT) into business operations, which may evolve the redesign of internal processes around ICT, or the complete reinvention of an organization’s business model. Relation to the ICT is a key feature of KIBS which has been attracting a great deal of attention in the literature (Hempel, 2002; Broersma & Ark, 2007; Muller & Doloreux, 2009). In the most dynamic service industries, investments in ICT are larger than in the manufacturing sector and the available statistics concerning ICT investments show that service sectors account for the biggest – and growing-share of the total expenditures in ICT in the economy (Corrocher et al., 2009). Today ICT must be conceived broadly to encompass the information that business create and use, as well as the wide spectrum of increasingly convergent and linked technologies that process that information. Therefore, ICT can be viewed as a collective term for a wide range of software (human and social capital), hardware (information and communication technology), and and the fundamental socio-economic environment, which are linked in a systematic way by the entrepreneurs (Brandy et al., 2002; Porter & Millar, 1985). ICT have the potential to generate a steep change among KIBS and make them more competitive, innovative and generate growth. The importance of the services industry has only been acknowledged in the last decade (Gallouj & Weinstein, 1997; Tether, 2003). According to Tether et al. (2001) innovation in the service industry firms is perceived as something that occurs very slowly. Services are perceived as being incapable to innovate, adopting innovations generated by the transforming industry’s firms. Alongside Tether et al. (2001), Pavitt (1984) also believes that smaller services firms are less likely to develop R&D roles, thus becoming recipients of technology and innovation produced in other sectors.
Decision-Making for Location of New Knowledge Intensive Businesses on ICT Sector
Within the services industries, the rapid growth of KIBS has exposed their major role in innovation processes (Howells & Tether, 2004; Koch & Stahlecker, 2006; Muller, 2001; Toivonen, 2004). The role played by KIBS in the innovation process is affirmed, above else, by the fact that they do not have a simple performing role in the innovating activity, such as meeting demand and, more specifically, their clients’ wishes. Rather, they act as builders of “knowledge bridges”, or “innovation bridges”, between firms and science (Czarnitzki & Spielkamp, 2003; Miles et al., 1995). Nevertheless, few studies have been made on the innovative activity carried out by this sector of services (Koch & Strotmann, 2008). KIBS are services that rely deeply upon professional knowledge (Miles et al., 1994). Thus, the employment structures of firms in these sectors are heavily weighted towards scientists, engineers, and specialists of all types. Some are strongly technology-oriented, while others are much more concerned with knowledge of administrative, regulatory or social affairs. The intent of this research is to fill this gap in the literature and intends to contribute to the analysis of location factors of KIBS in the ICT sector. This study aims to examine the existence of distinct types of new KIBS, and to analyze the possible differences between them as to the factors that influence the location of new KIBS firms on ICT sector in a particular region. The article is structured as follows: next to this introduction, comes a theoretical framework of the characteristics and nature of KIBS and ICT. In the third section, theoretical approaches on KIBS’s location are developed, and the research hypotheses and the research model are proposed. In the fourth section some methodological aspects, particularly the unit of analysis (the Region Centro of Portugal), methods of data collecting, and Data analyses are presented. In the fifth section, the empirical research is developed, where the location factors are identified and the typology of KIBS obtained. In the end, the conclusions and
recommendations, with limitations and future lines of research are addressed.
2. CHARACTERISTICS AND NATURE OF KIBS AND ICT: A THEORETICAL FRAMEWORK Interest in the global diffusion of technology has been derived by arguments that it may increase knowledge diffusion through improving communication efficiency, improve political engagement (Norris, 2001), and allow developing countries to ‘leapfrog’ traditional methods of increasing productivity (Steinmueller, 2001). In this light, the striking international differences in ICT diffusion that exist today, often referred to as the Global Digital Divide, may pose a serious challenge to policymakers (Chinn & Fairlie, 2007). The rapid acceleration in the evolution of ICT and the broadening of its applications (in particular in the services sector) during the 1990s has established the nature of ICT as a generalpurpose technology. Today ICT is ubiquitous, with widespread applications; it generates new technological developments; and it has the ability to generate a stream of cost-reducing innovations, affecting in many ways the innovative behaviour and productivity performance in all sectors of the economy (Broersma & Ark, 2007). Although the enduring growth of the service sector in the advanced economies, services have long been perceived as non-innovative or technologically backward activities (Gago & Rubalcaba, 2007). It was only during the 1990s that the traditional conception of services as innovation laggards gradually changed. The earlier researches that covered the way for this shift were mainly focused on the use of technologies by services activities, especially ICT in creative rather than standard ways (Antonelli, 1998; OECD, 1996). In this picture, service innovations were inherent in the hardware components and transferred when
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implemented by service industry users (Gago & Rubalcaba, 2007). According to Gago and Rubalcaba (2007) ICT are drivers, facilitators and agents of four non-independent types of services innovation: product and process, organization, interfaces and co-production schemes, and business services and KIBS-related innovation. For others the debate on the growth of KIBS swirls around their new specializations of the business process that they run themselves and the rise of the tertiary sector in general. More and more specialized service providers will appear on the market, able to cover specific business processes for a larger number of customers. This increasing specialization will create ever longer and more complex advanced services (Corrocher et al., 2009). It is becoming increasingly obvious that both the new manufacturing processes and the new services and innovations in general find their origin more and more on KIBS (KaraÃmerlioglu & Carisson, 1999; Tomlinson & Milles, 1999). Since KIBS play a role of increasing importance in the economy, it is then desirable that KIBS are stimulated into adopting new technologies more rapidly, and creating innovative products more competitively. It requires that KIBS have the right environment to prosper, and from a skilled workforce and drive economic growth (Chinn & Fairlie, 2007; Sánchez et al., 2007). Hauknes (1999) draws our attention to a particularly significant question: what is, after all, knowledge intensity? According to him, knowledge intensity is hard to define and still harder to measure. To the extent that knowledge intensity reflects the integration with a generic or service specific science and technology base, it can be seen as a combination of knowledge embedded in new equipment, personnel, and R&D intensity. Furthermore, he argues that, another way at a micro-level may be to define it in terms of conditions for the transaction between the service provider and the service user or procurer. A simple approach to this would be to try classifying services according
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to relevant knowledge requirements of service provider and related knowledge requirements of the service procurer in a two-dimensional plot: low and high. Depending on the level of specialization in intensive knowledge on the part of the supplier, whoever requires a supplier of this type of services, will choose one type of supplier or another. In this case, knowledge intensity allows consumers to choose a service in detriment of another, taking into account its higher or lower degree of knowledge intensity. According to Broersma and Ark (2007) in relation to ICT there is a clear role for KIBS in contributing to changes in work organization (by consultants or technical engineers), introduction of standard or customized software solutions (by IT services) or the introduction of new client interfaces (marketing services). Hence the interaction between ICT and KIBS can lead to causality in dissimilar directions, but are typically focused on customization of the new technologies and further development of consequent – unique – innovations. In other words, such combinations typically concentrate in the management of interfaces between external and internal knowledge (Antonelli, 2000; Broersma & Ark, 2007). The proliferation of ICT has helped the diffusion of KIBS, because these new technologies influence the conditions of information like its tradability, which in turn affect the generation and organization of knowledge. In other words, KIBS have become a crucial part in the way firms organize and innovate their business process (Antonelli, 1998; Broersma & Ark, 2007). This has led to a new division of labour between specialists in KIBS on the one hand and the producers of manufactured goods on the other. This specialisation has been translated into a significant growth of knowledge intensive labour in modern industrialised (OECD, 2008) countries and manufacturing job creation in newly-industrialising countries. The location of High-order Producer Services (HOPS) has been extensively documented for the 1970s and 1980s when researchers turned
Decision-Making for Location of New Knowledge Intensive Businesses on ICT Sector
their interest to the effects of tertiarization on regional development (Coffey, 2000; Shearmur & Doloreux, 2008). Coffey (2000) stresses the growing interest in HOPS, and their important role in Western economies, producing possible spillover effects, synergies between economic sectors and labor market effects, into the spatial analysis. As service producers, their rapid growth in this specific segment of the economy has been perceptible (Coffey & Shearmur, 1997; Daniels, 1985). On the other hand, their role in the competitiveness of regions has also been observed and deserved the attention on the part of regional geographers and scientists (Beyers & Alvin, 1985; Coffey & Polèse, 1987; Drennan, 1987; Illeris, 1996). Nevertheless, there is a great deal of difficulty in finding distinct definitions for KIBS and HOPS as both expressions are used to define the services sector. In other words, business services and producer services are sectors whose clients are mainly firms and rarely individual customers. HOPS are all those services that require complex handling of symbols and transformation of information, which is often complex and atypical (Bryson et al., 2004; Daniels, 1985; Reich, 1992). In general terms, KIBS are mainly concerned with providing knowledge intensive inputs to the business processes of other organisations, including private and public sectors clients (Muller & Doloreaux, 2009). Miles et al. (1995) identified three essential characteristics of KIBS: 1. They rely heavily on professional knowledge; 2. They either are themselves primary sources of information and knowledge or they use knowledge to produce intermediate services for their clients’ production processes; 3. They are of competitive importance and supplied to business. More precisely, these authors defined KIBS as services that involved activities which are intended to result in the creation, accumulation or dissemination of knowledge. KIBS definition is
not uniform in the various existing studies (Muller & Zenker, 2001; Muller & Doloreux, 2009). According to the Standard Industry Classification (SIC), KIBS may be divided into two groups: Technological KIBS (t-KIBS); and Professional KIBS (p-KIBS). The t-KIBS are mainly related to information and communication technologies as well as technical activities (IT-related services, engineering and architecture activities, R&D consulting, etc.). The p-KIBS are traditional professional services, liable to be intensive users of new technology (business and management services, legal accounting and activities, market research, etc.). Freel (2006) concluded that t-KIBS employ higher qualified people, and that this relates to their level of innovation. In the case of p-KIBS, he noticed that the relationship between them, suppliers and clients fosters innovation. As for the transforming industries, as it is not in their interest to invest in R&D, their level of innovation is extremely low (Freel, 2006). The development of ICT advances the demand for KIBS in several ways. Along with the explosion of the amount of information, there is a growing need for highly qualified professionals who are able to provide comprehensive and customised interpretation of random data (Lundvall & Johnson, 1994). On the other hand, the development of ICT also gives new incentives to the codification of knowledge (Smedlund & Toivonen, 2007). It increases the divisibility of information, which, together with the enhanced accessibility, results in the growth of the commercial potential of information. KIBS tend to be among the chief advocates and supporters of the emerging information markets. Finally, ICT has essentially increased the opportunities to effectively combine external and internal knowledge sources. It has enabled easier interfaces and higher levels of appropriability of specific problem-solving methodologies. Through the use of these new means, KIBS can better than previously provide their clients with access to information dispersed in the society and enhance
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shared learning experiences between the nodes of innovation networks (Antonelli, 1998; Smedlund & Toivonen, 2007). Figure 1 presents the main possible interrelations between knowledge intensity and High-order producer services based on a multidimensional view of KIBS and the complementarities between professional and technological knowledge intensive business service in an ICT sector. According to Wood (2005), research on regional innovation merely echoes national studies that focus primarily on regional competitiveness, as a process that is oriented and technologically pushed by innovation. According to this author, the provision of information services for innovation purposes must be acknowledged as a service that is inbuilt within a scientific and technological services division, whose adoption by firms from other sectors is vital for its own success. Sheamur and Doloreaux (2008) present two perspectives that indicate how KIBS contribute towards regional development: 1. The way KIBS interact with other local players with the aim of producing innovation and Figure 1. Characteristics and nature of KIBS
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subsequent regional development. Thus, this first perspective suggests that KIBS should be involved in the development of regions as long as synergy effects occur in the very same regions; 2. KIBS may be involved in regional development, but instead of being in the regions, they may be located elsewhere in the country, and so be involved at a distance. From these two perspectives, we are inevitably led to the question of location of KIBS. The location of these firms and their contribution to local economies have been analysed by several researchers (Coffey & Shearmur, 1997; Gong, 2001; ÓhUallachain & Reid, 1991). Their localization in the urban system, their sensitivity to the economies’ general agglomeration (Eberts & Randall, 1998; Poehling, 1999; Wernerheim & Sharpe, 2003) and their tendency to set up around spatial clusters (Coe, 1998; Keeble & Nachum, 2002), have been documented through several tools and methodologies. A large part of these studies has been motivated by interest in researching the dynamics of local economies, regional
Decision-Making for Location of New Knowledge Intensive Businesses on ICT Sector
development and the reason why some regions grow faster and more than others (Moyart, 2005).
3. THEORETICAL APPROACHES ON KIBS’ LOCATION E-commerce, facilitated by the Internet, is dramatically changing the manner in which buyers and sellers find and interact with each other. Electronic networks (namely, Electronic Data Interchanges) have existed for some time allowing many large companies to communicate with other large suppliers and/or customers (Hatiwanger & Jarmin, 1999). This has potentially important implications for the nature and location of businesses – particularly those involved in the distribution of goods and services – and important implications for how markets work (Brynjolfsson & Kahin, 2002). Competitive challenges faced by firms from ICT sector require that maximum effort is put on exploiting the e-business potential in supporting innovation and competitiveness. According to Capello and Spairani (2004) after two decades of study there is world-wide recognition that the impact of ICT on firms’ performance depends on various micro-behavioural elements, which have a primary role in allowing better exploitation of these technologies. These micro-behavioural elements explore concepts involved in human spatial decision making and choice behavior. Human spatial behavior can be defined as any sequence of consciously or subconsciously directed life processes that result in changes of location through time (Golledge & Stimpson, 1997). Areas that give the strongest support to ICT exploitation are special areas such as cities, and large towns in particular, characterized by high levels of human and relational capital, and other special areas defined in the literature as industrial districts or innovative milieux. In these areas, the strategic elements that support ICT adoption and use – organizational flexibility and innovative capacity – can be reinforced by the local envi-
ronment in which the firm is located (Capello & Spairani, 2004). According to Malecki et al. (2004), KIBS are essentially located in cities, as the latter are the optimum places for corporate innovation, as well as for networks leading to innovation. Sheamur and Doloreaux (2008) present a distinct viewpoint, based on their study in Canada, whereby the sample was selected from Censuses carried out in 1991 and 2001. They selected KIBS from 152 urban agglomerations and KIBS from 230 rural areas. The authors then noticed that in the beginning of the 1990s, this service providing companies were, in their large majority, based in urban areas. Roper and Love (2006) argue that still rural areas lag far behind their urban counterparts relating to KIBS creation. In this sense, classical and contemporary economic thoughts have consistently depicted urban agglomerations as the chosen location for conducting business (Marshall, 1920; Hoover, 1948; Jacobs, 1969; Krugman, 1981). Nevertheless, improvements in the transport and communication infrastructure have considerably shrunk the physical and psychological distance between rural and urban areas (Grimes, 2000; Phelps et al., 2001). Few of these insights reflect on the motives which led firms of high technology to set up in rural areas. The reason behind this lack of information lies, probably, in the small number of firms located in rural areas. Nevertheless, and due to the development of information technologies, particularly the Internet, Grimes (2000) and Ferreira et al. (2009) identified an increase in the number of firms which set up in those areas. According to Silva (2006) the spatial distribution of economic activities results from opportunities and location strategies devised in accordance with particular objectives. However, decisionmaking processes are complex and involve an important economic component, since a large part of human activities require the use and sharing of limited resources. Capello (2007) recognizes two groups of regional economic theories that look
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into the issue of economic logic, which intends to explain the location of firms: 1. Location theories: economic mechanisms that cause the distribution of activities in space; 2. Growth and regional development theories: they focus on spatial aspects of economic growth and on territorial distribution of income. On the other hand, Hayter (1997) set off to analyse the location of economic activity through three distinct approaches: 1. Neoclassical, which focuses mostly on the location theory and centres its analysis on profit maximization strategies and minimization of costs (transportation costs, human resources costs and external economies); 2. Institutional, which states that it is important to consider not just the firm’s search for an appropriate location but also the institutional milieu it is part of (clients, suppliers, commercial associations, regional systems, the government and other companies); and 3. Behavioural, which focuses on situations of uncertainty and lack of information. According to him, these three approaches have the purpose of demonstrating how complex the reasons that motivate the location of a particular economic activity are, and they allow us to analyse factors of location at a more “micro” level. Galbraith (1985) studied 98 entrepreneurs of high technology firms in Orange County, California (USA). He concluded that high-technology firms, in their location decision process operate within a framework of factors that are different from those observed in traditional industries. These conclusions are similarly shared by Arauzo and Viladecans (2006) in their study on the level of spatial concentration of new firms (in the period
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1992-1996) in the municipalities of Spanish urban areas. In fact, smaller cities appear to be preferred for the location of technology-based firms, as they offer a quieter environment, better quality of life and become highly advantaged by the presence of qualified individuals working in these industries. According to Hayter (1997) the location of many firms is explained by behavioural factors, since many entrepreneurs, when deciding on where to set up their firms, end up choosing the places where they were born. In order to identify what behavioural factors influence the locations of the KIBS, the following research hypotheses are formulated: H1a: The founder’s wish to live in this locality influences the location of KIBS. H1b: The employees’ wish to live in this locality influences the location of KIBS. H1c: Proximity to the founder’s residence influences the location of KIBS. H1d: Access to good housing conditions influences the location of KIBS. H1e: The founder’s birthplace influences the location of KIBS. H1f: Recreational and leisure opportunities influence the location of KIBS. H1g: The climate in the region influences the location of KIBS. H1h: The community’s attitude to business influences the location of KIBS. According to the neoclassical approach, the location of firms lies essentially on the power of economic forces (Hayter, 1997). According to Hayter (1997) this situation often has a perverse influence in the theories of researchers who
Decision-Making for Location of New Knowledge Intensive Businesses on ICT Sector
strictly defend the neoclassical approach, given that, through common sense, as well as a result of economic advantages, the entrepreneur, when choosing the location for his firm, takes into account all types of costs, thus deciding where to set up where costs are lower. According to Ouwersloot and Rietveld (2000), one of the key factors for economic development is technological innovation: the introduction of new production techniques, products or services. These researchers concluded that the factors that make firms decide to set up in a particular region depend on the type of firms. In other words, for traditional transformation firms, the industrial composition of the place where they will be based is a key factor. If the firms are service-based, what influences them most in their choice of location is physical infrastructures and knowledge. Accordingly to these previous authors, several neoclassical factors might influence on locations of firms. Therefore, the following research hypotheses are formulated:
H2b: Road infrastructures influence the location of KIBS.
resorted to 20000 new German firms specifically on the basis of their deep knowledge of research institutions. The results demonstrated that these start-up high-technology firms tend to trust science with a high degree of intensity, which made them set up near research institutions. Audrestch et al. (2005) stressed the importance of access to knowledge spillovers when new technology-based firms decide on their location. Their results revealed that new high-technology firms are influenced by factors other than regional traditional characteristics, such as the opportunity to access knowledge generated by universities. In turn, Autant-Bernard et al. (2006) analysed the determining factors in the creation of new biotechnology firms in France over the past decade (1993-1999); and demonstrated the need for the existence of a large and diversified scientific basis inside a region to enable these firms, after they were set up, to continue their activity for many years. There are also entrepreneurs who prefer to set up business near universities, research centres and governmental bodies, in order to have more adequate support to the activities they intend to develop within their firms (Hayter, 1997). Based on these arguments, several institutional factors might influence on location of KIBS. Consequently, the following research hypotheses are considered:
H2c: The cost of real estate influences the location of KIBS.
H3a: The existence of a business incubator in the region influences the location of KIBS.
H2d: The cost of land influences the location of KIBS.
H3b: Access to knowledge generated by universities, technology parks or research centres influences the location of KIBS.
H2a: Distance from the capital of the region influences the location of KIBS.
H2e: The level of economic activity of the region influences the location of KIBS. H2f: The level of specialisation of firms in the region influences the location of KIBS. Elgen et al. (2004) analysed the role which public research institutes play in capturing and attracting new technology-based firms. They
H3c: R&D, company or job creation incentives in order to locate business in this region influence the location of KIBS. H3d: Technology fairs organised regularly in the region influence the location of KIBS.
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Decision-Making for Location of New Knowledge Intensive Businesses on ICT Sector
H3e: The “role models” in the region influence the location of KIBS. In sum and according to the literature review, we present our research model (Figure 2) which intends to highlight the main factors that have influence on KIBS’ location decision.
4. METHODOLOGY 4.1- Unit of Analysis: Location of Region Centro of Portugal The Portuguese conditions have also generated the autonomous KIBS, whose relatively self-contained behaviour is somewhat unexpected for this type of firm (Fontes & Coombs, 1995). Because of the structural gaps in the Portuguese scientific technology infrastructure and industrial structure, firms will possibly continue to be launched in fields scarcely exploited in Portugal, in spite of recent entrepreneurs’ tendency to concentrate in Figure 2. Proposed research model
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fields where expertise exists locally (Fontes & Coombs, 1995). The experience of the KIBS, initiated in new fields and without close links with local sources of technological knowledge, but which were able to build alternative relationships elsewhere, can provide some learning ground for those entrepreneurs (Fontes & Coombs, 1995; Mamede et al., 2007; OECD, 2008). Today, the increased entrepreneurial activity of Portugal is evident; according to INE (2007) in 2003 the KIBS firms presented 13.76% of the total of firms and in 2006 increased to 16.72%. The number of KIBS in Portugal is still small. At the end of 2006, there were 189 400 (INE, 2007). However, dynamic behaviour of Portuguese knowledge-based firms and industries presented some distinctive features during the second half of the 1990s (Mamede et al., 2007). In particular, KIBS have grown faster, their price-cost margin has been higher, and firms within knowledge industries have lived longer than the average (Mamede et al., 2007).
Decision-Making for Location of New Knowledge Intensive Businesses on ICT Sector
The Region Centro is a Nomenclature of Territorial Units for Statistics (NUT) II in Portugal, it has a surface of 28.198, 70 km2 (INE, 2007), which it represents about 30.6% of the Portuguese territory and it incorporates 12 sub-regions (Baixo Vouga, Baixo Mondego, Pinhal Litoral, Pinhal Interior Norte, Dão-Lafões, Pinhal Interior Sul, Serra da Estrela, Beira Interior Norte, Beira Interior Sul, Cova da Beira, Oeste, and Médio Tejo) that contain 100 municipalities, 36 cities, and 1334 counties. With a total of 2.385.911 inhabitants in 2008 (INE, 2008), the Region Centro presents a population density of 84.3 hab/km2, below the national average value (114.3 hab/km2) and below the average value of Europe. The Region is located among two metropolis of the country: Lisbon and Oporto that exert strong forces of attraction on them. There is, however, an increasing concern with the definition of regional strategies and the infrastructures creation that supports the articulation of some urban territorial systems and its local systems of productivity with logic of complementarities in the access to the facilities and productive and social infrastructures. In the Region Centro of Portugal, we observe the presence of some favourable physical conditions (infra-structures and accessibilities) and institutional conditions (science parks and universities) which may have driven latent entrepreneurship and led to the recent increase in KIBS initiatives (Fernandes, 2008; Ferreira et al., 2009). The increased entrepreneurial activity of Region Centro of Portugal is evident, according to INE (2007) in 2003 the KIBS firms presented 10.38% of the total of firms and in 2006 increase to 13.28%. However, it is our argument that, although some changes in the institutional environment that are making the entrepreneurial decision more attractive, some institutional and behavioural barriers still remain and the process is far from being sustainable (Ferreira et al., 2009).
4.2 Data Collection The classification into these main sub-sectors is gradually taking root in the literature (Doloreux & Muller 2007; Freel 2006; Miles et al., 1995). Activities are selected according to Portuguese Classification of Economic Activities CAE1 codes, as has happened in other research that used NACE codes, which correspond to the CAE (Muller, 2001; Shearmur & Doloreaux, 2008). In rural areas of region Centro, there are 330 new KIBS created between 2003 and 2007 (INE, 2007). A questionnaire was developed from extant literature and piloted on a small group of academics and business people in the Region Centro of Portugal. The 330 questionnaires were mailed to a cross-section of owner managers of new KIBS located in rural areas in this region. Contact addresses were solicited from industry organizations and commercial data providers. Data was collected between February 2008 and April 2008 and the final response rate was 20 per cent (66 completed questionnaires). Data was analysed using conventional bivariate and multivariate techniques in SPSS 15. To sum up, Table 1 summarizes these methodological aspects.
4.3 Data Analyses To enable us to identify the location factors of KIBS in the Region Centro of Portugal, we subjected the 19 items of the questionnaire to a factorial analysis. Factorial analysis is a set of statistic techniques that aims to explain the correlation between observable variables by simplifying data by means of reducing the number of variables that are necessary to describe them. It presupposes the existence of a lesser number of non-observable variables that are subjacent to data (factors), which express the common denominator in the original variables (Maroco, 2003). This way, the main objective of using factorial analysis on data was to obtain a reduced number of factors that enable us to identify the structural relations between the
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Decision-Making for Location of New Knowledge Intensive Businesses on ICT Sector
Table 1. Methodological aspects Region
Region Centro of Portugal
Population
330 rural KIBS.
Sample unit
Rural KIBS created between 2003 and 2007.
Size of sample
66 responses (20% response rate) corresponding to 77.3% of p-KIBS and 22.7% of t- KIBS.
Respondents
Entrepreneurs – firms’ owners.
Questionnaire model
The questionnaire is formed by closed questions, using a Likert scale.
Statistical models used
Factor analysis of the main components; Mann-Whitney Test Statistics.
Data analysis
SPSS 15.0
nineteen variables that measure the importance of firm location factors. In order to use the factorial model, there must be a correlation between the variances. If those correlations are small, it is unlikely that they share common factors. Kaiser-Meyer-Olkin (KMO) and Bartlett’s sphericity test are two statistical procedures that enable us to estimate the quality of the correlations between variances, in order to conduct a factorial analysis. KMO is a type of statistic that compares zero-order correlations with partial correlations observed between variables, while the Bartlett’s sphericity test checks the hypothesis of the correlation matrix being the identity matrix, in other words, it tests if the correlations between the original variables are sufficiently high to make the factorial analysis useful when estimating common factors. In this case, recommendation based on factorial analysis is acceptable (KMO=0,684). Bartlett’s sphericity test ( 2 cGL= = 645, 987 and p-value=0.000