Innovation Through Collaboration

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INNOVATION THROUGH COLLABORATION

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ADVANCES IN INTERDISCIPLINARY STUDIES OF WORK TEAMS Series Editor: Michael M. Beyerlein Volume 1:

Theories of Self-Managing Work Teams

Volume 2:

Knowledge Work in Teams

Volume 3:

Team Leadership

Volume 4:

Team Implementation Issues

Volume 5:

Product Development Teams

Volume 6:

Team Performance Management

Volume 7:

Team Development

Volume 8:

Virtual Teams

Volume 9:

Team-Based Organizing

Volume 10:

Complex Collaboration

Volume 11:

Collaborative Capital: Creating Intangible Value

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ADVANCES IN INTERDISCIPLINARY STUDIES OF WORK TEAMS VOLUME 12

INNOVATION THROUGH COLLABORATION EDITED BY

MICHAEL M. BEYERLEIN Department of Psychology, University of North Texas, USA

SUSAN T. BEYERLEIN Center for Collaborative Organizations, University of North Texas, USA

FRANCES A. KENNEDY School of Accountancy and Legal Studies, Clemson University, South Carolina, USA

Amsterdam – Boston – Heidelberg – London – New York – Oxford Paris – San Diego – San Francisco – Singapore – Sydney – Tokyo JAI Press is an imprint of Elsevier

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JAI Press is an imprint of Elsevier The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, UK Radarweg 29, PO Box 211, 1000 AE Amsterdam, The Netherlands 525 B Street, Suite 1900, San Diego, CA 92101-4495, USA First edition 2006 Copyright r 2006 Elsevier Ltd. All rights reserved No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without the prior written permission of the publisher Permissions may be sought directly from Elsevier’s Science & Technology Rights Department in Oxford, UK: phone (+44) (0) 1865 843830; fax (+44) (0) 1865 853333; email: [email protected]. Alternatively you can submit your request online by visiting the Elsevier web site at http://elsevier.com/locate/permissions, and selecting Obtaining permission to use Elsevier material Notice No responsibility is assumed by the publisher for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions or ideas contained in the material herein. Because of rapid advances in the medical sciences, in particular, independent verification of diagnoses and drug dosages should be made British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library ISBN-13: 978-0-7623-1331-0 ISBN-10: 0-7623-1331-5 ISSN: 1572-0977 (Series) For information on all JAI Press publications visit our website at books.elsevier.com Printed and bound in The Netherlands 06 07 08 09 10 10 9 8 7 6 5 4 3 2 1

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CONTENTS LIST OF CONTRIBUTORS

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ACKNOWLEDGMENTS

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ABOUT THE EDITORS

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INTRODUCTION Michael M. Beyerlein, Susan T. Beyerlein and Frances A. Kennedy

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COLLABORATION IN CROSS-FUNCTIONAL PRODUCT INNOVATION TEAMS Avan R. Jassawalla and Hemant C. Sashittal

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LEADING INNOVATION THROUGH COLLABORATION Cynthia T. Matthew and Robert J. Sternberg

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COMMUNITIES OF PRACTICE: A CRITICAL PERSPECTIVE ON COLLABORATION Yue Lin and Michael M. Beyerlein

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TEAM INNOVATION THROUGH COLLABORATION Claudia A. Sacramento, M.-W. Sophie Chang and Michael A. West INNOVATION: ACHIEVING BALANCE AMONG EMPOWERMENT, ACCOUNTABILITY AND CONTROL Frances A. Kennedy and Lydia Schleifer v

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CONTENTS

INNOVATION AND TECHNOLOGY TRANSFER INTERMEDIARIES: A SYSTEMIC INTERNATIONAL STUDY David Pollard

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COLLABORATION, PROXIMITY, AND INNOVATION Sam Boutilier and Rod B. McNaughton

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SOCIAL NETWORKING AND THE DEVELOPMENT OF NEW VENTURES Karl Wennberg and Henrik Berglund

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CREATION OF A COLLABORATIVE ENVIRONMENT FOR INNOVATION: THE EFFECT OF A SIMULATION TOOL’S DEVELOPMENT AND USE Lina Longhitano and Stefania Testa

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BUILDING COLLABORATIVE CAPACITY: AN INNOVATIVE STRATEGY FOR HOMELAND SECURITY PREPAREDNESS Susan Page Hocevar, Gail Fann Thomas and Erik Jansen

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LIST OF CONTRIBUTORS Henrik Berglund

Department of Innovation Engineering and Management, Chalmers University of Technology, Go¨teborg, Sweden

Michael M. Beyerlein

University of North Texas, Denton, TX, USA

Sam Boutilier

Cape Breton University, Sydney, Australia

M.-W. Sophie Chang

Aston Business School, Aston University, Birmingham, UK

Susan Page Hocevar

Naval Postgraduate School, Monterey, CA, USA

Erik Jansen


Avan R. Jassawalla

Jones School of Business, State University of New York at Geneseo, Geneseo, NY, USA

Frances A. Kennedy

School of Accountancy and Legal Studies, Clemson University, Clemson, SC, USA

Yue Lin

University of North Texas, Denton, TX, USA

Lina Longhitano

DaimlerChrysler Mercedes Car Group/ Development, Stuttgart, Germany

Cynthia T. Matthew

PACE Center, Yale University, New Haven, CT, USA

Rod B. McNaughton

Department of Management Sciences, University of Waterloo, Waterloo, Ontario, Canada

David Pollard

Dundee Business School, University of Abertay, Dundee, Scotland

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LIST OF CONTRIBUTORS

Claudia A. Sacramento


Hemant C. Sashittal

Bittner School of Business, St. John Fisher College, Rochester, NY, USA

Lydia Schleifer

Clemson University, SC, USA

Robert J. Sternberg

Tufts University, Medford, MA, USA

Stefania Testa

Department of Communication Computer and System Science, University of Genova, Genova, Italy

Gail Fann Thomas


Karl Wennberg

Center for Entrepreneurship and Business Creation, Stockholm School of Economics, Stockholm, Sweden

Michael A. West


ACKNOWLEDGMENTS This work was partially supported by the Center for Collaborative Organizations, which was formerly The Center for the Study of Work Teams. The change in name reflects our recognition that collaboration occurs at many levels of organization besides the team level. Innovation also occurs at all levels and depends on collaboration across boundaries. The Center has always considered bridging of the gap between the worlds of research and practice as a primary mission. The success of that bridging is critical for understanding practice and for basing practice on tested theory. The chapters in this book reflect this kind of bridging partnership. We want to acknowledge the help and support of Nancy Gorman. For 6 of the 12 volumes in this series, Nancy has been responsible for communicating with authors, editors, and the publisher, arranging for flow of manuscripts back and forth among these people, educating all of us on manuscript format, arranging for proofing, catching the errors the editors miss, and bringing the chapters, introduction, and preface together in a final assembly to complete a whole for the publisher. Nancy has done an outstanding job under the pressure of significant workload to pull the pieces together into a carefully prepared manuscript. She has consistently taken the initiative to look for new ways to contribute – modeling the attitudes and skills that collaboration depends on. Much of the quality in appearance for this volume is due to her thoughtful work.

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ABOUT THE EDITORS Michael M. Beyerlein is director of the Center for Collaborative Organizations (www.workteams.unt.edu) and professor of Industrial/Organizational Psychology at the University of North Texas. His research interests include all aspects of collaborative work systems, organization transformation, creativity/innovation, knowledge management and the learning organization, and science education. He has published in a number of research journals and has been a member of the editorial boards for TEAM Magazine, Team Performance Management Journal, and Quality Management Journal. Currently, he is the senior editor of the Elsevier annual series Advances in Interdisciplinary Studies of Work Teams and the Jossey-Bass/ Pfeiffer Collaborative Work Systems series. He has authored or edited 18 books. His most recent books include: Guiding the Journey to Collaborative Work Systems: A Strategic Design Workbook (2004) and Collaborative Capital (2005). He has been involved in projects at the Center for Collaborative Organizations (formerly, The Center for the Study of Work Teams) with such companies as Boeing, Shell, NCH, AMD, Intel, Raytheon, First American Financial, Westinghouse, and Xerox and with government agencies such as Veterans Affairs, DCMAO, EPA, and the City of Denton. Susan T. Beyerlein holds a Ph.D. in organization theory and policy with a minor in education research from the University of North Texas. Since 1995, she has been an instructor of business and psychology at Our Lady of the Lake University in Irving, Texas. Susan has served as a research scientist/project manager with the Center for Collaborative Organizations at the University of North Texas, and has been a recipient of research grant awards from the Association for Quality and Participation, the National Science Foundation, and corporate donors. Since 1995, she has co-edited the Elsevier/JAI Imprint annual book series entitled, Advances in Interdisciplinary Studies of Work Teams, and has served as an ad hoc reviewer for The Academy of Management Review. She has been an editor of the JosseyBass/Pfeiffer Collaborative Work Systems series since its inception. Susan has published book reviews on contemporary business offerings in Business and the Contemporary World, and her work has also appeared in Structural xi

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Equation Modeling: A Multidisciplinary Journal, Journal of Management Education, Empirical Studies of the Arts, and Multiple Linear Regression Viewpoints. She is a member of the Academy of Management, Beta Gamma Sigma – the honor society for collegiate schools of business, and Phi Kappa Phi National Honor Society. Frances A. Kennedy is an assistant professor at Clemson University. Her interest in teaming organizations comes after 13 years of experience of industry and public accounting experience, including eight years with Rubbermaid, Inc., where she was extensively involved with the team pilot facility. She has published in the area of intellectual capital and conducts research in lean manufacturing, teams, performance measurement, and decision making. Recent articles are found in Advances in Interdisciplinary Studies of Work Teams and The Collaborative Work Systems Fieldbook. Dr. Kennedy has also presented papers on team strategies and lean manufacturing at numerous international and national conferences. She continues research projects with several Fortune 500 companies.

INTRODUCTION Volume 12 of the Elsevier annual series, Advances in Interdisciplinary Studies of Work Teams, focuses on achieving improving innovation in organizations through collaboration. The chapters in the volume present a variety of methods and settings that explore ways that collaboration can be utilized to enable and enhance innovation. The innovation may be incremental or breakthrough and evident at any level of organization: team, community of practice, project or program, company, joint venture, alliance, partnership, or supply chain. Innovation is defined as creative thinking transformed into useful outcomes, and always depends on a social network. With the increasing complexity and pace of work, the quality of that network becomes more critical. In this volume, we refer to high-quality social interaction in the network as collaboration. We believe creating the context for effective collaboration in an essential core competency of the organization. Working together involves deepening trust among members to address organizational challenges and problem solve, cross-fertilization and constructive conflict around ideas, joint effort, shared vision, transfer of knowledge, and so forth. In contrast to collaboration, we see many examples of isolation at individual, group, disciplinary, department, project, and organizational levels, which are generically termed silos. When a silo structure exists, sharing is minimal, feedback is missing, and opportunities to leverage the available resources – both technical and human – are lost. As innovation becomes the key to competitive advantage at company, supply chain, and regional economy levels, a shift from silos to collaboration becomes essential. World-class levels of performance are impossible without mastery of collaborative methods, processes, and designs, and often business survival itself becomes difficult. At the micro level, the social network depends on behavior within a context. The context includes trust, reciprocity, mutual benefit, shared values, and so forth. At the macro level, the context consists of increasing blurring of the traditional lines among industries, supply chains, economic regions, business ecosystems, and so forth, where effective partnering brings success to large-scale projects. The sharing of critical resources and xiii

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knowledge requires collaboration across boundaries inside and outside of the organization. For example, research and development work often depends on a team with members from multiple disciplines, work sites, and national cultures. The goal is to bring together the expertise of the members from anywhere in the world in a manner that enables them to generate new ideas, solutions, and prototypes quickly and inexpensively. Few companies have mastered the discipline of collaboration well enough to achieve the highest levels of performance in these complex socio-political work situations. Inter-agency collaboration in government is equally challenging, as is supply chain operation where there is an important shift occurring from legal contracting to relationship-based agreements that speed transactions and share risk and reward. The literature on organizational learning argues that collaboration not only transfers existing knowledge across organizations, but also facilitates the creation of new knowledge and production of synergistic solutions. Finally, research on networks and inter-organizational politics suggests that collaboration can help organizations achieve a more central and influential position in relation to other organizations. When the context supports collaboration, shared creation can occur. Competitive advantage depends on creative knowledge generation which in turn depends on shared solutions. Innovation is required in products, services, processes, systems, strategies, and organization. Collaboration is becoming more important in all six of these areas of innovation. Companies are realizing that creating, developing, and delivering new products and services depend on the quality of collaboration in the organizational context up and down the supply chain; not simply in new product development labs. The tendency for companies to form partnerships is reinforced by the desire for new business growth and by the nature of modern economies. For example, industry works closely with universities and institutes to achieve research breakthroughs, companies partner with competitors to win market share and contracts with special projects, and government agencies coordinate efforts in the face of national emergencies. The chapters in this volume explore the motivations underpinning collaborative approaches to innovation and the mechanisms and tools that contribute to the quality of collaborative effort. This volume opens with a chapter by Avan Jassawalla and Hemant Sashittal, exploring the challenge of achieving high levels of collaboration in cross-disciplinary new product development teams. They report on data collected from 14 firms that revealed direct team improvements in

Introduction

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cross-functional communication, implementation of structure and process redesign, and use of liaison role/processes to improve innovation – a more organic solution to the problem of creative knowledge generation. Innovation begins with creativity. In Chapter 2, Cynthia Matthew and Robert Sternberg build on his investment theory of creativity (Sternberg & Lubart, 1991, 1992) to explore the role of leadership in establishing a context for innovation – transforming good ideas into valuable products or process improvements. The challenge of an innovation-based business creates demands on the leadership system. The leaders need skills such as risk tolerance, supportiveness and collaboration and explicitly value novelty, learning, and change to manage such a complex social system. The social system requires upward and lateral communication where ‘‘fast to failure’’ is as valuable as ‘‘fast to success.’’ Leaders must model creativity to start building the culture that supports it, but turnover endangers that basismaking institutionalizing innovation absolutely critical for the long term. Yue Lin and Michael Beyerlein, in Chapter 3, propose that communities of practice is the ideal environment for innovation. These communities emerge around shared interests of the members and operate out of a new set of assumptions about organizing that greatly enhances the ability of the group to collaborate, learn, and create together. Practice provides the situational and historical contexts that give meaning to that behavior. The negotiation and co-creation of meaning provides the dynamic of the community. However, such a dynamic cannot be effectively captured in a modernist framework because of its emergent and nonlinear nature. The accumulated interactions of the autonomous members lead to creation of shared values, norms, and goals leading to a complexity of thought that enables higher levels of learning and creativity. In Chapter 4, Claudia Sacramento, Sophie Chang, and Michael West address how teams can maximize their creativity and how they can subsequently implement their ideas by establishing collaborations with other entities in the organization. Using West’s (2002) model of team innovation, the first part of the chapter focuses on factors associated with promoting team creativity and innovation. Recognizing that the majority of teams do not have the authority to implement their own ideas, the authors draw on realistic conflict theory and social identity and categorization theories to inform their thesis concerning the need to develop collaborative relationships with other teams and managers within the organization in order to gain acceptance of new ideas. The chapter concludes with five recommendations for teams that aim at maximizing creativity and increasing the quality of innovation.

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Frances Kennedy and Lydia Schleifer, in Chapter 5, explore the problem of establishing fit between empowering designs, information that influences or facilitates decision making, and management control systems. With good fit among the three components, an innovation culture can emerge. Innovation through collaboration usually requires significant changes in the design of the organization, such as pushing decision making down the hierarchy to the lowest levels. This results in a major change in how control enhances or inhibits innovation. Support systems such as management control and accounting that govern information access and provide the decision framework must also be redesigned to align with the new design. Change is required in management control and accounting to unleash the power of innovation that teams can provide the organization. In Chapter 6, David Pollard uses a systemic approach to examining the role of Technology Transfer Intermediaries (TTI) in developing and sustaining innovation. Whereas most research revolves around the development of innovations within companies or across geographical boundaries, fewer studies have looked at innovation enabling transfer mechanisms between countries and communities of countries (e.g., European Union), or universities. The ability of entities to assimilate technology combined with its contexts determines the degree of successful innovation. Collaboration provides the bridge for innovation across boundaries. Sam Boutilier and Rod McNaughton raise a series of interesting questions in Chapter 7. If collaboration is a necessary element for innovation and collaboration is enhanced when companies are located within close proximity, does it follow that geographically isolated companies do not innovate? Does location matter? What impact does near costless communication technology have with regard to geographic separation? This chapter uses information from the Survey of Innovation 2003 administered by Statistics Canada to examine this issue. The authors find that it is clearly possible to innovate without collaboration with other companies. However, due to confidentiality issues with regard to the survey, they are unable to draw any substantive conclusions regarding the impact of the innovation and collaboration relationship. The authors raise a host of related ideas for future research. In Chapter 8, Karl Wennberg and Henrik Berglund compare two new business ventures over a five-year period in Sweden that relied on contrasting entrepreneurial strategies. The authors suggest that the contrasting way the entrepreneurs utilized social networks illustrates how the networks provide access to key resources in developing new products and their markets. New firms seem to be handicapped by the size of their resource base. The

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social network provides access to additional expertise, contacts, funding, and so forth, which enables the businesses to grow and flourish. However, the relationships may change as the businesses mature. The two cases described in this chapter provide illustrative stories about the way the social network contributed to the evolution of new product ideas. The new businesses needed to be competent at building an extended partner network and resource base as an important part of their venture development strategy. Innovation has always depended on sharing of information, and advances in technology have made this more rapid and sophisticated. The challenge is in teaching and motivating employees to use the tools available. A number of papers have been published in the past few years concerning the failure of companies to use information technology effectively enough to justify the financial cost of such tools. In Chapter 9, Lina Longhitano and Stefania Testa examine the use of a specific design tool for automobiles and conclude that the way the tool is used determines whether or not collaboration is improved in ways that facilitate innovation. The evidence from the case seems to suggest that effective development and use of the simulation tool activates the social interactions and collaboration and thus enhances innovation processes. In the final chapter, Susan Hocevar, Gail Thomas, and Erik Jansen of the Naval Postgraduate Schools look at the operation of the new Homeland Security Agency through the lens of collaborative capacity. Effective response to major crises like terrorist attack and hurricane damage depends on inter-agency collaboration that leverages dispersed resources. The authors conducted two sets of interviews with managers involved in such crises as Hurricane Katrina to discover how they dealt with the problem of crossing agency boundaries to improve decision making and interdependent task completion to aid victims. A number of success factors were identified, including: shared purpose, willingness to adapt to each others’ organizations, and lateral mechanisms such as social capital. The latter represents trust and effective communication. Barriers were also identified with the implication that there is room for improvement in inter-agency collaboration. Effective collaboration during response to a catastrophe requires preparation before the event. Taken as a whole, the 10 chapters in this volume provide a rich array of perspectives on the relationship between collaboration and innovation. Although the definitions of these two terms vary slightly from chapter to chapter, there is a general convergence of meanings and implications in the authors’ work. Several things are quite clear: (a) innovation is about generating value from ideas and making changes in existing products, services,

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and processes; (b) innovation depends on creative thinking – imagining alternatives and focusing on one; and (c) the quality of working together in an open and trusting exchange facilitates both the thinking and the implementation that create valuable innovations – in industry and government. We hope the ideas shared here will stimulate your own thinking in both research and practice on ways that collaboration can enhance innovation.

REFERENCES Sternberg, R. J., & Lubart, T. I. (1991). An investment theory of creativity and its development. Human Development, 34, 1–31. Sternberg, R. J., & Lubart, T. I. (1992). Buy low and sell high: An investment approach to creativity. Current Directions in Psychological Science, 1, 1–5. West, M. A. (2002). Sparkling fountains or stagnant ponds: An integrative model of creativity and innovation implementation in work groups. Applied Psychology: An International Review, 51, 355–387.

Michael M. Beyerlein Susan T. Beyerlein Frances A. Kennedy Editors

COLLABORATION IN CROSS-FUNCTIONAL PRODUCT INNOVATION TEAMS Avan R. Jassawalla and Hemant C. Sashittal ABSTRACT High-technology firms often institute cross-functional teams to manage product innovation initiatives. The assumption is that (a) creative and successful products from new technologies must reflect the integration of multiple talents, therefore the innovation process will require integration among people who possess them, and (b) when people with multiple talents are placed in teams, they will interact, cross-fertilize ideas, and collaborate to produce creative new products from new technologies faster and cheaper than those produced by alternative structural arrangements. While teams are easy to institute, fostering high levels of collaboration among participants has proved harder in practice. While some teams achieve high levels of collaboration, others merely replicate rivalries that exist in the organization and breed cynicism. Based on our study of product innovation processes in high-technology industrial manufacturers, this chapter discusses the differences between high- and low-collaboration teams. Specifically, we report the key (a) developmental milestones in the process by which groups of people from diverse functional areas become high-collaboration teams and create new products faster and cheaper, and (b) factors associated with participants, Innovation Through Collaboration Advances in Interdisciplinary Studies of Work Teams, Volume 12, 1–25 Copyright r 2006 by Elsevier Ltd. All rights of reproduction in any form reserved ISSN: 1572-0977/doi:10.1016/S1572-0977(06)12001-4

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team leaders, senior management, and the organizational culture that seem to shape the emergence of collaboration in teams.

INTRODUCTION Since Henri Fayol (1916) advocated for division of labor and unity of direction as fundamental principles of management, organizations have accomplished complex tasks by separating work and employees by discipline. When product innovation processes are organized this way, the engineers work with other engineers, production employees operate on the factory floor, and marketing and sales work in the field. Interfunctional communication and interaction is not only limited, but the firm is characterized by micro-cultures and calcified boundaries between us and them. Moreover, the process of value creation is linear-sequential and over the wall. R&D (Research & Development) develops new technologies, prototypes, and tests new product ideas. Then it hands its output over the wall to production engineering. The engineers ensure that the prototype is reproducible in the factory, and hand their output over the wall to production. The factory produces the product and hands it over the wall to sales and marketing, which then engages in a hunt for customers. Even though some firms may still operate this way, we have known for quite some time that such relay races of product innovation are inordinately error prone, slow, and wasteful (Griffin & Hauser, 1996; Sheremata, 2000; Takeuchi & Nonaka, 1986; Zahra & Ellor, 1993). In the previous three decades, a large body of literature dedicated to conceptualizing and empirically testing less linear-sequential and more organic ways of organizing product innovation activities has emerged. One of the principal questions that these writings have addressed can be summed up as follows: How can firms ensure that multiple talents and skills (such as R&D, production, marketing) and key stakeholders (such as customers and suppliers) cooperate and collaborate from the initiating stages of product innovation in order to accelerate the process, reduce cost, and maximize the likelihood of commercial success – even as competition intensifies, technology development accelerates around the globe, and the macro-environment changes (see Ancona & Caldwell, 1990; Clark & Fujimoto, 1991; Zirger & Maidique, 1990)? In particular, scholars have focused on the issue of integration, i.e., the coming together of multiple talents to focus on the common purpose of product innovation processes (see Griffin & Hauser, 1996; Gupta, Raj, & Wilemon, 1986; Kahn, 1996; Song, Montoya-Weiss, & Schmidt,

Collaboration in Cross-Functional Product Innovation Teams

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1997; Souder & Moenaert, 1992). The body of writing is understandably voluminous because the question is complex; and the emerging knowledge is understandably uncertain because its validity depends on an inordinately large number of controllable and uncontrollable factors. Cross-functional teams have emerged as a favored structural mechanism for ensuring high levels of integration among participants in product innovation processes. Our purpose here is to explicate the concept of collaboration in such teams charged with making new product-related decisions and organizing its workflow. We propose that collaboration as a metaphor for interaction among participants in product innovation teams better addresses some of the more persisting and emerging challenges of product innovation in firms that have already taken substantial steps to improve interfunctional integration. Our learning emerges from a review of the literature coupled with a two-stage study of product innovation processes, which we conducted in 14 high-technology-based industrial manufacturers (see the appendix for details). In this chapter, we discuss our learning about the process by which a group of people transform their thinking and behaviors and become highly collaborative. The chapter also identifies factors associated with participants, team leaders, senior management, and the organization’s culture that shape the collaboration achieved on teams.

INTEGRATION AND COLLABORATION Our sample of firms have made a large number of changes in their product innovation processes over the years to reduce cost and accelerate the process. To one extent or another, they have (a) found ways to encourage cross-functional communication, (b) adopted features of flattened and customer-focused organizational designs, total quality management (TQM) and Six Sigma approaches, and processes for assessment and accountability, (c) experimented with structural arrangements including liaison roles, project and product management, matrix structures and concurrent engineering teams to improve coordination and cooperation among participants, and (d) cross-trained key employees and rewarded people for creativity and cooperation with others. Sampled firms are also increasingly entrusting product development related decision making and workflow to cross-functional teams. This structural mechanism is instituted based on the assumption that if people representing the breadth of talent necessary for developing new products from new technologies are put together, freed from the larger bureaucratic

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forces of the organization that otherwise display turf protection and disintegrative tendencies, and encouraged to cooperate from the initiating stages of product innovation, they will cross-fertilize ideas and innovate more effectively and efficiently. In practice, we find that cross-functional teams often engender high levels of integration among participants. In particular, they (a) increase frequency of meetings and information sharing among participants and departments, (b) raise awareness of the reciprocal interdependencies that link the multiple players in the process, and to some extent (c) heighten interest in contributing to decision making and effectively implementing team decisions. Cross-functional teams also appear to help participants overcome physical and perceptual distances, exchange ideas, develop a shared vision, and transform linear-sequential processes to more concurrently organized, organic processes. Our learning about teamwork and the resulting integration and concurrent organization of activities mirrors current concerns about product innovation processes. For instance, a recent industry report notes about Apple, Inc.: Apple employees talk incessantly about what they call ‘‘deep collaboration’’ or ‘‘crosspollination’’ or ‘‘concurrent engineering.’’ Essentially it means that products don’t pass from team to team. There aren’t discrete, sequential development stages. Instead, it’s simultaneous and organic. Products get worked on parallel by all departments at once – design, hardware, software – in endless rounds of inter-disciplinary design reviews. TIME, October 28, 2005, p. 68.

A dismaying yet persisting feature of product innovation processes is that once technological advances occur, and great ideas are discussed among participants, the process of implementation tends to put a damper on creativity. Instead of multiple minds adding to the creativity and innovation, creative ideas get compromised and watered down. Steve Jobs (CEO, Apple Inc.) describes this phenomenon in the following way: You know how you see a show car, and it’s really cool, and then four years later you see the production car, and it sucks? And you go, ‘What happened? They had it! They had it in the palm of their hands! They grabbed defeat from jaws of victory!’ What happened was, the designers came up with this really great idea. Then they take it to the engineers, and the engineers go, ‘Nah, we can’t do that. That’s impossible.’ And so it gets a lot worse. Then they take it to the manufacturing people and they go, ‘We can’t build that!’ And it gets a lot worse. TIME, October 28, 2005, p. 68.

Steve Jobs succinctly describes the challenges faced by our sample of managers who have already made substantial advances in engendering concurrent and organic product development processes, and instituted crossfunctional teams. In particular, they seem challenged by the prospects of (a) nurturing the creative potential of employees and producing innovative


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solutions for customers in ways that stretch the firm’s technical and organizational capabilities, (b) fostering synergistic interaction among highly intelligent and qualified participants and creating new products that reflect much more than a simple sum of talents people bring to the table, (c) developing intellectual capital and accumulating learning within the organization, and (d) ensuring that once cross-functional teams are instituted, they foster high levels of collaboration (see Farkas & DeBacker, 1996; O’Reilly, 1997; Stewart, 1997). We learn that while cross-functional teams increase integration, not all teams are equally collaborative, or equally effective in addressing these new and emerging challenges. Moreover, we learn that the term collaboration (versus integration) is a more appropriate metaphor for describing the extent and quality of linkages among team members. The term collaboration originates in the conflict management literature, and refers to a process by which competing forces transcend diverse agendas and achieve win–win outcomes (Thomas, 1992). It also refers to a metacapability, i.e., the learned ability to renew skills and adapt to a changing environment (Liedtka, 1996). While the key concern with integration is about overcoming departmental, structural, and systemic barriers to interaction, communication, and coordination, the key concern with collaboration is about harnessing the efficiencies and synergies of the team’s multiple orientations and skills, and about producing outcomes that reflect much more than a simple sum of talents (see Table 1 for key differences between integration and collaboration). In the following discussion, we identify and briefly discuss the key milestones in the cognitive, emotional, and behavioral development of highly collaborative teams. To derive this learning, we (a) rank ordered teams based on their relative success, i.e., the extent to which they achieved their time-tomarket and cost as well as sales and marketing objectives, and (b) compared and contrasted teams that were ranked high with those that we ranked low (see Table 2 for a brief comparison of low- and high-collaboration teams).

Developmental Milestones of Collaboration New product cross-functional teams (henceforth teams) differ in terms of their interpersonal dynamics, decision-making processes, and actions. From participant voices, we identify four clear milestones in the cognitive, emotional, and behavioral development that occurs among groups of people who eventually transform into a collaborative, high-performing team (see Fig. 1).

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Table 1. Differentiating Integration from Collaboration as Metaphor for Cross-Functional Linkages in Product Innovation Processes. High Levels of Integration is about

Early involvement of participants with multiple orientations who take collective responsibility. High levels of integration can occur even when participants are socially distant, and hold unequal power An improved understanding of cultural, perceptual, and behavioral differences of participants. High levels of integration do not require explicit discussion of all agendas Frequent meetings, greater extent of communication, development of shared vision, and fewer conflicts. High levels of integration can be characterized by decisions that do not receive universal and enthusiastic support from all participants High levels of cooperation and coordination of activities among participants. Integration does not require the learning of dramatically new behaviors

Additionally, High Levels of Collaboration Can Lead up to, or Result in High levels of at-stakeness where all participants function as equal voting citizens with equal power and privileges

High levels of transparency; participants are continually involved in making explicit all assumptions and aspirations. There are no hidden agendas High levels of mindfulness; participants internalize the differences that exist among participants, and make decisions and take actions based on this understanding. Team decisions enjoy emotional commitment and support of all participants High levels of synergy; participants engage in constructive conflict and harness the creativity that can result from interaction among a breadth of voices and talents

As the figure shows, at-stakeness, transparency, mindfulness, and synergy refer to four distinct developmental milestones associated with (a) the learning of increasingly more complex ways of thinking and behaving, and (b) higher levels of efficiency and effectiveness in product innovation processes. Each stage emerges from clear antecedents, and results in new learning (see Table 3). We discuss each of these developmental milestones next. At-Stakeness. The first developmental milestone on the way to high levels of collaboration relates to participants’ equal and high levels of personal commitment to the team’s intents (Liedtka, 1996). Cross-functional teams reflect high levels of at-stakeness when all participants are equally involved in the team’s decision making, commit equally to the implementation, and collectively and equally share responsibility for the outcome. In high-tech


Table 2.

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A Comparison of Low- and High-Collaboration Product Innovation Teams.

The Product Innovation Process in the Least Collaborative Teams (and their Firms) was Characterized by

The Product Innovation Process in the Most Collaborative Teams (and their Firms) was Characterized by

Inequalities in the distribution of power among participants Participants and functional groups are largely isolated. They import and export ideas and outputs through gates and gatekeepers The concern for technology (and technological solutions) overrides concern for interpersonal interactions and dynamics

Equal distribution of power among the participants in the process Boundaries among functional groups are highly porous. All participants function as boundary spanners The concern for interpersonal interaction and dynamics is as high as the concern for the technology and technical solutions Imperceptible pecking order of status and stature

Noticeable pecking order of decision makers in terms of their status and stature, and their influence over new product-related decisions Participants hold strong affiliations with their functional groups, and define their participation in terms of representatives charged with protecting their departmental turf Notable social and perceptual distances among participants Conflict is unproductive and results in stalemates or compromises Interactions among participants are entropic; they deteriorate in the absence of directives from a higher authority

Participants hold strong team (and weak functional) affiliations. The concern for departmental turf is imperceptible Notably narrow perceptual distances among participants Conflict is mostly productive, and results in creative new solutions Interactions are self-initiated, intrinsically motivated, and synergistic

firms, progress toward at-stakeness occurs when the dominant player in product innovation (often R&D) begins to ask others to share responsibilities, and asks them to perform product innovation related tasks. Attempts to include others and share power are motivated by the interest in (a) accelerating the innovation process and meeting cost and time constraints, (b) ensuring that blueprints are reproducible in the factory, (c) finding ready buyers once the product is ready for shipment, and (d) sharing blame for cost over-runs and eventual failure (if and when that occurs). Such actions also indicate a somewhat growing awareness within the firm that customers want solutions that reflect an integration of the firm’s skills and competencies.


Product innovation efficiency and effectiveness

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HIGH

SYNERGY MINDFULNESS TRANSPARENCY AT-STAKENESS

LOW LOW

HIGH

Complexity of Behavior

Fig. 1.

Developmental Milestones in the Process of Transformation of Highly Collaborative Teams.

In cross-functional teams led by R&D, at-stakeness improves when representatives of other functional groups such as marketing and manufacturing begin to see direct connections between the contributions they are making to new product discussions and the ultimate decisions implemented by the team, and task performance, and the goals ultimately achieved by the team. At-stakeness improves markedly when a leader, free of functional group affiliations, and skilled in managing the interpersonal interactions within the team, is selected by senior management. Without the team leader’s commitment to equal distribution of power among participants, high levels of at-stakeness largely fail to emerge. The contrast between poorly integrated and highly collaborative teams shows clear differences in terms of the at-stakeness. In the latter, all participants are equally involved from the initiating stages of product innovation. Key decisions are made by consensus. In one team, leadership was rotated among participants, and resulted in heightened interest in participating and committing to team decisions. In poorly integrated teams, on the other hand, hierarchies of power and authority get in the way of shared ownership among members. For instance, in one firm, the R&D representative serves as the appointed leader in the team. The unequal distribution of power has resulted in low involvement and finger-pointing when problems arise. The representative from the manufacturing department laments: Every week we get calls from the R&D representative saying, ‘‘Oh, here is one more part.’’ So, we’ll go out and build it and we’ll find out – guess what – there is another part he missed. Now if we were involved a little bit more up front, it helps because if there was an assembly missing from R&D’s plans and we knew it because we’d worked on it, we could say, ‘‘Now wait a minute, what about xyz assembly? You never gave us anything for that.’’


Table 3.

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Antecedents and Learning for the Developmental Steps of Collaboration in Teams.

Antecedent Structure and Processes

Stage in Transformation

Structurally divided organization, linear development of new products (relay races). Key managers function as liaisons

Low levels of collaboration

Institution of cross-functional teams. Increased inclusion of marketing and production groups from the initiating stages of decision making

At-stakeness

Participants begin sharing information about their aspirations and orientations. They begin to use hard data in their communication, and develop a shared understanding

Transparency

Communication patterns favor discussion of hidden agendas. Locally made decisions get approval and support from all participants. Trust begins to emerge

Mindfulness

Learning and Felt Need

Learning: Relay races and over the wall product innovation processes are error prone and slow Felt need: To gain cooperation and equal commitment from participants, sharing power is essential Learning: Participants emotionally commit and take ownership when they share power with others Felt need: To explain one’s own, and understand others’ constraints, motivations, and interests is essential Learning: Information sharing and reliance on hard data create a transparent environment, and promote an integrative understanding of the breadth of agendas and orientations represented within the team Felt need: To ensure that decisions and actions begin to reflect the emerging transparency Learning: Trust is critical for gaining emotional commitment and risktaking initiative from team members Felt need: To take advantage of the diverse orientations among participants, when each is emotionally committed to supporting the team’s decisions

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Table 3. (Continued ) Antecedent Structure and Processes High levels of trust within teams encourage constructive conflict, risk taking, and initiative

Stage in Transformation Synergy

Learning and Felt Need

Learning: Quantum leaps in innovation occur upon synergistic interaction, and search for solutions that stretch the thinking of all participants Felt need: To harness the potential to discover new and serendipitous solutions that gain the emotional involvement of customers

Transparency. Communication problems often arise in cross-functional teams because of variance in participants’ vocabularies, worldviews, orientations, and aspirations. Cross-functional teams become transparent when each participant develops a high degree of awareness of these variances, and this awareness becomes embedded in their tacit knowledge. Transparent teams engage heavily in communicating with each other about the technical as well as sociopsychological issues of the participants. Transparent teams have no hidden agendas; information is freely shared and all decisions that affect the team are made jointly (versus those made by a subset of members). This milestone in the team members’ cognitive, emotional, and social development is associated with fairly complex changes in their belief systems and attitudes. In particular, teams begin to gain transparency when they accept that a shared understanding is essential among participants aiming for common goals, and issues arising from internalized, unarticulated differences in agendas and orientations get in the way of effective decision making and implementation. A high-collaboration team member describes how his teammates express divergent ideas and disagree but do so in ways that are healthy: It’s two people who are persistent in their pursuit of a common objective, who are able to put personalities aside if necessary and confront each other over issues where there’s disagreement in terms of what the priorities are and they can walk away from that session feeling the same high regard for each individual, the same respect and self-esteem. The people who want to stay away from that avoid issues hoping they’ll go away, and that is where we have the most trouble.


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Steps toward transparency are often rooted in self-serving actions motivated by the need to define one’s own boundaries, and make others aware of one’s constraints and interests. This process is accelerated when participants consciously and deliberately act to tell others what they want others to know about themselves – motivated by the need to gain empathy and influence decision making. Cross-training of participants also seems critical for the emergence of shared understanding of multiple orientations. Team leaders play a critical role in fostering high levels of transparency. Reducing the distances and collocating participants to encourage personal, face-to-face interaction (versus telephone and e-mail) seems to help. In transparent teams, there is no deal making between leaders and a subset of participants; decisions are made only after issues are discussed openly with all team members. Transparent teams have no coalitions jockeying for power, all participants appear to coalesce around common and well-articulated interests. Early involvement of key contributors seems to accelerate the emergence of transparency as well. In one notably transparent team, representatives of suppliers and the union are engaged from the initiating stages of new product-related decision making. In low-collaboration teams, by contrast, infrequent interactions among participants result in low levels of comfort with open communication. Team members invariably hold untested assumptions and negative stereotypes about each other, and harbor suspicions about others’ motives and agendas. Mindfulness. Some at-staked, transparent teams take the next step in the cognitive, emotional, and social development toward collaboration when they begin to display signs of mindfulness. Team members are mindful when their actions reflect the breadth of concerns, orientations, and agendas that exist in the team – i.e., their actions reflect the transparency achieved within the team. Several behaviors signal the emergence of mindfulness. Team members’ autonomous and local decisions and actions begin to make sense to others because they begin to reflect the breadth of concerns that exist within the team. Autonomous decisions and actions begin to gain the enthusiastic commitment of others. When asked, team members can articulate why others are acting the way they do, and can speak of their emotional commitment to supporting the actions of others. The development of mindfulness is associated with new ways of thinking and defining the environment, and new theories of action. Participants learn that implementation of complex goals requires high levels of emotional commitment from people over whom they have no control. While the origins of mindfulness appear rooted in the concern for avoiding errors and

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rework, participants eventually learn that healthy relationships are about interdependence and choice. Dated beliefs about turf protection and functional loyalties are replaced by a sense of shared ownership and commitment. A high-collaboration team member, describing the high levels of mindfulness that emerged, reports: I would say what the organization has learned is a greater appreciation for what goes on in other boxes. All representatives of functional groups on the team have a better appreciation now for what the others do. Now we need to go past awareness, develop detailed knowledge, and translate that knowledge into a way that we can all interact together more efficiently.

Training in teamwork skills as well as the team leader’s coaching to ensure that members incorporate diverse orientations into decisions, seem to contribute to increase in mindful actions. Team leaders free from functional affiliations and focused on encouraging members to continually interact and seek mutually beneficial solutions seem to help. Mindful actions tend to breed higher levels of mindfulness; the demonstration of concern for others’ idiosyncratic orientations provides strong reasons to participants in favor of committing to the team’s collective intent. Mindfulness can radiate from within the team into its larger ecosystem as well. A team leader from a highly collaborative team notes that he continually quizzes departmental heads of production, engineering, and marketing functions so that the team’s decisions can fit their realities as well. By contrast, low-collaboration teams do poorly in terms of engendering at-stakeness and transparency. Hence, they fail to generate the level of trust, and the faith in interdependence necessary for the emergence of mindfulness. Synergy. This developmental milestone refers to the team’s capacity for intense interaction, cross-fertilization of ideas, and more importantly to the growing comfort with constructive conflict. Without a team that is emotionally and cognitively matured to engage in high levels of constructive conflict, it is difficult to produce results that reflect much more than a simple sum of what participants bring to the table. Synergistic interaction results in quantum leaps in the team’s ability to conceptualize and implement creative solutions. Synergistic interactions, the post-mindfulness step in their cognitive, emotional, and behavioral development, have multiple roots including the concern for identifying alternatives that stretch everyone’s thinking each time they are called to make decisions and take action, and shedding existing ways of thinking because they seem to result in currently known solutions in favor of new ways of thinking that promise new results. Participants begin


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to exhibit high levels of skepticism and intolerance for status quo and existing ways of thinking. Synergies also emerge when team leaders favor experimentation and tolerate failure. In one team that displayed high levels of synergistic interaction, the team leader describes how he shrugged off skepticism and experimented with two-way radios to improve real-time communication among participants: The reaction from others when I suggested two-way radios to connect team members was, ‘‘It will not work, it can’t work, we’ve never done that.’’ Well, I went ahead and did it. Now they won’t give up the radios because now they could talk to each other. Although we all had beepers, you can’t rely on that and the telephone. It’s too late. I need answers now, you need the person who has a problem on the line with the person who has a solution. So, we had to break some paradigms there in order to get that done.

By contrast, synergy is entirely absent in low-collaboration teams. Outputs reflect the inordinate compromises that occur among people unwilling to abandon old agendas and learn new ways of interaction.

Impact of the Participants The extent of collaboration achieved in teams depends strongly on the participants, i.e., their propensities to change, cooperate with others, and attribute trust to others. We discuss these participant-related factors next. Propensity to Change. All participants in our study favor change, and seem acutely aware that producing innovative products requires the firm, the team, and individuals to change their behaviors. However, most appear to implicitly believe that it is others who need to change. Despite assignment to the team, a fourth of participants report no (or minor) changes in their behavioral patters. That is, they report virtually no difference in their activities before and after their assignment to the team. About half report increased involvement in information sharing, largely in terms of sharing their technical insights and expertise with others, and reporting the occurrences in the team back to their home departments. Only about a fourth of the participants, also associated with high-collaboration teams, appear to change their attitudes, develop new mindsets, and learn new behaviors. Propensity to Cooperate. A fourth of the participants indicate that they prefer to work in isolation and communicate with others on an ‘‘as needed’’ basis. Another fourth of the participants seem interested in meeting with others and sharing information only when important issues arise. Only a small fraction (15%) report that they discuss every idea within the team,

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identify as much with the product innovation process as they do with their home departments, care about the interdependent relationships in which they find themselves, and spend energies on trying to coordinate actions and develop solutions jointly. Hence, for a majority of participants, teamwork produces low levels of collaboration. Most seem to view themselves (and their departments) as more willing cooperators, and attribute low collaboration to the proclivities and actions of others. For most, their stated intents about cooperation fail to translate into sustained actions. As such, individuals’ propensity to cooperate appears to shape the collaboration that emerges within teams. Level of Trust. Mindfulness and synergy are milestones achieved almost exclusively by participants who can interact with others and build trust. Low-trust teams are also the ones that meet infrequently, fail to resolve conflict, engage in turf-protection behaviors, and report markedly low levels of collaboration. In low-trust teams, despite agreements, participants often stall during implementation of ideas. Conversely, higher level of collaboration appears linked with greater attribution of trust among participants. By attribution of trust, we refer to the attribution of competence and responsibility to others, and to the belief that others are open to new ideas and eager to contribute to common interests. In high-trust teams, participants appear more willing to discuss their concerns, errors, and weaknesses, more eager to ask for help, and more likely to propose risky solutions and face the scrutiny of their peers. They are also more likely to provide honest critique to the ideas of others. In high-trust teams, there are common beliefs around the notion that all members are insiders and interested in working toward the team’s (as opposed to their department’s) benefit.

Impact of Leadership Collaboration emerges in teams largely as a function of the choices made by the leadership and their carefully considered actions and initiatives. In particular, team leaders seem more effective in fostering collaboration when they take initiative to (a) protect the team from the bureaucratic forces of the larger organization, (b) encourage risk taking and tolerate failure, and (c) coach team members to share information and seek input from others before making decisions. At-stakeness improves when team leaders work with department heads to carefully select team members on the basis of their technical as well as interpersonal skills, regularly schedule meetings and emphasize information sharing, and lobby senior management for resources


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to train members – both for technical and team skills. Transparency and mindfulness appear to improve when leaders collocate team members, role-model desired behaviors and visibly maintain contact with departmental heads, and regularly attend meetings in every department (i.e., visibly connect with outside constituencies), and foster constructive conflict.

Impact of Senior Management The extent of collaboration within teams appears strongly associated with senior management’s resource allocation choices reflected in (a) the organizational priority of product innovation, ranging from low to high, (b) the extent of decentralization, and (c) the process by which team leaders are selected (please see Table 4 for relevant actions). Priority of Product Innovation. The sense of urgency about product innovation that senior management conveys via their action, and the priority they attach to the product development process send powerful cues to participants, and strongly impact their propensity to cooperate and collaborate with others. When and why senior management initiates and allocates resources to the team appears to signal the priority they attach to product innovation as well. Collaboration is lower when resource allocation to product innovation is a defensive move against competitors, or when cost saving and reduced time-to-market are its principal drivers. Collaboration is considerably higher when senior management is interested in creatively utilizing every participant’s potential. Higher priority of product innovation is signaled when senior management (a) formally deliberates on the best structural mechanisms needed to manage product innovation related decision making and organizing its workflow, versus ad hoc or knee-jerk responsiveness, (b) is equally likely to support innovative ideas originating from customers, marketing, production, or other functional groups as the ideas emerging from R&D, (c) defines product innovation as the principal vehicle for organizational growth and survival, and (d) invests in people who, in addition to possessing technical skills, possess strong interpersonal skills as well. In the most collaborative of firms, innovation is part of the organizational culture, and a central part of what the firm does. Senior management seeks opportunities to develop new technologies and scans multiple venues (customers, trade shows, competitors) for ideas. The firm is significantly engaged in re-thinking and re-organizing its systems and processes for product innovation. On the other hand, the firms with poorly integrated product innovation processes appear defensive in their initiatives,

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Table 4.


What Firms do to Foster Collaborative New Product Teams.

To Increase y At-stakeness

Transparency

Mindfulness

Synergy

Collaboration in general

Firms y Select a cross-functionally trained person with technical as well as interpersonal skills as leader Involve all participants in decision making from the initiating stages of the product innovation process Ensure that all participants have equitable access to information and resources Select participants with technical as well as interpersonal skills Emphasize frequent formal meetings. Organize forums for participants to share information Collocate participants and functional heads View external stakeholders (such as lead customers and suppliers) as insiders, and capable of being engaged in a co-creative endeavor Invest in training participants for improved interpersonal and teamwork skills Sponsor/invest in activities that build trust among participants. View membership as a privilege, and remove participants from teams unable to trust others, or to commit to the team’s collective intents Ensure that the breadth of talent and skills necessary for product innovation are included in the team Grant teams (and leaders) the autonomy to select (and deselect) team members Avoid edict and directives, and consciously decentralize decision making to the team View organizational change as necessary, and as an energizing and revitalizing force View teams as complex structural mechanisms; believe that effective teamwork requires the learning of new and unlearning of old ways of thinking and doing View product innovation as a high-priority organizational activity, and install processes to evaluate new product ideas, regardless of their source

i.e., serious discussion about innovation begins when customers threaten to switch suppliers. In our sample, the lower priority of innovation appears to result from a combination of the following (a) a concern for protecting current investment in technology, (b) a preponderance of firefights and kneejerk responsiveness that prevents the firm from focusing on the future, (c) periods of undercapitalization which prevent the firm from allocating capital to risky (and longer term) innovation processes, and (d) relatively lower rates of product obsolescence that lull firms into a false sense of security.


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Extent of Decentralization. The extent of autonomy and access to information and resources made available to the team is closely linked to the collaboration they eventually achieve, i.e., higher levels of decentralization appear associated with higher levels of collaboration. In our study, collaboration is notably lower when senior management (a) tightly controls resources and information, (b) views itself as the primary decision maker and the team as the primary implementer, (c) subjects all team decisions to centralized scrutiny, either their own or that of a designated functional group (such as R&D), and (d) allows one functional group (mostly R&D) to dominate the product innovation related decision making, and to direct and perform most of its activities. Conversely, collaboration is notably higher when teams are empowered to make their own decisions and organize the new product-related workflow. Nature of Leadership. When we rank-order the teams in terms of their collaboration, we find an interesting pattern in terms of who leads the crossfunctional team, and how they are selected. We find poorly integrated, lowcollaboration teams in firms where R&D’s influence on product innovation processes is notably higher than others’. Product innovation processes dominated by R&D are either apt not to use cross-functional teams, or routinely appoint one of their own as a leader when one is formed. When the responsibility of product innovation is more equitably shared by other functional groups, cross-functional teams are used more often than not, and led by a leader carefully selected by the senior management. The differences between an R&D appointed leader and a senior management selected leader are worthy of note. Appointed leaders signify the relative importance of the appointing department (e.g., R&D), and the persisting inequality in status among participants. Appointed leaders consult with participants when necessary, but do little to engender cross-fertilization of ideas. They tend to view the team as a vehicle for gaining compliance from participants in the innovation process. Appointed leaders are less likely to represent an interested, enthusiastic bunch of participants engaged in synergistic interactions. Leaders are often selected by senior management for their technical as well as interpersonal skills, hold no clear functional group affiliations, and often symbolize equality of status and stature of all participants. By selecting such leaders, senior management communicates that the collaborative intents and non-functional affiliations determine product innovation outcomes. Additionally, the process of selecting the team leader seems to heighten senior management’s commitment to the leader’s (and the team’s) success. In such instances, they seem more likely to grant requests for

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resources and new initiatives. A team leader selected for his technical as well as interpersonal skills notes: It’s clear that this (new product development) is a fairly major investment of resources, it’s highly risky, and involves a lot of complex interactions. So, the organization goes to work and says, ‘‘Who is the best qualified person to meet the requirements of the position (of team leader)?’’ y our V.P. y is responsible (and coordinates the selection of the team leader). But the key players who would be involved (in the selection are) y business managers for both our North American business and our European business. They would review the (team leader) candidates, and ultimately my boss’ boss – the general manager of this division, would have to buy-off on me as a candidate.

Impact of Culture Participants from all teams can articulate the importance of cooperating with and trusting others, the value of attaining transparency and mindfulness, and the worth of constructive conflict. Only a fraction can translate this apparent awareness into sustained actions that result in high levels of collaboration, and produce substantial improvements in product innovation outcomes. Our interest in explaining this persistent and glaring gap between knowing and doing led us to identify distinctive cultures of sampled organizations, to see whether we could explain why some and not all teams can translate their convictions about collaboration into actions. In particular, we focused on the key features of their psychosocial environment including the values, beliefs, and assumptions, and on their physical artifacts including observable rituals, physical symbols, mythologies, and vocabularies. We next discuss the interesting patterns in their stories, rituals, and physical symbols that seem to differentiate high-collaboration teams from others. Stories. Critical incidents and significant events in the company’s recent past are often recounted as cautionary tales. In high-collaboration teams, stories emphasize the failure of the old ways and the need for dramatic changes. Near-death experience for the firm, loss of key customers, and drastic action tend to be the essence of these fables, and hold distinct lessons for listeners. For instance, in one firm with a highly innovation-supportive culture, multiple product innovation participants talk about ‘‘the old way’’: Oh y the old way y we almost went bankrupt here. Back in the middle ‘80s y we had a product that we tried to launch that almost busted us. Because there was no team, it was throwing it (all decision-making and work flows) over the wall. It was late, everybody had their own agenda, everybody had their own little domain. Everything was fragmented and nothing was coming together. And the customer was about ready to say ‘‘Hey, we’ll go someplace else.’’


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The stories in innovation-supportive cultures also highlight individual initiative and risk taking that apparently leads to great benefits for the organization. The stories explain how past importance given to participants’ technical abilities was less useful than the new selection criteria that places equal emphasis on interpersonal and team skills. Senior managers and team leaders often tell stories that describe how they overcame participants’ resistance to change. The common themes underlying these stories are about building a climate of openness and trust, involving participants early and often in decision making, and encouraging intense information sharing. Team leaders also narrate stories about initiative they took and unorthodox ideas they implemented, often overcoming skepticism, and eventually convincing participants to break status quo and try new things. A team leader who encouraged participants to think outside the box and involve assembly line workers to solve a major problem notes: And that is new and different; we’ve never done that before. We put together an assembly team of hourly people and they designed and developed the assembly line. They built the assembly line. They decided where the material handling was going to be, how the material was going to be handled, what kind of machines were needed to put it together. They did it themselves, instead of a group of engineers sitting up in the office laying out this beautiful assembly line and then turning it over to the workers and saying, ‘‘Here, you make it go, and look at this wonderful assembly line.’’ The workers would then not have any ownership because they did not have input. Three and a half years ago when we started programming, we put this group together and said, ‘‘You meet as often as you want to meet, but it is going to be your line. You lay it out the way you want.’’ They did that, and that line down there today is a result of those workers doing it. That was different, and had never been done before. We had to break some paradigms there in order to get that done.

The contrast is particularly stark when we look at the culture in organizations with low-collaboration teams. Stories are about dominant functional groups and laments about the lack of appreciation received. Stories are often self-aggrandizing; they portray the tellers as intelligent and reasonable heroes, and others as uncreative, error-prone villains. Stories perpetuate negative stereotypes and promote competitiveness. For instance, in one such firm, the R&D function dominates the product innovation process and makes all key decisions without involving others. This has reinforced the negative stereotype that the marketing and manufacturing departments already hold about R&D. There is widespread resentment and the stories recount R&D’s failure to listen not only to their colleagues within the organization but also to customers. A marketing manager notes: I think R&D can be so driven from a non-customer satisfaction standpoint that they lose sight of what their job is all about and that’s satisfying customers y. Give engineers a set

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AVAN R. JASSAWALLA AND HEMANT C. SASHITTAL of problems and they’ll work their way through it, and as soon as they come out with the very first fix, they’ll stop and say ‘‘okay! (rubbing his hands together) Design’s done. It’s going to work everywhere.’’ And you might say, ‘‘Well, the problem came from Brazil and you fixed it, but I have another problem here from Korea, and I can tell you that your fix for Brazil won’t work for Korea.’’ And they look at me and say ‘‘But it’s the same part. It’s got to work.’’

In low-collaboration cultures, stories also emphasize the lack of transparency and the resulting mindlessness perpetuated by the dominant functional group. Tales abound of missed opportunities and deliberate insensitivity toward other team members. A manufacturing manager notes: (New product development processes would be) smoother if they (the team leader and the R&D department he represents) knew the processes better and the limitations of the processes; and if they knew the effect on other departments of changes in certain demands and certain (customer) requirements. Sometimes we have to spend quite a lot of time working on something and get something that will work y and sometimes it (the leader’s idea) just doesn’t pan out. Sometimes y up front you know it’s impossible and it’s going to be very very costly and time-consuming to pursue, and yet you have to pursue it and find out down the road that it really isn’t that important y. It would have been nice if they had known what it would cost and compare that to the importance of the feature. We could have saved a lot of time.

Rituals. Rituals relate to formal or semi-formal, regularly scheduled activities that become venues for interaction and information sharing among participants. They are often the setting where stories are told and beliefs and values are reinforced. We find cultures of collaborative teams characterized by a regular schedule of formal meetings where participants share information, express disagreement, and manage conflict. Regularly scheduled meetings ensure that all voices are heard and all functions are included in decision making. A regular schedule of meetings seems critical for creating a new team identity and overcoming the ‘‘us-versus-them’’ mentality. Training programs also emerge as important rituals for building collaboration. In one firm, a leader has taken his team to an off-site team-building program facilitated by a consultant. Training programs function as a symbol of the senior management’s commitment to team work. In another firm, the meetings for implementing total quality management (TQM) principles, and associated training programs led by senior managers have strongly symbolized the importance of involving multiple functional groups, and the learning of new attitudes and behaviors. The marketing manager describing the cascade training in TQM in this firm notes: What helped us a lot was TQM. We followed all recommendations, and probably the best one was to train the executive management of the organization y formally train them all in TQM principles and team building. And these people (senior managers)


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conducted the training seminars for the rest of the organization. And that tells everyone that management takes this seriously. You better learn this stuff; we’re not just going through the motions.

In contrast, while the low innovation-supportive cultures hold formal meetings, they are markedly different in tone. In one firm, for instance, meetings are organized and conducted by the senior managers (V.P. and department head) of the R&D department. Because the R&D representative is the team leader, these meetings start under the guise of ‘‘collecting information’’ and end with finger-pointing. They also include communication of R&D mandates about how others should cooperate and comply with R&D’s standards. Discussions deteriorate to ‘‘what went wrong,’’ and ‘‘who is to blame.’’ Similarly, training and education is discussed, but rarely implemented. In one low-collaboration team, marketing’s efforts to initiate training is strongly resisted by the design engineering group that sees its role primarily as the creator of new technology. Because they believe that they exist to add value via their technical skills, they view the proposed training in team skills as a good idea in theory, but impractical, unessential, and time wasting. The design engineering head, explaining that his people are too busy applying their technical expertise and cannot waste time on cross-training and team building, notes: Those kinds of education (from workshops) don’t sink in when they are a small part of your job. (The marketing department’s head) has often mentioned that he wants (his people) to get more involved in what we do y But to learn anything significant in the field is going to cost time, and nobody’s got the time for that kind of education. (I’ve had) y some very frustrated engineers come to me just overwhelmed. So (the workshops and meetings are) a nice ideal, and it’s one that’s talked about and promoted verbally here, but there isn’t any way of doing it. Unless we work two shifts, one for education and one to get the job done.

Physical Symbols. Concrete objects, physical location and layout, displayed trophies, and documents are examples of the artifacts that often communicate the organization’s priorities. We can identify several physical symbols in innovation-supportive cultures that connote the value placed on equality among participants. In one team, members carry a laminated, wallet-sized mission statement developed collectively by the team. Members are quick to display and refer to this symbol of common commitment. A team leader who made multiple references to this symbol notes: Each team has a mission statement. We (the team) came up with our mission statement. Everybody’s got a copy of that. We got it reduced and laminated so people can carry ‘em around in their planners. And I pull these out in meetings. And it got so that people

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AVAN R. JASSAWALLA AND HEMANT C. SASHITTAL would pull them out. If there was some conflict or something, people would go, ‘‘Hey, our mission statement says this and this and this.’’

The physical location of participants serves as a powerful symbol as well. In one firm that fostered a high-collaboration team, senior management has placed department heads in adjacent offices. This has increased communication because they can now walk into each others’ offices without resorting to memos, e-mail, and phone calls (they do not know the other’s phone number). In another firm, the team leader has collocated team members in a large room to facilitate communication. Isolating them from their departmental locations and forcing them to coexist in a small space has helped increase cross-fertilization of ideas. The team leader, explaining the merits of collocation, notes: First thing you gotta do is to physically collocate these guys away from the functional groups and managers. Our functional managers and folks are located on the second floor of this building. This team is locked away in a room on the first floor, all collocated, and the more you can do that the better off you are. Because that gets them away from mother telling them what to do and gets them out on their own where they have to think about what to do for themselves. The second thing that really works is to do what we’ve done which is once you get them into that room, you intermix them. Don’t let all the manufacturing guys clump together in one corner of the room and the engineering folks in another corner of the room. Get ‘em in the same room sitting side-by-side and back-to-back.

In low innovation-supportive cultures, physical artifacts symbolize distances among participants. In one firm, team meetings are held in the R&D facility located a mile away from the facility in which both the production and marketing departments are housed. Any agreements that emerge in team meetings are effectively undone during the conversations that occur during the long walk that the rest of the team has to take on their way back to their offices. The marketing manager from this team, describing the negative stereotypes that resume from the physical distances, reports: Right now we’re separated by a mile, which could be the other end of the earth for all it matters y. You can’t just go into an engineer’s office y and say, ‘‘Look at this problem.’’ So, the only time that we really go over to see them is when we have a real problem. The only time engineering sees Joe is, ‘‘Okay, Joe’s got a problem.’’ So, now when you put Joe into the meetings, it’s like, ‘‘oh, it’s that complainer.’’

CONCLUSIONS While cross-functional teams are easy to institute, and can do much to alleviate problems associated with the complexity of product innovation,


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only a handful undergo the cognitive, emotional, and behavioral transformation necessary for high levels of collaboration that produce creative and successful new products, and they can rarely overcome systematic and deepseated problems created by isolation, distrust, and divisive functional groups and fragmented organizational cultures. Where we find low-collaboration teams, we also find little effort on senior management’s part to articulate the rationale for teamwork, or institute needed organization-wide changes. Team members wonder aloud about the wisdom of instituting teams when one department continues to exert the most influence on product innovation processes. The result is a growing cynicism about teams and suspicion about the motives of senior management. While these firms have adopted teams, they have failed to foster teamwork. In firms with high-collaboration teams, we find active signs of organizational changes – only one of which is the institution of cross-functional teams. In our sample, changes include relocation of a division in a singlestorey structure, placement of departmental heads in adjacent offices, and regularly scheduled meetings for joint discussion of every new product idea emerging from individuals. Innovation-supportive firms develop new procedures for feedback, assessment, and accountability – and significantly intensify cross-functional communication. Moreover, senior management in such firms seems aware of the time and effort that collaboration requires and expects resistance to change. They recognize that teamwork cannot occur if one functional group dominates product innovation decision making, or if participants fail to receive training for interpersonal and teamwork skills. In low-collaboration firms, much of the dissatisfaction and cynicism, when it arises, is rooted in unrealistic expectations that (a) just because people are placed into teams, they will collaborate, (b) a team retrofitted in a compartmentalized organization will, in and of itself, overcome people’s tendency to stay loyal to their functional affiliations and lead them to abandon concern for turf protection, and/or (c) the team will insulate participants from the disintegrating forces and departmental rivalries that characterize the larger organization. Cross-functional teams are not bandaids to organizational problems, instead they tend to accurately reflect the interpersonal and departmental dynamics of the larger organization.

REFERENCES Ancona, D. G., & Caldwell, D. (1990). Improving the performance of new product teams. Research-Technology Management, 33(2), 25–29.

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Clark, K., & Fujimoto, T. (1991). Product development performance: Strategy, organization, and management in the world auto industry. Boston: Harvard Business School Press. Farkas, C. M., & DeBacker, P. (1996). Maximum leadership: The world’s leading CEOs share their five strategies for success. New York, NY: Henry Holt & Co. Fayol, H. (1916). Industrial and general administration. Paris: Dunod. Griffin, A., & Hauser, J. R. (1996). Integrating R&D and marketing: A review and analysis of the literature. Journal of Product Innovation Management, 13(3), 191–215. Gupta, A. K., Raj, S. P., & Wilemon, D. L. (1986). A model for studying R&D-marketing interface in the product innovation process. Journal of Marketing, 50(2), 7–17. Kahn, K. B. (1996). Interdepartmental integration: A definition with implications for product development performance. Journal of Product Innovation Management, 13(2), 137–151. Liedtka, J. M. (1996). Collaboration across lines of business for competitive advantage. The Academy of Management Executive, 10(2), 20–37. O’Reilly, B. (1997). The secrets of America’s most admired corporations: New ideas, new products. Fortune, 3, 6–64. Sheremata, W. A. (2000). Centrifugal and centripetal forces in radical new product development under time pressure. Academy of Management Review, 25(2), 389–408. Song, X. M., Montoya-Weiss, M. M., & Schmidt, J. B. (1997). Antecedents and consequences of cross-functional cooperation: A comparison of R&D, manufacturing, and marketing perspectives. Journal of Product Innovation Management, 14(1), 35–47. Souder, W. E., & Moenaert, R. K. (1992). Integrating marketing and R&D project personnel within innovation projects: An information uncertainty model. Journal of Management Studies, 29(4), 485–512. Stewart, T. A. (1997). Intellectual capital. New York, NY: Doubleday/Currency. Takeuchi, H., & Nonaka, I. (1986). The new new product development game. Harvard Business Review, 64(1), 137–146. Thomas, K. (1992). Conflict and negotiation processes in organizations. In: M. D. Dunnette & L. M. Hough (Eds), Handbook of industrial and organizational psychology, (2nd ed.). Palo Alto, CA: Consulting Psychologists Press. Zahra, S. A., & Ellor, D. (1993). Accelerating new product development and successful market introduction. SAM Advanced Management Journal, 58(1), 9–18. Zirger, B. J., & Maidique, M. (1990). A model of new product development: An empirical test. Management Science, 36(7), 867–883.

APPENDIX The study was conducted in two phases: First, we conducted a pilot study consisting of in-depth interviews with six managers from four high-technology firms. The interviewees were directly responsible for their firm’s product innovation processes. We asked them to describe their experiences, identify key issues, and reflect on their learning. The interviews lasting between 90 and 120 min were tape-recorded and transcribed. We compared our data to the extant literature and identified managerial issues related to product innovation processes that deserved further scrutiny. We designed


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research questions and developed an interview protocol to guide the second phase. We also concluded from the pilot study that the sample for the second phase should consist of mid-to-large high-technology firms since small firms do not adequately shed light on cross-functional interactions (often one individual is performing multiple functions in small firms). In the second phase, we depth-interviewed 40 managers from 10 mid-tolarge high-technology firms (employing 650 or more employees). Thirty-nine interviews were conducted in-person, and one was conducted via telephone. All interviews were tape-recorded, transcribed, and content analyzed. All the firms invested in product innovation to overcome product obsolescence. Our sample includes manufacturers of locomotive brake systems, singlepackage cooling units, emissions control equipment, electric and electronic components, electrical construction materials, automobile transmission systems, medical diagnostic instruments, jet engine cables and harnesses, hightechnology specialty metals, and radar systems. We interviewed at least one manager from the R&D, production, and marketing department in each firm. Most of the interviewees had worked for 10 years or longer in the industry (90%), and in their firms (70%). We also interviewed team leaders, department heads, and senior managers when the participants indicated that these were important contributors to the product innovation process.


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LEADING INNOVATION THROUGH COLLABORATION Cynthia T. Matthew and Robert J. Sternberg ABSTRACT This chapter explores the unique role of leadership in organizational innovation. Drawing from the investment theory of creativity (Sternberg & Lubart, 1995), we show that organizational innovation begins with a leadership decision. Based on a review of the creativity, organizational, and leadership literatures, the key components of organizational innovation are examined from individual, group, and organization-wide perspectives. Leading innovation is conceptualized as a special case of leading organizational change, which requires creative leadership skills applied to social systems. Establishing an organizational environment that supports innovation in the current market environment increases systemic paradoxes that must be managed by leaders. We conclude that leading innovation increases the creative demand on the leadership system, which requires leaders who have a developed understanding of the process of innovation and its environmental requirements.

The transition from an industrial to a knowledge-based economy in the latter half of the 20th century brought about significant change in approaches deemed effective for leading and managing organizations. Command and

Innovation Through Collaboration Advances in Interdisciplinary Studies of Work Teams, Volume 12, 27–52 Copyright r 2006 by Elsevier Ltd. All rights of reproduction in any form reserved ISSN: 1572-0977/doi:10.1016/S1572-0977(06)12002-6

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CYNTHIA T. MATTHEW AND ROBERT J. STERNBERG

control through traditional hierarchies gave way to shared leadership practices in flatter management structures. The capacity to effectively lead change through a system of leadership was emphasized as the global market intensified competition and new technology changed business operations. Does the leadership requirement for innovation through collaboration differ substantively from the requirement for leading organizational change generally in the current market environment? In this chapter, we explore the unique leadership requirements for organizational innovation. Based on a review of relevant theory and research findings and an examination of systemic factors, we discuss leading organizational innovation as a special case of leading change. Knowledge about leading innovation through collaboration can be found at the intersection of leadership, creativity, and organizational literatures. Drawing from these literatures, we first describe organizational innovation, unpack its key components, and review its requirements. Second, since creativity results from an interaction between person and context or sociocultural environment (Amabile, 1996; Csikszentmihalyi, 1994, 1996; Sternberg & Lubart, 1995), we examine environmental factors that uniquely facilitate organizational innovation. Innovation ultimately involves change in what is produced and/or how work is accomplished in organizations. Accordingly, leading innovation is considered next within the framework of leading organizational change. We show that leading change requires creative leadership applied to social systems. Finally, we discuss how an organizational environment that supports creativity presents inherently more paradoxes that must be managed, which increases the creative demand on the leadership system. We conclude that leading innovation requires creative leaders who have a developed understanding of the process of innovation and its environmental requirements.

ORGANIZATIONAL INNOVATION Organizational innovation has been recognized as a key element of business growth and success for over a decade by organizational scholars (Amabile, 1988; Kanter, 1983, 1984, 1985, 1986, 1988; Woodman, Sawyer, & Griffin, 1993). Recently, the idea has taken hold in the popular business press and in business practice as reflected in a recent Business Week special report, in which Nussbaum (2005) states, ‘‘The Knowledge Economy as we know it is being eclipsed by something new – call it the Creativity Economy’’ (p. 62). What are the leadership requirements for organizational innovation?

Leading Innovation through Collaboration

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Theories of organizational creativity emphasize the important influence of environment on employee creativity (Amabile, 1988, 1997; Ford, 1996; Woodman et al., 1993). However, exploration of the role of leadership in creating the environment for innovation is limited. In general the literature suggests leader characteristics such as risk tolerance, supportiveness, and collaboration in complex social systems or networks are essential. During the industrial age innovation was generally regarded as a Research and Development function, where creative engineers and scientists focused on product development and produced periodic product breakthroughs and inventions. Today innovation is conceptualized more broadly as an organization-wide objective, for which every unit and department should develop the capacity regardless of function. This implies a systemic and continuous process of generating new ideas and improvements across levels and functions that is embedded in the culture and facilitated by the climate of an organization (e.g., Mauzy & Harriman, 2003). Organizational innovation is made up of two distinct phases or aspects, creative idea generation and creative production, which some scholars term ‘‘creativity’’ and ‘‘innovation’’, respectively (Kanter, 1988; West & Richards, 1999). Creative idea generation involves breaking down prior assumptions, making new connections, and synthesizing them into new ideas. These ideas can be generated by an individual independently or in collaboration with others. Creative production involves transforming high-potential ideas into valuable products or process innovations. It requires collaboration among individuals and teams that may cut across organizational levels and functions. Theoretical and empirical studies of creativity suggest building blocks for leading organizational innovation. In the following section we present a selected review of the concept of creativity as it relates to individual and group-level performance, how it can be assessed, and the organizational environment that facilitates it.

CREATIVITY Psychologists agree that to be creative, one needs to generate ideas or products that are relatively novel, useful/adaptive, high in quality, and gain social acceptance (Barron, 1955; Csikszentmihalyi, 1994, 1996; Sternberg & Lubart, 1991, 1995). Leadership is considered an aspect of creativity because personal influence over others is needed to make a creative contribution in any field (Gardner, 1995; Simonton, 1984; Sternberg, 1999; Sternberg, Kaufman, & Pretz, 2003). However, the theoretical relationship between leadership and

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creativity remains unclear in the literature. Gardner’s (1995) case-study analysis of eminent individuals from a wide range of domains suggests that eminent creators are ‘‘indirect’’ leaders, who exert impact through the works they create, whereas eminent leaders are ‘‘direct’’ in that they affect the thoughts, feeling, and behaviors of people directly. In a historiometric study, Simonton (1984) found so many similarities between eminent leaders and creators that he proposed creativity is a form of leadership. Alternatively, Mumford and Connelly (1991, 1999) argue that organizational leadership imposes too many constraints on leaders to render it a ‘‘creative domain’’. However, they assert that leadership requires creative thinking because it involves solving novel, ill-defined organizational problems. Change is considered an inherent aspect of creativity. Csikszentmihalyi (1994, 1996) asserts that creativity occurs when a person makes a change in a domain and that change is transmitted over time. Scholars recognize that creativity can be distinguished in terms of degree of change ranging from an incremental departure from the status quo (‘‘little c’’) to a high level or more radical departure (‘‘big C’’) (e.g., Amabile, 1983; Gardner, 1993; Lubart & Sternberg, 1995). Sternberg (1999) and his colleagues (Sternberg et al., 2003) apply the concept of level of creativity to leadership and specify eight types of change brought about by creative leadership in any domain including organizational administration. Researchers consider creativity to be a complex phenomenon that comprises four components (‘‘four Ps of creativity’’): (1) person (e.g., personal characteristics), (2) process (e.g., thought processes), (3) product (e.g., output), and (4) press of the environment (e.g., context and input) (Brown, 1989). A variety of frameworks have been developed that conceptualize creativity as an interaction between characteristics of the person and of the situation or sociocultural context (Csikszentmihalyi, 1994; Gardner, 1993; Lubart & Sternberg, 1995; Sternberg, 1999). Recent approaches to understanding creativity suggest that multiple components converge for it to occur. In general, these ‘‘confluence’’ approaches account for diverse aspects of creativity including intellectual abilities, thinking styles, personality attributes, task-focused motivation, and an environment that supports and rewards creative ideas (Amabile, 1983, 1996; Csikszentmihalyi, 1988; Gardner, 1993; Gruber, 1989; Perkins, 1988; Simonton, 1988; Sternberg, 1985a, 1985b, 1996; Sternberg & Lubart, 1991, 1995). When applied to organizational settings, the notion that multiple factors contribute to creative performance implies the importance of attracting and retaining individuals with creative potential and establishing an environment that emphasizes, facilitates, and supports creative activity.


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Amabile’s (1988, 1996) model of creativity specifies three essential components that in combination enable an individual to be creative. These components, which include domain-relevant skills, creativity-relevant skills, and task motivation, are germane to organizational assessment and development. Domain-relevant skills include factual knowledge, technical skills, and special talents in the domain in question. Creativity-relevant skills include: (a) a cognitive style characterized by facility in understanding complexities and breaking one’s mental set during problem solving; (b) knowledge of creativity heuristics that facilitate set-breaking and novel ideas; and (c) a work style characterized by concentrated effort and attention over long periods of time, an ability to abandon unproductive search strategies and put aside stubborn problems, persistence, high energy, and willingness to work hard. Task motivation, in particular intrinsic motivation, is the important determinant of the difference between what a person can and will do. Support for aspects of this model has been found in studies in the organizational domain. Sternberg and Lubart’s (1995) confluence theory suggests a useful profile that can be applied to leaders or champions of organizational innovation. Using an investment metaphor, a creative person is characterized as someone who ‘‘buys low’’ and ‘‘sells high’’ in the world of ideas. According to the theory, creativity is an attitude as well as a decision to be creative. Creative people reject currently popular, conventional ideas, then generate and advocate new ones until the worth of their new ideas is recognized and accepted by others. They posit six major characteristics associated with the creative person that are substantiated by their own and others’ research: (1) perseverance; (2) willingness to grow; (3) willingness to take sensible risks; (4) tolerance for ambiguity; (5) openness to experience; and (6) belief in oneself and the courage of one’s convictions. Individual Creativity Is it reasonable to assume that everyone is creative? It is generally accepted that there are individual differences in certain native abilities and personality attributes required for creativity. Nonetheless, many scholars agree that most people do not realize their creative potential, which can range from the capacity for incremental creative solutions (‘‘little c’’) to the capacity for breakthrough creative accomplishment (‘‘big C’’). In regard to intelligence, the literature suggests that intelligence may be a necessary but not sufficient factor for creativity to emerge. A number of studies have shown that while low levels of intelligence are associated with low levels of creativity, higher levels of intelligence are associated with variable levels

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of creativity. This suggests that some minimum level of intelligence may be required to facilitate the acquisition of sufficient knowledge through which creative performance can emerge (Amabile, 1996; Barron & Harrington, 1981; Getzels & Jackson, 1962; Perkins, 1981). There are two relevant implications in regard to organizational innovation. First, because intelligent individuals vary with respect to creative ability, individuals should be selected for creative potential, in addition to other knowledge, skills, and abilities. Second, since most people do not realize their creative potential, organizational context and development activities may be designed to enhance the creative output of its members. Creativity may be enhanced in individuals through training, practice, and conditions that facilitate its expression (Amabile, 1996; Nickerson, 1999). Efforts to enhance creativity may not expand one’s inherited potential but they may maximize expression of one’s potential (Plucker & Runco, 1999). While there may not be a prescribed scheme for enhancing creativity, empirical studies provide support that it can be enhanced through certain methods that target modifiable factors such as cognitive skills, attitude, and task motivation. In regard to cognitive skills, explicit instruction can provide an individual with knowledge and strategies that facilitate original and flexible ideation and insight (Harrington, 1975; Perkins & Laserna, 1986; Runco & Okuda, 1991). Imagery, for example, has been shown to maximize generation of insights about inventions (Finke, 1990). In regard to attitudes, several studies have shown that training can change attitudes toward various aspects of the creative thinking process such as preference for ideation, tendency to [not] make premature critical evaluations of ideas, and valuing new ideas (Basadur & Finkbeiner, 1985; Basadur, Wakabayashi, & Graen, 1990; Sternberg & Lubart, 1995). In regard to task motivation, studies suggest that motivation to engage in an activity solely for the enjoyment, challenge, or personal satisfaction that arises from the activity itself (intrinsic motivation) is conducive to creativity, whereas the belief that one’s work will be later evaluated by others may hinder it (Amabile, 1996). A number of studies have shown that creative performance decreases when subjects are told their performance will be evaluated or observed by others (‘‘extrinsic constraint’’). In addition, studies have shown that creative performance decreases under conditions where it is linked to rewards (‘‘extrinsic motives’’). However, a growing number of studies suggest that this depends on how extrinsic constraints and motivators are perceived. Extrinsic constraints and motivators can be conducive to creative performance when perceived as providing useful, and desired, information, and detrimental when perceived as controlling (for a review, see Collins & Amabile, 1999).


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Group Creativity Organizations can be highly suitable environments for creative activity depending on the extent to which creativity is part of its mission and championed by the system of leadership. Systemic innovation involves a continuous process of generating and implementing novel and useful ideas that can range from incremental improvements (‘‘little c’’) to radical breakthroughs in products or processes (‘‘big C’’) throughout an organization. Organizations that are committed to systemic innovation require leaders who can design groups that promote creativity and effectively manage group process paradoxes and losses. Creativity is essentially a social phenomenon that depends on interactions with others in groups that range from informal collaboration among colleagues to academic colloquia, scientific research laboratories, and organizational teams. Individuals can generate ideas that are later shared, changed, and developed through interaction with others. Creative ideas can also emerge from an interaction among group members such that the group co-creates an idea that no one member could generate on his or her own (Montouri & Purser, 1995). Studies of scientific research laboratories have shown that group interaction taking place in regular laboratory meetings where research findings are discussed facilitates important discoveries (Dunbar, 1995). Groups provide social and cognitive stimulation that facilitates the production of novel ideas and the use of relatively unique categories of thought. Although the literature is mixed, in general, factors that seem to be associated with group creativity include: (a) clear group vision or goals; (b) norms that support creativity; (c) climate where it is safe to share novel ideas; (d) individuals with creative abilities; and (e) member diversity (Agrell & Oustafson, 1996; Paulus, 2000; West, 1990; Woodman et al., 1993). The tendency toward agreement and conformity in groups can inhibit creative idea generation (Asch, 1955; Janis, 1972). Group members tend to seek shared areas of knowledge and agreement to make decisions and act, yet these tendencies may actually reduce the extent to which diverse information, different perspectives, and unique ideas are ever considered. One way to mitigate against the tendency to agree and conform in groups is to increase group member diversity. Groups in which members represent a heterogeneous set of knowledge, perspectives, and styles optimize novel idea generation. The research suggests that groups made up of people with diverse but overlapping knowledge domains and skills tend to be most creative (Stroebe & Diehi, 1994). However, evidence of the beneficiary effects of diversity is rather mixed (Cohen & Bailey, 1997). The optimal extent and type of

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diversity seem to depend on the type of team and type of diversity (Paulus, 2000). In addition, group sessions followed by individual idea-generation sessions to fully tap the cognitive benefits of the exchange process seem to enhance the potential for group creativity (Csikszentmihalyi & Sawyer, 1995). When ideas and styles diverge in groups, there is an increase in the likelihood of conflict, which can interfere with group functioning. While a persistent minority opinion can increase divergent thinking in groups, it may also provoke negative reactions and controversy. Conflict can inhibit or facilitate creativity in groups depending on its degree and type. Experimental studies have shown that the expectation of and experience of conflict may increase narrow and rigid thinking and decrease creative problem solving (Carnevale & Probst, 1998). Moreover, conflict may induce negative mood, which has also been associated with a reduction in certain aspects of creative thinking. Nonetheless, research on team innovation suggests that task conflict, which involves differences of opinion on specific work issues and goals, can aid the creative process in teams when the level of conflict is moderate (Jehn, 1997; Kurtzberg & Amabile, 2000–2001). Based on the foregoing discussion, leaders should establish norms of tolerance for diversity and conflict to promote group creativity. In addition, specialized knowledge and skills are needed to establish and lead teams that facilitate creative group performance. The important role of leaders in designing, managing, facilitating, and coaching effective teams is emphasized in Hackman’s (2002) model of team effectiveness, which is based on experimental and field research. According to the model, the key components of team effectiveness include: (a) ‘‘real team’’ (e.g., interdependent task, clear boundaries, specified authority, and stability over time); (b) compelling direction (e.g., challenging, clear, and consequential); (c) enabling structure (e.g., work design, norms, and composition); (d) supportive context (e.g., reward system, information system, and educational system); and (e) expert coaching (e.g., facilitating, and minimizing process losses and fostering gains). A democratic and collaborative leadership style has been associated with creative group output (Kanter, 1983). Moreover, leaders who are willing to take risks have been associated with successful scientific research teams (Dunbar, 1995, 1997; Sternberg & Lubart, 1995). Assessing Creativity Establishing an effective system for assessing whether an idea is creative, high potential, and worthy of investment is a critical leadership function.


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Creative ideas must come to the attention of leaders who facilitate assessing their worth. One approach to assessing creativity that has been successfully utilized for over 20 years in social psychology research on creativity is the consensual assessment technique (CAT) (Amabile, 1982, 1988). CAT is widely used in creativity research and has been validated in experimental (Amabile, 1983, 1996; Baer, 1993, 1998a; Hennessey & Amabile, 1999; Runco, 1989) and field studies (Baer, Kaufman, & Gentile, 2004). Research utilizing CAT demonstrates that evaluators who have adequate experience in the domain in question can reliably recognize and agree on judgments of product creativity even if they themselves have not produced work judged to be creative. Moreover, these evaluators can assess and agree on the relative degree of creativity when comparing one product to another. Managers can apply CAT guidelines from research to structures and systems for evaluating creative ideas in organizations. CAT has been shown to yield reliable measurements across domains and in ratings of process and product judgments, when certain procedural requirements are met. Judges should all have experience with the domain in question, although their level of experience need not be identical. They must make their assessment independently and should not confer with one another. Judges should not be trained or provided with specific criteria for judging creativity. They should be instructed to rate products relative to one another rather than rating them against some absolute standard they may hold. Judges should view the products in a different random order to avoid agreement based on methodological artifacts. When evaluating performance on a task that has not been applied in the past, judges should be asked to rate the products on other dimensions in addition to creativity such as technical aspects, aesthetic appeal, etc., to insure discriminant validity. Environment for Creativity An organizational system exerts substantial influence over the conditions, resources, and rewards that support (or hinder) creative activity. Such conditions will affect the extent to which creative individuals will be attracted to and retained by an organization. Organizational environments that emphasize conformity, hierarchy, and agreement unavoidably stifle creativity, and individuals with creative talent are not likely to select or remain in such systems. System-wide innovation requires that leaders align organizational subsystems to support creative activity (Kanter, 1988; Schein, 1992; Snudgren & Styhre, 2004). It begins with leaders establishing a vision for organizational innovation, communicating it in compelling and engaging

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ways, and embodying innovation by exhibiting behaviors required for it (Burke, 2002; Kotter, 2002). Innovation becomes part of organizational functioning when structure, management practices, and policies and procedures facilitate the expression of individual and group-level creativity (Burke, 1994; Katz & Kahn, 1978). The literature on creativity and organizational innovation puts forward distinctive values and attitudes that support creative activity. The leadership system must explicitly value novelty, learning, and change, values that must ultimately become embedded in the way the organization functions. Creative ideas emanate from openness to new and unconventional perspectives and tolerance for disagreement. Transforming creative ideas into innovative products and processes requires a spirit of flexibility and experimentation. Unavoidably many projects, if not most, will fail. Accordingly, organizational leaders must be willing to take sensible risks and tolerate failure (Mauzy & Harriman, 2003; Sternberg & Lubart, 1995; West, 1990, 1997). Organizational innovation initiatives emanate from ideas offered by members at any level in any function. Development, assessment, and implementation of these ideas depend on communication and collaboration that cuts across levels and functions (Kanter, 1988; Woodman et al., 1993). As such, organizational innovation requires a flexible and extended communication network in which upward and lateral exchanges are as sensitive, effective, and efficient as downward exchanges. This suggests a system of leadership that is not constrained in terms of role, hierarchy, or function. Accordingly, specialized structures and systems must be in place to facilitate the development of collaborative relationships through which creative ideas are recognized and evaluated. High-potential ideas should be identified and tested quickly and effectively. ‘‘Fast to failure’’ is often as important as ‘‘fast to success’’ for organizational innovation, where a 40% success rate is considered exceptional in organizations (Jonash, 2005). However, it is important to note that the process of transforming creative ideas into product innovations can take many years and involve several iterations before achieving success. For example, the 3M post-it note started with an adhesive innovation in 1964 that was transformed into the highly profitable product over the course of more than a decade. The capacity for internal and external social networks that involve collaboration within and across organizational boundaries is rooted in an ethic that emphasizes collaborative learning oriented toward larger outcomes rather than team- or unit-specific goals. It has been characterized as dynamic cooperation across complex, loosely tied internal and external networks (Hatchuel, 2001). For example, in the pharmaceutical industry,


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breakthroughs seem to take place in various informal network activities. Previous research showed that even infrequent interaction called ‘‘weak ties’’ can promote creativity (Ford, 1996). As such, it is relationship-centered (Haskins, Liedtka, & Rosenblum, 2001). In a study of how downsizing disrupts an organizations capacity to innovate, Dougherty and Bowman (1995) found a critical factor was to be breakdown in a system of ‘‘entrepreneurial networking’’. In particular, they found that product innovation is driven by champions who use their personal influence to obtain support and resources through a complex network of formal and informal interpersonal and intergroup relationships. During downsizing, key relationships are lost, which interferes with the strategic linking process needed to champion product innovation. Leaders of organizational innovation must value and support professional social networks, adopt strategies to promote stability in the organization and avoid short-term cost strategies that disrupt them, such as downsizing. Research on climate for organizational creativity specifies the need for sufficient levels of autonomy or freedom in how work is accomplished, challenging assignments, supervisory encouragement, workgroup support, sufficient resources, and freedom from excessive workload pressure (Amabile, Schatzel, Moneta, & Kramer, 2004; Kanter, 1988). Management practices that support creativity enhance intrinsic motivation by stimulating an individual’s sense of ownership and control over how work is done. Creative performance can be enhanced when people are told that evaluations and rewards are specifically linked to creativity in such a way that they enable rather than restrict performance. Drawing from a distinction between two facets of extrinsic motivation: control and information (Deci & Ryan, 1985), Amabile’s (1996) Intrinsic Motivation Principle suggests that informational or enabling extrinsic motivation can be conducive to creativity, particularly if initial levels of intrinsic motivation are high. When evaluations and rewards lead a person to feel controlled and are incompatible with intrinsic motives, they are detrimental to creativity (Amabile & Conti, 1999; Collins & Amabile, 1999). Accordingly, supervision that is supportive and informational rather than controlling is recommended to avoid the hindering effects of evaluation on creative performance. Creativity requires an environment where people feel free to challenge assumptions and conventional ways of doing things in search of more creative and profitable alternatives. A team environment characterized by ‘‘psychological safety’’ should facilitate creativity by alleviating excessive concern about others’ reactions to actions that have the potential for embarrassment or threat. Psychological safety is the shared belief that one can

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take interpersonal risks that could potentially result in rejection, punishment, or embarrassment, such as asking questions, admitting errors, and voicing objections. Psychological safety has been associated with workplace learning and innovation in teams (Edmondson, 1999). Leaders contribute to creating a climate of psychological safety by engaging in behavior that is supportive, coaching-oriented, and non-defensive in response to questions and challenges.

LEADING INNOVATION The ‘‘GE Action Workout’’ illustrates the essential role of leaders in establishing an environment for collaborative innovation. The genesis of that program itself represents collaborative innovation championed by a visionary leader. Organizational innovation begins with a leadership decision (Sternberg & Lubart, 1991, 1995). Executives motivate internal leaders, formal and informal, to value, promote, and invest in high-potential ideas that may lead to process and/or product change. In doing so, the leadership system promotes beliefs and assumptions (Schein, 1992) that support creativity, which fundamentally contribute to creating a modifiable culture. Modifiability refers to the inherent receptivity and desire for actual change in the system (Sternberg, 2002b). In this sense, a culture that supports organizational innovation can be considered a special case of one that facilitates change. To be innovative, an organization needs to attract, select, develop, and retain members with creative potential. Critical cultural assumptions include the belief that individuals are the source of good ideas and most productive when given autonomy in how work is accomplished. An important belief about group performance is that the best solutions are found when diverse perspectives are considered and ideas debated. Cultural values should include novelty, continuous learning and experimentation, and change. Time perspective must be long rather than short term, as a creative idea can take years to be transformed into a successful innovation. Organizational boundaries should be porous rather than closed based on the assumption that success depends on an exchange of ideas inside and outside of the system. In this sense, organizational innovation depends to a great extent on the nature of relationships among individuals and groups, within as well as outside the organization. Innovation is highly sensitive to leader approach and management practices that are relationship-centered and emphasize shared power and collaboration


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(Amabile et al., 2004; Kanter, 1986). Conceptualization of the nature of authority relations as ‘‘power with’’ or a shared influence process (Follett, 1925; Katz & Kahn, 1976; Wartenberg, 1990) may be a defining cultural dimension of an innovative organization. Shared power assumes that co-influence among involved parties over organizational processes will maximize outcomes. It is based on a belief that the shared influence process itself is a means to discover and implement optimal solutions. Shared power is characterized by reciprocal influence or collaboration across levels and functions. Consequently, power differences must be de-emphasized to create a context that encourages contribution by involved organizational members (Walsh, Bartunek, & Lacey, 1998). The role of shared influence in high-performance organizations can be found throughout the history of organizational study (Likert, 1961, 1967; McClelland, 1975; McGregor, 1960; Sagie & Koslowsky, 2000; Vroom & Jago, 1988). For example, Likert (1961) asserted that a group systems approach to management, in which cross-functional groups rather than ‘‘manto-man’’ hierarchy influenced executive decisions, produced more accurate and thorough communication across functions and better decisions based on a company-wide perspective. As modern organizations face the need to have greater adaptability and creativity, leadership models that emphasize the engagement of followers have been developed. Shared leadership (Badaracco, 2002; Pearce & Conger, 2003; Vroom, Jago, Eden, Yetton, & Craig, 1998), self-leadership or ‘‘superleadership’’ (Manz & Sims, 1980, 1989, 1991; Pearce & Manz, 2005), and relational leadership (Fletcher, 1999, 2004; Kouzes & Posner, 2003; Rosener, 1990) are three such models. Shared leadership entails the ‘‘simultaneous, ongoing, mutual influence process within a team that involves the serial emergence of official as well as unofficial leaders’’ (Pearce & Manz, 2005, p. 134). Self-leadership advances the notion that, to some degree, all organizational members are capable of leading themselves. It extends the notion of self-management beyond just meeting work standards to evaluating and modifying them when appropriate. Relational leadership is an approach based on a fundamental belief in the interdependent nature of all individual achievement. This approach is characterized by skills and behaviors that are collaborative and oriented toward mutual development of involved parties. Behaviors associated with relational leadership may be associated with the experience of psychological safety in followers (Fletcher, 1999, 2004; Kouzes & Posner, 2003; Matthew, 2003; Rosener, 1990). Leaders shape culture directly by attending to and role modeling behavior consistent with espoused values and underlying beliefs and assumptions

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(Burke, 2002; Schein, 1992). Based on the preceding review of environmental factors that support creativity, behaviors associated with leading innovation should include an open exchange of information, engaging diverse perspectives, demonstrating risk and conflict tolerance, collaborating, shared learning, and experimentation. Leaders indirectly influence culture by initiating structures and systems that facilitate and reinforce behaviors consistent with values and beliefs (Burke, 1994). For systemic innovation, this would involve establishing network forms and group systems to facilitate upward, horizontal, downward communication, collaboration, and decision-making (Dougherty & Bowman, 1995; Hatchuel & Glise, 2001; Kanter, 1988; Mitra, 2000) as well as rewards to reinforce creative activity. As discussed previously, a characteristic feature of an environment conducive to organizational creativity is perceived leader support. Empirical evidence suggests that such support is transmitted through everyday seemingly mundane supervisory behavior (Amabile et al., 2004; Ford, 1996). In particular, leader behaviors that influence the perception of support are associated with interpersonal skill, ability to obtain useful ongoing information about the progress of projects, openness to and appreciation of subordinates’ ideas, empathy for subordinates’ needs and feelings, and the facility for using interpersonal networks to give and receive relevant information. Behaviors that reduce perceived support include giving assignments without sufficient regard to subordinates’ capability or other responsibilities, micromanaging, and dealing inadequately with difficult technical or interpersonal problems. Leading organizational innovation requires a formal and informal leadership system made up of champions of innovation (Schon, 1963; Tushman & Nadler, 1986). Champions are individuals who actively and enthusiastically promote a high-potential creative idea through informal and formal channels to transform it into an innovation. Many field and case studies suggest that innovation success is strongly related to the presence of a champion. Howell and Higgins (1990, 1996) report evidence that the fundamental components of a champion’s capacity to introduce technological innovations include: (a) articulation of a compelling vision of the innovations potential; (b) expression of confidence in others to participate effectively in the initiative; (c) display of unconventional, innovative actions to achieve goals; (d) belief in one’s capacities to initiate change; and (e) assessment of environmental resources and constraints for bringing about change. They suggest that champions lead innovation through charismatic leadership and influence tactics. In other words, champions may be formal or informal leaders of change through innovation.


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Does leading innovation differ from leading change generally? Fundamentally, leading innovation may be considered a special case of leading change requiring similar leadership characteristics and processes. However, the environmental requirements particular to organizational innovation suggest additional factors. In the next section, we explore these issues. First, we show that leading change is inherently a creative process that requires creative leadership skills applied to social systems (Matthew, 2005). Next, we demonstrate how leading innovation intensifies the demand for leader creativity in unique paradoxes presented by the environmental demand for innovation. Finally, we conclude that to successfully lead innovation, leaders must have a developed understanding of the process of innovation and be themselves champions.

LEADING CHANGE Leading change involves forging a new direction in an uncertain and ambiguous environment, gaining acceptance within and outside of the organization, and implementing change within the organization. Creativity appears to be central to the three core functions of leading change, which include creating vision, aligning people, and motivating people (Kotter, 1995, 2002). For example, creating vision involves developing an image or idea of a future state that is compelling, meaningful, and energizing to people (Nanus, 1992). Aligning people with conflicting interests and needs under the banner of shared vision, involves creative communication through words, symbols, or actions (Gardner, 1995). Motivating and inspiring people involves creatively providing for people’s basic needs for achievement, belonging, recognition, self-esteem, control, and ideals (Burke, 2002). Existing theoretical and empirical studies support a link between creativity and leadership. For example, in a review of originality and leadership Bass (1990) found that the magnitude of correlations reported in early studies ranged from moderate to quite high (0.38 to 0.70). More recent studies suggest that divergent thinking, an aspect of creative ability (Guilford, 1968), is positively correlated with leader performance (Bass, 1990; Zaccaro, Mumford, Connelly, Marks, & Gilbert, 2000). Furthermore, creative problem solving has been shown to predict leader performance in Army leaders. Evidence suggesting that creativity in particular may be an important predictor of leading organizational change was found in a longitudinal study of leadership during the divestiture of the Bell system at AT&T. Findings suggest that creative mental ability, tolerance for ambiguity, and risk-taking, all characteristics of creative people (Sternberg & Lubart, 1995) are

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associated with effective leadership performance in ambiguous (i.e., dynamic) environments (Moses & Lyness, 1990). Creative characteristics are also consistent with Zaleznik’s (1977, 1990) characterization of leaders as compared to managers. He asserts that leaders are inclined to challenge the current organizational system and they are temperamentally disposed to seek out risk and dangers, especially where opportunity and rewards appear high. The affective nature of the leader–follower interaction has been emphasized as a major requirement for leading change (Katz & Kahn, 1978). Particularly important is charisma, defined as the capacity to stimulate emotional identification and induce trust in followers during times of crisis (Beyer, 1999; Weber, 1947). Charisma is a major factor in contemporary models of transformational leadership theory put forth to explain the capacity to lead organizational change (Avolio & Bass, 1988; Burns, 1978; Conger & Kanungo, 1998; House, 1977). Theory and research associated with contemporary models of transformational leadership have made an important contribution toward identifying behaviors and traits associated with leaders of change as opposed to managers. Transformational leaders are conceptualized as leaders who attempt to shape and create rather than react to environmental circumstances. Empirical studies suggest that transformational leadership is associated with risk-taking and innovativeness (Howell & Higgins, 1990) and such leaders have been characterized as ‘‘inventors’’ and ‘‘motivators’’ (Church & Waclawski, 1998). Conceptualization of leading change as creative leadership applied to social systems is supported by findings that relate social and emotional competency with effective leadership. A consistent theme among organizational change scholars is the importance of understanding and managing people’s emotions (Burke, 2002; Katz & Kahn, 1978; Kotter, 2002; Mayer, Caruso, & Salovey, 1999). People seem to vary in their ability to take in and understand affective information, which has been labeled emotional intelligence (Salovey & Mayer, 1990). There is a growing body of conceptual work that associates emotional ability with effective leadership. Recent studies are beginning to show empirical evidence that emotional intelligence is linked to leadership. Emotional intelligence and in particular empathy has been shown to be related to dimensions of transformational leadership (Kellett, Humphrey, & Sleeth, 2002; Wolff, Pescosolido, & Druskat, 2002). The ability to understand and manage social processes is also emphasized as a necessary capability of change leaders (Burke, 2002; Goleman, 1998; Katz & Kahn, 1978; Kotter, 2002; Zaccaro, 2002). The distinction between social and emotional skills is not readily apparent in the literature. Some scholars consider social skills to be indicative of emotional ability (e.g., Bass,


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2002; Goleman, 1998). Others define social intelligence as the ability to understand ones own and others’ feelings, thoughts, and behaviors in interpersonal situations and act appropriately, which subsumes emotional ability (Marlowe, 1986; Thorndike, 1920). Alternatively, social intelligence has been viewed as a function of the knowledge that individuals bring to bear on their social interactions (Kihlstrom & Cantor, 2000). Social ability appears to extend beyond emotional ability in that it concerns understanding and working with collective social processes such as social norms, social contagion, and political dynamics (Matthew, 2005). Zaccaro (2002) argues that effective leadership requires social reasoning abilities to effectively perceive, judge, and diagnose social situations and relational competencies to effectively respond to and manage them. Empirical support has been reported for the link between social judgment skills, operationalized as the ability to attend to complex and conflicting social cues, and leader problem solving and achievement (Zaccaro et al., 2000). Taken together the literature suggests that leading change requires creative leaders of social systems. Leading change at any level appears to be primarily a creative function that involves: (a) creating a vision of an improved future state; (b) communicating it in compelling ways to persuade others of its urgency and value; (c) developing a strategic plan for realizing the vision; (d) anticipating emotional and social reactions to change and intervening, so that they do not contaminate or derail the change effort; and (e) shaping organizational climate (surface structure) or culture (deep structure) consistent with the improved future state (i.e., vision) (Burke, 1994, 2002; Katz & Kahn, 1976; Kotter, 1996, 2002; Selznick, 1957). As such, leading change entails influencing change in individual and group behavior and, in particular, how people think in the organization. The process of organizational change occurs primarily through the social system in support of the technical system (Burke, 2002; Burke & Hornstein, 1972; Katz & Kahn, 1978; Lewin, 1958). Changing the social system ultimately involves changing beliefs, values, and assumptions that motivate norms and characteristic behavior patterns among organizational members. If leading innovation is a special case of leading change, in what way is it unique? Leading innovation seems to increase the demand for creative leadership.

A SPECIAL CASE OF CHANGE Leading innovation increases the demand for creative leadership in two ways. First, the leader must embody the creative vision and mission. To

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‘‘walk the talk’’, leaders must demonstrate the behaviors (e.g., risk-taking, collaboration, and openness to diverse perspectives) required for creativity and innovation. Second, the process and environment that supports organization innovation creates paradoxes, which leaders must manage. How does one build a context to sustain innovation in a rapidly changing market environment that can require large-scale organizational change at any point in time? Leading in paradoxical circumstances requires a capacity to reframe problems and synthesize seemingly opposing elements of a problem in unusual ways. First, innovation requires an investment of resources in ideas that may take years to develop into profitable outcomes. However, the tumultuous market, short-term demands of shareholders, and relatively short tenure of most organizational leaders emphasize the need for near-term performance. Leading innovation requires motivating a longer-term perspective on organizational performance without sacrificing responsiveness to immediate short-term performance demands. Second, the context for innovation is relationship-centered. Social networks and collaboration across organizational boundaries depend on the development and maintenance of effective work relationships over time. Turnover of leaders and champions interrupts the strategic linking process through which innovation takes place in social networks. Leading innovation requires building sustainable social networks that institutionalize innovation in the context of rapid turnover of leaders and champions. Third, collaboration, which is critical to innovation (Paulus, 2000; Purser & Montouri, 1995), can decrease decision-making efficiency, which is essential to organizational survival. Collaboration can be ‘‘tedious, slow, and complex’’ and requires building and attending to relationships (Mintzberg, Dougherty, Jorgensen, & Westley, 1996). In contrast, remaining competitive in dynamic markets can require quick and effective decision-making to change course when the market dictates. Another opponent process associated with collaboration is that of social hierarchy. Hierarchy is a fundamental organizing principle in all human groups (Sidanius & Pratto, 1999; Weber, 1947), which can serve an adaptive function to promote quick and efficient group action. In groups, people will position themselves relative to others based on perceived power, which according to French and Raven (1959) is based on legitimate (position power), reward (recognition or pay), coercive (discipline or job action), expert, and referent (personal identification) power sources or bases. People are hesitant to contradict others who they perceived as authority figures (e.g., Milgram, 1983). Accordingly, hierarchy can exert a strong effect on human relations in


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ways that limit open and honest dialog (Islam & Zyphur, 2005). Leading innovation requires minimizing the pull of social hierarchy enough to support collaboration for group creativity, while maintaining sufficient authority to promote efficient and rapid group action to insure organizational survival. Finally, the context for creativity depends on supportive supervision, informational feedback, and a climate of cooperation, which increases the demand on supervisory resources. In addition, diversity is a source of creativity and innovation that increases the risk of workplace conflict, which can require managerial facilitation. However, the current competitive organizational environment has led to a reduction in supervisory and management resources, which can ultimately result in reduced motivation for creative performance and increased competition. Leading innovation requires promoting collaboration and cooperation with fewer managerial resources to do so.

CONCLUSION Leading innovation requires creative leaders who have a developed understanding of the resources for creativity, process of innovation, and its environmental requirements. According to the investment theory of creativity (Sternberg & Lubart, 1995), creativity can be developed by choosing to ‘‘buy low’’ and ‘‘sell high’’ in the work of ideas, much as an investor buys low and sells high in the work of securities or other investments. To do so, one must: (a) generate ideas that other people do not think of, and recognize which are good (intelligence); (b) know what other people have done and not done in your field of endeavor (knowledge); (c) like to think and act in creative and contrarian ways (style); (d) be willing to take risks and overcome obstacles (personality); (e) have the drive to act on creative or contrarian ideas (motivation); and (f) chose an environment that supports doing these things (context). The investment theory of creativity provides a highly applicable metaphor for leading organizational innovation. Leaders must make an executive decision to ‘‘buy low’’ and ‘‘sell high’’ in the world of creative ideas. This involves developing a system of leaders who think and act in ways that ‘‘defy the crowd’’ and are willing to take educated risks. To succeed leaders must cultivate an organizational environment that supports creative activity by embodying the creative vision and mission and managing inherent paradoxes. In an interview with Business Week, Jeffrey R. Immelt, CEO of GE, expressed the importance of leader creativity in the following statement,

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‘‘We’re measuring GE’s top leaders on how imaginative they are. Imaginative leaders are the ones who have the courage to fund new ideas, lead teams to discover better ideas, and lead people to take more educated risks’’ (Nussbaum, 2005, p. 66). There appears to be a growing trend toward organizational innovation in force. In this chapter, we have shown that leading innovation increases the demand for creative leadership. When should organizational leaders make the innovation ‘‘decision’’? What methods will be effective for assessing and developing creative leaders? Can there be too much leader creativity? These are some of the many questions that should be explored as the ‘‘creative economy’’ moves forward.

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COMMUNITIES OF PRACTICE: A CRITICAL PERSPECTIVE ON COLLABORATION Yue Lin and Michael M. Beyerlein ABSTRACT The importance of collaboration had been widely recognized but its nature has remained obscure. This chapter suggests that an appropriate level of analysis for collaboration research would be social interaction and the optimal unit of analysis would be communities of practice. Such a sociocultural approach departs from the traditional positivist approach, which echoes the long-standing conflict between postmodernism and modernism. Principles of organization in traditional institutions and communities of practice are then contrasted. The differences among coordination, cooperation, and collaboration are presented, suggesting that the prototypical form of collaboration locate in communities of practice. Finally, a new look at the relationships between collaboration and learning, collaboration and innovation is extended to describe the workspace created by communities of practice.

INTRODUCTION Collaboration is receiving vast attention for its ability to promote innovation and effectiveness of organizations (Beyerlein, Freedman, McGee, & Innovation Through Collaboration Advances in Interdisciplinary Studies of Work Teams, Volume 12, 53–79 Copyright r 2006 by Elsevier Ltd. All rights of reproduction in any form reserved ISSN: 1572-0977/doi:10.1016/S1572-0977(06)12003-8

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Moran, 2003). In the past few years, we have seen the magic power of collaboration from the booming of the Silicon Valley (Delbecq & Weiss, 2000), success of the Boston biotechnology network (Powell, 1998), growth of the Hsinchu industrial park in Taiwan (Hage & Hollingsworth, 2000), triumph of India’s Bangalore region (Cooke, Davies, & Wilson, 2002), Toyota’s network of suppliers (Dyer & Nobeoka, 2000), and the communities of practice in IBM (Lesser & Storck, 2001). Although the authors above widely recognize collaboration’s role in intra- and interorganizational relationships, they tend to treat collaboration as structure. Such a conceptualization is limiting and fails to recognize collaboration as a social construct. This chapter criticizes such a conceptualization of collaboration and proposes to define collaboration from the perspective of communities of practice by emphasizing practice, community, engagement, and autonomy. Wood and Gray (1991) reviewed nine different definitions of collaboration and identified dozens of elements, and proposed that ‘‘collaboration occurs when a group of autonomous stakeholders of a problem domain engage in an interactive process, using shared rules, norms, and structures, to act or decide on issues related to that domain’’ (p. 146). This means shareholders create a social system for processing information leading to discussions and actions. Such a social system is seen as different from other institutional structures, such as hierarchies and markets. Although Wood and Gray’s definition greatly improves our understanding of collaboration, it fails to address several important issues. First, the nature of collaboration is not clearly spelled out. The related ontological and epistemological issues are not addressed. Second, the distinctions among coordination, cooperation, and collaboration are not consistently recognized. These terms are used interchangeably sometimes, but meant differently at other times. Third, the connections between collaboration and other organization constructs are not well articulated. For example, collaboration is studied independently from learning and innovation. To resolve these conceptual issues, a different conceptualization of collaboration would be necessary. The first section of this chapter reviews some preceding work on the level of analysis and social interaction. The concept of communities of practice is then introduced as the optimal unit of analysis for collaboration research. The second section explores the ontological and epistemological sources of communities of practice by discussing the modernism and postmodernism debate. The third section depicts the principles of organization in traditional institutions and communities of practice. In the fourth section, the differences among coordination, cooperation, and collaboration are put forth. In the fifth section, the relationship between learning and collaboration is

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discussed in the framework of communities of practice. Finally, the relationship between collaboration and innovation is reconsidered, and a different strategy of promoting innovation will be proposed.

COMMUNITIES OF PRACTICE Collaboration can be studied at multiple levels. Specifying the optimal level and unit of analysis thus becomes important for understanding the nature of collaboration. This section adopts a social interaction approach and suggests that an interactional level of analysis is the most appropriate. Communities of practice are then introduced as the candidate for the optimal unit of analysis. Levels of Analysis In the organization literature, level of analysis has received more and more attention (Chan, 1998; Klein, Dansereau, & Hall, 1994; Morgeson & Hofmann, 1999). As for collaboration, some researchers (e.g., Schreiner & Corsten, 2004) focus on collaborative capabilities at the individual level, while others (e.g., Astley, 1984; Borys & Jemison, 1989; Geser, 1992; Martin, 2003; Warren, 1967; Wood & Gray, 1991) go beyond the individual level. Similarly, learning has been traditionally studied at the individual level of analysis, but more and more writers focus on organizational learning (e.g., Argyris & Schon, 1978, 1996; Lave & Wenger, 1991; Wenger, 1998). Argyris and Schon (1978, 1996) recognized that errors pervade in interpersonal interactions. They tried to answer why people interact irrationally and keep repeating that behavior. They proposed that the organizational learning system, including structures and assumptions related to learning, determines how people interact in the organization. Morgeson and Hofmann (1999) insisted that such conceptualization of higher level analysis is meaningful only if the nature of the new construct is explicated. Based on this insight, they posited interaction as a fundamental component of collective action. In the same vein, Weick (1979) suggested interactions, in the form of interlocked behaviors and double interacts, are basic elements of organizing. From a situative perspective, Greeno (1998) also suggested that behavior in all research settings be analyzed as interactions, and proposed a shift from focusing on the behavior of individuals to focusing on the behavior of systems. Therefore, this chapter adopts social interaction as the level of analysis.

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Social Interaction Social influence and social interaction are two alternate approaches to study of interactions among multiple parties (Eskola, 1988). The social influence approach treats each individual as a self-sufficient entity with various psychological properties. When multiple individuals interact, exchanges take place between the psychological properties. The social interactionist approach, in contrast, moves beyond the psychological processes by taking contextual factors into account. Bourdieu (1977, pp. 81–82) argued that the truth of the interaction is more than the interaction itself by stating: This is what social psychology and interactionism or ethnomethodology forget when, reducing the objective structure of the relationship between the assembled individuals to the conjunctural structure of their interaction in a particular situation and group, they seek to explain everything that occurs in an experimental or observed interaction in terms of the experimentally controlled characteristics of the situation, such as the relative spatial positions of the participants or the nature of the channels used.

Without considering the objective structure of the relationship, which bears social and historical contexts, researchers are vulnerable to the drawbacks of positivism. The interaction between individuals and between individual and environment has received a lot of attention from multiple generations of researchers (e.g., Bateson, 1972; Dewey, 1929/1958; Giddens, 1979; Katz & Kahn, 1978; Lewin, 1946; Vygotsky, 1934/1987; Weick, 1979). Dewey (1929/1958) recognized the dynamic relationship between individual and environment and suggested that to learn is to inquire into the environment, which could consist of objects, people, symbols, and forces external to the individual. To understand the interaction between individual and environment, Lewin (1946) in his Field Theory, attempted to use the concept of field to describe forces in the environment. These forces reside in individuals’ heads and thus are psychological in nature, but such a conceptualization fails to consider forces that are social in nature (Martin, 2003). In contrast with Lewin, who treated the environment as something ‘‘out there,’’ Vygotsky (1934/1987) emphasized the inseparability of the individual, the context, and the object. Such a notion echoes the Gestalt psychologists’ (Koehler, 1947; Koffka, 1935) notion of holism and implicates an ontological departure from the traditional positivist approach to knowing (Packer & Goicoechea, 2000). We will discuss the distinctions between the ideas of Lewin and Vygotsky in terms of modernism and postmodernism later in this chapter. The dynamics between individuals and between individual and the environment are also demonstrated in the activity model developed by Vygotsky

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(1934/1987). The activity model is composed of three elements: subjects, objects, and tools/signs, which can be represented as the points on a triangle. The model has been readily extended to situations where multiple participants form a community (Engestrom, 1999) and where multiple communities form a network (Blackler, Crump, & McDonald, 2000). Some contemporary scholars (e.g., Blackler, Crump, & McDonald, 1999; Greeno, 1998; Lave & Wenger, 1991) follow this sociocultural line of pursuit. Since communities of practice bear situative and historical contexts and contain rich interactions, we propose them as an important vehicle to study social interaction. Communities of Practice Subjecting interactions to scientific inquiry has been regarded as a serious problem for scientists (Argyris, Putnam, & Smith, 1985), mainly due to the subjectivity of meaning. How common sense is achieved among actors becomes a key to solving such a problem. Communities of practice provide an environment where common sense can be achieved (Argyris et al., 1985; Wenger, 1998). A community of practice consists of ‘‘groups of people informally bound together by shared expertise and passion for a joint enterprise’’ (Wenger & Snyder, 2000, p. 139). Wenger (1998) detailed five critical elements for communities of practice: practice, community, meaning, learning, and identity. These five elements are described below. Practice. First, practice is where formal structures and procedures are ‘‘abstracted’’ (Brown & Duguid, 1991). Practice is about ‘‘how we actually do things around here.’’ It conveys the past, the present, and the future. Practice is embedded in the social context that denotes the present and the historical context, which encodes the past. In addition, it gives structure and meaning to what we do, which carries the future. Practice is not a ‘‘thing’’ that can be manipulated, but an ongoing, social, and interactive process. Practice revives itself when people interact to perform something currently. It not only provides resources for actors to behave, but also guides them to behave consistently. In this sense, practice coordinates social interactions. Community. Second, a community is where the practice resides. A community forms when people who share the same practice interact with each other. Unlike institutions, a community usually takes shape without deliberate construction. Membership is naturally developed, depending on whether one speaks the same language as others in the community and the competence he/she has. Wenger (1998) suggested that full membership

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denotes a high competence, while novices do not have full membership due to lack of competence. Sharing the same practice in a community does not necessarily mean a homogeneous community. Members may differ in interests, goals, agendas, status, and levels of competence. The existence of expert-based power in communities of practice has been acknowledged by Lave and Wenger (1991), but described as communities of domination by Huzzard (2004), because of the influence tactics of senior members. Meaning. Third, common sense can be achieved by the negotiation of meaning in communities of practice. According to Wenger (1998), participation and reification are two interacting constituent processes of the negotiation of meaning. Participation denotes mutual recognition between community members, who then become so interconnected that they see each other as part of themselves. Reification is an abstraction of experience, which is a ‘‘thing-like’’ existence but subject to various translations. Both processes are necessary for negotiation of meaning. Without participation, reification cannot be translated into shared meaning. In the same vein, without reification, participation is deprived of resources, and thus is pointless. As demonstrated by Wenger, computers cannot participate and thus cannot share meaning between them, though they can store a large amount of reification. In contrast, trees are participative, but they cannot share meaning between each other because reification is not present. Communities of practice support meaning making because they promote both participation and reification. Learning. Fourth, knowing instead of knowledge is emphasized, and learning/knowing is the engine of communities of practice (Wenger, 1998). According to Wenger, knowing refers to competent participation in the practice, while knowledge is reified knowing in practice. Greeno (1998) expressed the same idea by stressing the engagement of different parties in activities and the interactive construction of understanding. In other words, knowledge is neither inside the head, nor out there in the object, but in the relations between subjects and objects. Therefore, communities of practice shed different light on understanding of learning by treating it as a situative and historical process instead of a cognitive structure. In an interview, Wenger stated that ‘‘Learning is best understood as an interaction among practitioners, rather than a process in which a producer provides knowledge to a consumer’’ (Kahan, 2004, p. 28). Identity. Fifth, a key structuring element of knowing is the identity developed as a person feels belonging in a community of practice (Wenger & Snyder, 2000). Wenger and Snyder noted that it is passion, commitment,


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and identification with the community’s expertise that bind the community together. Identification of the community of practice is followed by high motivation to learn and trustful relationships between each other. Wenger (1998) noted that as a novice of a community of practice, commitment to the practice is relatively low, but as the novice becomes more competent, he/she gets more committed to the practice. Since identity represents competency in a practice, it is rewarding for less experienced members to learn from more experienced members and establish trusting relationships with them. The five elements are integral components of communities of practice (Wenger, 1998). Practice is the cornerstone of the community, for it provides the community with situative and historical contexts. Community is the container of the practice, as only through participation can the practice gain its currency. Meaning is the product of practice and community, and it revives the practice and the community. Learning not only nourishes the community, but also represents the trajectory of the practice. Identity is personal belonging that binds the community together. Because of the wholeness they inherit and their capacity to embrace social and historical contexts, communities of practice are the optimal unit of analysis for studying collaboration. Communities of practice represent a sociocultural tradition, which has been categorized as a thought of postmodernism (Prawat, 1996). The following section will discuss the ontological and epistemological differences between modernism and postmodernism and their implications to understanding communities of practice and collaboration.

MODERNISM AND POSTMODERNISM The debate between modernism and postmodernism could date back thousands of years, when the bifurcation of structure and process first arose. Such a ramification continues to grow, but in the new terms of being and becoming (Chia, 1995; Cooper & Burrell, 1988), distal and proximal views (Cooper & Law, 1995), agency and structure (Reed, 1997), and organization and organizing (Gherardi, 1999). According to Chia (1995, p. 579), being connotes ‘‘phenomenal states, static attributes, and sequential events,’’ which could be termed as structure, while becoming emphasizes ‘‘a transient, ephemeral, and emergent reality;’’ which could be coined as process. Wilson (1970) also distinguished two approaches to understand social interaction. The normative approach assumes people have a shared system of meaning for interacting in a stable fashion. An interaction can be reduced to

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dispositions of and expectations on an individual. Roles, therefore, are predetermined, and can establish dependable patterns of interaction and predictable responses. In contrast, the interpretive approach sees the preassumption of shared meaning as unnecessary. Meanings are negotiated and constructed by agents in particular situations and subject to change. Roles emerge from the dynamics of interaction. The word ‘‘agent’’ denotes proactiveness, while ‘‘role’’ denotes reactiveness. The two words correspond to the dichotomy of modernism and postmodernism. Modernism. Modernism assumes a reality independent from one’s consciousness. From the modernist perspective, human beings learn to study interactions based on their patterns. Structures are created and taken for granted as real. Artifacts and culture are also created to represent the meaning of interactions and subsequently treated as real existences. Culture and structure allow people to repeat the interactions consistently across time and consequently human beings can accumulate past experiences of success. Ouchi and Wilkins (1985) noticed that research on structure dominates the literature by focusing on explicit and rational aspects of the organization. Since most research is based on measurement, and structure is easier to measure, a natural tendency is to study what is easy. Ouchi and Wilkins also noticed that more and more attention has been paid to implicit or irrational aspects of the organization since the 1950s. For example, researchers (e.g., Barley, 1983; Martin, 1982; Pettigrew, 1979; Schein, 1984) introduced culture research into organizations. However, this line of research assumes the existence of shared values, beliefs, and basic assumptions (Linstead & Grafton-Small, 1992), therefore holding a modernist position. Meek (1988) stated that structure and culture, like two sides of the same coin, are both abstractions of interactions. By ignoring the temporal factor and excluding irrational topics, objectivism concentrates on reified objects and structures (Bourdieu, 1977). Modernists thus pay attention to abstractions of interactions instead of interactions themselves. Postmodernism. From the postmodernist perspective, process, rather than structure, is stressed (Chia, 1995). Although structure can stabilize and change the way people interact, it is an emergent phenomenon instead of real existence (Morgeson & Hofmann, 1999; Packer & Goicoechea, 2000; Weick, 1979). Referring to Heidegger’s (1962) phenomenological tradition, Gherardi (2000) reasoned that learning takes place in a flux. Subjects, objects, and contexts are inseparable until a reflexive act occurs. The inseparability breaks down as a reflexive act is exercised. Bateson (1972) referred to this as ‘‘a habit of punctuating the stream of experience so that it takes on one or another sort of coherence and sense’’ (p. 163). Therefore, structure is


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constructed by the human mind. Linstead and Grafton-Small (1992) went even further by asserting that the reflexive act itself is socially and historically determined, which divests the wholeness of subjectivity. The divestment of subjectivity leads to the concept of objective structure, from which habitus or practice develops (Bourdieu, 1977). Since structure is a subjective product of mind, it cannot be the starting point of study. Moving from an emphasis on structure to an emphasis on process has several important implications. First, structure and culture are emergent phenomena and must be investigated in the context. Miller (1999) suggested that culture is a constitutive component of communities of practice. Second, postmodernism implicates more autonomy than control. People are encouraged to explore and try multiple tracks (Cooper & Burrell, 1988). Third, postmodernism stresses agency more than roles. Emphasizing agency represents an ontological shift from the dualism that characterizes modernism (Bandura, 2001). Fourth, nonlinearity and irrationality are treated as important phenomena worthy of investigation in postmodernism. In his discussion of the Hawthorne experiments, Roethlisberger (1989) stated, ‘‘Too often we think of collaboration as something which can be logically or legally contrived. The Western Electric studies indicate that it is far more a matter of sentiment than a matter of logic’’ (p. 13). The sentiment in the experiments is a legitimate subject matter of study from the postmodernist perspective. Postmodernism thus legitimizes studies on phenomena that are autonomous, agentic, contextual, and nonlinear. The opposition between modernism and postmodernism offers a critical insight into the relationship between coordination and collaboration.

PRINCIPLES OF ORGANIZATION The most ancient coordination mechanism could lie in the intentionality that is indigenous to human beings. As indicated by Engestrom (2005), shared intentionality plays an important role in aligning interactions. Tomasello (1999), from a perspective of comparative psychology, proposed that human beings and other species are different mainly because human beings are able to understand others’ intentionality, while other species cannot. Human beings thus can learn more efficiently and cooperate more complexly than other species. Meanwhile, the growth of interactions in human society introduces more and more conflicts of intentionality, posing a great challenge to human beings’ capacity to align. As a result, coordinating

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interactions gets very difficult and critical. A structural account1 of coordination is proposed by modernists to deal with such a problem. Coordination in Traditional Institutions An organization is typically viewed as collection of people working together in a division of labor to achieve a common purpose (Schermerhorn, Hunt, & Osborn, 2004). Division of labor and coordination are thus two key principles of organization in formal institutions. This account of coordination reflects a modernist tradition, which favors structure. Argyris and Schon (1978, 1996) contended that a collectivity, like a mob, gets organized when rules are established regarding the procedures for decision-making in the name of the collectivity, authority to act for the collectivity, and membership of the collectivity. An organization is a cooperative system whose members take on different roles, and the division of labor is an important component of the organizing process. Meanwhile, the rules, together with the norms, strategies, and assumptions of the organization, constrain how the organization acts and coordinates the activities of its members. Therefore, coordination should be studied along with the division of labor. Kogut and Zander (1996) conceded that division of labor and coordination are both principles of organizing. Malone and Crowston (1994) proposed an interdisciplinary framework of coordination and defined it as management of dependencies between activities. Such dependencies include shared resources, task assignments, producer/customer relationships, and so on. Correspondently, different coordination mechanisms and processes exist to cope with these dependencies. For instance, ‘‘first come, first serve’’ can solve the shared resources problem. Jennings and Wooldridge (1993) saw coordination as ‘‘the process by which an agent reasons about its local actions and the (anticipated) actions of others to try and ensure that the community acts in a coherent manner’’ (p. 226). They postulated that coordination mechanisms can ultimately be reduced to commitments and conventions, which corresponds to Durfee, Lesser, and Corkill (1989) notion that a system with good coordination mechanisms should exhibit both predictability and flexibility. Focusing on the division of labor, structure, and rules demonstrates a modernist tendency to study coordination. However, as indicated by Bateson (1972), coordination based on purposes and goals reflects a positivist approach, and thus is problematic. Bourdieu (1977) also demonstrated the fallacies of rules. Communities of practice offer an alternative perspective on coordination, which is based on practice.


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Coordination in Communities of Practice Greeno (1998) stated that the main theoretical focus in interactional studies is on principles of coordination in socially organized activity systems and of organization of the practice. Wenger (1998) proposed that practice is a source of coherence, and that mutual engagement, joint enterprise, and shared repertoire are three characteristics of practice that are relevant to the coherence of the community. According to Wenger, mutual engagement denotes participants who engage in actions and negotiate the meanings of the actions with each other. Joint enterprise is the result of such a process of negotiation of meaning, indicating mutual accountability in participants. Shared repertoire refers to the resources for negotiating meaning, which may come from the process of pursuing enterprise or from the outside or the history of the community. Mutual engagement, joint enterprise, and shared repertoire denote present, future, and past participation in the practice and thus are sources of coherence. These principles can be extended to a network of multiple communities of practice. Wenger (1998) asserted that boundaries exist because multiple communities of practice have different practices, different ways of engaging with each other, different histories and routines. He believed boundaries can be crossed by the act of brokering. Brokers who share multiple memberships of communities of practice would introduce a practice from one community to another. In addition, boundaries can be permeated by boundary objects, which could be artifacts, policies, procedures, and other reification. Wenger (2000) indicated that multiple communities can be bridged by the processes of engagement, imagination, and alignment. To make sense of other communities of practice, an act of direct engagement is the most effective way. When direct engagement is not viable, having an accurate imagination of other communities of practice becomes the key. Cross-boundary teambuilding activities such as organizational mirroring (French & Bell, 1999) provide opportunities to enhance that imaging process. An act of alignment is required when a shared goal needs to be accomplished. In considering a network of activity systems, Blackler et al. (2000) proposed perspective taking, perspective shaping, and perspective making as three core organizing processes that can help communities to make sense of each others’ practices, the collective objects, and the process of engagement itself. Principles of coordination between communities are thus distinct from those within a community. Traditional institutions adopt a mechanistic view of designing and implementing coordination mechanisms, which leaves their interactional

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attributes overlooked. A traditional approach to coordination thus could be inadequate for these organizations to survive in the face of growing uncertainty. Schwartz (1998) admitted that rules are not adequate to ensure collaboration and the importance of agency should be acknowledged. Blackler et al. (1999), through an activity theoretical analysis, demonstrated how the mode of coordination changed from the one based on rules and hierarchy to that based on collaboration, mutual adjustment, and shared sense making. With organizations being more complex and interrelated, Blackler et al. (1999, p. 27) stated: Finally, integral to this development is the development of new approaches to integration and control. Multi-disciplinary working, which involves the co-ordination of different specialists each of whom are applying their specialist approaches, must give way to supra-disciplinary working, where collaboration takes place between experts who are all contributing to the joint development of a shared agenda.

Corresponding to the distinctions between modernism and postmodernism, traditional institutions and communities of practice adopt different principles of organizing, a structural approach for the former, and a processfocused one for the latter. Differences among coordination, cooperation, and collaboration can be derived from such a division. Coordination, Cooperation, and Collaboration The distinction between coordination and cooperation has gained some attention (Wooldridge & Jennings, 1999). Coordination can be centralized or decentralized (Jennings & Wooldridge, 1993). In centralized coordination, a third party may carry out the function when two parties have conflicting schedules. In this case, the dependency between the two parties is weak and social interaction is minimized. In contrast, in a decentralized situation, two parties who have conflicting schedules work out a solution by interacting together to coordinate their actions. In this case, the parties take on more autonomy and interact directly to manage the dependency. Cooperation, like coordination, also manages dependencies between activities (Malone & Crowston, 1994), but it always denotes some social interactions between agents, although such social interactions can be controlled, like in the Prison-Dilemma game simulations (Axelrod, 1984), or be encouraged, like in the cooperative problem solving tasks (Wooldridge & Jennings, 1999). Although cooperation and collaboration are usually used interchangeably, some researchers (Dillenbourg, 1999; Dillenbourg, Baker, Blaye, & O’Malley, 1995; Roschelle & Teasley, 1995; Schwartz, 1998) have tried to distinguish them. For example, Dillenbourg (1999) emphasized interactivity,

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synchronicity, and negotiation in discussion of collaboration. Schwartz (1998) sees agency as an exclusive feature of collaboration. Malone and Crowston (1994) noted that collaboration often connotes peers working together on an intellectual endeavor. In discussion of interorganizational collaboration, Lawrence, Hardy, and Phillips (2002) defined it as ‘‘a cooperative relationship that is negotiated in an ongoing communicative process and that relies on neither market nor hierarchical mechanisms of control’’2 (p. 282). Coalitions as one-time cooperative acts are different from alliances as ongoing cooperative relationships (Harcourt & de Waal, 1992). Another distinction could be: negotiations associated with collaborations tend to be more complex and fundamental and could lead to new understandings, norms, and practices (Phillips, Lawrence, & Hardy, 2000). Such negotiations include what the collaboration is intended to address, who should be involved, and how practices respond to the problem. The distinctions among coordination, cooperation, and collaboration listed above are quite tentative, since they are not based on a coherent framework or theory. Such a problem can be readily solved by adopting the community of practice as the unit of analysis for collaboration research. If the prototype of collaboration truly lies in communities of practice, its differences with the other two constructs can be depicted in five dimensions: the nature and extent of interaction, the scope of activity, the amount of autonomy, the degree of dynamism, and temporality (see Table 1). Note that cooperation is featured with characteristics of both coordination and collaboration. To describe the contrasts linearly, only coordination and collaboration are included in the following comparative analyses. First, coordination and collaboration differ in the extent of social interaction and engagement. Weick (1979) described several types of coordination, which need little direct interaction among parties. Coordination needs little engagement from members and instead relies more on symbolic imagination and structural alignment to manage dependency. In contrast, Table 1.

Social interaction Scope Autonomy Dynamic Temporality

Differences among Coordination, Cooperation, and Collaboration. Coordination

Cooperation

Collaboration

Few Narrow Low Low Discrete

Mixed Mixed Mixed Moderate Mixed

Rich Broad High High Ongoing

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mutual engagement is important to sustain the coherence of the community of practice, while imagination and alignment tie multiple communities of practice together (Wenger, 2000). In other words, collaboration is easier to nourish inside communities of practice, because members share the same practice, engage mutually, and negotiate meaning together. When multiple practices are considered, engagement is less possible and other coordination acts have to be taken, especially with cross-disciplinary collaboration (Klein, 2005). Second, coordination and collaboration differ in the scope of the field of interest. Coordination focuses on problem solving, which requires mostly cognitive contributions. In contrast, collaboration focuses on broader issues and asks for more than cognitive resources from the contributors. That is, people collaborate to enjoy what they are doing and make it meaningful to them. Since collaboration always takes situative and historical contexts into account, people can search in a bigger problem space, add their personal concerns in, and develop a solution meaningful to them. With a narrow focus, coordination often creates new problems as it solves an old one, and the process is characterized with alienation, anger, frustration, and lack of meaning. Third, coordination and collaboration can be distinguished by the degree of autonomy members enjoy. Coordination emphasizes structures, roles, and control. People lack the autonomy to determine the goal, the division of labor, the procedure, and the outcome. Such a modernist approach works best when the scope of the problem is narrow and a conventional solution is satisfactory. In contrast, collaboration values processes, agency, and autonomy. People work together to decide what to do and how to get it done. The division of labor is negotiated and remains flexible for adjustment. Different emphases on autonomy result in disparate attitudes toward innovation. Coordination hardly encourages new solutions, but collaboration places strong emphasis on them. Fourth, coordination and collaboration differ in the dynamism they own. Since coordination is a linear and rational process, it can do a good job when the scope of a problem is small and the complexity is low (i.e., when dynamism is low). Collaboration, in contrast, treats nonlinearity and irrationality as legitimate phenomena worthy of study. Collaboration thus is valuable in dealing with complex issues of broad scope. In this case, the best way to manage interdependence is to engage people fully. Fifth, coordination and collaboration differ in temporality. Coordination in the objectivist sense ignores the factor of time (Bourdieu, 1977). Coordination is discrete and takes place when it is needed. In contrast,

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collaboration is an ongoing process and can continue to be present even when community members get off work or travel to different countries. Revisiting the Definition of Collaboration Communities of practice thus help us to understand the differences among coordination, cooperation, and collaboration. Meanwhile, they imbue new meanings into the definition of collaboration provided by Wood and Gray (1991). Table 2 illustrates the differences between the traditional understanding and new understanding. First, Wood and Gray (1991) recognized that the scope of collaboration could go beyond a specific problem and thus extend to the problem domain. However, the term ‘‘problem domain’’ is too tractable in the scientific sense and it denotes purposefulness that Bourdieu (1977) argued against. We see practice as the starting point of theory building. Practice provides a situative and historical context for collaboration to occur. People collaborate not only to solve problems, but also to learn, to share identity, or just to be together. Second, Wood and Gray (1991) suggested that collaboration still occurs when some members in a group are not engaged. They assume that the group has a clear boundary and that membership is predetermined and fixed. To communities of practice, the boundary is permeable and membership reflects shared interests. Peripheral members can exist and are welcome in communities of practice, since they have potential to become full member when they are competent in practice (Lave & Wenger, 1991). In addition, they help to cross boundaries between different communities of practice. People can belong to multiple communities of practice simultaneously with different degrees of participation and competence, and act as Table 2.

Differences between Wood and Gray (1991) and this Paper.

Wood and Gray (1991) Focus on a problem domain Group with clear boundary and predetermined membership Interact purposefully (act and decide)

Autonomy from the modernist perspective. Control is primary

This Paper See practice as the starting point Community of practice with permeable boundary and flexible membership Engage each other deeply and broadly. Negotiate meaning and develop identity, participation Autonomy from the postmodernist perspective. Autonomy is primary

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boundary brokers (Wenger, 1998). This enables collaboration across disciplines that is enhanced by using senior personnel as cross-boundary knowledge brokers (Conway, personal communication) Third, interaction is an important element in Wood and Gray’s (1991) definition, but the authors tended to define interaction as purposeful and instrumental. The scope and the degree of interaction are quite limited in comparison to those defined in communities of practice. Mutual engagement in communities of practice involves not only cognition, but also affect and commitment. Meanwhile, interactions in the Wood and Gray definition aim to decide and act on issues related to the problem domain. In contrast, communities of practice emphasize participation, which is not limited to onthe-job activities. Fourth, Wood and Gray (1991) placed great emphasis on individual autonomy in collaboration. However, control is still conspicuous. Since the group is embedded in the institutional context, membership, goals, and even the division of labor are prearranged. Therefore, autonomy is limited in the group. The postmodernist perspective of autonomy allows community members to explore tracks that are vastly different from the existing one. Community members negotiate membership, goals, and the division of labor. As a result, community members enjoy more autonomy than group members who share different practices. Therefore, the essential facets of collaboration are practice, community, engagement, and autonomy. Collaboration is not only cognitive, but also social and historical. Without considering these, we run the risk of confusing coordination, cooperation, and collaboration. Some companies have recognized the true nature of collaboration and take efforts to nurture it. Toyota exemplifies this. Toyota Cases Wolf and Evans (2005) compared the Linux open-source software (LOSS) community to Toyota. The volunteer, self-organizing community of opensource programmers is well known for its ability to organize large projects virtually and produce innovative products. The authors believe it combines the self-organizing advantages of markets with the low-transaction cost of hierarchies. Both Toyota and the LOSS community are featured with a common work discipline, dense localized communication, and leaders as connectors, which together engender a new form of collaboration. The authors show how rich, flexible collaborations not only produce rich knowledge, but also extraordinary motivation and high levels of trust. From the


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perspective of communities of practice, we can see how collaboration works in this case. A certain task was taken on by engineers who shared the same skills. First, they formed a virtual community, which had open membership and the membership was distributed across different time zones. Second, participation was voluntary and the communication was widespread. Third, members worked on the task granularly, which meant anyone could go on to solve any problem he/she was capable of and move the work forward. Fourth, the plan was emergent and autonomy was assured. Therefore, both Toyota and LOSS enjoy true collaboration. Dyer and Nobeoka (2000) contrasted Toyota to American auto companies and found Toyota’s superior performance could be attributed to the parallel growth of suppliers. The success of Toyota depended on the success of suppliers, and vice versa. Toyota organized a supplier association and consulting teams to exchange explicit and tacit knowledge, respectively. Suppliers who were similar also set up voluntary learning teams to improve factory productivity. They visited each other’s factories, diagnosed problems, and solved them. Over time, strong ties were developed among suppliers and networks3 came into shape. The perspective of communities of practice also demonstrates that collaboration has been nourished in Toyota. First, suppliers who shared similar practices formed a community of practice. Second, membership was voluntary and the boundary was permeable. Third, these suppliers interacted with each other and engaged each other to solve various problems. Fourth, these suppliers were autonomous in deciding which problems to tackle and the methods to approach them. The development of communities of practice thus brings about true collaboration among suppliers. We can see that the case comparing Toyota and LOSS can be analyzed at the intraorganizational level and the case comparing Toyota to American auto manufacturers at the interorganizational level. A structural framework treats collaboration as a combination of markets and hierarchies, instead of emphasizing its processual characteristics. This new framework of interpretation places emphasis on common practice, open membership and permeable boundaries, mutual engagement, and full autonomy, demonstrating unique vigor in both cases.

COLLABORATION AND LEARNING Traditionally, learning and collaboration are seen as two independent constructs. But recently, collaborative learning has received researchers’ attention (e.g., Roschelle, 1992; Dillenbourg, 1999). Collaboration is found

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to contribute to learning in multiple ways. Social interaction provides new resources for human cognitive accomplishment (Shirouzu, Miyake, & Masukawa, 2002). First, participants can more easily exchange their ideas. The cognitive value of externalization in social interaction is based on a process of making internal processes of thought visible. Second, social interaction fosters the emergence of a more abstract conception than individual working (Schwartz, 1995). Variations of solutions differing in the degree of abstraction could create a ‘‘ladder’’ for subjects to climb up the levels of abstraction. Third, Karpov and Haywood (1998) noted that collaboration facilitates metacognition, as others can monitor the learning process and provide feedback on it. Learning thus can be facilitated in a collaborative relationship. Research on collaborative learning undoubtedly is meaningful, but mechanisms/rules in the modernist sense will not work, because they fail to take situative and historical contexts into account. Karpov and Haywood (1998) noticed this issue and depicted how contemporary school systems shape the way learning is conducted. The separation of objects from subjects obscures meaning, identity, collaboration, and power from our attention. By treating learning as a rational process, researchers are legitimized to study the structure of the learning process (Greeno, 1998). Learning thus becomes an individual undertaking, and collaboration becomes an independent construct that correlates with learning. Cooperation, a word that denotes more rationality than does collaboration, is adopted to depict more mechanistic and rational relationships among people. Marshall (1997, p. 181) laments: y We created brain and learning-antagonistic environments that actually inhibited integrative learning, distorted that learner’s identity and his or her competence as a learner, and discouraged inventiveness, inquiry, and complex cognition y it must be established and built upon a foundation of connection, coherence, mutually created meaning and purpose, dynamic relationship, and the evolutionary nature of the human experience itself.

An alternative approach, which treats collaboration and learning as inseparable, is worthy of examination. Such a new approach sees communities of practice as containers of both collaboration and learning. Communities of practice provide the environment where shared mental models (Senge, 1990), intersubjectivity (Vygotsky, 1987), common ground (Rogoff, 1990), theories in use (Argyris & Schon, 1978, 1996), or shared thoughts (Levine & Moreland, 1990) develop. To achieve them neither collaboration nor learning is dispensable. Brown and Duguid (1991) consider collaborative learning and individual learning as inseparable when a group of people works together. If Brown and Duguid are right, collaboration and learning are also


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inseparable. They both center on the practice and are embedded in the community. Marshall’s (1997) vision of learning will be possible only when collaboration and learning are treated as constitutive parts of communities of practice.

COLLABORATION AND INNOVATION Innovation refers to the successful exploitation of new ideas (Duggan, 1996). Creativity, the ability to make or bring into existence something new, thus is seen as a part or an antecedent of innovation, while innovation denotes testing, experimenting, and embodying the new ideas. A slightly different definition of innovation views it as the process by which a new idea is discovered and created (Rogers, 1995). Both definitions are processual. Schumpeter (1947) treated innovation as an alternative way to increase firm profits, and states that innovation is the only way to sustain profitability in the long run. He saw innovation as context specific and localized. A firm’s innovation capacity is determined by its existing knowledge base and the complementarity between the knowledge base and the technological opportunity. The social capabilities of the firm determine its ability to absorb new knowledge and technology. Schumpeter emphasized the ability to learn in the process of innovation. Hage (1999) identified three factors important to organizational innovation. First, an organic structure is beneficial to organizational innovation as it allows information or knowledge to flow freely. An organic structure also permits organizational members to act autonomously and overcome institutional barriers easily. Second, a risky strategy can promote innovation in the organization, since it can provide goals and motivations for organizational members. The creative tension can act like leadership, setting ambitious but reachable goals (Senge, 1990). Third, the complexity of division of labor contributes to organizational innovation by creating a knowledge base of complexity. Such a knowledge base has an impact on the organization’s absorptive capacity (Cohen & Levinthal, 1990) and on the number of alternative solutions. Dunbar (1996) also indicated that cognitive division of labor is an important prerequisite for the advancement of science. In his discussion of knowledge creating, Nonaka (1994) noticed three factors that influence innovation: creative chaos, redundancy, and requisite variety. Creative chaos is generated when the organization faces a crisis and requires an alternate solution. Creative chaos thus places a need for innovation on the organization. Redundancy of knowledge in the organization means that

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knowledge is widely shared across the organization. It can reduce the impact of managerial hierarchy and increase mutual trust. Requisite variety denotes that the organization should create the same degree of diversity as that in the environment. Studies by Hutchins (1995) and Dunbar (1996) revealed that groups that consist of members with different but partially overlapping expertise were more effective and innovative than groups with homogeneous expertise. Hage (1999) and Nonaka (1994) therefore agree that the external environment and the internal structure of the organization are critical in supporting innovation. Focusing on structures and cultures, which promote innovation in a topdown manner may be an effective strategy to promote innovation, but only when people in communities of practice respond to these interventions correctly. People in communities of practice may react differently to what management promotes (Brown & Duguid, 1991; Wenger, 1998). An alternative approach is to preserve and enhance autonomy of communities and move local innovations across boundaries to other communities (Brown & Duguid, 1991). Focusing on communities of practice represents a bottom-up approach. A top-down approach could overwhelm the local communities, which could cause their defensiveness. An organic structure could produce information overload with people in the organization not knowing which piece of information is relevant to them. Popper (1970) also expressed such a concern. He contended that ideology of democracy could do harm to individuals’ freedom, instead of promoting it. Therefore, an ideology of innovation could actually do harm to the organization. The bottom-up approach, in contrast, preserves the wholeness of the communities of practice. A processual approach to understand how innovation evolves in a community and between communities focuses on investigating the possible sources of innovation. Based on the three core organizing processes, Blackler et al. (2000) introduced three types of innovation. Boundary innovation refers to sensemaking of other communities, which corresponds to perspective taking; contextual innovation refers to sensemaking of the contexts, which corresponds to perspective shaping; domain innovation refers to sensemaking of the processes, which corresponds to perspective making. Thus, innovation can come from boundary crossing, contextual understanding, and processual organizing. However, it should be noted that innovation with multiple communities of practice is difficult to realize, due to lack of mutual engagement, joint enterprise, and shared repertoire. Innovation within a community of practice, in contrast, is easier to materialize, simply because community members can engage each other, share the same practice, and use the same language and tools. Linking across communities

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of practice remains a key challenge for the organizational pursuing major innovations.

CONCLUSION Collaboration has received more and more attention from both researchers and practitioners. However, a theoretical framework is underdeveloped and the nature of collaboration is unspecified. The purpose of this paper is threefold: (1) explore the nature of collaboration under the framework of communities of practice, (2) distinguish coordination, cooperation, and collaboration by relating collaboration to communities of practice, and (3) reconsider the relationships of collaboration to learning and innovation. To investigate collaboration, theories should go beyond the psychological properties of individuals and treat social interaction as the basic level of analysis. Moreover, social interaction theories are chosen over social information theories, because the former considers situative and historical contexts. Communities of practice, which bear situative and historical contexts, thus are an optimal candidate for conceptualizing collaboration. Five critical elements of communities of practice are then introduced: practice, community, meaning, learning, and identity. Communities of practice, a sociocultural construct, reflect a postmodernist tradition. The contrasts between postmodernism and modernism (process versus structure, autonomy versus control, agency versus roles, nonlinearity versus linearity, and irrationality versus rationality) imply ontological and epistemological differences between traditional institutions, such as markets and hierarchies, and communities of practice, thus implicating the differences between coordination/cooperation and collaboration. The Wood and Gray (1991) definition of collaboration takes on new meanings when practice replaces problem domain, community replaces group, engagement replaces interaction, and participation replaces act/decision. The new conceptualization of collaboration has advantages over a traditional structural account of collaboration in two Toyota cases. In both cases, Toyota achieves higher effectiveness through ‘‘real’’ collaborations. The new conceptualization of collaboration implies that learning and collaboration are inseparable in communities of practice. Separating collaboration from learning could thwart learners’ autonomy, agency, meaning, identity, and connection to others. The new conceptualization of collaboration also offers a different approach to promote innovation. The traditional top-down approach could actually overwhelm and even break down

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communities of practice, thus inhibiting innovations. A bottom-up approach, which safeguards the autonomy of communities of practice, may be a better alternative for promoting innovation, or a balance of top-down structure and bottom-up emergence may be the ideal – if the seemingly inherent conflict between the two forms can be managed.

NOTES 1. Schreiner and Corsten (2004) proposed that the collaborative capability consists of structural, cognitive, and affective components. Fitzgerald (2004) proposed a collaborative capacity framework, which also includes structural elements. In their discussion of interorganizational collaborations, Mankin, Cohen, and Fitzgerald (2004) explored the effects of organizational goal, culture, leadership, authority, and communication on collaboration. All these studies adopted a structural account of collaboration. 2. Although markets and hierarchies are quite different in many aspects, they share the same assumptions that goals, the division of labor, rules, norms, and coordination are predefined. In markets and hierarchies, people are coerced to obey rules and sometimes norms by the third party, otherwise their deviants could be punished. In contrast, members in a collaborative relationship usually have high autonomy. They cocreate goals, the divisions of labor, rules, and norms. Coordination is emergent instead of planned. Popper (1972) distinguished between systems that are like clocks and those that are like clouds. Clocks operate in an orderly way. The actions of each component are predictable from the other, synchronized, and unified. Other systems are more like clouds. Clouds lack the obvious structure of clocks. 3. Adoption of network analysis (Powell, Koput, & Smith-Doerr, 1996) and actor network theory (Latour, 1986; Law, 1992) in collaboration research has received more and more attention. In their discussion of informal social networks, Cross, Borgatti, and Parker (2002) demonstrated how social network analysis can be effective in: promoting collaboration, crossing boundaries, and ensuring integration.

ACKNOWLEDGMENTS Our thanks go to Mal Conway, Malcolm Conway, Managing Consultant, IBM Business Consulting Services, for his suggestions on how to enhance several of the concepts in this paper.

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TEAM INNOVATION THROUGH COLLABORATION Claudia A. Sacramento, M.-W. Sophie Chang and Michael A. West Teams often generate and sustain ideas that can enable organizations to achieve their goals but are unable to implement these ideas on their own. In this chapter, we analyze the factors facilitating team innovation and discuss how teams can further promote the implementation of their ideas via collaboration with other individuals, groups, and organizations. We draw upon an integrative model of team innovation and suggest that task characteristics, group knowledge, diversity and skills, and the external demands the team faces are important inputs for idea generation and innovation implementation in teams. Integrated group processes, such as participation in decision-making, support for innovation and reflexivity, interact with the aforementioned inputs to predict team creativity and innovation implementation (West, 2002). Moreover, we extend this model to account for how collaboration with other teams can further facilitate implementation of such ideas. We focus on two activities teams can engage in, boundary spanning and team members’ knowledge networks, as means to complete the innovation process. To collaborate, which is the action of working with someone to produce something (Oxford, 2005), does not come as a novelty to modern society. Since the beginning of time, humans had to collaborate with each other in order to ensure their protection and nurturance in the hostile savannah. Innovation Through Collaboration Advances in Interdisciplinary Studies of Work Teams, Volume 12, 81–112 Copyright r 2006 by Elsevier Ltd. All rights of reproduction in any form reserved ISSN: 1572-0977/doi:10.1016/S1572-0977(06)12004-X

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Very early, men and women were aware of their limitations as individuals and realized that their chances of survival would increase if they aligned themselves in a network rather than try to survive in isolation. If we look at how fast humans elected the group as a work unit (Roberts, 1995), we realize that this had to occur as a consequence of their awareness of the benefits collaboration could bring them. As times evolved, societies grew more complex and the need for collaboration became increasingly prominent. During the 15th and 16th centuries, Portuguese and Spanish navigators synthesized knowledge of distant geographical locations and enabled them and exchange their goods. This constituted the beginning of a global economy that grew remarkably by the end of the 20th century. The emergence of digital networks, software, and new media shortened distances and approximated different markets. Until then, human production and consumption of goods and services had developed separately over different parts of the globe. Of course, there are many examples of companies from different countries working together, but the international market was restricted to a small number of more powerful organizations. Afterward, it became much more common for organizations of countries very far apart, such as China and UK, to be business partners. Advancements in modern technology fostered a global economy characterized by the strategic establishment of alliances and partnerships across regions, countries, and continents. This occurs mainly because the global economy increased the range of opportunities offered to each organization. However it also carries threats such as high levels of competition and ever evolving environments. In order to succeed, organizations have to be able to cope with the fast pace of the global economy and to be more innovative than their competitors. In such a hostile environment, collaboration can be a source of competitive advantage (Huxman, 1996) and a key for innovation. Collaboration is not restricted to a specific level, it can take place between individuals, between teams (e.g., Harrison, Price, Gavin, & Florey, 2002), and between organizations (e.g., Ring & Van de Ven, 1994; Simonin, 1997). The two concepts previously interlinked – collaboration and innovation – lead us to the purpose of this chapter. For the sake of clarity, we should start by presenting our definition of both terms. Collaboration is here described as the quality of social interactions within a network. It differs from cooperation (when the goals of the different parts involved are perceived to be positively interlinked; Tjosvold, 1998), a concept that we will also address later on. As we understand, collaboration does not require the settlement of interdependent goals, tasks or resources, but refers solely to the quality of

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the social interactions between groups of individuals, teams, or organizations that at a certain point in time work together. The second core concept, innovation, is defined as the ‘‘intentional introduction and application within a job, work team, or organization of ideas, processes, products, or procedures that are new to that job, work team, or organization’’ (West, 1990). Our objective is to address how teams can maximize their creativity and thereafter promote the implementation of their ideas by establishing collaboration relationships with other entities in the organization. This issue seems to be of significant relevance as teams are often owners of a vast range of ideas with the potential to benefit them and the organization. However, most of the time they lack the means to introduce them. To accomplish this, we first look at the factors that stimulate creativity within the team (as well as innovation implementation, when the team has the means to conclude the process on their own) and afterward we will suggest how teams can promote the continuity and successful implementation of their ideas via collaboration with other entities within the organization. Collaborative relationships between organizations (e.g., partnerships), or directly between teams and the environment external to the organization (e.g., customer relationships), although extremely significant for organizational innovation, lie outside the focus of the present chapter. Our focus of analysis is therefore the team, defined as ‘‘a group of individuals who work together to produce products or deliver services for which they are mutually accountable’’(Mohrman, Cohen, & Mohrman, 1995, p. 39). This choice is informed by the relevance teams that have assumed in modern organizational settings. Teams have emerged as a privileged form of organizing work and the number of organizations implementing team work-based structures has increased steadily (Mohrman et al., 1995). We do not refer specifically to a type of team: we choose to discuss collaboration and innovation in the context of a generalist team rather than analyzing, for example, the specific dynamics that take place in cross-functional teams (this is covered elsewhere in this volume). We organize this chapter into two main parts: the first part focuses on the factors that promote the generation of ideas and their implementation within the team, and the second looking at how the team can establish collaboration relationships with others in order to implement the ideas that they do not have on their own the power to do so. The chapter unfolds as follows. Firstly, we draw on West’s (2002) model of team innovation to summarize the factors associated with team creativity and team innovation of implementation. Secondly, we draw on intergroup relations theories to identify the conditions that are more conducive to team collaboration.

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Thirdly, we extend West’s (2002) model and integrated how the relationships of the team with the outside context can promote the implementation of its ideas leading consequently to team and organizational innovation. The levels of formal external collaboration between teams and other entities in the organizations are very much restricted by the structure of the organizations; however teams do have the power to establish informal relationships of collaboration through their personal contacts. We focus on activities under the teams’ control and analyze the value of boundary spanning and personal networks for creativity and implementation of innovation. We conclude the chapter by presenting recommendations for best practice.

CREATIVITY, IMPLEMENTATION OF INNOVATION, AND COLLABORATION As other researchers have done previously, we conceptualize innovation not as a linear process but as a cyclical one (e.g., Van de Ven, Polley, Garud, & Venkataraman, 1999), which consist periods of innovation initiation, implementation, adaptation, and stabilization (West, 1990). Within this cycle it is possible to distinguish two major components: the beginning of the cycle, which is dominated by the generation of ideas that is generally also designated as creativity; whereas the dominant activity at the end of the cycle which is the implementation of ideas (hereafter referred to as the implementation of innovation). Creativity is then likely to be most evident in the early stages of the innovation process, when those in teams are required to develop or offer ideas in response to a perceived need for innovation. Creative thinking is also likely when teams proactively initiate proposals for change and consider their initial implementation. As the innovation is adapted to organizational circumstances, there is less need for creativity. At the outset of the process, creativity dominates, to be superseded later by innovation implementation processes. Of course, it can be argued that creativity is important throughout the innovation process, but in general, the requirements for creative ideas will be greater at the earlier stages of the innovation process than the later stages. Innovation is restricted to intentional attempts to bring about benefits from new changes; these might include economic benefits, personal growth, increased satisfaction, improved group cohesiveness, better organizational communication as well as productivity. Various processes and products may be regarded as innovations. They include technological changes such as new products, but may also include new production processes, the introduction


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of advanced manufacturing technology or the introduction of new computer support services within an organization. Administrative changes are also regarded as innovations. New human resource management (HRM) strategies, organizational policies on health and safety, or the introduction of teamwork are all examples of administrative innovations within organizations. Innovation implies novelty, but not necessarily absolute novelty (West & Farr, 1990). For example, if teamwork is introduced to a government department, it is considered to be an innovation if it is new in that government department, irrespective of whether it has been introduced into other government departments. It is important for the purpose of this chapter to analyze the relevance of collaboration between teams and other entities at both stages of the innovation process. Team creativity is a function of contextual influences, group composition, group characteristics, and group processes (Woodman, Sawyer, & Griffin, 1993). Creativity is positively influenced by crossfertilization and discussion of ideas from different perspectives (Amabile, 1988; Ford, 1996), which would lead us to attribute a determinant role to collaboration at this stage. However, we take the stance that the team itself can be a source of different perspectives that stimulate creativity and therefore collaboration with other entities is not so crucial for the generation of ideas. Even without the establishment of (formal or informal) collaborative relationships, team members can gather information from the external environment via different sources (for example, formal communication, media, informal conversations, specialized journals), and consequently find a trigger for creativity. Innovation implementation, on the other hand, often involves changing the status quo, which implies resistance, conflict, and a requirement for sustained effort. A team that attempts to implement innovation is likely to encounter resistance and conflict by others in the organization, and therefore sustained effort is required to overcome this resistance to innovate. In order to implement its idea, the team has to mobilize support across the organization and acquire approval for its execution. Collaboration, for example, lateral collaboration between teams, becomes extremely relevant in this particular stage of innovation. We do not assume that collaboration between teams has a neutral impact on the first stage, it can certainly influence creativity positively as well, and later on we also discuss how boundary spanning and networks can foster creativity. Collaboration between teams can, for example, be very useful in preventing group think (Janis, 1972) in highly cohesive groups. As collaboration requires interaction between the different parts involved, it is more

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likely to promote higher reflection amongst each team member than what the simple exposure to external information would do, promoting divergent views and enhancing creativity. We also recognize the role of collaboration when different teams work together to identify and solve a specific problem that neither team would be able to effectively solve on its own. However, we argue that a team has higher autonomy and resources to engage in creative processes on its own than it has to implement the ideas produced. Depending on the magnitude of the innovation to be introduced, teams have generally to obtain approval and ensure the resources to implement their ideas, and they have to do so via collaboration. Therefore we argue that collaboration between the team and external entities gains further importance at the implementation stage of innovation. It is, however, necessary to make an important distinction between those situations in which the job requires the team to be creative from those in which creativity occurs beyond the job description. In the former, creativity is externally driven (Unsworth, 2001). One example would be a software team in charge of developing a new software program for the company’s finance management system. In the later, creativity is internally driven. An example of this type of creativity would be the suggestion of a new system for allocation of night shifts in a hospital (for a study of internally driven creativity, see Frese, Teng, & Wijnen, 1999). When the driver for creativity is external, teams are creative as part of their work role and the organization facilitates the means for the implementation of their ideas. On the other hand, when the driver for creativity is internal, teams are going beyond their work role. Their creativity is not usually associated with the project they are involved in, but is more associated with aspects indirectly related to the projective, for example, job processes. As this is not part of the job description, the organization is not automatically prepared to supply the means for the implementation of these ideas. It is the establishment of collaborative relationships that can then help team in gathering support and acquiring approval. We argue then that collaboration between the team and other entities is of foremost importance at the time of innovation implementation and when the creative idea to be implemented was internally driven.

A MODEL OF TEAM INNOVATION As we mentioned previously, first analyze which factors facilitate team creativity (and team implementation of innovation when the completion of the

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Team Innovation through Collaboration Boundary Spanning Knowledge networks Group Task Characteristics

Creativity (-) Integrating Group Processes (+)

External Demands ~ Innovation (+) Implementation

~

Group Knowledge Diversity and Skills Key: ~ Inverted U relationship Direction of principal relationships

Fig. 1. Factors in Team Creativity and Implementation.

process is in the team’s power). Although collaboration within the team is not central to this chapter, we will also analyze how each factor is related to collaboration between team members when relevant to do so. We argue that team creativity and implementation of ideas is determined by four levels of factors: task characteristics, group knowledge diversity and skills, external demands, and integrating group processes. Fig. 1 depicts the principal relationships between these elements. As shown below, we suggest that task characteristics, integrated group functioning, and diversity of knowledge and skills are requirements for both creativity and implementation of innovation; the effects of external demands and threat upon creativity and innovation implementation are, we propose, quite opposite (see Fig. 1). The model also includes collaborative activities that teams use to foster the implementation of their ideas. These activities include boundary spanning and knowledge networks. This aspect of the model will be discussed later on. Group Task Characteristics The task that group performs has significant influence on the work group, defining its structural process and functional requirements – the people in

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the group, their roles, the extent to which they have to collaborate and the nature and processes of the tasks they individually and collectively perform. Indeed, in a sense a team is defined by the task it is required to perform. The task will therefore influence the level of creativity and innovation implementation in the team. Several systems of task categorization have been proposed. Dimensions include task difficulty; solution multiplicity; intrinsic interest; cooperative requirements (Shaw, 1976); tasks which are unitary versus divisible, conflict versus cooperation elements; conceptual versus behavioral components (McGrath, 1984); and disjunctive, conjunctive, or additive (Steiner, 1972). These classification systems are, however, somehow limited when analyzing group performance and innovation in organizational settings, probably because such goals as producing TV programs, battleground training, health care, product development, and providing financial services cannot be neatly categorized into discrete tasks and subtasks (Tschan & Cranach, 1996). Socio-technical systems theory (STST, Trist & Bamforth, 1951) seems to provide a more useful framework for examining the effects of task design on group collaboration and consequent work group innovation. STST proposes that the technical subsystems of any work unit must be balanced and optimized concurrently with the social subsystem; technological and spatial working conditions must be designed to meet the human demands of the social system. Within this framework, the key to effective performance depends on whether the work group can control the variation in quality and quantity of their task performance at source (Cordery, 1996). Such variance control implies innovation, since the work group will suggest and try to implement new and improved methods of working or technologies in order to achieve control of variance in task performance appropriately. What characteristics of the work group and the group’s task encourage creativity and innovation implementation? The joint optimization of the two subsystems is more likely when work groups have the following characteristics: The team is a relatively independent organizational unit that is responsible for a whole task. The tasks of members are related in content so that awareness of a common task is evoked and maintained and members are required to work interdependently. There is a ‘‘unity of product and organization;’’ that is, the group has a complete task to perform and group members can ‘‘identify with their own product’’ (Ulich & Weber, 1996).


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With reference to the task, it is possible to identify, according to STST, six characteristics that evoke task focus or intrinsic motivation (and therefore creativity). Tasks that involve completion of a whole and identifiable piece of work (completeness), which the team can look upon afterward as the product of their efforts are more meaningful for the group. Second, tasks comprising varied demands that consequently require the use of several skills are more motivating than repetitive tasks. A third influential characteristic is the amount of opportunities for social interaction. Tasks that involve team meetings or require exchange of information amongst colleagues are more intrinsically motivating than tasks in which individuals work alone. Autonomy is also extremely important. If the task allows the group substantial freedom and discretion to decide about their work, it fosters higher motivation. Another relevant factor for intrinsic motivation is the extent to which a task promotes development of knowledge. As a consequence of an intrinsic need for growth (Steers, Porter, & Bigley, 1996), tasks that offer the group opportunities for learning are more motivating than tasks that only require the use of previously acquired knowledge. A last characteristic is the extent to which a task allows the development of new and challenging possibilities for the team. Group Knowledge Diversity and Skills The diversity of knowledge and skills within a team is considered by several researchers to be an important element for team creativity (e.g., Amabile, 1988; West, 2002; Woodman et al., 1993). But is diversity always associated with positive outcomes such as team innovation? And how are the diverse contributions effectively integrated in order to foster team creativity and consequent implementation of innovation? Several considerations have to be taken into account in order to address these questions. In considering diversity, researchers tend to differentiate between functional diversity, that is, those attributes that are directly related to work roles (such as organizational position or specialized technical knowledge), and social categorical diversity, that is, those attributes that are more enduringly characteristic of the person (such as age, gender, ethnicity, social status, and personality) (e.g., Jackson, 1992; Jehn, Northcraft, & Neale, 1999; Milliken & Martins, 1996; Tsui, Egan, & O’Reilly, 1992). These researchers suggested that functional diversity is associated with higher levels of innovation, whereas social categorical diversity is associated with lower levels of innovation. Findings of a recent meta-analysis (Webber & Donahue, 2001), however, did not support these propositions

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suggesting that the explanation might be more complex than that. To overcome these shortcomings, Van Knippenberg, De Dreu, and Homan (2004) proposed that underlying group processes accounted for the positive and negative effects of diversity on innovation. In their categorization elaboration model (CEM), the authors corroborate that the positive effects of diversity on innovation are triggered by information elaboration processes, whereas the negative effects are triggered by social categorization processes. Prior research suggests that divergence of views offers multiple perspectives and the potential for constructive controversy. Diversity contributes to the magnitude of the team’s total pool of task-related skills, information and perspectives, and to the potential for more comprehensive or creative decision-making. For example, in a study of 100 primary health care teams, Borrill, West, Shapiro, and Rees (2000) found that the greater the number of professional groups represented in the team, the higher the levels of innovation in patient care. Groups comprising people with differing professional backgrounds, knowledge, skills, and abilities, are more innovative than those whose members are similar because they bring useful differing perspectives on issues to the group (Paulus, 2000). However, van Knippenberg et al. (2004) argue that conflict or dissent per se is not sufficient to guarantee the team’s higher effectiveness, but only if associated with the deep-level and creative processing of information. They argue that the primary process for diversity to harvest its benefits is elaboration of task-relevant information which, within the conceptualization of a group as an information processor (Hinsz, Tindale, & Vollrath, 1997, p. 1011), they define as ‘‘the exchange of information and perspectives, individual-level processing, of the information and perspectives, the process of feeding back the results of this individual-level processing into the group, and discussion and integration of its application.’’ Conflict and dissent, they add, might lead to high elaboration, but may also disrupt this process if, for example, the group just chooses a quick compromise. Further, in-depth processing might also occur without previous disagreement but just as a consequence of the change of information and ideas and viewpoints. The elaboration process can, however, also be negatively affected by diversity via social categorization and intergroup bias (van Knippenberg et al., 2004). Theories within the social identity paradigm, which are social identity theory (SIT, Hogg & Abrams, 1993; Tajfel, 1982) and social categorization theory (SCT, Turner, Hogg, Oakes, Reicher, & Wetherell, 1987) make two important assumptions. First, the theories suggest that people try to maintain a positive self-identity. Second, they hold that human beings have a


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tendency to simplify the world by sorting each other into social categories that are relevant to their identity. A wide range of social categories – specifically, all diversity characteristics – have the potential to trigger social categorization processes. Age, gender, occupational background, and culture are examples of potential categories. To secure a positive self-image and to enhance self-esteem, people develop positive views and judgments about their own category and less favorable ones about members of other categories. This so-called intergroup bias is enhanced under conditions where group members’ positive self-image is threatened (e.g., under conditions of social competition for social status and prestige and competitive interdependence within the team) leading to prejudices and discrimination of outgroup members and the formation of subgroups. Under such conditions, group members are less likely to exchange and elaborate on task-relevant information leading to lower levels of innovation. Considering that diversity is capitalized into creativity and innovation if the group has a deep level of information processing, and that this process is severely hindered if the team members perceive the existence of a threat to their identity (to their self-views), it is determinant then to minimize the perception of this threat. Although our aim is not to focus on collaboration between team members, it is important at this point to enhance the role of collaboration for diversity to be beneficial to the group. Teams in which team members work in collaboration will be more likely to have a stronger collective identity and to engage less in intergroup bias. Team members of collaborative teams are also expected to share their knowledge more promptly with the team promoting the elaboration of different perspectives. But it can be more difficult for a diverse group to collaborate than for a homogenous one (Webber & Donahue, 2001). We argue that the existence of good group processes such as intragroup safety and reflexivity can help overcome the difficulties associated with diversity and facilitate collaboration in diverse groups. External Demands The external context of the group’s work, be it organizational climate, support systems, market environment, or environmental uncertainty, is likely to have a highly significant influence on both its creativity and innovation implementation. We argue that teams will innovate partly in response to external demands, but such demands will inhibit creativity. It is important to first clarify what we refer to as external demands. We conceptualize external demands as the set of contextual factors within

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the individual, team, or organizational environment that exert a direct influence on their work, demanding further effort in order to cope effectively. External demands are likely to take the form of uncertainty (experienced as potentially threatening) and are supported with Burns and Stalker’s (1961) finding that a strong relationship exist between environmental uncertainty and organic structures in organizations, which themselves facilitate innovation. The price of crude oil is a constant uncertainty in petroleum refining and retailing organizations and this prompts continuous innovation in retail operations to win customer loyalty. Another form of external demand is time constraints imposed by the organization or the environment. Competition is also clearly a form of demand as well as the severity or of the environment. Stressors such as high quantitative or qualitative workload are also encapsulated under the term external demands. There are several experimental and field studies showing the negative impact of demands on creativity. For example, using the Luchins water jars problems (Rokeach, 1950), it is possible to demonstrate how time pressure inhibits creative problem solving. In a field study, Amabile et al. (2003) asked participants to fill in an electronic diary over 30 weeks collecting measures of time pressure and engagement in creative processing. Results showed that time pressure on one day predicted lower levels of creative cognitive processing on that day, the two following days and later. This was not mediated by intrinsic motivation (there was a positive relationship between time pressure and intrinsic motivation), suggesting a direct impact of time pressure on cognitive processes. In our research, we arrived at results that at a first glance contrast with prior examples. We have found in a number of studies that among individual health workers high work demands are significant predictors of individual innovation (Bunce & West, 1995, 1996; West, 1989). Indeed, studies of work role transitions show that changing role objectives, strategies, or relationships is a common response to the demands of new work environments (West, 1987a, 1987b). In a recent study of over 10,000 health care workers, work overload emerged as a significant predictor of innovation (Hardy & West, 2000). The relationships between knowledge diversity, external demands, group processes, and levels of team innovation were examined in a study of 100 health care teams. There was no direct relationship between external demands on teams and their level of innovation, but group processes moderated the relationship between external demands and innovation, such that good group processes and high levels of external demands were associated with high levels of team innovation. Using data


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from firms’ efforts to commercialize technological inventions, Katila and Shane (2005) verified that new firm innovation is greater in competitive and small markets and in environments that do not demand extensive production assets. Of course, the relationship between external demands and innovation implementation cannot be linear. Extreme demands or sustained high levels are likely to produce paralysis or learned helplessness. When individuals are confronted by sustained demands cannot meet, they are likely to respond with apathy or learned helplessness (Maier & Seligman, 1976). So either very low or very high levels of demands will be associated with relatively low levels of innovation implementation – an inverted U relationship. Earlier, it was suggested that creative processes (idea generation) occur in the earlier stages of the innovation process, while innovation implementation processes occur predominantly at later stages. What is suggested therefore is that external demands will inhibit creativity that occurs in the earlier stages of the innovation process, but they will facilitate innovation (via innovation implementation) at later stages. It is also interesting to analyze the relationship between external demands and collaboration. We suggest that high levels of external demands increase group cohesion because they represent a threat to the group, the corollary of which is that high levels of internal group cohesion enable the group to cope more effectively with demands and uncertainty (Mullen & Cooper, 1994). Collaboration between team members is more likely to occur in cohesive teams, we propose then that moderate levels of external demands can lead to team collaboration. On the other hand, extreme threats can be too disruptive and diminish team cohesiveness, impairing collaboration. Group Processes The group processes enable the team to translate the effects of task characteristics and diversity of knowledge into creativity and implementation of innovation; we now analyze in detail each of the following team processes considered essential for team innovation. 1. 2. 3. 4. 5.

Clarifying and ensuring commitment to shared objectives; participation; minority influence processes; support for ideas to introduce new ways of doing things; and reflexivity.

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We consider each of these processes below. 1. Clarifying and ensuring commitment to shared objectives. Ensuring clarity of and commitment to shared team objectives is a sine qua non for integrating knowledge diversity to meet task requirements for teamwork. In the context of group innovation, ensuring clarity of team objectives is likely to facilitate creativity by enabling focused development of new ideas, which can be filtered with greater precision than if team objectives are unclear. Theoretically, clear objectives will only facilitate innovation if team members are committed to the goals of the team since strong goalcommitment will be necessary to maintain group member persistence of innovation implementation in the face of resistance from organizational members. If team members have interdependent goals, that is, if they perceive the achievement of their personal goals to be positively associated with the other team members’ personal goals (Tjosvold, 1988), it is more likely that they will collaborate with each other. This can be achieved by aligning team member’s personal goals to the team goals using, for example, a contingent reward system. Strong team reward contingency (the degree to which rewards to team members are dependent on outcomes of their team) leads to higher levels of team collaboration (Harrison et al., 2002). However, the relationship between cooperative and competitive goals and team performance is not a straightforward one and requires further attention (e.g., Beersma, Hollenbeck, Humphrey, Moon, & Conlon, 2003). 2. Participation in decision-making. Research on participation in decisionmaking has a long history in both social and industrial/organizational psychology, and suggests that participation fosters integration and commitment (Heller, Pusic, Strauss, & Wilpert, 1998). But we should be wary of assuming a link with creativity at the early stages of the innovation process. Participation in teams can lead to high levels of creativity under appropriate conditions. Group members can be motivated to perform at higher levels of creativity by social comparison processes (providing group members and teams with a comparison standard) and providing feedback on individual performance (Paulus, Dzindolet, Poletes, & Camacho, 1993; Paulus, Larey, Putman, Leggett, & Roland, 1996). But it is clear that many of the benefits of group participation for the generation of creative ideas are manifested only if the group has appropriate teamworking skills. 3. Minority influence. An important perspective on conflict and creativity is offered by minority influence theory. A number of researchers have


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shown that minority consistency of arguments over time is likely to lead to a change in majority views in groups (Maass & Clark, 1983) or at least more comprehensive processing of information by majority members than would otherwise be the case. The experimental evidence suggests that while majorities bring about attitude change through public compliance prior to attitude change (i.e., the individual first publicly conforms to the majority view prior to internalizing that view), minority influence works in the opposite direction. People exposed to a confident and consistent minority change their private views as a result of more thorough cognitive processing of information. Minority influence researchers have labeled this process as ‘‘conversion.’’ Research on minority influence suggests that conversion is most likely to occur where the minority is consistent and confident in the presentation of arguments. Moreover, it is a behavioral style of persistence that is most likely to lead to attitude change and innovation (Nemeth, 1996; Nemeth & Owens, 1996). De Dreu and West (2001) integrated research on team participation in decision-making with research on minority dissent and individual creativity as well as team diversity and the quality of group decisionmaking, with research on team participation in decision-making. From these lines of research it was proposed that minority dissent would predict innovation in teams, but only when teams have high levels of participation in decision-making. This hypothesis was tested in two studies: one involving a homogeneous sample of self-managed teams and one involving a heterogeneous sample of cross-functional teams. Both studies showed more innovations under high rather than low levels of minority dissent, but only when there was a high degree of participation in team decision-making. They concluded that minority dissent stimulates creativity and divergent thought, which, through participation, manifests as innovation. 4. Supporting innovation. Innovation is more likely to occur in groups where members have made a decision to be innovative and where there is consequent support for innovation. In such teams, attempts to innovate will be rewarded rather than punished (Amabile, 1983a; Kanter, 1983). Support for innovation is the expectation, approval, and practical support of attempts to introduce new and improved ways of doing things in the work environment (West, 1990). Within groups, new ideas may be routinely rejected or ignored, or attract verbal and practical support. Such group processes powerfully shape individual and group behavior (for reviews see e.g., Hackman, 1992) and will encourage or discourage team members to introduce innovations. In a longitudinal study of 27 hospital

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top management teams, support for innovation emerged as a powerful group process predictor of team innovation (measured by independent evaluations of implemented innovations) (West & Anderson, 1996). Further, studies in TV production teams (Carter & West, 1999), primary health care teams and community mental health teams (Borrill et al., 2000) have strongly supported this finding (see also Agrell & Gustafson, 1994). 5. Reflexivity. Team reflexivity will also predict group innovation (as well as effectiveness) (West, 1996, 2000). Team reflexivity is ‘‘the extent to which team members collectively reflect upon the team’s objectives, strategies and processes as well as their wider organizations and environments, and adapt them accordingly’’ (West, 1996, p. 559). There are three central elements to the concept of reflexivity – reflection, planning, and action or adaptation. Reflection consists of attention, awareness, monitoring, and evaluation of the object of reflection. Planning is one of the potential consequences of the indeterminacy of reflection, since during this indeterminacy, courses of action can be contemplated, intentions formed, plans developed (in more or less detail), and the potential for carrying them out is increased. High reflexivity exists when team planning is characterized by greater detail, inclusiveness of potential problems, hierarchical ordering of plans, and long as well as short-range planning. The more detailed the implementation plans, the greater the likelihood that they will manifest in innovation (Frese & Zapf, 1994; Gollwitzer, 1996). Indeed, the work of Gollwitzer and colleagues, suggests that innovation will be implemented almost only when the team has articulated implementation intentions. This is because planning creates a conceptual readiness for, and guides team members’ attention toward relevant opportunities for action and the means to implement the innovation. Action refers to goal-directed behaviors relevant to achieving the desired changes in team objectives, strategies, processes, organizations, or environments identified by the team. In a variety of studies, links between reflexivity and team innovation and effectiveness have been demonstrated (Borrill et al., 2000; Carter & West, 1998; West, Patterson, & Dawson, 1999). Having analyzed the factors that promote creativity and innovation within the team, we move now to the second part of this contribution in which we look at how the team can promote the implementation of its ideas via collaboration. We first discuss different conditions that promote collaboration between teams and later focus on two specific strategies for collaboration, boundary spanning and the use of networks.


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PROMOTING COLLABORATION BETWEEN TEAMS: THE INTERGROUP RELATIONS THEORIES Teams are not isolated social structures operating in a vacuum, they function in a context of interdependent relationships with other organizational groups (van Knippenberg, 2003). They are embedded in a social and organizational context in which they are expected to assume formal collaborations and in which they are also able to establish informal collaboration relationships. In fact, as companies adopt more flexible and less bureaucratic structures, groups find themselves able to decide how to relate with other groups. As a result, organizations are more dependent on acts of voluntary and proactive cooperation between their teams for their effective functioning (van Knippenberg, 2003). Analyzing the degree to which teams are likely to collaborate with each other leads us to the domain of intergroup relations theories. Two main theories account for the effectiveness of intergroup relations, realistic conflict theory (RCT, Campbell, 1965; Sherif & Sherif, 1966), and SIT/SCT (Hogg & Abrams, 1993; Tajfel, 1982; Turner et al., 1987). RCT suggests that intergroup behavior is a reflection of group interests (Campbell, 1965). If groups perceive their interests to be compatible, they will react positively and intergroup relations will be harmonious. If the group perceives its interests to be incompatible, a range of negative answers such as prejudiced attitudes and discrimination will emerge. This means that compatible interests between teams should promote collaboration, whereas an absence of compatible interests should hinder collaboration. This idea is also present in the cooperation and competition theory, which emphasizes the role of structural aspects in collaborative settings (Deutsch, 1973; Tjosvold, 1988). It states that groups can find themselves in negative or positive goal interdependence with other groups. When in negative interdependence, the achievement of the one teams’ goals decreases the likelihood of the other team obtaining its goals. On the contrary, when in positive interdependence, the achievement of one team’s goals raises the probability of the other team having its goals reached as well (Thomas, 1992). Research within this framework suggests that effective intergroup relations are based on cooperative and not competitive interdependence between groups. Cooperation is generally associated with positive group relations, whereas competition is associated with negative group relations (e.g., Sherif, Harvey, White, Hood, & Sherif, 1961). For example, it was found in an empirical study that in situations involving positive interdependence managers

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approached potential conflict issues in a constructive manner and this constructive controversy was associated with positive outcomes such as customer service, efficiency, and the viability of the teams working together in the future (Tjosvold, Dann, & Wong, 1992). Within this paradigm, the key for positive intergroup relationships relies on positive goal interdependence between teams and the existence of a supraordinate goal. Before discussing the limitations of this theory of explaining intergroup relations, we should first reflect on how competition and collaboration relate to the specific outcome of innovation. It is generally accepted that cooperation is more beneficial than competition and is associated with a range of positive outcomes. Indeed, cooperation promotes constructive controversy (Deutsch, 1973), leads to exchange of ideas, and enables a deeper task knowledge and higher cognitive flexibility as a consequence of exposure to different perspectives. One should therefore conclude that the level of cooperation with other teams should then increase the amount of creativity within the team. Competition, on the other hand, is generally associated with negative outcomes. Although intergroup competition may enhance group performance and motivation, subject to whether or not groups are able to intervene with each others’ task performance (Richter, West, Sacramento, & Hirst, 2005; Tauer & Harackiewicz, 2004), generally the effect of competition in intergroup relations is considered to be more detrimental than beneficial. Groups in competition restrain each other not only by hoarding valuable resources, but also from the benefits of critical exchange of information. Prior studies have noted several limitations of the RCT. Some studies have demonstrated that competition is only detrimental when individuals identify with the group, whereas others have shown that cooperative goals may not reduce intergroup biases. Furthermore, other researchers have found that intergroup relations can deteriorate even in the absence of interdependence between groups, and conflicting interests (Brewer, 1979; Brewer & Brown, 1998). An alternative account of intergroup relations stems from social identity and social categorization theories (to which we referred previously when discussing the effects of diversity on team innovation). This line of research shifts the focus from the structural characteristics of interdependent groups to the cognitive processes of individuals. It is based on the assumption that individuals perceive others and themselves in terms of their membership to social groups and consequently distinguish between the ingroup (groups the individual belongs to) and the outgroup (groups the individual does not belong to). These group memberships are incorporated in the self-concept


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and represent a valued component of the individuals’ identity. Social identity is the part of the self-concept that represents the individuals’ membership in social groups. Social identification is the extent to which belongingness to a certain group is important for the self-definition of an individual in a particular situation. As the status of the ingroup reflects on the self, and people want to feel good about themselves, it is important to maintain a positive social identity. This is achieved by becoming a member of a high-status group or by ensuring that the group to which the individual belongs has higher status when compared with significant outgroups (Festinger, 1954). In this line of reasoning, even when apparently there is no reason to compete, groups might engage in social competition for status, as it is the way the group stands relative to others that contributes to a positive identity. This competition offers the grounds for intergroup biases to occur. Intergroup bias refers to the ‘‘systematic tendency to y evaluate one’s own membership (the ingroup) or its members more favourably than a nonmembership group (the out group) or its members’’ (Hewstone, Rubin, & Willis, 2002, p. 576). It can involve behavior (discrimination), attitude (prejudice), and cognition (stereotyping). Team members will favor the ingroup in their evaluation and exhibit more positive attitudes toward the other ingroup members, and at the same time they will discriminate against the outgroup members and be less willing to exhibit positive attitudes toward them. Within this framework, social categorization is the root of negative intergroup relations. The strategies to maximize collaboration between teams involve minimizing social categorization. We will now focus on the three forms usually suggested to breakdown intergroup categorizations: decategorization, cross-categorization, and recategorization. Decategorization involves breaking the ingroup/outgroup categorization by leading individuals to think of the outgroup members as separate individuals. This strategy, although previously shown successful for reducing group bias (Gaertner, Mann, Murrell, & Dovidio, 1989), has a severe drawback in that it hinders group and organizational identification and consequently hampers individual’s commitment to the group and the organizational goals. Cross-categorization is based on the fact that individuals have several social identities. Group bias can be minimized by ensuring that individuals that belong to opposite groups according to one dimension are members of the same ingroup according to another dimension (Deschamps & Doise, 1978). Although appealing, it is not logistically feasible or practical an organization to engage in calculating all the possible combinations and ensuring a balance between all individuals in all significant categories.

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Finally, recategorization is based on priming individuals that both members of the ingroup and the outgroup share a common identity as part of a larger superordinate goal (Gaertner, Dovidio, Anastasio, Bachman, & Rust, 1993). Within the social identity perspective, the promotion of both strong identification with the group and the organization (dual identity theory, Ashforth & Mael, 1989; Gaertner et al., 1993) seems to be the strategy that gathers the strongest empirical support in reducing intergroup bias (e.g., Richter, West, van Dick, & Dawson, 2005) and consequently in promoting intergroup collaboration. In summary, two different lines of research provide guidance on promoting collaboration between teams. From an RCT perspective, organizations should promote goal interdependence in order to maximize the likelihood of their teams engaging in collaborative actions. On the other hand, SIT/SCT suggests that a dual identity, meaning a strong identification both with the group and with the organization, enhances collaboration between groups. Organizations should therefore focus individuals on the fact that ingroup and outgroup share a common identity as part of the same organization.

COLLABORATION FOR INNOVATION As initially stated, for a team to be able to implement its ideas and complete the innovation process, the level of collaboration they establish with other teams and entities within the organization is a determinant of success or failure. Team members develop high expertise by closely working on their tasks, a facilitative factor of creativity (Amabile, 1983b). It is therefore more likely that the team, rather than management, can think of ways to improve the work processes. Teams often have in their possession a range of ideas that may be beneficial to their organization but these ideas are usually abandoned or set aside as they do not have the means to implement them. If a team is able to establish informal collaborative relationships with external entities, the likelihood of having its desired innovations implemented increases significantly. The establishment of formal collaboration between teams is highly dependent on the organizational structure and cannot be controlled by individual teams. Team members have the power to establish informal collaborations through informal contacts. The following sections focus on these activities and discuss how each mechanism can lead to innovation and which factors facilitate such liaisons. A comprehensive review of all the


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possible collaborative relationships a team can establish and the factors leading to its success or failure is beyond the scope of this chapter. Rather, we focus on boundary spanning and networking, two activities in which team members have enough autonomy to engage and develop. Boundary Spanning Boundary management, a set of activities teams can use to manage their organizational environment (Ancona & Caldwell, 1992), can result in useful collaborations. Prior studies found evidence that external communication may have a positive influence on team effectiveness. In a study with five consulting teams, Ancona (1990) verified that those teams which actively engaged with outsiders, revised their knowledge of the environment through external contact, initiated programs with outsiders, and promoted their teams achievement within the organization (probing teams) were better performers than those which stayed relatively isolated from their environment (informing teams) and those which presented high levels of passive observation (parading teams). In a complementary study, Ancona and Caldwell (1992) verified that, in the addition to the amount of communication, different types of communication also contributed to performance. The three types identified by the authors as determinant to team performance were vertical communication, aimed at shaping the views of top management; horizontal communication, aimed at coordinating work and obtaining feedback; and horizontal communication aimed at general scanning of the technical and marketing environment. Based on the above considerations, it is possible to extrapolate several strategies a team can pursue in order to successfully execute the desired innovation plan. If the objective is to stimulate team members’ creativity and promote generation of ideas, horizontal communication aimed at general scanning of the technical and marketing environment seems to be the most appropriate type of strategy. Of course, vertical communication with management can also be useful as it can provide the team with information on possible changes that management would welcome. However, we argue that interaction with peers will be more stimulating as it is more likely to inform the team of the latest technological developments or market needs. On the other hand, if the objective is to initiate the implementation of an idea already developed within the team, it is of extreme relevance to establish a vertical communication with management in order to seek their approval and ensure that resources are available. Horizontal communication aimed at obtaining feedback from persons outside the team is also important

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at this stage in order to reshape and improve the idea, involve more agents and obtain further support from other entities in the organization. A key factor for the team’s level of collaboration with other teams is the leader’s behavior. As the team’s representative, the leader should act as boundary spanner, initiating and maintaining contacts with other entities inside the organization and mobilizing support for the implementation of the team’s ideas. In a study involving self-managed teams, it was found that effective leaders moved back and forth across boundaries in order to build relationships, gathering the necessary information and persuading outsiders and the team to support one another (Druskat & Wheeler, 2003). The authors identified one important facet of the leader’s activity as persuasion, defined as working to influence other members of the organization to support their teams and influence team members to set priorities that support organizational goals. Successful persuasion results in team empowerment and the acquisition of resources necessary for team success. We therefore identify the role of the leader as a trigger for the team’s success in innovative endeavors. The leader should assume ambassadorial activities – gaining access to the power structure, promoting the team, securing resources, and protecting the team from excessive interference in order to maximize the chances of successful innovation implementation. Networks Personal networks, the team members’ web of personal relationships, is another mechanism that can be used by teams to promote the implementation of their ideas. Social networks have been shown to be positively associated with a range of positive outcomes, including individual and team performance (Baldwin, Bedell, & Johnson, 1997; Balkundi & Harrison, 2004; Mehra, Kilduff, & Brass, 2001). Social networks are important for both the first stage of the innovation process, the generation of ideas (for a theoretical elaboration on the effects of social networks on creativity see Perry-Smith & Shalley, 2003), and for the second, the implementation of innovation, as they can provide the team with key contacts with sufficient power to champion the idea. The strength of relationship between two elements of a network, often referred to as tie strength, is of great relevance for the effectiveness of a network (Grannovetter, 1973). Tie strength is a continuum concept that varies from weak relationships to strong relationships. Movement along this continuum is a function of the amount of interaction, emotional intensity, and reciprocity between two individuals in the network. Although apparently


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strong ties might seem to be more beneficial, it has been argued that weak ties are actually of greater importance (Grannovetter, 1973, 1982). Strong ties are more likely to be redundant within the network: if individual A has strong ties with individual B and C, even if B and C initially belonged to different networks, due to the dense social interactions they both have with A, they will eventually meet and develop another strong (and redundant) tie. As a result, there is a smaller chance of strong links being structural bridges (a connection between two networks established only by one person in each network) (Friedkin, 1980).Weak links, on the other hand, have higher probability of being unique. A large number of weak links is therefore more useful, as they are more likely to be non-redundant connections between dense social circles providing the network with a wider and more varied range of connections. Furthermore, weak links are more likely to be established between people from different social circles that do not share much in common, whereas strong ties are more common between similar people (Ibarra, 1992; Lincoln & Miller, 1979). The contact with more diverse people and consequently the acknowledgment of a wider range of perspectives is expected to trigger creativity. Individuals acquire the necessary information that builds task-relevant skills and the exposure to different perspectives also promotes the development of creativity-relevant skills, which should result in higher levels of creativity (Perry-Smith & Shalley, 2003). Additionally, stronger ties, as they are usually established within dense networks of similar individuals, are more likely to be associated with high levels of cohesiveness, low autonomy, and pressure for conformity (Coser, 1975; Grannovetter, 1973; Ibarra, 1992) that may hinder creativity. Not all the benefits are, however, associated with weak ties. For example, it was found that when in uncertain contexts, people are more likely to rely on stronger ties than in weaker ones (Grannovetter, 1982; Shah, 1998). Considering that innovation is associated with uncertainty as a new idea is being tested, we suggest that it will be more likely for a team to find support for the implementation of an innovation within their stronger tie connections than within the weaker ties. To collaborate in promoting the implementation of an innovation, the counterpart has to trust the side suggesting the idea, as the engagement in an unsuccessful innovation process can bring negative consequences to all associated with it. We suggest that weaker ties are more useful at the time the team is generating ideas, but when it comes time to implement them, the team leader should look for support within the strong ties of the network. Given the relevance of networks for team innovation, it is important to understand the factors that promote an individual’s networks. Here we

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focus on knowledge networks as these are considered a primary source of social capital with a relevant role in innovation (Ibarra, 1993). We limit our analysis to the team-level antecedents of individual networks rather than discuss organizational factors such as formal structures (Leifer & Huber, 1977) in which the team does not have direct power to intervene. A recent study addressed this issue and identified several team-level antecedents of individuals’ knowledge networks (Hoegl, Parboteeah, & Munson, 2003). In their analysis of 145 software teams, the authors concluded that the team’s perception of the organizational knowledge-sharing climate, the team’s networking preference, and the team’s perceived importance of networking for project success had a positive impact on network building. Taking into consideration these findings, we suggest that the leader might not be able to change how the team perceives the organizational climate toward knowledge sharing in the short term, but he or she should be able to influence the team’s preference for using or not using social networks for solving a problem and persuade the team members of the relevance of networking for project success, for example, by setting the example (Bandura, 1971) or through inspirational communication (Bass, 1985). However, it is important to note that not all types of networking are positive and networking is not desirable at all stages of a project. Establishing and maintaining contacts requires time and effort, which might hinder the team’s focus on the current project and also decrease team cohesiveness (Alderfer, 1986). It is also important to consider that teams in large networks have more difficulties keeping confidentiality than when they are isolated.

RECOMMENDATIONS FOR PRACTICE Leaders play a very important role in promoting the creativity of their team members (e.g., Basadur, 2004; Oldham & Cummings, 1996; West et al., 2003) and finding a sponsor to support the implementation of the teams’ creative ideas. On one hand, the leader should ensure that the team has good integrative processes, while, on the other, the leader should also represent and protect the team interests within its external environment. Team members are responsible for the team’s good functioning and can contribute to the team’s innovation with their personal networks. The following recommendations summarize key actions aimed at maximizing team creativity and fostering the implementation of ideas via collaboration with others.


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Regularly check that the team is functioning well. Leader and group members must individually and collectively develop the skills to work well as a team, encouraging integrative group processes. This means continually clarifying and ensuring group member commitment to shared objectives; encouraging information sharing, regular group member interaction, and shared influence over decision-making; and encouraging high levels of emphasis on quality and practical support (time, money, and cooperation) for innovation. It also includes encouraging group members to regularly reflect upon and adapt their objectives, strategies, and processes – consciously and continually improving their functioning as a group. Ensure that team members face challenging tasks and environments that stretch them. It is important that teams are exposed to high but not extreme levels of external demands (West, Hirst, Richter, & Shipton, 2004) to trigger the willingness to implement their ideas. At later stages of the innovation process, if group members feel pressured, or are uncertain, they are more likely to implement innovations, as long as the demands and uncertainties are created by agents external to the group – (this is sometimes called the ‘‘burning platform’’ effect) and the level of demand is not crippling. Today, competition, threat, pressure, and uncertainty are characteristic of most public and commercial sector environments, particularly as globalization increases apace. There is rarely reason to increase the level of demand. But there is much more reason to improve the level of safety and the integration skills of team members. Provide a more relaxing climate while individuals or groups are generating ideas and create a sense of urgency at the time of implementation. The team’s leader is able to influence the perception of threat and pressure. Therefore, he/she can promote a more relaxed, pressure-free climate at the time the team has to be creative and afterward create a sense of urgency in order to foster the effective implementation of those ideas. Probe the environment and discuss new ideas with the group. The leader should not allow the team to be isolated from the external environment and be without access to relevant information or recent developments in the field. It is important that team members are informed about what happens in the organization and are included and motivated to participate. The leader can be the bridge between the team and the external environment. He/she should encourage team members to scrutinize the environment and bring to the group topics for discussion that they find relevant. A more

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formal way of achieving this is to allocate a time slot every week or every fortnight just for the discussion of these topics. Engage in both vertical and horizontal communication. The leader is expected to represent the team’s interests (having previously ensured that these are aligned with the organization goals) across the organization. He/she should work toward gathering support to enable the implementation of the team’s ideas and ensure that the team has the required resources to perform its job. In order to do so, it is important that the leader is able to effectively engage in both lateral and vertical communication with peers and superiors. Ensure that the team has cooperative relationships with different teams in the organization. Having cooperative relationships with a number of teams is certainly beneficial in moving the implementation forward. These teams will provide your team with the required resources in moving its ideas forward, given that their goals are positively interdependent on the team’s goals. Promote team members’ identification with the team, and also with the organization. Identification with the team facilitates commitment and loyalty, but might lead to isolation. Ensuring that individuals see themselves as part of a team, and also part of a broader identity named organization will facilitate exchanges and collaboration between members of different teams. Foster a climate that values networking and motivates team members to maintain and build new contacts. Since team networks are of great influence to the implementation of their ideas, the leader should create a climate that fosters team members’ engagement in external contacts. This can be achieved through enhancing the value of networks and by setting an example.

CONCLUSION How can we promote effective team innovation? We have identified team diversity of knowledge and skills, team composition, external demands, and good integrative processes such as support for innovation and reflexivity which are factors critical to team creativity. Looking at how relationships with other teams can facilitate the implementation of innovation, we conclude that cooperative relationships are vital for idea implementation. Furthermore, collaboration between teams is facilitated if team members identify not only with their team, but also with the organization as a whole.


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We suggest that team members must have enough autonomy to undertake extensive and task-focused boundary spanning in order to create knowledge networks which will facilitate the implementation of innovation. Teams are the most powerful source of creativity and innovation in organizations, but we must create conditions for that powerful potential to be released.

ACKNOWLEDGEMENTS The authors are thankful to Yves Guillaume and Andreas Richter for their comments on earlier versions of this chapter.

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INNOVATION: ACHIEVING BALANCE AMONG EMPOWERMENT, ACCOUNTABILITY AND CONTROL Frances A. Kennedy and Lydia Schleifer ABSTRACT Organizations are reorganizing into collaborative subunits or teams in order to generate innovative ideas and stay ahead of the competition. Traditional control systems were established to direct employees and prevent control problems, such as fraud or theft, and were designed for vertically managed systems where managers and supervisors made decisions and their subordinates performed tasks. As companies evolve into a team-based structure, decisions are made at lower levels. Restructuring for teams makes information more available and decisions more transparent. Traditional controls no longer apply and can be detrimental to empowerment and the generation of innovative ideas. With increased empowerment there will be a need for different controls and maybe even more control. Innovation can thrive when collaboration takes place and collaboration can occur best when teams are empowered. This chapter presents three separate domains – models of empowerment and innovation, decision-influencing and decision-facilitating information, and management


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control systems – and illustrates how they interact in a holistic way to either enhance innovative culture or inhibit the generation of ideas.

INTRODUCTION It is imperative that companies innovate in order to survive (Damanpour, 1991). The market no longer forgives slowness, low quality or high cost and companies are increasingly using collaborative structures, or teams, to succeed in an environment of intense competition (Lawler, Mohrman, & Benson, 2001). Changing organizational structures to include teams is only one component of implementing collaboration. A myriad of authors discuss the importance of developing an appropriate teaming environment and culture through careful planning of group design and team training as well as consideration for long-term nurturing of a continually developing collaborative culture (Beyerlein & Harris, 2002; Hackman & Morris, 1975; Katzenbach & Smith, 1993; Kennedy, 2003; Mohrman, Cohen, & Mohrman, 1995; Shea & Guzzo, 1987; Stevens & Campion, 1994). Traditional organizations are vertically structured, with several layers of management within the reporting hierarchy, and with little question about who is responsible for decisions; in addition, performance appraisal systems complement the individual accountability in vertically managed systems. Unfortunately, the performance of these traditionally structured organizations is sluggish and slow to react to changing competitive environments. This is largely due to limited cross-functional communication, since inquiries and information go up one chain of command and down through another. Operating decisions are the purview of managers who, because they are usually separated from the process, need to gather information prior to making the decision. The communication process is inefficient and therefore decision-making is less than optimal. As companies begin evolving into flatter, more collaborative organizations, communication is enhanced; teams are empowered to make decisions; response time quickens; and teams develop innovations. But as teams take on more decision-making responsibility, the team manager is no longer always within the decision loop. The managers are often uncomfortable and concerned about being held accountable for outcomes and decisions over which they have limited influence (Ezzamel & Willmott, 1998). For example, a production supervisor may be assigned as a facilitator (or team manager) for two or three production teams. The supervisor’s manager looks to the

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supervisor to provide information and explanations about team progress. As a result, the supervisor may have a tendency to remain too involved in the team’s daily activities, which the team can interpret as evidence that it is not really being empowered after all. When managers think about control, it is most common for them to immediately think in terms of decisions – who makes what decisions; and accountability – who is held responsible for what decisions. Much of the emphasis is on personal responsibility. The commonly held idea is that the best way to ensure action is to identify an individual, measure performance, and hold that individual accountable for the consequences. The concept of control in modern organizations, however, must encompass more than just individual responsibility. The focus of management control systems (MCS) is upon the entire organization, its subunits and its employees. MCS is multi-faceted and should be designed to guide allocation of resources, actions, and decisions to pull all the efforts of the organization toward meeting shared objectives. Simons (1995) contends that with more empowerment should come more control. This is because as decisions are no longer centralized, but made at lower levels by a greater number of people, there is an increased need to ensure that those decisions are in the company’s best interests and support organizational goals. However, is there such a thing as too much control? Can excessive control or the wrong type of control be counterproductive and obstruct the meeting of objectives? If achieving organizational objectives requires innovation, at what point does too much control squash creativity? What kinds of control are necessary and appropriate in teaming organizations? We approach these critical questions in two ways. First, we present models of creativity (Amabile, Conti, Coon, Lazenby, & Herron, 1996) and empowerment (Kirkman & Rosen, 1999) and discuss implications for innovation in a collaborative organization. Second, we review a model of MCS (Merchant, 1985) and discuss the potential effects of various control mechanisms on innovation. Finally, we propose how companies need to rebalance the mix of control mechanisms as their organization evolves from traditional to team-based management. The practical implication of this framework is that it provides a guideline to companies selecting control mechanisms in order to manage and optimize innovation. The rest of this chapter is organized as follows. First, we discuss the role of different types of information used in decision-making and examine how access to information is used as a control mechanism in teaming organizations. This is followed by models of empowerment and innovation. In the final section, we explore the control mechanisms in Merchant’s (1985) control framework and how they can be adapted to team-based organizations.

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ROLE OF INFORMATION Work structures involving teams are often more efficient and effective than individual work (Hoegl & Gemuenden, 2001). Birnberg (1998) argues that coalitions evolve in order to facilitate the pooling of information. This concept suggests that team structures develop to make information more available and decisions more transparent. When team structures change, the needed information changes, and the uses of that information to measure change and motivate performance also change (Atkinson et al., 1997) A significant element of control is about managing through information. Useful and meaningful information is the lifeblood of the organization. Accessibility to necessary information when appropriate is essential to optimal performance and decision-making. Managerial accounting takes information and makes it accessible and useful so that decision makers can use the firm’s scarce resources effectively and efficiently and therefore enhance firm value (Sprinkle, 2003). This is accomplished by providing both decision-facilitating and decision-influencing information to users who manage resources (Demski & Feltham, 1976; Sprinkle, 2003). The goal of decision-facilitating information is to reduce decision uncertainty before the judgment is made. It does this by enhancing employees’ knowledge and enabling them to make appropriate decisions compatible with organizational goals. In a team setting, managerial accounting information facilitates group discussions and focuses team members on key issues. It helps them to plan, reach agreement, and, finally, to make informed decisions. In addition to this tactical help, managerial information in the form of appropriate and timely feedback concerning task outcome allows members to adjust their course of action as needed. The decision-facilitating use of information also helps to accomplish problem solving (Sprinkle, 2003). Task feedback provides not only information, but also motivates, resulting in increased effort (Hollenbeck, Ilgen, LePine, Colquitt, & Hedlund, 1998). Overall, information aids in decision-facilitating for a team when it increases the team’s knowledge and guides more informed decisions and action choices by the team (Sprinkle, 2003). Decision-influencing information is used to motivate employees and align their behaviors with owners’ interests by measuring and rewarding actions and decisions. Essentially, decision-influencing is about solving organizational control problems. Control problems arise when information asymmetry exists because the team possesses knowledge about their process that managers do not (Sim & Carey, 2003). This private team knowledge informs the team’s actions and decisions, which in turn are not always

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Exhibit 1. Uses of Information. Decision-Facilitating 1 2 3 4

To reduce uncertainty (pre-decision) To perform belief revision To accomplish problem-solving To improve employee’s knowledge and make better informed decisions and action choices

Decision-Influencing 1 2 3 4

To reduce uncertainty (post-decision) To evaluate performance To perform score keeping To help solve organizational control problems and encourage employees to act in company’s interest

Source: Demski and Feltham, 1976.

clearly understood by managers who are monitoring and measuring the team’s performance. This information asymmetry leads to a problem referred to as moral hazard, which describes the possibility that teams will make decisions in their own best interests rather than in the best interests of the organization without the manager’s knowledge. Exhibit 1 compares and contrasts decision-facilitating and decision-influencing uses of information to show overall how decision-facilitating processes lead to the decision and how decision-influencing process tends to enter into the picture after an initial decision has been reached. Information asymmetry leads to poor management decisions because managers have to fill in the information gaps about the team process and performance. Management accounting information should strive to minimize this gap and to provide information to teams to facilitate team decisions and influence manager and team actions. Sprinkle (2003) suggests that decision-facilitating and decision-influencing can be interdependent. An example of this would be quality information that can be used to both make decisions and evaluate performance. He also suggests that whereas some management accounting techniques may be used equally well for both decision-facilitating and decision-influencing reasons, there may be others that can fulfill one of these very well, but at the sacrifice of the other. Decisioninfluencing information may include group results measures used for group rewards. These measures may be focused on an immediate benefit, such as the promise of reduced costs. This could conflict with long-term goals if the specific costs are simply deferred (as with machine maintenance), and decision-facilitating information indicates that delayed repairs may cause increased damage and higher long-term costs. Contemporary technologies, such as lean manufacturing, have led companies to move toward more flexible work structures involving teams. This change in work structure ultimately requires changes in managerial

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information, recognizing that both the types of information and the users of that information are changing. Decision-facilitating information needed by teams will have to be determined partially by the degree of empowerment (decision authority) of those teams. The decision-influencing information needed by teams will be determined by the type of control exercised over and within groups; the type of control will be related to how groups are to be influenced to achieve organizational goals.

COLLABORATIVE INNOVATION FRAMEWORK Innovation and empowerment will be affected by the change from a traditional to a team-based organization. Organizations become flatter, increasing the managers’ span of control and creating a need for employees to work more autonomously at lower levels. Empowering individuals to make decisions, refine their work processes, and develop new ideas is a necessary precondition to expanding innovations. Innovation Innovation has been described as new approaches to methods or technologies (Schroeder, Scudder, & Elm, 1989). Even more simply, innovation takes an idea and turns it into action (Amadon, 1998). Generating an idea is the first step in the innovating process – there would be no innovation without that creative spark that is critical for process innovation (Sim & Carey, 2003). Montes, Moreno, and Morales (2004) call the difference between the firm’s innovation and the external environment’s level of innovation as the ‘‘innovation gap’’. Proactively filling this gap requires firms to develop certain competencies that foster the development of innovative ideas. Amabile et al. (1996) also maintain that although creativity is the ‘‘seed of all innovation’’ (p. 1155), other conditions must exist to implement a creative idea, turning it into innovation (Gilson & Shalley, 2004). These conditions are the focus of Amabile et al.’s five dimensions that promote (or stifle) the generation and implementation of creative ideas, leading to successful innovation. Each of these dimensions is described below. Encouragement of creativity. The first dimension, encouragement of creativity, comes from the organization, the supervisor, and the work group itself. Through its goals and performance evaluations, the organization can encourage or inhibit risk-taking and idea generation. If explicitly included as

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part of their job, employees will be more likely to engage in creating new ideas. The expectation of fair performance evaluation can motivate teams; however, if the expectation is threatening, employees are likely not to digress from the status quo (Amabile et al., 1996; Deci & Ryan, 1985). Supervisors encourage creativity by frequently interacting with teams, communicating clear goals, and supporting the teams. These actions communicate to teams that their role is meaningful. The group itself also encourages its members through constructive exchange of ideas, openness, and a shared commitment (Beech & Crane, 1999). Autonomy. Autonomy originates from a sense of ownership over decisions and processes. This feeling of ownership encourages team members to seek information and make decisions concerning their processes. Autonomy is most often associated with decision-making and, as such, is inextricably linked with the concept of empowerment. When autonomy leads to or supports successful decision-making, then that decision maker is empowered. Essentially, autonomy supports and thus links together both innovation and empowerment. The link between autonomy and empowerment is explored later in this chapter. The effect of autonomy as it relates to creativity and innovation is in the freedom to try new approaches. The team’s creativity is assumed to increase with increasing levels of freedom although not necessarily in a linear manner. Too much freedom, if accompanied by too little control, may undermine the improvement in creativity, causing it to decline. Having the freedom to take risks and explore ideas outside of traditional processes promotes the efficacy of the group (Amabile et al., 1996; Sim & Carey, 2003). This feeling of autonomy can be repressed, however, if team members perceive that they either do not have access to the necessary information or that their recommendations and ideas are not valued by the organization. When decision-making authority is centralized, innovation is repressed. Dispersion of power and decision-making authority facilitates innovations (Thompson, 1965) by increasing awareness and involvement (Damanpour, 1991). Allocation of resources. The third dimension concerns allocation of resources to team projects, which in turn signals to the team that its work is important and its contribution positively impacts the organization (Amabile et al., 1996). Creativity is enhanced with the perception that resources will support ingenuity. If, however, resources are continually withheld, team members perceive that their efforts are not appreciated and may reduce the expended effort. Pressures. Pressures interact with the creative processes in two ways. Excessive workload pressures can negatively affect creativity. Employees can

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simultaneously be team members on several cross-functional teams. This excessive workload can overwhelm the employee and require that he/she allocates personal resources. At the same time, it can reduce the amount of time and creative effort the team member is able to invest in any one team. The second way that pressures impact creative processes is with stretch goals. Although a difficult or unattainable goal may adversely affect performance, the pressures of a good ‘‘challenge’’ should stretch ideas and promote creativity. Almost four decades of research developing a theory of goal setting generally support the idea that the process of goal setting, done appropriately, can lead to success in reaching goals (Locke & Latham, 2002). The right mix of goal setting and pressure can promote creativity. Organizational impediments. Formal management structures, conflict and conservatism are considered organizational impediments that hinder the development of creative ideas (Amabile et al., 1996). These are external influences that send mixed signals and detract from idea generation and creative processes. One example of an impediment would be an employee appraisal system that has not been adjusted to include collaborative behavior or team results. If employees are assessed and subsequently rewarded on individual behavior alone, the effort expended in teaming processes may be reduced. A team-based organization must have the necessary organizational environment (Smolek, Hoffman, & Moran, 1999) and infrastructure to have successful teams. There are many areas in which companies should make an effort to minimize organizational impediments; among them are compensation, selection of teams, training, information systems, communication methods, and technology (Smolek et al., 1999). Empowerment Innovation can thrive when collaboration takes place and collaboration can occur best when teams are empowered. Innovation takes place, ‘‘. . . when different ideas, perceptions, and ways of processing and judging information collide. And it often requires collaboration among players who see the world differently’’ (Leonard & Straus, 1999, p. 57). As companies are changing their work structures to involve teams, they have been empowered to make decisions within the scope of the team mission. Empowerment can be defined as ‘‘y a means of giving the authority to make decisions to that level or people in the organization which, by virtue of available knowledge and closeness to the activity concerned, is most able to make a correct, quick, and effective decision’’ (Sim & Carey, 2003, p. 112). An essential ingredient for empowerment is information. In team-based organizations,

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decision-facilitating information needed for decisions should be made more available to teams. This information allows them to see the big picture and to better understand their roles and make informed decisions (Spreitzer, 1996). Transfer of power and decision authority to the team positively influences the teams’ perception of opportunity (Robbins, Crino, & Fredendall, 2002) and yet empowerment can also contribute to information asymmetry because as teams seek their own information, managers are no longer the team’s primary source. Teams often have an information edge because they are closer to the process and because managers cannot observe all the inputs into that process. Communication is essential so that each party, teams and managers, has the appropriate information required for decision-making at that level. Communication can also facilitate the sharing of power and decision authority. As teams accept the mantel of empowerment from the managers who are enabling this empowerment, they can begin to function as intended. This chapter draws on empowerment categories described in Kirkman and Rosen (1999). They describe four dimensions of team empowerment: potency, meaningfulness, autonomy, and impact. Their model emphasizes the point of view of a team or teams that have successfully become empowered. Potency is the collective belief of a team that it can be successful in reaching its goals (Guzzo, Yost, Campbell, & Shea, 1993) and is influenced by the team’s perceptions of available resources and the skills and abilities of its team members. Meaningfulness at the team level is a shared perception of how to value their task and whether they perceive the team has a worthwhile impact on the organization. Autonomy is the degree of decision-making authority teams exercise in their task environment. Team autonomy reflects freedom and independence in choosing actions as a team. The last dimension, impact measures the teams’ perceptions about the value of their work to the organization. Teams can assess their impact by gathering feedback from outside the team (for example, from customers). Kirkman and Rosen (1999) find that these four dimensions of empowerment are distinct and yet related in the sense that they are mutually reinforcing. These two models of innovation (Amabile et al., 1996) and empowerment (Kirkman & Rosen, 1999) contain overlapping and complimentary dimensions. Both models include autonomy or decision-making authority. In Amabile et al.’s (1996) innovation model, practices and behaviors encourage creativity because the team perceives that its task is valuable. This links closely with Kirkman and Rosen’s (1999) meaningfulness dimension because of the perception that the team contributes to the organization. The resources dimension of innovation (since receiving resources signals value)

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influences teams’ perception of the potency and impact dimensions resulting from their empowerment. The pressures dimension of innovation can increase or decrease potency. Finally, the innovation model goes a step beyond the empowerment model by describing impediments to innovation as formal organizational structures and conflicts. Whereas this dimension is not explicitly included in Kirkman and Rosen’s (1999) empowerment model, it is not too great a leap to suggest that these obstacles would also restrict the extent to which teams feel they are actually empowered. Exhibit 2 displays a Conditions Enabling Successful Collaboration and Innovation

EMPOWERMENT (Kirkman and Rosen 1999)

CONDITIONS FOR CREATIVITY (Amabile et al1996)

Encouragement of Creativity Potency

Autonomy Meaningfulness Allocation of Resources Autonomy Pressures Impact Organizational Impediments

Exhibit 2.

Complimentary Dimensions of Empowerment and Creativity.

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more complete representation of the relationships among mutually reinforcing dimensions of these models. This discussion highlights the need to take a more holistic approach to engaging the entire organization in motivating innovative behavior. Accountability Managers are anxious about releasing their decisions because there is no guarantee that employees will work to pursue established priorities (Ezzamel & Willmott, 1998). When considering how to make people act in certain ways, making people accountable for actions is the most natural and the first thing that comes to mind. However, accountability is not the panacea of ensuring that decisions are made as desired. Other considerations must be taken into account. In this section, we discuss the concept of accountability to the organization and how the failure to take a holistic view of accountability can be detrimental to decisions. This is followed by a discussion of management control from a systemic point of view. Simons (1995) argues that with decision-making authority (empowerment) should come accountability for decisions. A situation that accommodates accountability provides a way to measure whether expectations have been met. Full accountability is only possible when performance is measured quantitatively (Epstein & Birchard, 2000). Improper actions may result, however, when too much reliance and managerial emphasis are placed on metrics. Excessive reliance on metrics relieves the decision maker of the responsibility to integrate additional information (Porter, 1995). Tetlock’s (1985) behavioral theory of accountability maintains that the knowledge that one will be held accountable affects behavior. Further, when the dimensions upon which individuals will be held accountable are clearly defined for them, they will organize themselves around those dimensions. Therefore, establishing a system that clearly makes managers and teams accountable will make them more aware of the need to react to information cues (Birnberg, 1999). Birnberg also argues that high levels of accountability may be inconsistent with high levels of innovation. For example, a system like total quality management (TQM) is centered on a number of criteria (like a focus on continuous improvement and customer satisfaction) that require being attuned to various information cues. Holding people accountable for measurements of these information cues will supposedly lead to the ability to make things better through adapting. Therefore, effective TQM depends on being able both to control and to learn (Sitkin, Sutcliffe, & Schroeder, 1994); the drawback is that too much emphasis on routine

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measures may undermine the motivation to innovate. As the responsibility for decisions descends to lower levels (for the purpose of encouraging innovation), there is greater need for mechanisms that facilitate the diffusion of decision authority and balance the factors that enable organizations to both control and empower their teams so that they can innovate (McNair & Carr, 1994). For this to happen, management should attend to all four elements of accountability: governance, measurement systems, management systems, and reporting (Epstein & Birchard, 2000). Governance. Organizations are under increased pressure to improve governance and make it transparent. As boards of directors face increased pressure to be independent but also to be more knowledgeable about and involved with decision-making for the organization, organizations have to create an environment where outsiders need to be able to come in and immediately understand how the organization is running. As a control mechanism, performance measures are seen as a device to demonstrate to the board of directors how the organization is performing and in turn to provide the board with a means of exercising its independent oversight. Measurement. The corporate world already operates in an environment of increased emphasis on non-financial as well as financial measures (Scott & Tiessen, 1999). Quantifying performance provides a measure that is an objective assessment, minimizing judgment and depersonalizing the assessment process (Ezzamel & Willmott, 1998). Measurement is considered a natural way to make employees accountable because it is perceived as being biasfree. With the focus on creating and identifying indicators for decisionmaking and value creation, the corporate culture is ready to support and maintain a team performance measurement system. The success of contemporary manufacturing techniques, such as just-in-time (JIT) and TQM, hinge on measuring and managing processes. The continuous improvement culture originating with these manufacturing techniques has broadened into the lean enterprise environment and now includes knowledge work processes (Swank, 2003). In a recent presentation, an employee-involvement manager at the Boeing Company included process measurement as a lesson learned on their journey to continuous quality improvement (E. Schaniel, personal communication, October 3, 2004). Management systems. Management systems have to be able to link business strategy with workers at all levels. The challenge in this is that employees need to see the link between what they do and that business strategy. They need to buy into the measures that are used to assess whether their actions lead to meeting business goals and strategies. The appropriate (or optimal) management system will enable managers and employees to

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determine what shows success and how to measure it. Management systems govern information access and, as such, provide the decision framework for the information user. The levers of control framework developed by Simons (1995) to characterize management systems describe two types of controls: diagnostic and interactive controls. Diagnostic controls are designed to ensure that predictable goals can be achieved in complex environments where a large number of decisions are made by subordinates. Senior managers need to be assured that these decisions are made in line with organizational goals. The formal informational systems designed to provide a performance comparison to present expectations are diagnostic controls. In other words, quantitative goals are predetermined and compared with actual performance, highlighting deviations. This type of management system is designed to ensure a set level of performance and therefore limits innovation. On the other hand, interactive control systems stimulate new learning and allow new strategies to emerge. These controls involve information that continuously monitors critical information that may require managers to adjust strategy (Simons, 1995). An example of an interactive control would be information about changes in the competitive environment external to the company. Interactive controls are designed to encourage new information search and promote innovative thinking. Reporting. Reporting structures both facilitate and inhibit innovation. Hierarchical levels increase the number of communication channels, inhibiting the flow of innovative ideas (Hull & Hage, 1982) because at any juncture information can be blocked or transformed. There has been considerable emphasis in the press lately on increased transparency for external financial reporting. The obvious reason is that, in a number of cases, inaccurate or insufficient information led investors to make less than optimal decisions and did not monitor company performance in a manner that alerted them to changes that would prompt investor actions. For similar reasons, there should also be an emphasis on the transparency of internal reporting, both financial and non-financial. The pay-off of this transparency is the ability to engage stakeholders to generate ideas and innovations to improve the business (Epstein & Birchard, 2000). Measuring team outcomes can facilitate this internal transparency and even has the potential to inspire new ideas for adding value. Transparency can be achieved through access to real-time information by all employees, reducing information asymmetry between team members and managers. Exhibit 3 shows empowerment and innovation as complimentary states whose dimensions overlap and enhance one another as previously discussed.

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EMPOWERMENT: giving authority to make decisions (Sim & Carey, 2003) Positive: Empowerment requires greater control (Simons, 1995; Sim & Carey, 2003) Negative: Empowerment could lead to control failure or control could lead to empowerment failure(Sim & Carey, 2003) Positive: Empowerment phenomenon shifts the focus of accountability (McNair & Carr, 1994). Negative: Empowerment enhances firm performance only when workers are held accountable for their output and when collective welfare is maximized (Sims & Carey, 2003).

INNOVATION: The successful implementation of creative ideas within an organization (Amabile et al. , 1996)

Positive: Independent innovations are greater with individual-based incentives; cooperative innovations are greater with group-based incentives (Sim & Carey, 2003) Negative: The controllability principle may reduce innovation (Atkinson, et al., 1997) by restricting actions and decisions.

Positive: Supportive, informative evaluation can enhance the intrinsically motivated state that is most conducive to creativity (Amabile et al., 1996; Deci & Ryan, 1985) Negative: Expectation of threatening, highly critical evaluation can undermine creativity (Amabile, et al., 1996)

ACCOUNTABILITY: Being held responsible for ones’ actions (Tetlock, 1985; Birnberg, 1999)

Exhibit 3.

CONTROL: Communicating and motivating behavior to pursue certain goals (Birnberg 1999; Sims and Carey, 2003)

Tensions between Empowerment/Innovation and Accountability/Control.

Empowerment requires the appropriate level of competency and therefore depends on the right training and experience. Too much empowerment without direction and control can endanger the security of the company through poor decisions by people with insufficient information or without the expertise to use the information they do possess. Too little empowerment restricts innovation because people do not have the autonomy or the encouragement necessary to develop creative solutions and rarely want to expose themselves by taking risks that may not only be unappreciated, but could result in punishment. Further, the controllability principle may reduce innovation because managers gauge the riskiness of stepping out of the status quo (Demski & Feltham, 1976; Gibbs, Merchant, Van der Stede, & Vargus, 2003) and the majority of performance measurement systems encourage maintenance of the status quo. Accountability and control are also complimentary mechanisms in that existing control devices make specific people accountable for their actions. Exhibit 3 illustrates positive and negative tensions between empowerment/innovation and accountability/control.

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MANAGEMENT CONTROL SYSTEMS MCS reinforce goal congruence and corporate values and beliefs (Sisaye, 1998). Merchant (1985) describes control as ‘‘keeping things on track’’ (p. 1). In an organization, control focuses on human behavior since it involves influencing people to help achieve an organization’s goals. Control problems usually stem from three sources (Merchant, 1985). The first problem is that employees lack direction and do not have a clear picture of what is expected of them. Not understanding expectations reduces the likelihood that actions will be as desired. The second problem is motivational where there is a lack of goal congruence between the individual and the organization. This creates the situation where an individual heads down a path or set of actions (either intentionally or unintentionally) that is not contributing to organizational goals. The third control problem is due to personal limitations that simply result in an individual being incapable of performing a given task. This is largely due to lack of training, experience, or necessary information. A control system is a collection of control mechanisms with the goal of avoiding unpleasant surprises in the future. Merchant (1985) suggests three categories of control mechanisms: results controls, action controls, and personnel controls. The following section discusses these categories as they would be defined and applied in a traditionally managed organization. We use the phrase ‘‘traditionally managed organization’’ to describe a vertically managed organization where managers make the majority of key decisions and subordinate employees perform their job tasks under management’s direct supervision. Following this discussion of controls in traditionally managed organizations, we present how these controls need to be modified in team-based organizations whose goal is to facilitate innovations. Controls in Traditionally Managed Organizations Results, action, and personnel controls have traditionally been designed and implemented to enable managers to make decisions and employees to do their work accordingly. Each of these types of controls facilitates motivating employees to work toward organizational goals. Results controls. Results controls involve rewarding people or holding them accountable for certain outcomes. Usually these results are defined in financial terms, such as return-on-assets, net income, or market share. To be effective, results controls should fulfill three criteria. First, they should provide useful knowledge of desirable results to managers. Top managers,

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who are usually responsible for overall performance, can easily find applicable measures. Managers may find it somewhat easier to develop results measures for narrow, routinized tasks such as those found on a production line. These measures become more difficult to define for complex tasks and for middle managers whose responsibilities are varied (Merchant, 1985). The second criterion for effective results controls is that individuals be held accountable for only the results over which they have control. A key behind the successful interpretation of results measures is that these metrics are only useful when they provide information about the actions that were taken to achieve those results. If, however, the results are not controllable by the individual held accountable, the measures cannot tell us anything about the actions that are controlling the results (Merchant, 1985). The third criterion requires that the results can be measured effectively. This means that the measures should be congruent with objectives, as precise as possible, objective and timely. The affected individual must understand what results are being measured and how to affect changes (Merchant, 1985). Action controls. Action controls involve making people perform (or not perform) certain desirable (or not desirable) actions. Action controls are direct controls in the sense that they directly enforce those actions that are best for the organization. A strength of action controls is that there is a close link between actions or decisions and outcome that can more easily and quickly be monitored. According to Merchant (1985), there are four forms of action controls: behavioral constraints, preaction reviews, action accountability, and redundancy. Behavioral constraints can be either physical or administrative and prevent people from doing things that should not be done. Physical constraints are designed to make it impossible to engage in an unwanted task. Examples include locks, passwords, and controls over physical access to information. Modern lean production technologies would call this a poke-yoke, or errorproofing (Galsworth, 1997). Administrative constraints (a form of behavioral constraints) include separation of duties and centralization. The latter constraint became very popular in the late 1980s and early 1990s as a means of centralizing decision-making to top management levels. This entails removing decision-making autonomy from lower level employees. The behavioral constraint is the most dominant form of control in traditional organizations (Merchant, 1985). Preaction reviews are intended to head off a mistake or control problem before it occurs. It normally involves formal policies, guidelines, and

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standard operating procedures that guide decisions in a certain direction. This effectively takes unfavorable options out of the decision mix. Preaction reviews can also be informal, simply with the supervisor being in close proximity to the individual. This form of supervisor–employee monitoring regulates actions by eliminating mistakes before they happen and with the threat of imminent review at any time (Merchant, 1985). Action accountability is an action control that holds employees accountable for actions and decisions. It specifically requires defining the acceptable action, tracking performance, and rewarding or punishing according to the results. This type of control is most effective, or is most likely to achieve its objective, when communicated through written rules and procedures though these controls are often communicated orally in professional organizations (e.g., lawyers, doctors) (Merchant, 1985). Redundancy is the final type of action control and involves assigning more people to a task than necessary. This is most common in computer operations where keying of information is done twice to validate entry. Inspection of work product is another common form of redundancy control. As companies strive to compete on lower costs, many instances of redundancy controls have been eliminated. One example is the elimination of product inspection after production due to the implementation of more regulated work processes. Personnel controls. Personnel controls depend on self-control and social control. Self-control is the notion that most people are internally motivated to do what is right and derive self-satisfaction from doing so. Social controls rely more heavily on placing individuals in a setting that encourages mutual monitoring by peers. Companies can encourage monitoring behavior in several ways. Through careful hiring and assignment to work groups, employers can ensure that the right mix of experience and knowledge is available to the work unit. Training provides a positive motivational effect because it engenders a greater sense of professionalism as well as the confidence that comes with having more knowledge about how to complete a particular job. A company can also nurture the culture in such a way that employees have a sense of shared traditions, beliefs, and values. Although difficult to achieve, a shared culture can be a very effective way of ensuring that employees behave in desirable ways. Providing groupbased rewards to compliment individual rewards encourages peer monitoring in order to share workloads and achieve group goals. Finally, providing resources, such as information and supplies, signals to the team that their work is important and they have the support of the organization (Merchant, 1985).

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These three categories of controls as originally defined by Merchant (1985) are well suited to traditionally managed organizations. Clear indication of this is the emphasis on results measures and behavioral controls that are heavily laden with restrictive information access and supervisory controls. The primary decision makers are the managers and supervisors and, thus, the control mechanisms restrict information access to them and hold them individually accountable for their actions and decisions. Controls in Team-Based Organizations Empowerment requires greater control and must be balanced with control in a way that does not lead to either a control failure or an empowerment failure (Simons, 1995). Birnberg (1998) argues that the focus of control systems is shifting from controlling individuals and tasks to controlling the organization. In their field study of a Fortune 500 manufacturing company, Selto, Renner, and Young (1995) found a conflict between vertically managed organizations and empowerment needs (e.g., information, autonomy) in teaming environments. This company had reorganized the workforce into minimally empowered workgroups, but failed to provide the necessary information or the authority to manage their work. As traditionally managed organizations evolve into team-based organizations, traditional controls that focus on making supervisors and managers primarily accountable for decisions are no longer effective. This is because the actor – or decision maker – changes. As decision-making moves to lower levels, access to decision-influencing and decision-facilitating information must also change. The shift from management to workers, or concertive control (Barker, 1993; Sisaye, 1998), requires that management rethink control mechanisms. It is not always easy to see necessary changes in existing, traditional mechanisms that have been used for years. Also, in Barker’s (1993) experience, the exercise of control by fellow team members (concertive) seemed to become tighter and more oppressive than bureaucratic control. So it is not always easy to accomplish the change in control smoothly or effectively. We posit three primary differences in control mechanisms between vertically managed and team-based organizations. The first of these concerns results controls. Whereas these controls consist mostly of financial outcomes, such as return on assets or net income, they are well suited for upper managers responsible for overall performance. These are not as useful for teams who require more real-time feedback information, and generally more non-financial measures, in order to facilitate their decisions.

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Consequently, results control measures focus on the upper levels of management and are not as prevalent throughout the team-based organization. The second major difference concerns action controls. As described by Merchant (1985), action controls are used to make people act in certain ways due to the close tie between the action and the outcome. Merchant’s action controls involve close supervisory control through monitoring and behavioral constraints including restraints in accessibility and detailed documented procedures. These are well suited to traditionally managed organizations where supervisors are held accountable for the outputs of their subordinates, but they are not conducive to the empowered workforce. Interestingly, Merchant (1985) maintains that action controls can discourage creativity and innovation because people are constrained in their choice of actions and tend to follow the rules. He further argues that results controls are more conducive to innovation because results measures provide direction and yet leave the actor to determine how to achieve those results. Results controls, however, are lagged measures and are not timely enough for real-time decisions and are, therefore, not conducive to innovations (Merchant, 1985). Empowerment requires less supervisory control and procedures and more decision-facilitating information in the form of frequent feedback concerning the process in question. Therefore, action controls in team-based organizations must be expanded to include more process information and less direct supervision. The third difference in control mechanisms is in the personnel controls. Merchant (1985) describes these as relying on self-control and on group monitoring. In a traditionally managed organization, there is less emphasis placed on this control category because of the extensive use of action and results controls. In a team-based organization, however, results controls are less applicable due to decisions being made by employees at lower levels. There are more action controls in the form of timely feedback as well as much more emphasis on social mechanisms. Personnel, or social, controls develop human capital through training, empowerment, and peer pressure. Exhibit 4 graphically illustrates the dramatic shifts in control mechanisms required to meet the needs of collaborative organizations. Traditional organizations rely heavily on results controls because decision-making is centralized with management. As described earlier, results controls are historical and usually provided to lower level employees too late to be useful for real-time decisions. As results controls lose relevance in team-based structures where employees are empowered to make decisions more frequently, action and behavioral controls substitute for these deficiencies. For example, as less real-time results information is available, there is greater reliance on the employees’ training and experience (personnel controls) to make appropriate and effective decisions.

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Shifts in Control Mechanisms 100% 80% 60% 40% 20% 0% Traditional Team-Based Organizations Organizations

Exhibit 4.

Results Controls Action Controls Personnel Controls

Shifts in Control Mechanisms.

REBALANCING CONTROL MECHANISMS The introduction posed questions concerning excessive or inappropriate use of control mechanisms and potential effects on innovation. The chapter has discussed at length three domains that must somehow interrelate in order to successfully drive innovations: (1) the use of information to control and guide actions, (2) conditions for empowerment and creative innovations, and (3) the selection of control mechanisms. These three separate domains interact to create an environment that will, when thoughtfully aligned, either facilitate productive collaborations, or obstruct employees from acting in the company’s best interests. Exhibit 5 demonstrates how these three areas interact to influence appropriate actions. In this exhibit, the decision makers are teams, while the desired action/ decision is innovation. Decision makers initially use decision-influencing information in the form of targets and results measures to guide their actions. This information provides direction and motivation. Behavioral controls, such as timely feedback, and social controls, such as training and peer pressures, provide decision-facilitating information that allows the decision maker to adjust their subsequent strategy and actions. Decision-facilitating information is a critical requirement of empowerment. When decision-influencing and decision-facilitating information provide conflicting directions (e.g., different priorities and values), then the probability of the decision maker reaching the organizational goal of innovation is greatly reduced. However, when decision-facilitating provides appropriate information for an action and decision-influencing information communicates similar priorities, the probability of a successful outcome increases.

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Personnel Controls

Decision Facilitating Information (enhances empowerment)

Action Controls

INNOVATION

DECISION-MAKERS (TEAMS) ACTION/DECISION

Decision Influencing Information (provides direction and motivation)

Results Controls (targets and rewards)

Exhibit 5. Interaction of Information, MCS and Innovation.

CONCLUSION There is always pressure on organizations to change and improve. Recent trends have pushed organizations to evolve into team-based organizations in order to improve through innovation. The goal is to increase innovation in a way that leads to improvement. An appropriate amount or level of empowerment will facilitate that innovation. However, this empowerment of teams in a collaborative environment will put demands on the organization’s systems that will require shifts in the accountability and control mechanisms until the right balance is achieved among all the factors that comprise the concepts of innovation, empowerment, accountability, and control.

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INNOVATION AND TECHNOLOGY TRANSFER INTERMEDIARIES: A SYSTEMIC INTERNATIONAL STUDY David Pollard ABSTRACT This chapter considers the role of technology transfer intermediaries (TTIs) in the processes of innovation in networks involving universities, research and development centres, and business firms from an international perspective. A diversity of types of TTIs is recognised in terms of their particular interests in the operation of innovation processes and the conditions they impose in transactions involving intellectual property. It will identify the various objectives of sponsoring stakeholders as differentiating the missions and accountabilities and, in turn, determining the focus and roles of different types of TTIs and the interactions and networking between them, both formal and informal. In discussion, the chapter will propose that the significance of systemic influence on the processes of technology transfer and innovation should be researched at two levels. At the micro-level of personal interactions, examining how systemic influences shape tacit knowledge transfer between and learning by individuals engaged in research and innovation processes. Second, at the level of national cultures, examining the ways in which the Innovation Through Collaboration Advances in Interdisciplinary Studies of Work Teams, Volume 12, 137–174 Copyright r 2006 by Elsevier Ltd. All rights of reproduction in any form reserved ISSN: 1572-0977/doi:10.1016/S1572-0977(06)12006-3

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cultural context institutionalises patterns of innovation and technology transfer networking.

INTRODUCTION Perhaps due to the sheer diversity of organisations, and departments within organisations, which function as technology transfer intermediaries (TTIs), such as university faculties and industrial liaison offices, governmentsponsored agencies of various types and private research institutions, no generally agreed definition of what constitutes a TTI has thus far been advanced. Most commentators, however, agree that the fundamental purpose of a TTI is to stimulate and facilitate the flow of intellectual property (IP) to business organisations of varying size (e.g., see Shiau, Smith, & Cesa, 2001) to enable the evolution of effective value-creating applications through effective integration of new IP with existing systems. Universities and independent research institutions have also established TTIs to facilitate the commercialisation of IP created by staff members, one common example being the commercialisation of university research output (Siegel, Waldman, Atwater, & Link, 2003). Although TTI organisations exist in diverse forms, they invariably function as part of complex networks, which generally meet the twin goals of minimising the cost of obtaining useful and reliable information and of providing target organisations (usually small and medium size enterprises (SMEs)) with scientific and technological information and services related to the various corporate functions. As will be shown, regional and local networks often operate together and, in addition, both national and international networks may play significant roles. These networks often defy sectoral barriers; as what attracts firms may be the important features of regional institutions such as universities and venture capital firms. This decentralised system provides significant mechanisms through which intangible technological capabilities and understandings can be diffused. A great deal has been written concerning the transfer of technology from one entity to another. Many factors have been studied, such as the ability of organisations to benefit from technology transfer (technology absorption and absorption rates); the role of institutions at a national and regional level in the creation and transfer of new technology (national and regional innovation systems); the role of SMEs in both generating and integrating new technology through collaboration and otherwise, and the mechanisms of transfer and the formation and operation of various types of network.

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Rather fewer studies have investigated interactions between people and organisations, the personal relationships involved and the implications of networking in technology transfer activities, especially across borders. As will be shown, government policies related to the diffusion of new technology vary between countries, but there is general recognition that there is a fundamental requirement to diffuse such technology, in order to provide economic development opportunities and to attract new investment. While policy content differs and the mechanisms and networks for technology diffusion exist at various levels of sophistication, there is considerable similarity in motive on the part of national and regional governments. Pouder and St. John (1996) suggest that innovation is subject to individual, organisational and environmental influences. A systemic approach has been adopted in this study owing to the fact that systems thinking and systemic analysis provide a holistic method of examining the complex methods employed by various actors, agencies and organisations in operating together within innovation systems and how the various components of these systems interact with their environment or outside influences. Furthermore, in taking a holistic approach, both the tacit and explicit natures of TTI interactions with their sponsors and target organisations can be identified. The environmental factors affecting the operation of TTIs are discussed later in this chapter. The aim of this chapter is to explore the systemic characteristics of TTIs and their function in the IP transfer process in various countries and contexts, including national, regional and local innovation systems. The importance of absorptive capacity and of networks for TTIs is explored. Following a discussion of the contexts within which TTIs operate, the main stakeholders in the process and their roles are described. These stakeholders include governments and, on occasion, large firms as sponsors, universities and R&D institutions as hosts and businesses, in particular SMEs, as IP users. The international context of TTIs and innovation is described and commonalities discussed, before moving to a general discussion of TTIs within various innovation systems including the challenges facing TTIs in the effective diffusion of new technology and the increasing complexity of networks. Finally, suggestions for further research are advanced.

THE CONTEXT OF TECHNOLOGY TRANSFER AND IP INTERMEDIARIES A great deal of research attention has been given to the aims and objectives of technology transfer and, more recently, to the technology transfer process

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itself; but comparatively little attention has been paid to the systemic nature of these processes (Chung, 2002) and to the operation of TTIs in general. Fritsch (1999) states that a significant advantage of analysing innovation systems in a systemic manner is that such an approach may be utilised to account for the activities of institutions and other organisations and actors within the innovation system as well as their interaction with external bodies and individuals. As Balzat and Hanusch (2004, p. 198) suggest, ‘‘y the systemic approach to innovation is based on the notion of non-linear and multi-disciplinary innovation processes, and interaction on the organisational level as well as the interplay between organisations and institutions, is given central interest.’’ The literature concerning IP intermediaries displays similar features, in that their individual functions have been relatively extensively researched but not the interaction between them and other actors (Shohet & Prevezer, 1996). Yet it is these interactions, together with the aims and purpose of intermediaries, which form an essential part of innovation and technology transfer systems. In order to understand the nature and effectiveness of such interactions, it is necessary to discuss various innovation systems and the significance of firms’ absorptive capacity on those interactions.

Innovation Systems According to Metcalfe (1995, p. 462), an innovation system ‘‘is that set of distinct institutions which jointly and individually contributes to the development and diffusion of new technologies and which provides the framework within which governments form and implement policies to influence the innovation process. As such, it is a system of interconnected institutions to create, store and transfer the knowledge, skills and artefacts which define new technologies.’’ The effectiveness of an innovation system is strongly correlated with the nature and intensity of the systemic interactions and networks involving relevant institutions, organisations and learning processes (Freeman, 1991; Patel & Pavitt, 1994). Fritsch (1999) suggests that although many authors deal with innovation systems at the national level, this should not form a limitation to investigations. In fact, several commentators have taken a narrower geographical locus of analysis, discussing, inter alia, international and regional systems that include examples of regional development and the operation of industrial districts or clusters.


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Supra-National Innovation Systems Surprisingly, perhaps, very little research work has been done in analysing the interactions of various institutions, companies and others in assisting with policy design and implementation at the supra-national level (i.e. within geographical groups of nations or in a wider international context). In the European Union (EU), several schemes have been developed over the past decade to promote innovation, both within the existing EU member countries and in those countries seeking membership. Caracostas and Soete (1997) demonstrate that simultaneous development has occurred between EU institutions and innovation-led organisations. The operation of EU-wide programs of innovation, for example, and the actors, organisations and institutions involved inform national systems of innovation. In comparison, within the Association of South-East Asian Nations (ASEAN), relatively little has been done to formalise innovation systems across member states, although some cross-border collaboration has been evident (Konstadakopulos, 2002).

National Innovation Systems Considerably more attention has been given to national innovation systems, although the concept is of comparatively recent vintage (Freeman, 1995; Lundvall, 1992). It has been further elaborated and applied in varying contexts – see, e.g., Balzat and Hanusch (2004); Edquist (1997); Lundvall, Johnson, Andersen, and Dalum (2002); Nelson (1993); Patel and Pavitt (1994). Chung (2002) provides both what he terms a narrow and a broad definition of a national innovation system; the former concentrating on organisations and institutions, while his narrower definition is similar to that of Metcalfe (1995) in which it also includes interactions and collaboration activities. Cooke, Uranga, and Etxebarria (1997) suggest that national innovation systems are also built around national commonalities such as history, culture and language. Organisations, institutions and actors interact and influence one another within national innovation systems. The locus of attention should therefore reach beyond product and process innovation to relevant learning processes, networks and the existence of skilled labour. Recent research has taken the concept of national innovation systems further, by assessing the nature of the various organisations and institutions involved, and by examining measures of performance effectiveness and policy generation (see, e.g.,

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Lundvall et al., 2002). The existence of different evolutionary trajectories within national systems has been identified and this has given rise to debate on the sources of regional and local innovation systems.

Regional and Sub-Regional (Local) Innovation Systems Freeman (2002) notes that the word ‘regional’ can be used to describe two separate phenomena: wider geographical areas, including several countries such as south-east Asia, and areas that are sectors of nations – counties, states, etc. This ambiguity goes even deeper when one considers smaller industrial concentrations, such as industrial districts in Italy, science parks and university – business incubator links. Doloreux and Parto (2005) claim that, although ambiguities remain, the concept of a regional innovation system has evolved into a position where it may be utilised in developing an empirical base for policy making in innovation, a view supported by Chung (2002) and Carlsson and Stankiewicz (1995). However, both the latter researchers and Berman and Machin (2000) recognise that wider international issues may also be relevant. Interest in regional innovation systems has increased during the past decade (Doloreaux & Parto, 2005), mainly due to the success of particular clusters of firms. While there is no precise definition of a regional innovation system, they cite the work of Dolereaux (2003) to suggest that such a system comprises ‘‘a set of interacting private and public interests, formal institutions and other organisations, which function according to organizational and institutional arrangements, together with relationships conducive to the generation, use and dissemination of knowledge’’ (Doloreaux & Parto, 2005, pp. 134–135). This definition is remarkably similar to Chung’s ‘‘narrow’’ definition of national innovation systems (Chung, 2002), and research institutions, universities, business organisations and regional government are identified as the main players in a regional innovation system. Regional innovation systems, like national innovation systems, seek to encourage firms within the region to develop various forms of capital that are derived from social relationships and interactions within the community. Such behavior results in local knowledge synergies which help firms in the region to compete and which also provide a basis for local economic development, although the extent of the economic contribution of innovation systems remains questionable (Oh, 2002). The existence of localised systems, such as clusters and business incubators constructed adjacent to university campuses, brings into question the


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generic usefulness of the term ‘‘regional innovation systems.’’ While business parks, clusters and other types of industrial agglomeration develop within a systemic interaction of national and local government initiatives seeking to promote the diffusion of innovation and learning, many of the networks and TTI-based activities that enable such diffusion emerge around localised industrial agglomerations. Ambiguities with the word ‘‘regional’’ still have the power to confuse; although some attempts have been made to address this area of ambiguity, for instance, Breschi and Malerba’s (1997) work on sectoral systems of innovation. The context in which TTIs operate is affected by the ability of target organisations to identify, and ultimately benefit from, the new technology. Albino, Garavelli, and Schiuma (1999) identify the crucial role of the leader firm in Italian industrial districts and the efficacy of technology transfer due to this firm’s knowledge of the various companies operating within the district. Much, however, will depend on the level of economic development of the region and the absorptive capacity of the firm to deal effectively with external sources of innovation and subsequent implementation. Absorptive capacity is discussed more fully in the following section.

The Importance of Absorptive Capacity Absorptive capacity is usually defined in terms of a company’s ability to identify, assimilate and apply new knowledge obtained from an external source and applied for commercial purposes (Cohen & Leventhal, 1989, 1990). Absorptive capacity activities are, therefore, not passive but occur as a result of entrepreneurial activity. If a firm wishes to exploit a new technology, it has to invest in appropriate absorptive capacity activities to integrate the innovation and may thus require external support to achieve these aims. Research into absorptive capacity has ranged from the investigation of innovative dynamics and the existence of absorptive capacity in firms (Cohen & Levinthal, 1989, 1990), the transfer of innovations between organisational units (Szulanski, 1996) and questions of absorptive capacity in collaborating within strategic alliances (see Luo, 1997; Mowery, Oxley, & Silverman, 1996). Cockburn and Henderson (1998) identify the importance of absorptive capacity in interacting with public sources of R&D and the degree to which such firms are able to benefit. Mangematin and Nesta (1999) show that high levels of absorptive capacity are associated with diversification of firm-level activities through which absorption may occur.

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There is an obvious link between the absorptive capacity of a firm and its ability to benefit from the work of TTIs. New technological opportunities may be missed because managers are not able to assess them in an effective manner. Consequently, this calls for an appreciation of industry and firmlevel differences on the part of TTI sponsors and hosts. It may be as important to help firms increase their absorptive capacity through networking and education as managing the diffusion of particular IP. The extent to which firms, especially SMEs, can take advantage of technological opportunities depends on the orientation and motivation of owner-managers and the current knowledge and capacities that the firm has at its disposal – in other words, construction of a critical mass of relevant technological knowledge is most important. It must always be borne in mind, however, that although access to new knowledge is often provided by TTIs without a fee being charged, it is not entirely cost-free for the target company. The assessment, implementation and integration of new knowledge can be expensive, not only in financial terms, but also in management capacities and commitment. An ability to increase absorptive capacity is also related to the firm’s strategic positioning and the effectiveness and efficiency of its interaction with providers and support agencies. The effectiveness of an innovation system and the capacity of organisations to exploit new technology also depend, to some extent, on the diffusion mechanisms utilised and the form of interaction between sponsors, IP hosts and enterprises. One mechanism to effect this diffusion, extensively discussed in the literature, is that of networking; the use of networks to diffuse new technology through TTIs is explored in the following section.

TTIS AND THE ROLE OF NETWORKS The skills of major players in innovation and technology systems, together with the importance of inter-organisational relationships at the institutional and individual level have already been identified. A significant problem facing researchers in addressing discrete parts of a complex system is that the essence of influence and information flows within and between institutions and actors has tended to be understated (Chung, 2002). Some commentators portray innovation systems as techno-economic networks, which they see as loosely co-ordinated sets of heterogeneous actors collectively participating in the development and diffusion of innovation and technology transfer. These incorporate numerous interactions and


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personal relationships. Lundvall (1992) argues that networks enabling interactions with suppliers, industrial organisations and foundations of various kinds, may provide an important source of innovation capability. Tijssen (1998, p. 792) defines a network as ‘‘an evolving mutual dependency system based on resource relationships in which their systemic character is the outcome of interactions, processes, procedures and institutionalisation.’’ Activities within such a network involve the creation, combination, exchange, transformation, absorption and exploitation of resources within a wide range of formal and informal relationships. Networks are, therefore, not limited to the heterogeneous actors – many intermediaries exist between them, giving material content to the links uniting actors, and the whole system residing in a wider societal environment (Shohet & Prevezer, 1996). Adopting this characterisation of key actors, the gestalts of each of the principal agents can be explored, taking account of individual interests and the focus and expected outcomes of each in the innovation and technology transfer system, as discussed below. Some commentators go as far as to suggest that business networks are part of a new industrial order, in which production depends on continuous collaboration with external sources of knowledge and expertise (Best, 1990). However, notwithstanding this resurgence of interest, it should be noted that active informal networking, such as bidding consortia and procurement clubs, have been employed by groups of SMEs for some time. Commentators have argued that networking is a vital process in the shaping of successful economic activities and competitive regional economies (e.g., Cooke & Morgan, 1993; Saxenian, 1994a, 1994b). Networking is seen as a way to encourage bottom-up approaches to economic development, which are geared to the mobilisation of internal resources, to the development of a region’s own strengths, etc. Marin and Mayntz (1991) and Sotarauta and Linnamaa (1998) identify important interactions between regional authorities and business firms and also between the authorities themselves in promoting technology transfer. While theoretical perspectives are useful, the variety of richness and characteristics of networks make analysis more complex. Network participants are more loosely coupled than in organisational hierarchies and their autonomy is structured but not tightly controlled. For SMEs, more flexible and informal networks seem to be the norm and in rural areas proximity engenders informal communications between small firms (Malecki & Tootle, 1996). In the context of technology transfer, different network types may be identified. First, there is the industrial district or cluster, wherein firms are interlocked in a set of operations for the production of specific products.

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These groups of organisations may engage in reciprocal commitment and trust which, in the longer term, may evolve into deep-rooted informal and implicit relationships based on unwritten rules and codes of behavior. Industrial clusters are a revival of an old idea of industry agglomeration. In their newer form, clusters represent a group of related industries that can tap into advantages of co-location in order to lower costs and improve performance. The three general types of clustering forces are: (1) advantages based on production-relationship among firms located within a common production arena, (2) advantages gained from local markets and (3) advantages to be gained from relationships with non-business institutions. Second, what may be termed a ‘‘Territorial Ecosystem of Innovation’’ – based on the idea of co-evolution within industrial ecology (see, e.g., Moore, 1993) – promotes relationships in the two complementary forms of cooperation and competition. With a stimulus of declining costs of information communication technologies and promotion by a set of institutions, universities, local and regional authorities can thereby co-evolve capability and a broad range of infrastructural innovations, taking the form of science and technology parks, technology transfer and university–industry interfaces. It should be noted that construction of a framework for interfirm cooperation is just one element of the networking process. Understanding of and learning from the environment, as key to organisational survival and growth, has been discussed. However, if there is no mechanism to diffuse this within the firm, then organisational learning and strategic management will ultimately be restricted. A combination of purely public and also public/ private partnerships is important in strengthening these principles through provision of a variety of initiatives; see, e.g., Sotarauta and Linnamaa (1998). The role of support agencies in changing business behaviour and shaping particular innovative milieus has been addressed; for instance, Dickson (1996) found that trust and reciprocity varied considerably in informal business information exchanges between the firms studied. The process of diffusion of innovation and technology transfer, therefore, suggests a systemic underpinning, enabling the examination of interactions between institutions and firms and also, fundamentally, within them. This is a crucial issue because not only policies but also the actions of people are important. Dodgson and Rothwell (1993) argue that collaboration in networks is a fundamental stimulus to technological and organisational learning. Such collaborative interaction is essentially enabled by and through people engaged perhaps in multiple roles – for example, the university researcher is both teacher and a source of new information and knowledge for industry. SME owner-managers might be members of


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formal or informal groups as well as serving on local councils and research institutions and as governors or other industrial liaison roles in universities. Rothwell (1992) makes the important observation that successful innovation, that is, the successful implementation of new ideas, is a people-centred process. In the same vein, Audretsch (1995) argues that observation should be directed towards individuals and away from firms. This infers that any discussion of innovation processes should emphasise the role of individuals, together with person-centred activities such as social interaction, leadership and power. Taking a person-centred approach allows one to move away from concentration on the physical aspects of networks, the institutions and the links, to focus more attention on the communications and interactions occurring within networks. For example, in technology transfer, it has long been recognised that formal aspects of transfer are much more easily dealt with than the tacit information accompanying technology in the form of experience and know-how. The transfer of tacit information is much more subtle than explicit information, so that innovation and technology transfer is often the result of compact interaction between a set of relationships, rather than a single event. It is, perhaps, no surprise, that models of innovation and technology transfer are recognised as both complex and evolutionary (Rothwell, 1992), but the ‘‘magic combination’’ of such factors as will lead to success has proved elusive. Successful innovation may be multi-layered (i.e., particular factors such as technical issues may be more important in one industry, as opposed to market-related factors in another) as well as being multifactored (Rothwell, 1992). TTI networks are primarily designed to meet two goals: to reduce the cost of obtaining useful information, while at the same time ensuring that it is reliable, and to provide SMEs not only with scientific and technological information, but also with services related to the various corporate functions. As a result, networks are designed primarily to operate regionally and locally, even though national or international networks sometimes play a significant role in the process, particularly where highly specialised information is concerned. Networks often defy sectoral barriers, as what attracts firms may be general aspects of regional institutions such as universities, trade associations, PR and venture capital firms, which, for various reasons, the regional enterprise is unable to provide. This decentralised system provides an environment for the diffusion of intangible technological capabilities and understandings.

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The SME in the Innovation and Technology Transfer System The competitiveness of SMEs is determined by a wide range of factors including the entrepreneurial activity of owner/managers, the possession of relevant knowledge and innovation skills and the involvement of the enterprise in dynamic networks. The SME owner-manager, whose strategic decisions are critical to its success, does not necessarily always fully comprehend what constitutes strategically important data (Drilhon & Estive, 1993), and all the more so when the strategy of the firm is dependent on the exploitation of new technologies. Knowledge of the dynamic developments in the technologies is crucial in determining the competitiveness of the SME. SME managers rarely have the knowledge resources to develop new technologies by themselves or even to assess outside developments closely. Instead, they rely on a diversity of information sources when deciding upon future technology commitments. Frequently, they will depend on business customers in the supply chain. On occasion, these may be through commercial sales, development agencies and consultants, who frequently engage in emulation of a competitors’ use of technology. At the societal level, SME managers often belong to associations whose aim is to foster developments in the business community and they may have multiple roles in the community in addition to running their own businesses. SMEs often network closely among themselves, mostly on a personal and informal basis (Drilhon & Estive, 1993). Any of these interactions, and often the combination of them, can lead to a new technology source being identified or an innovation being pursued. As technology transfer involves an ongoing learning process (Rosenberg, 1982), adoption of new technology results in the SME owner-manager having to manage change over a period of time, and not only at the point of opportunity recognition. This on-going process is not always recognised by TTIs or owner-managers. The incorporation of new technology consists of several stages including research, selection and implementation (Izushi, 2003), which may require varying levels and content of support from TTIs. Izushi (2003) also recognises the potential existence of a technology gap and a cultural gap between TTIs and SMEs, both of which must be addressed as part of the technology transfer process. SME owner-managers often lack understanding of the motives and methods used by government-sponsored institutions and they are sometimes extremely individualist in their perception of what is good for the business – what Woodward (2001, p. 3) terms ‘‘deep-seated individualism.’’ Yet it has been shown that networking can be successful in terms of both small and


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large aspects of change, although the networks involved tend to be different in nature. As networks mature, however, relationships also mature and may provide additional insights for owner-managers. The Role of Government as Technology Transfer Sponsors Governments in most developed and developing countries are conscious of the need to create and adapt new technology in order to increase national competitiveness. As well as promoting the development of innovation systems, they have attempted to implement policies promoting the commercialisation of innovation and its adoption by industry. Intended to improve competitiveness and assist industrial restructuring, support has been channelled through a range of intermediary agents, often addressing regional business development issues. While there have been several initiatives, the implementation of technology transfer policies has proved problematic for several reasons. As Cervantes (1997) suggests, the process of technological diffusion itself is complex, the rate of diffusion differing between sectors due, for example, to variation in the nature of industries, competitive rivalry and the absorptive capacity of organisations. Difficulties are experienced in assessing the effectiveness of diffusion processes, not least because diffusion can be difficult both to measure and to evaluate, and best practice is difficult to transfer to subsequent policies (Drilhon & Estive, 1993). Diffusion also requires flexibility in meeting the diverse demands of firms and, as Cervantes (1997) argues, this flexibility is something which traditional public funding has not able to incorporate easily. Drilhon and Estive (1993) suggest that technology- and innovation-based initiatives are important in developing a vibrant SME sector and this is a prime source of economic development and growth. Jones-Evans, Klofstein, Andersson, and Pandya (1999, p. 48) state that ‘‘Policy-makers at regional, national and EU levels are beginning to appreciate the need to develop the effectiveness of different forms of technology transfer to bridge the gap between academic research, technological development activities and the commercial market.’’

THE ROLES OF TTI ORGANISATIONS In examining the roles of various institutions in technology transfer processes and interagency tensions, Shohet and Prevezer (1996) suggest that

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intermediaries often act as agents between providers and recipients of technology transfers in an imperfect knowledge market. Intermediaries also provide access to assets for developing technologies outside of traditional internal R&D activities. The boundaries of the various institutions, in addition to their aims and objectives, are fundamental parts of the system. Boundaries need to be permeable to allow for effective transfer of technology, but boundary barriers can work against the stated aims and objectives of the institution or firm. Often the aims and objectives are complementary, whereas the cultures are not. Boundaries can be mitigated by the existence of intermediaries, helping to overcome cultural differences or shortcomings in market knowledge and transaction expertise. Intermediaries are not alike and reflect differences in their accountability and mission.

Public-Supported Institutions Public-supported institutions have had mixed results in promoting innovation and technology diffusion. Difficulties occur in identifying and persuading SMEs to become involved in innovation projects. Researchers usually identify factors such as cultural differences adversely affecting links with public sector bodies and the generally individualistic nature of owner-managers. Ring and van de Ven (1994) suggest that firms are suspicious of public bodies. Drilhon and Estive (1993) also note a natural suspicion on the part of SMEs regarding government action. They advise that governments should make a systematic effort to design and implement programmes specifically tailored to SMEs’ needs, citing examples of ‘‘technology counsellors’’ in France who identify the SMEs in a particular region that are in need of new technology. Having identified this particular need, the counsellors subsequently connect firms with the agencies involved in the transfer (universities, consultancy firms, laboratories, technical centres). They help the enterprise to make the necessary administration formalities (particularly the funding arrangements, given the complexity of the aid system), and they monitor and follow-up the transfer (by organising the project and by checking that it proceeds smoothly). The value of such a facilitating relationship is confirmed in Gonnard’s study, where the French firms took time to consolidate links with the public research bodies, but as trust grew so did interaction. (Gonard, 1999). In his study of New Zealand institutional/industrial links, Perry (1996) identified one of the roles of intermediaries as promoters of networking among small businesses, where few or no networks existed. The fostering


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and promotion of networks is an important example of intermediary activity that would increase the effectiveness of new knowledge transfer by TTIs.

Universities and R&D Institutions as IP Hosts Debackere and Veugelers (2005) claim that a central issue within knowledge distribution aspects of innovation is the link between industry and the university. Etzkowitz and Leydesdorff support this view through their work on what has become known as the ‘‘triple helix’’ model, emphasising the interaction between government, industry and academia – see, e.g., Etzkowitz and Leydesdorff (2000). In most societies, research institutions and commercial firms have profoundly different missions (Siegel et al., 2003). While the central goal of universities and research institutes is to create and disseminate knowledge, the principal mandate of firms is to maximise the wealth of shareholders. The degree of cultural distance between academia and industry is rooted in the historical foundations of the educational system unique to each country. A greater commercial orientation in a nation’s research institutions translates into a smaller cultural distance between them and links between research institutions and industry are substantially improved (Bartholomew, 1997). University–industry interaction continues to receive considerable attention in the literature though the focus of research differs widely. For instance, Cervantes (1997), Shohet and Prevezer (1996) and Bird, Hayward, and Allen (1993) discuss the impact of reduced public research funding for universities and the resultant increase in motivation to commercialise innovation. Cyert and Goodman (1997) assess technology transfer cultures in university–industry links, and Sargent, Sadler-Smith, and Dawson (1997) argue that universities should market their services to industry more effectively, a view supported by Siegel et al. (2003), who argue for more understanding between academics and industrialists. Both Turpin, Garrett-Jones, and Rankin (1996) and Bonaccorsi and Piccaluga (1994) outline a typology of university–industry links, the latter emphasising a diversity of organisational formats and interactions. A common theme is emphasis on the university as a significant institution (or combination of institutions) within the innovation and technology transfer systems. The place of universities in innovation diffusion and technology transfer is complex and uneven. They act as IP hosts in commercialising research, but also have a role in raising the absorptive capacity of firms through education and skills development. MacLeod, McFarlane, and David (1997)

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identify an interesting historical paradox: that it was industry, together with other institutions which originally combined their efforts in England to create the ‘‘red-brick’’ universities of the early 20th century for the benefit of the communities involved. Today, much emphasis is on how to bring the knowledge and expertise of the university back into the community, especially to benefit the creation and growth of technology-based businesses. While some universities have close working relationships with business, others have yet to make a significant impact. There is, therefore, a tenable argument that universities should pay more attention to strategic identification of needs in the business community and to the design of services to meet those needs. Universities could perhaps respond by encouraging hybrid R&D activities between departments more akin to the process of product development in industry. Sargent et al. (1997) suggest that universities might also work together to provide technology transfer and other services to a wider region than that served by one university. But conflict often still exists between the desirability of commercial work and academic research career development (Siegel et al., 2003). Bird et al. (1993) note that, within universities, there remains a lack of definition of the role of the academic and a lack of appreciation of tensions in values and loyalties, of rewards and recognition, and awareness that national measures of academic output might not always encourage innovation. Debackere and Veugelers (2005) argue that, in the EU at least, there are significant obstacles to the transfer of IP, not the least of which is a lack of demand from enterprises. The writers see industry–university links as performing several functions: support of technology-based start-up enterprises based on research-led innovation, collaborative research with industry, contract research and various forms of specialist education and training. These activities are based on formal and informal relationships and networking, human capital flows and personal relationships, all of which intensify over time. Developments are prompted by increasing pressure on universities, because of changes in policy-making, to commercialise their research work and to generate an increasing level of income from their research and professional activities.

MNEs as Technology Transfer Intermediaries Multi-national corporations diffuse new knowledge between headquarters and subsidiaries and/or between subsidiaries, depending on specific organisational structures. This is particularly evident when the MNE affiliates


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operate within clusters. Technological diffusion is also evident in the relationships between the MNE and its suppliers and customers and between MNEs and other companies if these are located in clusters or business parks. Ivarsson’s (2002) study of MNE affiliates operating in West Sweden generated technological competences, not only within the corporation but also association with external business partners, including suppliers and customers, through organised networks that extended well beyond the local area. Ivarsson (2002) also makes the important point that technological links between MNEs and other local firms do not happen automatically but require long-term motivation, commitment and investment in personal and other resources. Technology transfer may also be made between the subsidiary and headquarters, with technology diffusion occurring in the homebase country.

The Gestalt of Publicly Funded TTIs TTIs are sponsored by public funding and operate without direct parenting by universities and R&D institutions. The sponsoring stakeholders, who are often local authorities and public agencies charged with regional economic development responsibilities, have sought to harness the TTI in fostering economic growth in their areas. Variety characterises the forms that these TTI organisations have adopted, and three variants, which show distinct differences of focus, are summarised below: (i) The TTI as business incubator. (ii) The TTI as IP broker and transfer facilitator. (iii) The TTI as catalyst of an innovation culture and enhanced technology transfer capacity. The Lanarkshire Business Incubation Centre in the west of Scotland is one example of a business incubator. Located within a region undergoing industrial reconstruction, the Centre aims to increase the generation of knowledge-based business start-ups. The Centre provides selected entrepreneurs with offices and office services, intensive business development, product development, marketing and technical support; and also provides introductions to seed capital and investment funding. The Centre seeks no stake in the assisted new business it is hoped will spin-out and locate locally (Monklands Enterprise Development Company Ltd., 1999). An example of an IP broker and transfer facilitator, Forthright Innovation is located in the Stirling University Innovation Park and targets existing

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(as well as new) technology-based businesses located in the Forth Valley region. Its mission is to promote technological competitiveness and facilitate access for businesses to necessary technology resources. As the Innovation Relay Centre for the area, the Centre’s reach for technology partners is European-wide. Although Forthright Innovation is situated in a science park, the Centre has no binding commitment to give preference to the IP interface between the local university and its business clients. As a free agent, Forthright serves the needs of its business clients (Forthright Innovation, 1999). The Regional Innovation Strategy (RIS) is a partnership serving the west of Scotland and is sponsored by the public authorities and local enterprise agencies in that region. RIS have, as their vision, the establishment of western Scotland as one of the most innovative region in Europe. The role of RIS is to orchestrate local partners – public and private, to achieve this. As a catalyst, they aim to improve the overall environment for innovation through the dual routes of increasing the number of innovative companies and improving the capacity of the education sector to support innovation. The main features of the RIS role are projects to promote the interfaces between businesses and technology/knowledge supplier, and dissemination and awareness creation (Strathclyde European Partnership, 1999). A common objective of these public-funded TTIs is the adoption and enhancement of IP and technologies by industry in the sponsors’ territorial areas.

The Gestalt of Universities and R&D Institutions as TTIs In addressing the commercial engagement with industry, universities have adopted a number of ‘‘supply side’’ measures, including setting up clientservice facilities in the form of industrial liaison offices (ILOs), etc., and participating in property-based ventures such as incubator centres and science parks. Universities in many countries have set up centres through which university-led IP can be diffused or spun-out, mostly for profit. Industrial liaison offices. Many universities have chosen to establish their ILOs to serve as intermediaries for technology transfers to business. ILOs provide liaison services between industry and academics, signposting market opportunities for academic expertise and promoting available university services and assets. The success of ILOs is debatable, not only because they may lack resources to make effective market surveys, but also because they may be


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perceived as an obstacle and ineffective by academic departments that have direct links within industry (Schaettgen & Werp, 1996). The defenders of the ILO argue that the effective marketing of knowledge is sophisticated and specialised, but it is noticeable that ILOs frequently specialise in contractual aspects of managing technology transfer, such as patenting and licensing, for instance. This is appropriate because the ILO has to serve the interests of the host university or R&D institution, when managing university links with industry, local and/or national government institutions and other research centres. Clearly, the primary purposes of the ILO are therefore to safeguard the intellectual research property assets of the university and to seek to obtain a financial return from the marketing of the IP (Schaettgen & Werp, 1996). Markman, Phan, Balkin, and Gianiodis (2005) found that ILOs having a ‘‘for-profit’’ orientation had a positive effect on new business start-up. Science parks, incubators and SME clustering. Factors affecting the location and grouping or clustering of small businesses have received attention from a number of research perspectives. Researchers have attempted to explain regional or local clustering of businesses in terms of regional differences in labour supply, regional development, infrastructure and the availability of government incentives, among others. Regional clusters of firms also seem to be important in the growth of innovation, as significantly more innovation occurs in these clusters than in large organisations (Audretsch, 1998). Wever and Stam (1999) portray the geographical concentration of business in clusters, and so forth, as a learning region and claim that the development and maintenance of networks is crucial to effective technology diffusion. The spectacular success of the ‘‘Cambridge phenomenon’’ in England is recognised by universities and property developers alike, but no two science parks are the same and generalisation about the effectiveness of provision for facilitating technology transfer may be dangerous. Even where universities are at the centre of such parks, relationships with on-site firms vary from strong links to little or no collaboration. Clearly, the cultural outlook of the academics is relevant here and physical proximity alone is no guarantee of interaction and technology transfer. Clustering by industry and/or the close proximity of firms from various sectors in science or business parks facilitates the technology transfer process. At the systems level, clustering assists in the diffusion of innovation and technology transfer through close proximity with other firms. This helps to foster networks and increased interpersonal interaction within the park environment. Universities have engaged in the operation of incubator centres

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(Drilhon & Estive, 1993), which can provide the universities with facilities to accommodate science/technology-based new business spin-outs. In ‘‘incubator’’ accommodation, close support can more easily be provided to such enterprises. Science parks situated adjacent to universities provide an important resource network for technology-based firms (Westhead, 1997). The advantages of being on or near a university campus are numerous and include state-of-the-art technical thinking and equipment, access to library facilities and undergraduates as well as a technically skilled labour force and a creative environment. Universities can offer research and consultancy talent as well as being a source of knowledge. Central services for technology and innovation incubators accelerate the development of entrepreneurial talent in high-technology issues. The aim of facilitating interaction underlies the science park/incubator concepts. Science parks can act as catalysts and incubators for new businesses (Westhead, 1997). In a science park environment, it is the opportunity for networking and knowledge exchange that exploits this locational proximity. The intensity of interactions may be heightened because of clustering and interaction between relatively dynamic companies. However, the dayto-day exchange of much networking is routine and operational, and rarely about strategic issues. Stevens (1997) points to the lack of interaction between the R&D institutions and SMEs, as even if situated locally, the SME networks are difficult for non-SMEs to join as the latter lack familiarity with the normal business of SME interchange. The different perspectives of key stakeholders are important factors in understanding the systemic links between the operation of ILOs and the successful diffusion of new technology. Siegel et al. (2003) identify key actions and motives of academics, ILOs and SMEs. The academic pursues new knowledge driven by motives of recognition and the ability to secure grant income. The ILO works as a go-between to structure deals and protect and market the academic’s IP, though often in a bureaucratic way. The firm commercialises new technology, primarily for financial gain in a more results-oriented context. These differences frequently give rise to cultural clashes, which may act as barriers to effective diffusion.

The Gestalt of Privately Funded TTIs Much technology transfer flows between businesses without the mediation of public-funded intermediaries. Increasingly, however, private sector sponsors,


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like their public sector counterparts, are keen to direct and accelerate the diffusion process. Traditionally, venture capital companies have tended to assess start-ups from a risk investment perspective. A number of venture capital organisations have recently expanded their activities to act as intermediaries, assisting with the technical and management support required to deliver the knowledge-based start-up. Venture capitalists tend to create new network pathways, whereas technology transfer often follows existing ones (Harmon et al., 1997). For example, in the early years of the present decade, CMGI Inc, a U.S.based company, targeted Internet start-ups. As an investment incubator group, through providing intense support, they aimed to increase the success rate of start-ups. CMGI operated a network enabling it to connect companies to each other to share technology, management insights and carry out cross-marketing – to gain ‘‘cross-hybrid technical capabilities.’’ The TTI motive was profit driven; the group secured an equity stake to be sold on when growth was capitalised at the time of company listing (The Sun, Malaysia, 2000).

COMPARING THE ITT PATTERNS OF TECHNOLOGY TRANSFER RELATIONSHIPS Outlines of the various types of intermediary have been provided in relation to their focus, dependencies and roles. This basis of description affords comparison in terms of the conditions that TTIs impose upon their relationships with other players in the innovation and technology transfer system and, in particular, upon business users of IP. As pattern variables, the following conditions of TTIs exchange appear to be most relevant:

the the the the the

source of the IP direction of the flow of the IP use of networks nature of IP contract and sponsor’s stake and expected return.

Table 1 highlights the defining characteristics of the TTIs in terms of these variables. The defining differences between the intermediaries occur in respect of the access mediated by them, to enable the IP user to gain access to technology

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Table 1. Conditions of Technology Transfer/Type of Intermediary Source of IP

Direction and flow of IP Network use Contractual/noncontractual Sponsor’s stake/ return

Types of Intermediary and Conditions of Technology Transfer.

ILOs

Business Incubators

IP Brokers and Transfer Facilitators

Catalyst of Innovation Culture/ Capacity

Venture Capital Incubator

One source – the university or R&D institution One-way – into SME Local

Multiple sources into TTI

Multiple sources into TTI

Multiple sources – across region

One-way – into SME Local intensive

Two-way – between SMEs Extensive–intensive

Contractual

Contractual

One-way – into SME Local and through relay partners Non-contractual

Informal

Multiple sources within corporate growth Two-way – within corporate growth Intensive – within corporate growth Contractual

License financial return

Equity financial return or regional gain (indirect)

Voluntary regional gain (indirect)

Voluntary regional gain (indirect)

Equity financial return

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Source: Kirk and Pollard (2002).


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and business networks. The richer networks, providing two-way access and wider partnering opportunities, are features accommodated by the brokers/ facilitators like Forthright, by catalysts like RIS, and, within the corporate group, by venture capital incubators. The university/R&D institution-based model of the industrial liaison office is least effective from this perspective. The ILO provides a constrained access to IP and their expertise in the contractual management of the transfer may prematurely risk first facilitating relationship building through sharing of tacit knowledge, leading to innovation and later to the formalised transfer of IP. In part, this is a matter of the operating style of the ILO and any shortcoming in affording network entry may be compensated for when the ILO engages actively in the networking activities of a catalyst like RIS and, in turn, facilitates access to the wider networks. However, this requires the ILO to recognise the value for the client service user in gaining access to the rich sources of IP that may lie beyond the services directly managed by the ILO. This spirit of open participation in the wider flows of interaction, information and value exchange, which provides a foundation innovation, is ultimately dependent, not upon the rhetoric of institutions, but also upon the outlook and behaviour of individuals operating as intermediary agents.

SOME APPROACHES TO INNOVATION AND THE OPERATION OF TTIS Europe The EU (at the time of writing, the EU member states were Austria, Belgium, Cyprus, the Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, the Netherlands, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden and the UK). TTIs have been identified by the EU as helpful in promoting the transfer of knowledge-based technologies into use in businesses, in particular into SMEs. The EU has supported the operation of Innovation Relay Centres to provide a network of interacting technology diffusion intermediaries throughout Europe. This has been backed by the EU’s active support for the development of innovation tools, information and communications networks and training packages to improve the skills and resources available to executives operating TTIs. At this supra-national level of innovation

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system, there is significant interaction between EU, national, regional and local technology transfer policies, including the enhancement of individual and organisational learning processes through regional innovation systems (Gerstlberger, 2004). In summary, it may be observed that EU and Government policy has supported demand side measures to stimulate innovation awareness and capacity within SMEs, including developing and supporting the professional capabilities of ITTs to link SMEs to R&D institutions. It is necessary to recognise that the sponsorship of technology transfer is not limited to public policy initiatives. ‘‘Big business’’ companies with an eye to the competitive advantage of new technology may seek to maintain and support links with R&D institutions, and may also sponsor SME incubators. Moreover, public–private partnership in R&D projects and its diffusion, particularly at pre-commercial stages of technology development, is evident at both EU and national levels. The motives for public and private sponsorship of technology transfer differ, but the public sponsor has found it possible to align with the private corporate. Belgium According to Debackere and Veugelers (2005, p. 330), ‘‘The federal– regional political system in Belgium introduces a high level of complexity that impedes the development of a consistent policy promoting industryscience links.’’ Despite this complexity, technology transfer programs do exist, albeit on a small-scale. Within these constraints, Debackere and Veugelers (2005) claim that there is an effective link between research institutes and university–industry networks are highly productive, compared to other EU countries.

The United Kingdom As well as operating within a wider EU framework, various schemes, both national and regional, exist to promote the transfer of new technology and its uptake and application in SMEs. Some Scottish initiatives have been outlined earlier by way of examples, these developments having involved a mixture of UK and EU sponsorship although the main drivers have been local authorities and institutions. In the case of England, Major and Cordey-Hayes (2000) suggest that getting SMEs interested in innovation matters can be difficult. Despite both


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local and national emphasis within an innovation development programme, they suggested that the efficacy of such programmes can be marred by a lack of understanding between sponsors and small firms. The role of intermediaries such as innovation and technology centres, chambers of commerce, universities and trade associations are seen as crucial in effecting technology diffusion. However, in dealing with SMEs, they should take notice of the disparity of orientations between individual firms.

Transformation Economies in Central and Eastern Europe As the economic transformation process evolves in central and eastern Europe, many governments are giving more attention to technology transfer, not only viewing firms in their socialist tradition, but actively supporting small business development as a way of sustaining the transformation to a market economy and of competing with foreign investment in their own countries. Many countries have had to add to their stock of technological knowledge and develop social capital owing to the fact that, under the old system, innovation was much more centralised and was mostly directed at heavy industry. While many countries possess a well-educated workforce, their technology may be less than modern and skills associated with market economies such as strategic management and marketing had not been well developed (Witt, 1998). Now there is a greater convergence with western models. Not all countries in the region are progressing through economic transformation at the same rate and much depends on the starting-point of the transformation process and the political situation in individual countries. This view is supported by Tihanyi and Roath (2002), who note that there are different groups of countries in CEE, for example, those more advanced in market development terms and recent members of the EU, compared with countries where little has changed during the transformation process and there are still significant levels of government intervention in industry. Accession to the EU by countries such as Poland and Hungary has had a significant effect on innovation system development. Palmai (2004) discusses the setting up and operation of an innovation park (INNOTECH) in Hungary adjacent to the Budapest University of Technology and Economics. This has the major function of providing an incubator for university professors’, but it also enhances the development of other firms resident in the area.

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In the Czech Republic, Lloyd-Reason, Muller, and Wall (2002) noted the setting up of industrial zones, initially located near the largest export markets, Austria and Germany, but the country suffered from a lack of local qualified labour. These districts were managed by local authorities, but with a 60% stake on the part of central government. Lloyd-Reason et al. (2002) claim that there were a comparatively large number of start-ups in these districts compared with the national average. Networking for new start-ups has been encouraged by a mixture of state and EU funding and with policies to support interfirm collaboration. However, there is the residual problem of a high tax on employment and other forms of taxation. The issue of network development was addressed by Dyker et al. (2003), who suggest that SMEs in both Slovenia and Hungary were dependent on networks, as sources of information, learning and innovation. In the case of Slovenia, the small size of the domestic market meant that many SMEs sought networks to enable them to engage in exporting and other international market activities. Muent (1999) suggests that firms used networks to overcome local disadvantages caused by transformation; such networks having been established between the firms themselves and also between them and universities. In general terms, institutional and network development are key issues in the development of innovation systems (Tihanyi & Roath, 2002) and key TTIs are not yet effective. Government-sponsored initiatives, where they exist, tend to be in the form of intentions, rather than as reality. Glas, Hisrich, Vahcic, and Antoncic (1999) suggest that, in the case of Slovenia, officials’ implementation of government-sponsored initiatives directed at the support of technological upgrading of small businesses is generally poor. Despite this potentially pessimistic view, there are examples of localised success. Woodward (2001) reports on networks between the Technical University of Lodz, Poland, and local business incubator and science park developments. Business incubators have been developed in association with the Technical University of Kouness, Lithuania and, as discussed above, Palmai (2004) reports on an incubator and science park development associated with a Hungarian university. In building national or regional/local TTI systems, government agencies face significant barriers in ensuring the effectiveness of these systems. One barrier has already been mentioned, that of the failure of local officials to implement policies effectively. This may be due to a negative perspective of entrepreneurial firms or perhaps political reasons. Another significant barrier is a commonly held negative attitude of SME owner-managers towards government and quasi-government agencies whom they treat with some


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suspicion, a legacy of the previous political system. Finally, and related to the first two barriers, is the existence of a significant informal economy that has little regard for government-sponsored initiatives and formal networks.

Asia TTIs in the Association of South-East Asian Nations (ASEAN) (The current member states of ASEAN are Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, Singapore, Thailand and Vietnam.) In contrast with EU innovation systems, ASEAN technology transfer is much more fragmented. Various elements of the TTI system exist and the stakeholders are similar to those found in Europe. What is missing is the implementation of regional policy and many of the necessary networks. Recent meetings of ASEAN members have developed wider-reaching plans for technological development, but a supporting institutional network is still in the early stages of development. Other issues include a lack of coherent education policies – vital if the skill levels of member countries are to be raised – and the differing levels of economic development and industrial infrastructures of member nations. ASEAN countries, Singapore in particular, have for some years taken the lead in high-technology industry development and, although the range of industries is comparatively narrow (Liu & Yang, 2003), this has had the advantage of developing specialisation. There is also evidence of crossborder technology transfer between organisations in Singapore and those in Malaysia (Konstadakopulos, 2002). Japan Eto (2005) suggests that, while there have been several governmentsponsored initiatives to promote innovation, these programs have not met with general success. He cites the development of new business parks and their failure to attract significant levels of new business, despite the efforts of local authorities and other TTIs. A wide cultural gap exists between business and institutions and this factor does not appear to be taken into account when developing innovation systems (Izushi, 2003). Eto (2005) further claims that the universities exacerbate cultural differences because they do not promote innovation effectively. Set against this is the development of ILOs in many Japanese universities and several incubator programmes linked to university campuses. But the cultural gap does indeed seem to be a significant barrier in the

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effective diffusion of new technology in this particular setting. Eto (2005) suggests the fostering of networking as a shorter-term strategy and, in the longer term, targeting particular industries for development, rather than attempting broader strategies.

China For many years, China pursued programmes of technological innovation with the intention of overcoming embargoes on technology transfer from the west, caused by the Cold War, and later from the USSR. Since the beginning of the reform period, several programmes have been introduced by the Chinese government to promote innovation. The High Technology Research and Development (863) Programme and the Torch Programme (Liu & Yang, 2003), to move from the imitation of western technology to higher levels of domestic innovation, are examples of such programmes. Other technology-related projects are funded by the National Natural Science Foundation and similar bodies. What can be discerned in China is an early stage of national innovation system development. Innovation systems are also evolving at regional and local levels, but these latter very much depend on the orientation and entrepreneurial outlook of local authorities. In Harbin, for example, the local authorities have provided business parks to encourage inward investment to help mitigate the effects of a declining state-owned sector. In the Yangtze River Delta and the pan-Pearl River Delta areas, local authorities have had a considerable influence on industrial agglomeration. Chinese universities are beginning to consider the best method of commercialising research, but the incidence of ILOs is still small compared to the West. While Chinese development of TTI systems may be comparatively rudimentary, at the time of writing several actors and agencies in China are taking an active interest in technology transfer mechanisms, particularly as a result of university research and increasing business know-how. Liu and Jiang (2001) suggest that, while university–industry links are relatively under-researched in China and that these systems are still under-developed, there are current examples of successful collaboration, citing developments at Tsinghua University. Tsinghua is building networks with other universities, collaborating with local governments and setting up university– industry mechanisms with representatives drawn from MNEs such as Motorola and NEC (Liu & Jiang, 2001). The innovation system is heavily affected by a combination of government policy and the Chinese economic system (Liu & Jiang, 2001), but the


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emphasis is on using technology developed in universities to promote social and economic progress. Whereas business parks and science parks have existed in China since the 1980s, they have concentrated on the attraction of relatively unrelated foreign firms, rather than the development of technology clusters. University Science Parks belie their name, often being merely university departments, which are science related. A significant barrier to innovation and technology transfer system development is the lack of an effective venture capital system, within which external investment could assist SMEs to adopt significant levels of new technology.

DISCUSSION In each of the countries discussed above, government policies relating to technology transfer have been implemented or are still being developed. It is readily seen that there is a good deal of similarity between countries in respect of need for the diffusion of new technology, in order to provide economic development opportunities. Additionally, both regional and national governments are recognising the importance of technological development. Both national and regional innovation systems can be discerned but, in China and other transformation economies, various types of industry– university links are forming an important first stage of innovation system development and these may constitute a part of a wider regional system, as economies develop. It is possible that localised and regional systems will coalesce in due course, to form the basis of a wider innovation system, but this will depend to a great extent on government policies. The setting up of business parks, industrial areas and business incubators is evident, albeit in different configurations, but with significant local government support. Educational institutions have a function, not only as IP hosts but also in skills upgrading (Siegel et al., 2003). This multi-faceted role is important, not only in effective technology transfer, but also in increasing the absorption capacity of firms. Challenges facing TTIs in effecting their strategies also display similarity, especially with the problem of engaging SME owner-managers in the TTI process and of ways of overcoming cultural differences between the organisations concerned. Metcalfe (1997) makes the important point that firms, universities and public research bodies are distinctly different kinds of institution and have specific different purposes. Intermediaries are very diverse

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and it is for this reason that a holistic perspective is important in explaining both interactions and conflicts within technology transfer. The attitudes and abilities of SME owner-managers are key to the effective operation of TTI systems and the influence and information flows within and between institutions by individual actors have tended to be understated. Given that entrepreneurs generally display highly individual characteristics and considering the cultural gap between the public and private sectors, finding common approaches will be difficult. Izushi (2003) argues that this cultural gap between institutions and SMEs is a key inhibitor to the technology transfer process. He also suggests that the smaller the information gap, the easier the transfer and the lower the associated costs. There is therefore a need to market TTIs effectively and for TTIs to appreciate differences between them and their clients. Financial support through venture capital and other mechanisms is not enough to transfer new technology effectively. Some means of effecting communication might be the fostering of networks over time; as the longer the relationship exists, the more easy it is to overcome barriers. Overcoming suspicion in transformation economies and in China is going to be a longterm task for governments and TTIs. The costs of absorbing new technology are not inconsiderable, especially when factors such as management time and disruption are taken into account. The larger the technology gap, the more expensive the process becomes. Part of the TTI process, therefore, may be to raise skill and competence levels and one facet of university involvement in such systems may be helping firms to prepare for technological updating. University– incubator links make such technology transfer easier, because of proximity and evolving personal relationships within the network. The embryonic state of the venture capital system in east and central Europe and the earlier stage of development in China places greater financial constraints on technology transfer, compared to the west, where venture capitalism is highly developed. Studies into the financing of SME development are underway in many of these countries but, again, it is a medium- to long-term area of development. The differentiation of types of intermediary made in this article has been drawn at the institutional level. In large measure, the analysis has defined the mission boundaries conditioning IP relationships and interactions. Analysis of innovation systems and TTI operations suggests that innovation may be multi-layered as well as being a multi-factored process. Taking a systemic approach in this chapter has highlighted the importance of assessing both existing and potential networks connecting the major


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players and individuals in TTIs. As Balzat and Hanusch (2004) argue, the systemic approach can be applied effectively to deal with the non-linear and multi-disciplinary nature of innovation processes, interaction at the organisational level and associations between organisations and institutions. The process of information and knowledge flows, particularly in the case of tacit knowledge, is an important feature of innovation and TTI systems. The importance of networks to support the work of TTIs has been examined in detail. While there are interesting arguments in the literature, relating to the necessity for and the efficacy and use of networks, especially those involving SME owner-managers, it seems that TTIs face complex problems in executing their role in the technology transfer process. There is an obvious necessity to understand the potential recipients and their needs as well as the manner in which firms should be approached and assisted with the introduction of new technology. Saxenian’s (1994) work on Silicon Valley restates arguments about the importance of local networking and organic growth of this high-technology cluster. Generalising on this, SME networks operate locally and regionally, and often networks defy sectorial barriers. Some knowledge, particularly tacit knowledge, can only be effectively transmitted between people and distance seems to be an inhibitor. On the other hand, some commentators indicate the development of networks outside their original areas and argue for virtual clusters, utilising advances in ICT technologies. Innovation diffusion and technology transfer into SMEs, as facilitated by local intermediaries acting as catalysts or go-betweens purely in the domestic system, is becoming an increasingly untenable position, not only because of globalisation of firms, products and markets, but in international R&D alliances, engagement with international research such as those sponsored by the EU and so on. Although a strong case has been made for investigating innovation systems at various levels, this approach may suffer from complications, such as the existence of local, national and international networks. The potential for virtual networks utilising recent developments in ICT systems brings with it increasing complexity as well as new options in the transfer of technology (see the work of Romano, Passiente, & Elia, 2001, for a discussion of virtual clusters). It may be that there is no one best way to evolve a universal approach to investigation of innovation systems, but the use of a geographical or a sectoral approach in the investigation should be determined by the individual research rationale. Institutional perspectives highlight two ways in which national institutional context shapes country patterns of innovation. First, they

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differ cross-nationally. To some extent, the policies and practices of a nation’s university and government research institutes are shaped by historical development. Owing to the fact that firms in technology-driven industries often draw on universities and research institutes for knowledge and human capital, the technological performance of a country’s firms is influenced by the features of those institutions (Nelson, 1993). Second, national context influences the institutional arrangements and behaviour patterns for the firms themselves. For example, the organisation of work and the patterns of communication within and between firms, or between firms and universities, reflects broader societal characteristics that have been imprinted on firms and institutionalised over time (Powell & DiMaggio, 1991; Di Maggio & Powell, 1983). Systems of technology transfer may also result in isomorphic behaviour in clusters, business parks and other groups of SMEs.

CONCLUDING REMARKS In this chapter, the systemic characteristics of TTIs and their function in the IP transfer process in various countries have been examined. The role of governments and MNEs as sponsor, universities and R&D institutions as hosts and TTIs and business, in particular SMEs, as IP users have been assessed, as have the interactions between these. The role of organisational and personal networks cannot be divorced from a systemic analysis, nor can the human relationships concerned. Thus, a systemic approach can be effective, as it links network interactions of organisations and individuals in the transfer and diffusion of new technology. TTIs work within interacting innovation systems; for example, EU initiatives inform national systems, which in turn have an impact on regional and local systems and the individual firm. It is because of this complex interaction of government, institutions, organisations and firms that TTIs operate in a complex environment. Another factor that TTIs must consider is the capability of the firm to assess, integrate and implement new technology – in other words the firm’s absorptive capacity. Many commentators argue that an international approach to innovation diffusion and technology transfer is needed, due to the increasing internationalisation of industry and technology, the existence of strategic alliances and the engagement of firms and universities with internationally sponsored research. Bartholomew (1997) and others have rightly identified international systems as increasingly important diffusion mechanisms in biotechnology and, by inference, in other sectors of the economy. It has been


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shown, however, that national, regional and local differences do exist and, for some countries, national and sub-national innovation systems are still evolving. Home-based intermediaries acting as catalysts or go-betweens in the domestic system are still important, but they increasingly function in a context of supra-national technological activity and networks – the EU, for instance. Although a strong case has been made for investigating innovation systems at various levels, this approach suffers from disadvantages such as the existence of local, national and international networks. The potential for virtual networks utilising recent developments in ICT systems brings with it increasing complexity as well as new options in the transfer of technology. It may be that there is no one best way to evolve a universal approach to investigation of innovation systems but that the use of a geographical or a sectoral approach should be determined by the individual research rationale. TTIs form a vital part of innovation systems. As such, their role in the transfer of IP is an important factor in the development of relevant policies and practices. However, such policies should be developed not only in the context of perceived needs for technological development, but also taking account of the cultural and developmental diversity of potential recipients. It has been shown that differing levels of absorptive capacity will affect the ability of firms, particularly SMEs, to take advantage of new technological opportunities and therefore contribute to the maintenance and development of national and local economies. Training and the fostering and development of networks are important features, which should be taken into account by policy makers. There is a need to market their activities to SMEs to avoid barriers created through suspicion and potential irrelevance of the technology concerned.

SUGGESTIONS FOR FURTHER RESEARCH Several studies exist on the development of TTIs, for example, university– industry links. However, there are several associated research streams that remain relatively underdeveloped, and which would help to consolidate and to expand our knowledge of TTI systems. For example, longitudinal studies of network development may provide more insight into network complexity than current snapshot views, for instance, the development of trust and personal relationships between actors and their effect on technology transfer. Studies of repetitive technology transfer may also provide insights into the increase of absorption capacity and the effectiveness of technology

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transfer. More research attention through the medium of empirical investigations into the means by which TTIs assess both the current and future technological needs of small businesses and TTIs and their target companies which deal with cultural barriers would be valuable. It is in the international arena, however, that perhaps the most complex but exciting research streams exist. The development of technology in China, for example, and the transfer of new technology within the country and outside as Chinese firms internationalise, will provide a wealth of research opportunities. The development of TTI systems within China (at present in its infancy) and the impact on institutions such as universities will be an interesting feature of the next 5 years. In-depth comparative studies of TTI institutional development, networks and operations in various countries and within economic blocs should also provide valuable insights.

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COLLABORATION, PROXIMITY, AND INNOVATION Sam Boutilier and Rod B. McNaughton ABSTRACT Collaboration as a means to enabling and nourishing innovation is an important theme in the extant literature, which posits that face-to-face interactions lubricate the knowledge flow between actors, and that clusters of complementary knowledge assets provide the necessary infrastructure for this process. What happens to firms that are located outside of urban agglomerations or in peripheral regions? Are they less innovative, or can information and communication technologies (ICT) serve as a proxy for face-to-face collaboration? Theory is polarized in terms of the role that ICT may play in collaborative transactions. For example, network theory explains that weak ties are important in terms of refreshing a firm’s innovation capacity by forcing it to include ideas from the periphery. Others argue that ICT cannot supplant face-to-face interaction since it is not an efficient medium for transferring tacit knowledge. This chapter uses data from the Statistics Canada 2003 Survey of Innovation to investigate empirically the relationship between firm location, innovativeness, and the extent of local and more distant collaboration.


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INTRODUCTION Collaboration, as a means to enable and nourish innovation, is increasingly an important strategy. Firms interact closely with customers, suppliers, research laboratories and universities, and even competitors to access new technologies, piece together solutions, and co-develop new products and services. Classic theories of economic geography suggest that proximity facilitates collaboration. Proximity reduces the costs of finding partners, increases familiarity with business practices and culture, favors frequent face-to-face interaction, and contributes to building trust. Clusters of firms in close proximity also benefit from knowledge spillover effects that may enhance innovativeness. What happens to firms that are located outside of clusters and are located some distance from potential partners? Do they collaborate less, and consequently are less innovative? Theories of economic geography assume the costs of communication and transportation increase with distance. However, modern information and communication technologies (ICT) alter the relationship between distance and cost, and make substantial and frequent interaction almost costless, regardless of the distance between parties. Extant literature is polarized in terms of the role that ICT may play in collaborative transactions. For example, network theory explains that weak ties are important in terms of refreshing a firm’s innovation capacity by forcing it to include ideas from the periphery. Others argue that ICT cannot supplant face-to-face interaction since it is not an efficient process for transferring tacit knowledge. This chapter contributes to understanding of this issue by providing data on the collaborative arrangements of Canadian firms in the ICT sectors. The Survey of Innovation 2003 administered by Statistics Canada provides information on the location, collaborative alliances, alliance motives, and innovation outcomes for a sample of more than 2,600 firms. This research sheds light on the importance of proximity in the modern context of nearly costless communication. It also clarifies the relationships between the incidence of collaboration and innovative outcomes. This is particularly important for understanding how firms located outside of clusters build collaborations at a distance to overcome limitations in local knowledge. The findings have important implications for the approach firms take to developing their innovation systems, and for agencies charged with promoting local innovation and economic development.

Collaboration, Proximity, and Innovation

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THEORIES OF COLLABORATION AND PROXIMITY Firms may follow different paths to achieve the goal of innovating for growth and prosperity. Collaboration is an increasingly important innovation path as firms struggle with resource and risk allocation for research and development strategies (Allen, 1983; Audretsch & Stephan, 1996; Hansen, Chesbrough, Nohria, & Sull, 2000). By sharing in the risks as well as rewards leading to an innovation, firms are able to make use of their own capabilities as well as complementary capabilities that may be provided by various partners including customers, suppliers, universities, and other firms (Bayona, Garcia-Marco, & Huerta, 2001; Tether, 2002). One of the reasons for establishing these collaborations is the depth of knowledge they encapsulate. Firms face the problem that the knowledge required to develop innovations is usually not held within the boundaries of a single firm. Firms use collaboration as a mechanism to acquire resources, knowledge and skills they do not possess internally, being ever vigilant not to share to the extent that would put the firm at risk (Powell, Koput, & Smith-Doer, 1996). There is considerable interest regarding the effect of geographic proximity and clustering on innovation (e.g., Brusco, 1990; Porter, 1998b; Rosenfeld, 1996). One area that lacks explanation, however, is how firms that are not co-located, and thus not able to benefit from the effects of clustering, overcome this disadvantage of their location. If proximity to other knowledge sources is critical for new knowledge to appear, then how do geographically ‘‘isolated’’ firms innovate? The extant literature provides few clues about how firms outside the clusters are able to survive and compete with firms that derive competitive advantage from the externalities of locating within a cluster. This issue is particularly interesting in the context of innovation, which involves sharing intangible knowledge, which is facilitated by face-toface contact, trust, and common business practices within a cluster (Acs & Feldman, 1994; Camagni, 1990; Krugman, 1991b). A fundamental concept in economic geography is agglomeration, defined as the spatial concentration of economic activity. Agglomerations contain large populations and employment. These areas provide a social context where innovators are recognized, encouraged, and rewarded causing that space to become propulsive in terms of ideas and creativity (Beal & Gimeno, 2001). Marshall (1910) referred to this when he spoke about the feelings people had of being in an ‘‘industrial atmosphere,’’ while Storper and Venables (2003) characterized the social context as ‘‘buzz.’’ Romer, citing Lucas (1988) in his seminal paper on the origins of endogenous growth,

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found the following observation very essential: ‘‘given all the cross-country growth regressions combined y people with human capital migrate from places where it is scarce to places where it is abundant’’ (Romer, 1994, p. 19). There are two major categories of agglomeration economies: urbanization economies and location economies. Urbanization economies occur because of the geographical proximity of industries and services (Hoover, 1970). Location economies arise from the geographical co-location of related economic activities. Co-located firms appear to maintain increasing returns to scale by utilizing positive externalities (Porter, 1990, 1998b; Rosenfeld, 2001). This increase in scale leads to reductions in long-run costs per unit of output, a strong basis for sustained competitiveness. Marshall (1910) posited the three main reasons for the existence of agglomeration economies: input sharing, labor market pooling, and knowledge spillovers. Input sharing is characterized by localized industries supporting the production of their inputs by other firms (Audretsch, 1998; Krugman, 1991; Rosenthal & Strange, 2004). Specialized supplier networks provide evidence of development to serve the agglomeration by providing services and materials. These networks may not be appropriate to serve areas that do not have the scale that agglomerations provide. For example, the clustering of film studios in Hollywood allows firms that supply that industry an opportunity to reach a large market within a relatively close space. A manufacturer of pyrotechnics located close to stunt designers derives market advantages by being close, and scale advantages due to the fact that so many similar industries operate within the same area (Lampe, 1988; Porter, 1990). However, these forward and backward market linkages account for only a small percentage of the benefits derived from agglomerations (Gordon & McCann, 2000). It is difficult to quantify how much of these inputs are physical and how much are knowledge related. It has been found, however, that these localized linkages are not so much caused by high transportation costs, but rather on informational costs (Storper & Venables, 2003). This leads to the conclusion that these linkages vary in importance between knowledge exchange and the actual exchange of physical goods. In this respect, input sharing is a part of knowledge spillovers rather than a standalone source of agglomeration economies. The second reason for agglomerations, labor market pooling, allows access to a large market of industry-specific skills. This, in turn, results in lower unemployment because of the industry–labor match as well as a lower probability of labor shortages (Arrow, 1962; Baptista, 2000; Brusco, 1990; Grant, 2004). Agglomerations afford labor many advantages, including access to a large number of local employers, increased career progression


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possibilities, and better chances for skill development and growth. Locational agglomerations lead to ever-increasing specificity of skill sets targeted to the related activities within the clustered firms. As with input sharing, there is a high degree of knowledge spillover associated with Marshall’s second input, labor pooling. A large labor pool facilitates learning and innovation within the particular skill area since these workers have common expertise to share and develop. For instance, programmers in an agglomeration share nuances and innovative practices. This is facilitated by their common educational background and proximity. Negatively, agglomerations also have potential to lock-in skills, causing innovation to occur along one trajectory to the detriment of the myriad of other possibilities. As well, there are possibilities for poor labor practices to be copied, the maintenance of redundant knowledge linkages, and the potential for hyper-competition (McNaughton & Brown, 2002). Knowledge spillovers make up the third reason that agglomeration economies exist. Knowledge spillovers occur when agents or firms learn new knowledge that can be used in their own products and processes (Acs & Feldman, 1994; Audretsch & Stephan, 1996; Inkpen & Tsang, 2005). For example, a computer programmer from firm A may learn a new approach to testing code from another programmer who works at firm B. This new information can be used to enhance the software produced by firm A. The knowledge therefore ‘‘spills over’’ from one agent to the other. Knowledge spillovers are apparent as part of Marshall’s first two reasons for agglomerations as well. The growth of service suppliers and the availability of industry-specific skills propagate knowledge throughout the agglomeration. Workers who change jobs do not leave their knowledge behind; rather they take it with them and share it with their new co-workers. Romer (1990) prominently identified knowledge spillovers in his theory of economic growth. He concluded that endogenous growth theory depends on the notion of imperfect competition. This occurs since patents allow some firms a type of monopoly power. As well, incomplete property rights are associated with the results of research and development and are a further illustration of spillover effects. The main conclusion of Romer’s work is the central role that knowledge plays in economic growth. Growth theory moves away from viewing knowledge as a codified public good and acknowledges the rightful role it plays in a profit-driven market bringing us full circle back to Marshall’s belief that knowledge, above all other factors of production, is the most powerful (Marshall, 1910). Krugman (1991), however, argues that in order to understand agglomeration economies, the focus should be on the value chain and labor pooling

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since knowledge flows are invisible and extremely difficult to study. Jaffe, Traitenberg, and Henderson (1993) refuted the invisibility of knowledge flows by investigating patent citations and determining that they provide evidence that knowledge spillovers are predominately local. One view that appears to be shared by most economists studying this phenomenon is that knowledge spillovers play an important role in how the economy grows and how firms innovate (e.g., Acs & Feldman, 1994; Audretsch & Stephan, 1996; Romer, 1994; Storper & Venables, 2003). Knowledge spillovers are derived without cost, making them non-pecuniary externalities (which are defined as being external to the normal mathematical approach to valuation). This differentiates spillovers from input sharing and labor pooling since they both represent examples of pecuniary externalities. Spillovers have also been referred to as incomplete property rights since they can provide their benefits for free (Romer, 1994). The fact that firms can benefit from free knowledge is important in terms of lowering their cost structure and making them more cost competitive. This source of knowledge is seen as part of the reason firms will pay a higher rent to locate in a city (Glaeser, Kallal, Scheinkman, & Shleifer, 1992). These firms view cities as places where more interactions occur, providing more opportunities for knowledge accumulation. Of the three reasons Marshall posited for agglomeration economies to form – input sharing, labor pooling, and knowledge spillovers – the latter is the focus of this chapter. Knowledge spillovers are the subject of much debate regarding the location of firm boundaries. It is argued that there may be geographic boundaries that limit the extent of knowledge spillover and in particular the spillover of tacit knowledge (Marshall, 1910, and then Klugman, 1991). In other words, people need to be in close proximity in order to transfer tacit knowledge; tacit knowledge being identified as knowledge that is difficult to codify and therefore difficult to impart (Gertler, 2001a, 2001b; Takeuchi & Nonaka, 2004). Others argue that technology and near costless communication reduce the necessity for proximity (e.g., Cairncross, 1997; Cornet & Beugelsdijk, 2002; Hansen, 2002). They argue that knowledge may be exchanged virtually, without the need for face-to-face interaction, as the new Internet and communications technology are a proxy for ‘‘being there.’’ Discussion of ICT substitution for face-to-face interaction coalesces around the concept of virtual clustering. Some argue that new communication technologies allow clustering to occur regardless of location. Consequently, location, agglomeration, and physical infrastructures do not restrict the mobility of workers in firms, although production does require a given level of communications infrastructure (Cairncross, 1997; Mejia &


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Molina, 2002; Webber & Gore, 2002). Using ICT as a proxy for face-to-face knowledge exchange is appealing given the amount of knowledge that would become available; however, practical matters such as trust between agents and asymmetrical knowledge can be limiting factors for this type of exchange. Cornish (1997) and Gertler (1993) provide convincing evidence for the deteriorating knowledge advantage of being close to customers. Using market intelligence as the basis of her study, Cornish found that greater distance does not seem to affect the ability of firms to gather that market intelligence. Agglomeration in this study has no positive effect on market intelligence acquisition or product performance. However, she does caution that location is still relevant and that agglomerations make important contributions to products produced there since early interactions with potential users are very important to the creative process. This is a key point since the early stage of the innovation process may be the most important of all the stages, and interactions seem most important at this stage. In terms of knowledge spillovers, tacit knowledge holds the most interest. Szulanski (2003) argues that tacit (or sticky) knowledge consists of two characteristics: casual ambiguity and unproveness. ‘‘Sticky’’ knowledge also has the following characteristics: 1. 2. 3. 4. 5.

a source that may be received as unreliable or that lacks motivation; lack of motivation on the part of the recipient; retentive and/or absorptive capacity; lack of an organizational context; and an arduous relationship between the recipient and the source.

This study by Szulanski makes clear the point that sticky knowledge is a cause of difficulty when firms attempt to extract full economic rent from their knowledge, because of the transaction costs involved. Given the difficulties in transferring tacit knowledge, it is evident that one key reason why agglomerations are economically meaningful is the role proximity plays in the knowledge transfer process. Audretsch (1998) identified the cost of transmitting tacit or sticky knowledge as being a function of distance; the longer the distance the higher the cost associated with it. In terms of innovation, the role of tacit knowledge is critically important in the very early stages where most of the knowledge is still resident in the mind of individuals. Furthermore, when knowledge becomes embedded within a network of people, it becomes even more difficult to codify since the knowledge is fragmented and context dependent (Beal & Gimeno, 2001). The argument thus hinges on whether firms that are within face-to-face communicating distance are able to exchange tacit information much more

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efficiently and cost effectively than firms that are located at some distance from one another (Acs & Feldman, 1994; Brusco, 1990; Gertler, 2001a, 2001b; Hitt, Lee, & Yucel, 2002). Since knowledge plays such an important role in innovation, firm location with respect to other firms is important in explaining how competition may be enhanced through increased opportunities for that innovation to occur. Some studies suggest that even with ICT, physical proximity remains an important factor in providing an innovation infrastructure that encourages the interaction of agents representing many different firms (e.g., Ghemawat, 2001; Porter, 1998a; Zaheer & Manrakhan, 2001). The literature contains additional arguments for the advantages of physical proximity. For example, the ability to draw knowledge from neighbors either intentionally or serendipitously (Lonsbury, 2002; Maskell, Eskelinen, Hannibalsson, Malmberg, & Vatne, 1998; Rosenfeld, 2001; Rosenkopt & Almeidal, 2001), and locating close to collaboration partners reduces the transaction costs of communicating between firms. Granovetter (1983) and Grant (2004) provide an understanding of how relationships affect information exchange between firms. It is not only necessary to have proximity, but to foster conditions of trust that lubricate sharing arrangements for the mutual exchange of externalities. Without trust, the exchange may be limited if at all. Storper and Venables (2003) argue that the main source of this trust derives from face-to-face interactions, and that agglomeration economies encourage this by providing densely occupied interaction spaces. Many researchers see face-to-face interaction as an enabler of tacit information exchange (e.g., Acs & Feldman, 1994; Gertler, 2001a, 2001b; Porter, 1998b). Others see face-to-face communication as the best practice for establishing the kind of trust relationships that allow for a freer exchange of information (Levin, 2000; Maxwell, 2003; Wolfe, 2003). Finally, Storper and Venables (2003) cite increases in long distance business travel as indicative of the importance of face-to-face exchanges. In other words, why would cost conscious firms expend resources on travel if there were better ways, for example, ICT, to perform those interactions? Hansen (2002) summarizes the counterargument to the cluster perspective and gives voice to the fact that there are other possibilities for collaborating rather than face-to-face. Table 1 illustrates the various findings Hansen uses to reinforce his point. These studies provide evidence that collaboration with global partners is happening and that it is an alternative to collaborating locally within a cluster. However, they do not examine if the firm is collaborating with a single uninvolved firm or a firm that is currently making use of complementarities within a cluster. Further evidence of distant collaboration is found in Cornet and Beugelsdijk (2002), who reported that

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Table 1. Author Angel (1995)

Hansen and Echeverre-Carrol (1997)

Kaufman et al. (1994)

Collaboration Outside of the Cluster.

Finding #1

Finding #2

Finding #3

One third of those firms studied were involved in collaborative activity The most important collaborations were between local and nonlocal partners 52% stated that geographic proximity was of little importance

Interfirm collaboration tended to happen more in larger firms

Collaboration was more prevalent in firms that export

Large firms and those that exported made more use of collaborative activity

Local linkages were seen as less significant than external linkages

Communication and transportation technology made distance less of a factor

There was much evidence of networks between company presidents over a wide area

proximity between firms made no difference in the Netherlands in terms of knowledge spillovers. They found spending on research and development was more important than research spending by adjacent firms. However, they found that proximity to a technical university was important to neighboring firms and that universities are ‘‘regional boosters’’ of economic development. In summary, proximity and agglomeration is important to the innovation process. They provide economies of scale using specialized input services, deep and targeted skill sets, and efficient mechanisms for the creation, accumulation, and transfer of knowledge for firms within proximity to that knowledge. The literature on economic proximity is divided on the issue of tacit knowledge. Most argue that face-to-face communication is the only reliable means to transfer such knowledge. Others argue that distance may be overcome using ICT as a conduit for transferring tacit information. The few empirical studies available do not provide a clear answer.

THE INNOVATION SURVEY Some empirical evidence on this issue is available in the Survey of Innovation 2003 conducted by the Science, Innovation and Electronic

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Information Division of Statistics Canada. This survey is part of an ongoing effort by Statistics Canada to measure innovation in Canada. The 2003 survey is the first to examine the ICT service industries. The survey collects data on new and significantly improved products and processes introduced to the market. The innovation studies are conducted every three to four years, and cover new products and process introduced over the preceding three-year period. The 2003 data include responses from 2,632 establishments. The sampling frame was stratified by province and randomly drawn from Statistics Canada’s Business Register. Responding to a Statistics Canada survey is compelled by legislation and the overall response rate was 70.5% (2,123 completed questionnaires). Thirty-five different four-digit NAICS industries are represented. The sample includes four sectors: information communication technologies (special ICT aggregation, not including ICT manufacturing), selected professional and technical services, resource industries, and transportation. The sample criteria are a: 1. threshold of $250,000 revenues and at least 15 employees per establishment; 2. census for Newfoundland, PEI, Nova Scotia, New Brunswick, Manitoba, Saskatchewan, the Yukon, Northwest Territories, and Nunavut; and 3. random sample for Ontario, Alberta, Quebec, and BC. Firms were sampled by establishment, unlike previous Innovation Surveys that were sampled by provincial enterprise. As a result, responses from multi-location firms are attributed to the location of individual establishments. This allows analysis of the influence of location on innovation. However, disaggregation beyond the provincial level is problematic, as Statistics Canada will not release data for many smaller urban areas to protect the confidentiality of respondents. Industry Canada (2000) describes the geographic distribution of ICT firms. Toronto has the largest concentration of firms, followed by Montreal, Ottawa, and Calgary. Analyses presented in this chapter use firms belonging to the special classification for the ICT industry. This group should have a high degree of familiarity with technology, which positions them as lead users. The 15 industries in the ICT classification represent 33.7% of the respondents. Owing to reasons of confidentiality, two of the industrial classifications – ‘‘Other telecommunications’’ (NAICS 5179) and ‘‘Web Search Portals’’ (NAICS 518112) do not have data associated with them. Similarly, data is not available for the Yukon, Northwest Territories, or Nunavut. Custom tables were purchased from Statistics Canada for ICT firms that indicated

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they had introduced a new product to the market in the last three years. Seventy-eight percent of respondents from the ICT group had introduced at least one new product in the last three years. Table 2 shows the proportion of firms in each province that had at least one innovation, and the proportion of firms reporting different numbers of new product introductions. Table 3 shows the provincial pattern of proportion of firm revenues accounted for by new products introduced during 2001–2003. Finally, Table 4 shows the proportion of new products that respondents claimed are ‘‘first in Canada,’’ or ‘‘world firsts’’ – a simple measure of the novelty of innovation. These measures provide insight into the rate, importance, and novelty of innovation within the ICT sectors, and differences between Canadian regions. Almost three quarters of firms reported innovating, though the proportion is much lower than the Canadian average in the Atlantic Provinces and in Manitoba and Saskatchewan. The modal category is the introduction of 3–9 innovations in the previous three years, which is consistent for all provinces except the western most – Saskatchewan, Alberta, and British Columbia – which have a modal category of 1–2 innovations. Across Canada, about 40% of respondents Table 2.

Number of New or Significantly Improved Products (Goods or Services) Introduced During the Period 2001–2003.

% of Responding Firms with at Least One Innovation

Canada Newfoundland Prince Edward Island Nova Scotia New Brunswick Quebec Ontario Manitoba Saskatchewan Alberta British Columbia

Number of New or Significantly Improved Products Introduced (2001–2003) 1–2

3–9

10–99

100+

71.3 57.9 x

% of innovating firms 42.2 48.8 x




65.7 69.3 67.9 73.7 64.9 44.5 71.2 74.2

39.6 38.1 37.3 39.5 38.6 67.4 55.5 48.4

45.1 30.9 51.6 47.3 42.9 32.6 36.2 33.7

7.4 30.9 11.2 10.5 18.5 0.0 8.3 14.3

8.0 0.0 0.0 2.7 0.0 0.0 0.0 3.6

Note: x ¼ Data not released by Statistics Canada to protect the confidentiality of respondents.

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Table 3. Percentage of Revenues in 2003 Generated by New or Significantly Improved Products (Goods or Services) Introduced During the Period 2001–2003. Percent of Revenues in 2004 from New or Significantly Improved Products Introduced (2001–2003)


0%

1–9%

10–24%

25–49%

50–74%

75–100%







4.1 12.0

19.7 6.5

35.8 57.6

7.8 11.0

8.3 0.0

24.3 12.9

1.8 3.2 0.0 14.8 13.5 4.4

25.6 11.3 20.0 29.7 14.2 9.8

27.4 36.1 35.6 31.8 20.3 35.9

8.1 24.1 27.2 13.8 24.0 11.4

18.5 10.1 9.0 9.9 9.9 7.7

18.6 15.2 8.2 0.0 18.2 30.8


indicated their most innovative product is a ‘‘Canada first,’’ and 22% a ‘‘world first.’’ However, more than half of those responding from Nova Scotia indicated their product is a ‘‘Canada first,’’ 46% in New Brunswick, and 45% in Ontario. Respondents in Manitoba reported that 27% of their most innovative new products were ‘‘world first’’ and Ontario respondents 28% (both higher than the national average). Tables 5 and 6 present data on the involvement of responding firms in collaborations. Table 5 shows the proportion of innovations developed primarily within the business unit, in co-operation with other firms, or primarily by other firms. Across Canada, the preponderance of innovations are developed in-house (approximately 70%), with 20% developed with other firms, and 10% by other firms. However, there are differences between provinces. Respondents in Newfoundland stand out for reporting 100% of their innovations are in-house, while Nova Scotia, Manitoba, and Saskatchewan notably rely on innovations developed outside the firm.

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Table 4.

Novelty of New or Significantly Improved Products (Goods or Services) During the Period 2001–2003.


First in Canada World first First in Canada World first First in Canada World first First in Canada World first First in Canada World first First in Canada World first First in Canada World first First in Canada World first First in Canada World first First in Canada World first First in Canada World first

Yes (%)

No (%)

Do Not Know (%)

41.2 21.9 29.3 11.0 x x 51.2 11.9 46.2 6.5 38.6 14.4 45.3 28.2 34.9 26.6 17.1 0.0 30.2 14.4 41.7 21.1

30.8 40.6 40.2 69.5 x x 20.3 36.5 22.1 43.1 43.2 56.6 25.1 30.7 35.2 43.6 50.9 82.9 36.1 46.9 25.5 41.1

28.0 37.5 30.5 19.5 x x 28.4 51.6 31.7 50.4 18.2 29.0 29.6 41.1 29.9 29.9 32.0 17.1 35.0 38.7 32.8 37.9


Table 6 lists reasons for involvement in collaborations. The second column shows the proportion of firms in each province that reported involvement in collaborative arrangements. The proportions are higher in the Maritime Provinces, about the national average in Central Canada, and lower than average in the western provinces (with the exception of Saskatchewan). The modal reason for collaborating cited by all respondents is to share costs. However, at the provincial level, this is only the modal category for New Brunswick (for which responses are particularly concentrated in this category), Alberta, and British Columbia. For most of the other provinces, the modal reason is to access critical expertise. The exception is Newfoundland, where more than half of the respondents cited the importance of accessing new markets. Finally, Table 7 shows the location of collaborators by type for all Canadian respondents. (The appendix provides the provincial distributions of

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Table 5.

Development of New or Significantly Improved Products (Goods or Services) During the Period 2001–2003.


Mainly within the Business Unit or the Firm they are Part of (%)

In Co-operation with other Firms or Organizations (%)

Mainly other Firms or Organizations (%)

69.9 100.0 x

20.3 0.0 x

9.8 0.0 x

60.2 65.5 76.2 72.8 67.9 43.1 70.0 65.1

20.3 23.0 16.5 19.4 15.3 26.4 23.4 21.3

19.5 11.4 7.3 7.8 16.8 30.5 6.6 13.6


these data. At the provincial level, Statistics Canada withheld much of the data because of confidentiality or reliability concerns.) The preponderance of collaboration is within Canada, but not necessarily within the same province. The exception is collaborations with consultants, provincial research institutes, and industrial associations, which either rely on face-to-face contact through local offices (consultants) or otherwise have a local mandate. One particularly important observation is the importance of collaboration with suppliers located in the US. (Almost 75% of respondents in Ontario that reported collaboration indicated they had relationships with suppliers located in the US.)

DISCUSSION The key question for this chapter is whether location matters for collaboration and innovative activity. Much of the extant theory argues for the importance of proximity in fostering face-to-face communication, trust, and collaboration. However, given near costless communication, is it not reasonable to expect that firms gather knowledge from any location without worrying about distance? The common response is that tacit information is

Percentage of Business Units Involved in Co-operative and Collaborative Arrangements and Reasons for Involvement During the Period 2001–2003. Of these, Reasons for Collaboration

Business Units in Collaborative Arrangements (%)


Sharing Costs (%)

Spreading Risk (%)

Accessing Research and Development (%)

Prototype Development (%)

Scaling-Up Production Process (%)

Accessing Critical Expertise (%)

Accessing New Markets (%)

Accessing New Distribution Channels (%)

Other (%)

55.0 83.3 x

57.5 45.3 x

42.9 24.0 x

41.5 46.7 x

40.0 25.3 x

16.0 0.0 x

63.8 48.0 x

48.2 52.0 x

33.7 28.0 x

4.7 0.0 x

66.2 58.0

29.1 91.6

29.5 72.2

19.5 54.5

24.7 75.1

0.0 36.3

64.8 63.7

55.3 54.5

44.4 46.4

5.0 18.6

60.6 53.1 52.2 57.6 51.0 52.6

56.1 55.5 35.6 72.7 65.4 64.5

42.9 43.0 12.8 9.2 46.2 48.2

41.1 40.3 48.2 38.7 37.9 50.9

42.2 31.7 46.9 41.6 47.7 57.1

12.7 11.6 16.2 15.5 27.4 30.6

67.9 65.4 73.8 75.2 49.5 59.8

42.9 47.9 37.4 41.6 42.9 64.1

32.5 23.5 35.3 15.5 33.6 71.7

10.7 3.3 0.0 0.0 2.6 0.0


Table 6.


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Percentage of Business Units Involved in Co-operative and Collaborative Arrangements and Location of Collaborators During the Period 2001–2003 (Canada). Business Units in Collaborative Arrangements (%)

Of these, Location of Collaborator Within 100 km (%)

In the Rest of Canada (%)

USA (%)

Mexico (%)

Central and South America (%)

Europe (%)

Pacific Rim (%)

Other Countries (%)

50.1

41.8

64.8

41.9

10.6

2.7

24.7

21.9

8.1

88.2 72.1

60.9 32.2

68.9 65.9

46.1 65.2

4.9 0.8

6.7 2.3

23.3 19.2

15.7 8.3

5.7 5.6

35.1 49.5 13.1

34.9 68.1 18.6

77.9 33.5 74.1

65.1 27.7 75.4

5.8 0.4 0.0

6.4 1.9 6.0

24.8 11.2 F

13.7 1.3 0.0

4.5 3.6 6.2

29.3

F

69.9

24.8

0.7

3.2

10.7

2.5

2.5

8.5

F

F

2.6

0.0

0.0

0.0

0.0

0.0

4.4

84.0

F

5.0

5.0

5.0

5.0

0.0

0.0

5.9

F

36.9

F

3.7

3.7

3.7

0.0

0.0

35.3 2.1

51.1 x

F x

35.9 x

0.0 x

0.0 x

11.5 x

7.8 x

0.0 x

55.0

Note: F ¼ Data not released by Statistics Canada because of low reliability.


Canada Of these, % that collaborated with Other business units within your firm Clients or customers Suppliers of equipment, materials, components, or software Competitors Consultants Commercial laboratories/ R&D enterprises Universities or other higher education institutes Federal government research institutes Provincial/territorial government research institutes Private non-profit research institutes Industrial associations Other types of partners

190

Table 7.


191

most important to the innovation process, and tacit information is difficult to share via ICT and requires high-trust conditions. What then happens in the case of firms located outside of core regions and large urban agglomerations where there are many potential collaborators in close proximity? The evidence from the Canadian Innovation Survey 2003 is varied. These data are important, providing insight into the innovation activities, location, and collaborations of a large proportion of Canadian firms in the ICT sectors. However, because of confidentiality concerns, the evidence must be viewed through bivariate tables rather than the individual responses, and it is not possible to disaggregate the data to the level of individual urban agglomerations. What the data show is this: among ICT firms, which are likely lead users of technology for communication, three quarters innovated during the 2001–2003 period, and only 55% reported collaborating. The typical respondent introduced fewer than nine new products during the period and many only one or two. However, new products accounted for about a modal third of revenues; and about 40% of innovations were ‘‘new to Canada,’’ and 23% ‘‘new to the world.’’ The effect of location on collaboration is uneven. The majority of ICT firms are located in Ontario (the Greater Toronto Area in particular), followed by Montreal (Quebec), and Calgary (Alberta). There are tertiary clusters of ICT firms in Halifax (Nova Scotia), Winnipeg (Manitoba), and Vancouver (British Columbia). The proportions for Canada as a whole are mirrored by Ontario and Quebec, as by far the majority of firms are located in these provinces. However, the patterns in more peripheral regions (especially Atlantic Canada) are not consistent. For example, respondents from New Brunswick report more than typical introductions of new products, while respondents from Alberta report atypical revenues from new products. Unusual levels of ‘‘world first’’ innovations come from both the most important province for ICT activity (Ontario), but also in Manitoba. Proximity of partners does display a pattern of distance-decay, especially for partnerships with consultants and provincial research laboratories. However, a considerable proportion of collaborations with customers and suppliers in particular occur across Canada and especially with firms located in the US (which is the world’s largest market for and leading developer of ICT technology and a market that is open to Canadian firms under the Free Trade Agreement). The highest level observation is one of diversity. Slightly more than half of respondents to the Innovation Survey reported introduction of new products/services, and slightly more than half of innovating firms reported collaborative activity. Thus, it is clearly possible to innovate without

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collaboration, though on average only about 40% of firms reported that their most innovative product was a ‘‘Canada first’’ and 22% a ‘‘world first.’’ Unfortunately, it is not possible to analyze the data for a relationship between novelty and collaboration. The geographic pattern of collaborations does show the influence of distance, with collaboration within 100 km (a proxy for face-to-face) being important. However, many firms also have maintain collaborations across the country and internationally, especially with organizations in the US. Firms with more distant collaborations are not necessarily located in the periphery, with firms located in the Ontario core having a particularly high proportion of collaborations with firms located in the US.

CONCLUSIONS The extant literature is clear on the success of agglomeration and clustering of firms in similar industries. A key question is if and how firms can benefit from knowledge spillovers when they are not co-located, likely through use of ICT. Clusters contain many desirable features for a firm such as deep skill sets, first-class research, and a context of innovation with all the entrepreneurial necessities nearby. Evidence from the Innovation Survey 2003 shows there are good reasons for firms to collaborate – to share costs, access expertise, new markets, and other benefits. The extant literature cites tacit information and trust as the two main obstacles to collaboration. Collaborations are between people and the social aspect of the exchange plays a very important role both in the establishment of a trust relationship and in providing a platform that enables the transfer of tacit information. They are partially the same. Trust lubricates the transmission of tacit information, while exchanging tacit information builds trust. Future research has a difficult task. It must model a process by which firms located on the periphery and/or outside agglomerations may access the knowledge within clusters. The data from the Innovation Survey 2003 reveal both patterns of distance-decay and collaboration at a distance. Further, the relationship is not necessarily as expected – firms in the most central region are most likely to collaborate with those further a field. Technology is making face-to-face and virtual meeting almost indistinguishable by creating software that allows for more communication channels. Coupled with this increased attention to providing the infrastructural technology is a new workforce much more skilled at using the technology, the first generation to view ICT as the norm for communication. A second factor is the concept of


193

a global economy. Innovation need not be viewed as the purview of a local and internal R&D department. Firms will reach out to the market for what is needed rather than depend on their internal capabilities. Contemporary forces may compress distance and make it less of a factor. Peripheral areas can gain from this. However, the whole idea of an exchange is that both parties participate. It is critically important that firms located on the periphery concentrate on core competencies that provide trading incentives for other firms. Without a solid basis from which to trade there will be little interest in collaboration.

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APPENDIX. PERCENTAGE OF BUSINESS UNITS INVOLVED IN CO-OPERATIVE AND COLLABORATIVE ARRANGEMENTS AND LOCATION OF COLLABORATORS DURING THE PERIOD 2001–2003 (BY PROVINCE)

Newfoundland Of these, % that collaborated with Other business units within your firm Clients or customers Suppliers of equipment, materials, components, or software Competitors Consultants Commercial laboratories/R&D enterprises Universities or other higher education institutes Federal government research institutes Provincial/territorial government research institutes Private non-profit research institutes Industrial associations Other types of partners

Of These, Location of Collaborator Within 100 km (%)


USA (%)

Mexico (%)


Europe (%)

Pacific Rim (%)

Other Countries (%)

F

F

F

F

0.0

0.0

0.0

0.0

0.0

92.0 100.0

F 16.0

F F

F F

0.0 0.0

0.0 0.0

13.0 20.0

0.0 0.0

0.0 0.0

16.0 18.7 0.0

x x ––

x x ––

x x —

x x ––

x x ––

x x ––

x x ––

x x ––

10.7

x

x

x

x

x

x

x

x

F

x

x

x

x

x

x

x

x

83.3

0.0

––

––

––

––

––

––

––

––

0.0

––

––

––

––

––

––

––

––

F 0.0

x ––

x ––

x ––

x ––

x ––

x ––

x ––

x ––


Business Units in Collaborative Arrangements (%)

Nova Scotia Of these, % that collaborated with Other business units within your firm Clients or customers Suppliers of equipment, materials, components, or software Competitors Consultants Commercial laboratories/R&D enterprises Universities or other higher education institutes Federal government research institutes Provincial/territorial government research institutes

x x

x

x

x

x

x

x

x

x

x x

x x

x x

x x

x x

x x

x x

x x

x x

x x x

x x x

x x x

x x x

x x x

x x x

x x x

x x x

x x x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x x x

––

––

––

––

––

––

––

––

x ––

x ––

x ––

x ––

x ––

x ––

x ––

x ––

74.3

F

F

0.0

0.0

0.0

6.9

0.0

27.7

89.9 59.0

F 17.4

F 82.6

33.8 24.4

0.0 0.0

5.7 0.0

11.5 0.0

5.7 0.0

0.0 0.0

39.5 F 9.8

x F x

x F x

x F x

x 0.0 x

x 0.0 x

x 0.0 x

x 0.0 x

x 0.0 x

F

x

x

x

x

x

x

x

x

5.1

x

x

x

x

x

x

x

x

0.0

––

––

––

––

––

––

––

––


Prince Edward Island Of these, % that collaborated with Other business units within your firm Clients or customers Suppliers of equipment, materials, components, or software Competitors Consultants Commercial laboratories/R&D enterprises Universities or other higher education institutes Federal government research institutes Provincial/territorial government research institutes Private non-profit research institutes Industrial associations Other types of partners

66.2

197

198

APPENDIX (Continued ) Business Units in Collaborative Arrangements (%)

New Brunswick Of these, % that collaborated with Other business units within your firm Clients or customers Suppliers of equipment, materials, components, or software Competitors Consultants Commercial laboratories/R&D enterprises Universities or other higher education institutes Federal government research institutes Provincial/territorial government research institutes Private non-profit research institutes Industrial associations Other types of partners Quebec Of these, % that collaborated with

Within 100 km (%)


USA (%)

0.0

––

––

––

––

––

––

––

––

F 0.0

x ––

x ––

x ––

x ––

x ––

x ––

x ––

x ––

82.7

F

F

F

0.0

0.0

0.0

0.0

0.0

82.7 90.7

F F

F F

F 91.1

0.0 0.0

0.0 0.0

10.2 0.0

0.0 0.0

0.0 0.0

F F F

F x x

F x x

F x x

0.0 x x

0.0 x x

0.0 x x

0.0 x x

0.0 x x

F

x

x

x

x

x

x

x

x

F

x

x

x

x

x

x

x

x

F

x

x

x

x

x

x

x

x

F

x

x

x

x

x

x

x

x

F 0.0

x ––

x ––

x ––

x ––

x ––

x ––

x ––

x ––

F

F

F

5.7

3.4

19.1

14.0

7.1

Mexico (%)


Europe (%)

Pacific Rim (%)

Other Countries (%)

58.0

60.6 62.5


Private non-profit research institutes Industrial associations Other types of partners

Of These, Location of Collaborator

F F

F F

F F

5.7 3.2

5.7 3.2

7.8 20.1

13.3 12.2

1.1 0.0

39.4 36.3 10.0

F 92.5 x

F 17.9 x

F F x

13.2 2.5 x

13.2 2.5 x

F 5.0 x

16.3 5.0 x

0.0 2.5 x

32.7

F

F

F

2.8

2.8

2.8

0.0

0.0

10.0

F

F

9.0

0.0

0.0

0.0

0.0

0.0

7.0

x

x

x

x

x

x

x

x

10.6

91.5

F

8.5

8.5

8.5

8.5

0.0

0.0

29.0 4.5

F x

F x

F x

0.0 x

0.0 x

11.9 x

0.0 x

0.0 x

F

F

73.6

F

F

0.0

F

F

6.4

89.2 F

66.9 22.2

80.0 F

F 74.7

5.4 0.3

7.1 2.2

F F

20.9 7.8

8.1 11.2

31.8 F 16.6

F F 2.1

F F F

F F F

4.8 0.0 0.0

4.8 0.0 9.2

F F F

F 0.0 0.0

10.4 3.1 10.8

F

F

F

F

0.0

0.0

F

0.0

0.0

4.0

x

x

x

x

x

x

x

x

1.7

x

x

x

x

x

x

x

x

1.9

x

x

x

x

x

x

x

x

F 2.1

F x

F x

F x

0.0 x

0.0 x

F x

F x

0.0 x

53.1

199

Ontario Of these, % that collaborated with Other business units within your firm Clients or customers Suppliers of equipment, materials, components, or software Competitors Consultants Commercial laboratories/R&D enterprises Universities or other higher education institutes Federal government research institutes Provincial/territorial government research institutes Private non-profit research institutes Industrial associations Other types of partners

85.2 67.1


Other business units within your firm Clients or customers Suppliers of equipment, materials, components, or software Competitors Consultants Commercial laboratories/R&D enterprises Universities or other higher education institutes Federal government research institutes Provincial/territorial government research institutes Private non-profit research institutes Industrial associations Other types of partners

200


Saskatchewan Of these, % that collaborated with Other business units within your firm Clients or customers Suppliers of equipment, materials, components, or software Competitors

Within 100 km (%)


USA (%)

Mexico (%)


44.4

9.8

F

F

0.0

0.0

85.9 63.5

F 0.0

40.8 F

52.7 F

0.0 0.0

0.0 0.0

24.0 42.3 10.7

x F x

x F x

x 0.0 x

x 0.0 x

14.7

x

x

x

0.0

––

––

0.0

––

4.4 25.4 0.0

Europe (%)

Pacific Rim (%)

Other Countries (%)

52.2 12.0

0.0

0.0

0.0

0.0

12.4 16.8

x 0.0 x

x 0.0 x

x 0.0 x

x 0.0 x

x

x

x

x

x

––

––

––

––

––

––

––

––

––

––

––

––

––

x

x

x

x

x

x

x

x

x ––

x ––

x ––

x ––

x ––

x ––

x ––

x ––

F

F

F

12.6

0.0

12.6

12.6

12.6

12.6

100.0 F

F 8.7

F 100.0

15.5 21.5

9.2 0.0

9.2 0.0

15.5 0.0

15.5 0.0

9.2 0.0

31.6

x

x

x

x

x

x

x

x

F

F

57.6


Manitoba Of these, % that collaborated with Other business units within your firm Clients or customers Suppliers of equipment, materials, components, or software Competitors Consultants Commercial laboratories/R&D enterprises Universities or other higher education institutes Federal government research institutes Provincial/territorial government research institutes Private non-profit research institutes Industrial associations Other types of partners


Alberta Of these, % that collaborated with Other business units within your firm Clients or customers Suppliers of equipment, materials, components, or software Competitors Consultants Commercial laboratories/R&D enterprises Universities or other higher education institutes Federal government research institutes Provincial/territorial government research institutes Private non-profit research institutes Industrial associations Other types of partners

F x

F x

F x

0.0 x

F x

F x

0.0 x

F x

F

x

x

x

x

x

x

x

x

9.2

x

x

x

x

x

x

x

x

F

x

x

x

x

x

x

x

x

0.0

––

––

––

––

––

––

––

––

F 0.0

x ––

x ––

x ––

x ––

x ––

x ––

x ––

x ––

51.0 F

5.2

F

F

0.0

F

F

F

F

80.2 F

F 30.3

F F

F F

7.8 0.0

11.7 4.2

F 1.3

10.5 4.2

7.8 2.9

25.3 41.6 12.0

F F x

F F x

F F x

0.0 0.0 x

8.6 F x

F F x

0.0 0.0 x

0.0 F x

32.9

F

F

F

0.0

F

F

F

F

12.8

x

x

x

x

x

x

x

x

8.4

x

x

x

x

x

x

x

x

6.8

x

x

x

x

x

x

x

x

F 0.0

F ––

F ––

F ––

0.0 ––

0.0 ––

F ––

0.0 ––

0.0 ––

43.9

F

F

F

0.0

0.0

F

F

11.1

95.9

F

F

F

1.7

4.8

19.2

9.6

4.8

52.6

201

British Columbia Of these, % that collaborated with Other business units within your firm Clients or customers

F 9.2


Consultants Commercial laboratories/R&D enterprises Universities or other higher education institutes Federal government research institutes Provincial/territorial government research institutes Private non-profit research institutes Industrial associations Other types of partners

202


Within 100 km (%)


USA (%)

85.8

30.6

F

71.8

0.0

F F 6.7

F F x

F F x

F F x

22.2

F

F

15.5

x

1.7

Mexico (%)


Europe (%)

Pacific Rim (%)

Other Countries (%)

0.0

11.4

11.1

0.0

0.0 0.0 x

0.0 0.0 x

0.0 0.0 x

5.4 2.9 x

0.0 0.0 x

F

0.0

0.0

0.0

0.0

0.0

x

x

x

x

x

x

x

x

x

x

x

x

x

x

x

10.9

x

x

x

x

x

x

x

x

F 0.0

F

F ––

F ––

0.0 ––

0.0 ––

5.3 ––

F ––

0.0 ––


Suppliers of equipment, materials, components, or software Competitors Consultants Commercial laboratories/R&D enterprises Universities or other higher education institutes Federal government research institutes Provincial/territorial government research institutes Private non-profit research institutes Industrial associations Other types of partners


SOCIAL NETWORKING AND THE DEVELOPMENT OF NEW VENTURES Karl Wennberg and Henrik Berglund ABSTRACT This chapter takes a closer look at how social networks can affect the early development of new ventures. The dynamic role of social networks is discussed and exemplified by two longitudinal cases that illustrate the radically different ways in which social networks can influence venture development. These differences relate to social or individual ownership of the innovation process, to risks or opportunities as the focus of attention, and to the creative relationship between networking and financial bootstrapping techniques.

INTRODUCTION Innovation, bringing something new and valuable to the market, is generally acknowledged as central to job creation, economic growth and industrial dynamics. New innovative ventures play a crucial role in this process because they are not constrained by routines and dominating logics to the same extent as large firms (Chesbrough & Rosenbloom, 2002), which in Innovation Through Collaboration Advances in Interdisciplinary Studies of Work Teams, Volume 12, 203–225 Copyright r 2006 by Elsevier Ltd. All rights of reproduction in any form reserved ISSN: 1572-0977/doi:10.1016/S1572-0977(06)12008-7

203

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KARL WENNBERG AND HENRIK BERGLUND

turn allows them to assume risks and pursue opportunities that larger firms avoid. Despite the recognized importance of agility and strategic flexibility, most research on innovation in new ventures examines individual entrepreneurs with one invention or idea, pursuing a single business opportunity from conception to completion (Van de Ven & Engleman, 2004). A number of researchers have sought a complementary perspective by highlighting how networks and contextual embeddedness affect the innovation process. Reliance on network contacts is especially important among new emerging ventures because of their limited resource base (Birley, 1985; Greene & Brown, 1997). Cooper, Folta, and Woo (1995) showed that inexperienced entrepreneurs tend to rely more on personal ties such as family, friends, and other business owners, compared to experienced entrepreneurs who use professional contacts such as lawyers and accountants during the start-up phase. Yet, most studies treat networks, individuals, and ventures as separate and stable entities, with focus on testing how variance in the former (e.g. strength or number of network ties) affect some outcome in the latter (e.g. firm growth or survival) (Hoang & Antoncic, 2003). This chapter uses a social network perspective to investigate the role of collaboration through social networks in the innovative processes of two new independent ventures. A social network approach allows us to explore how new ventures develop without constraining our focus to specific individuals or inventions (Jack & Andersen, 2002). What distinguishes this study, and where our approach takes a detour from much prior research, is the focus on the new venture as unit of analysis. We approached a wide range of stakeholders involved in two ventures, to discern how they and their social networks affected their development. These cases are used to discuss the role of individual versus social ownership of the innovation process, attitudes toward risk and uncertain opportunities, and how entrepreneurs use their social network to gain access to information and resources, bootstrapping their ventures. We conclude by offering some brief implications for practitioners and policymakers as well as discussing potential avenues for further research.

SOCIAL NETWORKS AND INNOVATION A social network perspective indicates the relationships between entrepreneurs and others that help them to access information and resources

Social Networking and the Development of New Ventures

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necessary to build a venture (Greve & Salaff, 2003; Johannisson, 2000). These relationships are typically investigated from either the network or the individual perspective. Perhaps the most elaborate theoretical framework of how social networks influence new venture development, is Larson and Starr’s (1993) network model of organization formation, where entrepreneurs’ relationships develop from a set of relatively simple, personal and one dimensional exchanges, into a network of stable, multidimensional and multi-layered relationships. The entrepreneur’s and other stakeholders’ separate contacts thus gradually develop into a more cohesive network that shapes the new firm. However, Larson and Starr tend to underestimate the role of networks in the very early venture formation phase, as their model assumes that entrepreneurs begin their search for appropriate contacts once the decision to start has already been made (Hoang & Antoncic, 2003). Others have suggested that both the identification and manner of exploration of new opportunities, is borne out of their existing networks (Birley, 1985; Davidsson & Honig, 2003). Hite (2003, 2005) instead puts forth a more fine-grained conceptualization of social networks. On this account, a social network is made up of more or less relationally embedded ties. That is, a specific network tie between an entrepreneur and another person is seldom characterized by pure economic exchange or pure social relationship but is somewhere on a continuum (Hite, 2003). A social network can be understood in terms of three distinct types of relationships: (1) personal relationships, (2) social capital, (3) dyadic economic interaction, or a mixture between these. The difference in these three types of embedded ties lies in the variation of the type of social relationship in which they are embedded (Hite, 2003). Sources of interpersonal trust and mechanisms of control accordingly differ between the three relational types: (a) network ties based on social capital dependent on reputational control and trust built through a third party, (b) network ties based on economic interaction depend on control stemming from the joint value of the relationship history, (c) and personal/competency trust such as goal congruence. The type of network ties to a large extent determines how entrepreneurs are influenced by their external relationships. For instance, a close friend or relative may offer information or resources that persuade the entrepreneur away from a preferred economic choice (Staber & Aldrich, 1995). Whereas many network ties are initially based on personal relationships or economic exchange, the interaction spawned by the venturing process often develops and strengthens the tie, making it both personally and economically embedded (Hite, 2005).

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As personal and economical relations overlap, it is difficult to know which relationships will turn out to be important for the venture. Network relationships and social capital are typically built up for reasons other than their potential economic value (Arrow, 2000). Many studies also indicate that social structures, including extended family, religious organizations and social clubs, provide both information and resources crucial to the venture’s development (Jack & Andersen, 2002; Davidsson & Honig, 2003).

NETWORKS AND RESOURCES As mentioned in the introduction, small innovative ventures are exposed to specific risks and opportunities. For example, where established firms can use their existing resource base or established contacts with suppliers to foster new innovative activity, independent ventures are generally more resource constrained, and have to establish new ties with potential suppliers and customers. This requires a certain measure of agility and flexibility on behalf of the small ventures. The literature often uses chess as a metaphor for the planning orientation of corporate strategy. In new venture development, poker is sometimes suggested as an alternative metaphor, because: ‘‘you play each hand as it is dealt and quickly vary tactics to suit the conditions’’ (Bhide´, 1986, p. 62). This short-term focus is often attributed to a lack of financial and other types of resources (Birley, 1985; Starr & Macmillan, 1990). Many studies have noted that new independent ventures have trouble finding financial capital on the open market (Bhide´, 1992) forcing them to use different forms of financial bootstrapping. Winborg and Landstro¨m (2001) describe six broad categories of bootstrapping techniques: obtaining support including unsalaried work from owner/managers and relatives; management of accounts receivable such as speeding up invoicing; sharing and borrowing resources from external actors; delaying payments which includes leasing or renting instead of buying; minimization of investment in stocks, for instance through good relationships with suppliers; and obtaining subsidies from different public agencies. Bootstrapping techniques allow entrepreneurs to develop their ventures at a minimum of financial risk. This relates to venture development strategies based on taking affordable risks rather than trying to maximize returns (Sarasvathy, 2001), seeking pre-commitments from stakeholders as a way to reduce uncertainty (Garud, Jain, & Phelps, 1998) and more generally adapting the businesses in accordance with external demands (Bhide´, 1986). These techniques tend to rely on networking and establishing relationships


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that go beyond mere exchange of resources. To further probe this relationship, we present two case studies that illustrate how collaboration in social networks can be beneficial for new ventures with a limited resource base. Case Illustrations The following two cases illustrate the quite different roles social networks can play in venture development processes. Traditionally, the role of networks in innovation has been investigated from either a structural or an individual perspective. This study departs from these traditions by taking the developing venture as the focal unit of analysis. Individuals and networks are thus seen as ancillary, as focus is on how various individuals in different ways contribute to the venture development process. This is in line with Van de Ven’s (1986, p. 591) description of the innovation process as ‘‘development and implementation of new ideas by people who over time engage in transactions with others within an institutional context.’’ The two cases are similar in many respects. They both developed in the same part of rural Sweden, are in their early stages and center around innovative product ideas based on patented inventions. At the same time, they differ radically in the way networks and relationships are used. We gained access to the two ventures from their connection to a professional network consisting primarily of innovators and entrepreneurs. We followed the ventures from spring 2004 until summer 2005 and the cases descriptions are based analyzed of seven face-to-face interviews lasting on average 2 hours, 12 telephone interviews of varying length, and over 20 e-mails with follow-up questions. We also downloaded annual statements and patenting information from publicly available sources. Furthermore, we were allowed to examine (but not take away) copies of board meetings, and to examine other written material such as business plans and market surveys. The ventures were both initiated a few years before the first interviews. Information retrieved about these years may therefore suffer from a number of retrospective biases. To reduce these problems we employed a careful stepby-step approach when analyzing and writing up the case histories. The existence, timing, and nature of all past and current critical events have thus been verified by approaching at least two different individuals on different occasions (cf. Van de Ven, Polley, Garud, & Venkataraman, 1999). When interpretations clearly conflicted, the two researchers listened, read, and compared interview material with archival data before arriving at a common interpretation. This procedure allowed us to check different sources against each other, thereby producing a more valid account of both the nature of

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Regular interviews commence 2001

2004

2002

Negotiations initiated with potential partners Tim and Larry

Crucial People

TIMELINE

2005

Professional CEO hired

Negotiations resumed with Tim and Larry

CEO leaves during bankruptcy

?

Crucial People

Crucial Events

Alpha Clean invented and patented

A retired inventor designs a new type of container lock. It is patented in several countries.

TransportSafe is founded and marketing research / product development initiated.

Alpha Clean expands overseas under hired CEO

Delivery problems in Alpha Clean

First round of financing is brought in from private investors.

Stephan joins the team bringing technical know-how.

An electromagnetic lock is developed.

Fig. 1.

Conflicts with CEO, large turnover but no profit

Alpha Clean is declared bankrupt

Coincidental meeting leads to deal with crane producer to include magnetic lock in a new crane system.

The electromagnetic lock is replaced with a radio-based system.

Timeline for the Two Ventures.

A tracking system for containers is developed and patented, as well as a new chip for security sealing.

Second round of external financing, brought in from a VC firm.


Crucial Events

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Table 1.

Characterizations of the Two Ventures. Alpha Clean

TransportSafe

No of initial partners No of partners added/ dropped

2 Prof. CEO added CEO sacked

3 2 founders retired 1 technician added 1 active investor added

Invention Initiation Product(s)

Internally generated 2002 Hand-held cleaning machine

Acquired/Internally generated 2001 Twistlock for containers (3 versions developed) Container tracking system Container security seal

Business model

Changed ad-hoc due to marketing difficulties

Changed several times New products developed New market discovered Partnering with big firm

Capital structure

Founders’ capital Local innovator grant

Founders’ capital Public innovation grant External capital (private) External capital (VC)

Gross sales 2004

$1,200,000

$29,000

Status spring 2004

Distribution problems Beginning international sales

Developed radio lock First round of financing (private capital)

Status summer 2005

Pending bankruptcy Trying to re-start

Deal signed with partner Production tests started Completed second round of financing (VC)

Team’s previous experience

Technical experience No entrepreneurial experience Contracting necessary skills

2 members earlier entrepreneurial experience in same industry Complementary skills

social relations and the venture development process in general. The overall development of the ventures and critical events are indicated on the timeline in Fig. 1, which follows after the case histories. In Table 1 below we also list some general characteristics concerning the two ventures. The table indicates the difference between the two ventures in terms of team structure, product and business model development, and in particular, the status and financial

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success of the ventures. While the first venture, Alpha Clean, clearly had a much higher market impact during the year of study, the case studies indicate the second venture, TransportSafe, as the more successful one.

ALPHA CLEAN Before starting Alpha Clean, the founder-manager Steve considered his active career to be behind him, and with extensive experience from machine tool repair shops and development projects for the military and large private firms, he had no problems getting by on part-time work and temporary contracts. The idea for Alpha Clean originated when Steve’s son took a job cleaning machine rooms and other risky facilities. The work environment was quite demanding with winding stairs, narrow passages and hard to reach areas around very sensitive equipment. Since the available cleaning machines were bulky and unsuitable for usage on uneven floors, work was very hard and labor intensive. Steve, therefore, tried to rebuild a few of the smaller cleaning machines available on the market, but without much success. After several attempts, he eventually constructed a completely new type of portable scrubbing machine, based on the technology used in automatic toothbrushes. Steve’s son tested the machine in various setting such as staircases, high walls, crowded industrial kitchens and other awkward places. The machine performed much better than anything he had seen on the market and together father and son were convinced that this could become a commercially successful product. Steve quickly applied for a patent and soon thereafter approached the cleaning division of a large home appliances firm. The manager responsible for the ‘wet cleaning’ product division was positive and signaled an interest in developing the product. However, one month after talks had been initiated, the firm unexpectedly pulled back, citing a review of their overall product portfolio. Steve and his son eventually decided to pursue the project themselves. Being new to the region, they lacked business contacts and therefore approached the local chamber of commerce. They found that their firm was eligible for ‘innovator grants’ from the local economic development authority. With these limited funds, Steve hired an industrial designer to finish the product. They then negotiated with a number of assembly plants with excess capacity, and after three months, contracted a firm to produce the cleaner. The only drawback was that the firm was located quite far away from Alpha Clean’s location in a regional distribution hub. According to Steve this was discussed as a potential problem and therefore he was


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careful to specify explicit delivery details in the final contract. From his long experience in the military sector, Steve felt quite comfortable with minding his part of the bargain and not to develop any deeper contacts with his distributors: ‘‘We needed a decently priced subcontractor and finding [this subcontractor], I was careful to outline everything I needed in the contract, that’s the way I’m used to [handle] things. All nearby plants were either too expensive or lacked capacity to help us. I really didn’t know anyone [nearby] that could do this, so it had to be this firm.’’

The final product was light and easy to use, with replaceable scrubber heads at the end of an adjustable ‘broomstick.’ Attached to the stick was a small water tank with an electric pump connected to the scrubber heads. They applied for European, Japanese and American patents, and Steve’s son also tested the final product at home and at various industrial facilities. A few machines had been sold for testing and development purposes at an early stage, but now it was time to start selling on a larger scale. The large cleaning firms had centralized purchasing departments and Steve found it difficult to bypass their established relationships with existing producers of cleaning machines. Instead, he approached local cleaning machines retailers directly who supplied equipment to the large, but highly fragmented, segment of small- and medium-sized cleaning firms. This segment includes countless small-scale cleaning firms, companies with their own in-house cleaning division, and private users. At this point, Steve’s son was handling most of the sales and since the first batch ordered from the assembly plant was quite large, he decided to introduce a discount system that would get distributors to buy more products. After a slow start the first few months, sales suddenly took off sharply. Since the first batch was not yet produced, the company had to introduce a formal waiting list for new customers. Given the high demand for the product, Steve decided to hire a professional CEO to build up a small sales force and begin to market the product overseas. At this point, we begin to follow Alpha Clean through regular interviews. Via the local Chamber of Commerce, Steve came in contact with a local innovator’s network. The other people in the network liked Steve and appreciated him as a knowledgeable ‘‘old-fashioned inventor.’’ As such, he differed from many of the young and typically IT-oriented entrepreneurs of the time. Steve himself did not think much of the people at the Network: ‘‘I never really liked it at those [Network meetings], you know. Sure, I met some nice people there and many where really interested in us. But that bothered me, the whole I’ll scratch your back you’ll scratch mine attitude. And then it was that collaboration that never came through, and those people really irritated me.’’

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This collaboration refers to contacts taken by Larry and Tim who had been involved in initiating the local innovator’s network and were also responsible for organizing the monthly meetings. Tim first met with Steve at the Chamber of Commerce, where he had recommended a production consultant who could pre-test and improve their product. Larry and Tim convinced Steve to present Alpha Clean at one of the Network meetings. After the presentation, Steve told Larry and Tim that the venture was having problems and that he could use some advice. Despite huge demand for the product and fairly low production costs, Steve had significant outstanding debts and the cash flow was very low. The problems could be attributed to production delays combined with low profitability on the products sold so far. Despite their assurances, the manufacturer had incurred repeated delays. Steve’s contract with the plant clearly stipulated regular delivery of products. Despite this, the first batch had been delayed several months. Shifting to another production plant was too costly and the lack of funds meant Steve could not afford to enforce his contract. All he could do was to keep scolding the assembly firm for not shipping in time. On hearing about the problems, Larry and Tim agreed to discuss how to resolve the predicament. They were both interested in the project and tried to get Steve to take them in as partners. Tim explained his view of the problem: ‘‘I was astounded by his choice of production facility. Sure, it was cheap enough, but why the heck did he choose that far-away location instead of something nearby? It must have contributed to him losing track [of the production progress].’’

Regarding the production situation, Larry and Tim could not help Steve beyond saying that a more accessible plant would have been better. When it came to discussing sales, Larry soon realized that this was big problem for the venture. He tried to convince Steve that a long-term sales strategy was important, and that such a strategy had to consider Alpha Clean, the end customer, as well as the middle man. Until now, Steve’s son had been in charge of sales and marketing. He soon realized that the cleaning equipment retailers only bought one or two products at a time in order to maintain a small stock. To boost sales, he had introduced a discount system that offered 20 percent discounts if customers bought more than 5 machines, and 50 percent discount for more than 10 machines. At the meeting with Steve and his son, Larry scolded the strategy and explained his reason to do so: ‘‘He had listed all distributors on his web-site, to gain credibility or something, I dunno. Apparently, the distributors had simply got together to buy in bulk and get the large discounts offered. So he sold the products beforehand at a 50 percent discount, and when the first few batches took several months to deliver, he had to offer some of them even higher discounts for them not to cancel their orders.’’


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In the end, despite low production costs and good sales, Alpha Clean made almost no profits. At this point in time, production had also begun to pick up and the firm had employed two secretaries and the production consultant that Tim had recommended. Money started to come in to the company, but flowed out just as fast. After two weeks of meetings and informal advice, Larry and Tim offered Steve a deal. They wanted to enter the venture as equal partners, but in order to get rid of the poor agreements with the manufacturer and current customers, they suggested that the patent, which was Steve’s and not the firms, should be transferred to a new company that would be jointly owned by the three of them. Steve wanted none of this: ‘‘They just acted like they knew what was best for me all the time. Do this! Do that! It was my invention. I didn’t need anyone in the driving seat telling me what to do. All I needed was advice on how to manage this sales network, which obviously didn’t work.’’

The negotiations with Larry and Tim ended in disagreement and bad spirits. Instead Steve promoted the production consultant that Tim had recommended to CEO and put him in charge of the firms’ international expansion. The consultant had impressed Steve by speaking six languages and boasting lots of overseas business experience. Steve was confident that a professional CEO would be able to handle ‘‘much of the management details.’’ Soon after having been promoted, the CEO went on to set up a Paris office from which to manage the European expansion. Steve designed an elaborate contract that included incentives to boost sales and establish new contracts with local dealers in different countries. The contract also included a very generous severance package. This proved to be a big mistake: [Steve]: ‘‘In the first half year of international expansion, everything went well. We finally had production on line, and the international deals made up for the bad first deals in Sweden. And we were selling a lot! Actually, we where selling so much I was surprised that not more money was flowing in.

As Steve and his son looked into the accounting of Alpha Clean, they began to suspect that the CEO had embezzled money from the overseas sales. However, they had no clear evidence and the CEO vigorously rejected the accusations. Still, it was apparent that the CEO had signed a number of highly questionable long-term contracts with overseas partners. The worsening relationship between Steve and the CEO did not help business, and since the international contacts were handled by the CEO personally, not much could be done about the situation. Steve realized he had to get rid of the CEO to turn the venture around. Unfortunately, the severance deal meant that this was quite an expensive alternative. This was a very difficult

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period for Steve and during the spring of 2005 he left the day-to-day operations to his son. At this time Steve only gave interviews over the phone: ‘‘Last year we sold over one million dollars but at the end of the day there was nothing left. After all our hard work! I felt like crying.’’

Steve and his son thought of alternatives that would secure the future of the firm. In May 2005, they declared Alpha Clean bankrupt. Apparently this was the only way to get rid of the CEO and get out of the poor contracts he had signed. Steve and his son lost their invested equity, but the patent was still theirs. As of summer 2005, Steve wanted to discontinue the interviews, clearly feeling bad about the way things had turned out. He was back negotiating with his old contacts Tim and Larry, about possible financial restructuring and re-start of the firm.

TRANSPORTSAFE TransportSafe started with a famous Swedish inventor who, during his retirement, had produced and patented a new type of mechanic twistlock for loading and unloading shipping containers. After his retirement, the inventor moved to a small city in rural Sweden where he became neighbors with Bill. At the time Bill was involved in a partnership trying to market a new type of absorption material for container use. As Bill’s current venture was reaching a dead-end, he suggested to his partner John that they abandon the current idea and approach the inventor. The inventor agreed to sell the invention in exchange for cash and a partial ownership in the new firm that the three of them set up. John, who knew a lot of wealthy people from his earlier job as a tennis instructor, approached one of his friends and convinced him to invest in the firm. This provided the capital injection necessary to start developing the invention. With the experience from the shipping industry from their former venture, John spent a couple of months traveling the world doing market research, talking to industry specialists, dock and shipping managers, and the like. He realized that there was a huge market that has not been modernized in many years. All available twistlocks were either manual locks that were locked and unlocked by hand, or semi-automatic locks that closed automatically but had to be manually unlocked before containers could be unloaded. This meant huge labor expenses for the shipping business, which had to employ large numbers of stevedores to climb the containers on ship decks to lock and/or unlock containers, often stacked up to eight containers


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high. Calculating that a large ship carries over 6,000 twistlocks, John saw a hefty profit to be made for anyone who managed to produce a lock that could reduce the problem of manual locking and unlocking. The suggested twistlocks relied on guiding wires that allowed ship operators to open them by pulling a trigger connected to the crane, lifting the containers. John had a factory produce a dummy of the lock, an impressive one-foot 45-pound piece of solid iron. Bill, John, and the inventor approached a big crane company in the shipping business. The company showed interest and organized a presentation of the product during a pan-European sales conference. The idea was met with skepticism by the gathering of international salesmen, especially regarding the robustness of the guiding wires supposed to connect to the container locks. The inventor then asked: ‘‘But we have also been talking about doing an electromagnetic version of this lock, where the guiding wire goes down with a small magnet, and an electronic engine pulls down a small lever to connect the magnet.’’

This was clearly more interesting for the people at the conference. But how would they produce this? John and Bill were not technicians, the old inventor had no experience in electromagnetic applications and also his health condition was getting worse. John, who had participated at a few meetings with the local innovation network, remembered a retired technical manager who was working part-time as a consultant in various product development projects. John went to meet with the consultant, Stephan, and explained the idea with the big iron lock in front of them on Stephan’s porch table. Was Stephan interested and able to design some sort of electromagnetic tool to operate the lock? Stephan joined the venture, putting up a trickle of money and buying into the venture. For a small consulting fee, he together with a few former colleagues managed to produce the suggested electromagnetic tool in three months. John’s friend, who had invested most of the money, provided a second small capital injection together with a group of wealthy businessmen. This is the point where we came in and began to follow the venture. It was yet unclear who would be the customer of the product. Bill had now stepped back as a passive owner as he felt he had little to contribute to the current state of the venture. The original inventor had also withdrawn. John and Stephan approached the main European shipping firms to investigate their interest. The reaction of the biggest shipping firm was negative: ‘‘Why are you still doing that thing with the guiding wires? On our new boats we are trying to replace the 40-feet containers with 45-feet [containers], there’s no chance you could fit those guiding wires down on the sides. What we want is a purely automatic lock! Come back if you have something [like an automatic lock].’’

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Disappointed, John and Stephan discussed with their board what to do. According to Stephan, the highly magnetic environment of container docks would make it extremely difficult to get a reliable radio signal through. Their lawyer suggested they liquidate the firm and try to sell the existing patent since the business idea seemed unfeasible and keeping the patent internationally active was expensive. The current investors, however, wanted Stephan to investigate the possibility of a radio-based locking system. At least they knew that the shipping industry was interested and that nobody else seemed to have such a system. Stephan searched his former colleagues and eventually found that one of them was managing a research group in microwave engineering at the local university, looking for new projects as the telecom industry was cutting back on R&D. On behalf of TransportSafe, a research group was set up and in only six weeks they had managed to modify the lock so that a radio signal from a loading crane would be able to open and close the lock. The final lock, operated by remote control, seemed to be the first such solution in marine history. TransportSafe immediately applied for worldwide patents. One of the new investors in TransportSafe had also joined the management team as a production specialist. He negotiated with a factory that could cast the non-electronic parts of the locks; however, they where hesitant toward the project as it would entail significant initial costs in producing molds and running trial batches. The newly patented radio system together with an official letter of interest from the director of the large shipping firm was used as support in discussion with the casting factory, and finally the manager of the casting factory was convinced: ‘‘See, we didn’t believe in the project to start with, [it] all sounded kind of hazardous and untested, producing a large batch of a completely new type of lock. This is a highly centralized market, you know. Though we liked them [the TransportSafe team], we couldn’t bet on the project to succeed. We needed something, and I believe by that [recommendations from the shipping firm] they gave an argument that I could present for my boss.’’

During the renewed talks with the shipping firm, a new idea was initiated. Although safe transports was still of key interest for the firm, another issue had climbed to the top of their agenda: that of security. As John explained: ‘‘They [the shipping firm] told us that the radio link was all great. But it will take time and come through with new cranes for the harbors. And it seemed the harbors were pressing the [shipping] industry to improve upon security. The heightened awareness of this since September 11 brought up the issue of the immense difficulties in keeping track of containers. A harbor manager even said that over ten percent of all containers are lost when they are unloaded and it usually takes several days to find them. Imagine, Ten percent! Of all the million containers out there, every day. I saw that this could be an important area.’’


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The reason it was impossible to keep track of containers was that the general GPS system could not be used to pinpoint containers due to radiation and magnetism generated by the metal containers in a dense harbor. The engineering group employed by TransportSafe therefore constructed a small transponder that could be activated when the ship unloads. Since all ships are controlled by GPS, it would thus be possible to link a particular ship to its containers. This seemed to be exactly what the shipping firm was interested in. In addition, an electronic seal was developed to record when and for how long a container had been opened. TransportSafe now had three patented products: First, the radon lock that facilitated loading and unloading of containers. Second, the tracking system that would help shipping firms keep track of their containers, ensuring delivery-on-time for the customer as well as improved security for harbors and authorities. And third, the security seal that made sure that no one unauthorized to do so could put something in a container during transportation. Now the question was how to proceed with selling the products. The tracking system and security seal only existed as prototypes and the radio lock was not compatible with the current container and crane standard. The big shipping firms had expressed their interest, but discussions in the venture now centered around who should be the final customer, shipping firms or harbor management firms? As the question was pondered and tested on various possible customers, Stephan was contacted by a delegation from the Chinese Shandong province, currently on visit in Sweden. Since China is of key interest for anyone seeking business in the shipping industry, Stephan invited the delegation for dinner in his big summer house. The delegation was administered by a Chinese woman married to a Swedish executive at a big crane-producing firm. Stephan described the meeting as a coincidental stroke of luck: ‘‘When he asked me what I was doing I replied ‘Well, I’m working in a start-up developing automated containers locks’, the executive replied ‘Heck, automated shipping systems, that is what we are doing!’’

It turned out the big crane firm was trying to automate their crane system to sell at harbors, and they needed a product just like TransportSafe’s. Could they license the radio lock system? After lengthy negotiations, a deal was made where the crane firm would handle sales and marketing to harbors, buying the electronic locks from TransportSafe for inclusion in their crane systems. TransportSafe would also sell the new locks directly to shipping firms, with the crane firm taking a small percentage for the lock

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to be sold jointly under the crane firms and TransportSafe’s labels. A professional CEO with experience from the shipping industry was recruited and TransportSafe began to look for an investor to bring in a round of capital until the firm could achieve profitability. They negotiated with several venture capital (VC) firms as well as a public investment agency. In spring 2005, a VC firm with strong regional ties bought a large minority post in TransportSafe. This guaranteed funding for at least a couple of years, given the current level of operations. John and Stephan’s active roles in the company’s management now declined and instead the CEO and his newly recruited production consultants gradually took over most of the day-to-day management. An electronics supplier had been contracted so the priority now was to develop the production system with the firm that would produce, cast and assemble the lock. The first batch was scheduled for late 2005, with marketing activities to commence the following year. With the original venture team taking positions as board members or passive owners, the case study was concluded on a very positive note in the summer of 2005.

DISCUSSION Both Alpha Clean and TransportSafe started with patented innovations that were exploited in independent ventures, targeting established industries. However, the ways the ventures developed was very different. In Alpha clean, the inventor Steve was also the entrepreneur and even though he interacted with external stakeholders he was reluctant to let others influence the venture development process. In TransportSafe, the original inventor let go of his idea, and as the venture developed the leading individuals were often replaced by others, which led to a continuous infusion of alternative perspectives and ideas. Both cases highlight the important role of social networks in the venture development process. The story of TransportSafe particularly illustrates how social networks and the opportunities they reveal can have a major effect on the direction and structure of ventures. In what follows we take the two cases as point of departure to glean three more general lessons relating to ownership of the innovation process, focus on risk or uncertain opportunities, and the relationship between network embeddedness and bootstrapping.


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INDIVIDUAL OR SOCIAL OWNERSHIP OF THE INNOVATION PROCESS A key difference between the two ventures’ network structure was that TransportSafe through their different stakeholders had a larger number of embedded ties, and more variation in type of embeddedness. Alpha Clean primarily relied on formal contracts and the embedded network ties of the father-and-son founders seem to primarily have grown out of their prior economic interaction with various individuals. TransportSafe on the other hand used both formal and informal contracts in interaction with others, and the embedded network ties of the founders seem to have grown out of a combination of personal relationships, social capital, and economic interaction. Arrow (2000) argues that all agreements to cooperate involve non-economic understandings in addition to those that are specified in a formal contract. Such non-economic understandings would be relatively more important for new independent ventures that are in weak positions to enforce contract compliancy due to their limited resource base (Bird, 1995). This framework would explain the outcome of Alfa Clean as being negatively affected by a lack of supportive non-economic relationships. This concerns Alfa Clean’s insufficient governance mechanisms, namely the assembly plant, sales agents, and the hired CEO. Choosing an effective governance mode requires consideration not only of the transaction, but also of the type of relationship (Hite, 2003).

FOCUS ON RISK OR OPPORTUNITIES A related issue concerns whether focus in a new independent venture is on managing perceived risks or exploring uncertain opportunities. Many of the differences between the two ventures seem to hark back to a focus on handling the existing risks or exploring uncertain opportunities. Alpha Clean and its owner-manager Steve sought to avoid uncertainties. The main priority was to keep existing risks under complete control. This was evident in relationships with other organizations as well as with individuals. In either case Steve’s goal was to maintain control and only enter into relationships that could be clearly specified from the outset. Alpha Clean thus tried to draw up explicit contracts to handle the visible risks, but paid little attention to uncertain issues that were not directly obvious. This indicates a view of

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the future as predictable. If, on the other hand, the future is seen as highly uncertain and unpredictable, actions need to be based on vague perceptions of benefits that are not always conceivable at the present time (cf. Lane, Malerba, Maxfield, & Orsenigo, 1996). Allowing new people to influence a venture, means that new skills and also a wider network is brought to bear on the venture. This increases the likelihood that it will develop in novel ways that could not be perceived from the outset. The openness to uncertainty seemed to pervade TransportSafe. For instance, the originally negative response from the large shipping firms triggered a broad search for potential solutions. Without knowing what he might find, Stephen contacted some old colleagues and happened to come across a potential solution that would lead the venture in a radically new direction. The TransportSafe story also indicates that network contacts can be providers of tangible resources, but also have reputational or signaling content. This is exemplified with how TransportSafe used their biggest potential customer, with whom they had close ties, as a reference to the casting factory that were hesitant to accept the initial order for casting the new container locks. In the uncertain and dynamic environment of new independent ventures, resource holders such as the TransportSafe’s casting factory are likely to seek information that helps to gauge the underlying potential of a venture (Hoang & Antoncic, 2003). To summarize, a focus on clearly perceived risks may lead to an overly defensive attitude where uncertain alternatives with great potential may be neglected. It would seem that entrepreneurs should be careful to not only manage risk, but also to consider the opportunities available in the uncertain future, even if potential gains are often hidden. Taking a cue from the discussion of social ownership, a focus on exploring uncertain opportunities rather than managing risk suggests a more creative role of financial bootstrapping than is typically described in the literature.

NETWORK EMBEDDEDNESS AND BOOTSTRAPPING Hite’s (2003, 2005) classified entrepreneurs’ social network according to three types of relationships: personal relationships, social capital or economic interaction. The two cases exemplify how network relationships relate to the types of bootstrapping techniques available for entrepreneurs (Winborg & Landstro¨m, 2001). TransportSafe frequently used unsalaried work from friends and colleagues of the venture team. The strategy was taken one step further as lawyers, technical designers and others with important skills were


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actively invited to join the venture team as either employees or board members. The venture also managed to access cheap external resources as in the case of the local research team, or when the casting factory was persuaded to share the risk of producing the first trial batch (Garud et al., 1998). By using bootstrapping techniques like these, TransportSafe was able to identify a broader range of ideas and options, besides lowering direct costs of development. Alpha Clean initially used some typical bootstrapping techniques, such as seeking subsidies from public agencies and obtaining support in the form of unsalaried work from owners and relatives. Most of the resources, including design expertise and production, were however bought on the open market with involvement regulated in formal contracts. A key assumption in the bootstrapping literature is that lack of resources forces entrepreneurs to experiment with alternative solutions, such as getting access to resources obtained from external stakeholders or the entrepreneurs’ friends and relatives. However, two cases suggest that individuals with more management experience and richer personal networks, tended to use more external contacts regardless of the resource needs of the venture. This indicates that the network relationships available to a new venture, affect what types of bootstrapping techniques are employed. It also seems that entrepreneurs with extensive and well developed social and professional networks have a large collection of contacts that can introduce them to new stakeholders. Conversely, entrepreneurs with more limited social networks find more of their bootstrapping opportunities in personal relationships with friends and family. This resonates with Cooper, Folta, and Woo (1995) who found that inexperienced entrepreneurs tend to rely on personal ties such as family, friends, and other business owners, whereas experienced entrepreneurs rely more on professional contacts such as lawyers and accountants during their start-up phase. Examples of how network embeddedness is related to the type of relation embeddedness are described in Table 2. It is interesting to note that TransportSafe, which received two rounds of external funding, still relied heavily on bootstrap techniques. Judging from the constructive effects these relations had on the development of the venture, it seems reasonable to suggest that the rationale for using bootstrap techniques should be extended beyond economic necessity to also include its role as a creative venture development strategy. To the extent that bootstrapping techniques rest on embedded network ties, they serve to generate and validate ideas regarding the venture’s focus and business model. A creative function for bootstrapping techniques seems to fit with the idea of social ownership of the venture development process and the focus on exploring new opportunities rather than managing perceived risks.

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Table 2.


How Bootstrapping Activities Differ Depending on Relational Embeddedness.

Type of Network Embeddedness

Bootstrapping Activity

Personal relationship

Get friends involved

Social capital

Use network to establish contacts with potential suppliers, investors, etc

Economic interaction

Convince potential suppliers, auditors etc. To provide resources and services without monetary remuneration, instead taking up residual claim in the firm (e.g. stocks, licensing deals)

Example from Cases

John of TransportSafe convinced an old tennis friend to invest the first money in the firm Steve of Alpha Clean approached the professional network and received help from Tim to hire a production consultant, whom later became the firm’s CEO Stephan of TransportSafe crane negotiated a deal with a large crane firm that would take care of marketing and sales of TransportSafe’s main product under a joint label

This extends suggestions Johannisson (2000), Sarasvathy (2001) and others by showing how informal tactics for attaining financial resources are part of the creative strategies by which ventures enact the future through the formation of an expanded network of stakeholders.

CONCLUSIONS Social networks are essential for understanding the innovative processes in new independent ventures. This study presented two cases and extracted some tentative insights about how social networks can influence the innovative processes in new independent ventures. However, one should be careful when judging the present findings in the light of the venture outcomes. Both ventures had their ups and downs and if the study had ended half a year earlier, Alpha Clean would have come across as the great success with tremendous potential for international expansion. The results should therefore be seen as elaborations of the role played by social networks in the innovation process.


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A key lesson from this study is that venture development can be facilitated by a gradually evolving coalition of stakeholders whose contributions make it possible to explore the uncertain opportunities that new ventures face. If venture ownership resides with a single individual or a homogeneous group, the venture may miss important avenues for action. By bringing more people in, more potential opportunities may be identified. However, individuals’ interests and knowledge might also constrain perspectives and possibilities for development. As a venture grows and changes it may therefore be important not only to manage the expansion of the network of stakeholders, but also to make sure that some people leave or at least stop influencing the venture. A related lesson concerns the distinction between risk and uncertainty. If a new independent venture focus on managing clearly perceived risks, it is likely to ignore vague but important opportunities. Leaders of innovative processes in new ventures would benefit from trying to promote and invest in new ideas, despite their inherent uncertainty (Matthew & Sternberg, this volume). The importance of social ownership and openness to uncertainty also help us understand the affects of bootstrapping. Obtaining support from external sources can be facilitated by socially embedded network ties, regardless of the resource needs of the venture. This means that bootstrapping is not only a reaction to economic necessities but also a creative strategy of venture development. This understanding of bootstrapping techniques provides a practical illustration of ventures as an expanding network of stakeholders (Larson & Starr, 1993; Johannisson, 2000). The cases also indicate that entrepreneurs with strongly embedded ties can leverage their venture development process by using relationship-based bootstrap techniques. This should be an important consideration for practicing entrepreneurs with a limited resource base. The role of social networks for new independent ventures can also be of interest for policy makers: Currently, much effort and resources are spent by policymakers trying to increase entrepreneurship either from society’s supply side or demand side, for example by increasing the attractiveness of entrepreneurship as a career choice or lowering the tax rate for new firms (Stevenson & Lundstro¨m, 2002). By supporting the establishment and development of professional networks, such as the one mentioned in this article, policy makers can help to facilitate contacts and exchange of ideas between innovators, entrepreneurs, financers, and other key actors in the innovation process. Specifically, policy makers who seek ways to enhance the resource base of new ventures, for instance by public innovation grants or other types of public support, need to understand that resources acquired

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through networking activities have important additional benefits. By encouraging networking, perhaps by supporting local inventor’s associations, policy makers may indirectly help the development of more sustainable ventures than does the handing out of direct support.

ACKNOWLEDGMENTS Both authors contributed equally in writing this chapter and are listed reverse alphabetically. We are grateful to Johanna Levallius and Ingela So¨lvell for helpful advice. Remaining errors are entirely our own.

REFERENCES Arrow, K. (2000). Observations on social capital. In: P. Dasgupta & I. Serageldin (Eds), Social capital: A multifaceted perspective (pp. 3–5). Washington, DC: World Bank. Bhide´, A. (1992). Bootstrapfinance: The art of start-ups. Harvard Business Review, 70, 109–117. Bhide´, A. V. (1986). Hustle as strategy. Harvard Business Review, 64, 59–65. Bird, B. (1995). Toward a theory of entrepreneurial competency. In: J. A. Katz & R. H. Brockhaus (Eds). Advances in entrepreneurship, firm emergence, and growth (Vol. 2, pp. 51–72). Greenwich, CT: JAI Press. Birley, S. (1985). The role of networks in the entrepreneurial process. Journal of Business Venturing, 1(1), 107–117. Chesbrough, H., & Rosenbloom, R. S. (2002). Role of the business model in capturing value from innovation: Evidence from Xerox corporation’s technology spin-off companies. Industrial and Corporate Change, 11(3), 529–555. Cooper, A. C., Folta, T. B., & Woo, C. (1995). Entrepreneurial information search. Journal of Business Venturing, 10, 107–120. Davidsson, P., & Honig, B. (2003). The role of social and human capital among nascent entrepreneurs. Journal of Business Venturing, 18(3), 301–331. Garud, R., Jain, S., & Phelps, C. (1998). Organization linkages and product transience: New strategic imperatives in network fields. In: J. Baum (Ed.), Advances in strategic management (Vol. 15, pp. 205–237). Greenwich, CT: JAI Press. Greene, B., & Brown, T. (1997). Resource needs and the dynamic capitalism typology. Journal of Business Venturing, 12(3), 161–173. Greve, A., & Salaff, J. (2003). Social networks and entrepreneurship. Entrepreneurship Theory and Practice, 28(1), 1–22. Hite, J. M. (2003). Patterns of multidimensionality among embedded network ties: A typology of relational embeddedness in emerging entrepreneurial firms. Strategic Organization, 1(1), 9–49. Hite, J. M. (2005). Evolutionary processes and paths of relationally embedded network ties in emerging entrepreneurial firms. Entrepreneurship Theory & Practice, 29(1), 113–144.


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Hoang, H., & Antoncic, B. (2003). Network-based research in entrepreneurship: A critical review. Journal of Business Venturing, 18(2), 165–187. Jack, S. L., & Andersen, A. R. (2002). Effects of embeddedness upon the entrepreneurial process. Journal of Business Venturing, 17(5), 467–487. Johannisson, B. (2000). Networking and entrepreneurial growth. In: D. Sexton & H. Landstro¨m (Eds), Handbook of entrepreneurship (pp. 368–386). London: Blackwell. Lane, D., Malerba, F., Maxfield, R., & Orsenigo, L. (1996). Choice and action. Journal of Evolutionary Economics, 6, 43–76. Larson, A., & Starr, J. A. (1993). A network model of organization formation. Entrepreneurship Theory & Practice, 17(2), 5–15. Matthew, C., & Sternberg, R. (this volume). Leading innovation through collaboration. Sarasvathy, S. D. (2001). Causation and effectuation: Toward a theoretical shift from economic inevitability to entrepreneurial contingency. Academy of Management Review, 26(2), 243–263. Staber, U., & Aldrich, H. E. (1995). Cross-national similarities in the personal networks of small business owners: A comparison between two regions in North America. Canadian Journal of Sociology, 20(4), 441–467. Starr, A. S., & MacMillan, I. C. (1990). Resource cooptation via social contracting: Resource acquisition strategies for new resources. Strategic Management Journal(11), 79–92. Stevenson, L., & Lundstro¨m, A. (2002). Beyond the rhetoric: Defining entrepreneurship policy and its best practice components. Stockholm: Swedish Foundation for Small Business Research. Van de Ven, A. (1986). Central problems in the management of innovation. Management Science, 32(5), 590–607. Van de Ven, A., & Engleman, R. (2004). Event- and outcome-driven explanations of entrepreneurship. Journal of Business Venturing, 19(3), 343–358. Van de Ven, A., Polley, D., Garud, R., & Venkataraman, S. (1999). The innovation journey. New York: Oxford University Press. Winborg, J., & Landstro¨m, H. (2001). Financial bootstrapping in small businesses: Examining small business managers’ resource acquisition behaviors. Journal of Business Venturing, 16, 235–254.


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CREATION OF A COLLABORATIVE ENVIRONMENT FOR INNOVATION: THE EFFECT OF A SIMULATION TOOL’S DEVELOPMENT AND USE Lina Longhitano and Stefania Testa ABSTRACT The aim of this chapter is to analyse and to define the role and opportunities offered by the adoption of a new ICT (Information and Communication Technology) tool within an organization, focusing attention on internal collaborative processes that have been induced by the development and use of the new tool. As noted by some authors, ICT tools may create a virtual meeting place where individuals can engage in dialogue and collaboration. However, other authors argue that technology could reduce direct involvement, social interaction, collaboration and reflective conversations that traditionally give rise to knowledge processes and thus to innovation processes inside the organizations. Nevertheless, some research contributions show that it is not an ICT tool itself that provides positive or negative effects on organizations, but how the tool is used in conjunction with complementary human resources. These contributions avoid technological determinism by stressing contingency and by coupling human design intent and activity with the disposition of actors inside organizations. Innovation Through Collaboration Advances in Interdisciplinary Studies of Work Teams, Volume 12, 227–253 Copyright r 2006 by Elsevier Ltd. All rights of reproduction in any form reserved ISSN: 1572-0977/doi:10.1016/S1572-0977(06)12009-9

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LINA LONGHITANO AND STEFANIA TESTA

In order to fulfil the aim of the chapter, a study was carried out in a leading firm in the automotive industry, till now involved in a project aimed at implementing a new simulation tool for the assembly process. The evidence from the case seems to suggest that the development and use of the simulation tool activated the social interactions and collaborations that enacted innovation processes. The simulation tool seemed to facilitate a productive dialogue among the different departments and a deeper understanding of the different challenges involved. The development of the simulation ‘‘forced’’ experts of different departments to meet and to keep the focus on salient aspects. The simulation acted as a boundary object. The development of this boundary object was un-intentional but it is clear that the simulation contributed to the formation of a community of collaborators. It is worth noting that this was not the result of the simulation tool itself but rather the result of management actions aimed at making sense of the whole project, supporting the initiative and thus motivating users.

INTRODUCTION As noted in literature, different organizational dimensions may affect innovation and knowledge processes (Hurley, 1995). Collaboration, broadly defined as the organizational assets that enable people to work together well (Beyerlein, Beyerlein, & Kennedy, 2005), is mentioned among the most impacting dimensions (Grant, 1996; Swan, Newell, Scarbrough, & Hislop, 1999). To understand the role of collaboration in knowledge processes, Nahapiet, Gratton, and Rocha (2005) suggest considering the underlying social processes of knowledge exchange and combination: where information and expertise are held by different people or groups, social relationship is a prerequisite for that. People are more willing to engage in social relationships in general and collaborative interactions in particular where trust is high. Trust leads to the openness, dialogue and shared experimentation that are so important for innovation (Nahapiet & Ghoshal, 1998). In literature, many effects/manifestations of collaboration have been described collaboration. 1. facilitates communication between groups and information exchange (Angle, 1989; Daft & Becker, 1978; Damanpour, 1991; Shepard, 1967) and it goes beyond: it includes ‘‘high involvement’’ (Lawler, 1992) and ‘‘high care’’ (von Krogh, 1998);

Creation of a Collaborative Environment for Innovation

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2. reduces fear and increases openness and therefore encourages risk taking (Cummings, 1965; Gibb, 1972; Pierce & Delbecq, 1977; Scott & Bruce, 1994); 3. nurtures and encourages innovative ideas (Waldman & Bass, 1991) and increases cross-fertilization (Aiken & Hage, 1971); 4. encourages employees to care about innovation for the good of the organization (Eisenberger, Fasolo, & Davis-LaMastro, 1990; Waldman & Bass, 1991); and 5. involves joint effort, shared vision, transfer of knowledge, and, according to De´tienne et al. (2005), the confrontation and combination of perspectives by means of establishing common ground, perspectives clarification and convergence mechanisms. It is worth noting that the conclusion that interaction by itself leads inexorably to improvements has been challenged by many authors (Heath & Gonzalez, 1995; Lakemond & Berggren, 2005) who underline that interaction often tends to increase not only the absorptive capacity, speed of problem solving and creativity, but also the diversity of interpretations and task disagreement and thus the risk of failure. Thus, creating the context for a collaboration that is really effective becomes a core competence for the organization. Many practitioners and academics focus on how it might be deliberately increased where desirable but not occurring naturally (Windsor, 2003), but it is all too clear from practice, and the literature being generated about it, that what it means to work collaboratively is not something that can be reduced to a formula. Nevertheless, some authors argue that collaboration is seldom developed in a deliberate and systematic way but rather it is an incidental outcome of formal and informal changes in organizational systems, practices, design, learning and culture. In this context (i.e., in inducing changes in human practices and organizational systems), artifacts play an important role (Miettinen & Virkkunen, 2005) and the introduction of new technological artifacts (Barley, 1986) can re-define institutionalized roles and patterns of interaction. New technologies can in this way ‘‘disturb’’ consolidated patterns of behaviours and cause them to change. So the question is not ‘‘what kind of technologies foster and enable collaboration?’’ but ‘‘what is the role of any technology in fostering and enabling collaboration?’’ The literature contributions on this topic can be classified into two main streams: the first stream considers ICT (Information and Communication Technology) tools enhancing the quality of social interactions and the second one considers ICT tools inhibiting the quality of social interactions. According to the first stream, Stenmark (2002) argues that information technologies may

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create a virtual meeting place where individuals can engage in improved dialogue and collaboration, and Knorr-Cetina and Bruegger (2001) suggest that the use of information technology allows the creation of ‘‘forums of exteriorizing processes and activities.’’ According to the second stream, Rorty (1979) and Gill (1995) argue that technology could reduce direct involvement, social interaction, collaboration and reflective conversations that traditionally give rise to innovation processes inside the organizations. Nevertheless, some research contributions show that it is not an ICT tool itself that provides positive or negative effects on organizations, but how the tool is used in conjunction with complementary human resources (Massa & Testa, 2004; Orlikowski, 1992). These contributions avoid technological determinism by stressing contingency and by coupling human design intent and activity with the disposition of actors inside organizations (Henfridsson & Soderholm, 2000) and focus on the emergent use of technology. Considering that organizations adopt more and more pervasive and complex technologies, researchers and practitioners call for new studies aimed at investigating the interaction with these advanced technologies (Gillan & Cooke, 2003). The aim of this chapter is thus to analyse and define the role and the opportunities offered by the adoption of a new ICT tool within an organization, focusing on internal collaborative processes that have been induced by the development and use of the new tool and their impact on innovation processes. In order to add new empirical data into the phenomenon, a twoyear grounded research study has been carried out in a leading firm in the automotive industry, which until now has been involved in a project aimed at implementing a new simulation tool. Nowadays, simulation techniques have reached a state where considerable empirical data, in relation to performance gains, have been collected and analysed even though some authors (Thomke, 1998) argue that the evidence is mostly anecdotal and thus ask for further research mainly for investigating effects from a broader perspective. This chapter will be organized as follows: the methodological issues will be detailed in the next section. Then, the research setting will be introduced. The empirical evidence will be described and discussed in another section. The last section will suggest some conclusions.

RESEARCH METHODOLOGY In order to target our research aim, we adopted a qualitative approach, namely grounded theory (Glaser & Strauss, 1967), because, as noted by some authors (Blackler, 1995; Miner & Mezias, 1996), qualitative approaches are

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the most appropriate ones in order to deeply investigate social dynamics. The qualitative analysis allows the researchers to better understand the context; it is consistent with the sociology of technology perspective, in which innovation is not simply a technical-rational process of ‘‘solving problems,’’ but it also involves social processes in articulating interests, building alliances and struggling over outcomes. As regards data collection, data were primarily obtained by using semistructured in-depth interviews supported by documentation and observation, as well as by means of the direct participation in the simulation project of one of the co-authors. Our aim is to put our experience from practice into a form that makes sense also to the broader audience, as suggested in (Heiskanen & Newman, 1997). The use of multi-method approaches, designed to compensate for any singlemethod’s weaknesses, was thought to be particularly useful in terms of increasing the richness of the data and constructing the ‘‘full picture’’ of the organization’s simulation tool development and use. The study thus incorporates Kanter’s (1977) suggestion that different sources of data have to be used to validate each other. We sought to improve our research by studying the organization for a considerable length of time (25 months) and collecting data from many informants representing different levels (see Table 1), also including several external participants (suppliers of the company under investigation). Table 1. Department

Research Informants. No. of Interviews

CAD/CAM-supporting Design Production planning

1 1 5

Product creation

4

Engineering

9

Suppliers Liaison with the production plant

2 2

Position 1 1 1 1 1 1 1 2 2 4 2 1 1 1 2 1 1

manager manager employee manager senior manager vice president president employees managers employees managers senior manager vice president president employees manager senior manager

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The interviews lasted from one to two hours. Whenever possible, group discussions, where informants representing different hierarchical levels or departments argued with each other, followed the individual interviews, and every effort was made to transcribe interview and observation notes verbatim as soon as possible. Data collection focused on the technology itself (implementation strategy and schedule), the context in which it was developed, the rationale for the tool implementation, key players involved, managerial commitment, individual and group experiences in the implementation process as well as changes associated with the simulation tool in terms of knowledge processes, work changes, interactions among participants and required skills. As regards induced changes, in this paper we will mainly focus on those related to the interactions among participants. In order to assist readers in identifying potential commonalities with other organizations we are going to include detailed description of the research setting and each research finding will be supported using citations from informants themselves. As regards data analysis, it consisted of different stages. In the beginning, interviews were more open-ended and later directed by the emerging issues, after a review of the data that were gradually available. Then a stage of coding, conceptualization and ordering (Stern, 1994) followed. This was the phase we made our attempts to introduce our own interpretation and understand what was actually happening within the simulation project. As the data analysis process began to yield a number of themes, concepts and relationships, we started to compare these with the extant literature that facilitated an understanding of how to conceptualize and integrate the data (Creswell, 1998). During the research process, the theoretical basis about effects/manifestations of collaboration described in the introduction section was used in order to be able to search for, and recognize meanings in the data (Orlikowski, 1993; Scott, 1998). Through open coding we identified several general categories: creating trust, fostering commitment, cross-fertilization of ideas, joint effort, shared vision and values, transfer of knowledge, reciprocity, mutual benefit, etc. (for the full list of categories, see the third column of Table 2) Research Setting The research setting is the Mercedes Car Group (MCG) division of DaimlerChrysler (DC) whose brands range from passenger cars (Maybach, Mercedes-Benz, Chrysler, Jeeps, Dodge and smart) to commercial vehicles

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Table 2.

Result of Content Analysis and Sample Comments.

Sample Comments

‘‘When I saw the simulation of the assembly parts without jigs and our simulation expert informed us about the possibility to integrate the jigs in it, I was really interested and I recognized the potential of this new simulation method for our project, especially during the design release and the buy-off, and decided to support it’’ ‘‘The possibility to see the simulations and discuss directly the open issues with our customer DC helped us to better understand their needs and to react to their changes quickly’’ ‘‘Before these meetings I was very skeptical about this new simulation, I’ve been working in this field for twenty years and I could not believe a digital process could help our work in the workshop. Now I changed my mind and I cannot figure a buy-off without digital supporting!’’ ‘‘I decided to support the developing of this project because I realized that the simulation team wanted to understand and solve the problems related to the development and manufacturing of the jigs’’ ‘‘I extracted and explained the structure and the components of the jigs to the simulation experts in order to made the simulation possible’’ ‘‘The process’s knowledge created during the meetings was spread among all participants by means of a manual that also codified technical details of the simulation tool and that was loaded on the intranet’’ ‘‘Videos have been helpful for training. None of my team members had ever participated in an activity such as prototyping. The videos made them familiar with the process before ever travelling to Germany’’ ‘‘After having collected feedback from digital buyoff workshops, we (the simulation team members) improved the simulation method and the process. We also noticed that all the participants understood what could be reached by means of the new tool and how to interpret and communicate inside the company the structured results and documentation generated by the process’’

Semantic Relationship

Categories

Is a kind of

Cross fertilization

Is a kind of

Cross fertilization

Is a kind of

Increased openness and shared vision

Is a kind of

Increased trust

Is a way of

Transferring knowledge

Is a way of


Is a way of


Is a kind of

Convergence mechanism

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Table 2. (Continued ) Sample Comments

‘‘The supplier discovered relevant process-related knowledge useful for simplifying its working activities as well as for improving the communication with DC, increasing speed and quality thereby reducing misunderstanding and failures in the supplied products’’ ‘‘When I was back at my company after the digital buy-off and the real buy-off, it was evident to me I had to optimize our internal processes to get better integrated into our customer processes’’ ‘‘After three months, all the results were collected and presented to management in a meeting with all the project’s participants. The presentation of the positive results reached by the project convinced one of the managers of the Engineering Department to finance the adoption of the simulation for two other car lines that he was responsible for’’ ‘‘Knowing that the simulation team had controlled the functionality of the assembly line gave me security.’’ ‘‘It was clear to me that the digital process wasn’t introduced to reduce employees, but to support us in our daily activities’’ ‘‘As a project leader, together with the person responsible for the jigs and the person responsible for the simulation, I created and promoted the project among the suppliers and colleagues, often working directly at the workshop’’ ‘‘During the digital workshop in the VRC (Virtual Reality Center), I could use my experience and give my colleagues important information about how things are going on in the assembly line. In return I got a lot of interesting hints about issues in the digital world’’ ‘‘The close collaboration between the Development and Engineering division (EP) and the Production Planning (PP) division determined the reduction of the buy-off time (i.e., an advantage for PP), a higher quality of the prototypes (i.e., an advantage for both EP and PP) as well as a cost reduction due to parts changes (i.e., an advantage for EP)’’


Categories

Is a way of

Facilitating communication between groups

Is a way of

Nurturing innovative ideas

Is a way of

Fostering commitment

Is a kind of

Reduced fear

Is a kind of

Joint effort

Is a kind of

Importance given to reciprocity and facilitated information exchange

Is a kind of

Awareness of mutual benefit

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Table 2. (Continued ) Sample Comments


Categories

‘‘Several departments co-operated in order to develop the project: the Advanced Engineering department the CAD/CAM Support and Methods department, the Design department, the Pre-series department, the Production Planning department, the Product Creation and Engineering department and the department responsible for the liaison with the production plant. These departments were not used to communicating between themselves so often’’ ‘‘At the beginning I thought that this was a tool which could be used only by specialized people, now I have to admit that every workshop team member could use it and reach a better qualification and improve work quality without many efforts’’ ‘‘At the beginning of the project we dedicated extra time at participating to meetings in order to give our feedbacks and our ‘‘workshop’’ experience in an early phase, when project’s benefits were not yet clear to all’’ ‘‘It was very useful that we had the simulation and visualisation (in CAD as well as video format) of the assembly line. It helped the communication and reduced misunderstandings’’

Is a kind of

Increased communication between groups

Is a kind of

Reduced fear and increased openness

Is a kind of

High involvement and high care

Is a way of

‘‘Being in the workshop during a real buy-off and having the possibility to speak with the project leader as well as with the jigs experts and suppliers was essential to better understand the real process, and thus to build the digital one.’’ ‘‘We noticed that the use of the simulation and the creation of videos gave a big input to the spread of information between departments. This is an important issue especially in a big company where information can be used strategically. All this brought new transparency to the project for all the participants’’ ‘‘As the number of experts sharing the ‘‘simulation knowledge’’ increased, it was possible to optimize the process for all the car lines. We, the simulation team members, started to work at these new projects’’

Is a way of

Establishing a shared syntax and language for individuals to represent their knowledge Facilitating a process where individuals can jointly transform their knowledge Facilitating information exchange

Is a way of

Is a way of

Nurturing the innovation process

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(Mercedes-Benz, Freightliner, Sterling, Western Star, Setra and Mitsubishi Fuso) as well as to financial services brands. The case study is focused on a project aimed at implementing a new simulation tool for supporting the development of car lines during engineering and the pre-series phase. The aims of the project were to try to overcome the organizational barriers that impeded integration and to test what the full potential of simulation could be. The project started with the formation of a team from following departments: the Advanced Engineering department (responsible for the tolerance, clamping and locator concept), the CAD/CAM (Computer Aided Design/Computer Aided Manufacturing) Support and Methods department, the Design department, the Pre-series department and the Production Planning department, the Product Creation and Engineering department and the department responsible for the Liaison with the production plant. It is important to emphasize that the main part of the project was settled in Germany, in the Development & Engineering as well as in the Production Planning departments. Another part of the project was settled in the Tuscaloosa plant (Alabama, USA), where cars had to be manufactured. For this reason, most results (i.e., the videos of the assembly processes or the information about possible problems of the jigs) were very helpful also in USA, especially from the pilot team members, who are responsible for building the first cars and to train the workers of the plant. In the past, they could participate to the hardware process and the team members had to travel to Germany to learn the assembly sequence. At MCG, diversified types of simulations (e.g., crash simulation) are developed and used. For the engineering department, which is responsible for the building of the prototypes, a new assembly simulation was developed and officially introduced in the car development process in 2000. The first phase of the building of a car consists of the welding together of the metal sheets which are parts of the Body in White (BIW) (i.e., the metal body structure of the vehicle) of a car. A car is assembled at different stations in the so-called assembly line, starting with small parts and ending with large ones, e.g., the painting. The basic idea was to use the CAD-tool, which was available on every workstation in the development and engineering departments of MCG, to develop and implement this assembly simulation (see Fig. 1). This tool was a big help for the designer, but it could confirm just a part of the process, because in the real assembly, the metal sheets are welded together in several jigs with variable complexity. In 2003, the introduction of the new version of the tool, which has some new features, made simulation of more complex assembly lines possible and also provided a new perspective.


Fig. 1.

Fig. 2.

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Simulations with and without Jigs.

The Old and the New Process for Jig Design.

Before the adoption of the simulation of the assembly line with jigs, the design process of the jigs (see Fig. 2) were articulated in two main phases: a concept phase and a hardware phase. In the first phase, engineers, body shop technicians, and clamping and locator specialists discussed the concept and the design of the jigs by analysing CAD data. In the second phase, after the design release, the jigs were manufactured and for the first time the whole process of the assembly (i.e., loading the part in the jigs and closing the jigs) was tested. This is the reason why some problems were discovered

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only during the buy-off at the suppliers’ workshops. This did cause delays because concepts had to be changed before the jigs could be sent to the body shop, where the BIW had to be built. The repair solutions applied in the workshops were sometimes less than optimal. Thus, the person responsible for the digital reference process together with the person responsible for the jigs decided to support the introduction of a new digital process in order to confirm the process digitally in an early phase and, consequently, get an improvement of the process as well as of the product. In the new process, the simulation was integrated into several steps. After the concept revision and before the design release, a design check was introduced. The simulations were made and used until the buy-off at the suppliers. A documentation of the working instruction, in the form of a video, was made for the project participants. About two months before the start of the design of the jigs, the single assembly parts of a car were put together digitally in several assembly stations in order to obtain the complete BIW of the car. With this assembly simulation, it is possible to analyse the fitting of the assembly parts to each other. The parts were digitally assembled in order to avoid interferences between the parts and in order to discover construction problems in an earlier stage of the development. In the plant body shop, the shipping units were loaded onto the jigs. Therefore, it was important to have a realistic representation and simulation of the assembly line. In this simulation it was possible to control not only the interferences between assembly parts, but also between assembly parts and jigs in order to confirm or modify the jigs before their manufacture. It was important to solve these problems and errors before the production of the parts and jigs. Improvements of the jigs and, consequently, a higher quality of the BIW could be reached. This kind of assembly simulation was, at that time, not integrated to the extent that it could take full advantage of simulation technologies. The process for digital buy-off of the jigs consists of several sub-processes: Commission/Assignment, Creation of the simulations, Workshop for work instructions, Verify the collision, Creation and tracking of open issues, Support during the buy-off at the supplier’s workshop, Changes after the buy-off, Documentation of the simulation. Commission/Assignment. The project leader of the jigs together with the project leader of the digital buy-off plans the number of jigs to be simulated and the schedule as well as the resources for the project. The specification for the digital buy-off is integrated into the contract for the supplier. They have to provide the data in a new format and structure.


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Creation of the simulations. Each station of the BIW assembly can be simulated. A simulation consists of digital data of assembly parts and of the jigs corresponding to a single station. The sequence of the assembly is based on the work instructions. Workshop for work instructions. After the simulations are completed, workshops with several team members are organized in the Virtual Reality Centre (VRC is a facility at the Mercedes Technology Centre where it is possible to create a three-dimensional immersive environment on a big screen), in order to discuss the simulated assembly process. Car and jig designers, suppliers, the staff responsible for the clamping and locator concept, colleagues from the body shop as well as from the production planning department can see and modify all the elements seven weeks before they will be manufactured. The introduction of these workshops was very important, because all the employees involved in the project got the information about the current issues as well as the assembly process. During the meetings, they could discuss, insert changes and verify those changes. Bringing together different employees and allowing them to give their inputs and ideas improved the process and gave an incentive to the deployment of the tool itself, because all the project participants gave their suggestions in order to be able to optimally use the tool in their departments. The person responsible for the production planning reported: During the meetings we analysed the simulations of the assembly line and I could explain the important issues for us to the simulation team. The colleagues of the other departments did the same from their perspectives. Finally the tool could be developed so that everybody could receive a benefit from it.

Verify the collision. In the simulation the assembly is digitally confirmed. The visualization of the assembly line and the collision checks during the simulations allowed the experts to discover possible errors in the design and realize improvement. All these types of errors were also found in the old process but normally only during the buy-off of the jigs at the suppliers. Every change in this phase is expensive and time critical. Creation and tracking of open issues. The open issues are documented and linked together in a complete list, where it is possible to track the entire process. These files are sent to the suppliers and as well as to experts, that is those who are responsible for the body shop, for the clamping and locator concept, and so on. Support during the buy-off at the supplier’s workshop. The jigs are also verified in the hardware. In this phase, the simulation can support a buy-off

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of the jigs at the suppliers, especially if the car parts are not available. The assembly simulation of the car parts can be shown on the monitor of a portable computer. Experts can use the simulations to compare the real jigs with the digital one, make measurements and check possible interferences. The open issues of the digital buy-off are controlled. Changes after the buy-off. After the buy-off, other possible improvements to the hardware can be done and they are reported also into the simulations. Documentation of the simulation. For every simulation, corresponding to an assembly station, a video in a standard format is created. This is a new kind of documentation, which can be used for training, for the production, for the suppliers or for comparison between different car lines. These videos can be shown on every computer.

EMPIRICAL FINDINGS Empirical evidence seems to suggest that a link between a simulation tool and the creation of a collaborative environment inside an organization may exist. The simulation tool development will be described in this session, following the coding paradigm suggested by Strauss and Corbin (1990): conditions, context, action strategies and consequences. Causal Conditions for Developing and Using the New Simulation Tool Initially, a vice president of the engineering department created a team with the task to simulate the assembly of the car in an early phase. One of his main objects was to establish an interface between the engineering and the production planning departments. The senior manager responsible for prototypes and pre-series established a digital reference process with the goal to control all the processes. These aspects were fundamental for the setting of the simulation process without jigs. The simulation expert was invited to support the buy-off at the suppliers. This was an important step, which brought all the technical staff together. During this visit they had more time to discuss about the possibilities of this kind of simulation and they started to develop this new idea. The simulation expert stated, Being in the workshop during a real buy-off and having the possibility to speak with the project leader as well as with the jigs experts and suppliers was essential to better understand the real process, and thus to build the digital one.

A new, rich collaboration between people working in the digital world with people working in the workshop started. The simulation expert together


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with the project leader of the development of the jigs and the expert of the jigs and of the clamping process, influenced by the environmental, organizational and Information System contexts, identified and articulated the following points: (a) the integration of the new process into the old one, (b) the definition of the data requirements and (c) the simulation method and the integration of the supplier. The goal was to reach a highly optimized process with key focus into the quality of the prototypes, the adherence to delivery dates and process reliability. They thus chose to launch the simulation project with the aim of covering those emerging points. The Context As regards the environmental context, DC is faced both with new challenges and opportunities as it strives to compete. These include serving new markets, enriching relationships, constantly innovating and making continuous improvements for enhancing the quality of processes, mainly realizing faster new product introduction. This last goal could be reached by using simulation tools whose benefits in terms of efficiency gains are particularly significant in a context, like that of automotive industry, where the introduction of a new car takes millions of engineering hours and lasts many months, with a high degree of variation in prototype models (Clark & Fujimoto, 1998). As regards the organizational context, DC is interested in decreasing the costs of the whole production process, with a focus on the new product development process. More precisely, it aims at developing solutions to digitally confirm the assembly line of the BIW about two months before the jigs are completed, learning from a simulation-driven, cross-disciplinary approach to advanced development and increasing and leveraging the developers’ knowledge on prototyping processes. As regards the ICT context, there is a centralized department responsible for all CAD/CAM Application Support and Method. It is important to underline, that at MCG/D (Mercedes Car Group, Development & Engineering), there is a central division responsible of the IT strategy for all the car line’s division, but every car line project has a Cax-Team (CAx: Computer Aided everything, i.e., CAD, CAM, CAQ, etc.; a CAx-Team is responsible for all the CAx Processes of a car line) which is able to start pilot projects in agreements with other teams. At the beginning of the project, the pilot simulation expert team was in one of these CAx-Teams and was responsible for the simulations in one business unit/department, that is for a car lines project. At MCG/D, many types of 3D, 2D, 1D simulation are implemented and used (like crash, flow computing, etc.).

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The Development and Use of the Simulation Tool Resistance to change is a classical problem in the introduction of a new ICT tool inside an organization. People involved in the change primarily fear power relationship modifications (Dhillon, 2004). Some groups perceive they have more to lose than other groups. For this reason, the first issue was to sign an agreement with other departments in different business units, which were involved in the digital process. It was important to establish the project without entering their core competences. This was not self-evident because of the innovative, interdisciplinary as well as inter-organizational aspects of the project. After some initial resistances and several coordination meetings, the new project was accepted and officially integrated in the digital development system of the MCG. The project met with general acceptance from all the project members. This was not easy because employees, especially from the workshop, were not used to working with these new technologies; they just worked with physical parts, which they could really touch (the hardware). They were afraid not to be able to face these technological changes and they were concerned about losing their jobs. At first, most workshop team members thought this digital process was not at all useful to them. The big burst out was activated by the participation of the simulation expert at the real buyoff, which showed the similarity between the digital and the real world and helped to understand which use a workshop worker could make of the simulation. It is important to underline that there was a previous project for another car line, whose goal was the assembly simulation of the metal sheets (without jigs). This was developed using the current CAD Platform. A colleague of the CAD Support department convinced the person responsible for the simulation, to start the pilot project by using the new version of the CAD tool in use. This was a fundamental issue, because only with these new functionalities (i.e., the moving of several parts with different tracks simultaneously) it was possible to integrate and simulate the jigs. Consequences of Developing and Using the Simulation Tool Because this study in DC was a part of a larger research project, all the data collected from interviews, observation and documentation were examined and coded by focusing only on the collaboration aspects associated with the simulation tool. In the beginning, the simulation project acted as a power relations breaker. Project participants showed conflicting views of the value


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of the simulation and different acceptance of the tool. They were faced with conflicting loyalties, power map relationships, constraints and requirements. Most of the participants of this project knew the assembly simulation of the sheet metals without jigs. A process innovation as well as the introduction of a new ICT-Tool in such a big company is completely successful only when it is accepted by the project members of all car lines. An interesting aspect is that every CAx-Team of a car line project had the task of introducing process and technical innovation into its projects. This was an important function, because the integration of the jigs into the simulation gave the project a peculiar aspect. On one hand, it rendered the simulation more complete and similar to the real project in hardware. On the other hand, those employees, who were more oriented towards high technologies, gave their support with much more enthusiasm because of this innovative aspect. There was the conservative group who said, ‘‘We’ve always done it like this, why should we change it now?’’ There were also the employees, who were afraid of losing their jobs: ‘‘If we use this tool, may be we’ll be faster and in the future they won’t need so many people for the building of the cars in the workshop and they will post us and then employ people specialized in CAD.’’ On the other side there was the team responsible for the optimization of the digital processes: ‘‘We knew we were going in the right direction, we had just to convince our colleagues of the advantages.’’ There were also the ones traditionally working without digital tools, who recognized that they themselves could learn to make their decisions in an early phase by using this tool: ‘‘It was important that I used my experience in the real world by making decisions in the digital phase. It was clear to me that the digital process wasn’t introduced to reduce employees, but to support us in our day’s work.’’ Only after several meetings could all the employees take part in the realization of the project, the simulation development, and use the tool to span boundaries in between departments and to foster commitment as well as to translate knowledge and focus attention on important issues. The recurrent meetings about the simulation tool allowed the creation of a shared vision, the development of trust as well as the encouragement of a joint effort of individuals from diverse backgrounds and with different perspectives. Because of this new disposition of actors involved in the meetings, new challenges were discussed, allowing cross-fertilization of ideas. As an example, the colleagues of Production Planning and of Advanced Engineering recognized the necessity of integrating the jigs in the simulation. The intuition of an employee, who brought the idea of using the CAD-tool to simulate the car assembly with the jigs, communicated this new method to

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the other meetings participants. The person responsible for the jigs development reported, When I saw the simulation of the assembly parts without jigs and our simulation expert informed us about the possibility of integrating the jigs in it, I was really interested and I recognized the potential of this new simulation method for our project, especially during the design release and the buy-off, and decided to support it.

The management supported this project from the beginning by creating a situation of mutual understanding and trust between the different departments and employees involved in the project, and by facilitating knowledge sharing and innovation deployment. The final idea that emerged from brainstorming meetings was then translated into the new simulation tool and the related technical reports. All the departments involved shared their technical knowledge. An employee of the Advanced Engineering department, with years of experience in this field extracted and explained the structure and the components of the jigs to the simulation experts. He discussed with them which kind of problems he expected to be solved by the simulation. He reported, I decided to support the developing of this project because I realized that the simulation team wanted to understand and solve our problems during the developing and manufacturing of the jigs. It was a great challenge for us, we had no ‘off-the-shelf’ solutions, and a new process inside the company and with the supplier had to be built.

This awareness of reciprocity and mutual benefit played an important role in the project and took repeated time-consuming interactions among participants. After several meetings, one of the participants, an expert of jigs, emphasized, Before these meetings I was very skeptical about this new simulation. I’ve been working in this field for twenty years and I could not believe a digital process could help our work in the workshop. Now I changed my mind and I cannot figure a buy-off without digital support!

The use of the simulations in the process followed. The explicit knowledge was transferred and shared among all participants by means of a manual that codified technical details of this simulation tool and that was loaded on the intranet. In this phase, the jigs supplier was also integrated in the process. His role was to prepare the data for the simulations in the required form, thus the simulation team knowledge was coupled with external contributions introduced by the supplier. After testing, the open issues were communicated to the company experts as well as to the supplier, who were responsible for solving the problems that emerged. In the Virtual Reality Centre, a series of workshops, called ‘‘digital buy-off,’’ were organized by


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the simulation team. The simulations and the open issues were presented to all the participants in the project. A supplier reported, ‘‘The possibility of seeing the simulations and discussing directly the open issues with our customers helped us to better understand their needs and to react to their changes quickly.’’ An expert of the jigs reported, ‘‘It gave me security to know that the simulation team had controlled the functionality of the assembly line.’’ Another important aspect of this phase was the participation of the simulation team members to the traditional buy-off at the suppliers’ workshop. This was very important because it helped the workshop team members to better identify and understand problems as well as show the design data in comparison to the real jigs. But most important of all, they could show that their digital world corresponded to the real one, validating their results and building a solid basis for the next processes. A workshop technician reported, The first day I saw this CAD tool with the simulations in the workshop, I could hardly believe that it could help me. But I spent some time trying to compare the digital world with the real one and I realized that it fit quite well, and I could use the simulation to better understand and solve the manufacturing problem encountered during the buy-off.

After the buy-off, all the simulations were documented with videos, which were called digital working instructions. The use of the simulation and the creation of videos gave a big input to the spread of information among departments. This is an important issue especially in a big company where information can be used strategically. It brought new transparency in the project to all the participants. For this project, transparency was very important because the development and engineering departments were in Germany and the production plant in USA (Tuscaloosa, Alabama). Spatial, cultural and language barriers prevented collaboration. The introduction of the simulation and their videos sustained the knowledge exchange as well as a better understanding by improving the collaboration among the engineering department, the production planning and the plant. As the person responsible for training the pilot team members of Tuscaloosa reported, For me the videos were helpful as a training aid. None of the team members had ever participated in an activity such as prototyping. The videos made them familiar with the process before ever travelling to Germany. After beginning the activities, if there were questions regarding assembly sequences, we could refer back to the videos if needed. Personally, I think that the Digital reference process and the videos can be a great help before ever beginning to build cars in hardware. Many of the issues that were seen in hardware could be found before ever starting to build cars if the designs are available early enough. I still believe that the advantages of the Digital Process are tremendous.

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After collecting feedbacks that emerged from digital buy-off workshops, the simulation team improved the simulation method and the process. All the participants understood what could be reached with the new tool and how to interpret and communicate inside the company structured results and documentation generated by the process. The contextualization of knowledge took place at the supplier side, too. Contextualization is a process that results from the internalization of external stimuli and from integrating newly acquired knowledge with the previously existing one (Nonaka & Takeuchi, 1995). The supplier discovered relevant process-related knowledge useful for simplifying its working activities as well as for improving the communication with DC, increasing speed and quality, thereby reducing misunderstanding and failures in the supplied products. In fact, one of the suppliers underlines, When I was back at my company after the digital buy-off and the real buy-off, it was evident to me I had to optimize our internal processes to get better integrated into our customer processes. I realized we needed to modify our internal workflow because it was the first time we had to provide the CAD data during the design phase. In order to improve the teamwork, we dedicated an employee to act as an interface to the project Digital Buy-off.

After three months, all the results were collected and presented to the management in a meeting with all the project’s participants. The presentation of the positive results reached by the project convinced one of the managers of the Engineering Department to finance the adoption of the simulation for two other car lines that he was responsible for. The person responsible for the project under examination gained the lead of the coordination of the project for all the actual car lines and was asked to work for a certain period of time at the engineering department in order to foster the sharing of experiences and a learning-by-doing process. As the number of experts sharing the ‘‘simulation knowledge’’ increased, it was possible to optimize the process for all the car lines. The simulation team members started to work at these new projects. Experts found solutions on how to use the simulation tool for all the car lines.

SUMMARIZING The simulation project contributed to the creation of common space supporting collaboration among various organizational units. It allowed a number of benefits, including: (a) cutting across organizational boundaries of geography (e.g., the case of Tuscaloosa in the USA) and departments


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(advanced engineering, CAD/CAM support and methods, design, pre-series, production planning, product creation and engineering, liaison with the production plant, as well as some supplier’s departments); (b) tapping and pooling expertise of individuals (as an example, an employee of the Advanced Engineering Department, with years of experience in this field, extracted and explained the structure and the components of the jigs to the simulation experts); and (c) supporting the awareness of others in the organization and their availability for collaborative action (e.g., in the words of one interviewee of the Advanced Engineering Department: ‘‘I decided to support this project, because I realized that the simulation team wanted to understand and solve the problems related to the development and manufacturing of the jigs’’). The simulation facilitated interpersonal networks (e.g., between the simulation project manager and the members responsible at the Tuscaloosa plant) and person-to-person knowledge exchange (e.g., the case of the employee of the CAD/CAM support and methods department that suggested the simulation project manager start the pilot project by using a new version of software whose functionalities allowed integrating and simulating the jigs). The main categories and concept related to the different collaboration manifestations that were enacted during the development and use of the simulation tool are summarized in Table 2. Column 1 includes sample comments obtained from interviews; column 2 describes the semantic relationship between the collected data and the labels/categories of phenomena (effects/manifestations of collaboration), described in column 3. The products of labeling and categorizing are the basic building blocks in grounded theory construction that allow us to draw the following conclusions.

CONCLUSIONS In the ICT literature, simulation tools have been essentially considered as tools able to store large amounts of data and information both for representing the real world on a computer and for storing the results of the thing being simulated. Many contributions appear to neglect the social worlds coping with ICT tools and, as Kakola (1995) argues, organizations have often insufficient knowledge about the role of ICT as a structural property mediating communication, collaboration and control in the articulation of work processes. The evidence from the presented case seems to add new insights into the phenomenon, referring to a large amount of company data. The simulation

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development and subsequent adoption activated enriched social processes that turned to collaboration. The simulation project contributed to the creation of a cross-functional team that, as already noted in literature (see, e.g., Lakemond & Berggren, 2005), often tends to increase not only the absorptive capacity, speed of problem solving and creativity, but also the diversity of interpretations and task disagreement and thus the risk of failure. In this case, on the contrary, the simulation tool improved the quality of interaction, helping to handle the diversity within the team in a way that enhanced team members’ freedom of expression and propensity to interact in a collaborative rather than in a contentious way. It is important to focus here on the concept of quality of the interaction because, as noted by Lovelace, Shapiro and Weingart (2001), and Patrashkova and McComb (2004) most studies hereto had focused just on the increase of the quantity of interactions in cross-functional teams, a direction which had yielded inconclusive results. The simulation provided a shared representational format, on which to communicate and contributed to building a common jargon as well as establishing a common ground in which actors involved mutually established what they knew so that activities could proceed (Clark & Brennan, 1991). The simulation was developed despite different viewpoints, local contingencies and interests that were temporarily reconciled in the implementation of the tool. In our opinion, these findings pose interesting challenges to researchers, because they describe fostered collaborative processes that would not have been there but for that project and tool. People from different departments used the simulation as a point of reference for conversation. The simulation served to bring different communities of practice (Brown & Duguid, 1991) together to co-operate. Developing the simulation was at once an ongoing conversation and an intensely practical activity. As reported by one interviewee: We were often organizing meetings in order to present our work in progress. In this way, we could take problems and goals of others into account in ours and vice versa. We needed to talk and collaborate to get the job done, and later to stop talking and to come back working!

The simulation tool seemed to facilitate a productive dialogue among the different departments and a deeper understanding of the different challenges involved. The development of the simulation ‘‘forced’’ experts of different departments to meet and to keep the focus on salient aspects and acted as a ‘‘focusing device.’’


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The coding we performed shows that the simulation acted as a boundary object. The concept was first introduced by Star and colleagues (Star, 1989; Star & Griesemer, 1989). Boundary objects are objects that work to establish a shared context that ‘‘sits in the middle’’ (Star, 1989, p. 46–47, emphasis in original), establishing a shared syntax or language for individuals to represent their knowledge, providing a concrete means for individuals to specify and learn about their differences and dependencies across a given boundary, facilitating a process where individuals can jointly transform their knowledge (Carlile, 2001). They are flexible enough for local needs and robust enough to maintain identity across boundaries. It is around boundary objects that communities of practice often gather. The development of this boundary object was un-intentional, but it is clear that the simulation contributed to the formation of a community of collaborators. This further confirms that the construction of boundary objects is strictly related to the characteristics of the participating actors (Boland & Tenkasi, 1995). The content analysis shows that the simulation also acted as a ‘‘white box’’ (Kakola, 1995) that is an application that is transparent (white) to the user instead of burying knowledge within an inaccessible (black) box. In fact, the need to create the process in the virtual reality pushed participants to rethink the assembly process and formalize it in an explicit form. Everyone can see how the whole process is working even though he/she is not directly involved in all phases. It is worth noting that collaboration was not the result of the simulation tool itself, but rather the result of management actions aimed at making sense of the whole project, supporting the initiative and thus motivating users. In fact, as noted by Brown and Duguid (1996), inter-communal documents (or artifacts) can both promote and retard institutional development, depending on whether boundary objects lead to control or collaboration (e.g., in this case, the increased collaboration between DC and the jigs supplier). Nevertheless, what emerged from the study confirms that the diffusion of technology inside organizations is emergent (Mark & Poltrock, 2004) rather than a rational, top-down, well-planned process. The simulation tool was adopted across the organization also in the absence of a top management mandate in the very beginning. In fact, the introduction of the idea was triggered by the suggestion of three employees (and not topdown directed), and it was feasible because of the individual autonomy that motivates employees inside DC (Nonaka & Takeuchi, 1995). Understanding the ongoing process of the simulation development and use has implications for addressing the issues of collaboration, highlighting how participants co-ordinated their work and efforts as well as how they

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chose to collaborate without any top management mandate, sometimes under the constraints of their social and work context. To conclude, the result of our research seems to confirm what recent literature argues about the role of collaboration in creativity and innovation (see Harrison, Price, Gavin, & Florey, 2002, for a summary). Studies in this area have examined the dynamics of groups, and there is a general consensus that diversity rather than conformity are more likely to produce novelty and quality (De Dreu & West, 2001; Nemeth, 1986; Nemeth & Nemeth-Brown, 2003) even though some authors (Carbonell & Rodriguez, 2006) warn against too highly diverse teams and speak about an inverted curvilinear U-shaped function in describing the relationship between innovation and diversity. According to them, a too big diversity can make it very difficult to create a shared vision and value set, so moderate diversity is preferred. It has to be seen if an emergent boundary object as the one above described and/or professional facilitators could overcome the problem.

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BUILDING COLLABORATIVE CAPACITY: AN INNOVATIVE STRATEGY FOR HOMELAND SECURITY PREPAREDNESS Susan Page Hocevar, Gail Fann Thomas and Erik Jansen ABSTRACT Recent events such as the terrorist attacks of September 11, 2001 against the United States and the national disaster of Hurricane Katrina demonstrated the acute need for interagency collaboration. Using a semi-inductive method, we conducted two studies with senior homeland security leaders to learn more about organizations’ collaborative capacity during the early planning stages. In study One, we used an interorganizational systems perspective to identify factors that create or deter effective collaboration. Study Two elicited vignettes from a second group of senior homeland security leaders to gain further insights into the ways in which their organizations are successfully building collaborative capacity. While accounts of 9/11 are filled with examples of heroism and valor, reports also reveal that communication, coordination, and command failures Innovation Through Collaboration Advances in Interdisciplinary Studies of Work Teams, Volume 12, 255–274 Copyright r 2006 by Elsevier Ltd. All rights of reproduction in any form reserved ISSN: 1572-0977/doi:10.1016/S1572-0977(06)12010-5

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cost hundreds of precious lives (National Commission on Terrorist Attacks upon the United States, 2004). We know, for example, that the New York Police and Fire Departments were aware of the need for a single radio frequency to share time critical information in the event of a disaster. In 1996 and 1997, dozens of new radios had been distributed to key police and fire commanders to address failures identified in the 1993 World Trade Center bombing. Nevertheless, coordination stalled when representatives of the two departments could not agree on who would be in control of the interagency frequency and who would decide when it would be used. As a result, the radios remained in the fire chiefs’ car trunks and on the police chiefs’ shelves on September 11th (Dwyer & Flynn, 2004). This is but one example of a disastrous consequence that resulted from a lack of collaboration among agencies as they prepared for terrorists’ attacks. After 9/11, the nation turned its attention to terrorism and the need to better collaborate among local, state, and federal agencies. In the spring of 2003, the Department of Homeland Security (DHS) was established, with 22 distinct agencies and bureaus and more than 180,000 employees. The formation of the DHS was a direct response to interagency shortcomings associated with 9/11. It was aimed at increasing interagency integration, preparation, and responsiveness in the increasingly uncertain, complex, and hostile context of terrorist threats. Weaknesses in the newly formed Department became apparent during the interagency fiascoes of Hurricane Katrina that impacted nearly one-half million people in Louisiana, Mississippi, and Alabama. Once again the failures of local, state, and federal agencies’ capacities to collaborate revealed acute weaknesses in preparation, alarming failures in translating preparation into action, and the inability to improvise in the face of lifethreatening events. In short, reports now make it clear that the development of collaborative capacity in the preparedness stages would have reduced the devastating effects of this economic and human disaster (Comfort, 2005; United States Government Accountability Office, September 2005). While the need for collaboration may seem obvious, Katrina and 9/11 are simply dramatic and visible examples revealing agencies’ failure to develop adequate collaborative capacity. For our purposes, we define collaborative capacity as the ability of organizations to enter into, develop, and sustain interorganizational systems in pursuit of collective outcomes. Organizations fail at collaboration for many reasons: organizations have their own missions with goals and incentives that often conflict with one another; agencies often have histories of distrust that are hard to alter; leaders may not

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actively support collaborative efforts; and coordination systems and structures that might support collaboration are often lacking (United States Government Accountability Office, December 2002). After viewing these disasters, we became intrigued by the question of why collaboration is so difficult in the preparation phase and wanted to identify factors that might be leveraged to overcome these barriers. To this end, we conducted two studies with senior homeland security officials. We chose a semi-inductive approach to identify critical factors that create and deter effective interagency collaboration during the earliest planning stages when organizations prepare for potential disasters. In this chapter, we begin by briefly discussing the construct of collaborative capacity and then explain the need for collaboration in the preparation stages. Next, we present the research findings and point the way to next steps in designing measures for building collaborative capacity.

COLLABORATIVE CAPACITY FOR HOMELAND SECURITY Collaborative capacity as it relates to interagency collaboration resonates in the work of a number of academics and practitioners (e.g., Bardach, 1998; Gray, 1989; Huxham, 1996; Mowery, Oxley, & Silverman, 1996; Seidman, 1970). Pelfrey (2005) defines collaboration for homeland security as ‘‘agencies, organizations, and individuals from many tiers of public and private sectors, working, training, and exercising together for the common purpose of preventing terrorist threats to people and property’’ (p. 7). For the purpose of this study, we also include activities related to natural disasters.1 A capacity for collaboration enhances the probability of mission completion by leveraging dispersed resources. The benefits of developing collaborative capabilities include cost savings through the transfer of smart practices, better decision making as a result of advice and information obtained from colleagues, enhanced capacity for collective action by dispersed units, and innovation through the cross-pollination of ideas and recombination of scarce resources (Hansen & Nohria, 2004). In the case of Homeland Security, we argue that developing a capacity for interagency collaboration is critical both for efficiently conducting routine tasks and for innovatively responding and improvising in the face of terrorist threats or natural disasters. While collaboration may not be equally desirable in all cases or in all stages of interagency work, it is likely to be more critical as decision making and task interdependencies increase. Our

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focus is on identifying this capacity during the preparation stage prior to the demands and incentives generated in the face of an actual crisis.

THE NEED FOR COLLABORATION IN THE PREPARATION STAGES DHS has identified several phases that correspond to a terrorist threat or natural disaster: detection, prevention, response, recovery, and incident management. Coordination and collaboration are critical in all these phases, with agencies seemingly more capable of working together in the response phase. Experience tells us that agencies are less able to work together effectively as they prepare for a terrorist attack or national disaster. Even though homeland security efforts typically focus on the response stage, scholars are now beginning to develop a strategic approach to preparedness. Pelfrey (2005) underscores the importance of preparedness and has developed a cycle of preparedness that places the greatest weight on prevention because effective preventative measures are assumed to deter, detect, prevent, or eliminate potential threats. According to Pelfrey (2005), collaboration and information sharing are the two most essential approaches to prevention. Further, she argues that collaboration requires collegiality, trust, flexibility, openness, mutual respect, social capital, and pathways of communication. While inflexibility and cultural restrictions create substantial barriers. Once collaboration is established, information sharing becomes more effective.

METHODS Data reported in this chapter were gathered in two different ways and at two different points in time. All of the study’s participants are experienced professionals working for civilian, government, or military organizations from around the U.S. who have on-going DHS responsibilities. Illustrative organizations and positions include: USNORTHCOM (mid- to seniorranking officers), U.S. Coast Guard, Centers for Disease Control, Directors of Offices of Emergency Management, captains and chiefs of city-level police, and fire departments. All participants were enrolled in a master’s degree program in Homeland Security at the Naval Postgraduate School.2 The students are resident for two weeks each term and do distance education along with their full-time work commitments during the remainder of the program.

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RESULTS Study One was a workshop conducted by the authors (and one other colleague3) in 2004 and included 25 participants mentioned above. The purpose of the workshop was to identify factors that created conditions for successful interagency collaboration during the preparation phase. We also identified barriers to interagency collaboration. Study Two involved a second group of participants who were asked to provide critical incidents about successful interagency collaboration during the preparation phase. We report a summary of the critical factors as well as examples to illustrate key factors. Study One: Thematic Analysis of Success Factors and Barriers The workshop began with the following instructions to the participants: ‘‘Think back to a specific DHS or other effort that included at least two other agencies or organizations that you consider to have been a successful collaboration in the preparation phase (not response phase) of DHS. Identify three key factors that contributed to this success.’’ Participants were asked to record a brief description of each success factor and a word or short phrase to summarize the factor. They also identified the key participating organizations. This activity was repeated to identify three key barriers to collaboration as evident in a particular experience they had when interagency planning or prevention efforts were not successful. Following the workshop, the data were transcribed into two spreadsheets for further analysis. Through an iterative process, the research team analyzed and consolidated the factors into common themes to create a more parsimonious and usable taxonomy. Ultimately, Galbraith’s (2002) framework for organization design seemed most useful for organizing and communicating the themes derived from the DHS professionals. The five main elements adapted from Galbraith’s ‘‘Star’’ model are Strategy, Structure, People, Incentives, and Lateral Mechanisms. We used this model because it offers a systematic diagnosis of organizational factors that both enhance and impede collaboration, while also guiding action toward improved collaborative capacity. Table 1 presents the specific themes derived from the success factors and barriers identified by the homeland security professionals. These themes are organized by the five elements of the organization design model. Factors reported in Table 1 include all those identified by at least three individuals (i.e., 12 percent of participants). Those indicated in bold font were named by

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Table 1.

Factors Affecting Interorganizational Collaboration (Study One).

Organization Design Component

‘‘Success’’ Factors

‘‘Barrier’’ Factors

Purpose and strategy

‘‘Felt need’’ to collaborate Common goal or recognized interdependence Adaptable to interests of other organizations

Structure

Formalized coordination committee or liaison roles Sufficient authority of participants

Lateral mechanisms

Social capital (i.e., interpersonal networks) Effective communication and information exchange Technical interoperability Collaboration as a prerequisite for funding or resources Leadership support and commitment Absence of competitive rivalries Acknowledged benefits of collaboration (e.g., shared resources) Appreciation of others’ perspectives Competencies for collaboration Trust Commitment and motivation

Divergent goals Focus on local organization over cross-agency (e.g., regional) concerns Lack of goal clarity Not adaptable to interests of other organizations Impeding rules or policies Inadequate authority of participants Inadequate resources Lack of accountability Lack of formal roles or procedures for managing collaboration Lack of familiarity with other organizations Inadequate communication and information sharing (distrust)

Incentives

People

Competition for resources Territoriality Organization-level distrust Lack of mutual respect Apathy

Lack of competency Arrogance, hostility, animosity

Note: Items in bold were identified by at least 25 percent of the study participants.

at least six individuals (25 percent). The most frequently named factors are discussed below. Success Factors. Overall, a vast majority of the participating professionals identified having a shared purpose as a critical success factor. Two of the


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three success factors related to ‘‘purpose and strategy’’ were named by at least 25 percent of the participants. Purpose can be driven by a commonly perceived risk or threat (‘‘felt need’’) or a common goal such as improving information sharing, coordinated training, or overall preparedness. Accomplishing a shared purpose is enabled by the third factor in this category – the willingness to adapt the collaborative effort to the needs and interests of other participating organizations. ‘‘Lateral mechanisms’’ were also frequently mentioned as contributing to success. Specifically, social capital and effective communication were named by at least 25 percent of the participants. Social capital represents the interpersonal trust and exchange orientations that come from human interaction providing an important foundation for civic behavior (e.g., Adler & Kwon, 2002; Putnam, 2000). We classified social capital as a lateral mechanism within the organization design framework. Examples of this phenomenon include: 1. ‘‘[Our success was the] development of camaraderie/esprit de corps to carry the group through conflicts.’’ 2. ‘‘[We had] a longtime history working together.’’ Effective communication was a related lateral mechanism that was also named with great frequency by study participants. While respondents often did not elaborate this factor, some characterizations of effective communication were offered, to include: timely dissemination of information, free flow of information, and the establishment of communications systems and processes across organizations. Effective communication, along with the increased familiarity that comes with interpersonal networks, provides an important means for collaboration. ‘‘Incentives’’ was the third category of factors mentioned most frequently by the participants. In particular, government grant requirements were cited frequently as contributing to successful collaboration. Comments in the discussion at the workshop as well as the results of the analysis of ‘‘barriers’’ indicated that there is often a history of competition for resources among city, county, regional, and state-level service providers. The competition can be across agencies or within an agency but across jurisdictions. By establishing a requirement that grant proposals be developed with multiagency participation, an initial incentive to collaborate is established. While this does not guarantee success, it creates an opportunity to develop other important collaborative capabilities. Collaborating in the development of a grant proposal is a focused, time-limited activity with clearly identified ‘‘payoffs.’’ The process of this effort can generate a better understanding of

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other organizations’ interests and capabilities, create social capital as interpersonal relationships are developed, and may result in the establishment of temporary or permanent structures for collaboration and processes for information exchange. Incentives to collaborate can be achieved through mandates or external requirements for funding (Cummings, 1984). Another frequently mentioned incentive to collaborate was strong leadership. A leader who clearly expresses commitment to a vision of collaboration with other agencies can provide an important incentive for other organizational members to engage in this ‘‘new’’ activity. This is similar to the acknowledged role of leadership in effective change management (e.g., Kotter, 1990). Barriers to Collaboration. The identified barriers to collaboration substantially reinforce the factors identified as contributing to success, even though they are not an exact replication of the capabilities described above. For example, ‘‘lack of familiarity with other organizations’’ and ‘‘inadequate communication and information sharing’’ represent missing enablers of collaboration. Some participants identified distrust as a cause of inadequate communication. Distrust was sometimes characterized at the organizational level, as in ‘‘the organizations have a history of distrust.’’ Other times the participants attributed distrust to individuals; in this case, we categorized the factor into the design factor of People. Behaviors that are both instigators and symptoms of distrust included ‘‘arrogance, hostility, and animosity’’ in the People category and ‘‘lack of mutual respect’’ when attributed to organizations (in the Incentives category). Two other frequently cited barriers were ‘‘competition for resources’’ and ‘‘territoriality and turf protection.’’ These two factors were categorized as (dis)incentives. These factors are related to the Lateral Mechanisms and People factors described above. While the causal relationship is not definitive, a clear relationship exists among competition/territoriality and lack of familiarity, inadequate communication, and distrust. Together, these system dimensions can create a continuing cycle of dysfunction. When organizations are competitive, distrustful, or just unfamiliar, with each other, this can impede necessary communications. The inadequacy of communications, in turn, continues the lack of familiarity, or in the more extreme cases, can increase distrust. This suggests that specific interventions to disrupt this cycle and shift the alignment toward constructive interactions are necessary to build collaborative capacity. While mentioned less frequently, other barriers to effective interorganizational collaboration were classified as Structural. Specific examples include: procedural prohibitions such as security classifications, lack of formal


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roles and procedures to enable collaboration, inadequate authority of participants to engage in negotiation or decision making on behalf of their organization, and lack of accountability. Most of these are indicators of problems that can exist in ‘‘under-designed’’ systems (Cummings, 1984). Because well-established, institutional mechanisms for coordination are unlikely to exist or are likely to be underdeveloped in extra-organizational relationships, the importance of leadership, followership, and colleagueship (i.e., the capacity for mutual adjustment) is increased. Study Two: Thematic Analysis of Success Factors We undertook the second study approximately 18 months following the first to both validate and elaborate the findings described above. This study involved a different group of students in the same Homeland Security master’s program. They were from similar organizations with similar mid- to upper-level management positions. The design for the second study was different, because we were interested in eliciting more detail about the factors and the relationships among the success factors for interagency collaboration. Since most of the students’ master’s program is conducted using distance learning while the professionals maintain their full-time jobs, discussion questions are often posted by their faculty on an electronic blackboard. We posed a discussion question to which 26 students responded; these postings could be viewed by other class members and were ultimately used as part of their course discussions. The data solicitation question was worded as follows: One of the few consistent findings in homeland security is that effective collaboration is the foundation of successful prevention. There is a need, however, to understand how we can get better at collaboration. Think about a specific homeland security (or related) effort that included at least two other agencies or organizations that you consider to have been a successful collaboration. Whenever possible, use an effort that was oriented to preparedness or prevention, not to response. (a) Briefly (one or two sentences) describe the event including the names of the primary organizations that were involved in the collaboration. (b) Rank order the three key factors that contributed to the success of the collaboration (1 ¼ most critical success factor). (c) Finally, provide a brief explanation of why the most critical success factor (your #1 factor) mattered.

Table 2 presents the thematic analysis derived from the success factors identified by this group of professionals. As in Table 1, at least three

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Table 2. Success Factors in Interagency Collaboration (Study Two). Organization Design Component Purpose and strategy

Structure

Lateral mechanisms

Incentives People

‘‘Success’’ Factors

‘‘Felt need’’ to collaborate Common goal Willingness to address other agency’s interests or cross-agency goals versus local organizational goals Formalized structure for coordination (e.g., committee or liaison roles) Formalized processes (meetings, deadlines, agendas) Sufficient authority of participants Role clarity Dedicated assets (people, resources) for collaboration Social Capital (i.e., interpersonal networks) Effective communication and information exchange Technical interoperability Combined training events Collaboration as a prerequisite for funding or resources Respect for other parties’ interests, expertise, roles, perspectives Perseverance/commitment

Note: Items in bold were identified by at least 25 percent of the study participants.

individuals named all items presented, and those in bold font were identified by at least six individuals (i.e., 25 percent of participants). There is substantial reinforcement of the thematic factors derived from Study One, with a couple of new additions. Of significant note is the fact that the three factors under the organization design element of Purpose and Strategy are the same as the three factors identified in Study One: (1) felt need to collaborate; (2) common goal; and (3) willingness to address other agency’s interests or cross-agency goals versus local organizational goals. However, in this study, each factor was named by at least 25 percent of the respondents; thus, this domain was seen as providing a critical success factor for at least a majority of the participants in this study. While similar to each other, these three factors show a somewhat different emphasis that provides important descriptive value in terms of understanding the dimensions of shared purpose that can be developed to improve collaboration. Two other factors that were frequently named in Study One are again reinforced in Study Two. First, an important Incentive is created when interagency collaboration is a prerequisite for grant funding or other resources. Second, the social capital available through personal relationships creates a Lateral Mechanism for collaboration. Some participants cited this


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factor as foundational to the initiation of collaborative activities. Others described the value of developing personal relationships in early phases of collaborative activities. As relationships develop, social capital accumulates in the form of increased respect, trust, information exchange, and mutual understanding, all of which contribute to increased success in collaboration and an increase in what we call collaborative capacity. A new finding in this study was the identification of combined training events, which we categorized as a Lateral Mechanism, that contributed to successful collaboration. The role of some formalized structure for collaboration (e.g., interagency committee, liaison roles) was a stronger outcome in Study Two than in Study One. While mentioned less frequently, other specific structural dimensions were identified including role clarity, dedicated assets (e.g., time, people), and formalized processes (e.g., deadlines, agendas) that increase accountability for collaboration. Assuring that people with adequate authority for decision making or resource allocation are involved in the interagency effort also was reinforced in Study Two. Study Two: Narrative Examples of Success Factors Many respondents provided much more detail than requested by the data solicitation instructions above. Samples of responses are presented below to provide some increased richness to the themes identified and offer further clarification to the conceptual model. In addition, the vignettes provide insights about the relationships among factors that can improve collaboration. The quotes come directly from the participant responses, but, to protect their anonymity, specific organizations and locales are not given. Purpose: ‘‘Felt Need to Collaborate.’’ The following quote illustrates the fragility of relying solely on threat response as the aligning factor for interagency collaboration. The most critical success factor is the recognition of the need to engage in prevention activities by all partners. The U.S. Department of Homeland Security designed the ‘‘Buffer Zone Protection’’ training course and the [State] Department of Public Safety hosted the course. [Our city] sent officers to attend the course. The [county] Emergency Management Agency engaged in vulnerability assessments, and private sector partners were cooperative and receptive to working with [police] officers. This window of opportunity may slip by soon. Once people no longer believe terrorism is a real threat they will be less willing to cooperate in this type of activity.

This quote also suggests the value of the training event as a lateral mechanism for bringing parties together and the consequent initiation of personal

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connections among police officers, emergency management workers, and private sector representatives. However, the final statement can be taken to imply that powerful institutional barriers to collaboration could easily overtake the current shared purpose of responding to terrorist threats as the sense of imminent threat recedes. Collaborative Structure. As noted in the thematic analysis above, several participants identified the establishment of a formal structure for collaboration as a key factor to success. The following vignette is an example: What had [the most] beneficial impact on collaboration was the formation of a multiagency team y. It involved creating a Community Defense Unit (CDU) that not only encompassed the Joint Terrorism Task Force, but also included officers/agents from the 11 different state, federal, county, and municipal agencies. This collective effort focused on everyone’s joint mission of countering terrorism by conducting criminal investigations and surveillance.

This police officer clearly stipulates that the establishment of a structure that brought together representatives of different agencies and jurisdictions enabled a secondary factor that was the determination of a ‘‘joint mission.’’ The statement also implies that the nature of this joint mission (criminal investigations and surveillance) requires information sharing across agencies (i.e., lateral mechanisms). In another example, the chief of a large, urban fire department described the role of collaborative structures as a mechanism for enabling other factors that, in turn, further increased effectiveness of collaboration. In these examples, formal structure initially enabled the collaborative development of response plans. As part of these plans, joint training and exercises were conducted, which in turn led to the development of personal relationships. ‘‘Each member then has a better understanding of each other’s needs y. The common goal, safety of civilians, can be achieved through the exchange of information and knowledge. Collaboration is attained through a personal touch, a handshake and a smile.’’ Incentives to Collaborate. The participants had several examples of the impact of an externally driven financial opportunity that required collaboration. One example follows: The initial development of the group [resulted from having] to determine how to spend around $7 million. While this amount will not provide ample funding for security for all agencies, the coming together and development of a single vision of what homeland security should be in the region was developed.

This quote indicates that the external incentive and requirement initiates the collaboration. In successful situations, this initial interaction generates a


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shared purpose or common goal beyond the initial requirements of a grant application. Another participant made explicit the extent to which these incentives were causing a new way of thinking and new innovative behaviors: For several years, there was so much dissent and resentfulness between the county and the city y. The grants seem to migrate to the city, leaving the county feeling like a stepchild. For FY05, the rules changed. When it was stipulated that all grant proposals had to be a ‘‘regional’’ effort, the tables turned. Suddenly, competing for the grant was out of the question because winning the proposal would benefit all counties in the region y This was a big change and we had more cooperation and collaboration than at any other time. I believe it is simply because the element of competition was removed from the process.

This quote, while generated to describe a success factor, also illustrates a barrier to collaboration that was frequently identified in Study One: ‘‘competition for resources’’ and ‘‘territoriality.’’ This response and others like it provide further evidence that the challenges of effective collaboration are qualitatively different in the phases of DHS planning and prevention than in the situation of crisis response (Bellavita, 2005). In a crisis situation, the issue of competition is less present; agency rivalries are more likely to become secondary to time critical response requirements. However, in planning and prevention, bureaucratic processes and historical relationships embedded in competition over resources, decision authority, power, and visibility prevail and create inhibitions to cooperation. These can be overcome in the short term by mandating collaboration or creating incentives that foster cooperation (e.g., regional grant proposals). The preliminary evidence from the stories shared by these professionals suggests that both collaborative structures and external incentives can enable personal interactions. Thus they provide a forum, but they do not assure successful collaboration. They offer technical vehicles that can – but do not necessarily – generate increased familiarity across organizations, an appreciation of the capabilities and requirements of other agencies, and opportunities for participating individuals to build social capital. All of these factors, in turn, improve collaborative capacity. Social Capital as a Lateral Mechanism. As noted in the discussion of social capital in Study One, this factor derives significantly from networks of human interaction. The quote ending the section on ‘‘collaborative structures’’ gave a simple illustration of how social capital is developed: ‘‘Collaboration is attained through a personal touch, a handshake and a smile.’’

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Another study participant gave a more detailed explanation of the value of this concept in developing collaborative capacity. For a time-constrained professional, one way to screen work/opportunities/tasks is by evaluating the messenger. This task force only got off the ground when members of the task force, all of whom have known each other for a number of years, agreed to pursue this joint venture. A shared respect by the involved parties provided the impetus to push pre-existing priorities aside in order to make room for this new effort. These relationships ensure that phone calls are answered, e-mails replied to in a timely manner, and, generally speaking, that we stay on task. Without these relationships, this project would have been just another thing to do ‘‘some day.’’

This quote also provides a significant contrast to the approach of top–down or externally driven mandates or incentives for collaboration. In this vignette (and others identifying the key value of social capital), the initiative came from inside the organization and was based on the lateral network of social and professional relationships. We hypothesize that interagency interactions that are based solely on external incentives will not develop a sustainable collaborative orientation or necessary collaborative capacity unless participating organizations are able to successfully develop the social networks illustrated by the example above. Another participant in Study Two provides an additional perspective on the need for social capital: I wonder, probably because our state is reorganizing and many key players in homeland security are losing their positions, how do we keep up with our collaborative efforts without losing momentum in times of change for political and other reasons? It seems that if we do not have relationships with the individuals in middle management in partnering organizations, we will always be starting over and never get past the first stages of collaboration and, therefore, unable to build solid preparedness, prevention, and response systems.

This quote identifies the problem of relying on social capital that may only exist at the top of government agencies. Because these positions are political appointments, and may turnover frequently, it is important to build stable social networks at the mid-level and operating core of the organization. Also implicit in this quote is an acknowledgment of the developmental nature of collaboration. Building collaborative capacity is a multifaceted endeavor requiring systemic attention, resources, commitment, and opportunities for interaction. People: Mutual Respect. Several participants mentioned positive and respectful interpersonal interactions as important to the success of interagency collaboration. For example, ‘‘treating all players with dignity and honor enabled the project to have a unified front.’’ A medical professional working


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on bioterrorism preparedness identified mutual respect and acknowledgment of expertise: ‘‘We respected everyone’s role; let each discipline do what they do best.’’ It might be argued that the factors that were summarized above as social capital under Lateral Mechanisms should be placed in the category of People in the systems taxonomy. We acknowledge that social capital is grounded in individual-level networks and rely on individual lateral skills (Mankin, Cohen, & Fitzgerald, 2004). However, we judged that the importance of this factor, in the context of interagency collaboration, is better characterized by emphasizing the role of social capital as a lateral mechanism than as an individual-level phenomenon.

DEVELOPING ORGANIZATION DESIGN DYNAMICS TO IMPROVE COLLABORATIVE CAPACITY: AN INNOVATIVE STRATEGY FOR DHS The data from Study Two provide important insights about the interrelationships among the factors that contribute to successful interorganizational collaboration in the context of homeland security. Most of the quotes above, while used to illustrate a single factor, also elaborate how one factor either contributed to or derived from other factors. For example, a perceived threat or high-risk situation (felt need) might lead to the establishment of an interagency committee or task force (collaborative structure) to address the concern. This might generate joint procedures (formalized structure) or an interagency training event (lateral mechanism). Through the interaction resulting from planning joint procedures or conducting joint training, social capital can be developed. Alternatively, the initiation of collaboration might come from an external grant opportunity (incentive) that requires multiple agency participation. The process of accomplishing this task likely depends on establishing a task force or liaison roles (collaborative structures). At the organizational level, working together to meet the proposal requirements requires identifying a common goal or a willingness to address other agencies’ interests (purpose and strategy). This planning process can increase familiarity and appreciation for the interests and capabilities of participating organizations and build social capital through strengthened professional networks (lateral mechanisms); it can contribute to the development of trust and understanding at the level of individual representatives (people). A quote from a research scientist in Study Two nicely illustrates one example of how the organizational systems components interact in building

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collaborative capacity: Four agencies were to investigate the vulnerabilities of a metropolitan water distribution network y. Unless you have worked with these groups, it is difficult to appreciate how much non-cooperation occurs. Quite a bit of turf protection goes on because of walls built through time and lack of communication between managers. We discovered that by defining each agency’s responsibilities, both communication and teamwork effort progressed well; cooperation between agencies was enhanced. Early in the process we realized that y one specific agency did not have the expertise necessary to address the matter at hand; it would require the expertise of numerous personnel from the various groups y. By delineating responsibilities between agencies and groups, the effectiveness of interagency communication and teamwork was enhanced. As a result of this process, plans are underway to develop a training scenario that will involve local hazmat teams, fire, police, and the EMS along with the four agencies. Finally, in my opinion, the relationships fostered from this [vulnerability assessment] have gone a long way in knocking down the barriers between agencies (at least locally), which should greatly improve future cooperation and collaboration.

This example begins by stipulating the context of ‘‘non-cooperation.’’ Clearly, an innovation in interagency interaction was required to address a problem that exceeded the capacity of any single organization. This acknowledged interdependence created a shared purpose. Role clarity provided structure and improved communication (lateral mechanism). The initial effort has led to plans for a joint training scenario (lateral mechanism) that will bring together personnel from four different agencies. The more immediate result of the work to date has been in the development of interpersonal relationships. All of these elements, together, have contributed to the improved collaborative capacity of the system of agencies facing a common problem of homeland security. We try to capture the dynamic interaction among all of these factors in the image presented in Fig. 1. This diagram shows two organizations (A and B) facing a homeland security problem in which they have some interdependent interest or responsibility. Each organization can be represented in terms of the five organization design components derived from Galbraith (2002). The arrows indicate the dynamic interaction among the system elements both within and between organizations as they contribute to the collaborative capability to meet the homeland security problem. The dynamic interactions occur in at least three domains. First, effective collaborative capacity requires that the five system elements (Strategy, Structure, Incentives, Lateral Mechanisms, and People) for each participating organization be aligned with each other and with the environmental requirement or challenge (cf. Nadler & Tushman, 1980). This is reflected in the arrows within each of the three pentagons. However, because the


Fig. 1.

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Developing Organization Design Dynamics to Improve Collaborative Capacity: An Innovative Strategy for DHS.

homeland security problem assumes interdependence among multiple organizations, developing collaborative capacity cannot be accomplished by focusing solely on the dynamics within each organization. There also needs to be alignment of the system elements across organizations. Finally, as illustrated by the data reported above, temporary or permanent interagency structures are frequently established to better enable the collaborative response to the DHS problem. In such a case, a third domain of interaction needs to be developed so that the design characteristics of the interagency task force or team are not only internally consistent, but also are aligned with the primary organizations that it represents.

CONCLUSION Collaboration is required in partnerships, teams, and organizations, but our focus is on developing collaborative capacity between and among

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organizations. Collaboration for homeland security is occurring in the context of under-designed institutional relationships. Leaders and interagency collaborative teams must therefore work to create novel processes, systems, protocols, and networks. They are faced with tasks of overcoming likely institutional barriers resulting from unique and partially conflicting missions, goals and incentives, and they need to facilitate and enable organizational collaboration through processes that we have categorized in an interagency design framework. The alternative to design is organization ‘‘by default,’’ which is likely to be inadequate, as recent cases reveal. Organizational responses to hostile, complex, uncertain events – to crises – are always likely to require intelligent improvisation. But planning and preparation become critical in setting the stage for such successful reactions. In the absence of adequate preparation, collaborative capacity is likely to be low, plans are unlikely to be translated into action, and actions are likely to be delayed, inefficient, and ineffective. Proactive preparation and design can be conceptualized in terms of an interorganizational systems perspective. As in the literature on organizational change and intercultural learning, ‘‘felt need’’ is likely to be a prerequisite for building collaborative relationships. Common goals and recognition of interdependence – we succeed or fail together – provide a sense of purpose for individual actors to move toward the new paradigm of working as a larger team. Divergent goals, goal ambiguity, parochialism, and organizational rigidity are barriers that will block the larger purpose of collaboration. Some individuals may not appreciate the importance of the larger structural context. However, formalizing relationships (e.g., coordination committees and liaison roles) and attending to issues of legitimacy and authority (e.g., making sure those on an interagency task force are representative of the organization and are capable of making decisions) are potential success factors. Conversely, inadequate authority, conflicting rules, and inadequate role clarity create a context for frustration and failure. Lateral mechanisms need to be developed that correspond to the requisite interdependence of the intergovernmental agencies. Where agencies depend on each other for resources or have sequential and reciprocal task interdependence, leaders must spend time and energy to develop and institutionalize lateral mechanisms. Of special importance in this context are social capital and opportunities and incentives for information exchange and social relationships. In the absence of familiarity and a history of information sharing, collaborative capacity is likely to be low. Rewards must be aligned to support collaboration. As Kerr (1975) reminds us, it is foolish to expect collaboration when incentives for

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collaboration are negative or non-existence. If collaboration is a prerequisite for funding and resources, and if leadership rewards the time and energy spent developing interorganizational relationships and clarifying roles and processes, then the collaborative capacity might be developed. If leadership rewards accomplishing localized, competitive objectives and goals, redesigning structures will not be sufficient to generate collaborative capacity. Finally, people who lack the ability and motivation (i.e., a lack of collaborative competency or arrogance and animosity for the other agencies) drain teams of the potential for collaborative capacity. Collaboration is interpersonally and managerially challenging and requires commitment and motivation, competence, trust, and an appreciation of how others do business.

FUTURE DIRECTIONS Collaborative capacity is an intuitively appealing construct but currently lacks clear operationalization. This deficiency is problematic for homeland security leaders and practitioners who want to identify the collaborative capacity of their agencies. The absence of measurement models also is problematic for the advancement of the social science of interagency collaboration. The factors in Studies One and Two above were inductively generated in the hope of identifying dimensions that need to be measured to operationalize the construct. Thus, the next challenge researchers must face is how to diagnose or audit the collaborative capacity of organizations that are expected to be in effective collaborative relationships.

NOTES 1. The Department of Homeland Security’s mission includes the prevention and detection of terrorist threats as well as coordinating national responses to natural disasters, or other emergencies. 2. The Center for Homeland Defense and Security (CHDS) is located at the Naval Postgraduate School (www.nps.edu) in Monterey, CA. Since 2002, CHDS has conducted a wide range of programs focused on assisting current and future homeland security leaders to develop the policies, strategies, programs, and organizational elements needed to defeat terrorism in the United States. The programs are developed in partnership with and are sponsored by the DHS’s office for Domestic Preparedness. 3. Stu Winby, founder and managing partner of The Sapience Group, assisted in the design and delivery of the workshop.

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REFERENCES Adler, P. S., & Kwon, S. (2002). Social capital: Prospects for a new concept. Academy of Management Review, 27(1), 7–40. Bardach, E. (1998). Getting agencies to work together: The practice and theory of managerial craftsmanship. Washington, DC: Brookings Institution Press. Bellavita, C. (2005). What is preventing homeland security. Homeland Security Affairs, 1(1), Article 3. Comfort, L. (2005). Fragility in disaster responses: Hurricane Katrina, 29 August 2005. The Berkeley Electronic Press, 3(3), Article 1. Cummings, T. G. (1984). Transorganizational development. In: B. M. Staw & L. L. Cummins (Eds), Research in organizational behavior (Vol. 6, pp. 367–422) Greenwich, CT: JAI Press. Dwyer, J., & Flynn, K. (2004). 102 minutes: The untold story of the fight to survive inside the twin towers. New York, NY: Times Books. Galbraith, J. R. (2002). Designing organizations: An executive briefing on strategy, structure and process. San Francisco: Jossey-Bass. Gray, B. (1989). Collaborating: Finding common ground for multiparty problems. San Francisco: Jossey Bass. Hansen, M. T., & Nohria, N. (2004). How to build collaborative advantage. MIT Sloan Management Review, 46(1), 22–30. Huxham, C. (1996). Collaboration and collaborative advantage. In: C. Huxham (Ed.), Creating collaborative advantage (pp. 1–18). London: Sage. Kerr, S. (1975). On the folly of rewarding A while hoping for B. Academy of Management Journal, 18(4), 764–783. Kotter, J. P. (1990). A force for change: How leadership differs from management. New York: Free Press. Mankin, D., Cohen, S., & Fitzgerald, S. P. (2004). Developing complex collaboration: Basic principles to guide, design, and implementation. In: M. M. Beyerlein, D. A. Johnson & S. T. Beyerlein (Eds), Complex collaboration: Building the capabilities for working across boundaries (pp. 1–26). New York: Elsevier. Mowery, D. C., Oxley, J. E., & Silverman, B. S. (1996). Strategic alliances and interfirm knowledge transfer. Strategic Management Journal, 17, 77–90. Nadler, D. P., & Tushman, M. L. (1980). A model for diagnosing organizational behavior: Applying a congruence perspective. Organizational Dynamics, 9(2), 35. National Commission on Terrorist Attacks upon the United States. (2004). The 9/11 commission report. New York: W.W. Norton & Company. Pelfrey, W. V. (2005). The cycle of preparedness: Establishing a framework to prepare for terrorists threats. Journal of Homeland Security and Emergency Management, 2(1), Article 5. Putnam, R. D. (2000). Bowling alone: The collapse and revival of American community. New York: Simon & Schuster. Seidman, H. (1970). Politics, position and power: The dynamics of federal organization. New York: Oxford University Press. United States Government Accountability Office. (December, 2002). Homeland security: Management challenges facing federal leadership. GAO-03-260. United States Government Accountability Office. (September 28, 2005). Hurricane Katrina: Providing oversight of the nation’s preparedness, response, and recovery activities. GAO05-1053T.

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