Complex Collaboration, Volume 10: Building the Capabilities for Working Across Boundaries (Advances in Interdisciplinary Studies of Work Teams)

CONTENTS LIST OF CONTRIBUTORS

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ACKNOWLEDGMENTS

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ABOUT THE EDITORS

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INTRODUCTION Michael M. Beyerlein, Douglas A. Johnson and Susan T. Beyerlein DEVELOPING COMPLEX COLLABORATIONS: BASIC PRINCIPLES TO GUIDE DESIGN AND IMPLEMENTATION Don Mankin, Susan Cohen and Stephen P. Fitzgerald

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CO-DEVELOPMENT: COLLABORATING ACROSS BOUNDARIES ON JOINT STRIKE FIGHTER Jude G. Olson

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NOT YOUR STEPPING STONE: COLLABORATION AND THE DYNAMICS OF FIRM EVOLUTION IN THE LIFE SCIENCES Kenneth W. Koput and Walter W. Powell

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THE IMPACT OF COLLABORATIVE MOTIVATION ON COMPLEX MULTI-AGENCY PARTNERSHIPS: A CASE STUDY OF THE UNITED KINGDOM Janine Stiles and Paul Williams

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COMPLEX COLLABORATIONS: THE CASE OF A BUSINESS SCHOOL AND ITS COMPLEX NETWORK OF RELATIONSHIPS Peter Lorange

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INTEGRATING PERSPECTIVES: A MULTIDIMENSIONAL CONSTRUCT OF COLLABORATIVE CAPABILITY Melanie Schreiner and Daniel Corsten

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THE COLLABORATIVE CAPACITY FRAMEWORK: FROM LOCAL TEAMS TO GLOBAL ALLIANCES Stephen P. Fitzgerald

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LEADING COMPLEX COLLABORATION IN NETWORK ORGANIZATIONS: A MULTIDISCIPLINARY APPROACH Karen L. Higgins and Joseph A. Maciariello

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“SKONK WORKS HERE”: ACTIVATING NETWORK SOCIAL CAPITAL IN COMPLEX COLLABORATIONS LuAnne R. Johnson and David Knoke

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MANAGING VALUE AND VULNERABILITY IN COMPLEX COLLABORATIONS: ALLYING WITH COMPETITORS Joseph P. McGill and Michael D. Santoro

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LIST OF CONTRIBUTORS Susan Cohen

Center for Effective Organizations, University of Southern California, USA

Daniel Corsten

Kuhne Institute for Logistics, University of St. Gallen, Switzerland

Stephen P. Fitzgerald

California School of Organizational Studies, Alliant International University, Alhambra, CA, USA

Karen L. Higgins

Executive Director and Director for Research and Engineering, NAVAIR Weapons Division, China Lake, CA, USA

LuAnne R. Johnson

Department of Sociology, University of Minnesota, USA

David Knoke

Department of Sociology, University of Minnesota, USA

Kenneth W. Koput

Eller College of Business, University of Arizona, USA

Peter Lorange

IMD – International Institute for Management Development, Lausanne, Switzerland

Joseph A. Maciariello

Drucker Graduate School of Management, Claremont, CA, USA

Don Mankin

Co:e-laboration Design Associates, Venice, CA, USA

Joseph P. McGill

College of Business, Kean University, Union, NJ, USA

Jude G. Olson

Lockheed Martin Aeronautics Company, Fort Worth, TX (AND) Fielding Graduate Institute, Santa Barbara, CA, USA vii

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Walter W. Powell

Education and Organizational Behavior and Sociology, Stanford University, Stanford, CA, USA

Michael D. Santoro

College of Business & Economics, Lehigh University, Bethlehem, PA, USA

Melanie Schreiner

Institute for Technology Management, University of St. Gallen, Switzerland

Janine Stiles

Henley Management College, Henley on Thames, UK

Paul Williams

National Centre for Public Policy, University of Wales, Swansea, UK

ACKNOWLEDGMENTS This work was partially supported by the Center for Collaborative Organizations, 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. The Center has always considered bridging the gap between the academic and practice worlds a mission to be pursued. 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 four 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 significant time pressure to pull the pieces together into a carefully prepared manuscript. Much of the quality in appearance for this volume is due to her thoughtful work.

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ABOUT THE EDITORS Michael 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, work stress, creativity/innovation, knowledge management and the learning organization, and complex adaptive systems. 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 senior editor of the Elsevier annual series of books Advances in Interdisciplinary Studies of Work Teams and the Jossey-Bass/Pfeiffer Collaborative Work Systems series. He has authored or edited 15 books. His most recent are Beyond Teams: Building the Collaborative Organization (2002), The Collaborative Work System Fieldbook (2003), and Team-based Organizing (2003). 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, Raytheon, First American Financial, Westinghouse, and Xerox and with government agencies such as Veterans Affairs, DCMAO, EPA, and the City of Denton. Douglas A. Johnson is director of the Industrial/Organizational psychology program, professor of psychology, and associate director of the Center for Collaborative Organizations at the University of North Texas. He has published research in a variety of areas ranging from teams, leadership and job satisfaction, to operant conditioning and interpersonal attraction. He co-founded and served as president of the Dallas-Fort Worth Organizational Psychology Group (now Dallas Area Industrial/Organizational Psychologists), and participated in the creation of the Dallas office of the consulting firm, Personnel Decisions International, from whom he recently retired. Susan Tull 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 xi

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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 a member of the Jossey-Bass/Pfeiffer Collaborative Works 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 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.

INTRODUCTION Complex collaboration refers to situations where working together effectively across boundaries is critical for complex projects and problems. This work often involves projects of large scope and long duration. The knowledge of a variety of disciplines may be involved. Such projects may cross organizational, national, and/or cultural boundaries. The problem of managing such situations includes ambitious schedules, conflict of cultures and practices, massive amounts of information, multiple languages, and ambiguity of roles and responsibilities. Complex collaboration represents a capability that is essential to effective execution in such situations as new product development, mergers and acquisitions, joint ventures, and supply chain management, as well as large government projects. A number of issues emerge in examining complex collaboration, including: unit of analysis, critical relationships, resource development, virtual teaming, key skills, and improvement processes. The chapters in this volume address these issues and share examples that illustrate the principles that may be operating in complex systems. The authors suggest new directions for research with some arguing that complex collaboration may be an emerging field. (1) Is the unit of analysis for research and change work the same across levels of such complex systems or different? This issue deals with convergence of research and change work. Part of the question involves the practicality of attempting planned change in a complex system. Most successful change work focuses on limited systems. For example, what may be referred to as “work at the corporate level” may actually be as simple as teambuilding with the top management group. Interventions such as organizational redesign usually occur at single sites. Little literature exists to test the question of whether or not change work can occur effectively across multiple boundaries. On the other hand, researchers must find ways to study the whole of a complex system, as much as the parts. Can a convergence of research and change work improve the way complex collaboration capability is developed? (2) Does success depend on a few critical links or on the overall set of relationships? A few critical members often determine how well an overall system functions. The network of relationships across the boundaries of component systems in a complex collaboration is often represented by how the few critical xiii

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members interact. However, total performance of such a system may depend more on raising the level of collaborative capability of all members. For example, if a front line worker in component system A can talk directly with a supply chain member in another component, an improvement in process may emerge. Is there an advantage in focusing on one or the other of these relationship sets? Does the preferred focus change with stage in the evolution of the project? (3) Should project leaders focus resources on infrastructure and skill development or on process improvement to achieve high performance? In every organization, simple or complex, resource limitations make tough choices necessary. In situations where complex collaborative capability is essential to successful attainment of organizational goals, the choice may be whether to spend resources such as money, time, and personnel on development of: (a) infrastructure surrounding the actual work, such as common computer platforms; (b) knowledge, skills, and abilities of the organizational members, so the quality of collaboration rises at all points of contact; or (c) processes that guide decisions and behaviors toward effective collaboration. Perhaps the answer, as usual, is “it depends.” It may depend on the nature of the project, the style and philosophy of the top management group, the level of complexity or uncertainty or risk, or the difference between currently adequate and inadequate levels of support. (4) Can the teams rely on virtual communication or is face-to-face interaction necessary? Complex situations depending on collaboration for knowledge sharing, innovation, and decision making, often involve geographic distances that require use of electronic forms of communication, ranging from phone & fax, to email, to video conferencing. With heightened travel restrictions in most companies now, a heavier reliance on virtual communication has emerged. What is the role of face-to-face contact in this situation? When is that essential enough to warrant increased expense and risk? Is there a way to find a balance point between the methods of meeting? (5) Are the key skills lateral or hierarchical in making complex collaborations work? Crossing boundaries for networking on a project involves lateral communications and the skills that go with that, such as the when, who, and how of connection. Much of the innovation work occurs in the conversations that occur in these lateral relationships. However, the more complex the project, the more important the big picture, and although it ought to be shared by everyone to some extent, its scope is likely to be such that only a few people higher in the hierarchy can achieve an adequate viewpoint. Control through top-down decisions is essential in coordinating the main components of a complex project. How can that control be managed so innovation at lower levels is not

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stifled? The answer depends on collaborative capability that is both vertical and lateral. (6) Is the role of change agent working on complex collaborations the same as or different than for traditional organizational change? Most organization change projects are complex but focus on a single site or group. As with most aspects of organization and change in a complex situation crossing multiple boundaries, the change agent may need to make changes in the change process. The term “complexify” in this context means that the change process must be as complex as the change target. However, there may be practical limitations to how complex it can become. (7) Is there a general set of steps to make any complex collaboration effective or are the sets tailored to particular complex collaborations? Building collaborative capability in a complex situation is likely to require a multi-pronged approach. Certainly some tailoring would be required across situations, but some questions remain unanswered, such as: (a) how much is generalizable; (b) how much needs to be tailored; and (c) how can the boundary between the two be established? Complex collaboration represents a capability that is essential to effective execution in such business situations as new product development, mergers and acquisitions, joint ventures, and supply chain integration. It can also represent a requirement in government collaborations such as economic, environmental, political, and war projects. There seems to be a naivet´e about collaborative organization on complex projects. At one extreme in practice, is an attitude of “it will take care of itself.” At the other extreme, disciplined process, carefully established infrastructures, and intelligent leadership enable the members of the project team to excel. The result of a laissez faire approach is frequently mediocre performance – a performance level that is acceptable, because of a failure to understand what excellence means in this situation. Simple solutions to the collaboration problem only work if a fractal structure is imposed where the practices and processes at the lowest or simplest level of coordination are mirrored at higher levels. Whether this is both necessary and sufficient remains an unanswered research question. However, it is becoming increasingly clear that collaborative capability is not something that will take care of itself. A disciplined approach is required that establishes effective ways of working together and a supportive context as the surround. Complex collaboration refers to knowledge-intensive business processes that require highly interactive communication, coordination, negotiation, research and/or development. Some projects require all of these. Such processes typically involve a large number of people, internal or external to the enterprise, large

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volumes of structured and unstructured data, and numerous steps. These solutions have critical applications across various industries including technology, manufacturing, financial, and pharmaceutical companies. Complex collaboration represents dynamic, complex systems. As such the rules of complexity theory may apply, but research evidence remains scarce. Complex systems have special vulnerabilities that increase the likelihood of system failure. Somewhat like the problem of the weakest link in the chain, complex systems have myriad interdependencies among components where performance at any particular link is constrained by the limits of performance of the remaining links and they are in turn constrained by the one link. Hence, failure at one link can endanger the whole enterprise and, conversely, enhancement of one relationship may contribute to overall performance improvement. Consequently, as business systems become more complex, collaborative excellence becomes more critical. Complex projects often struggle with complex problems or issues that have been called “fuzzy,” “wicked,” “ill-defined,” etc. (e.g. Pacanowsky, 1995). Such problems are characterized by an ambiguity of the problem definition, a need to invent new processes to solve the problem or develop a solution, multiple and conflicting perspectives of the goal, the need for an iterative and trial-and-error approach, and the absence of any objective measure of success. As projects become increasingly global, virtual, and fuzzy, the process will seem to be more populated with wicked problems. Several facets of this field of study are becoming obvious. First, complex collaboration is becoming more common. The number of examples is increasing. The number of industries relying on complex collaboration is increasing. The complexity and variety of those collaborations is increasing. Second, a wide variety of researchers are studying complex collaboration. Multiple disciplines are focusing on various facets of complex collaboration. The resulting issue is whether or not we have a case of the six blind men and the elephant with each discipline acting as a knowledge silo – unaware or unconcerned about what is happening in the other silos. This volume includes work from authors representing many of those disciplines, including psychology, sociology, management of technology, strategic management, finance, organization development, etc. Integration of knowledge and frameworks across disciplines will contribute to more informed research and more effective practice. This volume begins with case examples, where the authors have done in-depth studies of the practices of collaboration in industrial and government settings. The findings from the case studies led the authors to insights about the framework and principles that underlie effective complex collaboration. In the first chapter, Don Mankin, Susan Cohen, and Stephen Fitzgerald focus on their interview studies at John Deere, Radica, and Solectron. Each case has unique

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features and reveals principles that contribute to a framework. The Solectron case is the most complex with its focus on the supply chain relationships that enable the company to be a world leader. The second chapter presents an interdisciplinary framework and applies it in examining one of the most complex new product development projects in the world today – the design of the Joint Strike Fighter (JSF). Jude Olson, senior consultant of organization development for the project, provides a literature review to approach the interdisciplinary challenges of understanding co-development when collaboration across boundaries is required. She is in the process of researching JSF through qualitative interviews which will be provided in a later article. Chapter 3 examines new product development in biotechnology. Kenneth Koput and Walter Powell make the case that growth of biotech firms depends on collaboration as a way of accessing knowledge and resources – partnering for learning. A rich network of relationships between firms with diverse expertise increases the innovation resources of a firm over time. Janine Stiles and Paul Williams shift the focus from collaboration across industrial firms to the relationship between firms and government agencies in Chapter 4. They examine the collaboration between multiple stakeholders involved in healthcare in Wales. The relationships are complex and their management challenging. The framework that results from examining this case provides insights for use in future investigations. Peter Lorange, in Chapter 5, examines another non-industrial form of collaboration – partnerships with business, and between major business schools in Europe and the USA. His examples include IMD, where he is President, in Switzerland with partnering MIT and other schools. A key finding is that three different strategies for the collaboration are available and that their fit with the nature of the partnership is a key to success of the collaboration. Chapter 6, by Melanie Schreiner and Daniel Corsten, examines the software industry from the perspective of the resource-based theory of the firm. They argue that collaborative capability represents a key resource that must be developed. They show that this capability has multiple and complementary dimensions: structural, cognitive, and affective. These dimensions of collaborative capability must be balanced for effective management of collaborative opportunities. The final four chapters draw from multiple theories and multiple examples to present general models. In Chapter 7, Stephen Fitzgerald bases his model on literature from seven fields to create a multi-level picture of collaborative capacity based on 10 constructs. The environment around the core of collaboration is complex and must be attended to for successful partnership. Yet, he acknowledges that a true model would be even more complex, since each construct is multi-faceted.

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In Chapter 8, Karen Higgins and Joseph Maciariello note that executives use networks to combine competencies and talents of individual firms for given projects to create competitive advantage. They draw on multiple examples and findings from a major research project to identify a model for leading complex collaboration in network organizations. They argue that the success of a network organization depends directly on the trust between the executives of the participating companies and that depends on integrity. In these days with ethics at the top of the organization being under scrutiny, the conclusion that values drive business success provides some hope. LuAnne Johnson and David Knoke address a similar issue in Chapter 9 when they argue that social capital held by members of the network is accessed and acquired through activating a relationship. The model apparently applies to intraorganizational work teams and to cross-organizational networks. However, the latter are more complex because of differentiated authority and power structures. Recognizing that collaboration is particularly complex when competitors partner, Joseph McGill and Michael Santoro conclude the book by examining strategic alliances in high technology industries. The dilemma in these alliances is sharing selected resources while simultaneously protecting others from unintended transfer. They use resource-based, transaction cost, and industrial organization economic theories to model the risks and rewards of collaboration. The model is based on two dimensions: resource interdependence and competitive interdependence. When both of these are high, collaboration reaches its most complex level. Michael M. Beyerlein Douglas A. Johnson Susan T. Beyerlein The Editors

REFERENCE Pacanowsky, M. (1995). Team tools for wicked problems. W. L. Gore & Associates Inc. Organizational Dynamics, 23(3), 36–52.

DEVELOPING COMPLEX COLLABORATIONS: BASIC PRINCIPLES TO GUIDE DESIGN AND IMPLEMENTATION夽 Don Mankin, Susan Cohen and Stephen P. Fitzgerald INTRODUCTION People have worked together since the beginnings of human time. Since then the forms of collaboration have barely changed. While a group of laborers building the pyramids of Egypt might seem to bear little resemblance to a team of machine operators working in a plant, they actually have much in common. Both groups are made up of people of similar backgrounds with clear loyalties and interests, interacting face-to-face to perform relatively well-defined tasks in pursuit of a shared goal. But things have changed in recent years – new technologies have made the world a smaller place and altered the nature of work, competition and markets have become global, and knowledge is now the most important resource for organizations trying to make their way through an increasingly complex world. As a result, traditional forms of collaboration are no longer sufficient for competing effectively in this new, more demanding, global business environment. 夽 This chapter is adapted from Don Mankin and Susan Cohen’s book “Business without boundaries: An action framework for collaborating across time, distance, organization and culture” (Jossey-Bass, 2004).

Complex Collaboration: Building the Capabilities for Working Across Boundaries Advances in Interdisciplinary Studies of Work Teams, Volume 10, 1–26 Copyright © 2004 by Elsevier Ltd. All rights of reproduction in any form reserved ISSN: 1572-0977/doi:10.1016/S1572-0977(04)10001-0

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To meet constantly changing conditions and demands, business has to transcend boundaries to get what it needs regardless of where it exists – geographically, organizationally and functionally. Remaining competitive in the new global economy means collaborating across time, distance, organization and culture. Organizations now have to go further to find the right pieces and rapidly pull them together to create the best fit for their purposes. They also have to be able to take these collaborations apart just as rapidly when circumstances change and start over again with different pieces. In short, they need more complex collaborations to address the challenges of a more complex world. These new collaborative forms are not like the teams of recent years past. They can be strategic partnerships among multiple organizations with similar stakes in the outcome of the project. Or they may involve virtual collaborations among people and teams working in different parts of the world. Value chains – relationships among different organizations to produce a product or service that is primarily identified with one primary organization – are yet another collaborative form. What makes these collaborations so complex are the number of people involved, the multiple organizational contexts within which they must function, and the potential psychological, cultural, and geographical distances that must be overcome. That is what this chapter is about – how to span these distances and transcend these boundaries to create collaborations that can address the business challenges of the new global economy. In this chapter we will address this issue by describing the basic principles for the design of complex collaborations that emerged from our analysis of three case studies. Before that, we need to get a better understanding of what we mean by the expression, “complex collaboration,” the characteristics of these collaborations, and the unique challenges they present.

THE NEW WORLD OF “COMPLEX COLLABORATION” This is one of those situations where it’s easier to define an expression by first describing its opposite, a “simple collaboration,” and then to compare a complex collaboration against this base line. A simple collaboration is an ideal case – a situation that involves no barriers to overcome and where the collaborative process can flow unobstructed. The characteristics of simple collaborations and of their more complex counterparts are summarized in Fig. 1. One characteristic of a simple collaboration is a simple task, where the inputs are predictable and manageable and where the procedures for processing these inputs are well defined. These are “routine” tasks and are characterized by low

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Fig. 1. Simple versus Complex Collaborations. Source: Business Without Boundaries. Copyright 2004 by John Wiley & Sons, Inc. Used by permission.

“uncertainty” (Pava, 1983). A non routine or highly uncertain task – one in which the nature and timing of the inputs are difficult to predict and the task procedures are not predetermined but require judgement – is more complex. What is typically referred to these days as knowledge work is characterized by high task uncertainty (Mohrman et al., 1995). New product development, new program development, process improvement, and the buying, selling and manufacturing decisions involved in global supply chains would be examples of non-routine, highly-uncertain, and therefore, more complex tasks. The simplest kind of collaboration also involves only two people. With less than that, you do not have a collaboration. With the addition of more people to the collaboration, the possibility of different goals, points of view, personalities, etc. increases geometrically, as does the potential level of complexity. In fact, differences of any kind make the collaborative task more complex. Two very similar people do not need to spend a great deal of time understanding each other’s point of view, language, and expectations. The more diversity involved

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in the collaboration, the more obstacles to be overcome before the collaborators can successfully complete their task. Although everyone is now familiar with the challenges of cultural diversity, the challenges of organizational diversity may be less obvious but are just as important. People from different organizations involved in an interorganizational collaboration bring different agendas, goals, points of view, and even different cultures to the collaboration, making these collaborations far more complex and challenging than if they were from the same organization (Park & Ungson, 1997; Saxton, 1997). Similarly, people from different functional units – engineering, manufacturing, marketing – within the same organization bring their different professional “thought worlds” (Dougherty, 1992) or culture into the collaborative mix, making this more complex than a collaboration among two like minded engineers, for example. Face-to-face collaboration is simpler than virtual collaboration. The immediacy, almost instantaneous reciprocity, richness, and social cues of a face-to-face interaction generally make it easier for two or more people to collaborate if they are “co-located” and can, therefore, interact face-to-face when they need to. If they have to interact “virtually” via media that are less rich, more impersonal, and feature time delays between the back and forth responses that characterize successful collaborations, their task becomes more complex and difficult (Nemiro, 2003a). All of these factors can contribute to the complexity of a collaboration. “Complexity” is a continuum, not an “either/or” situation. Therefore, the important issue is not whether a collaboration is complex or not, but how complex it is. The more complex the collaboration, the more effort required to make it work. The challenge is to overcome the difficulty and compensate for the complexity. How to do that is the focus of this chapter.

ABOUT OUR CASE STUDIES This chapter is based on three very different case studies reflecting widely diverging purposes, forms, and circumstances. The first case features interorganizational collaborations among the John Deere Construction and Forestry Equipment Company and various John Deere dealerships and two-year technical colleges located throughout the United States. The purpose of the collaborations was to develop training programs for John Deere construction equipment service technicians, which were in short supply at the time the program was initiated. The case includes the overall program run by Deere – which initiates, facilitates and supports these programs nationwide – as well as two projects that have been conducted under the auspices of the program in different regions of the United States. This was the first case we examined so we had the opportunity to follow

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this case over an extended period of time. As a result we were able to observe the ebb and flow of a long term project – from the initial uncertainties as participants from different organizations feel each other out, through the development of critical relationships and trust, to the eventual pulling back as changing economic conditions produce different priorities. The second case shifts the focus to cross cultural collaboration, particularly collaboration across international boundaries. Only one company is involved in this case, the Radica Games Group, Inc., one of the leading developers and manufacturers of handheld electronic games and video game controllers in the world. This case also includes two projects, the development of the Bass Fishin’ Game in the mid-1990s and the more recent project to develop controllers for the video game consoles produced by Nintendo, Sony, and Microsoft. The Bass Fishin’ Game project involved different teams in Dallas, Hong Kong and Radica’s factory in Southern China; the Controller projects involved the same sites plus a team from a company in the United Kingdom that was acquired in the late 1990s. How they partitioned, allocated and integrated tasks among these different sites is one of the more interesting features of this case. The international nature of the case also enables us to take a close look at the challenges of collaboration across dramatically different cultures. We see how the CEO, Bob Davids, and his right hand man, S. W. Lam, an engineer from Hong Kong with a long-term interest in Western management ideas, collaborated early on in the shaping of the unique culture of this multinational company. We also see Lam’s critical role in the Bass Fishin’ Game project as a cultural and functional liaison between the teams in Dallas and Hong Kong. With the acquisition of the company from the U.K. several years later, Radica quickly became larger and even more dispersed and culturally diverse. The tensions and stresses associated with integrating the new site added yet another challenge, a challenge that was exacerbated by the intense time and performance pressures inherent to product development in the toy and game business. The third case also features an interorganizational collaboration, but with a very important difference. While the first case involved multiple organizations in a project that was only indirectly related to the core business of most of the organizations involved in the case, the third case focuses on a supply chain collaboration where interorganizational collaboration is not just the means, but also the end. The case focuses on Solectron, one of the pioneers in the electronics manufacturing services industry (EMS), an industry that is the epitome of the increasingly global and interrorganizational nature of modern manufacturing. In their evolution over the years from contract manufacturer to “global supply chain facilitator,” Solectron’s role now involves the facilitation of the entire supply chain, not just acting as one of the links in this chain. One could argue that collaboration is now the very core of their business.

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Since close collaboration is intrinsic to supply chains, the interorganizational collaborations in the Solectron case are more tightly linked and critical to the success of all of the parties involved in the collaboration than they are in the John Deere case. In fact, close collaboration with customers and suppliers is a particularly important element in Solectron’s new strategic direction. In this case we see how Solectron executes this strategy and supports their new emphasis, especially via the extensive use of performance metrics and information technology. The case also examines one of their most far reaching efforts to date, their close collaboration with their customer Brocade, a producer of data network storage systems. This close collaboration is especially apparent in the innovative logistics initiative, which involved a Solectron employee serving on site, in effect, as Brocade’s logistics department. This initiative demonstrates the challenges, risks, and rewards that go along with the blurring of boundaries in global supply chain collaborations that seem to grow closer and more complex every day. For each case we interviewed about 20–25 people who were either directly involved in the collaborations or were close enough to the projects to provide additional details and supplementary perspectives. The actual names of the organizations and individuals are presented in this paper with the exception of the John Deere case. The John Deere names are real, but the names of the other organizations and individuals in that case are fictitious. Before we describe the factors and principles that emerged from our analysis of these cases, we need to say a few words about how we approached that analysis, our perspective on the kinds of factors and principles we expected to find, and the framework we used to organize and understand our findings.

ABOUT OUR PERSPECTIVE AND FRAMEWORK We analyzed the case studies by identifying the critical success factors in each case. We grouped the factors into four broad categories that fit the kind of collaborations we examined in our case studies. The categories are:
organizational level factors – the characteristics of the organizations and teams involved in the collaboration (e.g. culture) and of the relationship among them (e.g. shared goals, complementary capabilities).
structure of the collaboration – The role of structure is to make complex collaborations less complex and more manageable by reducing uncertainty and increasing predictability. Simple collaborations among just a few people working for the same organization can be structured “on the fly” – spontaneously, informally, and as the need arises. As we will see in the following, complex

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collaborations require proactive structuring in the form of formal agreements (e.g. contracts); well-defined roles, tasks, responsibilities, and decision-making processes; and the like. Structure makes it easier for the participants to get a handle on the many issues, problems and challenges they have to face to make these collaborations work.
characteristics of key people and their relationships – personality and skills of people in critical roles and the relationships among these people.
collaboration process – how the people involved in the collaboration work together (e.g. the nature and style of leadership, how they communicate, the norms that guided their interactions, etc.). What we present in the next several pages is the integration of the findings, the critical success factors, from all three cases (the full case descriptions and analyses for each case are presented in Mankin & Cohen, 2004). These critical success factors help define basic principles that apply to all of the cases. In effect, we move from the critical success factors for each case to the basic principles that underlie all of our cases.

PRINCIPLES IN COLLABORATION DESIGN What can we learn from collaborations as varied as those in our cases? That is the purpose of this section – to pull together all of the separate findings from the three cases to identify basic principles for the design of complex collaborations. Table 1 presents these basic principles. All three of our cases demonstrate these principles in action, though their specific manifestations often vary from case to case. These basic principles can be used as a foundation for the design and implementation of complex collaborations, regardless of the forms they take or the conditions under which they operate (see Mankin & Cohen, 2004 for an action framework based on these principles). The Table and our description of the principles follow the organizing framework we described in the preceding section. The logical place to begin is with the highest level factors, those that define the context (Fitzgerald, 2003) and entity within which the complex collaborations unfold.

Organization The basic principles at the organizational level fall into three loosely defined categories. The first category includes those principles that bring teams and organizations together – we describe them as “magnetic forces.” They comprise the raison

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Table 1. Basic Principles in the Design of Complex Collaborations. Basic Principles Organization Shared goals Complementary capabilities Compatible cultures Bias for performance Mutual respect and trust High level management support Access to resources Prior experience Structure Formal roles, tasks, expectations and understandings Charter Formerly-defined liaison roles Special governance structures All entities represented Clarity and simplicity Clear decision authority Information, performance metrics, and information systems People and relationships Liaison roles and collaborating pairs Lateral skills Collaborative process Facilitative but adaptable leadership Frequent communications among participants and with external stakeholders via multiple means Face-to-face interactions and relationship building Attitudes, expectations, and norms Mutual respect and trust Communication norms (cultural sensitivity, 24 hour design) Formal and informal learning processes Adaptable goals and plans Utility of early wins Fun and playfulness

d’etre for the projects. The second category is the “glue” that helps keep them together, and the third includes the factors that propel the collaboration forward. The Magnetic Forces That Pull Them Together Of the organizational level factors, shared goals (Gomes-Casseres, 1993) and complementary capabilities (Doz, 1996) are a good starting point. In effect, they are what pull together the different organizations and teams involved in a

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complex collaboration; they provide the reason for them to collaborate. This is particularly easy to see in interorganizational collaborations such as those in the John Deere case. All of the organizations in that case had a stake in the success of the projects, albeit for different reasons. For John Deere, an on-going supply of well-trained service technicians helps them sell equipment; for the dealers, the revenues generated from servicing this equipment is one of their fastest growing sources of profit; for the colleges, the new programs and the students they attract is the coin of their realm. All of the organizations bring different capabilities to the mix – equipment for the students to learn on from the dealers; cachet, resources and wide spread experience from Deere; and expertise in curriculum development and instruction from the colleges. Without these shared goals and complementary capabilities, the collaborations would never have been able to get off the ground. These factors were also critical in the Solectron and Radica cases. Shared goals and complementary capabilities are essentially a “given” in the contract manufacturing business and are fundamental to the very nature of supply chains. They are also critical to new product development efforts, such as those conducted at Radica, involving as they do intra-organizational collaborations between marketing, design, engineering and manufacturing to develop new products. The Glue That Keeps Them Together The glue that keeps collaborating organizations and teams together is their compatible cultures (Doz, 1996; Dyer & Singh, 1998). We can see this factor in play in both Brocade’s and Solectron’s willingness to take risks and try new things – for example, by placing a Solectron employee in a sensitive position on-site at Brocade. Similarly, all of the organizations involved in the John Deere programs shared a commitment to hands-on technical careers in the construction industry, and their cultures tended to reflect the traditional values of this industry. The Radica case also illustrates this factor as well as the two dimensions that are most important to a supportive, collaborative culture. Despite the profound cultural differences between the product development team in Dallas and the engineering design team in Hong Kong, they both shared a commitment to “getting the product out the door.” In the toy and game industry if new products are not on the market in time for the Christmas season, the company risks losing out on the bulk of their sales for the year. Companies that do not have strong bias for performance do not last long in the toy and game business. The Radica case also illustrates the other side of this cultural coin. Mutual respect and trust (Inkpen & Currall, 1998; Ring & Van de Ven, 1994) played a critical role in the success of the Bass Fishin’ Game project. The CEO, Bob Davids, with the help of his cultural liaison, S. W. Lam, spent several years

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before the project intentionally and explicitly developing a culture of mutual trust and respect throughout the company. This culture laid the foundation for the project by guiding the kind of behavior needed to collaborate effectively across their considerable geographic, temporal and cultural differences. Without this culture, and the norms and behavior through which this culture was expressed, the company would not have been able to pull off this crucial project, especially given the time pressures they faced and the stakes involved. This cultural dimension was also a significant factor in the other cases, but nowhere was its role more dramatically illustrated than in the Radica case. The Factors That Propel Them Forward We now turn our attention to a number of factors that enable collaborating organizations and teams to continue collaborating and carry out these projects over time. One of the most important is high level management support and the access to resources that typically accompanies that support (Nemiro, 2003b). This was one of the most frequently mentioned success factors in all three of our cases. In the John Deere case, for example, high level support from the various partners fluctuated throughout the projects as personnel, priorities and other circumstances changed. When there was high-level support from all of the partners, the projects moved along, when there wasn’t, the projects stalled. The actions of the EVP for one of the dealerships provides an object lesson in what the expression “high level support” means in operation, transforming this obvious clich´e into a blueprint for executive action. First, prior to his involvement in this project he already had a reputation for “walking his talk.” He talked a great deal about how important the project was and backed up his “talk” by pressuring individual dealer stores to provide internships, tuition support, and jobs to students after they graduated from the program. One of his most important actions was to assign one of his employees almost full time to the project to serve as liaison and representative and provided her with a budget to support her role in this project. Our last principle in this category, prior experience with complex collaboration (Fitzgerald, 2003, Inkpen & Currall, 1998; Khanna, 1998), was only explicitly mentioned in the John Deere interviews, but it was at least implicit in the other two cases. Almost all of Solectron’s customers have used contract manufacturers like Solectron for years. In addition, Solectron only collaborates closely with their 100 or so best suppliers. And, the way a company becomes a “best supplier” is to have enough previous experience with Solectron to build up the kind of track record needed to qualify for that status. This factor was also an issue at Radica on the Controller projects after their acquisition of the company in the UK. Because of their history of collaboration on the Bass Fishin’ Game project, the Dallas and Hong Kong teams had little

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difficulty working together on the Controller projects. On the other hand, the UK designers from the newly acquired company did have some initial difficulty communicating with the Hong Kong engineers, and vice-versa. The employees at the two sites had never worked together before, so they were unfamiliar with each other’s language habits and cultural norms and sensitivities. Over time, as they became more familiar with each other’s culture and language constraints, they learned how to avoid many of their earlier communication problems and worked together more effectively from there-on-in. It seems clear from the Radica case, and is at least suggested by the other two cases, that previous experience may develop collaboration skills and possibly even help build a culture of relationships that can lay the groundwork for future collaborations across multiple boundaries.

Structure The structural principles also fall into three categories, though the categories do not seem to reflect as clear a logic as the categories in the previous section. The first category deals with formal roles for the entities involved in the collaborations – individuals, teams and organizations – the responsibilities that go along with these roles, and the relationships among the roles. The second category focuses on governance and authority structures – i.e. how projects are managed and decisions made. The third category has to do with how these roles and structures are supported, primarily via information and information technology. Formal Roles, Tasks, Expectations, and Understandings This principle manifests itself in very different ways in each of our cases. In the Solectron case it was in the form of formal contracts with the company’s suppliers and customers. At first glance this might appear too obvious to even mention. In a business where pennies per part can add up very quickly and delays in delivery schedules can shut down production, a formal contract specifying costs, delivery date and penalties for failure to perform would almost seem to be a given. According to one of our interviewees, however, a VP in the materials organization, the wide spread use of formal contracts is a relatively recent development in the electronic manufacturing services industry. Personal relationships and “handshake” deals used to be the norm in this industry. In recent years, though, relationships between Solectron and its suppliers have become “more than just a couple of beers and hot dogs,” but now have to be “based on good business principles.” Not surprisingly, these good business principles include formal contracts.

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Formal contracts were not as relevant in the John Deere and Radica cases, since nothing was being bought or sold among the participants. However, the basic principle still applies though the forms it takes vary from case to case. In the John Deere case, for example, there was some initial uncertainty about participants’ roles, responsibilities, and boundaries which slowed down both projects in their early stages. More formal documentation of these roles and other, related issues such as decision-making processes – in the form of a charter, for example (Dowling, 2003; Justice & Jamieson, 1999) – would have helped. In the Radica case, each team was given a well-defined goal, tasks were identified and allocated based on these goals, and then the tasks were integrated via shared understandings about what to communicate, when, and by which means. These task designs served the same purpose as formal contracts specifying roles, responsibilities and expectations. While the issues that need to be formalized depend on the nature of the collaboration – e.g. products, prices, and delivery dates for supply chain collaborations vs. roles and responsibilities for joint interorganizational projects – all complex collaborations require formally-defined liaison roles. In all three of our cases, people in these roles were responsible for integrating the teams, organizations and cultures involved in the collaborations. Without them, the projects would have failed. Too often, in an attempt to save money and resources, roles such as these are left to chance and good intentions, to be filled by whoever has the inclination and the time. But there is rarely time left over from other responsibilities, especially when these other responsibilities are important enough to be formal job requirements. Informal roles like this are rarely fulfilled, or at least fulfilled well. Therefore, liaison roles need to be created proactively and intentionally. Designating a formal liaison role with distinct responsibilities increases the likelihood that these responsibilities will actually be carried out. Creating this role is a design issue, a structural intervention that formalizes the role to make sure that it is not overlooked and that it receives the support, recognition and attention it deserves. Since liaison roles are so inextricably linked with the qualities of the people who fill those roles and the relationships among them, we will address this issue again in the section on “people and their interrelationships.” Special Governance and Authority Structures This principle is most clearly seen in the John Deere case. For each project, there was an advisory team to oversee the project and a separate implementation team (with some overlapping members) to carry it out. Special governance structures were not needed in the Solectron case, however, since the nature of their business is interorganizational collaboration and they have ongoing structures

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and processes in place, both formal and informal, to deal with their supply chain relationships. At Radica, the CEO acted, in effect, as the “special governance structure” for the Bass Fishin’ Game project by participating closely in the project from beginning to end. This informal approach worked well at the time because the organization was small, but a more formal structure was created when Radica grew larger and more complex, after their acquisition of the UK unit. Our findings suggest a number of criteria that can be used to design these governance structures. First, the structures need to ensure that all of the entities (organizations and teams) involved in the project are represented in the governance structure. Second, since interorganizational collaborations frequently involve organizations and/or people that have not previously worked together, simplicity and clarity is critical, especially if there are more than two organizations involved in the collaboration. In other words, the structure should be as simple as possible to minimize confusion, especially in the early stages of the project when the different parties are trying to figure out who everyone is, the roles they play, and the organizations they represent. The rule of thumb is to create the simplest structure that will enable the work to get done while providing adequate representation for all of the critical parties involved in the collaboration. The overlapping advisory groups and implementation teams used in the two John Deere projects are good examples of this tradeoff among simplicity, representation, and an efficient way to get work done. The advisory group provided for broad representation and access to a wide range of perspectives, experience and expertise to guide the projects. The implementation team made it possible for a smaller group of individuals, representing the organizations with the greatest stakes in the project, to dedicate time necessary for carrying out the day-to-day tasks. A third rule of thumb suggested by our cases is to create a clear decision authority, especially if the work is “high intensity” – i.e. critical to the success of the organizations, requires close collaboration, and is performed under significant time pressures. At Radica, the CEO was the clear decision authority in the Bass Fishin’ Game project. After the company acquired the UK unit, the new CEO could no longer be as closely involved, so the lines of authority became murky, at least for a while. This is one of the reasons it took so long to resolve the differences which slowed down the Controller projects in the early stages. As this last example illustrates, it is important to create this authority early on, before conflicts emerge. During the heat of battle is not the best time to make decisions about how best to make decisions. A clear decision authority was not as necessary for the John Deere projects, since they were under less time pressure and the projects were not as critical. Therefore, these collaborations functioned more informally and democratically. This suggests a general conclusion; the more

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critical the project and the greater the time pressures, the closer the collaborators need to work together and the greater the need for explicit and unambiguous decision-making processes, structures and authority. Information, Performance Metrics, and Information Technology and Systems In his ground-breaking book on organization design, Jay Galbraith argued that “the greater the task uncertainty, the greater the amount of information that must be processed among decision makers during task execution in order to achieve a given level of performance” (1973, p. 4). As we argued in the introduction to this paper, increased task uncertainty makes collaborations more complex. Therefore, more complex collaborations require more information – and more information technology – to manage the uncertainty and make these projects more manageable. We can see the importance of this factor by comparing the John Deere case with Solectron. The latter is more complex – more organizations (suppliers and customers), different kinds of relationships (with suppliers vs customers), more dispersed sites, greater time pressures, and outcomes that are more critical to the companies involved. Therefore, the use of performance metrics and other information is much greater. The conclusion that we can draw from this is that the more complex the collaboration, the more information and information technology are needed to support the collaborative relationships and processes. We see a similar relationship when we compare the two projects at Radica. The earlier, simpler Bass Fishin’ Game project was able to make do with fax machines and telephones, while the Controller projects needed technology that was far more complex, so they added email and 3-D design systems to the mix. We may be able to extrapolate from this conclusion about information to an even broader conclusion about structure in general. The totality of findings for this category supports one of the basic assumptions and premises upon which this chapter is based, that complex collaborations require significant amounts of structure to make the complexity more manageable; the more complex the collaboration, the more structure may be required. We saw this clearly as we moved from the John Deere case to Radica and then to Solectron. New layers of complexity were added with each case as tasks, roles, and relationships became more formal, less ad hoc, and more highly articulated and developed.

People and Their Interrelationships The principles in this category are few, straightforward and very basic. They are so closely related and universal that they comprise a foundation which may very well underlie all collaboration, complex or otherwise. This may be where all

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successful collaborations begin, with good relationships among competent people in the right roles. Liaison Roles and Collaborating Pairs This is one of the most compelling and consistent findings that emerged from our analyses of all three cases. As we mentioned earlier, liaison roles are actually structural issues since they are concerned with how tasks and roles are structured and designed, but the connection between the roles and the people who fill these roles is so close that it is easier to discuss these two issues together. Liaison roles are actually a kind of “integrating role,” which Jay Galbraith describes as an effective means to achieve “lateral coordination” across “functional specialization, business diversification, and global dispersion” (1994, p. 87). According to Galbraith, . . . these differences make it more difficult to integrate all subtasks into the completion of the whole task. The different specialities, countries, and businesses all have their own interests, constituencies, and ways of thinking. It is the task of the integrator to span these differences and achieve coordinated outcomes. Thus, the integrating role is to obtain better coordination, as well as more coordination (p. 87).

Liaison roles played a critical part in the success of the collaborations in all of our cases. Lam single handedly played that role for the Bass Fishin’ Game project at Radica, linking the Hong Kong and Dallas teams, as well as crossing the cultural and functional boundaries separating both locations. In most of the other instances throughout the three cases, the lateral integration was accomplished by “collaborative pairs” – i.e. designated individuals at each site responsible for working closely on common tasks with their counterpart(s) in similar roles at the other sites. For example, the relationship between the heads of the North America and UK divisions at Radica helped to resolve some of the initial tensions between these two units following the acquisition of the latter. These collaborative pairings are also critical at the operational level. In the John Deere case, it was the strong task-based relationship between two mid-level people serving in liaison roles that enabled one of the projects to get off the ground and helped sustain the project through its difficult initial months. Similar relationships among key liaisons at both the managerial and operational level were critical to the success of the Solectron-Brocade collaborations. Although collaborating pairs were the norm in most cases and instances, Lam’s example suggests another possible means for fulfilling this function – i.e. the single liaison person who effectively integrates separate organizations or teams by him or herself. We suspect that Lam was able to fulfill the liaison role by himself because the units he spanned already had close ties, and he had significant experience and

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relationships in both. We found another example of a single liaison person spanning two sites in the Solectron case. The person was also Asian, linked sites in Asia and North America, had spent time at both sites, and was fluent in both English and the language of the Asian site (Malay, in the latter case). In addition, like the Radica case the organizational separation was relatively small since both sites were part of Solectron. Aside from these two examples, the linking function happened via collaborating pairs, probably because the “organizational separation” was too great and no one had similar experience at all of the sites where tasks had to be integrated. All of this suggests a corollary to the basic principle of liaison people and collaborating pairs. Collaborations across different organizations almost always require separate liaison people to represent each of the organizations involved in the collaboration – collaborating pairs or even integrating teams of liaison people when more than two organizations are involved. On the other hand, complex collaborations within a single organization can get by with one person serving as the link between the separate plants, teams or units if the sites have close ties and if the liaison person is able to effectively represent each site via his or her experience, cultural background, and language skills. In conclusion, we are struck by how often these collaborating pairs appeared in our cases and how important a role they seemed to play in their success. These pairings are the axes around which the complex collaborations revolve. The question then is how to ensure that these collaborative pairings work effectively. Part of the answer, as we have already noted, is to create these roles, explicitly and proactively. Another part of the answer is to put the right people in these roles. By “right” we mean people who can transcend differences to work on shared tasks with their counterparts on other teams and in other organizations. The special challenges of lateral integration require people with special qualities to fill these critical liaison roles. What are these special qualities? What is it about the liaison people we found that enabled them to fill these critically important liaison roles so effectively? Lateral Skills We explored these questions by identifying key people who functioned effectively in these roles, and asking them and others who worked closely with them to speculate on the traits and behaviors underlying their success. From this we have been able to put together the beginnings of a profile which describes the “lateral skills” we consider to be indispensable for anyone serving in these critically important and challenging roles. First and foremost, the necessary but not sufficient foundation for this quality is good interpersonal skills. But it is much more than that. It doesn’t take very

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much in the way of interpersonal skill to get along with and work effectively with someone who is very similar and who has the same basic values, interests and background. But working effectively with someone who is very different requires skills that go well beyond the ordinary. It requires the kind of skill that enables, for example, a businessman from Los Angeles and a Hong Kong engineer several years his junior to collaborate on the transformation of an entire organization and its culture, as happened at Radica during the years preceding the projects in our case. Perhaps one way to understand the difference between what are merely good interpersonal skills and what we mean by the more important lateral skills is to imagine a person who might be best described as a “congenial racist.” This is a person who is personable and gets along well with people who are similar in background and outlook and whose roots are in the same culture. On the other hand, this person has difficulty relating to anyone who has different experiences or points of view, or comes from a different cultural background. It takes a person with good lateral skills to work with someone who is very different. This a far more valuable set of skills – particularly in today’s multicultural, crossfunctional, and interorganizational workplace – and one that is much more difficult to find. To get a better handle on what we mean by “lateral skills” we go back to a definition we offered in our earlier book, “Teams and Technology” (Mankin et al., 1996). In that book, we describe lateral skills as the ability “to work effectively with people of different functional backgrounds, work experiences, knowledge bases and skills” (p. 97). What this means in terms of the preceding discussion is that people in collaborative pairs who possess strong lateral skills can transcend their differences to find a common ground. This common ground enables them to work together on mutual tasks to fulfill their shared goals. Our interviews, observations and previous work on this issue suggest that empathy plays an especially central role in lateral skills. By “empathy” we mean the ability to put oneself in another’s place, to be open to the opinions, concerns, perspectives and interests of others who are quite different. It also means the ability to transcend cultural boundaries, to respect and appreciate differences, especially differences associated with national, ethnic and functional cultures. One of our examples from the Solectron case enables us to add some additional wrinkles to our emerging profile of good lateral skills. Everyone we interviewed about the Brocade-Solectron collaborations pointed to one person in particular as one of the most important reasons for the success of the logistics initiative. This person, Glenn, was the Solectron employee chosen to be the logistics liaison person on site at Brocade and was one half of the collaborating pair that was the critical operational axis for this initiative.

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Our interviewees were also very consistent in their descriptions of those qualities they thought made Glenn so effective in this role. They described him as being open to working with others, especially customers, and sensitive to their needs and concerns. “He wants to help,” one interviewee noted, “he wants to understand others’ issues and concerns so that he can serve them better.” According to his boss at Solectron, “Glenn does a really good job of listening. He really hears what you have to say.” Glenn is clearly empathic in the way we describe above, but he is also more than that. He views the people he works with as his customers and does his best to serve them well. He is able to put himself in the customer’s place. Because he can internalize their needs and make them his own, he understands their needs and can serve them better. This is empathy in the “service” of customer service. Glenn’s example also suggests another dimension. In his role as Solectron’s logistics liaison to Brocade he had access to confidential information about other EMSs – Solectron competitors – that Brocade also used. Therefore, he had to be very careful about how he handled the boundaries of his role. His care and sensitivity did not go unnoticed by his Brocade collaborators. Many of them used descriptors such as “integrity” and “inspires trust” to describe this dimension of his personality and behavior in this all important role. It is easy to see how this character trait could affect an individual’s performance in a liaison role, especially in an interorganizational collaboration where confidentiality and other boundary issues can be so important.

The Collaborative Process Consideration of the collaborative process logically follows a discussion of the people who are the participants in this process. How they interact, the means they use to collaborate, and their attitudes and state-of-mind as they execute their tasks – these are the remaining principles to be addressed in the design and implementation of complex collaborations. Leadership This is one of the first basic principles underlying the collaborative process. How could it be otherwise? Leadership is necessary for focused and sustained action for almost all work-related activity, complex collaborations included, and is necessary for getting the collaborative process started. Beyond the obvious statement that leadership of some sort is important, what is most significant is the particular style, form and approach that seems most appropriate for the conditions and nature of the collaboration.

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In all of our cases, leadership was generally facilitative and shared, but also adaptable to different circumstances and stages. That said, there were also some very important differences between the leadership of the John Deere projects, on the one hand, and the Radica and Solectron cases, on the other. As we noted earlier in this paper, the John Deere projects were “lower intensity” than the others – i.e. the projects did not have the same sense of urgency as the projects in the other cases, and they were not as critical to the success of the organizations involved in the projects. Therefore, leadership was generally facilitative and shared throughout the projects. On the other hand, the need to get “the product out of the door” in the Radica and Solectron projects required an approach that could quickly get more directive when necessary. This was especially apparent in the Bass Fishin’ Game project in the Radica case where the CEO would step in and make decisions about the design of the game when the members of the project team couldn’t agree or were reluctant to make the decision themselves. Communication Communication among participants as well as between participants and others not directly involved in the collaboration was also critical to the success of all of the cases. The participants in our cases communicated frequently with each other by whatever means they had at their disposal. They also communicated frequently with external stakeholders, particularly in the interorganizational collaborations – i.e. the John Deere and Solectron cases – where the project participants communicated regularly with their managers in their “home” organizations, as well as with others who provided critical support and were most impacted by the projects. Our cases demonstrate that face-to-face interaction is still one of the most important means of communication, not just for sharing information and working together on shared tasks but also for building and maintaining relationships. Over the last decade the idea of virtual collaboration has spread throughout the business world, promoted as the cure for skyrocketing travel costs, as the means for linking distant sites and collaborators, and so on. Every day, more and more business leaders, consultants, and writers are buying into the seductive vision of individuals interacting with each other via the internet or videoconferencing technology rather than face-to-face (FTF). Unfortunately, this fevered interest has tended to distort our perception of how work is actually changing in this era of global enterprise. Recent research and the experiences of many people on virtual teams offer a very different picture of the relative roles of virtual and FTF interaction in complex collaboration. Maznevski and Athanassiou (2004), writing in the recent book, Virtual Teams That Work (Gibson & Cohen, 2003), succinctly capture the new conventional wisdom “[F]or a virtual team, the single greatest challenge is building relationships . . . [and]

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it is easier,” they continue, “to build strong ties in face-to-face relationships” (p. 210). The reality of virtual collaboration is that there is no substitute for FTF interaction. Our findings are consistent with this emerging consensus. Face-to-face interaction was an important factor in all of our cases. This was even true in the Radica projects where the different teams involved in the projects were so widely dispersed – in Dallas, Hong Kong, southern China, and in the Controller projects, the UK. The design of the tasks in both the Bass Fishin’ Game project and the Controller projects allowed for intensive FTF interaction where it was most needed – e.g. among the product designers in Dallas and among the engineers in Hong Kong. However, even in this case, Lam, the CEO and others traveled when they had to, and several other people felt that they could have worked more effectively with their collaborators at other sites if they were able to travel more often. Face-to-face interaction is particularly important in building relationships, especially the collaborating pairs described in the previous section. The importance of this issue is succinctly described by the head of Radica’s North America division, who played a major role in resolving the conflict that slowed down the Controller projects following the acquisition of the company from the UK. “Solutions work out much better if you have a personal relationship with the person you are dealing with,” she notes in reference to her relationship with her UK counterpart. “If you have the opportunity to spend some time with that person, then it’s easier to work out issues via email or phone.” With respect to some of the initial difficulties between the two divisions, she concludes that “we would have solved it much faster if we could have gotten all of the key people together in the same room and had these meetings beforehand.” She sums this up well in her final words on the subject, “before I had an issue, I had a relationship,” a relationship, we would add, that was built on a foundation of face-to-face interaction. Of course, the problem is that FTF interaction is often not possible or far too expensive, especially in situations where collaborators are separated by great distances. In those situations the only choice is to make virtual collaboration work. What that means is learning when and how to use the media that are available – fax, phone, email and the world-wide web – and when and how to supplement these media with FTF interaction via meetings, co-location, and the like. In addition, many of the factors we have already described (e.g. structuring tasks) and will soon describe (e.g. communication norms) can help make virtual collaboration work. Attitudes, Expectations and Norms Complex collaborative processes require well-defined and explicit attitudes, norms, and expectations to guide these processes, especially those underpinning

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the prerequisite culture of mutual respect and trust (Fitzgerald, 2003, p. 86; Hood et al., 1993). This was especially important at Radica where the cultural and geographic differences were so great. That is why the CEO and Lam worked so diligently for so many years to create this culture and the norms that go along with it. Without this foundation, they never would have been able to transcend the formidable boundaries of time, distance, and culture so that this very complex collaboration could succeed. Norms that guide communications with other collaborators are also important. These norms include how often to communicate, by what means, and the need to acknowledge receipt of phone and email communications and provide a timely response. Also important are norms that call for sensitivity and judgment in all communications, particularly in email communications where the possibility of misinterpretations and unintended slights is so great (Nemiro, 2003a). When these communications span geographic and cultural distances, the challenges and potential consequences are even greater. International collaborations, for example, require that special attention be paid to cultural sensitivity, especially when email is the medium for communication. In addition, expectations about daily communications and responses might need to be established if the international collaborations cross significant distances and time zones, the work days of widely separated sites do not overlap, and significant time pressures are involved. The Radica Bass Fishin’ Game project is very instructive here. At the end of every work day, the product design team in Dallas would fax drawings to the engineering team in Hong Kong. Because of the 13-hour time difference, the drawings would be waiting when the engineers in Hong Kong arrived for work each morning. They would then work on the engineering designs and fax their responses back to the Dallas team by the end of the work day in Hong Kong – pointing out, for example, that the game features the Dallas team was asking for would raise the manufacturing costs above the targeted price point for the game. This process would go back and forth until the issues were resolved, much like passing a baton back and forth in a never-ending two-person relay race. These communication norms, coupled with the culture of mutual respect and trust that the CEO and Lam had worked so hard to develop, enabled this 24 hour design process to proceed unaccompanied by the rancor and tension that one might expect in situations marked by such intense time pressures and profound cultural differences. Learning Processes Once the collaboration is well underway, formal or informal learning processes can be used to monitor progress and explore how to improve the effectiveness of the collaborative process. All of the organizations involved in our cases either used

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some form of learning process or intended to do so in the near future. One of the best examples is the annual meetings jointly sponsored by Solectron and Brocade to address high level strategic issues in the increasingly close collaboration between the two companies. These meetings were usually attended by five to seven VPs and other senior level managers from the two companies, as well as by some of the key operational level people involved in the collaboration. The agenda typically included such items as an overview of the activities and developments of the past year, what the two companies had learned from the initiatives, the areas that needed improvement, and what they would focus on for the next year. The John Deere case demonstrates that these learning processes can lead to significant mid-course corrections. The slow economy during the early years of the decade led many of the organizations involved in the various programs to rethink their priorities. The programs continue but with more modest goals. This example illustrates that complex collaborations functioning in equally complex and dynamic times need to have goals and plans that are adaptable to changing conditions. This means reasonable goals, flexible plans, and a willingness on the part of the participants and their managers to change goals and plans when necessary. The Solectron-Brocade collaborations illustrate a corollary to this principle, the utility of “early wins” – modest but meaningful goals that can be achieved quickly. The logistics initiative was intentionally designed to produce “early wins” that would quickly build support for the initiative at Brocade and confidence and trust in Glenn. Fun and Playfulness Our last basic principle is perhaps the most difficult to get a handle on, at least in terms of how to make it happen. This was only occasionally mentioned in our interviews, but it was clear from the tone of the interviews that many people derived a great deal of intrinsic satisfaction from their participation in the projects, especially when things were going well. If this is an important principle, the logical question, then, is how to make this an actionable principle. In other words, how to make the collaborative experience pleasurable and fun? Our cases suggest an answer to this question, not because of what was done but what was apparently not done, or at least was not perceived to be important enough to be mentioned by our interviewees – i.e. specific team building activities, experiences, or even social events designed for the explicit purpose of having fun, rather than doing work. We have no doubts that there were some experiences of this sort in all of the projects, but they did not seem to play an important enough role for any one to cite them as a major factor in the success of their efforts. Since extrinsic sources of fun – parties, games, clowns, humor consultants – did not play a significant role in the projects, we can only conclude that the fun came from

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the intrinsic pleasures of doing a difficult job well. The other factors described here are what made it possible for the participants to have fun – to be challenged by the demands of a complex project, to meet these challenges by performing their tasks effectively, and to derive great satisfaction from the success of their efforts. In other words, fun is not the cause of their success, it is a byproduct of their successful efforts. Therefore, by focusing on the other factors, the fun will likely follow.

CONCLUSION: TOWARD AN ACTION FRAMEWORK FOR THE DESIGN OF COMPLEX COLLABORATIONS In this paper we have identified a number of basic principles for the design of complex collaborations. These principles apply in all three of our cases, and possibly to all forms and under all conditions. However, some circumstances can accentuate the importance of particular principles or make different aspects more salient. For example,
A performance-oriented culture, clear decision authority, and a more directive leadership approach are especially important in “high intensity” projects.
International collaborations require that more attention be paid to developing communication norms that emphasize cultural sensitivity.
Shared goals, complementary capabilities, and information sharing are more likely to be critical issues in collaborations among multiple organizations.
The more complex the collaboration, the greater the need for information, information technology, and performance metrics – in fact the greater the need for structure in general. All of these principles, plus the limited caveats and qualifications listed above, may be too complex for many managers and others who face the challenges of real world collaboration. Therefore, in these last few paragraphs we offer a “meta-principle” which underlies and integrates the basic principles we have described in the last several pages. For the most part, the basic principles are essentially specific manifestations of this overarching meta-principle. The meta-principle is much easier to keep in mind, and it may be all that is needed in many situations and projects. It is our hope that once the meta-principle is internalized and deeply grasped, the specific action steps to be taken will easily follow. They will flow naturally from the convergence between the logic of the principle and the particular conditions of each project.

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There are two threads that weave through the principles and help tie together what might otherwise look like a disconnected series of items in a long laundry list. One thread conveys the “soft side” of complex collaboration, i.e. the people, their relationships and how they work together. This is the foundation of all collaborations, complex or otherwise. This is where collaboration begins and the petri dish within which it breeds and grows. The second thread involves the structuring elements that support the collaboration – i.e. the infrastructure that helps focus action, informs decisions, buffers distraction, and improves efficiency. In and of itself, this structure is not the essence of collaboration. However, as we mentioned earlier, it does reduce uncertainty and confusion, increase predictability, and can make complex collaborations less complex and more manageable. Structure provides a safe harbor of predictability and stability within which creative collaborations can develop and thrive. These two threads weave throughout our principles. They are of course related and inseparable. Structure supports collaborative relationships, and these relationships produce structure. Both threads are needed to stitch the fabric of complex collaborations together; without both, the “garments” will fall apart. These are the fundamental truths that underlie our principles and our perspective on how to make complex collaborations work. The two threads represent the yin and yang of our meta-principle – the interdependence of structure and relationships. The synergy between the two can be summarized in four broad steps: (1) Collaborations start with relationships between the right people in critical liaison roles. Therefore, the first step is to explicitly and intentionally create these liaison roles and formalize these roles by defining specific responsibilities and requirements. (2) The next step is to put the right people in these roles – i.e. those with well-developed lateral skills. (3) After that, it is important to enable collaborative relationships to form among the people in these roles, by intention to initiate specific projects or by “enabled serendipity” – creating conditions that enable these relationships to form spontaneously around common interests which may evolve in time into joint projects. (4) Then the next steps are to use these relationships as the axes for launching a formal, more extensive effort by having the people in these relationships collaboratively design the structure (e.g. charters, governance and authority structures, performance metrics, etc.) that will help them focus on their collaborations and tasks. To state it as simply as possible, our meta-principle is to start with relationships among key people, then use the relationships to create the structure they need

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to do their work. By internalizing this meta-principle and using it as a mind set, plus referring to the specific principles for details as needed, managers and others should be able to design any complex collaboration, regardless of form, type or circumstances. Our working metaphor for the application of the basic principles is jazz. Neither the tightly orchestrated compositions of Stan Kenton – intricate, predictable, and smooth flowing – nor the free improvisations of Ornette Coleman – unpredictable, chaotic, and for many, very unsettling. Instead, the “jazz” of our framework is the music of Charley Parker and John Coltrane (before his cosmic period) which were characterized by improvisations on clearly stated themes. Like their music, the principles are meant to suggest approaches and inspire ideas, not to constrict action into narrowly defined boxes. In keeping with this metaphor, we encourage the “musicians” who read this chapter to follow their own muses and improvise their own melodies, coming back to the themes from time to time and keeping the score and the principles which underlie it squarely in mind. Like any good jazz musician, readers can improvise on the principles to create harmonious collaborations that transcend boundaries to produce deeply fulfilling performances.

REFERENCES Dougherty, D. (1992). Interpretative barriers to successful product innovation in large firms. Organizational Science, 3(2), 179–202. Doz, Y. L. (1996). The evolution of cooperation in strategic alliances: Initial conditions or learning processes. Strategic Management Journal, 17, 55–83. Dyer, J. H., & Singh, H. (1998). The relational view: Cooperative strategy and sources of interorganizational competitive advantage. Academy of Management Review, 23, 660–679. Dowling, K. (2003). Chartering your team for peak performance. In: M. M. Beyerlein, C. McGee, G. Klein, J. Nemiro & L. Broedling (Eds), The Collaborative Work Systems Fieldbook: Strategies for Building Successful Teams. San Francisco, CA: Jossey-Bass/Pfeiffer. Fitzgerald, S. P. (2003). Exploring collaborative capacity in a global chaordic alliance: The United Religions Initiative. Dissertation Abstracts International #AAT 3077445. Galbraith, J. R. (1973). Designing complex organizations. Reading, MA: Addison-Wesley. Galbraith, J. R. (1994). Competing with flexible lateral organizations (2nd ed.). Reading, MA: Addison-Wesley. Gibson, C. B., & Cohen, S. G. (Eds). (2003). Virtual teams that work: Creating conditions for virtual team effectiveness. San Francisco: Jossey-Bass. Gomes-Casseres, B. (1993, May 14). Managing international alliances: Conceptual framework. Harvard Business School Case #9–793–133, 1–20. Hood, J. N., Logsdon, J. M., & Thompson, J. K. (1993). Collaboration for social problem-solving: A process model. Business and Society, 32(1), 1–17.

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Inkpen, A. C., & Currall, S. C. (1998). The nature, antecedents, and consequences of joint venture trust. Journal of International Management, 4(1), 1–20. Justice, T., & Jamieson, D. W. (1999). The facilitator’s fieldbook (pp. 50–62). New York: AMACOM. Khanna, T. (1998). The scope of alliances. Organization Science, 9, 340–355. Mankin, D., Cohen, S. G., & Bikson, T. K. (1996). Teams and technology: Fulfilling the promise of the new organization. Boston: Harvard Business School Press. Mankin, D. A., & Cohen, S. G. (2004). Business without boundaries: An action framework for collaborating across time, distance, organization and culture. San Francisco: Jossey-Bass. Maznevski, M. L., & Athanassiou, N. A. (2004). Designing the knowledge-management infrastructure for virtual teams: Building and using social networks and social capital. In: C. B. Gibson & S. G. Cohen (Eds), Virtual Teams that Work: Creating Conditions for Virtual Team Effectiveness (pp 196–213). San Francisco: Jossey-Bass. Mohrman, S. A., Cohen, S. C., & Mohrman, A. M., Jr. (1995). Designing team-based organizations: New forms for knowledge work. San Francisco: Jossey-Bass. Nemiro, J. E. (2003a). How to effectively communicate virtually: Lessons from case studies of virtual teams. In: M. M. Beyerlein, C. McGee, G. Klein, J. Nemiro & L. Broedling (Eds), The Collaborative Work Systems Fieldbook: Strategies for Building Successful Teams. San Francisco, CA: Jossey-Bass/Pfeiffer. Nemiro, J. E. (2003b). Developing and assessing a climate for creativity in virtual teams. In: M. M. Beyerlein, C. McGee, G. Klein, J. Nemiro & L. Broedling (Eds), The Collaborative Work Systems Fieldbook: Strategies for Building Successful Teams. San Francisco, CA: Jossey-Bass/ Pfeiffer. Park, S. H., & Ungson, G. R. (1997). The effect of national culture, organizational complementarity, and economic motivation on joint venture dissolution. Academy of Management Journal, 40, 279–307. Pava, C. (1983). Managing new office technology: An organizational strategy. New York: Free Press. Ring, P. S., & Van de Ven, A. H. (1994). Developmental processes of cooperative interorganizational relationships. The Academy of Management Review, 19, 90–113. Saxton, T. (1997). The effects of partner and relationship characteristics on alliance outcomes. Academy of Management Journal, 40, 443–461.

CO-DEVELOPMENT: COLLABORATING ACROSS BOUNDARIES ON JOINT STRIKE FIGHTER Jude G. Olson ABSTRACT Product development becomes more complex when co-development involves multiple parties crossing boundaries of functions, companies, countries and even competitors. An interdisciplinary framework is needed to understand the challenges of structuring collaborative work within global product teams – especially in the research arenas of strategic partnerships, product development teams, collaboration, distributed work, organizational learning and new metaphors. The multi-party partnership of the Joint Strike Fighter Program at Lockheed Martin, the largest aerospace program in history, provides an illustration of the complex information-sharing and problem-solving challenges in aligning a large, distributed, global integrated product team in an environment where even connectivity is a challenge. It sets the stage for the innovative management approaches needed to build collaborative climates as well as research directions for the future.

At any point, it would have been easier to say, ‘This is too difficult. Let’s go back to the old way and split the plane up.’ But the management team made it clear that that was an unacceptable answer. And they were right. Neither of the three companies, individually, had the resources

Complex Collaboration: Building the Capabilities for Working Across Boundaries Advances in Interdisciplinary Studies of Work Teams, Volume 10, 27–58 Copyright © 2004 by Elsevier Ltd. All rights of reproduction in any form reserved ISSN: 1572-0977/doi:10.1016/S1572-0977(04)10002-2

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JUDE G. OLSON or the technology to make this happen. It took a collective team effort – pushing each other beyond our wildest dreams – to build this airplane. Martin Taylor, BAE Systems’ Program Manager for Joint Strike Fighter Lockheed and Northrop have battled each other for 60 years . . . in my career alone, we lost three out of four programs to Fort Worth. Those were knock-down-drag-out battles. At the time, I couldn’t believe it: We’re supposed to partner with these guys? Martin McLaughlin, Northrop’s Joint Strike Fighter Airframe Manager Running a three-partner team is not easy, but the deal bought us the power of three companies to combat Boeing . . . we realized that if we didn’t change the entire way we did business, we’d never beat Boeing. Mickey Blackwell, Lockheed Martin EVP (Breen, 2000, pp. 73–74)

THE JOINT STRIKE FIGHTER PROGRAM The challenge on the Joint Strike Fighter (JSF) program is to create collaboration between a disparate group of engineers, many of whom had previously been competitors. The special technical challenges also require an innovative management approach – including creating a collaborative climate and focusing and aligning a large, distributed, global, integrated product team. The JSF program is a tri-service, multi-national transformational weapon system with unique requirements recently won by Lockheed Martin in Fort Worth, Texas. Not only is it expected to be the most advanced fighter of its kind, it is expected to be “affordable,” driving transformation in military procurement and an industry known for its technical expertise, but not historically for its program management. As conceived by Lockheed Martin, JSF would represent a new kind of program as well as a complex organization built on collaborative teams and relationships. Recent acquisition reform in the Department of Defense contributed to making this largest aerospace program in history a “joint” model customized for three of our military services – the Navy, the Air Force and the Marine Corps as well as foreign customers – U.K., Netherlands, Italy, Turkey, Denmark, Norway, Canada. More than 3,000 aircraft will be designed, built, flown and supported with export sales. Tom Burbage, JSF Program Director, likens the organizational chart of JSF to a “jigsaw” puzzle – with many interdependent, sometimes conflicting or competing partnerships. The vision of collaboration among competitors was born on a rationale of selecting “Best Athletes” (people will lead Integrated Product Teams – regardless of whether they are employed by the prime contractor or by a partner) and using “Best Practices” (derived from Lessons Learned across partner companies) to give a competitive edge in winning the bid for the largest aerospace defense contract in history. Combining three fourths of the world’s tactical fighter

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expertise and industrial base in the United States and U.K., the Pentagon calculated that if the Air Force, Navy and Marines coordinated their planning and purchased the same plane together, they could slash the price tag to a more affordable one. The primary partners include: Lockheed Martin, Northrop Grumman and British Aerospace Systems (BAE). Other business partnerships include Lockheed Missiles & Information Systems, Fokker, Pratt & Whitney, Rolls Royce Allison and General Electric – as well as multiple key suppliers emphasizing supply chain management including TRW, Smiths Industries, Harris, Hamilton, Sundstrand, Honeywell and Moog-Parker, and others. JSF was conceived as a “world airplane.” This project, as it was designed, presented many paradoxical challenges that would strain conventional notions of organizing, including reframing the way companies construe traditionally competitive relationships. To cite but one example, the demand for “interoperability” would mean that other countries would be invited to share the costs of development. Companies from these host countries would then become eligible to compete as suppliers. To cite another unique challenge that strains traditional logics of organizing: In the U.S., the same airplane is expected to fill the needs of three military branches, even building a lift fan for the Marine STOVL version to lift vertically like a helicopter. The development process also faces unprecedented demands: engineers, vendors, suppliers, all of whom are expected to cooperate, would be using a novel digital design and logistics process. On the surface, a joint partnership to build the JSF is not so unusual. BAE and Northrop had teamed with McDonnell Douglas on the first round of the JSF competition. Lockheed had partnered with Boeing on the F/A-22 program. Typically, these projects consist of a prime contractor that doles out parts of the jet’s development to dozens of subcontractors and hundreds of smaller suppliers. These arrangements usually encourage predictable maladaptive behavior where the prime contractor browbeats the subcontractors and they, in turn, overcharge which results in delays and cost overruns (Fallows, 2002). Lockheed’s proposal offered BAE and Northrop a full-fledged strategic partnership in which the two companies would command a combined 30% stake in the program. Lockheed, Northrop and BAE people would work shoulder to shoulder to develop the entire aircraft. Lockheed brought in Burbage, a 21-year Lockheed veteran and Navy test pilot and graduate of the naval academy, to manage the complex collaboration that would be required to complete design and production goals. From the beginning, Burbage framed it as a challenge in managing collaboration rather than a challenge in managing complex technology. Burbage reflects on the challenge, “If one looks at JSF through the legacy management filters we have used in the past, it appears unmanageable. One

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of our ultimate challenges is to develop a JSF leadership and collaborative culture that will allow us to achieve success” (J. Olson, personal communication, October, 2002). This type of organization gives us a “living laboratory” for research on understanding collaborative start-ups and alliances. In taking an exploratory look at JSF, one can look at the literature of complex collaboration as if looking through an interdisciplinary lens or kaleidoscope. Different frames can give one a glimpse of different dimensions and when you turn it, you can see overlaps and interdependencies. The author is in the process of researching JSF through qualitative interviews which will be provided in a later article. This article provides a literature review to approach the interdisciplinary challenges of understanding co-development when collaboration across boundaries is required. The literature search intends to explore these questions and dimensions regarding complex collaborations: (1) What motivates partners to seek each other out and then stay together – innovation, new market needs, new capabilities, globalization? (2) Do they have the same vulnerabilities as in other alliances – disparate goals, lack of trust or lack of experience in partnering? (3) What are risk factors that lead to failures – different cultures, lack of integration, inability to learn? (4) What are key success factors that have been found in other partnerships – overcoming Not Invented Here (NIH) syndrome, structured processes, flexibility? (5) What can we apply from other collaborative settings – i.e. negotiations, International Government Organizations (IGO), union-management relations – to add to our understanding of the collaborative corporate world? (6) How do you balance cooperation with competition when your competitors are your partners? How do you overcome traditional win-lose strategies with multiple perspectives, thought-world’s and stakeholder creativity? (7) How does the composition and group processes of new product teams affect their ability to plan work, communicate and problem-solve? (8) What are the unique challenges faced by large companies when they organize to innovate? (9) What is the collective nature of multi-disciplinary work – creating new routines, systematic processes or chaos? (10) What are the communication and connectivity issues that geographically distributed work presents? (11) What does collective learning have to do with knowledge transfer and building community?

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(12) What new metaphors and models would enable us to look at collaborative work in new ways to better the understand the dynamics of complexity?

Strategic Partnerships and Start-ups Purpose In large companies, the primary reason for co-development is innovation. Faster time-to-market and more development output are the top reasons for small companies (Performance Management Group, 2003). Progress in co-development seems to be needed on multiple fronts: strategy, processes and tools. “Companies can no longer rely solely on in-house resources” is echoed in The Futurist where is it estimated that 50% of all technology developed will be transferred between countries by corporations or universities (Segil, 2002). Fifty-two percent of pharmaceutical products to be launched in 2002 were associated with alliances vs. 38% in 2001 and 25% in 2000. The accelerated growth through alliances is predicted to build the biopharmaceutical industry of the future (Dionne, 2002). This mirrors strategic reasons for forming acquisitions and alliances cited by others (Dionne, 2002; Henricks, 1991; Lev, 2001; Palcheck & Stewart, 2002) which include: strengthening competitive position in an existing market and gaining access to knowledge – obtaining competence or establishing a leadership position in technology or a market. Other companies may try to create a growth engine using products as a springboard for next generation or facilitate value creation through research, learning, development of products and services to gain speed to market. Alliances usually require a mixture of risk-sharing, overall integrated technology platform, globalization and shorter windows of opportunity – to create shorter product design cycles. A co-evolutionary theory of strategic alliances may be seen in the context of the adaptation choices of a firm over time. These alliances are embedded in a firm’s strategic portfolio and co-evolve with the firm’s strategy, the institutional, organizational and competitive environments and with management intent for the alliance (Koza & Lewin, 1998). This theory of co-evolution has over recent years, seen an increase in studies of organization adaptation at different levels of analysis – i.e. evolution of organizations cannot be understood independently from the simultaneous evolution of the environment (McKelvey, 1997). Lewin has advanced a theory of the evolution of new organization forms as an “outcome of the co-evolution of the competitive environment, firm intentionality and the institutional environment of the firm under conditions of stochastic or chaotic environmental uncertainty” (Lewin et al., 1998).

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One strategic model of alliances uses “exploration” and “exploitation” in organizations learning to provide a framework for linking adaptations at the firm level to changes occurring at the level of the organizational population. In terms of complexity theory, exploration is associated with prospecting for “new landscapes; discovering new opportunities for wealth creation and above average returns and involves basic research, invention, risk-taking, building new capabilities and entering new lines of business and investments in the firm’s absorptive capacity” (Cohen & Levinthal, 1989). Exploitation is associated with increasing productivity of employed capital and assets – “improving and refining existing capabilities and technologies, standardization, routinization, and systematic cost reduction” (Levinthal & March, 1993). Here the firm’s choice to enter into an alliance can be distinguished in terms of its motivation to exploit an existing capability or to explore for new opportunities. Levinthal and March (1993, p. 105) argue that the “survival of the firm is dependent upon the firm’s ability to engage in enough exploitation to insure the organization’s current viability and engage in enough exploration to insure its future viability.” They also see the environment as a dependent variable, suggesting that in stable markets, the firm’s focus on exploiting (refining, improving, cost reduction of) existing capabilities can lead to a stronger competitive position in that market. In changing competitive markets, the same self-reinforcing exploitation strategies may negatively affect the firm’s survival by creating a competency trap. This ability to achieve new forms of competitive advantage can also be described as a “dynamic capabilities” approach (Teece et al., 1997). “Dynamic” refers to the capacity to renew competencies so as to achieve congruence with the changing business environment and “capabilities” emphasizes the key role of strategic management in appropriately adapting, integrating and reconfiguring internal and external organizational skills, resources and functional competencies to match the requirements of a changing environment. Competencies and capabilities of a firm rest fundamentally on processes, skills and complementary assets that are difficult to imitate. The ability to calibrate the requirements for change and make the necessary adjustments would appear to depend on the ability to scan the environment, evaluate markets and competitors and to quickly accomplish reconfiguration and transformation ahead of the competition to be a “high-flex” organization. It is in this dimension of encompassing skill acquisition, learning and accumulation of organizational and intangible or “invisible” assets that some believe (Itami & Roehl, 1987) lies the greatest potential for contributions to strategy. In summary, we see that companies form alliances to respond to changing external environments and can be stimulated by market needs, new products,

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new competencies and managerial preferences. These alliances also require a complex response internally – development of new capabilities, skill acquisition and reconfiguration of resources and processes. Organizations need to get better at continually partnering over time. Failures Multi-party collaborations are unique challenges and often unsuccessful. Reasons for failures include lack of previous experience with partnering, integration of different management styles and learning capabilities, lack of cultural sensitivity and lack of trust. According to Sherman (1992), the rate of joint venture formation between U.S. companies and international partners has been growing annually by 27% since 1985. Roughly one-third reportedly fail to live up to parents’ expectations, however; and two-thirds of companies are not satisfied with their co-development efforts (Performance Management Group, 2003). Few companies are satisfied with current collaborative development tools. In a McKinsey study of 150 top partnerships ranked by market value (50 each from U.S., Europe and Japan), only 51% were successful for both partners. Cross-border alliances and cross-border acquisitions both have roughly a 50% rate of success (Bleeke & Ernst, 1991). Bleeke and Ernst also report that alliances between two strong partners are a safer bet than alliances involving two weaker players, and that 67% of alliances run into trouble during the first two years. The Alliance Analyst cites 30% of in the pharmaceutical industry fail outright and an additional 23% achieve only limited success (McCamey, 2002). AT Kearney research (Henricks, 1991) cites the most common pitfalls: a partner having little strategic alliance experience, integrating different management styles, not building consensus from the beginning and moving too fast on too many fronts. Management issues also continue to top the list of concerns (Performance Management Group, 2003), especially inadequate executive leadership. Mergers, in particular, seem to fail due to poor strategic fit, choice of poor acquisition candidate, poor financing, poor integration and lack of cultural and organizational sensitivity (Palcheck & Stewart, 2002). One key failing is the inability to sustain a spirit of cooperation and attention to the ongoing advantage of all partners. Newcomers to corporate alliances are often surprised by the demands placed upon them. One of the biggest variables is the concept of “trust.” It has been concluded that successful alliances exhibit trust between the partners. While many factors have been attributed to explain alliance success, failure and stability, trust seems to have emerged as the magic ingredient necessary for alliances to succeed. Kumar (1996) defines trust as “dependability” by the partners in which a “leap of faith” is made that each partner is interested in

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the welfare of the other. One can extend the theme of mutual welfare where trust is the “perceived likelihood of the other not behaving in a self-interested manner” (Madhok, 1995). Some define trust as “a type of expectation that alleviates the fear that one’s exchange partner will act opportunistically” (Gulati, 1995). Axelrod suggests that it is more likely that in successful alliances, organizational structures and processes have been developed which align interests so that “cooperation evolves naturally” (Axelrod, 1984). Segil (2002) has studied partner difficulties three to four years after the formation of the partnership and found that these primarily are due to differing culture and objectives of the partners. Economic changes also lead to shifts in market demands which then requires a constant refocusing of each company on individual strengths and core businesses. Failure can also be measured in the lack of collaborative learning that was not properly followed through or effort that was reduced over time. If success is defined in terms of learning where parties collaborate to acquire new skills and competitive advantage, then failure can be defined as one partner having advanced skills and the other having diminished skills with loss of competitive position and increased dependency. Firms often lack the organizational capacity to develop new competencies quickly and so need to make choices about how much to spend (invest) on different possible areas central to the firm’s strategy (Dierickx & Cool, 1989). Unless firms have replicated their systems of productive knowledge on many prior occasions, the act of replication is likely to be difficult. The ability to replicate indicates that the firm has foundations in place for learning and improvement (Teece, 1996). Dynamic capabilities thus reflect an organization’s ability to achieve new and innovative forms of competitive advantage given path dependencies and market positions. A firm’s previous investments and its repertoire of routines (its history) constrains its future behavior. Post success, an organization’s core capabilities can just as easily create “core rigidities” because learning tends to be local and a process of trial, feedback and evaluation (Leonard-Barton, 1992). Even measuring performance can be a challenge. McKinsey reports (Sherman, 1992) that although most large companies now have at least 30 alliances, very few systematically track their performance and doing so is “not a straightforward task.” Fewer than one in four have adequate performance metrics and it is estimated that few senior management teams know whether the alliance portfolio as a whole really supports corporate strategy. Success Factors Key success factors of alliances focus on integration – of task through work structures and processes; culture that strengthens shared perceptions, values and behaviors; and interdependence.

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Integration Many successful scenarios rely on strong implementation plans to chart integration and management plans by establishing clear goals and performance milestones. These focus on human resources, communication, a team approach, crossfunctionality and managing the NIH – “not invented here” syndrome. Procter & Gamble, for instance, uses an Alliance Toolkit for pre-alliance activities aimed at alignment: partner selection, preparing for due diligence, work and staffing planning, startup and alliance operations, conflict management and alliance key element assessment and renewal. The alliance framework emphasizes management structure, mid-course corrections and intellectual property (McCamey, 2002). How efficiently and effectively internal coordination or integration is achieved is very important, as is external coordination. Increasingly, strategic advantage requires the integration of external activities and technologies as seen in strategic alliances, the virtual corporation and buyer-supplier relations and technology collaboration (Aoki, 1990). A resource-based strategy model can aid managers to differentiate between resources which might support a competitive advantage from other less valuable resources (Barney, 1991). These describe productive factors having intrinsically different levels of “efficiency.” This helps a firm in deciding whether to license a new technology or whether to develop it internally (Peteraf, 1993). A survey conducted by Performance Management Group (2003) revealed the deployment of seven specific practices as key success factors: structured process, project teams, relationship management, partner management, partner selection, metrics and product strategy. Although all were deemed important, the respondents reported only 20% or less of these practices were deployed systematically. One of the key ingredients for success seems to be flexibility to allow joint ventures to overcome problems and adapt to changes over time. This may include objectives, resources, strategies and skills. These inherent tensions require more flexibility on the part of joint venture parents than many other business strategies. Meeting the requirements of change may also include rebalancing or even exiting the alliance.

Culture A common theme of risk is culture and relationship development where there is continued development of trust, acceptance of compromise and specific attitudes that contribute to managing change – like not assuming projective cognitive similarity (Segil, 2002). Millenium Pharmaceuticals uses core values

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and relationship values to synergize their alliances. These values include: “hiring the best people, creating an environment where people can succeed, listening and learning from everyone, encourage innovation in the search for breakthrough products, build a socially and ethically responsible corporation and believe that nothing is impossible.” They even use the term “over the top” alliances to describe those that truly transform the business of the two partners. Here they say the ingredients for success are “a breakthrough platform combined with a breakthrough business structure.” They shoot for transformation where they want to change the entire base of competition to dramatically increase productivity for new products. An extremely high degree of collaboration is critical in these scenarios (Dionne, 2002, p. 52). One critical phase in multi party issues is to arrive at a shared perception of a desired future and an overlapping task (Vansina et al., 1998). This challenge is quite complex, involving multiple perspectives and multiple resources. How is it possible to achieve collaboration between a diversity of interests, when parties represent different organizations, when there has been no or little common history of collaboration?

Interdependence According to Gray (1989) two factors that are necessary to motivate multi-party organizations to collaborate are “high stakes and high interdependence.” The literature on multi-party collaboration suggests that collaborative task systems are different from integrating teams in that they must start at an earlier stage, independent interest parties have to find common ground through sharing their views and definitions of a particular domain. Integrating teams already have shared interests; but collaborative start-ups need to discover or create shared principles that derive from common ground or shared interests. Cohen and Mankin (2003) suggest this process needs to be intentional – it won’t just emerge from the turmoil of collaborative start-ups. Stakeholders come from different institutions and need to negotiate agreements to achieve collaboration because their interests up to this point may not have overlapped. Fleck (1979) suggests that this collaboration problem of divergent understandings “runs deeper than conflicts over personality types or goals.” Nor is it the proverbial set of blind men touching a different part of an elephant. It is more like the tales of eyewitnesses at an accident, or of individuals in a troubled relationship – each tells a “complete” story, but tells a different one. Strategies to overcome these barriers might include: having innovators using and building on the unique aspects of each thought world, developing collaborative mechanisms

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that deal directly with the interpretive as well as structural barriers to collective action (interdisciplinary responsibility for focus groups, market research plans, technology audits and visits with customers) and finally, an organizational context for collective action that enables both. In building an organization’s capacity for commitment to the innovation process, Dougherty (1996) recommends we consider both organizational and individual levels – just as individual creativity triggers organizational innovation. The culture needed is that of risk-taking, values change and learning to reinforce the need to take innovative action. There needs to be an emphasis on the contributive nature of special knowledge and expertise with these tasks understood realistically as part of the business as a whole, not just abstracted out. This suggests a collective accountability where the innovator becomes legitimate and all participants take on some responsibility for innovation. Culture’s power comes from its integrative perspective that includes an organization’s fundamental goals, values, ways of thinking, managerial styles, the paradigms and approaches to problem solving. It can clarify expectations of the organization and of individuals in “codes of conduct” and expressions of a shared system of belief. Efficiently translating R&D into new products, which can be speedily gotten to market, requires creativity and innovation in business processes and systems as well. This calls for corporate cultures at ease with new ideas, changes, uncertainties and possible failure. Quinn (1985, p. 79) compares the process of introducing a new product to the world to raising a child. He suggests it needs a mother (champion) who loves and supports it, a father (authority figure with resources) to strengthen it, and pediatricians (specialists) to get it through difficult times. It may survive solely in the hands of specialist, but its chances of success are remote. Creativity, like children, can be difficult to contain, impossible to dictate and filled with indifference toward the status quo. Like children, ideas are the future and so the effort to cultivate them is indeed worthwhile.

COLLABORATION AND COMPETITION Literature has investigated the structure and processes associated with both cooperation and competition between and among organizations. Typically, these studies emphasized such phenomena as the struggle for power in interfirmnetworks (Cook, 1977). According to Gray (1989), this struggle can include asymmetrical power distribution among stakeholders differentiating those who are more influential and those who are weaker, disparate political cultures with differing values, attitudes and beliefs about the way the world works, and technical complexity which can hinder collaborative efforts because science is

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not easily translated into policy terms and may make it easier for stakeholders to use information to serve their own purposes. They also describe learning alliances where “partners hope to learn and acquire from each other technologies, products, skills and knowledge” (Lei & Slocum, 1992). Some are business alliances which maximize the utilization of complementary assets – each partner brings and contributes a distinctive capability in a particular value adding activity (Lei & Slocum, 1991).

Collaboration Gray (1989) suggests there are critical prior conditions essential to making collaborations work where reciprocity is key to advancing a shared vision. These include considering the organizational interests or stakes of the organization in the outcome of the joint effort – as well as the perceived interdependence with the other partners. Her framework for cross sectorial collaboration for social problem-solving lends itself to the needs of all partnerships – building of common definitions from problems stemming from interdependence, commitment to collaboration and identification of resources to enable the collaboration. Gray (1989, pp. 255–256) even suggests that there are several conditions under which collaboration should not be attempted: (1) the conflict is rooted in basic ideological differences; (2) a legitimate convener cannot be found; (3) one or more groups of stakeholders cannot establish representation; (4) the issues are too threatening because of historical antagonisms; and (5) maintenance of interorganizational relationships represents substantial costs to the partners. She recommends that all stakeholders must be included & perceive that their interests are fairly represented, because partnerships are not founded solely on philanthropic motives. The challenge is to discover shared interests, arrange the most advantageous trade-offs possible among differing interests and provide sufficient incentives for collaboration. Process factors require that stakeholders agree on the scope of the collaboration, that they negotiate in good faith and that the timing is right – meaning that stakeholders and their constituents are aware of the issue and have developed ideas about ways to resolve related problems. Resolution, Gray observes, often depends on stakeholder creativity: the ability to connect self-interest & community interest represents a new way of approaching international relations, which historically have been characterized by more competitive behaviors. Another arena of collaborative process models comes from the labor union and management negotiations where reliable partnerships are key to establishing strong communications systems and providing in equitable sharing of gains

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from workplace improvements over time (Kaminski et al., 1996). New benefits are being realized from “joint transformation initiatives” between unions and their companies to produce greater responsiveness to customer needs and a more highly skilled workforce. In particular, these benefits include a focus on developing new products and markets with joint design of work processes, work organization, technology and skills. Lessons learned concerning joint design include establishing good ground rules with solid, clear contract language for processes. It is suggested that neither management nor unions should enter into partnerships “lightly,” due to the serious time and financial resources required and the risk of long term failure of transformation efforts which lack planning and are poorly implemented. Lessons learned are also being identified in negotiating multi-party problems at the international level where stakeholders with complex interdependencies must construct governance structures to manage a variety of new global challenges. Collaborative efforts to institutionalize rules and decision-making procedures in several issue areas continue despite difficulties inherent in international negotiations. These lessons include that rules must be realistic – attainable, flexible and compatible with perceived needs – or they will not be followed. Many International Government Organizations (IGOs) have achieved success in attaining technical goals by facilitating rather than demanding absolute compliance (Golich, 1991). They also rely on discussion forums to ensure that member and process factors are incorporated into collaborative efforts. Stakeholder creativity is a key to resolving contentious issues where the ability to connect self-interest and community interest represents a new way of approaching international relations, which historically have been characterized by more competitive behaviors.

Competition Earley and Gibson (2002) also provide a framework for assessing multinational team functioning which clearly identifies those elements that could inhibit collaborative performance. These include: (1) nature of competition and cooperation within a team – e.g. for resources; (2) sense of fractionism or disunity within a team – especially when composed of members of multiple cultures; (3) development of a hybrid, team or culture; (4) shared understanding and meaning that exists for team functioning; and (5) shared goals and priorities viewed as a central feature of cooperation. “Principled negotiation” (Fisher et al., 1991) is a way for differing parties to see themselves as “partners” sitting on the same side of the table while facing

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a mutual problem or challenge together and advancing shared interests. They advise focusing on the problem, not the people; interests rather than positions; generating a variety of possibilities before decision-making and using an objective standard for evaluating results. They liken the negotiation process to shipwrecked sailors who must overcome seeing each other as adversaries, if they are to be able to focus on getting water and getting to shore. The goal, they say, is to “accept the task as a shared problem and face it jointly.” This also must be a continued effort, not just promoted as the beginning of a relationship. Their approach definitely requires a different mindset – where the game has changed from the traditional win-lose posturing often seen in union-management negotiations. Their premise is that, in most instances, to ask a negotiator “who’s winning” is as inappropriate as to ask who’s winning a marriage. “If you ask that question about your marriage, you have already lost the more important negotiation – the one about what kind of game to play, about the way you deal with each other and your shared and differing interests (Fisher et al., 1991, p. 148). In handling groups that may have differing values, cultures, experience or perceptions Fisher, Ury and Patton (1991) go on to suggest that agreement on the “best standard” may not even be necessary. They advise being sensitive to those differences of partners while avoiding stereotyping individuals and then adapting behavior accordingly. Questioning one’s own assumptions about the others’ intentions or interests is a vital part to listening very actively. Less is written about how to make a collaborative alliance work, once partnered – especially when it comes to collaboration among competitors. Very few of the research studies actually emphasize the competitive risks of partnerships other than to mention the issues of intellectual property rights and competing with customers or suppliers. When both partners have a presence in the same geographic market, alliances often lead to competitive conflicts (Bleeke & Ernst, 1991). The challenge of balancing collaboration with competition is considered by some to be a “wicked problem” where multiple perspectives must be integrated in a dance of change as incremental and revolutionary changes are introduced into the situation (Pacanowsky, 1995). Wicked problems are complex with interdependent facets and solutions need to be context-specific. Organizational transformation may be required for solving the problems of competition and collaboration.

NEW PRODUCT TEAMS In the overarching research on innovation, two broad areas of inquiry can be found (Adler, 1989). The first is an economics-oriented tradition, which typically examines differences in the patterns of innovation across countries,

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industrial sectors, and the evolution of technologies over time. The second is an organizations-oriented tradition, looking at a microlevel regarding how specific new products are developed (e.g. Ancona & Caldwell, 1992b; Clark & Fujimoto, 1991; Zirger & Maidique, 1990). This arena is where product development literature is found which especially focuses on the structures and processes by which individuals create products. Historically, the literature on product development can be seen as three separate streams: rational planning (which focuses on a broad range of determinants of financial performance of the product), communications web work (which is concerned with effects of communication on project performance) and disciplined problem solving (which centers on the effects of product – a development team, its suppliers and leaders on the actual product-development process) (Brown & Eisenhardt, 1995). Brown and Eisenhardt’s emphasis on execution spotlights that “internal organization is critical to product success” (1995, p. 351), especially cross-functional skills and their synergies with existing firm competencies. A new integrative model proposed by Brown and Eisenhardt (1995) attempts to improve the understanding of product development by synthesizing the common findings of the research streams and blend in complementary ones to form a model of factors affecting the success of product development projects. This research typically emphasizes factors primarily related to team composition, organization of work and group processes. The new model distinguishes between process performance, product concept effectiveness and financial success while broadening the importance of agents including team members, project leaders, senior management, customers and suppliers – all of whose behavior affects these outcomes. These streams complement each other as well as overlap. For example, in the communications web work stream, foundational work was provided by Allen at MIT (1977). The underlying premise is that communication among project team members and with outsiders stimulates the performance of development teams. The better that members are connected with each other and with key outsiders, the more successful the development process will be. A new perspective looks at how both internal and external communications come together with development processes into a theoretical overall “information-processing view” under process performance. This is first seen through a typology of external communication or “boundary-spanning” behaviors identified by Ancona and Caldwell (1992b). They surveyed 45 product-development teams in their sample to better understand communication strategy that was very comprehensive in combining external lobbying activities with task-coordination behaviors that helped these teams to secure resources, gain task-related information, and so enhance success. They also found that teams with a more thorough internal communication (e.g. they defined goals better, developed workable plans, and prioritized work)

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had superior performance (Ancona & Caldwell, 1992a). This also contributes to a “resource dependence view” which emphasizes that frequent political communication (typically external) leads to higher performing development processes by increasing the resources (e.g. budget, personnel, equipment) available to the team. Another example of complementary streams is portraying product development as a balancing act between product vision developed at the executive level and problem solving found at the project level. A study by Eisenhardt and Tabrizi (1995) examined the computer industry in Japan, Europe and the United States. This deductive study considered 72 products in 36 firms where the focus was on speed of development as the performance measure. They found that product teams who were engaged in more experiential or improvisational product design through frequent iterations, more testing, frequent milestones and powerful leadership developed products more quickly as well as did cross-functional teams. This adds to the research of two relevant problem-solving models for organizing product development for more stable products in mature settings (Clark et al., 1987; Clark & Fujimoto, 1991) where several Harvard researchers studied the management of product-development projects in the auto industry. Building on data consisting of in-depth case studies of 29 major car-development projects across 20 companies – three American, eight Japanese and nine European, these authors replicated earlier findings. They reported that supplier networks coupled with overlapping product-development phases, communication and cross-functional groups improved the performance of the development teams by introducing two central concepts: heavyweight team leaders and product integrity. The heavyweight team leads are actually “linking pins” with senior management who create an overarching product concept so that senior management can exercise subtle control by managing within a product context. Product integrity here is defined as being consistent with the corporate image. Overall, Brown and Eisenhardt (1995) try to organize their model to emphasize the relationships between the theoretical underpinnings identified from the combined research streams. For instance, process performance is driven by the amount, variety and problem-solving organization of information and by the resources available to the team. Product effectiveness is driven by the input of leaders, senior management and customers into the formation of a clear product vision. Both product effectiveness and product performance influence the financial success of the product. The key players in the model are the heart of the product development process – the project team. The composition, group process and work organization of the project team affect the information, resources and problem-solving style of the team. These factors ultimately influence process performance (i.e. speed and performance). According to Brown and Eisenhardt,

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consistent with the empirical support in all three research streams, cross-functional teams are associated with high-performing processes. Moreover, this link in their model is suggested to be among the most important and empirically robust (e.g. Clark & Fujimoto, 1991; Dougherty, 1992; Zirger & Maidique, 1990).

Innovation Dougherty (1996) further explores critical cross-functional issues of team communication by stating that organizations need to embrace “the principle that work is inherently collaborative.” She presents a useful metaphor of “tensions” to describe the number of challenges and conflicts of seemingly opposing forces that can be found in the innovation process – with an emphasis on innovative product development in large, established firms. She references the dialectical nature of innovation whereby the organization and new products are mutually constitutive. Four sets of activities are critical, she says, to effective product innovation. They include: first, conceptualizing the product which requires integrating market needs and technological potential called market-technology linking; second, organizing processes for creative problem-solving; third, monitoring the innovation process; and finally, she recommends that developing the commitment/culture to the innovation effort is critical. Dougherty (1996) goes on to suggest that these four activities all interrelate in practice and that product innovation is inherently interfunctional – second only to corporate strategy. It also is inherently ambiguous and involves varied perception and social constructionism. Each activity has their own set of organizational wide tensions, which can help illuminate the challenges of innovation. The arena of market-technology linking is particularly relevant to understanding the complex collaboration on new product teams where innovators try to create designs that reflect customer needs, market structure, technological capability, manufacturability, selling and distribution. Here, the tensions surface between internal and external activities – i.e. operations and technology. If the innovation can be handled in a single project, then the team members can collaborate among themselves, users and suppliers. Integrated Product Teams, for instance, were created to support this front-end market-linking and knowledge creation as innovators work with customers, experiment with new designs and test different approaches. Development of new products requires that technological and market possibilities are linked effectively in the product’s design. Dougherty (1990) demonstrated that two interpretive schemes are found to inhibit development of technology-market knowledge: departmental thought worlds and organizational product routines. Three implications from her findings

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relate to collaboration: (1) collaboration is necessary to technology-market linking, enhancing the product’s design along with improving the execution of the development process; (2) the styles in which people organize their thinking and action about innovation – their interpretive schemes are major barriers to linking and collaboration. These could be departmental & organizational routines which separate rather than coordinate the thought worlds; (3) correcting these innovation problems caused by interpretive barriers requires cultural solutions, not structural ones. Dougherty (1990) demonstrated that various functional departments were tantamount to “thought worlds,” each with its own fund of knowledge – what members know – and “system of meaning” – how members know (Dougherty, 1992).

Multi-disciplinary “Thought-Worlds” These “thought worlds” can create silos. Fleck (1979, p. 99) emphasizes the social basis of cognition and adds that “innovations often are epistemologically unsolvable by any one person.” Due to specialization, a certain thought world is likely to best understand certain issues, but also to ignore information that may be equally essential to the total task. Their intrinsic harmony would also reduce the possibility for joint learning, since members of a department may think they already know everything – the “Not Invented Here (NIH) syndrome.” He found four themes in thought worlds in new product development: (1) people’s descriptions of other departments and customers; (2) what people see when they look into the future and uncertainty; (3) what people consider to be the critical aspects of the product development process; and (4) how people understand the development task itself. Contrasting perspectives can seriously impede a dialogue over what the product is and how it should be developed. This will require new organizational routines in what Fleck (1979, p. 100) calls “collective work proper.” He suggests this is different than additive work, as when people come together to lift a large rock. Collective work refers to “the coming into existence of a special form, like a soccer match, conversation or orchestra.” This new social form alters the thought worlds’ existing readiness for directed perception to allow new possibilities for discovery and new facts. He further explains that each thought world rechannels its readiness from an inward focus to an outward focus so that their knowledge could join to produce new insights and facts. In his research, he saw how interdepartmental relationships encouraged ideas to be heard and built on and enhanced appreciation of one another’s contributions. Research on project development in the automobile industry (Clark & Fujimoto, 1991) also illustrates the role played by coordinative routines. Their study reveals

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significant degrees of variation in how different firms coordinate the various activities required to bring a new model from concept to market. Routines related to coordination are firm-specific in nature and these differences in coordinative routines and capabilities seem to have a significant impact on such performance variables as development cost, development lead times and quality. When organizing for innovation, innovators must solve complex problems to overcome surprises, work around barriers, merge processes from different functions and weave together resources from different locations. One of the prime tensions in jointly focusing on problems that affect more than one function is by taking into account the constraints of the other function. This is multidisciplinary work that must be coordinated (Dougherty, 1996). She proposes that to support creative problem solving in organizations, it is essential to see the organization itself as a process, focusing on organizing for innovation. It is suggested that if people could see work as a process, then they could see sets of work and emphasize the relationships between them. This would challenge managers with a complexity to solve cross-boundary problems, as well as provide a focus on product lines where managers can see how new ideas flow into generations or product revolutions. In summary, Dougherty (1996) presents a case that there is little insight into organizational problems of innovation because research has not been anchored into basic activities which underlie product innovation – they have either been project-focused or have been done at too high at a top-level of the organization. The question “How can we organize organizations to be more effectively innovative?” is put on the table to challenge our next frontier of research and analysis.

Organizing for Innovation Quinn (1985) found that big companies could stay innovative by behaving like small entrepreneurial ventures within an environment of “controlled chaos.” His research showed that a large company could emulate smaller ones by using groups that function in a skunkworks style. Small teams of engineers, technicians, designers, and model makers were placed together with no intervening organizational or physical barriers to developing a new product from idea to commercial prototype stages. The skunkworks approach eliminates bureaucracies, allows fast, unfettered communication, permits rapid turnaround times for experiments and instills a high level of group identity and loyalty. Overall, his suggested approach is not one of highly structured planning systems, but an “incrementalist” approach where “major innovations are best managed as incremental, goal-oriented, interactive learning processes” (Quinn, 1985, p. 82). He describes the innovative

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process itself as inherently incremental where technological systems evolve through relatively small steps marked by an occasional stubborn obstacle and by constant random breakthroughs interacting across laboratories and boundaries. The challenge for managers is how to manage this chaos. They may be able to learn lessons from venture capitalists who administer primarily by setting goals, selecting key people and establishing a few critical limits and decision points for intervention rather than by implementing elaborate planning or control systems. Quinn suggests that executives need to understand and accept the tumultuous realities of innovation. Beyerlein, Freedman, McGee and Moran (2003) suggest that collaborating is a process that forms the skeleton of a dynamic system. They describe work teams as the most common structural change to improve effective use of collaboration: a useful mix of expertise, an opportunity to increase commitment through involving employees in decision-making, leveraging of resources through identification of interdependencies, pooled energy through commitment to the team or common purpose. A team-based organization capitalizes on the competitive advantage of collaboration that grew out of socio-technical systems work, where the need to jointly optimize the social and technical facets of the organization was recognized as the key to performance (Beyerlein et al., 2003). Cooper and Kleinschmidt (1987) found that “although many managers profess to have a systematic process plan in place for product development, an audit of what actually happens “in the trenches” reveals many gaps and deficiencies.” Often, a number of activities, often critical, are either eliminated or key activities are superficially undertaken. This can result in poor design, product malfunctioning, product liability suits, expensive product recalls and potential higher production costs (Hise et al., 1989). The challenge is to speed up the product life cycle even in an industry like aerospace where slow, development cycles have been acceptable – without cutting corners or avoiding taking important steps which might sacrifice quality. Gupta and Wilemon (1990) researched the new product development (NPD) process of 12 large technology-based firms. They were chosen because they were known to have active NPD programs for a number of years and they had experienced both important successes and failure in their innovation programs. Although 88% of the respondents had experienced a need to reduce the development time for their new products since 1980, 87% of the study participants reported that most of the reasons that delayed product development in the past continue to exist in their companies. The four main categories of areas having significant impact on the NPD process performance in terms were senior management support, early integration of functional expertise in NPD, availability of NPD resources and their management, and an organizational environment that supports teamwork.

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Content analysis of the responses of the interviewees revealed that major concerns included management and organizational style, lack of attention to details, limited support for innovation, lack of strategic thinking, and inadequate manufacturing facilities. Roberts (1988), in his review article on managing innovation, emphasizes that the “management of technological innovation is complex, involving the effective integration of people, organizational process and plans.” If there is a breakdown in any one of these elements or if they are not well integrated, the NPD process becomes less effective. Cohen and Mankin (2003) suggest, “the structural challenge (as in any new product development project) is to partition the tasks effectively so that specialized work can proceed, while simultaneously integrating the different parts across the boundaries of time, distance and culture.” They also stress the importance for collaborators to be proactive in developing mutual understandings about respecting their each other’s boundaries. People with strong interpersonal skills, particularly “lateral skills” – the ability to work with others different than themselves – are critical to put in key linking roles to enable work integration across organizations. Cohen and Mankin suggest that an organization develops the capability to conduct complex collaborations when it can consistently and successfully execute them. This capability is developed when all parts of the organization are aligned to support complex collaboration – structure, task, technology, processes, rewards and people practices. Although the heart of new product development seems to rest on teams, their performance, in turn, relies on the larger organization of innovation that surrounds them. This complexity increases when these teams are geographically dispersed.

Distributed Work Virtual teams are an evolution of collaborative work. They have developed on two particular correlations: (1) the emergence of environments that require interorganizational cooperation as well as competition; and (2) the increasing globalization of trade and corporate activity (Townsend, 1998). Organizations have also recognized that team-based structures have the potential to create a more productive, creative and individually fulfilling working environment. Townsend (1998) suggests that new competencies are required of these virtual team members including superior team participation skills to assimilate with a team, proficiency with computerbased technologies and the ability to cross national boundaries and communicate with a variety of cultural backgrounds which will be represented on the team. Cohen and Mankin (2003) describe that “virtual organizations are more complex than traditional organizations, in that they connect multiple organizations

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in a dynamic network.” Each organization has its own policies, systems, and structures that may not easily mesh with its partners. The dynamic nature of the network as well as the number of boundaries that are crossed increase uncertainty and complexity. Collaboration is essential, although Cohen and Mankin (in press) go on to describe a paradox within virtual teams. They present a fragmentation which challenges workers to cut across multiple boundaries, country, department and discipline, and at the same time, creates a need to create those systems and enablers that would normally be taken for granted and yet, not in place. Complexities of multinational enterprises are also emphasized by Boudreau, Loch, Robey and Straud (1998) due to the management of interdependencies between nations, as well as companies. They found three characteristics of virtual organizations which seem to enhance global competitiveness: (1) seamless integration among a variety of federated organizations; (2) ability to overcome vast spatial and temporal barriers linking together geographically remote sites; and (3) flexibility to form, disband and reform to respond rapidly to changing business needs – especially customer needs. The new Lotus Sedan and Lotus Wagon are the result of a co-development dilemma – trying to preserve its carefully crafted image as a “different kind of car company” independent from GM decision-making (Pryweller, 1999). On the other hand, they wanted to save money by adapting a European car for the North American market. The challenge was manage the politics of world-platformsharing. The work was headquartered in Norwich, England at Lotus Group, Ltd., the outside British engineering and vehicle development company previously owned by GM. There, designers and engineers from around the world met to produce a vehicle that “cherry-picked” components from across GM. At any given meeting, Lotus coordinators might be hosting a group of 40 to 50 people that included Lotus engineers, Saturn’s manufacturing engineers from Spring Hill, Saturn vehicle engineers from Michigan, powertrain experts from New York and England, engineers from Saab, which supplies a transmission, and Opel engineers from Russelsheim. The engineers claimed that having England as a “neutral site” helped, and leveraging resources from around the world was their competitive edge (Chappel, 1999). Gibson (2002) continues to build the argument for multicultural virtual teams being able to enhance performance when well managed. Her research reveals that these teams seem more creative, can generate more and better alternatives including criteria and perform better on complex, multi-faceted tasks. The challenges they face include being geographically dispersed over multiple time zones, rarely meeting face-to-face, having members who do not share the same access to electronic communication and whose native language may be different than most team members. Diversity barriers could also include members who

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are from two or more functions or disciplines. She presents a design model for virtual teams that emphasizes people, process, group structure, organization context and technology building toward shared understanding, integration and trust. Hoped-for outcomes are described in both organizational and human terms. Mohrman (1998) speaks to the new need for “distributed work” with two requirements for success in today’s global competitive environment: (1) locating locations throughout the world in order to be close to needed resources and be responsive to customers; and (2) organizations having to leverage knowledge, products and activities around the world, requiring new activities to integrate across their operations. Using geographical dispersed teams also improves the capabilities of organizations to introduce new technologies, redefine core organizational processes and leverage knowledge capabilities. This enables companies to pull expertise from wherever in the company it happens to exist, which makes them heavily dependent on interactions with the systems and people that provide the resources, task, goal and performance-related information to them. Clark and Wheelright (1992) suggest a product development framework including the organizational issues of cross-functional cooperation, learning and building capabilities.

Organizational Learning Researchers (Doz & Shuen, 1990; Mody, 1993) have pointed out that collaboration and partnerships can be a vehicle for new organizational learning, helping firms to recognize dysfunctional routines and preventing strategic blindspots. The concept of dynamic capabilities as a coordinative management process opens the door to the potential for interorganizational learning. Learning requires common codes of communication and coordinated search procedures which may be expressed in new patterns of activity in “routines” or a new logic of organization. The capacity to reconfigure and transform is itself a learned organizational skill. (Argyris & Schon, 1978; Levitt & March, 1988). The recently popularized vision of a “learning organization” provides us with a new picture of companies as dynamic learning communities. Senge (1997) suggests that new capabilities are required for this vision, including creating a “set of practices for generative conversation and coordinated action; and a capacity to see and work with the flow of life as a system.” He then suggests that language functions as a device for connection, invention and coordination. “If people can talk from their hearts and connect in a spirit of dialogue then a common fabric connects them at a deep level of being,” Senge (1997, p. 18) writes. This, in turn, produces a tremendous power to invent new realities in conversation, and to bring about these new realities in action.

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Wenger and Synder (2000) suggests this is especially true in the workplace. They say we need to “view learning as work and work as learning.” Only when we recognize learning in all its forms can we find ways to nurture it and connect it across the organization. It is this view of the organization as a constellation of interconnected practices that can provide a new spirit for collective learning in corporations. They truly could be the springboards for creating organizations, which can thrive in a world of increasing interdependency, change and innovation. Most learning in organizations does not happen at the organizational level, it seems. It happens at the group and individual level in what Bristow, an international consultant who specializes in collective genius, calls “learning communities” (Bristow, 1997). He uses this term to describe both formal and informal associations where individuals take responsibility for their own learning, as well as the learning of those with whom they work and associate. Another way to design agile organizations is to develop the capability of collectively linking together working, learning and the capacity for change across inter-and intraorganizational boundaries in Communities of Practice (CoPs). Focused at the microlevel of how individuals and small groups make sense of and respond to their environment, CoPs embrace the social and dynamics of getting the work done, organizational processes and the challenge of agility (McDermott, 1990). Since CoPs embody and bind the knowledge of the organization’s processes, they can potentially hold that knowledge of practice from the rest of the organization. Agile organizations thus distinguish themselves by becoming proficient at communicating applying the knowledge of practice contained within multiple CoPs to solve complex organizational problems. It is in this spirit that CoPs can also learn from one another to lead continual innovation within an organization. Nonaka and Takeuchi (1995) describe an organizational knowledge creation and transfer cycle that loops from the individual to the group and then to the organizational level, a process that kneads both tacit and explicit knowledge through processes that they label “internalization” and “externalization.” From this perspective, innovation is best understood as the process by which an “organization creates and defines process problems and then actively develops new knowledge to solve them.”

Metaphors of Collaboration and Creativity Rugby In product development, the new emphasis on speed and flexibility calls for a different approach for managing new product development (Takeuchi & Nonaka, 1986), and so requires new images to describe collaboration and creativity (Brown

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& Eisenhardt, 1995). The traditional sequential or “relay race” approach to product development – typically called a phased program planning system – often conflicts with the goals of maximum speed and flexibility. Takeuchi and Nonaka (1986) suggest a holistic or “rugby” approach – where a team tries to go the distance as a unit, passing the ball back and forth – may be more relevant in today’s competitive requirements. Rugby is a team effort where its members continually interact until the game is over. On the other hand, a relay race is more like a typical sign-off procedure followed in many companies in which the job moves from one functional department to another. Such linear, relay race-type processes are often slow, inflexible and inefficient. Their approach to new product development would be characterized by small, self-managing, multi-functional project teams; overlapping development phases, multi-learning, subtle control, organizational transfer of learning, built-in instability, and tracking cycle time throughout the organization. Carrier Decks The environment of the carrier deck has often been used to describe a collaborative team – and collective mind – even within a bureaucratic system (Pool, 2000; Rochlin et al., 1987). What these research scientists were looking for were the reasons why so few accidents happened, even in treacherous conditions. The challenges of an aircraft carrier flight operations include many planes taking off and landing at the same time – often without using radar to avoid detection – with short take-offs and landings on decks covered with seawater and oil. Pool (2000, p. 88) says, “What they found was that on the surface, a nuclear carrier is run in exactly the rigid, hierarchical way that one would expect. But in times of high demand – such as the launching and recovery of planes – this traditional hierarchy dissolves and in its place appears a loosely organized structure in which officers and sailors collaborate as colleagues.” They discuss and negotiate about the best procedures and generally follow the lead of whoever has the most experience and expertise in a particular situation. In this mode, there is no sense of “not my job” or “not my responsibility.” A crewmember who notices an unusual reading on a gauge or who spots a potential problem with a plane is expected to respond quickly or else tell someone who will. If the circumstances warrant it, each member of the crew has the power – and the obligation – to shut down flight operations immediately. La Porte (Rochlin et al., 1987) describes “constant communications” as one of the key features of this alternative structure. The 60 seconds between the landing of one plane and the next offers no time to send messages up the chain of command and wait for orders to come back down. Instead, crew members are continually talking to one another, announcing what they have done and what

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they will be doing next. This ability to morph from one structure to another was not predicted by any of the standard organizational theories. La Porte (Rochlin, et al.) found that in these organizations, the managers are not conscious of having created any innovative organizational structure. Instead, the structures seem to have evolved naturally under the pressure of slipups and unforeseen events. The top-down command structure of a large organization enforces the discipline necessary to keep the rules respected and bad luck at bay. When it is impossible to control everything, and the pace and complexity of operations increases, it is not simply enough to follow rules and obey orders. Another analysis of flight deck processes (Weick & Roberts, 1993) describes these communications among colleagues as a “collective mind” found in organizations. They suggest that performance, itself, is mediated by collective mental processes that are inherent in all organizations. Some organizations just choose to develop these processes to more advanced levels. The word “collective” here refers to individuals who act as if they are a group and refers to the pattern of interrelated activities among many people. These create social forces that can provide integrated information about a situation, when in reality, the several sources are relatively independent of one another and located in different parts of the ship. The result is joint action that begins with individual contribution. Jazz McDermott (2000) and Barrett (1998) use a jazz metaphor to illustrate that collective “thinking” is the key to making information useful. When jamming, jazz musicians get a feel for where the music is going, adjust to their partner’s moves, change direction and readjust. They take in information, make sense of it, generate new musical ideas, and apply their insights to the ongoing musical conversation. Responding to each other, they draw on tunes, chords, progressions and musical “feels” they have known before, even though at any moment they could not predict “what next.” Barrett (1998) highlights the collaborative value of playing jazz by describing a “transformation occurring in a player’s development” when he or she begins to export materials from different contexts and vantage points – combining, extending, and varying the material to create different harmonies and grace notes (p. 607). Machine Shop Culture Despite his image as the “Wizard of Menlo Park” – a lone, heroic inventor whose brilliant mind created magical inventions – Thomas Edison rarely worked alone. Innovation in his laboratories was a “cooperative affair” (Millard, 2001). In fact, Edison organized for socialization. He modeled Menlo Park after the craft culture in Europe and the machine shops of Newark, New Jersey,

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which incorporated a measure of freedom and socialization quite different from other work environments of his day. He organized teams like today’s project teams, each composed of a chief experimenter and several assistants. These could be augmented by other machinists and craftspeople determined by the team, which also was free to draw on any resource in the laboratories (supplies, library information, Edison himself, the experience of tradespeople, etc.) Most importantly, the teams were encouraged to maintain communication among the teams because Edison knew that this was a vital part of the process of innovation. “The key to one problem might be found in the experimental results generated in another project. The openness of the machine shops permitted the ready spread of information, not necessarily the written knowledge of science but the nonverbal information of ways of doing things, of techniques and prior experience. The ease of communication in the shops had helped bring forth a great number of important inventions,” Millard (2001) describes. The other tradition of the shop culture was collaborative learning by doing across disciplines – or in the Menlo Park lab, it was “inventing by doing.” Millard (2001) describes that true to the democracy of the machine shop culture, Edison was always open to the suggestions and ideas of his men when it came to new experiments or inventions. Anyone was free to try a new idea. The machinists did more than act as Edison’s hands – they filled in the details that were omitted in Edison’s fast-moving thoughts, and they applied their own expertise in the struggle to get the thing to work. They also took the initiative to modify devices and to experiment freely. Machinist and experimenter were partners in invention. A nickname for these experimenters was “muckers” from the expression “to muck in” or “to muck about” – to fool about with little purpose other than amusement. Edison used laboratory notebooks to quickly record “half-baked” ideas or rough sketches. These were left on the experimental tables for others to pick up and use or pass on to one of the machinists to begin the invention process. Forests New metaphors are also being offered for distributed, collaborative work as by a key executive at Weyerhaeuser Corporation (Fisher & Duncan, 1997): “When we think a company is like an engine, we manage it that way. We assume that there are discrete activities like changing the oil or replacing the carburetor that will create predictable improvements. But companies don’t act like machines; they act more like gardens or forests. They aren’t mechanical; they are organic. It is time to change our metaphor. Instead of acting like mechanics, we need to act like farmers or foresters. We need to plant and nurture and analyze and protect, not tighten, fix or lubricate. We need to ensure that the soil of our organizations isn’t

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poisoned by distrust. Like farmers, we need to remember that success requires hard work, discipline, and patience.”

Future Directions for Research Results of these studies show that the picture and description of how complex collaboration actually functions needs more research. Metaphors may help us get a glimpse into the nature and rhythm of this phenomenon, but more study is required on the multiple variables that influence the success and failure of multi-party co-development. How these variables interrelate and synergize to produce true innovation requires new processes, capacities, routines and models of organizing. Brown and Eisenhardt (1995) indicate potential paths for future research that center on the links between process performance, effective product, market factors and financial performance – as well as the patterns of organizing product-development work. New metaphors are required for the image of product development, rather than just a focus as disciplined problem solving. Absent from the literature (Lewin et al., 1998) are studies of evolution of alliances over time – as they co-evolve with changing strategies of the firm, evolving industry strategic practices and the changing regulatory and institutional environment. The study of process variables also remains an unexplored area of research, as well as a clearer articulation of those routines that inhibit or foster innovation (Fleck, 1979). The biggest barriers in large organizations according to Dougherty (1996, p. 436) include the power of existing organizational routines and organizational structure, resource limitations, and an organizational cultural value that tradition is preferable to change. It is here, she concludes, that behavior and culture need to be “crystallized into skill sets or systematic patterns of thinking and acting,” or “capacities,” to enable the activities of innovation. New capacities would enable people throughout the organization to work with customers, form teams, solve problems creatively, apply technical potential to market needs and appreciate the relationships among functions and businesses well enough to shift them as necessary. Here large organizations can become as adept with ongoing product innovation as a new form and social system. They must find new ways to solve problems of normal functioning and still embody the tensions which power innovation. The author will be examining more closely the translation of collaboration into effective team behaviors across competitive boundaries on JSF. She will look into work task examples and identify how coordination challenges are solved by engineers using formal and informal mechanisms.

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Mohrman (1998) and Galbraith and Lawler (1994) both suggest future research is needed to develop new models of organization contexts within which distributed work can occur more naturally – especially forms with a boundaryless nature. Mohrman (1998, p. 20) says there is a need for an integrative framework for a myriad of dispersed, multi-dimensional activities. Following her direction, we see that dispersed teams and networks are a way of organizing work that challenges many of the assumptions and approaches of the traditional hierarchical business model. “We are on the edge of a theoretical frontier for new theories of organizing for innovation,” Dougherty (1996, p. 436) reflects. This applies as well to building the capabilities of complex collaboration.

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NOT YOUR STEPPING STONE: COLLABORATION AND THE DYNAMICS OF FIRM EVOLUTION IN THE LIFE SCIENCES Kenneth W. Koput and Walter W. Powell ABSTRACT In this chapter, we make the argument that science-based firms in the life sciences are expected to actively expand the volume and scope of collaborations, and broaden the kinds of partners with whom they collaborate, as they grow larger, older, and become successful. We base our arguments on a general process of organizational learning in which organizations with diverse ties are exposed to a broader stock of knowledge, heterogeneity in the portfolio of collaborators facilitates innovation, and repeat contracting enables organizations to deepen their protocols for the exchange of information and resources. We draw from these ideas the conclusion that interfirm collaboration is not a transitional stage, or stepping stone, to success or maturity, but a significant organizational practice in technologically advanced fields. Extending this argument, we suggest this strategy of interfirm collaboration represents neither dependency nor specialization but an alternative way of accessing knowledge and resources.

Complex Collaboration: Building the Capabilities for Working Across Boundaries Advances in Interdisciplinary Studies of Work Teams, Volume 10, 59–81 Copyright © 2004 by Elsevier Ltd. All rights of reproduction in any form reserved ISSN: 1572-0977/doi:10.1016/S1572-0977(04)10003-4

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INTRODUCTION Collaboration among competitors was once regarded as a provisional or transitional step taken to enter new markets, spread risks, or to share the early stage costs of R&D (Mowery, 1988; Porter, 1986). In contrast, recent studies suggest that various forms of partnership are now core components of corporate strategy. Indeed, contemporary research on organizations and industrial performance is replete with reports of a marked upsurge in various types of interorganizational collaboration. While these collaborations can take a number of forms (including research consortia, joint ventures, strategic alliances, and subcontracting) and span a wide range of key functions, a recent National Research Council analysis of trends in industrial research and development (R&D) suggests that the innovation process has undergone the most significant transformation over the past decade (Merrill & Cooper, 1999). A National Research Council survey of eleven industries, purposefully diverse in character and technology but all resurgent in the 1990s, observes in every industry an increased reliance on external sources of R&D, particularly universities, consortia and government labs, and greater collaboration with domestic and foreign competitors, as well as customers in the development of new products and processes (Mowery, 1999, p. 7). Other surveys also point to the enhanced centrality of interorganizational collaboration, especially in R&D (Rosenbloom & Spencer, 1996). For example, National Science Foundation data show a marked increase in the number of international alliances between the United States and Western European countries between 1980 and 1994; but by the mid-1990s, the formation rates for intranational alliances linking U.S. firms with their domestic competitors outpace international linkages (National Science Board, 1998). The former collaborations were motivated largely by concerns with market access, while the latter focus more on the development of new technologies by teams of organizations. Similarly, there is now ample research illustrating the growing links between U.S. firms and universities (Cohen et al., 1994), and greater involvement by firms and government labs in research joint ventures (Link, 1996, 1999). In the realm of science, Hicks and Katz (1996) find that research papers are much more likely to be co-authored and involve authors with multiple institutional affiliations that span universities, government, and industry. In short, as Mowery (1999, p. 9) observes, “the diversity of institutional actors and relationships in the industrial innovation process has increased considerably.” Complex networks of firms, universities, and government labs are critical features of many industries, especially so in fields with rapid technological progress, such as computers, semiconductors, pharmaceuticals and biotechnology.

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These developments in industry and science suggest a significant refashioning of the division of labor in which smaller science-based firms, and the linkages between them and centers of innovative activity, assume prominence in researchintensive fields. New science-based startup firms, whether spun out of an existing company or university or created as an entrepreneurial venture, have played a greater role in both the U.S. and the global economy over the past two decades. Moreover, these firms appear to operate according to a different organizing logic, with smaller workforces and extensive linkages to other organizations and partnerships with outside parties for key business functions. Despite the increasing salience of science-based firms, we know relatively little about their developmental trajectories. Thus, we want to add theoretical flesh to these discussions of the structure of the science-based firm (hereafter, SBF), and to debates over the importance of alliances and various types of collaborations. We take up the theoretical task in the next section, suggesting that, despite the hazards of collaborating, SBFs will expand the volume and scope and broaden the reach of their alliances as they grow, age, and succeed. We conclude with a discussion of the important properties of networks for innovation and industry evolution in research-intensive domains.

COLLABORATION AS A CORNERSTONE At the point of founding and in their initial years, startup companies face a number of challenges. Young firms lack an established reputation, are often resource-constrained, and face uncertainty with respect to the quality of their work (Stinchcombe, 1965). In knowledge-intensive fields, these concerns are mitigated somewhat by establishing alliances with organizations that provide resources and/or scientific expertise. These initial connections may well involve a variety of motives. A large corporate partner may turn to a smaller firm to do contract research. A university may license a new technology to a startup firm to speed the development of a new therapy. A professor from a university may found a company and forge a research partnership with a university, a research institute, or a government lab to help support the research. Financial institutions may seek to get in on the ground floor of the enterprise, and bankroll the new technology. Biotechnology provides a good illustration. The science underlying the field of biotechnology had its origins in university laboratories. The scientific discoveries that sparked the field occurred in the early 1970s. These promising discoveries were initially exploited by a handful of science-based start-up firms founded in the mid to late 1970s. The year 1980 marked a sea change, with the U.S. Supreme Court ruling in the Diamond v. Chakrabaty case that genetically engineered life

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forms were patentable. Congress passed the Bayh-Dole Act in the same year, which allowed universities, nonprofit research institutes, and small businesses to retain the intellectual property rights to discoveries funded by federal research grants. And Genentech, which along with Cetus was then the most visible biotech company, had its initial public offering, drawing great interest on Wall Street, with a single day stock price run up exceeding any previous one-day jump. Over the next two decades, hundreds of small, science-based human biotech firms have been founded, mostly in the United States but more recently in Canada, Australia, Britain, and Europe. The initial breakthroughs – most notably Herbert Boyer and Stanley Cohen’s discovery of recombinant DNA methods and George K¨ohler and Cesar Milstein’s cell fusion technology to create monoclonal antibodies – drew primarily on molecular biology and immunology. The early discoveries were so path-breaking that they had a kind of natural excludability, that is, without interaction with the university scientists who were involved in the research, the knowledge was difficult to transfer (Zucker et al., 1994). But what was considered a radical innovation three decades ago has changed considerably as the science diffused rapidly. Genetic engineering, monoclonal antibodies, polymerase chain reaction amplification, and gene sequencing are now a standard part of the toolkit of microbiology graduate students. To stay on top of the field, participants have to be at the forefront of knowledge-seeking and technology development. The commercial potential of biotechnology appealed to many scientists and entrepreneurs even in its embryonic stage. In the early years, the principal efforts were directed at making existing proteins in new ways, then novel methods were developed to make new proteins, and today the race is on to design entirely new medicines. The firms that translated the science into feasible technologies and new medical products faced a host of challenges, needing huge amounts of capital to fund costly research, assistance in managing themselves and in conducting clinical trials, and experience with the regulatory approval process, as well as manufacturing, marketing, distribution, and sales. In time, established pharmaceutical firms were also attracted to the field, initially allying with SBFs in research partnerships and in providing a set of organizational capabilities that SBFs were lacking. Eventually, the considerable promise of biotechnology led nearly every established pharmaceutical corporation to develop, to varying degrees of success, both in-house capacity in the new science and a wide portfolio of external collaborations (Arora & Gambardella, 1990; Gambardella, 1995). Thus, the field is not only multi-disciplinary, it is multi-institutional as well. In addition to research universities and both start-up and established firms, government agencies, nonprofit research institutes, and leading hospitals have performed key roles in conducting and funding research, while venture capitalists

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and law firms have played essential parts as talent scouts, advisors, consultants, and financiers (Gilson & Black, 1998; Lerner & Merges, 1998; Powell & Owen-Smith, 1998). Biotechnology emerged at a time, in the 1970s and 1980s, when a dense transactional infrastructure for relational contracting was being developed, especially in Silicon Valley (Powell, 1996; Suchman, 1994). This institutional infrastructure of venture capital firms, law firms, and technology talent scouts greatly facilitates interorganizational collaboration. Taking all these elements into account, two factors are highly salient. One, all the necessary skills and organizational capabilities needed to compete in biotechnology are not easily housed in a single organization (Powell & Brantley, 1992). Thus, organizations must work as teams. Two, in fields such as biotech, where knowledge is advancing rapidly and the sources of knowledge are widely dispersed, organizations enter into an array of alliances to gain different competencies and knowledge. In so doing, firms develop portfolios of relationships that permit access both to developments in science and skill in bringing new products to markets. Such collaborative arrangements involve an indissoluble mix of science, status, and strategy. Alliances with prestigious partners enhance a young firm’s reputation (Stuart, 1998; Stuart et al., 1999), while also signaling legitimacy (Baum & Oliver, 1991). External partners also provide much needed resources and complementary skills (Dyer & Singh, 1998; Powell & Brantley, 1992). And to the extent that new firms are formed by entrepreneurial faculty, collaboration often involves carrying the scholarly model of an invisible college into the commercial realm (Powell & Owen-Smith, 1998). Founders of firms who come from the academy wear dual hats, using one social form for a completely different purpose. Whether viewed through the lens of multiple networks or of refunctionality, the transposability of scholarly research linkages into business connections mixes science and strategy in a novel way (Padgett, 2000). Yet, alliances are also hazardous and commonly seen as unstable, both individually and as a strategy for organizing. Economists have stressed the threats of information leakage, adverse selection and moral hazard, opportunism, and hold-up problems (Holmstom & Roberts, 1998), whereas management perspectives view alliances as strenuous balancing acts involving sometimes incompatible interests (Das & Teng, 2000; Doz & Hamel, 1998). Alliances are the mode of organizing of last resort: used to overcome unaffordable costs, counter uncertainty, or acknowledge a weak or dependent market position. Hence, from an economic or management perspective, as firms grow, age, and succeed they should either outgrow or tire of alliances, allowing existing alliances to lapse and not pursuing new ones. We particularly identify three challenges to the viability of alliances as firms grow, age, and succeed. First, competition is frequently size-localized

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(Baum & Mezias, 1992; Wholey et al., 1992). As a result, partnerships typically involve firms with dissimilar market positions. Organizational growth brings a smaller firm into more direct competition with a larger ally, upsetting the balance between competition and cooperation that enables alliances between them. Second, firms should prefer to protect proprietary work in order to appropriate the gains from their innovations (Porter, 1980). Success would bring the necessary financial resources and “complementary assets” that allow firms to “go solo,” thus firms would no longer require linkages to organizations for the purpose of establishing credibility. Third, uncertainty stems from inexperience and lack of power (Pfeffer & Salancik, 1978). As a smaller firm grows, it develops internal capabilities and power that reduce uncertainty, obviating the need for outside assistance. The question we address here is whether science-based firms shift their strategies of collaboration as they grow older, larger, and more successful. We argue that in fields where knowledge is advancing rapidly, the three challenges to alliance stability may not hold; firms may come to view collaborations as more than a means to compensate for a lack of resources, internal skills, or market power. Collaboration may represent an admission ticket to an information network (Powell et al., 1996). In our view, collaborative networks constitute organizational teams and therein provide timely access to knowledge and resources, where learning is protracted and resources divided, while also testing internal expertise and learning capabilities. This access is exceedingly important in fields where scientific discoveries are occurring simultaneously in many different locations, and the time to discovery is protracted. Following ideas initially developed by Penrose (1959, pp. 222–225), smaller firms may thrive at the interstices of fast-developing fields, where they can play a bridging role linking participants in different organizations and different kinds of organizations. The crux of our argument is that SBFs utilize interorganizational networks as an important cornerstone of their strategy. The ability to reach across multiple partners in diverse fields is important in lessening dependence. Alliances across fields may place smaller organizations in an enviable arbitrage role, increasing access and prominence, and creating an opportunity to learn from a variety of partners. But we do not wish to overemphasize the logic of intention, as a logic of appropriateness may be equally salient. To the extent that key participants are drawn from the research community, the norms of collaborative science may cross over to the commercial realm. Or if collaboration with prestigious partners at an early stage produces success (or at least the illusion), then a bandwagon may be created. We do not, in this chapter, attempt to disentangle the twin pulls of strategic and appropriate behaviors. We first present an admittedly preliminary typology of dynamic alliance strategies and then develop hypotheses concerning the consequences of organizational

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growth, aging, and success for the collaborative arrangements that firms employ. Viewed differently, growth, aging and success are mileposts for organizations, and we can look at these road markers and see whether the mix of arrangements that were used to reach a particular milepost are continued, disbanded, or expanded, diversified, and broadened as movement toward the next marker occurs. Each process – growth in size, the gaining of experience, and the successful launching of a new product – presents a challenge to a firm in terms of how it chooses to organize. Growth brings problems of communication and coordination as the number of employees grows. As an organization ages, its stock of knowledge increases and its routines for organizing core tasks become more well developed. With a successful product, an organization faces the challenge of reproducing its initial success but now has new resources to deploy. Each of these stages could be the occasion to either retreat from alliances or become more deeply embedded in clusters of relationships with diverse parties.

STRATEGIES AND ALLIANCE LOGICS In actual practice, individual companies in a number of fields, including biotechnology, have pursued varied strategies of expanding, retreating, holding course, deepening, diversifying, and broadening collaborations over time. Commentators have portrayed alliances as strenuous balancing acts involving sometimes incompatible interests (Das & Teng, 2000; Doz & Hamel, 1998). Strategies for allying over time are attempts to manage this balance according to different logics.

Expanding To begin, some new entrants blast onto the scene and rapidly ramp up their portfolio of collaborators, seeming unconstrained by either hazards or capacity. The logic here is simply to get more alliance capacity, through investing internal resources. Often, such firms are carriers of critical new technologies. In the genomics area, Millenium made a splash by generating more than $2 billion through R&D partnerships with six different pharmaceutical giants. Arqule, another genomics entrant, rocketed from “0 to 60” by establishing dozens of affiliations with venture capital firms, DBFs and pharmaceuticals in its first few years of existence. This strategy derives from a network-theoretic perspective that emphasizes the competitive advantage of working in teams of allied organizations. Firms invest in routinizing structures and practices for collaborating that allow them to expand their alliance capacity. As a pure type, expansion occurs where

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the number of alliances increases without any change in the structure of individual relationships or the overall composition of the portfolio. Some of this may simply represent firms getting up to speed, although the latter is perhaps better reflected when increases in volume are accompanied by an extension of scope of activity. But, some if it also represents increases in alliance capacity.

Retreating Some companies begin, out of necessity, with external linkages but upon obtaining success with their initial products, they decrease their involvement with outside parties. Amgen, by some standards the most successful biotech firm, is a good example of this approach. It met with early success with its initial lead drug, Epogen, and opted to forego further collaborations in favor of internal expansion and a strategy of acquiring smaller, struggling young biotech companies. This strategy derives from the perspective that alliances clearly have many benefits for new firms, but collaboration also entails risks. Indeed, cooperation with potential competitors was once regarded only as a provisional or transitional step taken to enter new markets, spread risks, or to share early stage costs of R&D (Mowery, 1988; Porter, 1986). Cautious observers have stressed the threats of information leakage, adverse selection and moral hazard, and hold-up problems that attend various types of interfirm relationships (see the review in Holmstom & Roberts, 1988.) Others see alliances as learning races in which partners try to outlearn each other in order to appropriate common benefits into private ones (Hamel, 1991). Retreating occurs where a firm decreases the volume of alliances without increasing some other dimension of collaboration. The logic is to use alliances to get started, learn functional competencies from your teammates, and then go solo to minimize hazards.

Holding Course Rather than retreating from external affiliations or ramping up alliances, some firms stay the course and use the resources garnered from the successful launch of new products to reinvest in a cycle of collaboration. Genentech, another biotech industry bellwether, has developed novel medicines in a variety of therapeutic areas and uses collaboration with small companies and research centers to move into fast-developing areas, thus renewing its mix of ties as it builds its pipeline of new medicines. Chiron, also one of the larger biotechs, continually renews its mix of collaborations as it diversifies its coverage of different therapeutic areas.

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This approach acknowledges what appear to be diminishing returns to experience with and numbers of alliances (Powell et al., 1999), reinforcing notions from information processing theories that, conditional on their age, size, and so forth, firms may face some finite capacity for alliances. The logic here is to recognize and work at or near alliance capacity.

Deepening Building on the knowledge-based view of the firm, SBFs might respond to the challenge of managing the hazards and diminishing returns to alliances by deepening relationships with individual partners. The logic is to get more out of alliance capacity by getting more out of each alliance. Genzyme, the largest biotech in the Boston region, has moved from R&D linkages with smaller firms and research centers to clinical trials and co-development activities. The number of its partners stays relatively constant, but the depth of its ties change as the relationships evolve to cover multiple stages of the production process and entail extensive joint contact. By developing more multiplex ties with individual partners, either through pursuing multiple collaborations or expanding an existing R&D partnership into clinical development or manufacturing, SBFs increase the points of contact between the two organizations. Organizations with both multiple and/or multifaceted ties to others are likely to have developed better protocols for the exchange of information and the resolution of disputes (Powell, 1998). Recurrent contacts facilitate a strategy of long-term relational contracting in high-risk contexts (Ring & Van de Ven, 1992) such as the “winner-take-all” world of scientific research. Parties that develop a broader bandwidth for communication through relational structures are likely to be more capable of transferring tacit knowledge and more likely to uncover idiosyncratic ways to combine their resources to advantage (Doz & Hamel, 1998; Kogut & Zander, 1992; Zander & Kogut, 1995).

Diversifying Other firms may try to extract more from alliances by reshuffling their overall portfolio. The logic is to get more out of alliance capacity by getting more out of the structure of a portfolio. One approach is for firms to pursue economies of scope by diversifying types of activities. The advantages of economies of scope are well-known. Competences learned from managing one type of alliance activity can be appropriated to managing alliances of other types (Parisi & Henderson, 2001;

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Powell et al., 1996). As applied to collaboration in a knowledge-intensive field, diversity of alliance activities also reflects scientist-entrepreneurs commitment to re-investing in new upstream projects as other projects advance downstream. Rather than internalizing the new projects to protect against the hazards of alliances, this strategy emphasizes that experience lessens those hazards. At the same time, alliance experience combined with diverse points of contact into the information network enhances the firm’s ability to identify and absorb knowledge and exploit resource synergies (Powell et al., 1999).

Broadening Other firms may try to extract more from alliances by reshuffling their overall portfolio in a different way. The logic is again to get more out of alliance capacity by getting more out of the structure of a portfolio, but here firms pursue “creative abrasion” by broadening forms of partners. Following ideas initially developed by Penrose (1959, pp. 222–225), one strategy for SBFs is to locate at the interstices of fast-developing research areas and new technologies where they can play a bridging role linking participants in different kinds of organizations and acquiring competitive capabilities from organizations in different arenas (McEvily & Zaheer, 1999). In the area of commercializing scientific advances, heterogeneity in the portfolio of partners allows SBFs to learn from a wider stock of knowledge.1 Organizations with a broader network range are exposed to more experiences, different competencies, and added opportunities for discussion and debate. Such a setting creates an environment in which “creative abrasion,” the synthesis that is developed from multiple points of view, is more likely to occur. In this view, “innovation occurs at the boundaries between mind sets, not within the provincial territory of one knowledge and skill base” (Leonard-Barton, 1995, p. 62). A strong tradition of theory and research, running from Simmel (1954) to Merton (1957) to Granovetter (1973) to Burt (1992), makes abundantly clear that there are informational, status, and resource advantages to having a broad and diverse social circle. Networks rich in non-redundant contacts provide fast access to valuable information (Burt, 1992). How frequently broadening occurs is somewhat dependent on how we define it. When firms broaden their reach, this can occur with or without an attendant increase in scope, and firms broaden can their reach with or without also expanding their volume of alliances. Whether by diversifying activities or broadening partner forms, or both, restructuring is a theoretically tempting strategy. By having access to a more diverse set of activities, experiences, and collaborators, SBFs not only broaden the resource and knowledge base that they draw on, but position themselves to combine external

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knowledge and resources in novel and inimitable ways (Dyer & Singh, 1998; Gulati et al., 2000), increasing “combinatorial capabilities” (Kogut & Zander, 1992).

KNOWLEDGE, NETWORKS, AND ADVANTAGE The advantages of a heterogeneous team are well established in both social theory and network analysis. In the area of commercializing scientific advances, we note additional gains from network diversity. One, heterogeneity in the portfolio of partners allows SBFs to learn from a wider stock of knowledge. By having access to a more diverse set of activities, experiences, and collaborators, SBFs are broadening the resource and knowledge base that they draw on. By developing more multiplex ties with individual partners, either through pursuing multiple collaborations or expanding an existing R&D partnership into clinical development or manufacturing, SBFs increase the points of contact between the two organizations. When relationships are deepened, greater commitment and more thorough knowledge sharing should follow. Organizations with both multiple and/or multifaceted ties to others are likely to have developed better protocols for the exchange of information and the resolution of disputes (Powell, 1998). Parties that develop a broader bandwidth for communication are likely to be more capable of transferring tacit knowledge. SBFs may, therefore, have motive to develop deeper and/or diverse collaborations with a wider array of partners as they grow and age. SBFs have a different kind of competence, possessing a specialized expertise often needed by their larger industrial counterparts. Hence, they are vital teammates. Yet their scientific know-how is most valuable, we contend, when marshaled through networks with diverse contacts. The critical question becomes whether SBFs have the capacity to establish and manage broad, expansive networks. We expect growth and aging, along with success, will enhance an SBF’s ability to mobilize, manage, and strengthen these networks. Implicit in our analyses is the recognition that SBFs, even the largest ones, are typically small in comparison to the industrial giants that have dominated the U.S. economy during most of the 20th century. We begin our arguments by considering how the processes of growing and aging influence organizations’ capabilities for collaboration. As firms add employees and expand their operations internally, they face a series of choices. Organizations could opt to pursue more activities internally and fewer externally as they increase internal capacity. In contrast, a persistent finding from a diverse set of empirical studies is that internal R&D intensity and the level of technological sophistication are positively correlated with the number and intensity of strategic alliances (Freeman, 1991; Hagedoorn, 1995). Recent network studies have emphasized that

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growth is an outcome of network position (Baum et al., 1999). Powell et al. (1996) show that centrality in an industry network generates access to resources. Firms centrally positioned attract new employees and participate in more new ventures. Thus, “a firm grew by becoming a player; it did not become a player by growing” (Powell et al., 1996, p. 122). Seen in terms of contemporary work on learning and innovation, increased size can bring greater “absorptive capacity,” enabling firms to better exploit external sources of knowledge (Cohen & Levinthal, 1989, 1990). Absorptive capacity represents more than access to information, it also entails the ability to value, assimilate, and utilize information. Adding more staff may increase the odds that learning from collaboration occurs, and that knowledge spills over across projects and partners. Moreover, positive feedback from a practice can prompt firms to apply the practice to new activities (Child & Kieser, 1981). Consequently, Hypothesis 1. As SBFs become larger, they expand the volume and scope of collaboration; increasing the number of external ties and the diversity of types of collaborative activities. A well-established finding in the sociology of organizations is that growth is associated with increased complexity of activity and greater differentiation of structure and expertise (Blau, 1970; Haveman, 1993; Kimberly, 1976; Scott, 1992, pp. 258–267). The key question is whether growth and differentiation produce bureaucratization, as is often observed, or increase the diversity and expertise needed to collaborate on more complex projects and to reach and collaborate with heterogeneous types of partners. Externally, growth has two effects. One, larger size enhances a firm’s bargaining power, lessening its dependence and allowing it to garner less restrictive and exclusive agreements. Two, growth provides a signal of a firm’s quality and value as a collaborator to a broad range of potential partners, including those that may not be expert in assessing a firm’s science. Dependence on a single large partner is likely to inhibit the ability of small firms to obtain other partners, as large rivals are likely to prefer not to work with competitors. As small firms grow, they thus become less dependent, and, with a more developed internal structure, face less uncertainty. Uncertainty has been found to be associated with exclusivity and homophily in exchange relations (Podolny, 1994), thus increasing size should enable firms to develop promising ideas and leverage them with more partners from a wider range of sectors. Hence, we predict that increases in size allow SBFs to collaborate more broadly and/or intensively with partners. Hypothesis 2. As SBFs become larger, they broaden their collaborative reach; collaborating with more partners and more kinds of partner organizations; and engage in more multi-party and multiplex arrangements (multi-tie partners) and more complex agreements (multi-activity ties).

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The effects of age have been well studied in the organizations literature. Building on Stinchcombe’s (1965) key insights, there has been a great deal of attention paid to the liability of newness (Hannan & Freeman, 1989, pp. 245–270). Younger firms need to build credibility with consumers, suppliers, creditors and the like and overcome initial reservations toward a new entity. Given these obstacles, it is not surprising that SBFs turn to venture capital firms, law firms, and established companies for assistance, as well as rely on universities and government laboratories for key technologies. Consequently, survival often hinges on location in a supportive network in order to overcome initial questions about credibility and reliability. As a small firm ages, it faces a choice. Having overcome various liabilities, the company can become less reliant on external parties. Or, as the firm matures and expands its activities downstream from its initial research focus into product development, production, and sales, it may opt to become involved with more outside partners as it takes on new tasks. Researchers have stressed the importance of research prowess as an admission ticket to information networks in science-based fields (Arora & Gambardella, 1994; Mowery & Rosenberg, 1989; Powell et al., 1996). A firm can utilize its R&D ties to gain support for downstream activities. Other researchers have emphasized that initial ties admit the firm’s members into social circles, where the norms of collaboration become stronger over time (Gulati, 1995a, b; Uzzi, 1996). As a firm’s social circle broadens over time, the firm may combine its experience and recognition to reach a wider span of partners for key activities, selecting and being selected by a heterogeneous group of collaborators for critical functions such as R&D, commercial development, or sales. For firms that collaborate when young, age also brings experience at managing collaborations. Once developed, such experience becomes a skill to be employed in new domains, and imposes a cost to retreating from collaboration in prior domains. Further, the more experienced a firm becomes at collaboration, the more they will establish a reputation for being a reliable partner so that others will perceive them as unlikely to act opportunistically (Podolny, 1993). From a firm’s perspective, experience reduces uncertainty, thus allowing the firm to build on their reputation to work with kinds of partners with whom they have not interacted in the past. Consequently, Hypothesis 3. As SBFs become older, they engage in more downstream as well as more complex external activities, and they increase the reach of their ties (become involved with a more heterogeneous group of partners) for each activity. In many emerging industries with a strong science base, companies spend much of their early years burning up investors’ money on costly initial research. External

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support is the lifeblood during this phase and, as noted above, R&D alliances serve as the portal to benefit-rich networks. As the research program develops and moves into application and testing, the prospect of a new product looms larger. As the product cycle unfolds, companies have differential needs, and the nature of the reliance on others shifts depending on the stage of product development. For the successful firm, products are eventually released and sales generated. The firm again faces a choice. From a strategic standpoint, earnings can be used to integrate R&D and other activities to protect a firm’s technology and know-how. A number of scholars have argued, in contrast, that companies in knowledge-intensive businesses are involved in a cycle of learning in which initial success generates the resources that allow advancement to the next level. The “cycles of learning” argument suggests that organizations respond to the positive feedback provided by initial success of sales and/or profits by re-investing in external research affiliations (Powell et al., 1999). Hypothesis 4. As SBFs generate greater earnings, they subsequently engage in more external R&D collaborations. The above arguments suggest that SBFs play a critical role in binding innovation networks together, deepening, extending, and reshaping networks of collaboration. To evaluate this conjecture, we need to understand the range of possible roles performed by science-based companies. For example, SBFs may provide the ideas that jumpstart the innovation process. Because these firms are both closer to the underlying basic science and have a deeper understanding of the technology, they continue to exert influence as the ideas are translated into commercial products. In this scenario, the independent firm is able to use its knowledge to orchestrate production through an innovation network. In contrast, independent firms could serve as the sources of new ideas or novel products, but, due to their small scale, they are unable to develop, produce, or market the final product. Harrison (1994) has argued that small firms are largely captives of large firms’ networks, and thus limited to discrete stages in the production process. Or the smaller firms may follow a specialist strategy (Carroll, 1985), remaining a research boutique that generates ideas, while larger and more established firms pursue their smaller partners’ most promising leads and typically reap the lion’s share of the benefits from innovation. Alliances between small and large firms are forged for symbiotic reasons under this scenario, with smaller firms serving as incubators for new products and large firms controlling production and distribution channels. Alternatively, the process of innovation may favor a few winners at the expense of other parties. An inner circle of key participants may dominate the innovation network, and these centrally positioned actors can reap greater rewards from their strategic location in the chain of production. This inner circle might well comprises

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an elite mix of established corporations and SBFs, research institutes, financiers, and providers of other key resources that play a disproportionately large role. Finally, industrial structure might be highly fluid, with different organizations taking on more central roles at different times and in different places, as well as for different stages of the product life cycle. Under this latter scenario, there is neither an inner circle of participants, nor a boutique or orchestrating role for small firms, but a changing division of labor in which industrial leadership varies according to capability and resource availability. We assess the veracity of these divergent accounts of the division of labor by positing the following arguments: Hypothesis 5A. SBFs play an active role in every stage of product development rather than solely in research and development. Hypothesis 5B. There is a heterogeneous group of participants for each stage of product development, rather than an elite cadre that dominates every stage. Hypothesis 5C. SBFs play a lynch-pin role, hence they are active in all stages of product development, while other participants play more specialized roles.

DISCUSSION AND IMPLICATIONS We have argued that as SBFs grow, age, and succeed, they will (1) increase the number of alliances they engage in, (2) deepen existing alliances, renew R&D collaborations, and diversify their alliances into new business functions, and/or (3) become involved with a more heterogeneous set of partners. We have referred to these developments as expansion in volume, diversifying scope, and broadening the reach of their collaborative teams. In short, we predict a strong pattern in which “successful” SBFs are pursuing multiple collaborations with a more diverse group of partners, rather than establishing integrated, centralized structures or forming exclusive networks as fortresses against competition.2 In our view, there are clear gains from this strategy, despite some difficulties associated with it. Having an expansive, far-reaching network exposes a firm to many challenges, but in a fastmoving field there are also costs to not forging ahead and expanding the network portfolio. In the rapidly developing field of the life sciences, the core value of a SBF is its scientific expertise and technological leadership in a specific disease category. Maintaining that expertise enables the SBF to be an attractive partner. Linking with diverse participants for different activities permits a company to leverage its skills across a range of relationships with parties that have few interdependencies among themselves, but are connected through the biotech firm. Such a strategy

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has obvious benefits for a small science-based firm. If successfully pursued, the SBF contributes to the agendas of a diverse set of organizations without rendering itself redundant by allowing too much of its knowledge to migrate to others. By interacting with diverse participants, the SBF plays an orchestrator role rather than a specialist or dependent one. Network diversity thus allows little encroachment on the small firm’s scientific competence. Yet this is not a situation of a third party broker playing off others to maximize its own gain. The process of drug development is lengthy, costly, and protracted. The orchestrator role requires building across relationships for the advantage of all the participants. The better the transfer of knowledge and skills among the participants, and the better connected that partners are to one another, the richer the flow of information to all involved. Rather than exploiting one’s position, participants in these learning races must find a way to improve both their and their partners’ capabilities. On first observation in the biotech industry, we see SBFs actively linked to a great variety of different types of organizations – commercial, governmental, nonprofit, domestic and foreign. We suspect, but cannot demonstrate at this point, that these heterogeneous links represent alliance webs in different research and therapeutic areas. Put differently, competition in this field is not firm vs. firm or one firm’s network portfolio vs. another’s, but multilateral competition of different partners and different alliances on divergent projects. A collaborator on a cancer drug is likely to be a competitor in Alzheimer’s research. But such complex webs of multiple relationships present organizational challenges and tax the ability of an organization to sustain numerous external ties.3 Many organizations have ample trouble managing their internal operations, thus these diverse linkages post additional problems of control and coordination (for further discussion, see Doz & Hamel, 1998, pp. 195–220; Gomes-Casseres, 1996, pp. 157–166). Maintaining productive linkages with multiple parties is difficult; learning how to learn across relationships is even more so. Add to these operational challenges the strategic challenge of simultaneously learning from a partner while protecting core skills and knowledge base and the task is daunting. There is an inherent tension in this new form of interorganizational collaboration. An organization has a set of skills that makes it attractive to others and provides it with bargaining power. To be a valuable partner, it must share some of those skills and the knowledge or resources it acquires to create something it cannot create on its own. But it has to protect itself from letting its skills leak into the public domain, from learning less rapidly than its partners, and from being only a provider of a resource that others exploit to greater use. Given these challenges, heterogeneity is one solution. By having diverse collaborators, each participant provides a resource that the other party values and cannot readily find through alternative means.

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Finally, we should consider that in fields where knowledge is developing rapidly and the sources of scientific expertise are broadly distributed, there is a huge cost to inaction or inertia. In previous research, we have seen that repeat trading with similar partners lead to restricted access and cognitive lock-in. Powell (1985, pp. 202–207) found that repeated exchanges among a small circle of book editors and authors lead to parochialism and ossification. Glasmeier (1991) attributes the failure of Swiss watchmakers to adapt to digital technology to the restricted and insular nature of their contacts. Similarly, Grabher (1993) suggests overembeddedness led to organizational inbreeding in the Ruhr steelmaking district, leading to the decline of the German steel industry. Thus, even though the challenges of coordinating heterogeneous networks may be considerable, the alternative of parochialism is not viable.

CONCLUSION We seek to confirm the argument that commercial organizations in the life sciences are actively expanding their range of collaborations, and diversifying the array of business functions they collaborate on, as they grow larger, older, and become successful. If empirically demonstrated, we will attribute these results to a general process of organizational learning in which SBFs with diverse ties are exposed to a broader stock of knowledge. We could then draw from these results the conclusion that interfirm collaboration is not a transitional stage, or stepping stone, to success or maturity, but a significant organizational practice in this technologically advanced field. Extending this argument, we suggest this strategy of interfirm collaboration represents neither dependency nor specialization but an alternative way of accessing knowledge and resources. Our claim that this form of organizing is viable needs to be tempered in several ways. First, we have consistently linked these biotech firms to the adjectives emerging or small. Some of them, however, are not so small; the largest has 7500 employees and a number have sales in excess of one billion dollars. These are hardly weak or tiny firms. But all of them are relatively young, and even the largest biotechs pale in size compared to the large pharmaceutical corporations, all with employee counts numbering in the tens of thousands, or government research institutes, or elite research universities with whom they collaborate. To be sure, small is used as a relative term throughout, but the biotech firms are typically the smaller and younger party in any exchange relation. Second, we argue that the science-based firms in the life sciences are not specialists because they are diversifying their activities, both internally and externally, to all stages in the production process. Thus, they are not focused

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on only one aspect of production. But resource-partitioning arguments have primarily, though not exclusively, focused on product-market segmentation. Were we to analyze our companies in terms of the disease categories they concentrate on, we suspect we would find a persistent relationship: the smaller the company, the more focused they are on a single medicine or disease; as they grow, they branch into related therapeutic areas. With success and subsequent reinvestment in R&D, the SBFs branch into new therapeutic areas. This observation, however, represents conjecture at this stage in our research and awaits empirical testing. We have also not separately modeled the dynamics of expansion and contraction. The general picture we present is one where firms that are growing are broadening the network reach while other firms are both less attractive and less able partners and consequentially their networks are not expanding. But, are the networks of these firms actually collapsing, and if so, is there a difference between firms that are standing still, so to speak, and those that are shrinking in size?4 Finally, our ideas need to be considered in the context of the life sciences field, which both has some idiosyncratic features as well as characteristics shared with a number of high technology industries. Advances in basic science have continued to play a critical role in this field, and universities have a key hand in this process (Liebeskind et al., 1996; Powell & Owen-Smith, 1998; Zucker et al., 1994). In few other high tech industries have universities continued to exert such considerable influence for such a sustained period of time. Consequently, the industrial structure has evolved, in part, out of the invisible college structure of the academy. Moreover, scientific leadership is divided rather than concentrated, with diverse sources of expertise located in many advanced industrial nations. Again, the fact that scientific excellence is broadly distributed promotes interorganizational collaboration. Finally, interorganizational relations are largely focused on mutual learning, that is, developing new medicines or treatment regimes, and creating new medical markets. This orientation toward mutual gain extends the shadow of the future and lends itself to the expectation of future interaction. Effective sharing of knowledge is enhanced by awareness of a shared destiny. This open-ended time frame and focus on joint learning is not unique to the life sciences, however. Many new technologies, much more nascent than biotech, involve the delivery of new products or services and/or tap markets that did not previously exist. And fields such as e-commerce or wireless communications do not face the long arduous period of new product development, which presents many occasions for disappointment and defection, that characterizes biotech. The life sciences have also benefited from a decade of increases in research funding, both in the public sector at the National Institutes of Health and in the private sector, where increases in research spending have even outpaced government spending. But, again, a wide range of new research fields have benefited from

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this decade-long economic expansion. Indeed, the availability of venture capital funding has spurred the growth of a number of new industries. The coincidence of industry growth and a favorable economic environment raise the question as to whether these organizational arrangements are the product of a munificent environment. Many commentators have suggested that an eventual shakeout, or consolidation, will occur in these new fields. Others have contended that biotech and other new industries will eventually be absorbed by more mature, established firms. Still other pundits anticipate that with maturity will come a reversion to more traditional organizational arrangements. Obviously, access to capital in research-intensive fields is critical and the terms of contractual agreements vary with respect to the availability of capital (Lerner & Merges, 1998). But despite stiff competition for financing from other emergent industries, and the opening and closing of windows of opportunity for going public, the strategy of accessing external sources of expertise and support has not only continued, it has been deepened and refined. In sum, a single industry over a little more than a decade does not provide a definitive answer as to whether small science-based firms and collaborative practices are supplanting more traditional organizational arrangements based on hierarchy and economies of scale. Nevertheless, we follow March (1991) in arguing that all organizations face the challenge of balancing the demands of exploration, or experimentation with novel alternatives, and exploitation, the refinement and extension of existing competencies and technologies. We are persuaded that a good deal more attention needs to be paid to the processes of exploration and to those industries in which success is based on winning learning races. In such fields, more horizontally-based interorganizational collaborations appear to be a cornerstone of organizational practice, and these new routines are being actively developed.

NOTES 1. We thank Steve Klepper for first emphasizing this point to us. 2. Obviously, success is a relative term. None of these firms are hugely successful in comparison to pharmaceutical giants such as Merck, Novartis, or Pfizer. But success is used multi-dimensionally here; these firms are growing in size, surviving, and, in some cases, generating sufficient revenues for reinvestment. 3. An important question is just how much diversity can an organization sustain (Uzzi, 1997). In a recent paper, we found declining returns to network diversity and experience after an organization crossed a fairly high threshold of connectedness. Once centrally positioned, with a broad portfolio of partners, there were scant returns to performance from adding even more collaborators (Powell et al., 1999). 4. We thank Brian Uzzi for provoking this question.

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ACKNOWLEDGMENTS An earlier draft was presented to the Organization Science Winter Conference, Feb. 2000, the SCANCOR workshop, the GSB strategy workshop at Stanford, and the OB/IR workshop at the Haas School at UC Berkeley. We thank various participants, especially Trond Petersen and Toby Stuart, for useful feedback. We are particularly grateful to Joel Baum, Frank Dobbin, and Brian Uzzi for detailed and very helpful comments. Thanks also to the Co-evolution of States and Markets group (John Padgett, director, Sanjay Jain, David Stark, Sander van der Leeuw, Doug White, and Xueguang Zhou, participants) at the Santa Fe Institute for extensive commentary. Research support provided by National Science Foundation grant #9710729, W. W. Powell and K. W. Koput, co-principal investigators, and the Sante Fe Institute, where the final draft was completed.

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THE IMPACT OF COLLABORATIVE MOTIVATION ON COMPLEX MULTI-AGENCY PARTNERSHIPS: A CASE STUDY OF THE UNITED KINGDOM Janine Stiles and Paul Williams No single actor, public or private, has the knowledge and information required to solve complex, dynamic, and diversified problems; no actor has an overview sufficient to make the needed instruments effective; no single actor has sufficient action potential to dominate unilaterally. (Kooiman, 2000).

INTRODUCTION This chapter compares the literature on public and private sector collaboration and considers the implications for success in collaborative relationships between the sectors. It highlights key comparative drivers of intent for both types of organization, explores the relationship between them, and proposes a framework for primary investigation based on the relationship between the key areas of competitive positioning and level of risk. A case study analysis of two complex strategic partnership initiatives in Wales,1 both involving collaboration between local health boards, local authorities, health trusts and other statutory, voluntary Complex Collaboration: Building the Capabilities for Working Across Boundaries Advances in Interdisciplinary Studies of Work Teams, Volume 10, 83–108 Copyright © 2004 by Elsevier Ltd. All rights of reproduction in any form reserved ISSN: 1572-0977/doi:10.1016/S1572-0977(04)10004-6

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and private sector stakeholders is then used to illustrate the complexity of successfully managing relationships in this context.

BACKGROUND The use of collaboration as a form of business operation has grown rapidly over recent years as organizations find themselves increasingly challenged by more complex customer demands, competitive challenges and new market opportunities (Barrett, 1999; Butler & Gill, 2001; Kale et al., 2000; Schruijer, 1999). The notion of partnership can be seductive within this new and turbulent arena, as it offers a relatively rapid, low-cost and flexible opportunity for an organization to leap-frog regulatory boundaries, enter new markets, acquire new skill sets, develop complex new product/service offerings, and facilitates the easy exploration of multiple options. This is in contrast to the high cost and restrictive requirements of strategy based on acquisition or merger (Doz, 1992; Doz & Hamel, 1998; Stiles, 2001). However, an increasing amount of evidence shows that collaborative partnerships suffer from a dramatically high failure rate, and are usually inherently far less stable than more traditional forms of operation (Anand & Khanna, 2000; Doz & Hamel, 1998). The history of collaboration continues to be haunted by the skeletons in its cupboard, with failure rates of anything between 50 and 80% regularly reported from research projects studying this phenomenon. A wide range of interrelated factors often mitigate against the success of this form of organization. These include perceived differences in each partner’s external environmental influences, varying customer demands, competing aims and objectives, different organizational and professional cultures, contrasting planning and financial decision making processes, different accountability systems and forms of transparency, problems of language, imbalances in power configuration, as well as profound issues of complexity and lengthy timescales involved in managing the collaborative process (Huxham & Vangen, 2001). The way in which organizations respond to these factors influences the extent to which they enter and operate within the collaborative relationship, determines the choice of whether they pursue a competitive or collaborative approach to the relationship, and ultimately plays a significant role in shaping the success of that relationship (Stiles, 2001).

MULTI-AGENCY PARTNERSHIPS Recently, multi-agency partnerships in the United Kingdom have burgeoned across all main policy areas including health and social care (Bartlett et al., 1994;

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Labonte, 1993; Loxley, 1997; Scott & Thurston, 1999), social exclusion (Geddes, 1998), urban regeneration (Harrison, 2000), crime and community safety, and education. This approach to policy making is largely imposed and driven by British central government. Although there is by no means universal consensus, both the center right and center left of the political spectrum now envisage a role for the private sector in the planning and delivery of public services. However, the means of achieving these ends are still highly contested. Under the stewardship of successive Conservative administrations during the 1980s and 1990s, New Public Management, with its focus on private sector management methods, in combination with New Institutional Economics, with its aim of introducing competition into the public sector, were used to justify the dismantling of public sector monopolies, and creating new service sector markets for private companies. This resulted in the genesis of markets and private sector disciplines as a method of governing in the public sector. Purchaser/provider splits, quasi-markets, outsourcing, externalisation, public-private partnerships, and the formation of various types of arms length and special purpose companies, and non-departmental public bodies now proliferate across many areas of local and national government (Williams, 2003, p. 15).

Although political control at a national level in the United Kingdom has changed since 1997, and the language and rhetoric now centers on the term “partnership,” the involvement of the private sector still remains an important plank of government policy, and the analysis of Bryson and Crosby (1992, p. 92) remains true: In today’s shared-power, no-one-in-charge, interdependent world, public problems and issues spill over organizational and institutional boundaries. Many people are affected by problems like global warming, AIDS, homelessness, drug abuse, crime, growing poverty among children, and teen pregnancy, but no one person, group or organization has the necessary power or authority to solve these problems. Instead, organizations and institutions must share objectives, resources, activities, power, or some of their authority in order to achieve collective gains or minimize losses.

Thus an approach to public policy in the United Kingdom is predicated on forms of collaboration and partnership between different types of organizations – government, statutory, voluntary, private and independent. The notion of “governance” underpins this approach, and relates to a set of participants that are drawn from, but also beyond, government. This reflects a continuing blurring of boundaries and responsibilities for tackling social and economic issues, particularly between public and private interests, and the voluntary sector in the United Kingdom. Critically, as Stoker (1998, p. 18) comments, it acknowledges that “The capacity to get things done does not rest on the power of government to command or use its authority. It sees government as able to use new tools and techniques to steer and guide.”

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Yet it may be argued that an even greater potential exists for differences, and consequent lack of compatibility, to occur between multi-agency organizations than between firms operating solely within the private sector. Many government agencies have supported the development of partnership agreements in attempts to reduce the problems that can arise in this context, but with little success to date (European Commission, 1991; McDonald, 2001). Therefore, this chapter considers the impact of collaborative motivation on the likely effectiveness of forms of multi-agency partnership, and highlights the flavour it imparts to the collaborative process in terms of leadership, power, trust and other elements. Initially, the authors review existing research to identify the key drivers of motivation in both sectors. This is followed by the design of an investigative framework that sets out to determine how these might influence the success or failure of a collaborative relationship involving the two sectors. Finally, this framework is linked to two case examples and conclusions drawn.

THEORY AND FRAMEWORK DEVELOPMENT Private Sector Motivational Drivers Existing literature in this field identifies a number of factors driving interorganizational cooperation within the private sector. These stem from the need for private sector firms to respond to the dynamics occurring in the increasingly competitive environment they find themselves now operating in to achieve or maintain their market position as industry sector boundaries continue to merge, and customer expectations are driven higher by new technological developments. Traditionally, alliances tended to be viewed as a means of combining resources in order to benefit from the synergies produced by such ventures (Berg et al., 1982; Bleeke & Ernst, 1991; Mohr & Spekman, 1994). This is still a key factor for many ventures driving entry into the relationship as shareholders push for increasing returns on their investment. Where successful, combining resources can help to generate economies of scale and increased efficiency of operation, thus reducing each partner’s overall relative costs and consequently improving the bottom line returns and boosting profitability (Grant, 1991; Mahoney & Pandian, 1992). Also, a reduction in transaction costs can develop and be used to benefit the partners, thus enabling competitive advantage through an increase in economic efficiency (Kogut, 1988; Williamson, 1975). However, the extent to which each partner may benefit is not pre-defined. Much will depend upon the equity of distribution of the benefits between the partners; a factor that may be influenced in turn by the symmetry of the relationship and how this develops (Bleeke & Ernst, 1991). Also,

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profit growth through economies of scale or reduced transaction costs takes time to achieve and is often disappointing in the first two years of a partnership (Doz & Hamel, 1988). Initially, diseconomies can even occur as the partnership suffers from duplication of functions, or time-lags on agreements between the parties involved. Thus the profit motivation, though widely recognized as being a key driver and an expectation for shareholder returns, is not always easily achieved in a collaborative arrangement. The need to grow market share as a defensive mechanism against growing competition in the market place is behind many organizations’ drive to collaborate. One type of response to this is to enter partnerships that can enable access into new or uncertain markets with high potential. Joint ventures with local firms in different economies are commonly used as a way for multinational organizations to enter and operate within uncertain yet high-potential transitioning markets (Steensma & Lyles, 2000). This allows the firm to establish a presence within a new region through a partner while benefiting from the specific local knowledge of national policy, laws and customs the partner can supply (Sharp & Barz, 1997). This approach can be highly successful. Indeed, previous research has found that international joint ventures of this type are frequently more profitable than the state-owned local enterprises, and can provide a stabilizing influence in transitioning economies (Hamar, 1993). However, cultural dissimilarities can occur in any collaborative venture, and if not addressed early on, may result in collaborative failure (Anand & Khanna, 2000). The risk of loss of assets or returns to the partner can also increase in economies where stability is fragile or the economy in transition and the local situation moves into economic crisis or a closure of borders. The need for more rapid product development, or resource acquisition and skills transfer have also been recognized as key drivers in the growth of partnerships as firms try to respond to increasingly aggressive competition in their traditional markets, or try to maintain a lead in a consolidating industry. Smaller firms in particular are often constrained in terms of resources, and take time to develop ideas into innovative solutions. Collaboration with a larger firm enables these types of organizations with innovative idea generation capability to realise their full potential within the market place much more rapidly (Cooper, 2001; Rothwell & Dodgson, 1991). As shortening product life cycles and complex product requirements put increasing pressure particularly on high technology sectors, even larger firms are also finding that the challenge of maintaining the lead in a field is becoming more problematic (Duysters et al., 1999). Consequently, the attraction of partnership to share costs, research intellect or to bring together different technologies has significant benefits. However, this need for resource sharing and skill building can present a risk to participating firms. Where particular skills

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or technology capabilities are found to be transferable, one partner may suffer from a loss of its core competence or capabilities and, ultimately, a loss of market position as the acquiring partner ends the collaboration and continues to compete independently. Indeed, Ahuja (2000) argues that this is a key objective for some players as “Firms (will) seek to obtain control over those factors of production that can provide them with a competitive edge over their closest rivals” (p. 353). Hence, the need for each partner to protect its strategic resources needs to be recognized (Lei & Slocum, 1992; Lorange & Roos, 1992). In summary, collaboration by private sector organizations appears to be driven by the need to compete and satisfy shareholder profit expectations within an increasingly international, competitive and uncertain environment where customer expectations of products and services are becoming ever more complex and sophisticated. Therefore, the collaborative option is pursued in an effort to respond to this challenge through anticipated gains in cost, efficiency, market size and/or access to competitive resources or capabilities. However, the recognized benefits are also accompanied by potential risks which organizations need to manage or control to be successful.

Public Sector Motivational Drivers Until fairly recently, the planning and delivery of public services in the United Kingdom has been largely organized around a model of public sector monopolies – large, highly functionally differentiated and task orientated bureaucracies, often statutorily prescribed, and designed to deliver public and welfare services autonomously. Such organizations were driven by the virtues and values of a public service ethos, and legitimized by, and accountable to, a democratically elected body of representatives at national and local government levels. The defining challenge to the supremacy of this model was delivered by successive Conservative administrations in the 1980s and 1990s as a response to the growing problems of quality and efficiency in many public services. Major concerns were expressed about the way in which they were planned, organized and delivered particularly in relation to their producer as opposed to customer focus, inadequate or absent performance management regimes and general poor value for money. An alternative model was informed by two predominant philosophies. The first was New Public Management (Pollitt, 1990; Walsh, 1995) with its strong belief in the merits of private sector values, methods and working practices as an antidote to public service inefficiencies. The second was New Institutional Economics (Clarke & Newman, 1997) with its intention to introduce competition into the public sector by the creation of markets and opportunities for the private sector

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to compete for business. These philosophies were subsequently translated into public policy through a variety of policy instruments and interventions including compulsory competitive tendering in local government, the creation of quasi markets and purchaser/provider splits in the National Health Service, and the establishment of forms of non-departmental public bodies and next steps agencies designed to offer more freedoms and flexibility than was possible within traditional government organizations. Although there has been a change in the political persuasion of national government since 1997, it has not heralded a radical reversal in the approach to involving the private sector in the provision of public services. The language has changed – the talk is now of public/private partnerships and private finance initiatives rather than privatization – but the intent remains the same. It is an example of the “third way” approach (Institute of Public Policy Research, 2001; Office of Public Services Reform, 2002) and a key plank of the British Government’s “modernization agenda.” The rationale for such partnerships is highly contested territory. The British Government argues that the private sector is intrinsically more innovative and efficient than the public sector; its managers are more skilled and deliver better value for money; and public/private partnerships inject greater resources into the public sector and can absorb different types of risk. U.K. government policy has recently been set out in a document entitled “Reforming Our Public Services” (Office of Public Services Reform, 2002, p. 17) and this states that: alternative providers can also drive up performance across the service as a whole, even where the individual citizen does not gain a wider choice a result. Widening the market to create more suppliers of public services can improve the quality and management and value for money . . . public/private partnerships increase investment, with the private sector investment additional to that provided by the public sector . . . public/private partnerships are innovative schemes to increase investment and deliver swifter improvements in our public services (p. 17).

Opponents of this model challenge the so-called merits of this approach on a number of fronts, and point to the weakening of democratic accountability through lack in transparency and “commercial confidentiality;” the dangers of the profit motive gaining ascendancy over the public interest, and the argument that private sector investment is not additional to normal public expenditure because it is only a means of financing, with the costs of the investment having to be met by the public sector. In addition, the evidence that competition per se results in greater innovation and efficiency is contestable, as is the claim that the private sector possesses greater managerial skills than its counterparts in the public sector. A more fundamental objection concerns the increasing fragmentation of service delivery that results from public/private partnerships, and the problems of co-ordination that this presents for local and national governance. The pursuit of a holistic and joined-up approach to government is made more problematic in these circumstances.

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A second major stream to influence intent in the public sector is informed through concepts of holistic government (Perri 6, 1997; Perri 6 et al., 1999; Wilkinson & Appelbee, 1999) and network governance (Ebers, 2001; Jessop, 1997; Rhodes, 1996). Both take their starting point from the notion of “wicked issues” (Rittel & Webber, 1973) that are conceived as a special class of complex and interdependent policy problems afflicting contemporary societies – social exclusion, crime, health inequalities, poverty, unemployment and many more. These problems are cross boundary in nature, intractable, socially constructed by virtue of being framed through the lens of multiple stakeholders, not amenable to optimal solutions, non-linear in construction, and most importantly, not resolvable by single agencies or governmental sectors acting autonomously. The consequences of these influences are evidenced in the way policy is organized. This includes the placing of statutory duties on particular bodies such as local councils and health authorities to work in partnership, and the proliferation of various forms of interorganizational working – networks, strategic alliances, joint ventures – stimulated in particular by government initiatives, programs and pilots. Forms of partnership working are made a condition of access to funding opportunities. Consequently, it may be seen that motivation in the public sector in the United Kingdom to partnership is heavily mandated and influenced by national government. It is not voluntary but enforced and prescribed by a superordinate authority (Mackintosh, 1995; Oliver, 1990). There are a number of additional motivations and forces, more internal to public organizations, that impinge on the nature of public/private partnership formation (Clarke & Stewart, 1997; DETR, 2001). In a period of scarce resources and ever-increasing expectations on the quality and range of their services, public authorities are driven to forms of co-operation in order to achieve their own individual goals and objectives. This can take the form of a voluntary exchange of resources (e.g. finance, information, and status) and a working consensus around goals, functions, cultures and outcomes. This can be explained through a simple exchange perspective (Levine & White, 1961). However, the reality is that there is also competition for scarce resources made more complex by an underlying push for power and territory. Thus, one or more organizations are inducing others to interact within a particular domain, and bargaining and conflict are more commonplace – an aspect identified by Aldrich (1972) in his assessment of the power/resource dependency perspectives. The result is often an enlightened self-interest, but motivations are often multiple and conflicting in nature, and “true” motivations difficult to detect. Higher level or value-based intentions and drivers are also apt to confuse inter-organizational relationships. Notions of “the public interest” and “public sector ethos” can exert a significant influence, and certain client-oriented professional cultures such as those typically found in social

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care and health, are driven towards methods of working that value integration and co-ordination between different organizations. In summary, the key public sector drivers of multi-agency partnerships are very much a function of mandated co-operation orchestrated by national government; a rational/altruistic perspective grounded in concepts of holism and “wicked” issues; and a practical need to unlock resources through forms of co-operation that are rooted in exchange and resource dependency perspectives.

TOWARDS A FRAMEWORK FOR COMPARISON The task of linking the motivation or intent of an organization to engage in forms of inter-organizational working with that of the ultimate outcome or effectiveness of that relationship is considerable. Evaluation is a difficult task to manage within intra-organizational settings, and it assumes added complexity in partnership arenas (Hallett, 1995). Huxham (1996) also notes that the expectations and motivations of organizational actors may change over the course of the relationship as a result of on-going performance, additional information on partner abilities, intentions or reliability, and changing environmental conditions. Ebers (1997) further argues that an understanding of the conditions/context that lead to organizations with particular motivations to choose the partnership route, and the processes that lead up to a particular arrangement, is also necessary. A number of discursive models have been developed to try to deal with these issues. Of these, the authors consider that Oliver’s (1990) critical contingencies for inter-organizational relationship forming offers the most useful typology of causes and motivations, and therefore provides a relevant basis for the purposes of this study. These contingencies are listed as necessity, asymmetry, reciprocity, efficiency, stability and legitimacy. The typology allows for necessity to be either mandated or voluntary, with the remainder being all voluntary interactions. Additionally, although each determinant is separate, the contingencies are likely to interact and/or be multiple in particular circumstances. An application of this framework to existing theoretical and empirical research on collaboration suggests that a number of factors are influential in driving motivation within both private and public sector organizations. Similarities and differences between the sector drivers are also apparent and exert an influence on the overall compatibility of motivations within inter-sectoral partnerships. The following discussion considers these in relation to each of Eber’s contingencies. Necessity for collaboration in both sectors is driven by the need to respond to stakeholder demands. In the private sector this takes the form of shareholder expectations, which drive the company to seek increasing returns, fight for market

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share and defend market position in an increasingly competitive environment. In comparison, public sector organizations are also driven by necessity, which is instigated by the government as a key stakeholder, and operationalised through mandate in an effort to improve efficiency of operation and meet need. Organizations in both sectors are also striving to up-skill, and are seeking increasingly complex solutions in rapid timescales. Although both motivated towards collaboration by necessity therefore, it may be considered that the drivers operating in the private domain stimulate a higher level of risk-taking as organizations strive for higher profits. Necessity as a voluntary motivation is very apparent in the public sector. Starved of resources in the context of rising customer expectations and increasing social needs, public authorities are increasingly looking to lever-in additional resources through partnership ventures to achieve organizational objectives. Oliver (1990) defines asymmetry in terms of its potential to exercise power or control over another organization or its resources. In this context, private sector organizations operating within highly competitive or consolidating environments may be more likely under the right circumstances to adopt this approach, as they pursue profit motivation to retain access over specific resources, or to gain or defend market share. Additionally, many private sector organizations have the resources and/or financial capability to dominate a partner organization. In contrast, public sector organizations may be in a more vulnerable position. The primary objectives in this sector are not generally competitive and the motivation to dominate is much less of an issue. The reciprocity contingency can be interpreted as the need for up-skilling and development of more complex offerings – factors that are reflected in both the private and public sector literature. For both types of organization these aspects can be highly beneficial to the organizations involved. However, it can also represent a risk of de-skilling or loss of core competence/market to a stronger partner. Political and legal restrictions can provide some protection in this respect for some public sector areas. In contrast, private sector firms may be highly vulnerable to an aggressive partner and can suffer from a competitive acquisition. Reciprocity between the two sector partners may also prove problematic as the basis for this may lie in profit returns for the private sector organization, but driven by social values in the public sector. This differential could impact compatibility of goals or objectives of the partnership, or compromise the initial aims of one or other partner organization. Efficiency issues have some similarities for driving partnership between the sectors. Efficiency in private sector terms drives bottom-line returns through transaction cost reductions, economies of scale and rapid product/service development. In contrast public sector efficiencies, although also aimed at cost reduction and rationalization, may compromise its overall objectives if undertaken on a purely profit-driven perspective. Thus, there is a need to consider social value and

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contribution in addition to a more effective process/cost objective. However, in both sectors, anticipated efficiencies are not always guaranteed and can also take some considerable time to achieve. Additionally, in the initial stages inefficiencies can occur as the two parties operate with duplicate resources or processes, or invest time in clarifying and gaining key agreements. Stability in organizations is driven by a need to reduce environmental uncertainty, which, in itself “is generated by resource scarcity and by a lack of perfect knowledge about environmental fluctuations, availability of exchange partners, and available rates of exchange in an interorganizational field” (Oliver, 1990, p. 246). This occurs as organizations attempt to forestall or absorb uncertainty in resource flows and exchanges, and can be seen in the collaborative initiatives of both private and public sector organizations. Within private sector firms, stability helps to ensure the development of increasingly complex customer offerings, thus assisting in both new product development and related competitive advantage in the market place. Equally, public sector organizations will pursue stability through partnership with a private sector organization in order to reduce public service inefficiencies and ensure reliable access to additional resources. However, in doing so, public sector organizations may have to comply with a profit driven partner, and be faced with the dichotomy of pursuing profit over public interest. Finally, it may be argued that public sector organizations may have additional complexity to deal with, as they have to respond to political dictates in addition to economic uncertainties. The legitimacy contingency which Oliver (1990, p. 246) identifies may be viewed in terms of an organization’s needs to either improve or demonstrate its reputation, image, prestige or congruence with prevailing norms in its institutional environment (p. 246).

This form of response can be identified in different contexts in private/public sector operations. In the case of private sector firms, legitimacy may be sought in order to enhance a company’s image while pursuing a profit-driven motive, and may be a key factor in these types of firms seeking out a public sector partner. However, for public sector bodies, the social legitimacy factor is more central to the organization’s operation as it seeks to add social value as its main purpose. However, legitimacy in terms of having the skill and prestige to provide increasingly complex service offerings or funding to do so, are key drivers in this sector. Thus legitimacy may be applied to both sectors but must be interpreted differently according the different characteristics of the sectors. Overall, it is evident that multi-agency collaboration is subject to a highly complex number of drivers, which can influence either success, or ultimate failure of the relationship if the interface is not managed effectively. Although both driven towards collaboration, the benefits of allaying risk via up-skilling and improved

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Fig. 1. Competitive Positioning/risk Drivers.

access to resources for public sector firms must be seen in the context of a potential compromise, in terms of control and of the social objectives these organizations pursue. Further, the objectives they seek are often directed rather than calculated. Thus any competitive direction would appear more secondary and tactical than strategic in these cases. In contrast, the private partner will generally continue to pursue competitive objectives for collaboration, either for increased potential profit, access to resources or control over the marketplace, as a primary course of action. Lastly, they are more likely to seek out risk in collaboration in order to compete in this environment. This variance in key motivations is illustrated in Fig. 1 below.

THE THEORY APPLIED The following section moves the discussion to an illustration of critical contingencies theory through an analysis of two case studies. These are based on strategic interventions devised by national government, and delivered by local government in collaboration with a range of public, statutory, private, voluntary and independent agencies. Both are based in Wales, a country within the United Kingdom and are referred to as community strategies, and health, social care and well-being strategies. They are contemporary examples of complex forms of collaboration and are considered by the authors to be ideal vehicles to explore differences in collaborative motivation between multi-agency partners, and to examine the influence this has on the design, course and outcome of these relationships.

The Context In order to better understand the case studies, some contextual information is helpful. In the first case, a statutory requirement has been placed by central government

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on all local authorities throughout the U.K., including Wales, to prepare community strategies for their areas which promote the social, economic and environmental well being of their inhabitants, and contribute to sustainable development in the U.K. (National Assembly for Wales, 2001). The duty to do so is part of a battery of changes introduced under the U.K. government’s modernization program, which includes alterations to local political managements arrangements, and the introduction of a new performance management regime. Although the community strategies are intended to be a demonstration of local government’s community leadership role, the plans are envisaged to be an expression of a whole range of public, voluntary and private organizations’ proposed interventions in a particular geographical area. Most importantly, the strategies are seen as opportunities to meaningfully involve and empower service users and citizens in their design and implementation. Community strategies are expected to set out a vision and future for their areas over the forthcoming 10–15 years, but also to contain an action plan detailing how this is to be achieved. The strategies themselves are not directly related to resource or funding mechanisms, but by implication should inform a wide range of financial frameworks of the participating agencies, and bend priorities accordingly. Although the production of the strategies is a statutory requirement, and in sharp contrast to other initiatives, the advice on the form and process or realizing them is not prescriptive, considerable flexibility lies with local stakeholders to devise a strategy-making process that is tune with local circumstances. The second case – health social care and well-being strategies – has many similarities to the first, but also demonstrates material differences. It again stems from a statutory requirement placed by central government to produce and deliver health, social care and well-being strategies (Welsh Assembly Government, 2003). In this case the duty is jointly placed on all local authorities in Wales and on coterminous Local Health Boards. Local Health Boards are the planning and commissioning agents of the National Health Service in Wales, and distribute financial resources to social care and health providers to meet the various needs of the local population. This program is envisaged to be the result of effective partnerships between various stakeholders, and in contrast to the first, directly informs the distribution of financial resources. Interestingly, however, both cases exhibit a high degree of interdependence as the notion of well being is common to both, and health and social care are important elements of a community strategy. However, the extent to which they are integrated or managed as two separate collaborative processes is illuminating, and reflects the different motivations of the key actors and organizations within local inter-organizational domains. An overwhelming characteristic of both cases is their complexity. Each is struggling with multiple and sometimes conflicting objectives. They involve social, economic and environmental policy areas; they involve a wide range of both local

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and national actors and organizations; they relate to different time frames; and they aspire to cover each of the stages of the policy process from planning and formulation, through implementation and delivery, to monitoring and evaluation. On closer examination, perhaps unsurprisingly, the management of motivation plays a particularly central role in shaping the course and outcome of these inter-organizational ventures. Different contributing parties and organizations can be observed to have different motivations governing their aspirations, engagement, commitment and behavior in these fields of activity. To complicate matters further, motivation is sometimes multiple in form and not simply single in intention, and can also change over time as a function of the ongoing collaborative experience, and in the light of emerging circumstances. Many expressions of Oliver’s (1990) critical contingencies can be detected in these two case studies, and the individual types of motivation leave their indelible marks on the nature of the collaborative process.

Necessity: Mandated Co-operation Fundamentally, as Oliver (1990) and Mackintosh (1995) note, there is a material difference between mandated and voluntary interactions. Even if participants have a prior disposition to collaborative working, an atmosphere of coercion is different to one based on voluntary interactions. Both the examples cited above are framed within heavily prescribed statutory frameworks with central government attempting to set and control the rules of engagement. In both cases, this is manifested in a statutory duty of partnership – in the case of community strategies, on one lead organization, and in the case of the other, a joint duty of partnership on two leading organizations to formulate and implement a strategy. In addition, in the latter case there is also a “duty of co-operation” on the local authority and local health board to co-operate with other named members of a partnership including health service delivery agencies, private, business and voluntary interests. Understandably perhaps, neither the notion of “partnership” nor “co-operation” is defined, or whether, indeed, there is an actual difference between them! In the final analysis, the effect of statutory duties is to make certain organizations – in these case studies, local authorities and health boards – ultimately accountable for their performance within conventional democratic processes. Of course, the problem for these organizations is how to engage with other prospective partners upon whom the duty does not rest. The danger is that other organizations do not attribute the same importance to the delivery of these strategies, as do the two statutory bodies. Their motivations may well be rooted in other considerations. Indeed, it is apparent that community strategies have not altogether captured the imaginations of many prospective

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partners because of the protracted nature of the process, and the lack of connection between the strategies and any direct resource allocation mechanism or framework. Consequently, there is a reluctance to offer assistance to local authorities to fund the not inconsiderable costs of servicing strategic partnerships. This often takes the form of dedicated staff appointments, which help with general administration and support, but can have the effect of perpetuating the idea that it is the local authorities’ sole responsibility. Jointly funded and accountable appointments can help overcome this. Overall, the situation places a particular onus on local authorities to devise an inclusive collaborative process that can be seen to deliver benefits to other public and private agencies. It is reported that the private sector is universally boycotting local community strategy partnerships because of their perception that there is nothing in it for them, and many national agencies with local remits are reluctant to get involved because of their lack of capacity to service so many local partnerships, and their reluctance to allow local priorities to influence national frameworks. The preparation of health, social care and well-being strategies do not face quite the same problems as community strategies, fundamentally because of their link with resource allocation mechanisms. Hence, social care and health providers in both the public and private sectors have no option but to seek engagement. It is questionable, however, whether this is based on the spirit of partnership, or whether it is founded on self-interest with the objective of extracting the maximum benefit for their individual organization. The aim of the overall strategy is to ensure that services are planned and commissioned to meet the disparate needs of the population in a way that is efficient, effective, economic and fair. However, these are not neutral notions and considerable negotiation is called for to resolve inevitable tensions and conflicting priorities. The ways in which these are handled and managed within the strategy making process has an impact on partner satisfaction, and sets out an expectation and behavior that influence similar engagements in the future. A final point concerns the effect of the creation of an inner group of organizations on which a statutory duty lies, and a more peripheral group of organizations that, of necessity, have to engage in a partnership. The dangers relate to perceived equality of treatment, access to information, decision-making, and issues of trust. A two-tier partnership has to be handled with great sensitivity.

Asymmetry: Collaboration or Control? Although outwardly projecting a vision of mutually beneficial collaboration, many local authorities secretly cherish a desire to exert more direct influence and control

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over health services and policy, which are the responsibility of other organizations. However, health, social care and well-being strategies offer them a vehicle to pursue this agenda. Although a joint approach to the planning and delivery of health and social care offers the prospect of an efficient and effective use of resources, there are suspicions harbored by social care agencies and professionals that this would result in an unequal redistribution of resources in favor of health services due to the insatiable demands made for additional resources to secure improved health. The role of the voluntary sector has always been uneasy and somewhat ambivalent in relation to public sector agencies. Its claim to be a voice for countless numbers of voluntary groups in a local area is often challenged by those representatives of democratically elected institutions who question the fundamental legitimacy of such groups. Conversely, membership of strategic local partnerships alongside more powerful partners is a huge opportunity to promote the reputation and role of the voluntary sector. Although local authorities are exhorted to secure effective ways of engaging and empowering local citizens and voluntary organizations in the preparation of community strategies, many understand that the effect of this is a loss of power. There is inevitably a reluctance to proceed down this route, and a certain amount of tokenism is apparent with the decisions of strategic partnerships not necessarily being reflected and ratified in the decisions of the key sponsoring bodies. In the case of the health, social care and well-being program, there is some confusion as to whether the statutory prescription relates only to the formulation of the strategy or to the implementation as well. It is apparent that some partners would be more comfortable with the former view because it gives them more scope to interpret what is often highly ambiguous and very general strategic statements. Working in partnership on the implementation of policies and programs implies a far greater degree of collaboration and potential loss of control. The modernization of the public services agenda promoted by the U.K. government aims to reposition public authorities more within a mixed economy of planning and delivery of services. It seeks to create more permeable boundaries between the public and private spheres of society, and promotes a partnership approach to governance, but with public authorities taking a clear leadership role primarily by virtue of their democratic legitimacy. It is within the spirit of this role that local authorities, through mechanisms such as community programs, endeavour to influence and infuse partners with a common set of principles and values. Hence, discussions around social inclusion, equality of opportunity and sustainable development – often referred to as cross-cutting themes – increasingly form the foundations and building blocks of strategic partnerships. However, achieving any consensus on the meanings of these notions is difficult enough, without the additional problem of converting the rhetoric into

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practical applications that inculcate the policy process from inception through to implementation.

Reciprocity: Mutual Interest and Benefit Although both case studies are framed within mandated frameworks of cooperation, Oliver’s critical contingency of reciprocity is nevertheless alive in the motivations of organizations and people in the strategic partnerships. The public sector stakeholders are rooted in an ethos of public service values, and driven by a desire to meet the needs of citizens and communities. They recognize that many of these needs are multiple in form – for example health, social care and housing – and cannot be delivered by organizations acting autonomously. It requires joint and co-ordinated action with the starting point being the needs of the customer, not the administrative configuration, roles and responsibilities of public and private agencies. Hence, in both case studies, although difficult to frame, the sense of devising a strategic direction underpinned by a set of basic values to deliver improvements to the quality of life of individuals and communities, is a strong driving force. The hegemony of partnership working appears to be taking root, although the practicalities of making it work in practice is an entirely different matter, and there are many barriers to be overcome. For instance, at a micro level, individual actors involved in the collaborative process are often driven by professionalism and professional cultures. This involves deep-seated values, particularly those between the public and private sectors – about the respective merits of the private sector’s drive to profit maximization and enhancing shareholder value vs. public interest based on concepts of fairness and equality. The recipients of services are conceptualized in different ways – typically customers in the private sector and citizens in the public. However, these stereotypes have been increasingly interpreted in different ways in new models of public service planning and delivery, and concepts and notions of public and private sector value and motivation remain highly contested political and academic areas of debate. These issues surface particularly in the health and social care sectors, where elements of service delivery are provided by private sector agencies, e.g. care of the elderly and hospital services.

Efficiency: Efficient and Effective Use of Resources There can be no doubt that considerations of efficiency underpin many actors’ and organizations’ views on the need to work co-operatively. In the case of community

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strategies, there is a macro level imperative to use them as an opportunity to rationalize the strategic partnership initiatives that currently proliferate at a local level. The problem has been that the effect of the U.K. government’s drive to predicate all forms of policy intervention on partnership working, is a large number of different partnerships for different purposes, e.g. crime and disorder, youth offending, health alliances, drug and alcohol abuse and countless more. This congested local governance causes problems of lack of co-ordination, duplication and overlaps. In addition, servicing multiple partnerships causes capacity problems for partnering organizations and “partnership fatigue.” The preparation of community strategies offers the potential for the rationalization of current arrangements, and the deployment of a more effective use of resources. The quest for efficiency permeates the motivations of actors concerned with the planning and delivery of particular services. Using the example of health and social care (the responsibility of two separate agencies), problems of limited resources constantly bedevil practitioners and managers. Demand outstrips supply in most service areas, and additional pressures are placed on managers to demonstrate the efficient use of resources through ever-restrictive performance management frameworks imposed by central government. Therefore, opportunities for designing and delivering services in the most efficient manner are high on the partnership agenda. In particular, ways of securing the joint delivery of services through integrated forms of provision are seen as very important. This often requires innovative approaches to service planning and delivery that is made possible by the synergy of multiple perspectives and imaginations being applied to a particular problem. Central government has encouraged this process through a recent Health Act that allows local authorities and local health boards certain “flexibilities” to work together on common areas of interest and responsibility such as joint commissioning and integrated care provision.

Stability: Managing Turbulence and Change Oliver (1990) suggests that one reason for entering forms of collaboration is to alleviate or manage uncertainty and instability in the external environment. It is seen as a method of coping with the future, and what that might mean for particular organizations. Partnership working offers an opportunity of sharing information about the future and of mapping out future scenarios. It often results in the creation or reinforcement of networks of people who can be a source of support and of information about other organizations, new legislation and potential changes in the external environment. Certainly, formal arrangements for joint information sharing are a prerequisite of effective partnerships, and the necessary precursor of

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any integrated delivery framework. This is not always straightforward because of issues of client confidentially and for reasons to do with the basis on which data is collected in terms of compatibility, units of analysis, type of data and so on. The development of a strong culture of partnership working between a number of agencies has the potential of presenting a united front in the face of external threats. For instance, the relationship between national and local government is a source of tension, and strong inter-agency partnerships are used to influence the decision making of national government. However, in the final analysis, the reality is that stability and predictability are but forlorn hopes. The public policy context is characterized by turbulence and change. Increasing complexity is a feature that has to be addressed – problems and solutions are highly interconnected, and there is a high degree of interdependence between different policy areas. Changes in one part of the system have ripple effects in others – both intended and unintended. The agenda is fast moving; policy interventions are many and varied, and the most effective public and private organizations are those that have the flexibility to respond to emerging challenges, and not remain fixed within the constraints of a rapidly outdated strategic courses of action.

Legitimacy: Increasing Profile and Legitimacy Collaboration presents an opportunity for particular players to raise their individual profile and legitimacy. Among other motivations, this is certainly the case with local authorities and the health, social care and well-being partnerships as is discussed above. It offers this sector the chance of making a point to confirm its belief that health issues are also a legitimate concern of local government as well as the National Health Service. It does this in the confidence that local authority policy areas such as housing, education, transport and employment are critical determinants of the health of a population, and in the context of a move away from the limited medical model of health to the social model, its influence on the health status of an area is fundamental, and proportionately more that the direct health care services themselves. In terms of legitimacy, and again as was discussed above, the voluntary sector has much to gain from being around a decision making table with partners of hugely more power as measured in terms of resources – financial, land, staffing. The management of the collaborative process in the context of an unequal distribution of partner power is a significant challenge. Of course, an issue that often is faced by partnerships, and the two case studies are no exception, is the question of convenorship and who to invite to the table. Should the dominant partner assume the convenorship or leadership role or the one

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on whom the statutory duty lays, or in the spirit of impartiality and independence, should a more impartial or less biased representative be chosen? This sometimes smacks of tokenism but often raises the profile of junior partners, and enhances their legitimacy. On the question of who to involve, this is problematic at the margins of the partnership and relates to the different perceptions of the legitimacy of different organizations or people. Partnerships face problems of inclusively, and need to address issues of membership on a regular basis. In the case of the two case studies, the route taken has been to involve a different set of stakeholders at different stages of the policy process – strategic planners and managers at the front end, and service managers, practitioners and street level implementers at the other. As Mintzberg (1994) so cogently argues, the separation of the planning from the implementation stage of the strategic planning process is one huge fallacy that can result in considerable ineffectiveness.

DISCUSSION The preliminary findings of the case studies considered in this chapter resonate with Oliver’s (1990) proposition that “although each of the foregoing determinants may be a separate and sufficient cause of relationship forming, the decision to initiate relations with another organization is commonly based on multiple contingencies” (p. 246). The interaction between them is interesting question, which is not easily resolved given the range of individual and organizations operating in these multi-agency initiatives. In addition, motivation occurs at a micro level with individual actors, but is also expressed through individual organizations. As has been suggested, motivation can change over time, and facades of motivation can be detected where people’s real motivation is hidden behind another for purposes of convenience, and usually self interest. A useful extension of Oliver’s critical contingency theory involves an exploration of the manner in which different sources, or combinations of sources of motivation can shape the determining factors of the collaborative process, and ultimately affect the outcome. A few examples help to illustrate this proposition. First, in relation to the framing of problems and concerns, the importance of understanding the motivations of the multiple interests represented in community strategy and health, social care and well-being partnerships is critical particularly at the outset. “Wicked” issues are socially constructed in the sense that the conceptualization and analysis of problem structure, cause and resolution are a function of the “gaze” of individual stakeholders. Many problems have no universally understood meaning but only a “family” of meanings which “attaches

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to the particular social, communicative, experiential and perceptual world” (Harvey, 1993, p. 97) of the knowledge holder. In the dense policy spaces occupied by health, poverty or social disadvantage, the number and range of stakeholders is extensive including different professionals and practitioners, citizens and customers, politicians, local and central government officers, and people employed in the private and independent sectors. Schon (1987) refers to the act of framing because “depending on our disciplinary backgrounds, organizational roles, past histories, interests, and political/economic perspectives, we frame problematic situations in different ways” (p. 4). Stone (1989) argues that problem definition is influenced by competition over causal theories and “the active manipulation of images of conditions by competing political actors” (p. 299). The ascendancy of particular causal stories colors both the type of reform required, and empowers particular people who have the resources or skills to resolve them. Secondly, in relation to leadership, the initial stage of partnership formation and convenorship is a delicate and complex operation that requires a particular style of leadership to reflect a collaborative theatre comprising multiple stakeholders representing diverse interests and aspirations, and inspired by mixed motivations. Although the configuration of power relationships is unequal because of differential access to resources, legitimacy and status, leadership styles typical of hierarchical forms of organizing tend to be less effective in partnerships. Directive and controlling styles of leadership fail to appreciate that all partners need to be valued for their contribution, and any attempt to exert power unilaterally is likely to be counterproductive and unsustainable in the long run. Consensus seeking is more the order of the day, and catalytic and collaborative forms of leadership (Feyerherm, 1994; Kanter, 1997; Luke, 1998) based on facilitation, engagement and negotiation is more relevant to the challenges of securing collaborative outcomes. Ideally, the task of leadership needs to be shared among participating actors, and leaders themselves can perform a valuable role in managing meaning and sense making, by helping to deconstruct and communicating with others the different languages of individual actors, by helping to secure a safe environment in which to share value differences, and providing a mechanism to align aspirations and aims, and, lastly, by building an architecture and a process to deliver significant outcomes (Citation). Finally, in relation to goal congruence and consensus building, the effect of multiple motivations on achieving goal congruence and building consensus is significant. The difficulty is being able to broker aims and objectives of sufficient clarity and coherence to facilitate strategic action. An interrogation of typical strategies produced by community strategy and health, social care and well-being partnerships is likely to reveal that the goals developed are slippery and vague,

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and in effect can mean everything or nothing! The argument in favor of this approach is that it is only at this high level of abstraction that disparate partners are able to offer their public commitment. Tightly framed aims and objectives are difficult to negotiate, and they potentially reduce future flexibility and room for manoeuvre. Arguably, a more appropriate time for this detailed discussion is the delivery stage of the partnership, where projects and contracts are prepared, inter-agency agreements written, and financing arrangements settled. Here, individual organizations are able to judge the extent to which their particular aspirations are likely to be achieved, and negotiate accordingly. The importance of constructing consensus-building frameworks in collaborative arenas is premised on its potential to engage a wide stakeholder group in a process of dialogue and mutual action. Although tangible outcomes may be delivered by this approach, the process itself can be considered a legitimate outcome in its own right through the development of social capital in the system. Raised levels of trust, improved communication and networking, and shared learning might be expected to deliver, as yet unspecified, types of co-operation in the future. However, balancing the long-term potential of multi-agency partnerships against the imperatives (particularly political) of short-term interventions and successes is not easy, especially with the onset of partnership fatigue. This tests the robustness of partnerships, and the commitment of individual organizations to collaborative approaches. So, different motivations have a profound influence on the determinants of effective partnership working such as problem framing, leadership and goal congruence and consensus building. Further research is required in this area to further explore the nature of the interactions between type of motivation and key factors in the collaborative process.

CONCLUSION This chapter has looked at the different motivational drivers impacting multiagency partnerships within the United Kingdom. As these partnerships are often made up of combinations of both public and private sector players, it was considered important to evaluate influences impacting both sector players, and their implications on motivation. The investigation found that multi-agency partnerships are subject to a highly complex – and sometimes contradictory – number of drivers, each of which can influence the success or failure of the relationship if the interface between these is not managed effectively. The need for compromise in relation to control and value-added (however this is defined by each partner), and congruency in terms

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of agreed-upon objectives appears fundamental to the success of these forms of relationships. However, motivational drivers frequently push these in different directions for the individual players. Additionally, the level of importance of such aspects as access to resources, and transfer of risk (rather than risk taking) was weighted most strongly on the side of public sector rather than private sector partners. The case studies of two complex, multi-agency partnerships highlighted the impact the above factors can have in terms of design, course and outcomes of this form of relationship. Motivation, consensus, process and goal congruency were all critical issues that demanded clarity, cohesion and delicate handling between the many stakeholders involved. The achievement of these was made more difficult to rationalize, however, as differing objectives, values, languages and environments all acted to obscure the view of the players involved. All these are factors that require continued consideration when commencing and developing a successful multi-agency partnership. The need for improvement in the performance of these forms of partnerships as they continue to grow in the U.K. is evident. Where successful, their potential to drive the economy forward to provide for increasingly complex social needs efficiently and effectively is undisputed. The key question to-date has been how to address this issue in a structured way given the high level of complexity this type of relationship reflects. The aim of this chapter has been to provide an insight into the motivational drivers that need to be considered, and the potential areas which might offer some opportunity for improvement in this context.

NOTE 1. Wales is a country in the United Kingdom

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COMPLEX COLLABORATIONS: THE CASE OF A BUSINESS SCHOOL AND ITS COMPLEX NETWORK OF RELATIONSHIPS Peter Lorange INTRODUCTION How can studying the case of the modern business school potentially give us a better understanding of the phenomenon of complex collaborations? (Gregoire & Prigogine, 1989; Peak & Frame, 1994; Stacey, 1995). Why does a business school need to enter into complex collaborations? (Lorange, 2000, 2002c, 2003). As a starting position, we should recognize that the activities of the classic business school are generally rather mature. There is fierce competition among business schools, the supply is abundant, and there are only a few established, elite business schools that can be seen as being truly different from the large agglomeration of schools. As such, we can see the business school arena as relatively mature, even atomistic. Are there steps that a business school can take to distance itself from the rest, i.e. to create unique settings, which might mean that it operates in a less mature context? We shall see that complex networks are one such route. We do of course realize that this question is not relevant for a few elite business schools with exceptional brand names, such as Harvard, Wharton or Stanford. These schools

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are virtually a priori distanced from the rest. Beyond this, however, there are many opportunities for repositioning for those schools that are willing – and able – to make use of complex collaborations:
There seem to be opportunities for breaking new ground when it comes to business school teaching: away from classic teaching – to undergraduates, MBAs and PhDs – toward the executive education segment, say, with more action-oriented learning. And this will call for complex relations with firms.
Similarly one can observe a shift when it comes to research, although perhaps not as distinct. There is a move away from an almost exclusive emphasis on classic discipline-based axiomatic research toward more action-oriented research, focusing on how to better understand particular contextual realities. Again this requires a closer relationship with corporations – complex collaboration! In short, although the classic activities of business schools – primarily focusing on younger students – are becoming increasingly competitive, the corporate niche – focusing more, through network relations, on executives and corporations and their knowledge needs – seems to be growing. Many business schools have caught on to this trend. Indeed, some have even impressively built their reputation further by excelling in the executive segment. A key to their success has been their ability to work via complex collaborations. The shift toward relatively more focus on the executive learning segment can make sense for several reasons:
Competition might be less fierce, thus making it commercially relatively much more rewarding to operate in this segment. An underlying reason for this may be that there would be fewer schools active in this emerging value-creating segment. Schools such as INSEAD, IMD and several leading United States schools have indeed successfully developed new skill bases for this – and thus also enjoy competitive advantage relative to other schools, at least on a temporary basis. As we could have predicted, the commercial rewards also seem to be there, with these schools becoming financially strong without substantial cross subsidization from their universities and/or public funds. So, pursuing complex relations with business can pay off.
Learning-wise it can perhaps be argued that one can – in the longer run – get relatively much more out of working with experienced executives than with young undergraduates and perhaps immature MBA students. After all, the field of business administration is generally an experience-based field – hence, there is a lot of potential benefit to be gained from working with leading executives, who can bring “real life, real learning” into the equation of knowledge accumulation. Similarly, more action-oriented research can give faculty a sense of being able to

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contribute, of being part of the success of a given company, seeing the relevance of what they are researching more directly – as opposed to focusing on a rather narrow axiomatic research segment where only a handful of academic colleagues might perhaps understand the relevance of the research. One probable implication of all of this is that business schools, with their community of professors and professional staff, may have to – not only want to – become more closely involved in executive education, executive development and lifelong learning. And, as already noted, this implies working with business – typically in a complex way (Lorange, 2002a). It can also mean working with other academic institutions, again typically in complex collaborative ways. Why this need for complex collaboration?
With companies that are starting to demand executive education services, it will be important for the academic institution to understand, at least to some degree, the particular strategy of the corporation. The professors must have a feel for the unique strategic challenges. There might be different potential needs in the corporation’s various entities, calling for a situational view on what is needed in terms of lifelong learning for various stakeholders in each part of the company. This deep understanding cannot be gained without complex collaboration. Typically this would involve a large number of executives on one side, and a large number of professors and professional staff from the business school on the other side. As an example let us consider IMD’s executive education activities with Nestl´e – the world’s largest food company (Lorange, 2000a). Nestl´e operates in countries all over the world. Typically, many of these operations may face unique challenges, when it comes both to reaching the relevant consumers and to meeting the competition. Nestl´e’s business activities can be seen as falling into 10 strategic business units, ranging from coffee to water, from confectionery to pet food, all with different critical success factors. To provide truly relevant executive education in this context, IMD had to learn the essence of a broad variety of business situations, through a number of close cooperations with specific teams from Nestl´e. Without such complex collaboration, it is hard to see how cutting-edge executive development can realistically take place.
Similarly, the need for relevant competences offered by a particular business school may now become a limiting factor. These competences are easily broader than those necessary to meet the classic needs defined by the normal set of academic disciplines. Thus, a business school can perhaps no longer offer everything by itself, hence the requirement for strategic alliances with other entities – consultants, research institutes, other schools, i.e. complex collaborations again. Being able to mobilize the relevant knowledge set, either through internal efforts at the school or via collaboration with others, will also

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depend on a realistic perception of quality and relevance. Here what will be key will be the way individual executives perceive a given business school’s network with its partners in a complex alliance. Thus, when it comes to choosing which business school to work with, the complex collaboration must offer better intangible benefits than the classic, proven alternatives. Perhaps the most complete example of a complex collaborative setting aligned with a global geographical scope would be INSEAD. The school has a strategic alliance with the Wharton School, which might work particularly well to strengthen its delivery in the U.S. It also has a campus in Singapore, facilitating the strengthening of its presence in Southeast Asia. And to crown it all, the school has several smaller international alliances, for example with Fundac¸a˜ o Dom Cabral in Belo Horizonte, Brazil. The result is a complex network, well positioned to deliver superior, relevant value.

A SCHOOL’S DYNAMIC GROWTH MODEL We shall now draw specifically on a number of in-depth illustrations of how complex collaborations have led to dynamic growth and new academic value creation at one business school, namely IMD – International Institute for Management Development, based in Lausanne, Switzerland. A brief history of IMD is therefore appropriate. The school is the result of a merger that took place in 1990 between two smaller executive development institutions: IMEDE, founded in Lausanne in 1957 with support from Nestl´e, and IMI, founded in Geneva in 1947 with support from Alcan. The school is a self-owning, not-for-profit institution, with no university affiliation. The main focus has always been on cutting-edge research and teaching that targets the executive segment; there is also a relatively small MBA program. There are no undergraduate teaching activities, and no doctoral program either. At IMD the complex collaborations with a number of corporations – the Learning Network – involve 160 companies, mostly multinationals, from all over the world, including 10 corporations from Japan and a similar number from the U.S. IMD offers 10 Discovery Events to these companies per year. Here particular research findings are presented and discussed. The companies give valuable feedback – it is two-way learning, give-and-take. In this “real life, real learning” context, a “global meeting place,” the executives also learn a lot from each other. There are also a Business Advisory Council and a CEO Roundtable. These help IMD to reach a better understanding of how it might handle various emerging needs in the Learning Network companies, to do a better job in serving the companies and to allow for learning through exchanges between the companies themselves.

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A Weekly Webcast, lasting for approximately 20–30 minutes and followed by a 10-minute live Q&A period, is also offered. So far, more than 8,000 executives from all over the world log in, and most of the 160 companies actively participate in this webcast. The themes every week have to do with practical applications of ongoing research, presented by a professor in a managerial meaningful sense. There are also ad hoc special webcast series on issues such as successful women in leadership, the CEO’s issues and a book review series. All of this is “free” for the members of the Network organizations, covered by the annual fee. One can see these activities as an example of the way IMD is trying to strengthen its links with its key client companies. These tend to be those that use IMD the most. The complex network is thus a manifestation of a deeper elaboration of the relationship between established clients and IMD – on both open-enrollment and in-company programs. The Learning Network is indeed a way for IMD to present its existing knowledge through a more user-oriented framework. IMD protects and extends its base of existing clients through complex collaborations. How can a business school take its existing knowledge base and leverage or build on it to reach new students, new market category segments of learners? Fig. 1 illustrates this – a dynamic growth model for the school.

Fig. 1. A Dynamic Growth Model for the School.

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We see from Fig. 1 that a school might position itself through segmentation. The question is how a school can build on its proven strengths – protect and extend. Perhaps the easiest would be to make its existing knowledge available to new product segments, say in the executive education area, or to other groups of students, say at satellite campuses – a leverage strategy. Alternatively, the school could think about adding new competences to its offerings, say increasing the number of disciplines on offer, introducing more pedagogically advanced capabilities, action learning, technology-based distance learning – a build strategy. The model also shows the possibility of a transform strategy, which would consist of pursuing both new market segments and new knowledge. However, our research in other areas (Chakravarthy & Lorange, 2002) indicates that this will typically not be successful. Rather a school would be better to go via leverage before adding build capabilities, such as, for instance, entering new student segments through leveraging and then adding a distance learning capability via building, thus arriving at a transform strategy in two steps. Alternatively, a school could build a new capability, say for more action-oriented, diagnostic learning for particular companies, and then take this into a new segment. Again, it would indirectly arrive at a transform strategy via first build, then leverage. Underlying all of this is the assumption that a school will want to build on the strengths it has, actively working with them in order to avoid commoditization and to create dynamic growth. As we have seen, this would typically call for complex relationships, in order to actively be able to pursue various types of leverage strategies, as well as various types of build strategies. We shall now discuss this again in the context of IMD’s experience (Lorange, 2002b).

IMD’S COMPLEX NETWORK OF RELATIONSHIPS FOR GROWTH Figure 2 portrays how this growth model might look in terms of a number of complex collaborations at IMD. We have already discussed IMD’s Learning Network of more than 160 companies as an example of protect and extend, so we shall not elaborate further on this.

Leverage IMD has developed a close relationship with a number of companies when it comes to delivering tailored programs. This has frequently evolved further into a relationship with the corporate universities of these companies. Here IMD delivers specific

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Fig. 2. IMD’s Complex Network of Growth Initiatives.

program modules as part of the offering of a given corporate university. It can also support the corporate university with virtual learning inputs, say by facilitating the use of the materials that have already been generated via the Weekly Webcasts. The benefits for the corporate university are that IMD provides “fresh” inputs to avoid deterioration and stagnation. Also, IMD perhaps has a better understanding of the pedagogical learning dimension than the typical firm and is thus able to contribute particularly effective program designs. Otherwise there is a danger that a corporate university activity can end up becoming too much of a set of fragmented “dog-and-pony-show” sessions. Based on the experience of IMD’s interaction with corporate universities, the school has decided to attempt to develop even more in-depth key client relationships with 10 of its major customers. This will involve a more intensive effort on IMD’s part to be on top of these customers’ key issues:





Key challenges in the business today. Challenges in developing the firm’s people. Challenges in learning across organizational entities within the firm. Challenges in managing knowledge in the firm and its subunits.

On IMD’s side, a key account team is established with a particular faculty member co-leading the relationship with a member of IMD’s marketing field force. Other faculty members and staff are involved on an ad hoc basis. The key account team typically has global responsibility.

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IMD also encourages the formation of a corresponding team in the company itself. A multitude of relationships will thus be established – not having only one relationship, say with the head of human resources or executive learning, but also working with senior line executives. Key account plans focus on interactive and iterative discussions with each specific key client on subjects including:
The role of various faculty members and field force marketing representatives.
How to capitalize on low-hanging fruits to obtain more immediate results from the complex collaboration.
How to start working on – and developing – milestones for more involved, far-out learning initiatives, typically requiring more development work for both IMD and the company. This is a leverage strategy in the sense that the various capabilities and competences that exist within IMD’s community are being coordinated – “leveraged” – vis-`a-vis particular companies. Often a business school can be seen as analogous to a group of solo musicians, taking it in turn to perform their piece. This leverage strategy, however, is meant to draw on the entire body of knowledge of the school together, i.e. to create a performance analogous to that of a symphony orchestra. A fundamental question underlying this drive for leveraging would be how IMD’s professors and leadership identified possibilities and then created and maintained the possible partnerships. The key here is an open, iterative dialogue between specific corporations and the school. Typically this might start out as a rather simple working relationship. Over time, and helped by a sense of the benefits of the relationship activities, more and more actors might become involved on both sides, driving a broader and broader agenda for value creation. Always at the heart of this would be a strong commitment to serve the firm’s needs, and not impose IMD’s own solutions on the firm. Thus, a demand-side focus – not a supply-side focus – leads to the finding of relevant opportunities.

Build Let us now look at the other alternative for growth, namely developing new knowledge, which can then be added to the present knowledge base and thus become a build strategy. At IMD, new knowledge is constantly being developed, through the research undertaken by a faculty of 56 full-time professors, supported by 25 research associates. And there is continuous generation of knowledge via the accumulation

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of insights that come out of the various program initiatives with given companies. Although some of this knowledge is proprietary to the specific companies, most of it can be utilized as generic insights in other contexts. A considerable amount of pedagogically oriented knowledge is also accumulated. All of this can perhaps be seen as routine knowledge development, as part of the protect and extend strategic archetype. But what about adding more fundamentally new knowledge? Complex collaborations with other academic institutions are a realistic way to achieve this. First, IMD entered a strategic alliance with the Technical University of Switzerland, which has two campuses, one in Zurich (ETH) and one in Lausanne (EPFL). It has an outstanding reputation and is often referred to as “the MIT of Europe.” The strategic alliance was focused on developing a teaching and research program for executives from technology-based firms, i.e. the managerial side of technology development. Now in its seventh year, the alliance has been largely successful. Several professors are involved, the programs are offered jointly by all three faculty groups, and the physical location of the program modules rotates from campus to campus. The marketing of the program is done jointly by the three participating academic entities. This can indeed be seen as another example of complex collaboration. Then IMD went looking for another strategic alliance, to tap into the knowledge base of a leading U.S.-based business school. This led to an exclusive strategic alliance with the MIT Sloan School of Management aimed at developing a one-week teaching program with affiliated research:
Driving Strategic Innovation. Faculty members from both institutions are deeply involved in developing and delivering the program. The program is offered every six months, alternating between MIT Sloan and IMD. For IMD, on the one hand, there was a clear strategy of gaining access to relevant know-how that it would be too small to realistically develop on its own:
General management know-how.
Information technology know-how, drawing on MIT Sloan’s extensive base here.
Innovation know-how, again drawing on the U.S. school’s position as part of perhaps the most preeminent technical university in the world.
Financial management know-how. MIT Sloan, on the other hand, was interested in IMD’s know-how in executivedevelopment program design, marketing, promotion, etc.

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So far, the alliance is faring well, a complex and dynamic network created and managed by faculty from both schools. Transform One of the major barriers to growth for IMD is its relative lack of credibility in the major executive development market in the world – the U.S. Partly this can be attributed to IMD’s small size, which means it is unable to afford to develop a strong base among U.S. consumers in the broadest sense. Partly this can also be attributed to the fact that many of the world’s leading business schools are located in the U.S., which perhaps induces a sense of skepticism about the need to work with international business schools such as IMD. Interestingly, the relationship between MIT Sloan and IMD led to a further focus on U.S. corporations, in terms of how they could benefit from the jointly developed program. This was coupled with a focus on the 10 key client companies with which IMD is forging a particularly strong relationship, and the result was specific efforts vis-`a-vis a handful of these companies in the U.S. Two of these companies are headquartered in the U.S., and another four have a very strong presence there. This led to the development of learning strategies for the U.S. parts of these companies, building both on the leverage positions already established (key client relationships) and on the build relationship through the MIT Sloan alliance – a true transform strategy. The undisputed reputation of the MIT Sloan School of Management, coupled with IMD’s strong capabilities when it comes to tailored executive development, seems to work.

MAJOR CHALLENGES TO MAKING COMPLEX COLLABORATIONS WORK Experience so far has indicated that there are several major challenges to making these complex networks function as intended. Let us review several broad areas: one deals with the existing organizational context; another deals with the links to rewards, which need to be established realistically, and still others deal with some specific barriers that are often present. Organizational Context One issue is whether there is a single link or multiple links between the various entities in the network. We see a clear trend toward the need for multiple links.

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For instance, when it comes to links between specific corporations and IMD, the relationship tends to work better when there are several links, specifically when several line executives are involved. The least productive situation tends to be where there is one link, with the corporate staff human resource function only. Similarly, in IMD’s relationship with other academic institutions, there are a number of links from both sides. Although initially this was not well understood, this was a guiding principle for the development of the relationship with MIT Sloan. This is indeed analogous to the discussion of structural holes in social networks (Burt, 1997). The question of organizational stability is closely related. There will inevitably be changes in the relationships on both sides. A given executive will be reassigned to another job internally, and/or he/she might leave the organization. This can create dysfunctional effects. Similarly, within the academic institution a particular faculty member may move on to other tasks, again, potentially leading to instability. To safeguard stability in the complex collaboration, relationships must be backed up – from both sides of the relationship (Dooley & Van de Ven, 1999).

Complementary Capabilities It is important that the various entities in the complex collaboration have complementary capabilities. When it comes to the relationships between IMD and various key clients, for instance, IMD can design and deliver executive programs. The client company has the capability to select and assign the appropriate set of executives to the program. When it comes to a corporate university, it is also important for the capabilities on both sides to complement each other, so that there is no unnecessary duplication of effort, or perhaps even rivalry, between organizational subunits on both sides. When it comes to relationships with other academic institutions, it is important for both entities to have the ability to generate commercial results, i.e. effective marketing in order to attract executives to the programs. Similarly, it is important for both sides to have the capabilities to design and deliver executive programs from a content and pedagogical point of view. Still, the two must address different customer segments, bring complementary capabilities to the program design, etc. There must be mutual respect on both sides, not a “we are the best” attitude.

Shared Vision and Strategy Here it is important that the strategy, vision, and agenda to be followed are broadly shared. We have experienced that some entities can become out of sync with

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the shared vision, and can therefore act dysfunctionally relative to the common vision and strategy. Clarity in the common vision must be developed at several levels. For instance, it could be that the relationship is clear at the top, whereas particular entities further down the hierarchy may have a different agenda, say a division wanting to work with another business school. A top-down/bottom-up pattern of interaction must be delineated when it comes to developing a common vision for the complex collaboration (Collins & Porras, 1996; Neubauer & Parikh, 1993).

Core Values A key issue here has to do with learning as a core value that drives all entities in the complex collaboration. Many companies engage in executive development activities, for instance. At times this can perhaps be more or less a “detached investment,” rather than based on a true commitment to lifelong learning. It goes without saying that the broader vision must be articulated from the top. The energy has to come from here to counteract any tendencies to abandon a complex relationship, just because it is simpler to do so, and the transaction costs are high. Top-down energy is needed to keep the more ambitious visions alive! This can create relational stress, in that some entities evolve, while others are left behind in the complex alliance.

Change Similarly, what is the view of change? Is it a normal part of the evolution of the complex alliance, or do the various parties to the complex alliance see it as something different? Clearly “good must always be done better,” and hence change is a central part of any complex collaboration. But the shared core values remain. If there is no core value then it might be difficult to see how a complex collaboration can sustain the changes. In the case of ETH/EPFL, the core values of these organizations seem to be considerably different to those of IMD. Similarly, at MIT Sloan, the more axiomatic and traditional academic values there lead to potential dysfunctionalities compared with the more general core values at IMD. When the core values differ, then even more energy must be mobilized – typically from the top of the organizations – to keep the complex collaboration going. The extra energy required seems to argue for increased care and skill in complex collaboration (Flood & Jackson, 1995).

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Links to Rewards Complex collaborations cannot work unless the various key stakeholders see the benefits of the collaboration for themselves. Thus, a particular professor will only be involved in a key client relationship with a company provided that he/she obtains significant benefits from it, say, in the form of added learning, more work, additional research funds, even private consulting. It is important that this does not create dysfunctionality regarding stakeholder rewards. For instance, if collaboration takes the professor’s energy away from his/her key tasks, then it may be that the professor should decline. Realism here is key. Interestingly, in the relationship between MIT Sloan and IMD, joint research efforts have already been established between professors on both sides, leading to, for example, collaborative works, with inputs from professors at both schools.

Barriers “Not invented here” can be a real issue in complex collaborations. For instance, organizational pride and organizational profile can easily lead to problems if the parties feel that “we know best.” It is therefore important for each party to lay out its strengths and weaknesses, and to enter the collaboration based on this recognition. It is assumed that all institutions involved are of world-class caliber, but with different – complementary – strengths. Thus a “not invented here,” “we know better” attitude would be dysfunctional. It is important to dispel any sense of immaturity or insecurity in this respect. Complex networks can only thrive when there is a clear recognized complementarity, and a willingness of all parties to take advantage of it (Holland, 1995).

Meeting Place This is an issue of getting together to thrash out ideas, perhaps without even having a clear agenda, but to share with others from all sides when it comes to stating “challenges” that need to be handled, and perhaps coming up with “potential solutions.” This kind of brainstorming, creating deliberate meeting places without very tight agendas, and being willing to spend time on a predetermined, regular basis – say once every two months – seems to be very important for a complex alliance to succeed. What emerges from this sequence of interactions might be new

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shared insights on how to tackle particular value-creating challenges in the learning process. And additional insights create new challenges – “good must always be done better.” This openness from both sides is thus key – to add relevant energy to the complex relationship on an ongoing basis.

Critical Brain Talents It has been argued (Black & Gregersen, 1997) that it is now the key brains or talents in a company who will shape the organization they work in – based on their own professional goals, ambitions, career aspirations, etc. Thus the old dictum “strategy and structure” (Chandler, 1962) may no longer hold true. It follows for complex collaborations, too, that they will only prosper if the key executives involved want such arrangements to succeed. They must find that complex collaboration offers exceptional career opportunities, new ways for them to grow personally, more excitement and speed. Career benefits from being involved in complex collaboration can thus result from new thought leadership, which can make it attractive for faculty. However, faculty can of course be quite self-centered. Thus, they must put value on a broadened self-imposed professional mission of expanding into “uncharted territory,” such as further influencing the field of international business. As we know, the very high transaction cost dimension typically associated with complex collaborations might therefore represent a counter-force against their very existence. The key talents may prefer simpler structures. It goes without saying that it will be particularly important for senior decision makers to make the complex collaboration simple – “simple complex collaborations” – should not be a contradiction in terms. This implies that maintaining a complex collaboration requires the investment of time, energy and ideas, in simple but key ways, to keep it going. This is parallel to the discussion in the literature of complex adaptive systems, which says that complexity is built up from repetition of simple patterns (Holland, 1995; Mitleton-Kelly, 1997).

The CEO in Complex Structures With simplicity in mind, it is interesting, therefore, that some CEOs have decided to head the human resource management function themselves. In this way, they might be able to keep transaction costs under control and make the complex structures work. A CEO who is head of human resources has a legitimate reason to move around in the organization, to assess the situation, i.e. to manage the complex structure by “getting his/her feet wet.” He/she can use the HRM dimension as

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a way to legitimize keeping a finger on the pulse of the company, making the right organizational choices, etc., i.e. keeping the complex collaboration moving. He/she can thereby be sure that his/her overall vision is being met.

CONCLUSIONS We have discussed the phenomenon of complex collaborations and complex networks in the context of the modern business school. We have argued that for the modern business school to grow, and to distance itself from commoditization, it will increasingly be necessary to have such complex collaborations. Partly, these will be with leading corporations, and will involve leveraging the business school’s capabilities by coordinating them in a key client relationship mode, involving people from both sides – executives and professors – most often in a rather complex network pattern. Partly also, complex collaborations can be established between several academic institutions to generate the necessary know-how required today, which one institution might find it hard to create on its own. Again, complex network relationships will typically be a solution, involving several professors on each side. The conceptual model behind all this consists of building on one’s organizational strengths, a so-called protect and extend strategic position, and then entering into complex collaborations/complex network initiatives by expanding into new markets based on one’s proven strengths, i.e. a leverage strategy, and/or by building new competences that can be added to one’s established strengths, i.e. a build strategy. A transform strategy, with both new competences and new market positioning simultaneously, is not recommended as a strategic alternative for complex collaboration in its own right. Rather, such strategic positions should be achieved via a two-stage mode of complex collaborations – i.e. from protect and extend via build to transform, or the other way round, i.e. from protect and extend via leverage to transform. Needless to say, complex collaborations will have to be managed particularly carefully in order to achieve such a two-pronged focus. Complex collaborations do indeed have to do with the organizational context itself, with strengthening various value links, and with dismantling specific barriers.

REFERENCES Black, J. S., & Gregersen, H. B. (1997). Participative decision making: An integration of multiple dimensions. Human Relations, 50(7), 859–879. Burt, R. S. (1997). Contingent value of social capital. Administrative Science Quarterly, 42(2), 339–366.

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Chakravarthy, B., & Lorange, P. (2002). The growth imperative for Asian firms. Nanyang Business Review, 1(1), 69–76. Chandler, A. D., Jr. (1962). Strategy and structure. Cambridge: MIT Press. Collins, J. C., & Porras, J. I. (1996). Building your company’s vision. Harvard Business Review, 65–77. Dooley, K. J., & Van de Ven, A. H. (1999). Explaining complex organizational dynamics. Organization Science, 10(3). Flood, R., & Jackson, M. (1995). Creative problem solving: Total systems intervention. New York: Wiley. Gregoire, N., & Prigogine, I. (1989). Exploring complexity. New York: WH Freeman. Holland, J. (1995). Hidden order: How adaptation builds complexity. Reading, MA: Addision-Wesley. Lorange, P. (2000). Developing an internally driven growth strategy in network organizations: The Nestl´e friskies example. In: B. von Ostinger (Ed.), Unternehmen im Dialog (ed., pp. 38–47). Munich: Walter Biering. Lorange, P. (2002a). Setting strategic direction in academic institutions: The case of the business school. Higher Education Policy, 13(4), 399–413. Lorange, P. (2002b). Developing an internally driven growth strategy in network organizations: An organizational learning approach. In: V. Havila, M. Forsgren & H. Haakanson (Eds), Critical Perspectives on Internationalization. London: Pergamon. Lorange, P. (2002c). New vision for management education: Leadership, challenges. Amsterdam: Elsevier. Lorange, P. (2003). Global responsibility – business education and business schools – roles in promoting a global perspective. The International Journal of Business in Society, 3(3), 126–135. Mitleton-Kelly, E. (1997). Organisations as co-evolving complex adaptive systems. British Academy of Management Conference. Neubauer, F., & Parikh, J. (1993). Corporate visioning. International Review of Strategic Management, 4, 105–116. Chichester: Wiley. Peak, D., & Frame, M. (1994). Chaos under control: The art and science of complexity. New York: WH Freeman. Stacey, R. (1995). The science of complexity: An alternative perspective for strategic change processes. Strategic Management Journal, 16(6), 477–495.

INTEGRATING PERSPECTIVES: A MULTIDIMENSIONAL CONSTRUCT OF COLLABORATIVE CAPABILITY Melanie Schreiner and Daniel Corsten ABSTRACT With the advent of the resource-based and dynamic capabilities views of the firm, researchers of collaborative relationships have raised the question as to whether superior management of such relationships does indeed explain observed differences in collaborative performance of individual firms. While most research to-date has concentrated on antecedents and development of such management capabilities, in this chapter we propose a comprehensive construct aimed at capturing what constitutes collaborative capability. Results of an exploratory field study of vertical relationships in the software service sector suggest that collaborative capability consists of structural, cognitive, and affective dimensions. Based on our findings, we believe that the three dimensions of collaborative capability act as complements rather than substitutes, and that superior collaborative performance depends on a proper balance of the three dimensions.

Complex Collaboration: Building the Capabilities for Working Across Boundaries Advances in Interdisciplinary Studies of Work Teams, Volume 10, 125–159 Copyright © 2004 by Elsevier Ltd. All rights of reproduction in any form reserved ISSN: 1572-0977/doi:10.1016/S1572-0977(04)10006-X

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INTRODUCTION Recently, researchers have investigated the phenomenon of collaborative interfirm relationships drawing upon the theoretical contributions of the resource-based view of the firm (RBV) and the dynamic capabilities approach. They have found empirical evidence that a firm’s capabilities in managing collaborative relationships with external partners influences relationship performance: they may contribute to overall relationship success (Kale & Singh, 1999; Lambe et al., 2002) and firm profitability (Simonin, 1997), facilitate knowledge and competence development (Lorenzoni & Lipparini, 1999; Simonin, 1997), foster technical and commercial innovation success (Ritter & Gem¨unden, 1999), and have an impact on the company’s value creation (Anand & Khanna, 2000; Kale et al., 2002). Collaborative relationships can be defined as cooperative agreements between legally separable organizations that do not involve establishing separate organizations (Masten, 1988; Williamson, 1991). While positive effects of capabilities in managing such relationships find increasing support, their identification and operationalization are still in their infancy. To date, while drawing upon organizational learning and evolutionary theories, many researchers have concentrated on the cognitive and structural aspects of capabilities in managing relationships. Some have investigated how experience with managing relations with external partners translates via organizational learning mechanisms into future collaboration success (e.g. Kale & Singh, 1999; Simonin, 1997). Other researchers have focused on structural aspects such as an organizational function for collaboration management or the building of idiosyncratic resources for alliance creation (Kale et al., 2002; Lambe et al., 2002; Ritter & Gem¨unden, 1999). Surprisingly, although studies on the relationship level consistently point to the importance of affect-based factors such as trust or relational quality, scholars have almost completely neglected the relevance of the social and affective dimensions in collaborative relationships. However, increasing scholarly attention is being paid to the impact of affective and emotional elements of performance in business settings (e.g. Lawler & Thye, 1999; Luthans, 2002). However, overall it remains unclear as to what constitutes a management capability for collaborative relationships, in other words, which organizational processes, routines, actions and behaviors translate intended relationship goals into practice. In this chapter, we present the results of an empirical field study of capabilities for managing vertical relationships in the software service sector conducted according to grounded theory principles. Based on our findings, we have developed a multidimensional construct of firm collaborative capability which integrates structural, cognitive, and affective dimensions. In the subsequent sections, we first outline the conceptual foundations of the dynamic capabilities approach and

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prior research findings. After a detailed description of the research setting and methodology, we then report and discuss our findings pertaining to structural, cognitive, and affective capabilities, followed by concluding remarks.

CAPABILITIES FOR COLLABORATION A tremendous body of research on collaborative relationships has accumulated in various disciplines in recent decades, especially in the strategic management and marketing domains. However, research that focuses on management capabilities for collaboration from a single firm perspective has emerged only relatively recently with the advent of the resource-based view (RBV) and the dynamic capabilities view of the firm. These approaches promote firm-specific resources and capabilities as a source of inimitable and thus sustainable competitive advantage (Barney, 1991; Dierickx & Cool, 1989; Peteraf, 1993; Wernerfeld, 1984). As opposed to the view of the firm as being subject to deterministic environmental forces (Porter, 1980), resource-based theory suggests that firms’ unique assets and internal resources determine firm performance. The dynamic capabilities view extends this perspective. This approach posits that private wealth creation in periods of rapid technological change depends on honing technological, organizational, and managerial processes inside the firm. These internal processes serve to identify new opportunities and to organize effectively and efficiently to embrace them (Eisenhardt & Martin, 2000; Teece et al., 1997). Yet, the question remains as to the nature of capabilities. For the purpose of our research we are essentially relying on Dosi, Nelson and Winter (2000, p. 2) who state: To be capable of something is to have a generally reliable capacity to bring that thing about as a result of intended action. Capabilities fill the gap between intention and outcome, and they fill it in such a way that the outcome bears a definite resemblance to what was intended.

In other words, we embrace the now emerging consensus about: (1) the functional nature of capabilities; (2) the impact of managerial action upon their development and maintenance assuming that they are not completely tacit and intangible; and (3) their value in altering the resource endowment of the firm and handling change by transformation and a combining of old capabilities into new capabilities to achieve competitive advantage (Amit & Schoemaker, 1993; Eisenhardt & Martin, 2000; Teece et al., 1997). Although prior research on capabilities for the management of collaborative relationships is relatively limited to-date, existing literature shows a considerable variety of labels, definitions, conceptualizations and operationalizations (see Appendix A). In the field of strategic management, several researchers have

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emphasized the relevance of organizational capabilities for managing relationships with external partners without specifying accounts of the phenomenon (Dyer & Singh, 1998; Khanna, 1998). Most research concentrates primarily on the influence of experience and organizational learning mechanisms to develop capabilities for managing collaborative relationships (Anand & Khanna, 2000; Gulati, 1999; Kale et al., 2002; Kale & Singh, 1999; Lorenzoni & Lipparini, 1999). Just a few studies are concerned with the facets of a capability construct for the management of collaborative relationships (Lambe et al., 2002; Ritter & Gem¨unden, 1999; Simonin, 1997). However, they almost exclusively consider management tasks of the life cycle of a collaborative relationship, that is, identifying partners, negotiating, managing, restructuring, and eventually terminating the relationship. While marketing research has generated an enormous amount of knowledge on buyersupplier and various other forms of channel and market relations (e.g. Anderson & Narus, 1990; Dwyer et al., 1987; Heide, 1994; Heide & John, 1990; Hibbard et al., 2001; Hunt et al., 1985; Sivadas & Dwyer, 2000), Day’s (1994) seminal article on the capabilities of market-driven companies remained the only one to add to the relationship capability discussion. He accentuates customer-linking, respectively channel bonding capabilities. Almost all researchers in this area have modeled management capabilities for collaborative relationships as a predictor of relationship success. Yet, despite some initial forays, they remain surprisingly silent on the different dimensions of the capability construct and its operationalization. In other words, their research is unclear as to the specific organizational activities that translate the capability into practice in a specific realm, thus fostering relationship success. Detailed studies investigating which capabilities need to be developed, hence, what exactly constitutes an “alliance capability,” are still missing (Gulati, 1998). In our discovery-oriented approach, we attempt to fill part of that gap by an in-depth investigation of capabilities used to collaborate in a specific industry setting. Following a description of our research design and methods, we report and discuss our findings in conjunction with findings from prior research in management, marketing and other relevant disciplines.

METHODS AND DATA Research Design Our main objective in this study was theory development, especially broadening and deepening our understanding of collaborative capabilities in a specific context. The research design was guided by the following criteria: (1) a belief that existing empirical research on collaborative capability only scratched the surface

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of the phenomenon; (2) a desire to identify different capability dimensions, their interrelations and effects on each other; (3) a need for more fine-grained data in order to understand complex interactions, diffuse processes, and often tacit perceptions, beliefs, norms, and values guiding the behavior of actors. For all their inherent benefits, traditional deductive-analytic methodologies often disregard the multidimensionality and complexity of causal patterns of real world phenomena. The researcher is frequently forced to use crude surrogates for difficult-to-measure determinants or outcomes and narrow down the research scope. Thus, a qualitative approach based on the principles of grounded theory was inevitable (Miles & Huberman, 1994; Rouse & Daellenbach, 1999; Strauss & Corbin, 1998). However, notwithstanding the obvious strengths of inductive methods, we did not entirely follow the classical approach, which demands “high impartiality and to refrain from preconceived theoretical conceptions and ideas” (Glaser & Strauss, 1967, p. 37). Taking into account the rich existing literature in the field, building on potentially important constructs identified in prior research appeared to be the only logical approach for guiding the initial research phase of our project (Eisenhardt, 1989; Strauss & Corbin, 1998). From a conceptual point of view, the present research sought to examine capabilities for the management boundary-spanning collaborative activities from the perspective of the single firm. Our main questions concerned: (1) the capabilities needed to achieve collaboration success; and (2) the ways in which firms implement these capabilities. Because of the necessity for collaboration across organizations (i.e. boundary-spanning activities), we thus chose as our unit of analysis those distinct practices, behaviors, and actions (collectively referred to as “instances”) occurring within and between firms rather than residing solely within the individual firm. The instances investigated related to important constructs identified in prior research in the domain and were assumed to be representative of capabilities. This approach enabled us to overcome the fallacy of picking successful companies and then ascribing success to whatever practices, behaviors, and actions we would happen to find in those firms. This follows the proposed logic of Eisenhardt and Martin (2000) who suggest defining capabilities from their functional relation to their ultimate aim. To achieve consistency and comparability of instances, we chose a single industry setting in which the phenomenon was investigated, in order to preclude differing industry contexts from influencing capability development and occurrence.

Case Selection We selected the software service industry as our setting because: (1) it exemplifies the management challenges presented by inter-organizational collaboration; (2) it enables comparison between instances while; (3) exhibiting a wide variety of

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collaborations. Horizontal fragmentation and vertical disintegration of the value chain is common, thus, the need for collaboration to develop and market complex solutions is high, and actual collaboration is pervasive. In addition, collaborations built around the development, integration, implementation, operations, maintenance, and support of software solutions usually involve a high degree of interdependence between the partners. They include many different players who deliver diverse products and services, a wide variety of relationship types as well as relationship categories (e.g. global/national partners, exclusive/non-exclusive relationships). While the relationships show some features of channel relations (i.e. marketing and distribution objectives), typically, a complex contract product comprising hardware, software, and services is marketed. Marketing takes place before production, whereby both activities involve considerable inputs and development activities from several companies. Inter-firm relations are mainly designed as contractual arrangements serving as a platform from which specific projects are developed and sold. Contradictory to the high cooperation need, however, the selected industry is characterized by co-opetition. Firms that cooperate in one business area or project compete in or for another (Dowling & Lechner, 1998). Firms often cannot afford to renounce links with the major software manufacturers because otherwise they will not achieve competitive parity – let alone competitive advantage. Accordingly, cooperation often needs to be attained against structurally inherent countervailing competitive tendencies. Concerning the power structure, at first glance it would appear that the large providers of software products are dominating their partner companies. Taking a more micro perspective reveals that with regard to specific product and service segments partners may well be comparatively powerful in the context of the local market. Therefore, it is unreasonable to automatically assume that the larger partner is generally the more powerful.

Data Collection and Analysis We collected data on instances using semi-structured interviews with key informants, and to a lesser extent utilized document analysis and participant observation. Sampling of informants started with a selection of companies listed in the publicly available partner directories of the large software manufacturing companies. The firms were initially selected according to company size and partner type (i.e. solution, implementation partner, etc.). Within the companies, managers responsible either for a specific partnership or for partnerships in general were solicited as key informants. Larger companies tended to have single responsibilities for major partnerships; in smaller companies the informant was

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most often the CEO responsible for a number of partnerships. While data collection proceeded and major categories evolved, we increasingly relied on a snowball system to identify other information-rich and knowledgeable informants and also included informants from other functional areas of the companies to our sample (i.e. sales people, engineers) in order to saturate the evolving categories (Patton, 1990; Strauss & Corbin, 1998). The key informants represented companies ranging from 30 up to 30,000 employees on a global scale. Yet, the size of the local subsidiaries was 150–200 employees, on average. Informants had between five to several decades of industry experience. Experience with partnering ranged from two to twelve years. The interviews lasted one to two hours and addressed a set of important topics for collaboration management which we identified from prior research, that is, competences, resources, information and communication, trust, commitment, conflict, and equity. Informants were asked to report their companies’ approaches in managing these issues. We put considerable importance on eliciting “little narratives” pertaining to the topics in order to obtain action-oriented descriptions of instances and to understand the subjective meaning given to these instances by informants. As most of the informants’ companies had relationships with one another, we were able to cross check single key informants’ reports for specific or particularly interesting instances with the direct counterpart. Some informants were interviewed twice at intervals of nine months. The interview data was complemented with documents from company and industry websites, reports, and news releases, and observational data from trade shows and partner events. Regarding the data analysis, we literally transcribed the interviews followed by immediate categorizing and coding of the data according to the recommendations of Strauss and Corbin (1998) and Miles and Huberman (1994). From the data, distinct categories of instances pertaining to different dimensions of capabilities surfaced. While research proceeded, we increasingly refined our initial interview guidelines to focus on particular categories and dimensions and to reflect the emerging concepts. Eventually, we grouped the instances of each dimension as to success and failure, evaluating whether the specific practice, action, or behaviors led to the result as intended by the actors, that is, managers or organizations. The results are presented in the following section.

EXPLICATING THE COLLABORATIVE CAPABILITY CONSTRUCT The view of capabilities needed for collaborative relationship management that emerged from our fieldwork clearly deviates from the prevailing view, which

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Fig. 1. Dimensions and Components of Collaborative Capability.

describes those capabilities along the lines of the relationship life cycle. Our findings cumulate in the model represented in Fig. 1 and are further outlined in Appendix B. Management capabilities pertaining to collaborative relationships in the context studied are best viewed as consisting of structural, cognitive, and affective capabilities. They enable firms to manage all aspects of boundary-spanning activities.

Structural Capabilities: Setting the Stage The following is a representative statement of an executive responsible for partner management in a middle-sized systems development company. We are good at establishing the right structures. These structures create prerequisites for our employees that they can act appropriately, and, they will do so. My philosophy is that people always want to do their best, but they need a structural context in which they can do so.

It summarizes and highlights the importance our informants gave to the management of structural characteristics of interfirm relations. In particular, they pointed to the intra- and inter-organizational design of the resource configuration, coordination, and incentive adaptation as the most important structural design domains. Resource dedication. In our interviews, type, investment timing, and the amount of resources characterized resource dedication to a specific partnership. In order to initiate and to sustain the partnership, informants deemed continuous significant investments in management time the most essential. They consistently reported that failed activities were related to insufficient management attention either because management resources were limited, the need of management time was underestimated, or too many partnerships were pursued simultaneously. This restricted the management capacity available for each individual partnership and eventually led to a loss of focus. On the contrary, our interviewees associated successful activities with a manageable number of partnerships corresponding to available management

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capacity, and top management commitment. The latter became visible through appropriate dedication of management capacity equipped with responsibility and high autonomy. One partner manager of a small provider of connectivity services responsible for several partnerships summarized these elements as follows: I now have the feeling that we invest the necessary time and resources to get things started, working, and keep it going. Our executive board is very committed and conscious of the need to take necessary investments. Without this support and management actions, one discusses, [and] probably announces the partnership on the website. But likely, the partnership is never ever going to fly.

In general, top management was often only occasionally involved on the operational level but took the role of a partnership promoter, whereas the partner manager played a facilitator role for coordination processes and the development of inter-firm routines. Substantial investments in human resources used to develop specialized partner-related competences and skills surfaced as key enabler for partner success. For instance, several interviewees reported that their high partner-specific technical competence and skill level motivated the focal company to initiate a closer relationship. One interviewee responsible for the partnership with a large software vendor reported that at all times two of the ten employees dedicated to the partnership received training and education to maintain their partner-specific competence level. Generally, our informants emphasized that incremental accumulation of investments in partner- specific resources characterized a successful means of building and developing dedicated resources. In the event that the partner reciprocated small initial investments, the informants’ companies, in stepwise fashion, increased their resources dedicated to the partnership and awaited again reciprocation by the partner. One partner manager of a small but particularly specialized service provider stressed that “throwing something small at the partner” signaled commitment while simultaneously minimized the risk of loss due to possible opportunistic behavior of the partner. Furthermore, several other interviewees pointed out that small investments provided a means to verify the partner’s willingness to commit to the partnership. Eventually, a reciprocal investment cycle developed. In contrast, some managers connected unsuccessful instances with statements like “We had high initial investments but we were not able to recoup these investments and gain equivalent benefits in the relation.” In these instances, the partner company had apparently either taken advantage of them, or the relationship failed to succeed in the market. In some instances, companies invested in tangible assets, however, only after considerable proof of the partnership. Coordination. The interviewees described that coordination of partnership tasks between the partner companies varied in the degree of formalization and the

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design of interaction. Large partner companies often imposed highly standardized formal coordination processes. However, our informants almost always deemed these processes too inflexible, not appropriate, and regularly too slow for the fast-paced nature of the business in the industry. A typical statement from a manager of a mid-size implementation partner of a dominating vendor was: It is absolutely necessary to define clearly who the project leaders are, who the decision-makers are, and who are the right persons for commercial issues in the partner companies and what their responsibilities are exactly. Formal processes and regularities only need to be established when the activity level with that partner surpasses a critical point, but time-pressure of most arising issues renders such processes often obsolete.

Several managers distinguished successful from unsuccessful instances of coordination between people from different functional areas in the partner companies by an evolution of coordination routines rather than by a predefinition of interaction processes. The former often bypassed and circumvented pre-specified processes and interaction designs. Furthermore, informants reporting on successful instances stressed that they flexibly adapted the frequency of these routines to the current level of activity in the partnership in order to secure efficiency. Decision autonomy, clear responsibilities, and clear role assignments of employees involved in the partnership supported this evolutionary process. Therefore, employees’ uncertainty and ambiguity about appropriate action and behavior in the partnership were reduced, which increased the scale, the effectiveness, and the efficiency of joint operations. Nevertheless, the formal assignment of a partner manager who maintained frequent contact with the partner company was a key success factor for the partnership. A manager dedicated to the partnership facilitated the evolution of routines for joint activities in different functional areas, that is, marketing and sales, solution development, or implementation. For example, while comparing two partnerships with major software vendors, a CEO of a small service company reported that one partnership in which a partner manager had a clear responsibility was constantly creating more benefits, for example, in terms of obtaining valuable information about business opportunities. In general, a dedicated partner manager played an active and critical role in connecting relevant employees of their own company with similar people in the partner’s company. Interviewees informed us that the most important tasks of the partner manager were initializing boundary-spanning interaction and coordination, overseeing and tracking joint activities, and mitigating and resolving conflicts. Establishing connections on multiple management levels and in different functional areas between relevant people in both partner companies appeared to be of utmost importance. This provided the framework for a smooth working relationship. For instance, in two

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separate instances managers reported that top management contacts were critical in mobilizing resources for exploiting a large opportunity and a establishing a rescue task force. The most critical functional area in which to establish relationships was sales. Implementing a joint business plan required coordinated action between responsible sales people rather than partner managers. Thus, it was often necessary to overcome the hesitation of sales people who worried about disclosing proprietary customer information. In all instances pertaining to inter-organizational coordination, we found personal interaction with known contact persons to be the most reliable means to achieving timely and efficient coordination. Informants reporting successful instances claimed that sticking to impersonal electronic interaction coupled with standardized processes imposed by the large vendors inevitably did not lead to successful joint operations. To the contrary, delays or even failure to achieve coordination resulted. We observed hesitation in searching for needed information in the partner company. Also, responses to requests were late and inappropriate when relationships did not exist or were anonymous. This was acknowledged by several managers in the vendor companies. For instance, one manager said, “If the partner only relies on our formal procedures to get information and do business with us, the chance for his success is limited.” Cognitive Capabilities: Preparing and Learning the Text We know our partner very well, their technologies and products, but also the organizational setting and the people who may help us with problems . . .. And our partner knows us very well. We always tell them what we are doing, in which areas we are competent and in which not.

Although often manifest in the same instance, our informants constantly emphasized that two distinct cognitive abilities are vital for partnership success: (1) generating, assimilating, and employing partner-related information and knowledge in order to achieve the partnership objectives (knowledge absorption); and (2) conveying information and knowledge about own competences, interests, and organizational settings to the partner company (knowledge infusion). Knowledge absorption. All managers identified knowledge of the partner’s technologies and products as essential. Typical statements were: It is extremely important that our engineers and technicians understand the partner’s technology and products in detail in order to apply them without any hitches. Thus, they continuously devote a lot of time to training and education. Our consultants concerned with the technical and professional matters must be up to date at any time. And therefore, they maintain direct access to the development department of our partner company. They need to talk to our partner’s engineers.

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In institutionalized partner programs of large manufacturers, technical information was readily and excessively provided especially through regular shipment of information material and Internet sites. However, the standardized information procedures often led to an information overload on the partner’s side as one manager of a large technology partner accurately stated: Inevitably, with this information overload, even some important information might get lost on the way,. . . we make great efforts to appropriately manage incoming information.

Several managers stressed the importance of a well-developed ability to filter this information, that is, to recognize and to sort out the relevant part of it and to incorporate this in ongoing and future work. In addition, our informants reported that direct and close contact among technical staff in the partner companies led to detailed early information and helped to secure timely and adequate technical support when needed. A manager described an unsuccessful incident as follows: When we have a technical problem, it is difficult to get support. We have no direct contact with the relevant technical staff in our partner company, and it is troublesome and takes a lot of effort to get the needed information.

In general, the managers were convinced that the ability to filter information backed with direct access to the partner company’s technical staff provided a source of competitive advantage vis-`a-vis competitors in the “partner space.” Despite specific technological know-how, several interviewees emphasized that a prerequisite for successful joint action was development of a clear understanding of the partner’s technical, managerial, and market-related abilities in their own company. One manager of a small service company described the following instance: Recently, we had a meeting with several partners’ employees and our sales and professional service staff. Our people were informed about what our partner actually does and what his technical, managerial, and market competences are. If one doesn’t know the partner’s business, evaluation whether he is the right partner in a project is difficult. In case of doubt, one ceases to involve him.

The employees involved in the partnership needed a clear understanding of the partner’s business and competences to recognize and to evaluate possibilities and benefits of joint actions. All interviewees considered this knowledge critical for delineating areas of competition and cooperation. Reducing ambiguity and behavioral uncertainty about how to deal with the partner in daily action reduced the risk of losing business opportunities. It also enabled the partner to learn essential skills, thus, reasonable joint action was enhanced. However, only some interviewees reported on intentional actions to foster the development of such a body of knowledge. For instance, they indicated the need to systematically monitor

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the partner’s actions, to consult second sources, or to arrange cross-functional meetings with partner employees in order to generate first-hand experience. As the interviews progressed, it became increasingly clear that successful partnership operations depended on intimate knowledge of the partner company’s internal structures and configurations, where competences and skills reside, and who is able to help in case of support needs. An executive of a large manufacturing company describing their relationship to a large software partner pointed out: The greatest challenge is to obtain intelligence on strategies and personnel; who is responsible for what issues today and in the future; who indeed is the decision maker and the like. There is no piece of paper to read off this information. The only way to obtain this knowledge is to develop a close-knit partnership.

A director of a middle-sized technology company acknowledged: If we hadn’t become truly familiar with the internal structures and networks of our partner, we wouldn’t have prospered with that partnership.

Finally, the partner manager of a small service company stated: Especially when dealing with large organizations, one must know the relevant persons to obtain critical information and get quick decisions. This is extremely important because project implementation is often very time critical.

Without an understanding of the operational and personnel details of the partner, the level of overall activity in the partnership remained low and critical support, that is, sales assistance, or solution of sophisticated technical problems, was delayed. Using formal and informal opportunities to get and maintain multiple contacts in the partner company, informants stressed their potential to obtain valuable knowledge about market opportunities, for example, forthcoming requests for proposals for new projects or the chance to fill in a gap where a competitor failed to meet his obligations. Knowledge infusion. In our interviews, the ability to constantly convey and disseminate knowledge and information about one’s own company to the partner company emerged as key capability. Communication style, the accomplished dissemination in the partner company, and balancing between necessary disclosure and protection of proprietary knowledge characterized knowledge infusion. A typical statement that describes a successful incident was: We place special attention and effort on an appropriate design of the information flow in order to be present in the partner’s mind. Therefore, we systematically use regular status meetings, or we try to be present at internal sales meetings of the partner, to get time slots to present my company and its competences as often and to as many people as possible.

Technical and managerial competence was the most important criterion for partner selection. Hence, most of the informants were aware of the need to communicate

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their market focus, competences and skills to people in different functional areas and on different hierarchical levels in their partner’s companies. In order to differentiate their own company in the partner space and to achieve a preferred partner status, attempts to link their company’s name with special industries or customer types were common. A manager from a large system integrator who reported on the company’s partnerships with major hardware and software suppliers stated: A clear profile is important. I am glad when the partner company’s employees immediately think of us in case they get a request from a special industry. We always stress our special competences in this market.

Yet, despite the general importance given to this point by managers, we observed a surprisingly large number of instances in which attempts and actions to anchor this knowledge in the minds of partners’ employees failed. In these instances, the companies exhibited either no consistent market focus and business model, missed the chance to pursue and maintain effective communication, or did not address the actual decision-maker and relevant influencers in the partner company. Several managers of small and highly specialized companies informed us that, when initiating partnerships with large and powerful vendors, their companies encountered the problem of loss of proprietary information and knowledge, that is, special service know-how or most prominent customer information. Being overly eager in conveying their high competence level to the potential partner, they tended to disclose too much critical knowledge, thus, they provided the partner with the opportunity to take advantage of them without assuring his cooperative motivation. As expected, in ongoing partnerships co-opetitive issues were by far the most critical area of knowledge and information. Although most interviewees claimed to choose partners with the most complementary capabilities, competition was largely inevitable. A typical statement which reflects this situation was: Partnerships are never completely complementary; there are always more or less competitive overlaps in competences or assets among partners. But, joint delineation of cooperative and competitive areas, rich information, and open communication allows dealing with this in any specific situation.

Interestingly, non-complementarities and competitive tendencies were not in any instance a reason for frequent and prolonged conflicts and problems. Their occurrence largely depended on the communication style used. Our interviewees associated successful instances with an explicit and early addressing of the issue in the partnership instead of playing it down. Likewise, they stressed the importance of frankly expressing their own interests, either a priori regarding a joint or competitive action, or in a case where the partner violated the agreed-upon behavioral rules of the partnership. The worst-case scenarios outlined by the

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interviewees were situations where, in order to circumvent conflicts, the partner concealed his interests or even worse was deliberately deceitful. For example, in one instance the partner communicated with the apparent hidden intent not to engage in a request for proposal but rather to eventually bid for the contract with another partner. In contrast, one manager from a small solution service company described their successful practice as follows: We are really straightforward and honest. If we have made a decision for one partner to make an offer for a project, we immediately tell this all other partners, thus, they know what’s going on.

From the opposite perspective a sales executive stated: One can clarify a situation before a conflict arises. If our partner makes an offer with another partner and communicates that properly, which means in time and with reasonable explanation, I have no problem with that. I would only mind if they then precluded us from working on that account. Of course, we try to influence their choice.

In general, a priori, honest, communication and information served to reduce uncertainty in the partner company and mitigated conflict through clarification of the rules for cooperation and competition. Therefore, reduced risk and enhanced reliability established the basis for a trusting relationship. Affective Capabilities: Winning Over the Influence The whole life runs on a non-rational track. The emotional level matters a lot. Business to business with people. Do I feel well working with this partner? What do I need to do to make him feel well?

Without exception, interviewees were consistent in the view that non-rational issues, that is, affective states and feelings causing arousal with a positive or negative valence, are important influencing factors in collaborative relationships. Thus, the ability to address and deal with affective states was an important facet of management capabilities for relationship management. Enactment of these capabilities almost always took place at the level of individual members of the partner organization. However, we observed clear and homogenous attitudes concerning the seriousness with which different companies paid attention to affect, emotions, and appropriate interpersonal behavior. Partner companies were either generally perceived as “good fellows” or a “friendly partner company,” or in contrast as “unappealing” or “not much fun to do business with.” Some illustrative statements from different executives were: I have worked now for 15 years with that company. Historically, they often were an arrogant and very self-confident partner.

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Whether it is a pleasure to do business with a company is somehow a question of appropriate values of top management and that these values are practiced throughout the organization. In this company, nobody gets punished for dirty work or foul play when it leads to good performance. Thus, it is not a good partner as such, but there are some people one can work with.

In contrast, another stated: This partner has an extremely “good” track record, I am always very careful when dealing with them. But the other partner, they have a different culture. I have the feeling they really care about us and try to help where they can, that’s probably the reason why I feel much more comfortable with them.

Thus, capabilities of individuals varied at times quite dramatically. Nevertheless, informants described an overall coherence of the partner organization’s actions and behavior addressing and reacting to the affective states of the partner company’s members. It is noteworthy that most informants illustrated the concrete forms and day-to-day effects of these affective capabilities in terms of the partner company’s behaviors and actions rather than their own. The magnitude of affective states and behaviors surfaced in expressions like “the chemistry between partners,” “sensing the human side,” the need for “partner care,” to get a “feeling” for the partner, or “hold hands” when problems emerge. Based on these accounts, we summarize the most important capabilities as the ability to empathize with the partner and to express validation. Empathizing. Sensing the implicit and unspoken meanings of partner company employees’ verbal expressions and actions was deemed critical to track the relational atmosphere. In order to grasp and to get an understanding of the hidden and often unjustified uncertainties, reservations, and worries of the partner, some managers told us “one needs to have the antennas out.” Likewise, our informants stressed the importance of taking the counterpart’s perspective. The following statement from a partner manager of a large solution company captures most of our observations: To be successful in partnering you need to have a certain social capability. You have to feel and understand the partner, get into his shoes and take his perspective.

Eventually those “gut feelings” could be addressed by appropriate action and behavior to comfort the partner and prevent conflicts. Missing out in accounting for these affective states may lead to considerable delays and severe barriers to cooperation: They thought we were only following our interests but actually we were not. However, the relationship was blocked for months until we detected the problem by chance in a meeting held for some other reason. They felt that the relationship was a one-way road and were reluctant to put effort into our joint work.

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Another manager reported: Their gut feeling often hinders them in joining in with us. We invite the key players for dinner, ask “what’s your problem” and “how can we settle the issue,” pursuing the aim that they feel good. That’s the first step. Later, I am sure, we can prove that we are capable of what we promise, but they need to feel comfortable first.

In general, the interviewees most often characterized unsuccessful instances as a neglect of non- rational influences in business relations or the failure to accommodate and affectively address the partner’s employees. The statement of a sales executive in a small solution company captures this: We did not feel right about meeting the partner’s employees on a very personal level so that they would supply us with valuable information or go out of their way to help us.

Validation. An active expression of affective capabilities consistently emerged in our investigation. This was the necessity of conveying to the partner a feeling of being cared for and appreciated not only at an individual but also the organizational level, irrespective of hierarchical level and status. A CEO of a small company summarized this in the following way: I care about a partnership when I have the feeling that I am not only a number or a piece of paper. Imagine, in case of a personnel change, the new person recognizes, “Well, there is yet another partner,” and he makes an effort to call me and the first inquiry reveals he doesn’t know anything about me. Thus, I have no reliance and trust in the counterpart; actually, I would not even actively terminate the partnership [but] just leave it on its own because it’s not worth the haggling and effort to terminate.

The interviewees reported that caring and appreciation for the partner company and its employees was enacted by different means. First, one of the most basic requirements was to seriously attend to the other’s views and circumstances as this is generally seen as an expression of respect and signals that the other’s experiences and ideas are considered as valuable and worthwhile. Consequently, attention to the partner’s opinions, ideas, and expertise and involving the partner when important decisions concerning the partnership are made were viewed by informants as central elements of validation. Second, active caring also acted as a potent demonstration of the perceived worth of the partner, thereby bringing out individual efforts and strengthening the psychological attachment to the partnership. A manager from a distributor organization captured this as follows: . . . there is no commercial dependence [of our partners] but dependence caused by the way we care about the partner, let’s say a kind of psychological dependence.

It is important to note that this care and backing must not be contingent on immediate economic gains. Several managers expressed that good partnerships survive periods of unequal reward as long as a long-term outcome of fairness

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is achieved. Third, according to our informants, an important facet of showing appreciation was expressed in the nature and handling of decision processes in the relationship. In general, the degree to which partnership-related decisions were made jointly with active participation of all partners was linked to positive regard of the decision consequences and acceptance of compromises. To the contrary, unilateral decision-making that affected the partner company coupled with late communication to the partner elicited feelings of anger, frustration, and negative regard of the partnership. In effect, partnerships deteriorated and efforts on behalf of the partnership were considerably reduced. A sales executive reported: We have just been kicked [out] of the circle of the attended partners. We got the message and then we contacted our partner to discuss this and get an explanation. We were ask for specific actions, but this was all so frustrating . . . We eventually decided to withdraw further from the relationship.

Finally, expressing appreciation of the partner’s performance seemed to play a prominent role in eliciting a partner’s favorable approval of the partnership. We consistently observed that our interviewees displayed positive affect in response to approval of their performance through the granting of special contractual conditions and winning awards. These were perceived as concrete expressions of their status as a valuable, preferred partner. A manager described these events as follows: We worked closely together in a joint project. We took the project lead and finished on time. All were happy in the end, our partner, the customer, and us. We received this award for doing an outstanding job and that’s not only a paper. One has a reputational effect for further project acquisition, and actually, the leading project manager still gets misty-eyed when talking about this project.

Being rewarded was experienced positively not only because of its economic consequences but because it made people feel proud as well as flattered on an emotional level, which led to a positive perception of the partnership.

Synthesis and Commentary From our results, collaborative capability is appropriately viewed as a continuous construct. We found the existence of collaborative capability in an individual company to be a matter of degree. Companies vary in the extent to which they exhibit structural capabilities, that is, dedicate resources and coordinate cognitive capabilities; absorb and infuse knowledge and affective capabilities; and are able to empathize with and validate their partner organizations. Moreover,

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there might be differences in the individual dimensions; thus, each company has its own profile of collaborative capabilities according to the extent of each single capability. Apparently, different capability dimensions are not completely independent of each other. In many interviews, successful instances pertaining to one dimension were accompanied by successful instances related to other dimensions. For example, managers who reported on multiple linkages between the partner companies and efforts to build up personalized relations also often displayed considerable knowledge about the partner organization through access to “informal” information. Likewise, activities to broaden the knowledge base, for example, training and education, or regular participation in partner events, tended to correlate with empathic reaction and high validation of the partner. Nevertheless, it is important to note that we did not observe the mutually reinforcing nature of different capabilities in any case. For example, one manager reported the following: We had a close relation with one partner, we had offered and implemented projects quite successfully in the past. We were in regular close contact. Recently, while we were jointly in the middle of the sales cycle with an existing customer, it turned out that they were close to bankruptcy. We hadn’t recognized the signs and had a lot of trouble because of that.

In general, we observed that awareness and conscious design, in other words, intentional and coordinated action, in each single dimension led to a firm’s successful relationship management. While partner-related knowledge or coordination routines did develop without intended action over time, we found superior management performance related to purposefully sought development strategies and coordinated activities. Furthermore, during the analysis, we noticed that each of the three dimensions could have negative or positive effects, for example, an interviewee reported that despite the fact that partnerships were economically not viable, they were often upheld and nurtured because of high affective attachment. An over-reliance on structural aspects led to inflexible processes in some instances. We observed that a proper balance in the composition of different dimensions characterized accounts of successful partnerships. This suggests that the different capabilities are complementary rather than substitutes. Consequently, we propose that a proactive management approach balancing the individual capability dimensions is key. Based on the empirical findings reported in the preceding sections we offer the following formal definition of collaborative capability: Collaborative capability is a set of organization-wide intentional and coordinated processes, actions and behaviors to manage the structural, cognitive, and affective dimensions of collaborative relationships in order to bring about the individual and common objectives of that relationship.

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Organization-wide capabilities emphasize that collaborative capability must not be limited to individuals or special functions but needs to be present in all relevant departments and their employees. Furthermore, it is important to remember that the intention to engage in specific activities need not forestall the development of rather unconscious routines or draw upon already existing routines appropriate for relationship management. Finally, the incorporation of individual and common objectives underscores the fact that collaborative capability excludes aiming solely and intentionally at taking advantage of the partner in pursuit of one’s own interests.

DISCUSSION Our findings pertaining to structural, cognitive, and affective capabilities in the management of collaborative relationships corroborate, contradict, and extend aspects of prior research in the domain of dyadic and firm level relationship research. The results coincide with prior research in that they affirm the significance of dedicating specific investments and building up and maintaining specific resources as a prerequisite for a successful relationship (Dyer, 1996; Dyer & Singh, 1998; Heide & John, 1990; Lambe et al., 2002) and the importance of capabilities for coordinating within and across company boundaries (Kale et al., 2002; Kale & Singh, 1999). Following Williamson (1985), Anderson and Weitz (1992) argued that investments in partner-specific assets by the focal party align their self-interest. Specific assets motivate the focal party to continue the relationship in order to safeguard investments. The results also confirm the notion of an approach with incremental movements by gradually increasing dedicated resources that edge organizations and individuals closer and closer, when risk and uncertainty are high (Das & Teng, 1998; Larson, 1992). Our findings also concur with Sivadas and Dwyer’s (2000) reasoning that efficacy and efficiency of collaborative relationships depend on prior consensus regarding the responsibilities of the parties involved and the tasks each partner will do. Psychological and economic research on the individual level has repeatedly shown that high role ambiguity, that is, the lack of clear information associated with a particular role, is negatively related to individual’s performance (for a review see Tubre & Collins, 2000). Many researchers have highlighted the importance of establishing connectivity (e.g. Bensaou & Venkatraman, 1995; Diller & Kusterer, 1988; Ortmann & Sydow, 1999), and promoting personalized means of coordination (e.g. Mohr & Nevin, 1990; Van de Ven et al., 1976). Others stressed the value of circumventing formal structures in order to achieve

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appropriate coordination and information-processing capacity (Ortmann & Sydow, 1999). Yet, the pivotal role that the partner manager plays in the process of inducing and developing these coordination means has been barely addressed (see Spekman et al., 1998). Our preliminary findings call for more in-depth research on the function of the partner manager as a “catalyzer” of partnership development. Cognitive capabilities has been given a prominent place in prior research. However, research examining absorptive capabilities (or absorptive capacity as termed Cohen & Levinthal, 1990) in the context of collaborative relationships has mainly focused on: (1) how absorptive capacity enables inter-organizational learning and positive outcomes such as innovation (e.g. Ahuja & Katila, 2001; Lane & Lubatkin, 1998); and (2) how experience with collaborative relationships – implicitly assumed to be related to learning and the development of absorptive capacity in the domain – contributes to relationship performance (e.g. Kale & Singh, 1999; Simonin, 1997; Zollo et al., 2002). Nevertheless, researchers investigating the dyad rather than the participating companies have stressed the importance of accumulating partner-specific knowledge in order to enhance exploitation of opportunities in the relationship, to smoothen interaction patterns and to mitigate coordination, or information gathering problems and conflict (Doz, 1996; Dyer, 1996; Gulati, 1995). Yet, our study suggests that in order to obtain a competitive edge, partner-specific knowledge creation by chance or as a by-product of interaction is not sufficient. A systematic approach designed to collect, filter, absorb, and use partner-specific knowledge is needed. Furthermore, of utmost criticality is the accumulation of detailed personnel knowledge of the partner since this is key to obtaining further needed valuable information and knowledge. While virtually non-existent in the management literature, exerting influence through different information and communication strategies has taken a prominent place in relationship marketing research (e.g. Dwyer et al., 1987; Frazier & Rody, 1991; Mohr & Nevin, 1990; Sheth & Parvatiyar, 1995). Most often the perspective of the more powerful party is taken. Interestingly, the implicit assumption of most of this research is that, by default, a coercive influence strategy is best unless countervailing power is present on the partner’s side. Surprisingly, proactive information strategies and self-marketing attempts of the less powerful partner have been either neglected or taken for granted. Their information and communication abilities are only found in Hirschman’s (1970) response scheme of voice, neglect, exit, and loyalty to problems in relations. Yet, our results suggest that designing an effective strategy to infuse the partner company with information and knowledge about the own company is not a trivial issue and may lead to substantial positive effects, especially in co-opetive relationships. Indeed, it contradicts the prevailing view that less powerful partners in a relationship

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are constrained to a reaction vis-`a-vis the counterparts’ information and communication policies (Mohr & Nevin, 1990) instead of designing their own active information strategy. Our findings point to the pervasiveness of affect-based phenomena in collaborative relationships which to our knowledge has not been addressed in prior research. In general, the understanding has been that: because working relationships generally exist to accomplish tasks while social relationships (do) not, task achievement, task instrumentality and task-specific competence are especially important in work relationships, while affect and self-disclosure are less important (Gabarro, 1990, p. 79).

The limitation of the “homo economicus” assumption in reflecting economic reality and the underdevelopment of economic and social exchange theories are increasingly being recognized. Consequently, several scholars (Huy, 1999; Lawler & Thye, 1999; Luthans, 2002) call for the integration of affective concepts, for instance, positive efficacy, hope, subjective well being, empathy, or emotional intelligence in economic research. Although these concepts are derived on an individual level, several researchers conclude that it is reasonable to apply them to the organizational level. What organizations choose to reward, expect, and support can exert considerable influence on their members’ behaviors, which may form a consistent organizational pattern (Huy, 1999; Kahn, 1993). We came to the same conclusion. We observed that entire organizations exhibited patterns of affective capabilities enacted through the majority of their members. Prior research only hints at the relevance of affect and emotion in collaborative relationships. Dwyer, Schurr and Oh (1987) mention “psychological benefits” and “deep sentimental scars,” which may occur during the course of action in relationships and influence their future development. Ring and Van de Ven (1994) argue that building close personal relationships and forming psychological contracts between members of the partner firms is stronger glue than any formal contract. Still, the socio-psychological literature reports various findings pertaining to affect-based influence in interpersonal relations. Taking the perspective of the counterpart, empathic behaviors in groups have been found to lead to more creative problem solving, cooperation, trust, attraction, and satisfaction among group members (Falk & Johnson, 1977) and attribution behaviors favorable to relationship continuation between individuals (Parker & Axtell, 2001). Several researchers have emphasized motivational effects of feeling valued and appreciated which lead to behavior that goes beyond the call of duty and promotes cooperation (Hollander, 1990; Katz, 1967). Kim and Mauborgne (1998) found that people want to be treated with respect, dignity, and appreciation and that to the extent that this emotional worth is not considered, people feel anger and consequently tend to

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drag their feet refusing cooperation. Reversely, the findings of this study confirm that acts of validation elicit positive feelings in the reacting agent and prompt favorable reciprocal behavior. To sum up, to the best of our knowledge, the present study is the first to deliver a detailed picture of collaborative capabilities that integrates different perspectives and outlines a comprehensive collaborative capability construct. While some of the findings may be idiosyncratic to the specific industry context of the study, we are confident that the basic dimensions and components are generalizable to other contexts.

CONCLUSION In this chapter we have presented a construct of capabilities for the management of collaborative relationships, which encompasses structural, cognitive, and affective capability dimensions. These dimensions exert a positive influence on collaboration processes and outcomes. The view that emerges from the field study differs from the received view in the literature at least in three points: first, it deviates from the link between relationship management capabilities and phases of the relationship lifecycle (Lambe et al., 2002; Simonin, 1997). Instead, it appears that structural, cognitive, and affective capabilities build a horizontal layer important in all phases but varying in the needed extent over the life cycle, that is, cognitive capabilities play an important role in partner selection whereas structural capabilities are essential in initiating and implementation. Second, we conclude that collaborative capabilities are more partner-specific than suggested in prior research. Clearly, learning the broad spectrum of functional and behavioral alternatives in the different dimensions is essential for companies, yet, our results suggest that the value of collaborative capability is given by selecting appropriate strategies under a given set of specific characteristics of the actual partner. One essential related skill is to be able to quickly and precisely accumulate knowledge from and about the specific partner. Third, we suggest that it is important to be able to appropriately manage all three dimensions. It seems that a single superior capability, either structural, cognitive, or affective, does not lead to intended effects and increases the probability of turning from an asset to a liability or becoming a “core rigidity.” Some limitations apply to the findings outlined in this chapter. First, research on collaborative relationships is an emerging stream of inquiry borrowing from numerous disciplines with many important studies shedding light on different aspects. It is not yet a coherent body of knowledge. We have attempted to bridge insights from many different fields and to paint a comprehensive picture. However,

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in order to set the stage for a productive dialogue, we may have necessarily sacrificed depth for breadth in some areas. A second limitation revolves around our research process. In an attempt to gain an in-depth understanding of the phenomenon, we conducted an exploratory qualitative study in a single industry. We applied standard methodological rigor, however, the general limitations of qualitative methods in studying a single industry may raise the question about the general applicability of our findings to a broader context. Finally, we believe we have extended prior research on collaborative capabilities with a new distinctive dimension – affective capability – that has been rather neglected in economic and business research. As economic exchange relations are almost always and simultaneously social exchange relations, our perspective is that business research needs to include greater emphasis on the affective and emotional aspects of construct and theory development.

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APPENDIX A Prior Research on Collaborative Capabilities Concept

Theoretical Lens

Conceptualization

Empirical Validation

Treatment/ Modelling

Outcome Effects

Hillig (1997)

Cooperative competence

Organizational change, learning theory

Five dimensions of cooperative competence: self-organization, observation, shared understanding, trust and conflict

Exploratory case study of a joint venture

Predictor of success in processes of fundamental change aimed at by strategic alliances

Simonin (1997)

Collaborative know-how

Learning theory, organizations as learning systems

Five know-how dimensions: collaborative management know-how, negotiation know-how, partner searching know-how, knowledge and skill transfer, exiting skills

Survey of 151 large and medium-sized corporations from different sectors in the U.S.

Mediator between experience and (in) tangible collaboration benefits

Companies aiming at successful fundamental change processes through strategic alliances need to develop a cooperative competence as a basic necessity to achieve competitive advantage Tangible and intangible benefits obtained from collaboration are greater, the higher the level of collaborative know-how; experience does not directly influence the benefits

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Author(s)

Relational view, strategic management

Absence of, simply “a firm’s willingness and ability to partner”

Absence of, conceptual

Predictor for the generation of relational rents

Ritter and Gem¨unden (1999)

Network competence

Innovation/ Technology

Survey among 308 German engineering, electronic, tooling and medical device companies

Network competence as predictor of innovation success and technological interweavement

Kale and Singh (1999)

Alliance capability

Organizational learning, strategic management

Sets of network-related tasks and qualifications needed to perform these tasks: planning, organization, HR management, control, negotiation, exchange, coordination, social and technical qualification, task accomplishment, existence of qualification Alliance capability measured in terms of coordinative capacity and processes for articulation, codification, sharing and internalization of alliance-related knowledge

Survey of 160 U.S. firms in industries with allying being an important aspect of firm strategy

Coordinative capacity and management processes as predictor of alliance success

Relational capabilities or relation-building skills are argued to be necessary to employ effective governance mechanisms, create relation-specific assets and develop knowledge sharing routines Positive influence of network competence on technological interweavement, technical and commercial innovation success; network competence is related to resource availability in the organization, network orientation of HR management, an integrated communication culture and an open organizational culture Coordinative capacity and knowledge management processes positively influence alliance success; alliance experience also has a direct effect, but significance reduces upon inclusion of the knowledge variables

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Relational capability

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Dyer and Singh (1998)

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APPENDIX A (Continued ) Prior Research on Collaborative Capabilities Concept

Theoretical Lens

Conceptualization

Empirical Validation

Treatment/ Modelling

Outcome Effects

Lorenzoni and Lipparini (1999)

Relational capabilities

Organizational learning, RBV

Exploratory longitudinal case studies of three lead firm-network relationships in Italy

Predictor of lead firms’ knowledge access/transfer with consequences for growth and innovativeness

Relational capabilities help competence renewal and reduce resistance to change; lead firms can achieve valuable positions using multiple (in) formal ties to knowledge access and transfer; collaboration as valuable to expand and improve core competencies

Anand and Khanna (2000)

Alliance capability

Organizational learning theory, organizations as learning systems

Changes in the lead firms’ supplier networks towards fewer but closer suppliers; development of specialized supplier network while building a smaller more focused set of core competencies Estimation of firm-fixed effects over and above alliance experience to capture unobserved heterogeneity in firm level alliance capability

Secondary data on 1976 joint ventures and licensing agreements in the manufacturing sector

Predictor of abnormal stock market returns after an alliance announcement

Results show strong and persistent differences across firms in their ability to create value in alliances; the authors interpret these as differences in alliance capabilities

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Author(s)

Alliance competence

RBV, competencebased theory

Kale, Dyer and Singh (2002)

Alliance capability

Organizational learning, dynamic capabilities

Alliance competence as organizational ability for finding, developing and managing alliances: alliance experience, alliance manager development capability and partner identification propensity Existence of an alliance function to capture, integrate and disseminate alliance-related knowledge

Survey among 145 alliances managers of 71 different companies reporting on 145 alliances

Joint alliance competence as predictor of the creation of idiosyncratic resources and joint alliances success

Joint alliance competence is directly positively related to alliances success and indirectly via the combination of complementary resources in an alliances and the creation of idiosyncratic resources in the alliance

Archival data and data from two respondents in 78 companies in various industries who report on 1572 alliances

Investments in a dedicated alliance function as a predictor of abnormal stock market returns and overall success with alliances

Investments in a dedicated alliance function are positively related to alliance value creation; although alliance experience is important, it has the most impact when systematic coordination and leveraging is introduced in alliance management processes

Integrating Perspectives

Lambe, Spekman and Hunt (2002)

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APPENDIX B Characteristics of Successful and Unsuccessful Practices of Collaboration Management Characteristics

Successful Instances

Failure Instances

Function

High investments in training and education and management time Continuous Incrementally increasing to high level (“probing”)

Not enough management time

Knowledge and skill development Signaling commitment Providing framework for coordination and interaction

Structural Capabilities Resource Dedication Kind

Sporadic Starting too large in the beginning or remaining to small over time

Coordination Areas

Formalization

Partnership management and partnerships tasks (development, projects, [pre] sales, marketing) Low degree of process standardization, low centralization combined with high employee autonomy and clear responsibilities, active development of interaction routines

Overall low coordination activity, no integration of areas

Coordination and integration of action

Pre-formulated highly standardized processes, no clear responsibilities, slow decision-making, missing adaptability to partner organization

Flexibility and efficiency of processes

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Timing Amount

Face-to-face between partner managers with high frequency, direct interaction between employees in different functional areas, incorporation of different management levels, high degree of consistency

Too much or infrequent, no “personalization” of interaction, isolated, single contacts with one or few partner’s employees, frequent changes of responsible people

Coordination effectiveness Achieving connectivity

Partner-specific product/service related knowledge, organizational knowledge of partner strategies, structure, personnel, and specific culture Actively seeking and using different sources and opportunities to gain information not readily provided, systematically filtering and evaluating incoming information by knowledgeable employees according to own needs Transferring and disseminating information within own organization to relevant employees, taking quick action to exploit incoming information, using organizational information for information gathering and quick solution of issues

Ambiguity about partner competences and market position, failure to build up and maintain organizational knowledge

Assessing partner market position and competence fit for evaluating joint opportunity exploitation

Lacking attentiveness and exploitation of information opportunities, getting overwhelmed by incoming information

Getting partner “understanding” Maintaining skill level, detecting co-operative opportunities

Relevant partner-related knowledge kept isolated by few employees, missing putting together knowledge from different sources in order to get a “big partner picture,” hesitation and slow reactions in taking advantage of information gained

Quick action (first mover advantage) and exploitation of opportunities

Cognitive Capabilities

Integrating Perspectives

Interaction

Knowledge Absorption Knowledge domain

Recognition & evaluation

Assimilation & application

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APPENDIX B (Continued ) Characteristics of Successful and Unsuccessful Practices of Collaboration Management Characteristics

Successful Instances

Failure Instances

Function

Knowledge domain

Market position, competence, and interests

Clarification of business model and focus,

Reach

Defining relevant people in the partner’s organization, achieving “broad reach” within the partner company Proactively seeking and using opportunities, open, a priori information especially for “critical” information related to competitive action; proactively addressing emerging issues and conflicts

Early disclosure of critical proprietary knowledge concerning competences and customer data Failure to identify and win over important supportive people in the partner’s company

Knowledge Infusion

Reluctance and hesitation to express own interests, absence of or after the fact information about competitive action, delay of conflict resolution

Affective Capabilities Empathizing Sensing

Attention to the relational atmosphere, gathering implicit meanings and expressions, recognizing unspoken fears and worries of the partner, being able to assess situations, actions, and behaviors from the counterparts point of view

Assuming completely rational actors because of the business context, failing to recognize affective states of the counterpart and implicit non-rational barriers to cooperation

Partner understanding Detecting and balancing interests

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Communication style

Clarification of expectations and “rules of the game” (cooperation – competition) Educating the partner Mitigating conflict

Expressing and getting across understanding and readiness for dialogue, actively addressing counterparts’ concerns on cognitive and affective level

Failure to respond appropriately

Conflict mitigation and resolution

Showing continuous interest in the counterparts’ well-being, engaged in active listening and taking seriously the partner’s interests and concerns, helping the partner to solve problems when needed without expecting immediate, short-term benefits Using a personalized means of interaction at least to a minimum extent, employing a participative decision making style in the partnership, expressing honor for the partner’s efforts and achievements through non pecuniary means

Being intrusive or overly intentional

Signaling reliability and trustworthiness

Not consulting the partner when decisions are made, after the fact communication of decisions, unbalanced use of praise (none or excessive), thus, reliability is not achieved

Creating psychological attachment Motivating the partner Showing respect and dignity

Validation Caring

Appreciation

Integrating Perspectives

Comforting

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THE COLLABORATIVE CAPACITY FRAMEWORK: FROM LOCAL TEAMS TO GLOBAL ALLIANCES Stephen P. Fitzgerald ABSTRACT Collaborative forms range from co-located teams engaged in short term local projects, to international joint ventures, to worldwide networks of organizations and citizens linked together to generate global social change. In order to discern patterns that transcend the breadth of forms (including virtual), a new term is introduced that encompasses the entire spectrum: collaborative entity (CE). The diverse and far-ranging CE literature is then integrated into the Collaborative Capacity (CC) Framework. That framework is comprised of ten broad constructs and their interrelationships that, when considered together, capture fundamental aspects of all CEs. The CC Framework provides a bridge-building language to help facilitate inter-disciplinary, multi-dimensional dialogue, research, and perspectives on fostering collaborative capacity.

INTRODUCTION Increasingly diverse forms of inter-entity collaboration proliferated over the past two decades, and continue to do so (e.g. Gulati, 1999). Emery and Trist (1965) Complex Collaboration: Building the Capabilities for Working Across Boundaries Advances in Interdisciplinary Studies of Work Teams, Volume 10, 161–201 Copyright © 2004 by Elsevier Ltd. All rights of reproduction in any form reserved ISSN: 1572-0977/doi:10.1016/S1572-0977(04)10007-1

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first prophesied such a trend would develop in response to increasingly turbulent and uncertain environments. That trend shows no signs of abating as the ground swell of technological change and globalization continues, and a dizzying array of collaborative forms evolves. Those forms range from co-located teams engaged in short term local projects, to international joint ventures, to worldwide constellations of organizations and citizens networked together to generate global social change. For example, intersectoral partnerships link government, business, non-governmental organizations, and communities in addressing areas of common concern. Businesses enter intra- and international joint ventures, alliances, networks, and other forms of business collaboration in order to reap the benefits of mutual learning, exploration, development, and economic advantage. Some business scholars even herald the death of competition (e.g. Moore, 1996). These collaborative trends have engendered comparably diverse and prolific streams of research from a myriad of disciplines and theoretical perspectives. In this chapter, a conceptual framework is introduced that integrates and bridges these diverse perspectives on the breadth of human collaborative phenomena. First, the extensive prior research on cooperation is briefly touched on to draw attention to the rich historical roots of inquiry into collaboration, and to set the stage for the rationale for developing an integrative theoretical framework on collaboration. Next, two terms are introduced and defined to expand our conceptual boundaries: collaborative entity (CE) and collaborative capacity (CC). With these terms established, the CC Framework is introduced to define and illustrate the ten constructs that comprise this framework. Each construct and its interrelationships with the others is then elaborated through a review of the literature from diverse disciplines, levels of analysis, and theoretical perspectives that contribute to the development of this construct. The chapter concludes with an example of the successful application of the CC framework in studying complex collaboration across several levels of analysis, and a discussion of the implications for future research and application.

FROM COOPERATION TO COLLABORATION Research on collaboration has its roots in the similarly diverse history of research on cooperation, which spans more than a century. For example, during the twentieth century, biologists, sociologists, psychologists, anthropologists, sociobiologists, political scientists, economists, philosophers, communication theorists and others explored cooperation from within the constructs and methodologies of their respective fields. Synthesizing research findings across these disciplines,

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Argyle (1991) distinguishes three primary motives for cooperative behavior: (1) external rewards; (2) relationships; and (3) shared activities. Goal theory, which has been highly influential and prolifically researched, falls under the first category, but it does not account for the other two. Goal theory is a function of a western, rational, economic view of human interaction. However, it fails as a model for cooperative personal relationships, because it does not account for people’s concern for the welfare of their partners, and for the relationships themselves. Similarly, once people bond with an organization, they may exhibit “non-rational” (non-economic) behavior as a result. Affective bonding and internalization of an organization’s values have been important contributors to individual behavior as well as to team and organizational performance. In reviewing the extensive research on cooperation, Argyle (1991) sets forth extensive, multi-disciplinary evidence that supports the hypothesis that humans are essentially cooperative and that, similar to Tjosvold’s (1993) view, competitive and individualistic behavior is embedded within a fundamentally cooperative context. The two central theses of Argyle’s text are that cooperation leads to: (1) positive affect and emotional rewards; and (2) interpersonal attraction between those involved. He demonstrates that cooperative behavior requires intricate high level skills and that rather than being regarded as “selfish,” non-cooperative behavior might be more accurately viewed as a lack of social skill. There has been little reference to this historical legacy in the collaboration literature, and little cross-fertilization or dialogue among the various disciplines and theoretical perspectives that have been brought to bear on collaborative phenomena. In their introduction to the Academy of Management Journal’s special research forum on alliances and networks, Osborn and Hagedoorn (1997) encourage researchers to “abandon a singular, clear-cut description of alliances and networks based on the assumptions of a host discipline in favor of a more robust, sophisticated, multidimensional vision” (p. 274). To develop a fuller, more holistic view of inter-entity collaboration, a large interdisciplinary sample of research papers, chapters, and books on cooperation, collaboration, alliances, networks, inter-organizational relations, teams, and communities of practice was reviewed. That review led to the creation of the integrative CE concept and CC Framework. These are described next.

COLLABORATIVE ENTITIES In organizational studies, the term “team” refers to a relatively small, collaborative group of individuals, whereas “alliance” and/or “inter-organizational relationship” are commonly used to refer to collaborative efforts among organizations of all

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kinds (e.g. business, non-profit, and government entities). Inter-organizational collaborations come in a wide variety of forms, ranging from contractual joint ventures, to inter-sectoral partnerships, to relational networks. However, in today’s increasingly complex environment, some forms of alliances (e.g. “chaordic” alliances (Hock, 1998)) may include individuals, groups, and associations in addition to formal organizations or institutions. The distinctions among forms are blurring, thus the terminology in use, and the conceptual boundaries they represent, can no longer encompass the increasing diversity of collaborative forms. Further, collaborative forms span levels of analysis (e.g. dyads, teams, organizations, alliances) and have many characteristics in common. In order to help discern patterns that transcend these collaborative forms (including virtual) and levels of analyses, the CE construct is introduced. A CE is defined as a social action system (Van de Ven, 1976, p. 25) whose members “exchange information, alter their activities, share resources and enhance each other’s capacity for mutual benefit and a common purpose by sharing risks, responsibilities, and rewards” (Himmelman, 1996, p. 4). A CE’s members may include individuals, groups, associations, organizations, alliances and/or networks of organizations, and other collective phenomena. Thus, teams, joint ventures, inter-organizational relationships, strategic alliances, networks, communities of practice (Wenger, 1999), and so forth, are variants of the broader classification of collaborative forms.

COLLABORATIVE CAPACITY Collaborative capacity is the extent to which a CE and the factors that comprise it foster collaboration both internally and with external stakeholders (Fitzgerald, 2003). This definition builds upon and is synergistic with Huxham’s (1996a) concept of “collaborative advantage.” However, it differs from collaborative advantage in that it focuses on more than “the outputs of collaboration that could not have been achieved except through collaborating” (Huxham, 1996a, p. 15). It focuses on entire CEs, not just CE outputs. It includes all of the interpretations of collaborative advantage that Huxham describes, but it also encompasses collaborative disadvantages, failures, and even successes that may have intended or unintended detrimental impact on the CE itself, and/or one or more of its members and/or external stakeholders. Through the trans-disciplinary review of the CE literature, a cluster of recurrent themes became apparent that transcend disciplinary boundaries, theoretical perspectives, methodologies, levels of analysis, and types of collaborative structures. Each of these ten themes occurs in a dynamic, mutually influential relationship

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Table 1. Collaborative Capacity Framework. Constructa

Definition and Sub-Dimensions of Each Construct

Context

The Environments within which CEs are individually and/or collectively embedded, and the cultural, disciplinary, and theoretical Frameworks through which CEs and their Environments are construed. CE membership and how that membership is structured and governed. Includes formal (e.g. written bylaws) and informal (e.g. norms) structures. The extent or range of a CE and its resultant complexity. Dimensions include endogenous-exogenous (in relation to the focal CE). The strategic rationales, missions, visions, and/or “raisons d’etre” that are explicitly and/or implicitly expressed by the CE, its members, and/or key external stakeholders. Dimensions include voluntary-mandated, explicit-implicit, and utilitarian-visionary. The degree to which CE features, including structures, systems, processes, and/or member characteristics, are thought to complement, match, or “fit” one another, key external stakeholders, and Environments. Dimensions include extant-emergent, member-systemic, and differences-similarities. The entire spectrum of individual and collective behaviors that enhance both current collaboration and members’ capacity for future collaboration. Dimensions include extant-emergent, and implicit-explicit. The nature, strength, clarity, and unity of a CE’s identity and image among all levels of CE Membership and key external stakeholders; the CE’s level of autonomy; and boundaries that allow the CE to be distinguished from other entities (including its members) and surrounding Environments. All of the results or outcomes of collaboration. Consequences may have a symmetric or asymmetric impact on members, and may also influence the CEs external stakeholders and Environments. Dimensions include tangible-intangible, intended-unintended, constructive-destructive, narrow-broad. A person, thing, or event that precipitates a sudden, transformative CE change process. Dimensions include endogenous-exogenous. Processes of change within and among CE members, external stakeholders, and/or Environments that impact one or more aspects of the collaboration.

Composition Scope Core

Complementarity

Competence

Character

Consequences

Catalyst Course a Each

construct represents a generic theme that became apparent in the trans-disciplinary literature review. Each construct transcends disciplinary boundaries, theoretical perspectives, methodologies, levels of analysis, and types of collaborative structures.

with the others. These ten relational constructs appear to reflect fundamental aspects of CEs. They have been grouped together in Table 1 (Fitzgerald, 2003). Building on the suggestions of Osborn and Hagedoorn (1997), the CC Framework both incorporates and transcends clear-cut disciplinary perspectives, offering a multidimensional vision. It shares many of the underlying assumptions of the constructivist model of alliance anatomy and physiology set forth by Bouchikhi, de Rond, and Leroux:

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(1) Every CE may be viewed as a continually changing and unique configuration of the ten CC constructs; (2) Each construct may impact or be impacted by the others, either positively or negatively (hence the use of the term, “relational constructs”); and (3) The evolution of a CE involves convergence and divergence among the constructs propelled by various drivers of change (1998, p. 24). The CC Framework represents an effort to create an inclusive theoretical system that effectively balances “the essential trade-off between the competing virtues of scope and parsimony” (Parkhe, 1993, p. 246). As Parkhe notes related to one form of CE, the international joint venture (IJV), “a certain degree of complexity inheres in the phenomenon of IJVs; studying it at less than its level of complexity would represent, as Kaplan (1964) suggested, not oversimplification, but ‘undercomplication’ ” (p. 247). The ten constructs in the CC Framework are represented graphically in Fig. 1. The flow of time is represented from left to right by T0 , CE at T1 , and CE at T2 . Of course, given the complexity of CE phenomena, it is impossible to truly represent these constructs and their interactions in two dimensions. However, Fig. 1 illustrates the ten constructs and their relative interdependence. It tells a visual story. To help the reader better follow that story, it is expressed in narrative form in the following section.

The Generic Story of a Collaborative Entity In the beginning (represented by T0 in Fig. 1), the individuals, groups, and/or organizations in this CE’s story are independent of each other. Then something happens. The “lightening rod” of a Catalyst strikes in close proximity to these independent entities, and sets some of them on a Course of collaborative development toward a common Core. Within an organization, that Catalyst could be a decision to restructure and become a team-based organization, or to provide support for developing communities of practice. Nationally, it could take the form of a piece of legislation that alters the collaborative landscape. For example, China’s 1979 joint venture law catalyzed massive foreign direct investment specifically in the form of Sino-foreign joint ventures. It established a CE-promoting Environment at the national level with significant global impact (e.g. during the 1980s, more foreign joint ventures were formed in China than anywhere else in the world (Osland & Cavusgil, 1996, p. 106)). Thus, no matter what the form or scale of a CE might be, something catalyzes independent entities to move toward becoming that CE.

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Fig. 1. Collaborative Capacity Framework.

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A while later, after a short or long period of collaborative development, something emerges that looks like a CE (represented by T1 in Fig. 1). That CE is embedded within and interdependent with relevant Contexts in which it is immersed. Context includes Environments and Frameworks (Fitzgerald, 2003). For a joint venture, relevant Environments include national and international law, socio-political climates, national, regional, and local cultures, etc. For a team, Environments include its organizational culture, socio-technical systems that it interacts with, etc. Frameworks shape perceptions of how a CE is viewed (Osborn & Hagedoorn, 1997; Parkhe, 1993; Whetten, 1987). For example, when viewed through an economics Framework, the story of the formation of a joint venture is rather different than the story of the same entity when viewed through a population ecology Framework. Some CEs won’t even show up through certain Frameworks. For example, a community of practice is not likely to be observed or considered when viewed through a legal Framework. This newly emerging CE develops an increasing sense of Character that distinguishes it from its surrounding Contexts and helps its members feel like they belong to the CE (Hood et al., 1993; Van de Ven, 1976). At this point, the CE has a certain Composition of members (Huxham, 1996b; Osborn & Hagedoorn, 1997) that develop formal and informal governance structures (Child & Lu, 1997; D. Chisolm, 1989; Lawrence & Hardy, 1999). Informal structures (e.g. norms, social mores) typically come first (but not always) (Child et al., 1997), and some of those mechanisms eventually form the basis for more formal structures (e.g. corporate bylaws, team charters) (Dowling, 2003). When the members first come together, they bring varying levels of collaborative Competence that they’ve developed through previous experience (Inkpen & Currall, 1998; Khanna, 1998; Ring & Van de Ven, 1993). They also bring similarities and differences that seem to fit with or complement each other in various ways (Dussauge & Garrette, 1998) (Complementarity). As the members collaborate over time, they expand and deepen their individual and collective Competence, and may discover, elicit, and/or develop new forms of Complementarity (Doz, 1996). What holds them together, however, is their common Core: their vision, purpose, or “reason d’etre.” That Core may be primarily utilitarian (e.g. build an aircraft), visionary (world peace), or a combination of the two (Huxham, 1996a; Oliver, 1990). Core determines the Scope of the CE – its size, geographic reach, and intended duration and impact (Huxham, 1996a; Root, 1988). Scope distinguishes a co-located project team from a globally dispersed ongoing virtual team, or an intra-national product development joint venture from a global social change alliance (Khanna, 1998; Waddock, 1991).

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Every CE produces a variety of intended and unintended results or outcomes. Those Consequences may have a symmetric or asymmetric impact on the CE’s members, and may also influence the CE’s external stakeholders and Environments positively, negatively, or both (Bouchikhi et al., 1998; Dussauge & Garrette, 1998). The CE and its components each evolve and change through various Courses of development over time. For example, a team may grow through phases of forming, storming, norming, and performing (Tuckman, 1965), and an organization may progress through a lifecycle, or a dialectic process of development (Van de Ven & Poole, 1995). These processes of evolutionary development are punctuated periodically by revolutionary, Catalytic change – a CEO jumps ship, a technological innovation renders a market obsolete, a leader has a sudden calling to create a new global social change movement (e.g. Swing, 1998), or a new law or regulation creates potent market opportunities. This Catalytic change sets the CE on a new Course of collaborative development, and at some point in the future (represented by T2 in Fig. 1), the same CE may look rather different. Yet it is still embedded within a multi-dimensional and highly complex Context, has a Composition and Core that determine its Scope, expresses some level of Character, Complementarity and Competence, produces various sorts of Consequences that impact it, its members, external stakeholders and/or Environments; and is ultimately an amalgam of convergent and divergent processes.

The Ten Constructs of the Collaborative Capacity Framework The CC Framework reflects the tremendous complexity of collaborative relations in a new, generic language that transcends disciplines and levels of analysis. The above vignette of a CE’s story provides only the broadest brush strokes of the ten CC constructs and their interrelationships. These constructs and the literature that supports them are explored in more depth in the sections that follow (see also Fitzgerald, 2003, for a full articulation of the literature supporting the ten CC constructs).

Context Context, the first construct in the CC Framework, is represented in Fig. 1 as the amorphous boundary that surrounds the entire image. Context is comprised of the rich mixture of environments within which CEs are individually and/or collectively

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embedded (Environments), and the cultural, disciplinary, and theoretical frameworks through which CEs and their Environments are construed (Frameworks). Frameworks Each Framework draws attention to particular facets of a CE and its Environments. In doing so, it excludes from consideration far more information than it includes (Osborn & Hagedoorn, 1997). The Frameworks used to study CEs have a powerful impact on how they are construed, the questions that are asked, the language and terminology that are used, the nature and scope of the data that are obtained, and the conclusions that are drawn about them. Researchers have applied a diverse array of Frameworks to CEs (Parkhe, 1993). For example, Koza and Lewin mention seven disciplines that are used to study strategic alliances through the “gamut of methodologies and theoretical frameworks indigenous to those fields” (1998, p. 255). Other forms of CEs are construed through similarly diverse Frameworks (Whetten, 1987). To further complicate matters, each theoretical Framework may yield multiple variations. For example, the transaction cost economics Framework “has had a profound effect on analyses of interfirm collaboration,” yet “with all of [its] multiple interpretations . . ., it is quickly becoming more of a guiding metaphor than a tested set of propositions” (Osborn & Hagedoorn, 1997, p. 264). Researchers increasingly recognize the limitations of applying monoFrameworks to the rich complexity of CE pheonomena, and many are now engaged in multi-Framework research (e.g. Dickson & Weaver, 1997; Gulati, 1999; Osborn et al., 1998; Ramanathan et al., 1997; Van de Ven & Poole, 1995). However, this may be the first attempt to integrate Frameworks into a model as a fundamental construct. Weaving Frameworks into the Context of the CC Framework is intended to recognize, value, and help foster a multi-vocal science that transcends disciplines, theories, and levels of analysis within a broad, unifying framework. Environments A few macro-environmental features have transcended the “bewildering variety” (Emery & Trist, 1965, p. 24) of Frameworks and endured as explanations for collaborative phenomena. Those features include rapidly increasing environmental uncertainty and “turbulence” due to escalating interdependence, technological change and, more recently, globalization (e.g. Astley, 1984; Dickson & Weaver, 1997; Emery & Trist, 1965). The choice of Framework(s) impacts the nature of the Environment(s) perceived. For example, through some Frameworks (e.g. strategy), Environments tend to be conceived from the vantage point of single, focal organizations, while through others (e.g. population, social and/or human ecology) they are conceived

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at the level of populations (Astley, 1984). In fact, perspective is relevant throughout the CC Framework. Perspectives may be internal or external to a CE. The internal perspectives of CE members may vary with affiliation, centrality, and/or role. External perspectives may vary among parent firms, clients/customers, government agencies, other stakeholders, and/or research observers. Frameworks also differ significantly in the degree to which Environments are perceived as determining the life of organizations vs. the degree to which organizations are perceived as influencing or even creating their Environments (Astley, 1984). Thus to a certain extent, “Environments” are a product of the Frameworks through which they are conceived and through which they continue to co-evolve. Most CE research considers at least one Environmental element that is salient within the particular Framework(s) employed. A CE is defined, at least in part, by its Environments. In fact, it could be argued that a CE cannot be separated from its Environments (McKelvey, 1997), and that the two comprise a relational whole (Astley, 1984, p. 533). Further, the relationship between a CE and its Environments is not static. A CE changes over time, as do the Environments in which it is embedded. As they change, they influence each other in an ongoing process of co-evolution (Bouchikhi et al., 1998; Gulati, 1995, 1999; Koza & Lewin, 1998). In sum, Context refers to the Environments in which CEs are embedded and the Frameworks through which they and their Environments are construed. Frameworks, Environments and CEs influence and shape each other to varying degrees. They are interdependent and co-evolve. Context is socially constructed, malleable, and critical to CE life.

Catalyst For purposes of the CC framework, a Catalyst is a person, thing, or event that precipitates a sudden, transformative CE change process. The sudden, transformative impact of a Catalyst distinguishes it from the co-evolutionary change processes discussed briefly in the Context section above. It is indicative of “second-order change” (Van de Ven & Poole, 1995, p. 523, citing Watzlawick, Weakland & Fisch, 1974). The Catalyst construct is represented in Fig. 1 as the jagged lightening-like bolts that emerge from Context surrounding the CE and that radically impact the formation and change of the CE. Catalysts may be conceived through multiple Frameworks, and they may be exogenous (e.g. competitor announces breakthrough in same area (Bouchikhi et al., 1998, p. 32)), or endogenous (e.g. change of internal leadership (Gill & Butler, 1996; Shenkar, 1990) to focal CEs or populations of CEs at multiple levels

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of analysis (Gulati, 1999; Hackman, 1990, p. 481). Catalysts tend to be random and/or unpredictable; and although they are conceptualized as discrete events, they are often the byproduct of evolutionary change processes – just as a sudden earthquake is the result of a gradual buildup of pressure in a fault line. A CE itself may serve as a Catalyst for broader action, and certain CEs are specifically designed to do so. For example, Waddock and Post (1995) distinguish “catalytic alliances” as, “. . . temporary network organizations created to effect long-term social change through media-based campaign efforts to increase public awareness and commitment to action on social problems” (p. 951). Prototypical examples include Hands Across America and Partnership for a Drug-Free America. Other types of CEs may also serve as Catalysts. For example, bridging CEs “may also be the catalysts for the formation of networks focused on particular issues” (Brown, 1991, p. 815). Overall, Catalysts are implied in many studies and may play an important role in CE development. The construct transcends Frameworks and levels of analysis, and it provides a useful addition to a bridge-building process-oriented CE language.

Composition Composition refers to CE membership and how that membership is structured and governed, both formally and informally. In Fig. 1, Composition is represented both as the uppermost circle of the four central, overlapping circles (in the CET 1 image), and as the three starbursts containing the words “firms,” “groups,” and “individuals” in the foreground of those circles. The starbursts represent several categories of potential CE membership. Membership On its face, defining CE membership would appear to be straightforward. That may be true for contractually based CEs like equity joint ventures, or for clearly defined teams, but less so for other CE forms like communities of practice (Wenger, 1999) or bridging alliances (Lawrence & Hardy, 1999). Huxham notes that in defining the membership of a collaboration, “the distinction between internal and external stakeholders does not have to be clear-cut – a stakeholder can be a part of a collaboration for certain of its activities and not others” (1996b, p. 179). Thus, membership involves not only the dichotomous determination of “who’s in/out,” but also the level(s) of involvement of those who are determined to be “in” (Huxham, 1996b, p. 179; Osborn & Hagedoorn, 1997, p. 272). Member involvement may be comprehensive, spanning all CE activities ongoing, or it may be highly circumscribed. In communities of practice (Wenger et al.,

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2002) and some forms of alliances Members’ involvement levels may span a wide range. Determining “who’s in” is also a function of the Framework(s) employed and the perspective(s) of the person(s) employing them. Frameworks delimit categories of potential membership. Some Frameworks allow individuals, informal groups, and/or formal associations to be considered Members, while others confine membership to formal corporate entities. Those who are close to the heart of a CE may perceive and experience membership differently than those who are on its periphery or external to it. For example, “formal group membership status in a collaboration is often quickly determined, but psychological membership usually takes much time to develop” (Hood et al., 1993, p. 7). Even in “straightforward,” formally structured CEs, defining Membership may not be clear-cut. For example, in China the government “can function as policy-makers, buyers, suppliers, and partners, directly and indirectly affecting structure, strategy, and performance” (Osland & Cavusgil, 1996, p. 113). Thus the Chinese government might be seen not only as a dominant aspect of Context but also as an informal (and in some cases, formal) and highly influential Member of every Chinese CE. Further, contractual membership in a joint venture does not guarantee an experience of psychological membership, especially for workers with strong ties to their parent company and its culture (Shenkar, 1990). In sum, for purposes of the CC Framework, Membership includes the formal determination of “who’s in” a CE, their levels of involvement in it, and their informal psychological experience of Membership. Both formal and informal Membership may change over time. Membership changes may be ongoing in some forms of CEs and infrequent in others. Structure and Governance Governance and structure are interdependent. For example, according to GomesCasseres, “the structural form of an alliance is more properly seen as one of several ways of governing the relationship” (1993, p. 6). The traditional elements of intra-organizational structure – formalization, centralization, and complexity – may also be applied to the analysis of interorganizational structure (Van de Ven, 1976; Whetten, 1987). Structure may also be construed as a composite of formal and informal control mechanisms. Formal structural features of strategic alliances include, but are certainly not limited to, levels of equity/ownership and decision-making control (e.g. Child et al., 1997; Killing, 1988), vertical/horizontal orientation and structural interdependence (i.e. sequential, pooled, and/or reciprocal) of members with one another and with any parent(s) or other dominant organization(s) (Butler & Gill, 1997b, based on Thompson, 1967; Whetten, 1987), and integrating and/or

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monitoring mechanisms. In teams, formal structures include individual team charters (Dowling, 2003), policies, procedures, and formally articulated roles and responsibilities. Informal structural features of CEs include, but are certainly not limited to, Members’ levels of overall power and influence (Child et al., 1997), bargaining power (Gray & Yan, 1997, pp. 64–65), behavioral norms (Hackman, 1990, p. 10; Hood et al., 1993), and roles (Doz, 1996, p. 78). Although informal structure plays a vital role in all CEs, its influence surpasses that of formal structure in CEs that rank low on formalization (D. Chisolm, 1989; Lawrence & Hardy, 1999, p. 62). Thus, CE governance is comprised of an amalgam of formal and informal structural mechanisms. Structural Forms CE structural forms are diverse, far ranging, and to a certain degree, a function of their respective Frameworks. In the broadest sense, governance structures may be conceived of as voluntaristic (e.g. the managerial perspective), deterministic (e.g. the population ecology perspective), or some combination thereof (Oliver, 1990; Schopler, 1987; Whetten, 1987). Within business Frameworks, markets and hierarchies form the termini of what has become the most widely adopted typology of for-profit CE governance structures. Those structures are arranged on a continuum ranging from contracts and agreements (near markets) to equity relationships (near hierarchies) (e.g. Dickson & Weaver, 1997; Gomes-Casseres, 1993, p. 6; Gulati, 1995; Killing, 1988; Osborn & Hagedoorn, 1997, p. 264; Osborn et al., 1998, p. 621; Powell, 1990). Some non-business CE typologies are highly similar to their business cousins. For example, Whetten (1987) identified three generic types of CE coordination structures – mutual adjustment, alliance, and corporate – which mirror markets, networks and hierarchies respectively. Similarly, Waddock’s (1991) typology arranges three types of social partnership organizations (programmatic, federational, and systemic) and their affiliated structural characteristics along two dimensions ranging from low to high degrees of interdependence and scope. Programmatic partnerships are based on short-term contractual agreements (nearer to markets and similar to project teams), whereas federations establish either joint programs or joint organizations (nearer to hierarchies and similar to cross-functional coordination teams). However, Waddock’s typology diverges from the standard business typology in that systemic partnerships rank highest in interdependence yet exhibit temporary or ad hoc coalitional structures that seem to resemble networks more than hierarchies. That may be due to the interaction of interdependence with scope, which yields a three-dimensional model that may transcend the simpler market-network-hierarchy continuum.

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Some CE structural typologies transcend Frameworks and levels of analysis. For example, Oliver (1990, p. 251) includes three types of voluntary for-profit CEs that fall between markets and hierarchies, and three types of social service CEs that fall between mandated integration and agency autonomy. Gray (1996, p. 60) provides what may be the most comprehensive trans-Framework typology; it is based upon broad exogenous and endogenous incentives to collaborate. This does not exhaust the extensive literature on CE Membership, Structure, and Governance. Nor does it suggest an “ultimate” trans-Framework CE structural typology. Instead, it is intended to illustrate that Membership, Governance, and Structure are germane to CEs regardless of Frameworks, and to sketch the breadth and depth of the Composition construct. Relationship of Composition to Context Composition is strongly influenced by both Frameworks and Environments. Each Framework delimits the types of Members and Governance Structures that may be perceived through it. Environments impact CE structures both at formation and over time (e.g. Gray & Yan, 1997; Osborn et al., 1998). Finally, each CE’s Composition is, at least in part, also a function of its Core, its reason for being. That relationship is briefly discussed in the section on Core, which follows the next section on Scope.

Scope Scope (or “Compass,” Fitzgerald, 2003) refers to the extent or range of a CE and its resultant complexity. In Fig. 1, Scope is represented by the arrows that point to the boundary (Character) that distinguishes a CE from its Context. Graphically, the arrows refer to the extent or volume of “space” within a CE, reflected by the range of its boundaries. Waddock’s (1991) inclusion of scope as one of two dimensions in her typology of social partnerships may have presaged its importance for all CE forms. For example, Khanna argues that determining the scope of an alliance, while barely addressed in the literature, may be one of the most important tasks for alliance partners, and that “choice of scope affects alliance stability and alliance evolution” (1998, p. 341). Scope is multi-dimensional. For example, in a study of business joint ventures, Killing identifies five facets of alliance scope: (a) alliance objectives (an aspect of Core); (b) number of markets served; (c) number of products included; (d) number of business functions encompassed; and (e) intended alliance duration (1998,

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p. 58). At another level of analysis, these same five facets, slightly modified, are equally applicable to teams: (a) team mission and purpose (an aspect of Core); (b) number and variety of customers served; (c) number and variety of team tasks and deliverables; (d) number of organizational functions included; and (e) intended team duration. Other facets of Scope include: (a) the number of CE partners, and the nature (i.e. routine vs. non-routine) and frequency of their interaction (Killing, 1988); (b) the size of the overall CE and the relative sizes of its Members (Hackman, 1990, p. 32; Osland & Cavusgil, 1996); (c) the number of national environments and the diversity of cultural, political, economic, and legal systems that a CE is immersed in (Root, 1988; Shenkar, 1990, p. 83); (d) the range of membership categories included in the CE (Roehrig, 1994; Waddock, 1991; Waddock & Post, 1995); (e) the number, variety, and levels of sectors, domains, and/or societal institutions involved (R. Chisolm, 1998; Cummings, 1984; Roehrig, 1994; Waddock, 1991; Waddock & Post, 1995); and (f) the number, variety, levels and historical entrenchment of interconnected sets of social problems addressed by the CE (R. Chisolm, 1998; Van de Ven, 1976, p. 26; Waddock, 1991). Endogenous – Exogenous Most facets of Scope are endogenous to CEs (e.g. number and relative size of partners, nature and frequency of interaction). However, several are at least partially exogenous (e.g. number of markets/customers served, diversity of national/cultural/functional organizational environments) and one is temporal (intended duration). Although Scope is underemphasized in the literature, one or more of its dimensions is typically built into research designs as a byproduct of the nature and range of CE relationships considered. Complexity A CE’s complexity is a function of its Scope. Complexity tends to increase as Scope broadens. For example, Van de Ven (1976, p. 27) reasoned that as the number of members of a CE increases, the potential inter-linkages among them increase exponentially. That may also hold true for other facets of Scope, particularly when increased in combination. For example, a CE with two or more multi-nationals collaborating in a variety of global markets has a much broader Scope and far greater complexity than one involving two small intra-nationals engaged in a shortterm contract. Every CE, regardless of Context, has a multi-dimensional Scope and commensurate levels of complexity. Scope may be important in differentiating the applicability of CE theories and management prescriptions. It is a transFramework construct that is essential to comprehending and fully appreciating

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the tremendous diversity of CE phenomena. A CE’s Scope is a reflection of, and may be determined by, its Core.

Core Core is the fifth – and central – construct in the CC Framework. In Fig. 1, it is represented as the central, dominant circle of the four overlapping circles (in the CET 1 image). Core encompasses the visions, missions, strategic rationales, and/or “raisons d’etre” that are explicitly and/or implicitly expressed by the CE, its Members, and/or key external stakeholders. It is the “why” of the alliance anatomy model proposed by Bouchikhi et al. (1998). It unifies and orients a CE, and it lies at the heart of all CE forms. The construct transcends Frameworks and can help bridge the profit/non-profit and team/alliance divides. Dimensions of Core Like Composition, Core may be conceived of as being voluntaristic, deterministic, or some combination thereof. Thus a CE’s Core may be mandated by external entities (Raelin, 1980), or voluntarily generated by its Members. For example, the government may mandate the Core for a military or healthcare research and development collaboration, and an organization may mandate the Core for a team that it convenes. CE members may explicitly articulate their CE’s Core and/or implicitly express it through their behavior. Implicit Core includes Members’ covert, unexpressed and/or unconscious motivations and expectations (e.g. Doz, 1996, p. 67), as well as the construal of their motivations by researchers and other external observers. Explicit and Implicit Core may vary among Members. Implicit Core may also vary among observers and their Framework(s). Core may also range from Utilitarian to Visionary, from strategic intent to spiritual calling. Huxham (1996a) was perhaps the first to suggest the full instrumental/ideological spectrum of CE rationales. Utilitarian conceptions of Core dominate the CE literature (Huxham, 1996a). In fact, several of the most prominent alliance CE theoretical traditions are founded almost exclusively upon unique conceptualizations of utilitarian Core. These traditions include, but are not limited to: transaction cost economics, resource dependence, strategic behavior, and organizational learning (Lin, Yu & Seetoo, 1997; Osborn & Hagedoorn, 1997). These prominent forms of utilitarian Core are subsumed within Oliver’s (1990) five generic alliance rationales: asymmetry, reciprocity, efficiency, stability, and legitimacy. Reducing transaction costs falls under efficiency; controlling access to resources is one way to influence interorganizational asymmetry; strategic behavior also impacts asymmetry (i.e. barriers to entry, market power), and

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stability (i.e. reducing uncertainty); and organizational learning is an expression of reciprocity. A legitimacy Core is designed to enhance the image, visibility, reputation, etc. of a CE and its members. Two further facets of utilitarian Core do not fit as neatly within Oliver’s (1990) typology: exploitation of existing capabilities vs. exploration for new opportunities (Koza & Lewin, 1998). Visionary Core is comprised of unifying values and/or visions. Values may be emergent and implicit, or they may be consciously co-constructed and explicit. Visions are explicitly co-created. A CE with a predominantly utilitarian Core may also have an important visionary Core, such as an idealistic team or organizational mission, which influences the manner in which it executes its primary utilitarian objectives to some degree. These dimensions of Core – Mandated-Voluntary, Explicit-Implicit, UtilitarianVisionary – are not mutually exclusive; they may apply in a variety of combinations simultaneously and/or sequentially – especially when multiple Frameworks are employed. Further, a CE’s Core may be influenced by the Cores of entities external to it, as in the objectives of the parents of a joint venture, or in the influence of the values of center and peripheral organizations on “bridging” organizations in activist domains (Lawrence & Hardy, 1999). For example, Motorola is renowned for its ethical Core, which impacts its dealings with all of its partners, including joint ventures (Peach & Murrell, 2001). Relationship of Core to other CC Constructs Core plays a substantial role in determining CE Membership (Emery & Trist, 1965, p. 29), and structure (Koza & Lewin, 1998, p. 257; Lawrence & Hardy, 1999, p. 62). A mandated Core may specify CE members, whereas a voluntary Core serves to focus the range of potential members (e.g. to the individuals, groups, and/or organizations within a particular function, environmental niche, industry, or activist domain). Core also plays a substantial role in the determination of Scope (Huxham, 1996a, p. 13; Root, 1988). Typically, the more ambitious a CE’s Core, the greater its Scope. Overall, Core is a trans-Framework, multi-dimensional construct that lies at the heart of every CE. Its dimensions include, but are not limited to, VoluntaryMandated, Implicit-Explicit, and Utilitarian-Visionary. Several prominent CE theories are based upon distinct categories of utilitarian Core. Types of Utilitarian Core include, but are not limited to: asymmetry, efficiency, reciprocity, stability, legitimacy, exploitation, and exploration. Visionary Core is the glue that binds voluntary CE network forms and makes them viable entities. Core is intricately related to Context, Composition (membership and structure) and Scope, as well as to Complementarity and intended Consequences, discussed in the following sections. Its strong linkages to most of the other CC constructs also makes it the Core of this conceptual Framework.

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Complementarity Within the CC Framework, Complementarity is defined as the degree to which CE features, including structures, systems, processes, and/or Member characteristics, are thought to complement, match, or “fit” one another, key external stakeholders, and relevant Environments. In Fig. 1, Complementarity is represented as the left-hand circle of the four central, overlapping circles (in the CET 1 image). It is also represented by the synergistic nature of the shapes of the four overlapping circles within the CET 1 image, as well as of the similar geometric shapes of those same constructs within the CET 2 image. Similarity-Dissimilarity In the CE literature, “complementarity” typically refers to one or more complementary differences among CE Members. It is often contrasted with Members’ similarities or areas of overlap. However, some CEs are based upon complementary similarities (Dussauge & Garrette, 1998). Examples include oil and mineral exploration, and large real estate and R&D collaborations. Members of these CEs share a need to pool like resources to meet the enormous investment required, and to spread risks among more members (Contractor & Lorange, 1988, p. 19). Members’ similarities and/or differences may be construed as complementary, therefore Similarity-Dissimilarity forms the first dimension of Complementarity. Extant-Emergent forms a second, temporal dimension of Complementarity. First, CEs may be formed on the basis of the perceived Complementarity of potential Members’ extant assets, capabilities, etc. (i.e. those that they bring with them to the CE at its formation). However, unanticipated Complementarities may emerge during the actual process of Collaboration (Dyer & Singh, 1998). Extant Complementarities may strengthen or diminish over time as a function of Members’ learning, or of substantive changes in the CE’s Context and/or Core (Dussauge & Garrette, 1998). Emergent Complementarity may reflect latent Membership assets and capabilities that are discovered and called forth in response to a collective challenge, or it may be newly created as a byproduct of collaborative learning processes (Doz, 1996). Member-Systemic Business researchers have proposed, and to some extent investigated, the importance to CE success of Members’ Complementarity on a wide variety of Members’ characteristics (Bucklin & Sengupta, 1993; Li & Shenkar, 1997; Osland & Cavusgil, 1996; Park & Ungson, 1997; Shenkar, 1990; Tsang, 1995). Although the Complementarity construct has generally been limited to Member characteristics, it may also be extended to encompass the degree to which features of the CE itself

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are perceived to complement or “fit” one another and its external Environments (e.g. Osborn et al., 1998; Waddock, 1991). In the CC Framework, such “fit” among CE variables is referred to as Systemic Complementarity. Complementarity may be perceived within as well as among those variables. For example, Van de Ven and Poole identify four ideal-type change “motors,” and urge researchers to “consider the degree of complementarity among motors” (1995, p. 534). In addition to encompassing Member and Systemic levels, Complementarity applies to all types of CEs, ranging from teams (e.g. Hackman, 1990; Nemiro, 1996) to networks (e.g. Hertz, 1996). Thus Complementarity is a multi-faceted construct that transcends disciplines and levels of analysis. It incorporates the entire range of Member and Systemic, Extant and Emergent CE Similarities and Dissimilarities that are perceived to augment one another to the benefit of the CE and its Members. This significantly broadens the construct’s prevailing usage. Not all CE differences and similarities are complementary. Complementarity is discerned by way of Context, Core, and Composition. Context-Complementarity Relationship Within the realm of Context, perceptions of Complementarity are dependent upon Frameworks and Environments. Frameworks shape the forms of Complementarity that may be perceived. For example, “domain similarity” is salient within non-profit Frameworks (Van de Ven, 1976), whereas “customer-usage complementarity” is discerned within a marketing Framework (Dev et al., 1996). Environments impact Complementarity through their influence on Core and Composition. For example, Dussauge and Garrette (1998) note which alliance types tend to be favored by different industrial Environments. Their typology links Environments to Complementarity by way of Core and Composition. They observe that shared-supply alliances “are common in the automobile and computer industries” (p. 110), share a utilitarian efficiency Core (“in order to achieve greater economies of scale” (p. 109), and are similar “in terms of size, geographic presence, and competitive position” (p. 100). In contrast, “quasi-concentration alliances are found mainly in the aerospace and defense industries, where they account for 90% of all alliances” (p. 111). They share an efficiency Core based on creating and producing a common product that requires their contribution of similar assets and capabilities (p. 110). Composition-Complementarity Relationship Composition also impacts Complementarity. In fact, Governance Structure may determine the forms of Members that may be considered complementary. For example, a team or network cannot be considered for membership in a joint venture structure, no matter how complementary they may otherwise be.

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Core-Complementarity Relationship Core has perhaps the greatest influence on Complementarity. A new or expanded Core may generate a gap in capability, knowledge, and/or resources that cannot be satisfied internally. The specific nature of that Core will determine the particular kinds of partners and Member characteristics that would be considered complementary. Further, an expansive, visionary Core can help to reveal and/or generate Complementarity among potential CE Members who are otherwise unrelated, or even competitors, in other Contexts (Waddock & Post, 1995). Complementarity is generally considered to enhance collaborative capacity. However, its potential may only be realized in combination with relational Competence (Saxton, 1997, p. 449), a primary aspect of Competence as construed in this CC Framework, discussed next.

Competence Competence refers to the entire spectrum of individual and collective behaviors that enhance both current collaboration and Members’ capacity for future collaboration. It encompasses Members’ technical skills and abilities, but they are not its primary focus. Members’ technical/functional competence is a necessary but insufficient condition for successful collaboration. Behavioral skills and abilities that foster collaboration are essential. They comprise what may be thought of as “relational Competence,” which is the intended meaning of this construct within the CC Framework. Competence is represented in Fig. 1 as the right-hand circle of the four central, overlapping circles (in the CET 1 image). The literature on relational Competence is vast, and entire academic disciplines and streams of research fall within its domain. Facets of relational Competence include, but are not limited to, communication, conflict management, intercultural sensitivity and skill, leadership styles and processes, norms and informal structure, organizational learning, trust and relationship building behaviors (including commitment, reliability, equity, reciprocity, and flexibility), behaviors that enhance the experience of psychological Membership and CE affiliation and identification, and the provision of adequate resources to support the development of relational (in addition to functional) Competence. Many models of alliance performance are based almost exclusively on one or more of these facets of Competence (e.g. Olson & Singsuwan, 1997). Extant-Emergent Competence Like Complementarity, Competence may be Extant and/or Emergent. Prior experience with cooperative relationships is a form of Extant Competence. Such prior

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experience may lead to “the development of an ‘alliance capability.’ By the term alliance capability we refer to a firm’s ability to identify partners, initiate alliances, and engage in the ongoing management and possible restructuring and termination of these alliances” (Khanna, 1998).1 Individuals and entities that have developed Extant Competence may draw upon it (consciously and/or subconsciously) in every current and future CE that they engage in. In contrast, Emergent Competence refers to relationally supportive behaviors that Members develop during the process of their collaboration. Implicit-Explicit Competence CEs and their Members may or may not be consciously aware of their relational Competence. Thus Competence, like Core, may be implicit and/or explicit. Explicit Competence may extend beyond mere awareness and become consciously enacted or even codified or institutionalized behaviors. For example, a CE and/or its Members may establish formal structures for capturing and disseminating the learning obtained from their current and prior collaborative experiences. Informal Structure and Norms Although informal structure can be thought of as an aspect of Composition (as discussed above), it is also considered to be integral to Competence, because it is based upon individual and collective behaviors (and the internal psychological schemas that sustain them) that facilitate and/or impede successful collaboration. For example, D. Chisolm (1989) demonstrates the efficacy of informal social mechanisms in coordinating a highly complex public transit CE. He identifies many factors that facilitate the development of informal structure, including: (a) reciprocity, which is “a keystone of almost all societies, from the nearly prehistoric to the most modern and advanced” (p. 114); (b) habitualization (repeated interaction over time through both formal and informal channels); (c) exchange of personnel among Member organizations over time; (d) management’s support for the development of informal inter-Member relationships at all levels of personnel; (e) individuals’ personalities, attitudes, and formal organizational roles; and (f) “serendipitous propinquity,” which includes coincidental prior relational history in non-work settings, as well as chance meetings, co-involvements in community organizations, etc. (p. 135). These factors support the development of informal relationships, which serve to: Facilitate the exchange and acquisition of information essential to coordination through mutual adjustment. Personal trust developed through informal relationships acts as a lubricant for mutual adjustment. Informal conventions preclude some behaviors, establish commonly understood coordination procedures, legitimate the use of sanctions if those boundaries are crossed, and frequently define appropriate sanctions (D. Chisolm, 1989, p. 195).

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“Informal conventions” are commonly referred to as norms. Some, like reciprocity, are rooted in broader social systems while others are generated within a particular group. Dyer and Singh (1998) claim that such informal governance is a key source of CE competitive advantage. Thus informal mechanisms provide the social infrastructure necessary for the development of trust-based informal relationships and the capacity for organizational learning. Trust and Relationship Building Trust is a complex, multi-dimensional construct in and of itself with a variety of definitions, typologies, and construals. Parkhe (1993) argued that trust, reciprocity, opportunism, and forbearance are core constructs that “tap behavioral variables at the heart of voluntary interfirm cooperation” (p. 229). Parkhe’s four constructs have received considerable research attention primarily through the literature on trust in CEs, particularly joint ventures and other forms of strategic alliances. Inkpen and Currall (1998) summarize the literature on trust in joint ventures. They identify three primary Frameworks employed and their respective levels of analysis: trust as a psychological property (interpersonal level), social property (inter-firm, -group, and/or -personal level), and/or structural property (inter-firm level) (p. 4). They specify four facets of trust related behavior: “(1) communication and information exchange; (2) task coordination; (3) informal agreements; and (4) surveillance and monitoring” (Inkpen & Currall, 1998, p. 3). It is interesting to note that communication and information exchange are related to learning, and informal agreements and (to a certain extent) surveillance and monitoring are related to informal structure. Butler and Gill (1997a) argue that trust may be placed in people, formal rules and procedures (e.g. contracts), and/or institutions. They provide three further distinctions that apply to both personal and institutional (or impersonal) trust: Personal and impersonal trust can be seen in turn to consist of promissory, goodwill and competence components. Promissory based trust is the degree of confidence that a party can be relied upon to carry out a verbal or written promise (Rotter, 1967). Goodwill based trust is the degree of confidence that a party can be relied upon to engage in actions which benefit the other party or refrain from action which will disbenefit or damage the interests of the other party. This component of trust is closely related to the concept of forbearance. . . . Competence based trust is the degree of confidence that a party can be relied upon to have the knowledge, skills or expertise they claim or are believed to have (Sako, 1992; Butler & Gill, 1998, p. 3).

Thus the question is not simply how much trust is present, if any, but rather what types of trust are involved, what are the natures of the entities being trusted, by whom, and as construed through which Frameworks. Developing trust-based Competence may require behaviors (e.g. reciprocity, habitualization, forbearance) that build all forms of trust throughout the CE.

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Organizational Learning Learning is a primary purpose for many CEs. However, achieving learning objectives requires effective learning processes and the formal and informal systems that support those processes. Learning processes are vital to relational Competence, but they must operate in conjunction with other relationship building behaviors in order to enhance collaborative capacity. For example, a Member that excels at learning but behaves opportunistically is likely to foster termination, not collaboration. Like trust, organizational learning is a complex, multi-dimensional construct in and of itself with a variety of definitions and process models. Although the organizational learning Framework (OL) has primarily focused on intra-firm learning, in recent years CE learning processes have received increasing attention (Doz, 1996; Inkpen, 1997; Tiemessen et al., 1997). OL involves multiple forms of knowledge and learning (Tiemessen et al., 1997, p. 381), and it occurs through a variety of CE processes and facilitating mechanisms (Beeby & Booth, 1998; R. Chisolm, 1998; Doz, 1996; Levinson & Asahi, 1995). Dyer and Singh (1998) suggest that knowledge-sharing routines are one of four determinants of interorganizational competitive advantage. They distinguish two sub-processes of those routines. The first, partner-specific absorptive capacity, “is a function of: (1) the extent to which partners have developed overlapping knowledge bases; and (2) the extent to which partners have developed interaction routines that maximize the frequency and intensity of sociotechnical interactions” (Dyer & Singh, 1998, p. 665). The second involves Members’ implementation of formal and/or informal incentives “to encourage transparency and reciprocity and to discourage free riding” (p. 666). Overlapping knowledge bases may be construed as an expression of the availability of adequate resources, interaction routines are an expression of habitualization, and incentives may also be construed as expressions of Competence (e.g. informal incentives, Members’ commitment to OL) and Composition (e.g. contractual incentives as one facet of formal structure). In a further study of CE learning processes, Inkpen (1997) identifies four critical mechanisms that facilitate OL: “technology sharing, JV-parent interaction, personnel movement, and strategic integration” (p. 348). Mechanisms of technology sharing and JV-parent interaction involve regular meetings, site visits and tours which provide opportunities for habitualization, and strategic integration essentially refers to linking the CE’s Core to that of its parents. Thus a learning Core (learning as an explicit purpose or intention of the CE), commitment (another facet of Competence), adequate resources (redundancy), and behaviors that build informal structure (e.g. knowledge connections generated via habitualization, personnel movement) and trusting relationships (e.g. reciprocity,

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forbearance) together may provide the infrastructure that is needed to foster OL in CEs. This does not exhaust the possible categories and/or dimensions of Competence. It is intended to sketch the tremendous breadth and depth of this construct, and to demonstrate that at least some of its key facets are intricately interrelated, even though they are frequently treated independently. It is meant to demonstrate that Competence transcends Framework(s) and level(s) of analysis, and that it is vital to the development of collaborative capacity. Context-Competence Relationship Competence is Context dependent. Frameworks employed may limit the forms of relational Competence considered relevant and/or important, and Environments may support or suppress the development of one or more facets of Competence. For example, the interplay of members’ national, occupational, and organizational cultural Environments may affect CE learning capacity (Levinson & Asahi, 1995). Similarly, sectoral cultures affect norms for group behavior (Hood et al., 1993, p. 8). Environments also impact trust and relationship building processes (e.g. Leung et al., 1995), as well as members’ perceptions and assessments of Competence in themselves, their partners, and key external stakeholders (Olson & Singsuwan, 1997). Core-Competence Relationship Core also impacts various facets of Competence. For example, a CE with a strong learning Core is likely to ensure that its formal and informal systems support learning processes (Inkpen, 1997, p. 342). A Visionary Core helps build psychological membership and strengthens members’ affiliation and identification with their CE. Further, Hood et al. note that “the amount of shared vision and goals in the collaboration will affect trust, leadership, and conflict” (1993, p. 12). Composition-Competence Relationship The relationship between Composition and Competence is reciprocal in nature. Composition influences Competence through the nature of the Members and Governance Structures that are chosen for the CE. Members’ Extant Competence may influence the Members that they choose to partner with, the Governance Structures that they choose to implement together (Inkpen & Currall, 1998, p. 11; Ring & Van de Ven, 1993), and the ways in which they relate to and evolve those structures over time. Members bring their respective levels of extant Competence to their CE at formation, thereby providing a base platform for the development of emergent Competence.

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However, the governance structures that Members employ may encourage or discourage the development of emergent Competence. For example, overspecification of and reliance upon formal contracts and governance mechanisms may inhibit the development of trust. Cross-cultural Environments may exacerbate that situation. To illustrate, Child et al. (1997) advised that legal contracts are very difficult to enforce in China, and that the Chinese tend to view undue reliance on them – and efforts to enforce them – as offensive, representing a lack of trust that may “jeopardize the good relationships and trust on which the venture’s success depends” (p. 218). Structure may also facilitate or hinder OL (Levinson & Asahi, 1995, p. 56). Scope-Competence Relationship Scope and Competence are also intricately interrelated, although little has been written about this relationship. Different levels of Scope may require different levels of Competence. For example, extant Competence developed at finite, dyadic, intranational levels of Scope may not be sufficient for successful engagement in a multi-partner, multi-market, ongoing global alliance. Similarly, a team member who has only worked in a co-located, face-to-face project team may not have adequate extant Competence to engage effectively in an ongoing, globally multi-cultural, virtual team. Competence may need to develop through incremental collaborations of increasing Scope over time. On the other hand, perceived changes in relational Competence may prompt members to broaden or narrow the Scope of their collaboration (Inkpen & Currall, 1998). Competence is not static but changes over time. It involves processes of building and sustaining norms and informal structures, trusting relationships and learning capacity (at least) (Doz, 1996; Gill & Butler, 1996; Inkpen & Currall, 1998; Khanna, 1997; Ring & Van de Ven, 1994). In sum, relational Competence is an intricately interdependent, multidimensional construct. Given the predominance of voluntaristic managerial Frameworks, the many facets of relational Competence are frequently construed as independent of other key aspects of collaborative entities. However, Competence influences and is influenced by the other CC constructs. It is not independent of them.

Character Character, the eighth of the ten CC Framework constructs, is represented in Fig. 1 as an amorphous line that bounds the CE and distinguishes it from its surrounding Context. Character refers to the nature, strength, clarity, and unity of

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a CE’s identity and image among all levels of CE Membership and key external stakeholders. It also includes the CE’s level of autonomy. Identity reflects the boundaries that allow the CE to be distinguished from other entities (including its Members) and surrounding Environments. Those boundaries are largely perceptual, supported by legal documents, physical structures, virtual locations, and/or other cultural artifacts. Why largely perceptual? Simply incorporating as a business, or establishing a website, or producing a product, does not equate to establishing the identity of a CE. Without a certain level of collective perception of the CE as an entity, it does not have much in the way of Character, no matter how many physical manifestations it may generate or acquire. The consideration of boundaries at the group-as-a-whole level of analysis is important in assessing collaborative efforts because the relationship of the group or system to its external environment is critical (Alderfer, 1976). Boundaries are permeable to a greater or lesser degree, thus allowing more or less interaction with the environment. The boundary of a group is an abstraction, referring to both observable and subjective gauges (Hood et al., 1993, p. 7). Character is a subtle construct that is related to the domains of group theory and development (for fostering Character internally) (e.g. Hood et al., 1993), and advertising and public relations (for fostering Character externally). Van de Ven’s (1976) portrayal of the ability of an interorganizational system to act as a unit captures the essence of CE identity: The social structure among organizations in a social system is such that the system can act as a unit. This implies that many activities in an IR [CE] cannot be explained simply by analyzing the behavior of member organizations. Collective events arise out of the actions of the social system and are formally a property of the IR itself (9). Warren, et al. observe that: ‘one can describe and analyze as a single system of inter-action any group of organizations whose properties may differ from those of the interacting organizations themselves and cannot be reduced to properties of these individual organizations’ (42, pp. 54–55) (Van de Ven, 1976, p. 75).

Thus identity is a function of the ability to distinguish the actions and properties of a CE from those of its Members and entities external to it. This begs the question, whose ability to distinguish? A CE may be a research fabrication, distinguished only by academic observers (e.g. some networks). Those close to the heart of a CE (e.g. convenors, top management, social entrepreneurs) may view its identify differently from those who are at its periphery or external to it. Thus within the CC Framework, Character encompasses the entire range of perspectives on CE identity and image. Autonomy reflects a CE’s ability to act independently of its key external stakeholders and dominant Members. Recent studies suggest the importance of IJV autonomy to performance and trust-building (e.g. Gill & Butler, 1996;

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Robins, Tallman & Fladmoe-Lindquist, 1998). Character applies to all forms of CEs, including teams and networks. For example, teams are: real groups. That is, they are intact social systems, complete with boundaries, interdependence among members, and differentiated member roles (Alderfer, 1977). It is possible to reliably distinguish members of real groups from nonmembers – even if members do not have regular face-to-face interaction and even if membership changes frequently (Hackman, 1990, p. 4).

At the level of networks, Waddock and Post state that catalytic alliances “possess a ‘corporate identity’ (Aldrich & Whetten, 1981)” (1995, p. 952), and Hertz observes that a network may develop a common image (1996, p. 122). Relationships with other CC Constructs Character is dependent on Context, in that Frameworks delimit the forms of CEs that may be construed through them. It is partially determined by Composition, in that Members and Governance Structures help to define CE boundaries. Scope influences the degree of recognition and impact of a CE’s identity and image (e.g. local, national, global). Core establishes the basis for the emergence of Character by defining the CE’s “raison d’etre,” which in turn shapes its Composition and Scope. Aspects of Competence – for example, behaviors that foster the experience of psychological Membership and CE affiliation and identification – serve to strengthen, clarify, and unify a CE’s Character. A CE’s Consequences may also impact its Character, positively or negatively. For example, a research team’s major scientific breakthrough increases its prominence not only within its organizational context, but also nationally or even globally, an IJVs success prompts its parents to give it greater autonomy, or a CE is forced to surrender autonomy to regulators and/or parent entities following misconduct by its leaders. Finally, Character is not static but changes over time, thereby linking it to Course.

Consequences Consequences include all of the results or outcomes of collaboration. They may be tangible/intangible, intended/unintended, constructive/destructive, and narrow/broad. They may have a symmetric or asymmetric impact on Members, and they may influence not only the CE and its Members, but also the CE’s suppliers, customers/clients, other external stakeholders, and Environments. In Fig. 1, a CE’s Consequences are represented as fluid, curved lines that emanate from the CE and that point toward the CE at a later time, and/or to its surrounding Context, to reflect the various impacts that a CE may have. This

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construct was added to the CC Framework thanks to Bouchikhi et al.’s (1998) insight that the outcomes of collaboration affect the CE and its Environments, and that they therefore should be treated not simply as a measure of CE performance, but rather as an integral part of a constructivist model of inter-entity collaboration. Dussauge and Garrette (1998) identify three categories of Consequences in business CE’s that impact: (a) alliance evolution; (b) the strategic consequences for each Member; and (c) market competition and industry structure. Potential evolutionary Consequences include “natural” vs. premature termination, extension beyond original timeframe, continuation by one partner, or takeover. Potential strategic Consequences include: (a) Members’ symmetrical and/or asymmetrical acquisition of new capabilities (i.e. learning); (b) mutual specialization as Members “reduce and focus their portfolio of skills” (Dussauge & Garrette, 1998, p. 109); or (c) no changes in Members’ respective capabilities or business scope. Potential impacts on competition include increases, decreases, or no changes in the number and diversity of competing products and firms. Tangible-Intangible Consequences Bouchikhi et al. observe that “outcomes can be tangible (e.g. milestones achieved) or perceptual (e.g. a good working relationship)” (1998, p. 28). Tangible CE Consequences may include various measures of financial performance, project completion, and/or the successful joint production of products, services, programs, and/or agreements. Intangible CE Consequences may include perceived effectiveness, aspects of relationship quality, and increases in Extant Competence and Complementarity. The intangible process of collaboration may be as important as any Tangible Consequences (e.g. Huxham, 1996b; Waddock, 1991). Constructive-Destructive Consequences Consequences may also be considered to be Constructive and/or Destructive, and those perceptions may vary according to level of analysis and perspective. Perceived effectiveness is commonly construed as a Constructive Consequence of both business CEs (e.g. Bucklin & Sengupta, 1993) and human service/social problem-solving CEs (e.g. Hood et al., 1993; Van de Ven, 1976). The CE literature tends to be biased toward the beneficial Consequences of collaboration (Whetten, 1987). However, some researchers have also drawn attention to potentially destructive, generally unintended Consequences of collaboration (Bouchikhi et al., 1998; Waddock, 1991). For example, Whetten details “some of the most common dysfunctional consequences of coordination” (p. 248) within the Context of local public-service-delivery CEs: (a) reductions in the ability to adapt to environmental changes as a result of increasing interconnectedness among Members; (b) reductions in CE program innovation as a result of political

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bargaining among Members; (c) reductions in the quality of services provided throughout the CE as redundancies within it are eliminated; and (d) “increased expenditures for boundary-spanning personnel, reduced internal decision-making autonomy, and increased conflict” (1987, p. 250). Context-Consequences Relationship The relationship between Consequences and the other CC constructs is reciprocal. Although the impact of those constructs on Consequences may be self-evident, Consequences’ impact on them may be less so. For example, every entity has an impact on its Environment(s) (Astley & Fombrun, 1983, p. 585). Although that impact may be neglible, it isn’t always (e.g. Bouchikhi et al., 1998). A CE’s impact on its Environments may be purposeful, accidental, or both. In fact, the “raison d’etre” for some CEs is to influence their Environments (Schopler, 1987, p. 705). Composition-Consequences Relationship Similarly, although Members and Governance Structures clearly affect Consequences (Dussauge & Garrette, 1998), Consequences may also influence Composition. For example, the early success of a joint venture – a Consequence of its activity – may “create a self-sealing effect contributing to the perpetuation of the initial structure . . . Thus, a dynamic equilibrium is established within joint ventures that are experiencing early success” (Gray & Yan, 1997, pp. 79–80). Inpken and Currall (1998) note that the level of trust, which may be thought of as a Consequence, influences governance structures. In addition, at least two of the Consequences identified by Dussauge and Garrette (1998) impact Membership: continuation by one partner, and takeover. Core-Consequences Relationship A CE’s Core defines its Intended Consequences. Achievement of finite Intended Consequences (e.g. produce a specific joint product) may result in an intended termination of the CE, or the creation of a new or expanded Core that establishes a new set of Intended Consequences. Contrary to traditional population ecology Frameworks, such an intended termination would indicate success rather than failure (Osborn & Hagedoorn, 1997, p. 267, citing Gomes-Casseres, 1987). In addition, a CE’s Intended Consequences may change over time as its Core evolves (e.g. Hood et al., 1993, p. 10). Complementarity, Competence, and even Scope clearly have an impact on Consequences, but the reverse may also be true. For example, Consequences may influence Scope (e.g. increases in trust may lead to increases in CE scope,

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Inkpen & Currall, 1998), Complementarity (e.g. Complementarity may change as a function of Members’ asymmetrical acquisition of skills, Dussauge & Garrette, 1998), and trust-based Competence. For example, Inkpen and Currall note that, “although it has generally been argued that trust leads to performance (e.g. Harrigan, 1986; Saxton, 1997), the argument that performance leads to trust has merit as well. Yan and Gray (1994) suggested that performance might have a feedback effect on trust” (1998, p. 14). Consequences may also catalyze changes in the CE, its Members and/or Environments. For example, Gomes-Casseres notes that, “frequently, alliance change is motivated by developments set in motion by the alliance itself” (1993). In sum, every CE has Consequences that may range from intended, tangible, constructive, and/or broad, to unintended, intangible, destructive, and/or narrow. Consequences are more than mere indicators of CE performance. They may impact CE Context, Composition, Scope, Core, Complementarity, Competence, and Course.

Course Course is the tenth and final construct in the CC Framework. It is represented in Fig. 1 by the strong, curved lines that connect the three time points in the diagram (i.e. T0 , T1 , T2 ). Course encompasses all of the processes of change both within and among the CE, its Members, external stakeholders, and/or Environments that impact the collaboration at one or more levels. Course sets the entire CC Framework in motion over time. The processual nature of the other nine CC constructs and their interrelationships have been highlighted throughout this paper. However, the nature of change processes themselves are an important and separate focus of CE research. Course is therefore presented as a distinct construct so as to elucidate diverse conceptions of CE change processes and integrate them fully into the CC Framework. Process Theories Based upon an extensive review and analysis of the literature on organizational change processes, Van de Ven and Poole (1995) identified four ideal-type process theories that they arrange along two dimensions: prescribed/constructive, which is essentially the mandatory/voluntary distinction, and single/multiple entities, which differentiates theoretical families according to their intended levels of analysis. Prescribed theories include life cycle (at the level of single entities), and evolution (at the level of multiple entities). Constructive theories include teleology

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at the level of single entities, and dialectic at the level of multiple entities. Teleological theory is “the most common explanation of development in the management literature” (Van de Ven & Poole, 1995, p. 515). Teleological theory assumes that an entity is “purposeful and adaptive; by itself or in interaction with others, the entity constructs an envisioned end state, takes action to reach it, and monitors the progress” (p. 516). These researchers highlight the complex interplay of temporal processes. For example, “different influences may be acting simultaneously on different parts of the organization, each imparting its own particular momentum to the developmental process. In some cases, more than one change motor may influence development and change” (Van de Ven & Poole, 1995, p. 526). The researchers conclude by illustrating possible interdependent combinations of two, three, and all four change motors, further enriching the theoretical pallette. For example, “gradual accounts of goal implementation actually combine two of the ideal types, teleological theory and life-cycle theory, to form a composite model” (Van de Ven & Poole, 1995, p. 523). Catalysts tend to be random and/or unpredictable (i.e. constructive mode), and although they are conceptualized as discrete events, they are often the product or byproduct of evolutionary change processes (i.e. prescribed mode). Thus Catalysts represent a composite model. Similarly, Doz (1996) integrates evolutionary and teleological processes in his model of learning in strategic alliances. Ring (1997) offers a CE process model comprised of cycles of sensemaking, understanding, and committing. Based on longitudinal case studies, he suggests five potential process patterns based upon varying configurations of cultural and organizational Context, and Extant Competence (i.e. new collaboration within an existing CE, new CE rooted in a pre-existing web of relationships). Relationships with other CC Constructs Course is dependent upon Frameworks and Environments. As Van de Ven and Poole (1995, p. 514) clearly demonstrate, Frameworks shape and limit conceptions of CE processes. CE change processes are also clearly interrelated with those of their Environments (Koza & Lewin, 1998, p. 257; Whetten, 1987, p. 242). As a CE’s Scope and resultant complexity increase, the likelihood that multiple change motors will be in motion simultaneously within it also increases. In addition, each Member, nation, sector, industry, etc. included in the CE may have a different “default” change motor. For example, a government sector CE Member is likely to employ a significantly different change motor (or composite of motors) than a market-driven corporate Member. In reality Course is inseparable from the other CC constructs; it is an integral part of them and the entire Framework.

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Summarizing the CC Framework The CC Framework makes plain the tremendous complexities – and similarities – among collaborative relations. Regardless of the Framework(s) and/or level(s) of analysis applied, every CE: (a) is embedded within a multi-dimensional Context; (b) has a Composition and Core that determine its Scope; (c) expresses some level of Character, Complementarity and Competence; (d) produces various sorts of Consequences that impact it, its Members, external stakeholders and/or Environments; and (e) is ultimately an amalgam of interdependent convergent and divergent processes. As noted previously, Fig. 1 pictorially represents the ten constructs in the CC Framework. Of course, given the tremendous complexity of CE phenomena, it is impossible to truly represent these constructs and their interrelationships in two dimensions. It would take multiple dimensions to express more completely. For example, Fig. 1 does not show Course occurring within each construct, and among the constructs, as it does. It does not illustrate Catalysts that are endogenous to the CE. It does not illustrate gradual change processes, which are the norm, and it seems to indicate that Course is only prompted by Catalytic events, which is not the intention. Finally, it cannot express the multi-faceted nature of each of the constructs that comprise the Framework. However, it illustrates broad relationships and their relative interdependence, with Core clearly at the heart of the CE. It sets the CE within a changing Contextual frame, and shows Consequences’ potential impact on Context and the CE itself over time.

Applying the CC Framework to Multi-Level Collaborative Phenomena The CC Framework provides a bridge-building language to help facilitate inter-disciplinary, multi-dimensional dialogue, research, and practice regarding collaborative entities. The ten “relational constructs” that comprise the CC Framework reflect fundamental structural dimensions of – or domains of inquiry into – CEs. Every CE is a continually changing and unique configuration of these structural dimensions. Each dimension may affect and/or be affected by the others, either positively or negatively. Table 2 lists examples of these ten structural dimensions at the level of teams, organizations, and alliances. In applications where the scale of the inquiry warrants, it may be beneficial to explore the entire CC Framework. For example, Fitzgerald (2003) applied all ten dimensions of the CC Framework and their sub-facets in participatory action

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Table 2. Examples of Ten Dimensions of Collaboration at Multiple Levels of Analysis. Structural Dimensions of Collaborationa

Definitions and Sub-Facets

1. Context

Environments: External to the CE that affect it.

2. Composition

Frameworks: Cultural, theoretical, and/or philosophical “lenses” that the CE is being viewed through (e.g. AI). CE membership, and how that membership is structured and governed, includes:

Formal structures – Informal structures –

4. Scope

The CE’s visions, missions, “raisons d’etre.” May be voluntary or mandated, utilitarian and/or visionary, and explicit (e.g. words) and/or implicit (e.g. behavior). Extent or range of the CE’s focus and activities physically, geographically, temporally, and conceptually.

Teams

Organizations

Alliances

Organizational culture Tavistock, NTL, Social psychology

Industry

Government regulations Globalization, eCommerce

Individuals as team members

Team design Team norms Team’s mission often mandated, in part, by the org’n. Short-term, one-site project team

Corporate law, organization theory Employees, owners, contract workers, outsourced vendors Bylaws Organization culture Newman’s Own: Utilitarian & visionary core Multi-national corporation

Organizations, individuals, associations

Contracts Non-contractual inputs URI – visionary core, charter = explicit County-wide development association

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3. Core

Examples

6. Competence

7. Character

8. Consequences

9. Catalyst

10. Course

How well do the CE’s people and structural features complement, match, or “fit” one another, key external stakeholders, and environments. Entire spectrum of individual and collective behaviors that enhance both current collaboration and members’ capacity for future collaboration. Nature, strength, clarity, and unity of a CE’s identity and image among all levels of CE Membership and key external stakeholders; and boundaries that distinguish the CE from other entities (including its members) and environments. All of the results or outcomes of collaboration. May be tangible and/or intangible, intended and/or unintended, constructive and/or destructive, narrow and/or broad. A person, thing, or event that precipitates a sudden, transformative CE change process. May originate from within the CE, or externally. CE change processes that affect one or more aspects of the collaboration.

Team members’ diversity, skills, knowledge. Trust-building, leadership sharing, group goal-setting Member cohesion, identification with group, level of autonomy Quality improvements, products, feelings Reorganization (external), leader changes (internal) Forming, norming, storming, etc.

Strategy with competitive environment. Information sharing, profit sharing, organiz’l learning Branding, corporate image, employees’ sense of affiliation and ownership Products, services, environmental impact, profit/loss

Joint venture partners’ goals and structures. Reciprocity, forbearance, voluntary inputs

Leadership change (internal), new competitor (external) Organizational life cycle

China joint venture law (external)

Joint venture physically separate from parent companies

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Technology transfer, mutual specialization

Metaphorical: a dance, play, etc.

a Each structural dimension of collaboration represents a generic theme that became apparent in the trans-disciplinary literature review. Each transcends

disciplinary boundaries, theoretical perspectives, methodologies, levels of analysis, and types of collaborative structures.

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research with a global social change alliance, the United Religions Initiative (URI), that was in the process of launching a leading-edge “chaordic” design (Durrance, 1997; Hock, 1998). The result is a rich, holistic picture of interfaith collaboration in eight groups on four continents. The CC Framework facilitated that through both qualitative and quantitative analyses. Further, the research proved to be generative for participants at multiple levels: for individual participants, participating groups (which ranged from informal, non-incorporated groups, to local, regional, and national level non-profit organizations), some non-participant members, and regional and global support staff. Application of the CC Framework through inquiry and analysis made clear two distinct clusters among the eight groups that would have been difficult if not impossible to discern otherwise. At the cross-cluster analytic level, it surprisingly facilitated the discovery of potential synergies among the levels of analysis. Finally, it yielded practical design insights that have helped provide a better understanding and appreciation of the diversity of types of URI “cooperation circles,” with an extensive list of practical suggestions for application based on the ten constructs of the CC Framework. The distinction of the two clusters (outer-focused, formally structured, and inner-focused, informally structured) has since resonated with the practical experience people in other URI cooperation circles in the U.S. and other parts of the world. Many people in the URI have commented on how helpful the distinction has been for them.

Implications for Research and Practice Not all research warrants that level of depth of exploration, however. The CC Framework is versatile and highly adaptable, and does not need to be applied in its entirety. Indeed, most collaboration research focuses on one, two, or three of the ten constructs and/or relationships among them, albeit in the language and conceptual terrain of a particular Framework. What the CC Framework makes possible, however, is the inclusion of multiple forms of Collaborative Entities in the same study. To make this easier to imagine, examples of each of the ten CC constructs are listed in Table 2 at three levels of analysis: teams, organizations, and alliances. This holds exciting promise for inter-disciplinary research at multiple levels of analysis. However, it also holds promise for working in complex organizational systems, for example where teams, communities of practice, joint ventures, value chains, and other forms of alliances and networks are all vital to the life and success of a multi-national corporation – of a comprehensively collaborative entity. Design principles might be elicited that hold true across multiple forms

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of CEs associated with the same parent organization, thereby enhancing that organization’s ability to foster collaborative capacity systemically. For many years now, scholars have encouraged organizations to break down the hardened silos of functional organizational structures, and to develop crossfunctional teams and other integrative mechanisms to enhance organizational flexibility, responsiveness, learning, innovation, and performance. Perhaps the time has come for applying these same principles to our disciplinary and theoretical silos in the pursuit of more effective, integrative mechanisms for making sense of the complexity of CEs, and building collaborative capacity.

NOTE 1. This sense of alliance capability mirrors the concept of “Alliance Ability” created by the author with three colleagues (Frank Martin, Peter Szczensny, and Rehan ul-Haq) during a brainstorming session at the Fifth International Conference on Multi-Organizational Partnerships and Cooperative Strategies, Balliol College, Oxford University, July 7, 1998. It provided the first iteration of what has since evolved into the CC Framework. Alliance Ability was framed within a voluntaristic, managerial Framework, and focused on the skills and abilities of individuals and firms that were thought to be necessary for successful collaboration. In contrast, Collaborative Capacity is systemically focused, and it includes Alliance Ability within the domain of relational Competence.

ACKNOWLEDGMENTS This chapter is based on the author’s doctoral dissertation (Fitzgerald, 2003). Committee chair Jill E. Nemiro, California State Polytech University, Pomona provided helpful feedback on a first draft of this chapter, as well ongoing guidance and constructive input during the research process. In addition, committee members Kenneth L. Murrell, University of West Florida, and Ronald E. Fry, Case Western Reserve University contributed generative and provocative feedback on both the proposal and the final dissertation.

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LEADING COMPLEX COLLABORATION IN NETWORK ORGANIZATIONS: A MULTIDISCIPLINARY APPROACH Karen L. Higgins and Joseph A. Maciariello ABSTRACT Executives of network organizations seek to combine core competencies and talents of individual firms, along the various links of the value chain for a given project. These firms are brought together in alignment for the purpose of providing organizations a competitive advantage. Using multiple examples as well as results from an extensive research project, this chapter introduces a multidisciplinary model for leading network organizations. The model is informed by theoretical and empirical research and by executive practice. It includes consideration of an organization’s internal interactions as well as its interactions with the environment and with the external organizations within its network. The chapter provides leaders a set of four imperatives for achieving effective collaboration within networks.

Complex Collaboration: Building the Capabilities for Working Across Boundaries Advances in Interdisciplinary Studies of Work Teams, Volume 10, 203–241 Copyright © 2004 by Elsevier Ltd. All rights of reproduction in any form reserved ISSN: 1572-0977/doi:10.1016/S1572-0977(04)10008-3

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INTRODUCTION No man is an island, entire of itself; every man is a piece of the continent, a part of the main . . . (Donne, 1624, p. 392).

Little did 17th century man know just how “connected” our world would become four centuries later. However, even in the 1600s, John Donne eloquently recognized the relevance and “naturalness” of interdependence. What was not anticipated at the time was an explosion in technology that would simultaneously create a need to coordinate activities among organizations and facilitate our ability to be networked together in collaborative work. Remarkable change in our environment, much of which has been driven by advances in knowledge and technology, seems to have come about much like it did for the frog in the old adage. The unsuspecting frog lands in a pot of cold water sitting on a stove, but because the water heats gradually, the frog doesn’t realize it is boiling until it is too late to respond. When we lift our heads above our everyday tasks, we see a magnitude and speed of change far greater than we may have imagined. The challenge for our businesses to be successful hinges upon their ability to react more quickly to change than did the frog. Our leaders must develop strategies and new organizational forms to more readily achieve success amidst technology explosions, globalization, high degrees of interdependence, and an increasing need for collaboration.

TRENDS AND IMPLICATIONS In today’s increasingly interconnected world, an organization must be prepared to react differently than in the past. Developing successful strategies for today’s organizations requires a deeper awareness of trends and implications of those trends in our environment. Understanding the impact of information technology, advances in knowledge, globalization, systems’ thinking, and network organizational structures is critical to achieving success for today’s organizations.

Information Technology Even a few short decades ago, short of science fiction, we could not have imagined any technology that would so drastically increase the speed and accuracy of mathematical calculations and provide the foundation for the Information Revolution. Before the 1940s, a complex calculation took 15–30 seconds on the slide rule – the

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basics of which were invented in the 1600s. Even in 1946 when the first “computer,” the ENIAC [Electronic Numerical Integrator and Calculator], was developed, we could not have imagined that computations previously done at a turtle’s pace, could be done at teraops speeds of trillions of calculations per second. Nor could we have conceived that computing power previously costing millions of dollars would be so affordable that individuals would use their own computers to communicate and access information across the world at practically zero cost. Yet today we live in a web of interconnectivity, with data flying in invisible waves all around us. We only have to sit briefly at our computers to order a book, check the stock market in Japan or see a minutes-old image of an international incident occurring halfway across the globe. Such technology advances have created an explosive expansion of information exchange, often called Information Technology or IT. IT is not only enabling, but is actually driving change at an increasing pace. Even in the 1980s before the World Wide Web, electronic mail grew exponentially from less than 1/2 million to over 19 million mailboxes (Berry, 1993). IT has become the life-blood of the new economy; it is “. . . the DNA of the Information Age. . . . The underlying trends in Information Technology . . . are coalescing to create orders of magnitude increases in the ability of human beings to operate in the information domain. . . . Responsiveness and agility are fast becoming the critical attributes for organizations hoping to survive and prosper in the Information Age” (Alberts et al., 1999, pp. 15, 21).

Globalization Advances in information technology have changed the very nature of our social structure. In the words of Friedman (1999, 2000), “The world has become an increasingly interwoven place, and today, whether you are a company or a country, your threats and opportunities increasingly derive from who you are connected to . . . [Globalization is the] . . . integration of markets, nation-states and technologies to a degree never witnessed before . . .” (p. 8). He further characterizes today as an era in which even globalization itself has gone through dramatic change (1999, 2000). . . . [the] previous era of globalization was built around falling transportation costs. Thanks to the invention of the railroad, the steamship and the automobile, people could get to a lot more places faster and cheaper and they could trade with a lot more places faster and cheaper. But . . . today’s era of globalization is built around falling telecommunications costs – thanks to microchips, satellites, fiber optics and the Internet. These new information technologies are able to weave the world together even tighter (p. 8).

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We see all around us that we indeed do live in a highly interconnected world. Our organizations mirror this societal interdependence and rely more than ever on collaboration as opposed to independent actions. It thus becomes imperative that we lead and manage our organizations to continually adapt and leverage interdependency in this fast-paced environment.

Systems’ Thinking Systems’ thinking lies at the very heart of interactions and interdependencies in collaborative work and has its roots in a simple concept called “cybernetics.” Cybernetics, evolving from the concept of servomechanisms in the 1860s, is defined as “ ‘the science of control and communication in the animal and the machine’ – in a word, the art of steersmanship” (Ashby, 1964, p. 11). A steersman guides a ship and by using information feedback compares the actual direction of the ship to the planned course and makes corrections when significant deviations from the planned course are observed. A century later, in the 1960s, Forrester (1961, 1969), in his celebrated simulations, described the importance of understanding management processes as interactions among system components and the cybernetic, or feedback, elements within these systems. . . . the interactions between system components can be more important than the components themselves. The concepts of information-feedback systems will become a principal basis for an underlying structure to integrate the separate facets of the management process . . . An information-feedback system exists wherever the environment leads to a decision that results in action which affects the environment and thereby influences future decisions (Forrester, 1961, pp. 14–15).

Although cybernetics laid the foundation for a better understanding of interactions, this concept of simple feedback of performance and information must be expanded into the broader concept of systems’ thinking, as organizations become more inter-linked in collaborative pursuits. Peter Senge (1990) describes systems’ thinking as: . . . a discipline for seeing wholes. It is a framework for seeing interrelationships rather than things, for seeing patterns of change rather than static snapshots. . . . Today systems’ thinking is needed more than ever because we are becoming overwhelmed by complexity (p. 68).

Perhaps for the first time in history, humankind has the capacity to create far more knowledge and information than anyone can absorb; to foster far greater interdependency than anyone can manage; and to accelerate change far faster than anyone’s ability to keep pace.

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Systems’ thinking indeed is a fundamental lens with which we can make better sense of the complex environment faced by our leaders. Drucker (1973, 1974) states the case for systems’ thinking, for seeing as a whole the forces that face the business enterprise, rather than the alternative of compartmentalizing thought. The business enterprise is a system of the highest order: a system the parts of which are human beings contributing voluntarily of their knowledge, skill, and dedication to a joint effort. And one thing that characterizes all genuine systems, whether they be mechanical, . . . biological . . . or social . . . : it is interdependence. The whole of a system is not necessarily improved if one particular function or part is improved or made more efficient. . . . In some cases the best way to strengthen the system may be to weaken a part – to make it less precise or efficient. For what matters in any system is the performance of the whole . . . rather than of mere technical efficiency (p. 508).

Networks Application of systems’ thinking is timely, as we experience continuing advances in IT and increased globalization. Within this context, we are also witnessing how the concept of networks is being applied to every aspect of our lives, from communication and knowledge sharing, to social networks, to organization structures and even to networks for our national defense. A compelling case for the use of the network concept has been articulated by Friel (2002) as he describes the leadership in one such network. He decentralized decision-making authority and created a flat management structure to quickly respond to changes in his operating environment. He overcame turf battles by creating an overarching sense of mission and doctrine. He used the Internet, the globalization of news and the revolution in telecommunications to advance his organization’s goals worldwide. He developed a complex organizational network in which information gets only to the right people at the right times. In his network, connections between individuals and groups are activated at key times to get work done and severed when they are no longer necessary (p. 1).

Our first reaction here may be that the individual described heads a successful organization, for he or she well recognizes the challenges and enabling technologies of today’s world. In fact, he understood only too well the power of networks and collaboration. The reference describes Osama bin Laden and the strategy that led to the tragic events of September 11, 2001 in the U.S. We now recognize that even our national security is highly coupled to our ability to lead collaborative work within a network structure (Arquilla & Ronfeldt, 2001). Our military organizations, which are built upon centuries of extremely hierarchical structures, recognize the need for dramatic change in today’s environment. Accordingly, our national defense strategy is moving from what is termed “platform centric” in which individual ships or aircraft are relatively

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self-contained, to a “network centric” concept in which information passes freely among platforms, personnel and other information sources such as satellites or uninhabited vehicles. Shared awareness, flexibility, timely and accurate information, and fast response are products of this 21st century defense concept. Networks of collaborative relationships are also proliferating within business organizations. To ensure success, an organization’s leadership and structures must now embrace these network trends. Networks must provide ready access to information that may have been privileged in the past; and manage the complex interrelationships and interdependencies with those organizations and individuals formerly external to organizational boundaries. They must create and adapt their organizational contexts to facilitate changes. Lipnack and Stamps (1994) have noted, “[t]he network is emerging as the signature form of organization in the Information Age, just as bureaucracy stamped the Industrial Age, [and] hierarchy controlled the agricultural era” (p. 3).

THE NETWORK ORGANIZATION In this Information Age, the organization becomes a nexus where technology, globalization, and human nature coincide. Network structures and systems’ thinking play important roles in helping our organizations succeed. However, for an organization to achieve success, its leadership must not only understand and use these structures and systems, but also must understand their implications for managing collaborative work effectively. Using multiple examples as well as recent research in a network organization [Texas Instruments, Inc.] by one of the authors (Higgins, 1997), this chapter introduces a dynamic model for leading network organizations. This model considers an organization’s internal interactions as well as its interactions with the environment and with external organizations within its network. The chapter integrates multiple disciplines including systems theory, behavioral theory, and management control theory. It gives leaders a model and a set of four imperatives for achieving effective collaboration within networks. Leaders will learn successful actions to pursue and failure modes to avoid.

What is a Network Organization? A Network Organization is an organization that operates within a web of interdependent organizations for the purpose of achieving an objective that is agreeable to the partner organizations within that network.

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Executives of network organizations seek to combine core competencies and talents of individual firms along the various links of the value chain. These firms are brought together “for a given run and then disassembled to become part of another temporary alignment” (Miles & Snow, 1993, p. 82). A network is formed for the purpose of providing organizations a competitive advantage that those firms outside the network do not enjoy. Networks differ from other organizations and team structures in that they lack clear organizational boundaries. The boundaries that do exist are very fluid. Effective collaboration in a network thus relies upon resource exchanges, information exchanges, lateral interpersonal relationships, and trust rather than on organizational position and direct authority. Working relationships cut across intra- and inter-organizational boundaries. As a result, network organizations cannot be managed using traditional command and control techniques. The network has evolved from a functional, divisionalized matrix, where organizational boundaries are somewhat fluid. But, network organizations function with considerably more fluidity than matrix organizations. In matrix organizations, for example, the interactions with contractors tend to be formal whereas in boundary-less network organizations, relationships and contractual relations tend to be more informal. Yet, networks are not all created equal. Alternative forms of network organizations exist with different degrees of stability and formality depending upon the type of product, the dynamics of the environment, and the talents required of network partners.

Alternate Forms of Network Organizations Miles and Snow (1993) illustrate three broad categories of network organizations; internal, stable, and dynamic. The first is the Internal Network. Executives design internal networks as micro profit centers in which managers are free to acquire resources inside or outside the organization to fulfill the goals of their profit center. Internal units are provided incentives to become more effective and efficient. Unprofitable or inefficient, non-core activities may become candidates for outsourcing. The internal market concept thus creates market discipline inside an organization and a structure that encourages adaptation and innovation (Halal et al., 1993). Stable networks of companies and suppliers have existed for many years in industries such as retailing, film production, health care, defense, aerospace, and automobile manufacturing. In the stable network, the core firm breaks up its value chain and employs external organizations as long-term partners, each in the domain of its distinctive competence.

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Firms at the core cooperate with partner organizations in product design, manufacturing, strategic planning, and cost management. Partner organizations are expected to be proactive in efforts to continuously improve their performance as well as the performance of team members in other firms within their network. The Japanese keiretsu is a prime example of a stable network. For example, the Toyota Motor Company is at the core of a stable kieretsu network of automobile suppliers and parts manufacturers (Lincoln et al., 1998). Each of the thousands of suppliers in Toyota’s automobile network specializes in the area of its core competence. The kieretsu thus allows the core firm to specialize in its competence which historically at Toyota has been the design and final assembly of its vehicles. The kieretsu can be vertical, between suppliers and manufacturers, or horizontal, organized around a bank or another financial institution that owns equity stakes in members of the network. The keiretsu also demonstrates that stable networks between producers and suppliers need not be completely static in the presence of change. Toyota, for example, has had a long-term purchase-supply relationship with Denso Corporation, a designer and manufacturer of electronic components for automobiles. Denso itself was created as a spin-off of Toyota. Yet, the importance of electronic components in automobiles has increased significantly and Toyota now believes it is a core competence that it cannot completely outsource to suppliers, let alone to a single supplier. Thus Toyota has encouraged Denso to expand its customer base. In addition Toyota has created a relationship with Toshiba to act as a second source supplier for electronic components. The dynamic network is more widely used in organizations that experience rapid market and technological change. These companies are scrambling to find the right set of partners that meet the on-going challenges of their environments. Partners in the value chain of dynamic networks are constantly changing, unlike in the stable network, as firms attempt to lead and adapt to change. Many industries such as semiconductors, telecommunications, computing, software, and biotechnology use dynamic networks in order to more effectively innovate and adapt to their intense environments. Regardless of their precise form, network organizations must be designed and executives must lead them. We turn now to describe an overall model for the design of management coordination systems for leading collaborative work in network organizations.

LEADING NETWORK ORGANIZATIONS This model for leading network organizations is informed by the theoretical and empirical research carried out by Higgins (1997) at Texas Instruments (TI). The

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formal research project examined 6 inter-organizational teams within 2 business units at TI. The 6 inter-organizational teams included participants from 23 external partner organizations. Subsequent analysis and executive practice has led to the design of a general model for leading network organizations. Four management imperatives are derived from this model. A detailed understanding of the model and imperatives should be useful to executives of many knowledge-based organizations who lead network activity. It should also be useful to researchers who are interested in advancing the theory and practice of leading collaborative work in network organizations.

Implications of a Network Organization on Leadership We will start with a traditional command and control organization to explain the implications of a network organization on leadership. When designing a management control system for a traditional organization, we use mechanisms such as command authority, responsibility centers, budgets, performance monitoring, and rewards and punishments to motivate goal-directed behavior. Leaders in network organizations do not have direct authority over employees and leaders in partner organizations. But, leaders do have influence. They can empower people and coordinate their behavior but they cannot “command or control.” The executive has to think about management in a different way when leading people in a network. He or she has to think with more of a systems’ orientation about how to coordinate this whole collaborative organization to produce a product or service with which customers are happy and where organizational and inter-organizational goals are achieved. So, we turn now to explain how to lead complex collaboration in network organizations.

Management Coordination Systems for Network Organizations Systems’ thinking forms the basis of a model for a management coordination system (an MCS) to accomplish this leadership role and achieve the goals of an organization in a network. This MCS model depicts the components and interactions in an organization that are core to achieving success. It addresses leadership challenges inherent in a network organization. A leader can use this model to achieve goals and increase success. Goal alignment, as noted earlier, is fundamental to success, thus we start with the task of goal alignment in a simple organization.

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Fig. 1. Management Control Systems and Goal Alignment in a Simple Independent Organization: Two Basic Levels.

Achieving Goal Alignment in a Simple Organization Figure 1 depicts a very simple organization. The egg-yolk-looking circles represent individuals who work in the organization. These individuals have their own lives, jobs, roles, and motives. Each individual has a somewhat different combination of motives including financial rewards, job satisfaction, recognition, and a sense of achievement. Management control in this organization is a matter of selecting the right people and aligning their goals with those of the organization. Goal alignment occurs when individuals are motivated to achieve goals and objectives that are consistent with those of the organization. Even in the simplest organization there are at least two levels of goals; individual goals and organizational goals. The goal formulation process can be extremely successful and can highly motivate people if the goals of individuals and the organization happen to coincide or overlap. If people are happy they tend to be more productive and the organization is more likely to fulfill its mission. Yet even in this simple organization it is difficult to achieve goal alignment. Individuals and the organization have multiple goals. One must understand individual motivations and provide rewards that will motivate individuals to achieve the goals of the organization.

Achieving Goal Alignment in a Network Organization Figure 2 presents a much more complex challenge because here we have multiple organizations in a network. One of Higgins’ (1997) inter-organizational teams at

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Fig. 2. Management Coordination Systems and Goal Alignment in a Collaborative Network of Organizations: Three Basic Levels.

Texas Instruments exemplifies the challenges involved in aligning the goals among organizations in a network organization. This team was involved with another company in a joint venture. The primary focus of one of the companies in the venture was to earn the highest return possible on its investment. The other company’s main objective was to deliver a high-quality product, and although they also wanted to earn a satisfactory return, the primary goals of the two organizations didn’t match. There was inherent conflict in the goals of the joint venture. Peter Drucker (2001) notes that one of the factors leading to the break-up of alliances after they have successfully navigated the start-up period is the realization that the basic goals of partners are different. Conflict occurs over numerous decisions when basic goals differ. Such was the case on the TI team. Conflict arose because it was difficult to reconcile on-going decisions with conflicting organizational goals. When you overlay each individual within each organization onto a network it gets even more complex. Within TI, for example, individuals working on some of the inter-organizational teams were primarily motivated by technical excellence. They joined TI because they wanted to use and improve their technical skills and they received satisfaction from doing excellent technical work. On the other hand, TIers on other teams were motivated by financial rewards. Even motivations of TI personnel were different. Figure 2 shows three large organizations and multiple teams with people inside each organization operating under different rules and different motivations. One

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team’s goal, for instance, might be to complete a report by the next day, and another team in the same organization might need to get a weapon integrated onto an aircraft. They both may need to use the same analysis equipment. However, the leader on the first team might not really care about the needs of the second team. If teams internal to each organization share the same resources, each team wishes to have sufficient resources to meet its schedule and this often leads to conflict within one organization. Now, overlay the conflicts experienced between internal teams onto inter-organizational teams and the problem of achieving goal alignment becomes even more complex. When you have teams that cut across organizations, it becomes very difficult to simultaneously motivate individuals, motivate teams, align goals within an organization, and between organizations. Alignment involves multiple layers of interactions (i.e. a system of systems). It is important when leading network organizations to understand these dynamics within and among organizations and to coordinate the collaboration required to successfully achieve all of these goals. The leader’s role is critical and primary to achieving success. There are a number of steps leaders can take to achieve individual, team, organizational, and inter-organizational success. The remainder of this chapter describes components of a general MCS that can be used by leaders to successfully accomplish collaboration in networks. Components of an MCS for a Network Organization Table 1 lists the components of an MCS for a network organization. The basic building blocks of this system are the primary management systems which Table 1. Management Coordination System Components in a Network Organization. • Basic building blocks – Primary management systems • Individuals • Leadership system • Formal and informal systems – Performance • External environment • Internal environment – Trust/commitment/conflict/adaptability – Information processing – Goal alignment • Inter-organizational influences

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are designed to achieve organizational performance objectives while satisfying employees and customers. Other components, such as external environment, internal environment, and external organizations’ influence and are influenced by these basic building blocks. Primary management systems include individuals, a leadership system, and formal and informal management systems. Within a successful network organization there is no longer a pyramid with a CEO at the top saying, “this is our strategy and this is what we’re going to do.” Rather there should be a mix of leaders at all different levels who ask, “how are we going to interact together?” or “how can we combine our talents to accomplish our goals?” Leaders design formal and influence informal systems to achieve performance objectives. Next is the external environment. Each network interacts with its external environment. Some of the dynamics experienced in a network come from this environment. Leaders often find themselves asking questions like “what should I do if my product isn’t very popular today, or if technology has advanced, or if there’s no budget among customers for my product, or if an organization in the network goes out of business?” These kinds of external events are constantly churning and present major challenges for network executives. Then there is an internal environment within an organization or on a team whose members may come from different organizations in a network. The internal environment includes a number of soft variables, like trust and relationships. Information processing is also part of this internal environment and reflects how members within an organization and among organizations share information. The effort required to achieve goal alignment is also part of this internal environment. Next, there are influences from partners and external organizations in the network. These influences are called Inter-organizational influences. Finally, these components or interconnected parts of an organization have cause-and-effect interactions upon each other. Figure 3 is a diagram that shows many of the interactions among the components defined in Table 1. We will describe the components and the elements of this diagram, and their interactions, step-by-step, so that you can see how executives can lead collaborative work in network organizations using management coordination systems. You will also see by all the arrows and flows in Fig. 3 that there are a number of implied dynamics in this system.

The Individual’s Intrinsic Motivation We begin our explanation of network components by extracting, and placing in Fig. 4, the basic building blocks enumerated in Fig. 3. We start very simply, with the individual, and with intrinsic motivation of individuals.

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Fig. 3. Management Coordination System for a Collaborative Network of Organizations.

Fig. 4. Basic Building Blocks: Management Systems, Individuals, Performance.

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What is intrinsic motivation? Intrinsic motivation consists of the internal factors individuals bring to an organization. Internal factors define who we are and provide the impetus for our actions. Doing well in the world, serving others, feeling good about what we do, the desire for achievement, and acting with integrity are examples of internal factors that motivate individuals. Intrinsic motivation of individuals is a “self-control” system (Dalton & Lawrence, 1971), and because it is such a powerful force in motivation, organizations should seek individuals whose internal motives and values match the goals and values of the organization. Executives, in their recruitment activities, can select associates with attributes they desire. Furthermore, many attributes can be enhanced by a leader’s actions, oftentimes simply by setting an example or giving feedback. These intrinsic characteristics of individuals influence commitment to work as well as commitment to team members and commitment to the organization. When these intrinsic characteristics match the goals and objectives of a team or organization, they contribute to its success.

The Leadership System Leadership is the most important of the primary management systems since it has significant influence upon formal and informal systems and therefore on performance. Leadership is defined as the actions, values, style, and characteristics, which enhance the ability of executives of business units and of external organizations to operate in an informal, interactive, network organization. Leadership is considered a system because in network organizations, unlike in hierarchical organizations, leadership includes both organizational and inter-organizational leadership. Leadership in a network is not merely a person at the top of the hierarchy setting the vision and values for the rest of the organization. Rather, it is a system of people in various leadership positions both inside and outside of the organization who are responsible for the direction of the organization and the inter-organizational team. The concept of leadership as a “system” is an extension to networks of the organizational practices of “shared leadership” (Pearce & Conger, 2003) and “connective leadership” (Lipman-Blumen, 1996). Several empirical articles related to the concept of networked-based leadership have appeared in the literature in recent years. The work of Pearce and Sims (2002) and Pastor, Meindl and Mayo (2002) stand out as important examples. Pearce and Sims (2002), for instance, present a study of shared leadership in change-management teams. They conclude that the more leadership roles are shared within the teams, the more effective the teams. While Pearce and Sims’

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(2002) work on shared leadership is clearly related to our model, it is based on the team as the unit of analysis, while we are focused on the network as the unit of analysis. Pastor et al. (2002), alternatively, specifically focus on the network as the unit of analysis. However, as with most of the social network literature reported in empirical journals, Pastor et al. (2002) focus more narrowly on the importance of the role of the individual leader in the network. On the other hand, our model is somewhat more encompassing and attempts to articulate leadership as a critical function of a social network. As a result of the complexity of the topic of network-based leadership, and the subsequent need for significant journal space, the preponderance of the research on the topic has been reported in books. Therefore, research that has been reported in books has been particularly important for the development of the system of leadership contained in this chapter. This system of leadership has to formulate as well as implement strategy. Implementation of strategy, in turn, requires decisions concerning the allocation of resources. In this process the leadership group – organization, organizational unit, and inter-organizational team leaders – share opinions and engage in dialogue and conflict over direction. The system of leadership is responsible for uniting and motivating the rest of the members, at all levels, towards the vision and goals of the organization and its inter-organizational teams. The leadership team should combine its forces and understand the influence it can have upon overall performance. These leaders should ask themselves: “how by our values, style, actions and other characteristics can we influence our organization towards success and how can we use our formal and informal management systems to create an environment that leads to success?” The most important characteristics possessed by effective leaders of network organizations in the TI study were:
integrity,
relational skills,
a track record of success, and
the ability to:
use influence rather than direct authority in relationships,
empower others,
understand the “big picture,” and
establish a vision and set goals. These characteristics, almost identical to those identified by Kotter (1988), emphasize what a leader in a network does; not merely what a leader is. What do the leaders value? Do they create trust? Do they empower people? Or do they just monitor every little thing, micromanage, in other words? Are they competent? What are their motives? and What kind of strategies do they pursue?

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Formal Management System Leaders actively design formal management systems in organizations (Barnard, 1968; Blau & Scott, 1962; Kast & Rosenzweig, 1985). The formal management systems of an organization include organization structures, such as hierarchies and teams, formal monitoring systems and rewards, formal coordination mechanisms, such as electronic communications, training and indoctrination policies, and planning and control systems (Maciariello & Kirby, 1994). One example of interaction occurs between formal systems and intrinsic motivation. A formal reward based upon achievement may reinforce feelings of self worth and therefore appeal to intrinsic motivation. The Higgins study at Texas Instruments found that the most important formal systems for managing collaborative and inter-organizational work were:
the formal organizational structure for the inter-organizational team,
the roles of the members of the inter-organizational team,
formal training in team building skills,
training in management policies, and
planning and control processes including the goal alignment process (referred to as goal flowdown and catchball) and continuous improvement methods. Characteristics of the formal systems that led to ineffective performance were:
overly loose or overly tight planning and control processes,
formal coordination mechanisms that rely on rules and standard operating procedures,
ineffective feedback of information from the environment regarding performance on goals,
lack of a direct link between performance and rewards, and
unclear or constantly changing organization structure and roles. It takes time to design formal systems such as the organization structure, a performance monitoring system, or a reward system. And, it takes time to change them. So a leader has to be mindful that when she sets a policy or a system in place, it is not quickly changed. Informal Management Systems Although the formal system is a powerful mechanism for coordination in an organization, the greater power comes from its interaction with the informal system. It is a framework upon which the informal system hangs. The informal organization refers to the emergent patterns of social life “that evolve within the

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framework of a formally established organization” (Blau & Scott, 1962, pp. 6–7). Informal management systems include factors that are intangible but nevertheless very real. It includes culture or beliefs, inter-personal relationships, ad hoc roles, and informal rewards (Maciariello & Kirby, 1994). Does an organization see itself as a dynamic, great organization? Does it have high integrity? How do individuals interact and what do they believe? Do individuals in the organization share the espoused values of the organization? For example an employee may say, “I won’t cheat anybody because honesty is a value of my organization. I will not cheat and furthermore the organization won’t tolerate it.” Interpersonal relationships in the informal system may be fragile, and perhaps in some cases, extremely so. Think about interacting with people on a personal level. Suppose a person does something that irritates you. That can happen quickly, even in less than an hour. Your reaction may be, “I’m not going to work with you anymore. You really upset me so I am not going to have anything to do with you.” These are very real actions and although intangible, they’re a critical part of the informal system within an organization and subsequently may change the nature of the working relationships in the organization. Culture and beliefs in the informal system are also intangible, but may not change so quickly. The fieldwork at TI indicated that certain cultural values are important for the smooth functioning of inter-organizational coordination systems. These values, which were present at TI during the study period, are:
ethics and integrity;
a technical problem solving orientation;
a strong work ethic;
respect for the individual; and
the importance of teaming. Through his actions, a former president of TI set an example of strong ethics and integrity that has since become folklore in the company. In this example, his action was ingrained into the culture of the company and has been sustained. This man of high integrity didn’t tolerate any kind of underhanded-dealings. He received word that in trying to do business in a foreign country, employees there reported that a negotiator wanted TI to bribe him in order to get his business. He had said, “hey, give me money and we’ll do business with you.” The president was upset by the request for a bribe, and even though the prospective business would have made a big difference to the bottom-line of the company and to future profitability, he said, “no, we don’t do things like this.” He personally got on a plane and brought the TI employee back home. The president meant what he said about bribes! And, the example he set became a defining act for the culture of the company.

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So, you can see the effects of a leader’s action. If a leader espouses high integrity and takes actions that reflect that integrity, people will believe in the leader, they will trust the leader, and say, “okay, that is who we are; those are our values.” But, actions take a long time to get instilled into a culture. It happens over time. It takes longer than just signing a policy statement, or making a change in rewards, or changing another formal system. Although actions may take a long time to influence an organization’s culture, they are extremely powerful both in positive and negative ways. Leaders should understand the influence they have on the values and beliefs of their organization. This influence occurs by stating organizational values and then implementing them through consistent actions even if the actions are costly.

Interaction Between Formal and Informal Systems Another interaction in Fig. 4 is between the formal system and the informal system. The two systems are highly interlinked, with the informal system breathing life into the formal system skeleton, giving the organization personality and soul. Remember the informal system includes the beliefs and values of an organization; the network of informal relationships; and the informal recognition and reward system. For example, assume an organization’s formal system rewards getting projects done on time, and at any cost. The performance and reward plan might stipulate that a bonus will be given to team members if they complete a priority project by a given date. Assume further that an espoused value of the organization stipulates, “we don’t take shortcuts, we produce excellent products” and this is what people believe the values of the organization to be. If you continue to reward the behavior, “performance at any cost,” what do you think that will do to the values of the organization? How can individuals believe the espoused values if the organization rewards something else? A real conflict between performance and values often occurs with the “superstar.” These people are high performers, but they may be very wearing on their teammates. They simply want to get the job done without placing the same value on “teamwork” that the organization does – without supporting other teammates or minimizing dysfunctional conflicts. Organizations have these superstars who say, “I don’t care about you and your work because you don’t help me with my project. If I step on your toes by achieving my goals, I don’t really care. I’m going to get it done even at any cost.” Sometimes an organization rewards these individuals because they do get things done. One-high technology organization decided, “yes, it’s great to have people who get things done at all cost.” But, they found that the heaviest cost of this behavior

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was long-term cost; as they continually rewarded these people, others noticed and said, “but wait a minute. You’re saying on one hand you want us to be a team and you want us to work together and yet you’re letting this person go off and be so different just because he gets things done, that’s not fair!” The solution is for the leaders to act consistent with espoused values at every opportunity. Take the case of the superstar who doesn’t support the values of the company. If a leader sees people operating contrary to organizational values, they must let it be known that they will not tolerate this behavior. Some people get the point and change their behavior or leave. Others may need to be dismissed. However in asking a star-performer to leave the organization, a leader does not want to send a signal that outstanding performance is unwanted. Rather, they have to make it very clear why the individual is leaving. It isn’t because the star-performer excelled that they were let go, because the organization does reward outstanding performance. Rather, it is because they did not perform within the culture; they did not accept the organization’s beliefs.

Time Lags and Long-Term Effects You can see from this example that if a formal system rewards “getting things done at all cost,” but the informal system emphasizes teamwork, there’s a conflict between the formal and the informal systems. They are not supportive of one another. But, the conflict, normally, doesn’t hurt the organization immediately. Changes in the formal system, such in the reward system, don’t impact the informal system right away. There is a time lag. Espoused values are stated beliefs in the informal system, actions reflect true values, and if over time actions do not match beliefs, the espoused values are not believed, creating a disconnect between formal systems and espoused values in the informal system. Espoused values are embedded in the culture of an organization through two-way interactions between formal and informal systems. Interactions occur and individuals watch what happens and measure actions against what was said, continually analyzing actions in light of values. Over time, actions become the beliefs that are part of the culture. Prior to that time, however, the very divergence of espoused values and actions can affect many contributors to success. And this is critical because this diversion not only reduces employee satisfaction, but may also undermine the trust individuals have for their leaders. Through their actions, executives in our super-star example have stated their real beliefs, “we are not going to emphasize getting the job done at all costs.” In that case, individuals have to: (1) share the values of the organization; and

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(2) perform. If they don’t adhere to the values, they may be candidates for being released even if they perform well. In fact, some people have been released in our example because they did not practice the values of the organization even though their performance was acceptable. So in order to produce internal consistency between informal and formal systems, and maintain high integrity, a leader has to practice what she preaches. As some have noted (Whitney, 1994), trust is built when leaders “walk their talk.”

Performance The final component in the model in Fig. 4 is performance. Performance is measured by team, organizational, and inter-organizational success, with regards to project goals. These are the overall objectives of the primary management systems.

Feedback Let’s summarize Fig. 4 to this point. First, the leadership system should be in place. Then one attempts to get the intrinsic motivation of individuals lined up with the organization. Next, the job is to get informal and formal systems in synch, at least to the point where they are not counter-productive to each other and they are in line with leadership values that promote success. Then strategic thinking is carried out, plans are established and implemented. Finally, if all goes well, performance goals for all stakeholders (team members, organizations, and customers) are met. But we are not finished. The last component is feedback to the primary management systems as shown in Fig. 4. If the team and organization does well and meets its goals, adjustments to the MCS may not be necessary. If the organization fails to meet its goals, a leader might say “wait a minute, something is wrong here. As the leader of the organization I may want to change some things. Maybe we should reorganize. Or perhaps examine our values. Or look to see if our people are as productive as they should be or if they are in some way demoralized. Are they getting what they need from this organization?” The feedback loop is where we start seeing the importance of adopting a systems orientation. We recognize that some components and elements in the model affect other pieces and there is a feedback of results onto the rest of the system. The feedback process continues indefinitely following the precepts of management control theory (Maciariello & Kirby, 1994).

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Fig. 5. Open Systems: External Environment.

External Environment Variables external to the organization may significantly impact the performance of the organization. Performance, in turn, can affect these variables, thus the bi-directional supportiveness arrow in Fig. 5. We consider below two external variables, environmental intensity and unique environmental variables. We also describe how leaders must adapt the MCS to the external environment.

Environmental Intensity Various authors have identified some combination of three variables, complexity, dynamics, and uncertainty to characterize the environmental intensity in which organizations operate (Emery & Trist, 1965; Scott, 2003; Thompson, 1967). The nature of the industry itself, including the customer and the market environment, and the interdependency of the organization with external organizations all influence these intensity variables. Environmental intensity is the major factor differentiating organizations into those which may be characterized as make and sell versus those which may be characterized as sense and respond (Haeckel,

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1999). Make and sell organizations face less intense environments than do sense and respond organizations. Major differences existed in the environments faced by TI and by the 23 external organizations on the 6 inter-organizational teams. Differences in these environmental variables accounted for differences in their management coordination systems and, to a considerable extent, for differences in the performance of these teams when their MCSs did not appropriately accommodate the environment. The number of sources required to get the information needed to make decisions and the range of knowledge required to gain an understanding of these inputs are measures of complexity. The rate of change over one and five years in products, technology, legal environment, internal structures, number of employees, competition, and in the customer base provides a way to assess dynamics. Uncertainty is assessed by the extent to which individuals in a business unit have enough information on the environment to make effective decisions and to predict the outcome of their decisions. The external environment may be highly dynamic and move quickly. Technology, for example, changes very rapidly and significantly impacts affected organizations. An organization’s MCS must be flexible and adaptable enough to adjust to the complexity, dynamics and uncertainty of the external environment and to changes that are happening whether they’re rapid or slower. If changes are rapid, a highly bureaucratic organization, one that has rigid rules and procedures that it cannot deviate from, is unlikely to prosper and may not survive.

Unique Environmental Factors Unique features in the environment include specific industry features such as downsizing trends and availability of specific human, capital and physical resources and budget cuts enforced upon an organizational unit. These factors can affect the business unit, including its performance on goals. For example, an organization in an industry that is “downsizing” is beset by extremely demoralizing influences upon internal relationships. These external influences may impede the effectiveness in which an organization performs.

Adapting Primary Management Systems to the External Environment A way to acquire flexibility and adapt to a highly intense external environment is to create an organic organization structure (Burns & Stalker, 1961; Lawrence &

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Lorsch, 1967; Mintzberg, 1979; Williamson, 1981), one that permits supportiveness between the environment and the primary management systems. An organic structure is just that; it’s a living thing, it’s a dynamic thing. It almost breathes; it changes; it grows; it morphs into other things. An organic organization is very much based on the informal management system. It’s based on relationships, trust and interactions among people. Supportiveness between the external environment and the organization means that if the external environment changes rapidly, the internal environment is able to adapt to those changes quickly. If an organization lacks informal relationships that are required for rapid adaptation to the environment the leader can develop them – but it takes time. A leader may create situations which strengthen an informal system. Rewarding constructive informal behavior when it occurs can do this. For example, if someone has a good idea and has carried it out informally, the leader could say, “great idea, let’s do it. It isn’t in our rule book, but do it because it makes sense.” For example, assume you work for Mega County (actual example, disguised name) and county government operates in a very bureaucratic, rigid manner. Assume further that you have to travel somewhere and the County is going to spend $800 on the plane ticket. You say, “well heck, I’m just going to go online and buy a ticket at one of the auction sites for $199 and then bill the County for $199.” You explain that you saved the County $600 by simply shopping for the best fare. But, the practice violates County rules and in following the rules a normal supervisor would say, “we can’t pay that bill because it violates our rules and regulations.” But suppose your manager finds a way to pay the bill, commends you for the great idea and starts to change the rules. This attitude could be the beginning of change for a very bureaucratic system. However, you must be careful that in allowing some flexibility, you do not go overboard and move faster than the organization will permit. Note in this example, the external environment had changed but the rules had not. The informal system in this case allowed the manager to say, “hey, I know you. I trust you. I know you can help the County and we can all work together in an informal way to change the outdated rule.” This is a simple example of a complex class of problems. But, as the external environment facing an organization changes rapidly, it’s imperative to have internal operating procedures in place to adapt successfully to the environment. Just having bureaucratic rules and regulations won’t do it. That’s how a leader can encourage development of the informal system. It takes a deliberate thought process, but one builds the trust and says, “well okay you can go out on a limb a little bit. Go ahead and oh, by the way, if you want to, talk to so and so.”

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A leader can also encourage informal relationships and networking by chartering a formal team to solve a specific problem with expectations that informal relationships will form. This technique has worked effectively in many organizations where individuals from different parts of the same organization or from different organizations have been placed on a team. A recent example occurred in the Navy’s explosives community when executives brought together leaders from separate organizations to develop joint projects. These leaders traveled extensively, visiting each other’s sites. As they worked together, they interacted socially and broke down long-standing barriers of mistrust, learned each other’s skills and built close ties. Team members now call upon each other when they need support. This approach built a productive set of relationships that did not exist before the executives set up the formal team. Informal relations make the organization more adaptive and better able to cope with environmental changes. Another common example involves the response of a leader to the common but painful situation involving a deep budget cut enforced upon the organization by the loss of a key contract or by other specific environmental events. The budget situation creates a dilemma; the organization now has a number of excess people. How does the leader react to this unique environmental factor? Here is where it gets difficult. Leading companies have reacted differently. Some simply cut their work force to “right-size” the organization. Other companies have said to their employees, “you are valued employees, and we want to keep you as long as we can. So let’s figure out a strategy to solve the budget problem.” There are different ways an organization can change its formal system to react to budget cuts. And the ways an organization reacts do matter. One solution is for a number of executives and key employees to take a reduced salary until the environment improves. Another solution is for a leader to say, “I’m going to lay you off, but I will try to hire you back as soon as possible.” Sometimes the only strategy is to cut the work force. But one does need to think about how to implement these strategies and understand the effects of these alternatives upon the informal system for employees who remain. If those who remain feel so insecure in their jobs or feel that those who left were treated disrespectfully, the best of them may leave because they have other opportunities. They will have no allegiance to the organization, because they now believe it doesn’t have allegiance to them. If individuals feel, for example, that at every whim, at every up and down in the external environment their job is at risk, they would find it hard to stay motivated. If employees chose the company for the joy of achieving or for increasing their technical competence or even primarily for financial compensation, they might start looking elsewhere, because they know their jobs may no longer be secure and the company doesn’t really value them.

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In these cases, the leader needs to develop other motivators for commitment, such as training programs that will ensure individuals remain “employable” if not employed by that company.

Internal Environment The internal environment, as presented in Fig. 6, consists of a number of processes and variables to how an organization works. Not only do the primary management systems affect success, they also interact to create an internal environment, working together to encourage or discourage trust, commitment, constructive conflict, and adaptability. It is the operating environment where both formal and informal systems are used for information processing (Galbraith, 1994), whether via formal email systems or informal grapevines. Information Processing reflects the combined effects of the primary management systems on how goal alignment is actually accomplished. In turn, individual, organizational and inter-organizational goal alignment are critical for facilitating commitment, trust, constructive conflict and adaptability within the internal environment.

Fig. 6. Internal Environment Characteristics.

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Fig. 7. Goal Flowdown: The Goal Alignment Sequence.

Goal Alignment First, we discuss goal alignment. It appears as a component of the internal environment in Fig. 6. It is broken out further, in sequential steps, in Fig. 7. Goal alignment is an information processing sequence. The sequence is accomplished through the interaction of leadership, formal, and informal management systems. For example, the goal alignment sequence might start with leaders articulating their goals. Or, a leader might say, “these are my goals and I’m going to communicate them and get reactions from my people.” A key issue is deciding on the actual communication steps necessary to carry out the information processing steps show in Fig. 7. Texas Instruments (1994) carried out this sequence using a communication process called “catchball.” Catchball starts with overarching goals – a big idealistic vision, which they promoted in all of their magazines and newspapers. Everybody knew these overarching goals. At first people would look at them, and say, “okay, but I don’t fit there. I don’t see myself being networked into the TI world. I solder circuit boards. How do I fit?” In response, TI’s top executives gathered literally hundreds of supervisors over days and weeks and communicated these goals. Each of these supervisors went back and said, “this is how my organization fits.” It was like throwing a ball. “Here you go; here are the goals, what are you going to do with them? ‘I caught them. Now I’m going to share it with my people or with the next supervisory level down. Okay, here you go. What does it mean to your particular organization.’ ” Interviews at TI demonstrated that people at all levels knew the overarching goals. Furthermore, they knew their contribution to those goals. They were committed to these goals because they knew the goals, they accepted the goals; they trusted that the organization was concerned about the goals and that the goals

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were for their benefit. They were highly motivated to accomplish their goals, following the sequence in Fig. 7. So, this process of communication is extremely important. And the way TI did it was very effective because they involved everyone. Everyone had to write down in his or her own performance plan, “this is what I’m going to do and this is how it fits.” The catch-ball process at TI illustrates an exemplary goal alignment process for an organization and its individuals. Goal alignment has been the subject of recent research and much of this research is relevant by extension to alignment in a network organization. Pfeffer (1998) notes that a firm’s competitive success is dependent on alignment, i.e. an organization’s practices must first be consistent with one another and next must be consistent with its strategies. Labovitz and Rosansky (1997) further illustrate the power of a vertically and horizontally aligned organization. A vertically aligned organization is one in which employees are in complete alignment with the strategy of the organization. A horizontally aligned organization, on the other hand, is one in which the organization’s business processes align with the requirements of customers. The authors further indicate the mutually supportive nature of this alignment, “When alignment is achieved in both dimensions . . . a dynamic relationship exists between all four elements . . . each element is supported and strengthened by the others” (pp. 36–37). Another concept, the Balanced Scorecard, seeks to implement strategy through alignment. Kaplan and Norton (2001) have a long-standing program implementing the Balanced Scorecard in organizations. Developing a Balanced Scorecard is an extensive process in which leaders translate the strategies and financial goals of an organization into drivers of customer satisfaction, and into supportive business processes and workforce skills. The Balanced Scorecard process seeks to align the financial objectives of an organization with its strategies, processes, and people. It then develops metrics for each of these perspectives so as to motivate performance in a balanced way and thus implement an organization’s strategies to achieve desired financial returns. Individuals have their own motivations, and each has different motivations: great work, achievement, a sense of belonging, integrity, technical challenge, money, and so on. The organization has profitability, customer satisfaction, quality, and employee satisfaction as goals. Thus a key issue and a critical role for the leader is to align the goals of the individual with the goals of the organization. It requires knowing your people; and knowing how to motivate them; articulating overall goals well enough so that everyone can know where he or she fits and can hold these goals as their own. It is important that individuals agree with the goals of the organization and be committed to accomplishing them.

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Trust and Commitment Trust and commitment in an organization’s internal environment are important reflections of how primary management systems interact to achieve results (Fink, 1992; Whitney, 1994). In addition to the primary management systems, goal alignment as implemented in the internal environment is also an important influence on trust and commitment. Goal alignment enhances commitment and trust and commitment and trust enhance goal alignment (see Fig. 6). If individuals have the same or overlapping goals with the organization and know what these goals are, they are going to trust that they are working in synch with the organization. And trust is the lubricant for constructive inter-personal relationships. Trust suggests to the individual, “I know the organization isn’t going to fire me unless I do badly, and then I’ll know why I got fired. I know that they’re going to try to motivate me and I believe what they say is true.” Trust is also enhanced by the direct actions of leaders. Here is an example that shows the importance of understanding how to develop and maintain trust. During the September 11, 2001 incident, things were pretty chaotic for the first few hours at a number of potential terrorist targets. At the naval base at China Lake, California people were angry, frightened and did not know exactly how to respond to the potential threat. The base closed down immediately; nobody could get on or off. There are schools on this base and children were in school at the time. So people were even more worried. “What about my kids? How can I reach them? What’s going to happen?” How does one develop trust under these circumstances? The way to reinforce trust in times of tremendous pressure is to communicate. In the China Lake case the leaders kept people informed of exactly what steps were being taken, what they knew, and what they did not know. People knew they could trust that their leaders would make sure that they were informed, that they were safe, and that their children were safe. This incident illustrates the importance of the presence of trust in dealing with a crisis as well as steps that are necessary to maintain trust during a crisis. And a covenant of trust is critical to solving recurring problems in network organizations. Trust is imperative in leading people through crises and times of great change. Having developed trust, the leader maintains it by communicating exactly what is known and exactly what is not known. When as a leader you do not know something, you simply say, “I don’t know” and that fosters trust. Because truth-telling is a cornerstone of trust. So, in all of these things a leader’s actions matter. The leader has the greatest impact on trust by having high integrity and by living up to that integrity, and making sure that their actions actually promote that integrity.

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Trust and the Dangers of Micro-Management While there are many things that build trust, the practice of micro-management, or excessive monitoring of performance of knowledge workers, diminishes trust and normally should be avoided. If a leader micro-manages people they are essentially saying, “I don’t trust you. I’m going to watch you carefully.” It’s especially demeaning to knowledge workers and potentially very dysfunctional to individual and organizational outcomes. Figure 8 depicts a reinforcing process that was identified at TI when micromanagement was present. Qualitative and quantitative analysis in the TI field study uncovered a detrimental reinforcing feedback process, particularly in TI’s Commercial Business Unit. This feedback process involved the use of a micro-managing leadership style in contrast to an empowering leadership style. The diagram in Fig. 8 represents a potential scenario in which a detrimental reinforcing feedback process may develop among four elements of the model. First, arrow 1 in Fig. 8 shows that a lack of organizational trust encourages a micro-managing leadership style. Second, a micro-managing style of giving the how not the goal rather than empowering persons decreases goal consistency and goal acceptance. This in turn (arrow 2) negatively affects the goal alignment sequence. Third, lack of goal acceptance and goal alignment decreases organizational performance (arrow 3). Poor organizational performance intensifies the

Fig. 8. A Detrimental Reinforcing Feedback Process.

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micro-managing style (arrow 4) which itself further reduces trust (arrow 6). Poor performance also directly diminishes trust (arrow 5). To summarize, in Fig. 8 we see a detrimental, reinforcing feedback process linking micro-management to lack of organizational trust to poor goal alignment, and poor system performance. These relationships are entirely consistent with the internal environmental relationships shown in Figs 6 and 7. Figure 8 illustrates three reinforcing feedback processes:
Low organizational trust encourages micro-management and micromanagement reduces the level of trust (arrows 1 and 6).
Poor goal performance encourages micro-management tendencies (arrow 4), and micro-management decreases goal performance by negatively affecting the goal alignment sequence (arrows 2 and 3).
Poor goal performance reduces trust (arrow 5) and low trust reduces goal performance through its effect upon tendencies to micro-manage (arrow 1) and through its negative impact upon the goal alignment sequence (arrows 2 and 3). This scenario is found everyday in organizations. How often do we see managers immediately react to “bad news” by jumping in and trying to take over – micro-managing rather than allowing individuals to solve problems? And just as frequently, the individual will react to this management style – perhaps not immediately, but at a later time – by losing trust or by merely paying lip service to goals (thus diminishing goal alignment). The process of uncovering these three feedback processes is not intuitive but rather a result of systemic thinking and analysis. Yet a deep understanding of these processes is essential to effectively leading collaborative work in networks.

Constructive Conflict and Adaptability To increase adaptability to change, and to become more flexible, a leader should create an environment that encourages people to learn (Argyris, 1977). One way leaders facilitate learning is by encouraging constructive dissent. They open themselves to being challenged. One leader challenges people with; “you know what I don’t like? It is to have people just sit there and nod their heads and say, yeah, yeah, yeah. They sit there and agree with everything I say and then go away and do something else, or offer dissenting opinions later.” If a leader creates an environment that encourages people to open up and speak up, he or she will get wonderful ideas and learn things they may never have known. It is a trusting environment, one that tolerates failure, and allows the sharing of ideas and constructive conflict. It allows the organization to act

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quickly and flexibly. An open environment fosters a learning kind of adaptability, a desirable internal variable as seen in Fig. 6 (Haeckel, 1999). Constructive conflict (also see Fig. 6) comes about by setting up conditions whereby an individual doesn’t feel afraid when challenging a leader, regardless of that leader’s position or status. People get better, teams get better, the organization gets better and the network gets better by creating an environment where constructive conflict is encouraged and where people are allowed to learn through their failures. When this environment is not encouraged, success diminishes (Rahim, 1992). Actions of the leaders, formal policies for dealing with conflict, an informal system that values trust and builds relationships all work together to create an internal environment that’s very positive and one that permits adaptability. This type of environment facilitates adaptability to very intense external environments. To this point in this chapter we have focused primarily on a single organization within a network. We have focused on the individual, teams, an organization, and on dynamics. We turn now to examine inter-organizational influences within a network of teams and organizations.

Inter-Organizational Influences By adding other organizations and teams across organizations, we increase complexity and dynamics exponentially. Now individuals work on the same project but they may be from different organizations; the leader no longer has direct authority over individuals from these partner organizations. Numerous bilateral interactions occur among organizations in a network. Achieving goal alignment among partner organizations is essential to success. There is also a need for supportiveness between an inter-organizational team and its environment. These additional components and complexities are represented prominently in Fig. 3. There are several ways in which inter-organizational teams can influence internal business units of partner organizations. These influences are:
leadership characteristics of external team leaders
teams’ formal and informal management systems
the internal environment of a team, including goal alignment
commitment and trust among organization’s members on the team and
team success We will discuss effective methods of managing these inter-organizational influences by using an example of excellent practices from the TI study. These

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practices were evident on the Joint Standoff Weapon inter-organizational team at Texas Instruments. This team was comprised of a number of organizations working on the project. TI, of course, was one of them. The government was one of them, including government personnel from all over the country. The team also included multiple suppliers and other specialists. The two major leaders on the inter-organizational team, TI and the government, started the project by telling all team partners, “we will spend time in team building because we believe it is critical to a successful project. This project is highly important so we have to establish trust in our team, to determine and align goals, to gain pride in our goals, and finally to commit to our goals.” Team members spent days together, while many complained saying, “why are you wasting this time? Let’s just get on with it.” But, they spent days working on these issues. They worked at understanding what the project was all about; what were project goals; how they were going to operate; how they were going to resolve conflicts; and what were the ground rules. Whenever a team member came to one organization to complain about someone from another organization, executives would say; “we do not want to hear this. You work it out because we are all working together. We are working on the same goal and the goal is . . .” The leadership continued to make these very clear statements regarding what the team was about. As a result, there was no problem understanding what project goals were, or how the team was going to operate, or understanding that leaders would not tolerate adversarial relationships on the team. The leadership on this team – and it was a system of leaders – was saying, “we are working together. We have linked arms and we won’t tolerate any other kind of negative behavior.” And they didn’t. The result was the strongest, most successful team the researcher had witnessed. Top leaders took the time to establish the ground rules and to set the team in place. Then they empowered people saying, “These are our values,” “These are our goals,” and “This is how we will work together.” So, the integrity, the abilities, the characteristics of the leadership members filtered into the rest of the team and extraordinary performance resulted. Gaining inter-organizational goal alignment is absolutely essential to the success of a network. It’s more difficult, however, to accomplish this alignment in a network. It is more difficult because not only must goals be aligned within a single organization, but they also must be aligned among organizations. This alignment process must reconcile goals among organizations and each may begin with very different goals. Yet in the TI study, each of the 23 organizations studied on the interorganizational teams said, “we teamed with TI, in this particular case, because

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we share values, we have high integrity, and we share goals.” When quality vs. financial performance appeared as conflicting goals in one inter-organizational team in the study, that team showed less success than others. As referenced in the example above, it is also essential that organizations in a network share values. Optimal performance depends upon a match among the cultures of the organizations; or at least a match of the values that matter most to the success of the inter-organizational team. If an organization with high integrity tries to team with another company with less than high integrity, the result is a values clash. The project team will not work effectively because trust cannot be present, nor would you know how to go about establishing trust when dealing with such a partner. To summarize, although complex interactions exist within a single organization, the interactions are even more complex when you add other organizations to form an inter-organizational network. Leading network organizations poses the challenge of leading great complexity. There is a lag in potential inter-organizational influences, as shown on Fig. 3. If on an inter-organizational team, leaders and members from one organization influence the leaders and members from another organization, then the values and practices found in this inter-organizational team may over time permeate to each of the organizations themselves. Complex dynamics occur when coordinating collaboration within and across organizations in a network. The external environment influences the leadership system. Leadership can influence the formal system and then the informal system across organizations. Interactions of these systems create internal environments both in an organization and on teams whose members come from multiple organizations. Finally, there are time lags in the influence of one organization upon the systems of partner organizations.

PRACTICAL APPLICATIONS TO LEADING NETWORK ORGANIZATIONS Leadership at all levels has a dominant influence upon the success of network organizations. Table 2 distills into four imperatives the recommendations of this chapter for leading network organizations. The first imperative is that leaders should think in terms of a system of leadership. It’s no longer just one person up at the top of the pyramid making all of the decisions. The environment is too complex. Decisions are too complex. One cannot lead by using a command and control structure. A system of interactive leadership is needed that permits rapid information processing and adaptation to

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Table 2. Four Imperatives for Leading a Network Organization. • A “System” of leadership – Translates input from the external environment into strategy, goals, and competencies – Shapes management systems to influence the internal environment, goal alignment, and performance • Goal alignment – Shapes the internal environment – Directly influences success • System interaction and supportiveness – Complementary and dynamic interaction ensures adaptation and flexibility to external environment – Leverages awareness of interdependence among external environment, management systems, internal environment, external organizations, and performance • Trust-based interpersonal relationships – Lubricant for complementary and dynamic interaction among parts of the management coordination system

changes in general and unique environmental forces. This system of leadership should be supported by good information flows throughout the network. It should maintain an environment of trust, interpersonal relationships and collaboration using influence rather than control. Leaders develop goals and the competencies that are necessary to achieve those goals. Then leaders shape their formal and informal management systems. They may directly shape their formal systems. They may seek to influence their informal systems. This proactive shaping can be employed to develop trust, commitment, constructive conflict, and adaptability. But, this ability of the leader to proactively shape must be understood and used appropriately. A leader may also insure that information processing is continuous and focused upon monitoring critical external and internal variables. The second imperative is goal alignment. Goal alignment is one of the most critical elements in achieving goals. It directly influences performance. If there is any ambiguity about goals or about how to achieve them, the organization is bound to fail. If there is a lack of commitment to goals either because they are not accepted or because individuals do not trust the organization, goal alignment and performance will be impeded. The third imperative is system interaction and supportiveness. The primary management systems should be supportive of one another and be highly tuned to the environment. The primary management systems must facilitate an internal environment of trust, commitment, constructive conflict, learning and adaptability.

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The core values of the organization will probably remain fairly stable, but they may change at the margin. Values will change with leadership. Values will change as reward systems change. What leader(s) must do is insure that these changes, whether in the informal system or in the formal system, are supportive of each other. This supportiveness will guard against such counterproductive behavior as, “I’m going to reward you because you got your project done in two weeks and I don’t care who you killed doing it” while the stated value is to be respectful of people. These kinds of conflicts create a tense environment and they reduce trust. The fourth and final imperative is trust-based interpersonal relationships which must be a hallmark in network organizations. These organizations have to rely extensively upon interactive, organic structures that depend upon trust while facilitating the development of trust, and allowing tasks to be accomplished quickly. If elaborate rules and regulations bind an organization, that organization simply will not be able to react quickly. Trust based, inter-personal relationships are critical among individuals in the organization, within the leadership system, and between organizations in a network. Powerful organizations result when leaders understand these four imperatives, understand how they interact together, and use them to lead network organizations. The leader has influence on each of these four. Barring any unforeseen problems in the external environment, organizations that are so led should succeed. The people in these organizations should be committed, have high levels of trust, and succeed. Furthermore, people also should be happy working in these organizations.

SUMMARY: LEADING NETWORK ORGANIZATIONS We have now discussed the full model for leading network organizations. Our discussion covered some of the most important dynamics, basically the process of connecting the dots. It revealed that all of these systems are inter-connected. There are lags, such as those between setting up a formal reward system and seeing it played out in the informal culture. There are also lags in management or a leader’s actions in instilling a value system or in developing others who are empowering. Numerous dynamics exist in the coordination of collaborative work. Collaborative work is always changing. It is never constant, nor can it be, because the external environment is always changing. In today’s environment, one has to design adaptability into organizations which means that leaders must encourage and rely upon the informal management systems more than ever.

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Developing trust within and between organizations is essential to success. How does a leader establish this trust when each organization is an autonomous entity with its own self-interest? How does one insure that one does not have one organization in a network trying to control or withhold information from partners? How does one establish trust in the private sector where top leaders each report to their own board, their own shareholders, and their own stakeholders? For these difficult issues, simplistic answers will not suffice. So in deciding to network with another organization, a leader must first understand the values of potential partners. Before partnering, values should be aligned among organizations in the network. Integrity is the primary value that should be synchronized. Integrity means that leaders of partner organizations will live up to their commitments. Integrity means that leaders say what they mean and mean what they say. Trust is a by-product of integrity. Once leaders and partners trust each other and form a strong leadership system based upon integrity, the remaining ingredients for success in leading network organizations can be put into place. These ingredients include defining goals that are agreeable to all; establishing constructive informal relations within and among teams; and establishing formal processes, such as a conflict resolution process, that facilitate trust and relationships. Because not all conflicts among partners can be resolved, networks may have to be dissolved when partners are unable to work out conflicts. Following the four imperatives, a successful organization in a network will have a strong leadership system that proactively seeks to leverage individual motivation and shape the internal environment using informal and formal systems; it will have internal and inter-organizational goal alignment; and its primary management systems will be supportive and facilitate trust-based interpersonal relationships.

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“SKONK WORKS HERE”: ACTIVATING NETWORK SOCIAL CAPITAL IN COMPLEX COLLABORATIONS LuAnne R. Johnson and David Knoke ABSTRACT We construct a theory of team collaboration to explain how social actors activate their network ties to gain access to and acquire the use of social capital held by other network actors. Drawing from weak-strong tie theory and closure-brokerage models of network structures, our theory specifies dynamic processes in which relations vary in their potential for activation, and thus, project teams have differential probabilities of mobilizing and gaining collective use of the varied resources held by their network alters inside and outside the team. The theoretical scope is interorganizational team whose members are employed by two partnering organizations and are assigned to a joint project with a single task or goal to be accomplished within a limited period. We present and discuss a set of propositions about factors that affect the ability of a team to access its members’ social capital for use in a project task. ‘Skonk Works Here.’ 1943 telephone greeting at Lockheed Aircraft Corporation’s P-38 Lightning jet fighter project, derived from the Kickapoo Joy Juice still in Al Capp’s ‘L’il Abner’ comic strip.

Complex Collaboration: Building the Capabilities for Working Across Boundaries Advances in Interdisciplinary Studies of Work Teams, Volume 10, 243–262 Copyright © 2004 by Elsevier Ltd. All rights of reproduction in any form reserved ISSN: 1572-0977/doi:10.1016/S1572-0977(04)10009-5

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The fast pace of technological changes and informational requirements in the global economy exert growing demands for complex collaborations among organizations. In these situations, complex networks of work relationships must be established and sustained to achieve project goals, such as building a joint strike fighter or developing new commercial biotechnology (Barley et al., 1992). These collaborations present interorganizational complexities because multiple companies, sometimes from several nations, take part. The inevitable differences in corporate cultures can pose communication challenges at best. At worst, fear of leaking sensitive information to a potential competitor can lead to total distrust. Just as challenging are the intraorganizational complexities resulting from new organizational forms that are flatter (less hierarchical) than their parent firms. Such matrix forms of project management are designed to respond more rapidly to technological problems and to facilitate cross-departmental team participation (Burns & Wholey, 1993). Yet they present additional complexities stemming from the dual functional/team authority lines, as well as the need to coordinate the work of multiple departments. Taken together, both types of complex collaboration are ripe for role- and responsibility ambiguities and inefficiencies in allocating project resources. How, then, do individual participants in these collaborations resolve these ambiguities and build effective workteam networks that will result in successful collaborations (or conversely, fail to build such networks)? Several organizational theories, most notably transaction cost analysis and resource dependence, attempt to explain why and how organizations collaborate in joint ventures and strategic alliances (Knoke, 2001, pp. 156–163). Transaction cost analysis emphasizes two determinants of company decisions to work alone or to form interorganizational partnerships. The first factor is whether the required resources are specific to particular recurrent transactions between buyers and sellers. The more specific the resources needed, the more likely are the parties to engage in bilateral exchange arrangements. The second factor is opportunism, a tendency towards “self-interest with guile” in exchanges (Williamson, 1981), which necessitates contractual safeguards and close monitoring against partners’ potential deceit and dishonesty. The higher the transaction costs to prevent opportunism, the more likely that organizations will avoid collaborations and instead perform all work in-house. Resource dependence theory focuses on the tension between an organization’s need to obtain critical resources and its desires to retain autonomy in decision making. Organizations take actions to manage external interdependencies, and organizational behavior can be understood by analyzing resource flows and organizational attempts to bring resources under their control. Key components in both theories are resources and the social networks that put these resources to use. At the micro-level of project workteams, the concept of social capital precisely encompasses these components. We believe a well-formulated

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social capital theory can provide the micro-analytic foundations for a better understanding of how complex collaborations, operating through the social networks of team members, both reduce transactions costs and gain access to resources that project teams need to meet their technological and informational goals.

THE CONCEPT OF SOCIAL CAPITAL Although social theorists have extensively used the concept of social capital, they clearly lack consistency in how to define this concept. Pierre Bourdieu (1986, p. 249), one of the first authors to describe social capital, defined it as “the aggregate of the actual or potential resources which are linked to possession of a durable network of more or less institutionalized relationships of mutual acquaintance and recognition – or in other words, to membership in a group – which provides each of its members with the backing of the collectivity-owned capital.” In his approach, the volume of social capital possessed by an ego-actor depends on the number of its direct network connections to alters, and also on the volume of capital – economic, cultural, or symbolic – possessed by all the alters to whom ego is connected. (In a personal network, an ego is a focal actor and the alters are the set of actors who have ties to ego.) Those analysts who followed Bourdieu’s lead retained his emphasis on ego’s access to others’ resources. They typically examined the resource of occupational status and how the information and influence given by alters in high positions within hierarchical social structures could facilitate ego’s job search (Bian, 1997; Boxman et al., 1991; Flap & Boxman, 2001; Lin, 2001a; Renzulli et al., 2000). In the same vein, but with a less common perspective, was a study of the benefits to a corporation that utilized its employees’ social capital to reduce the screening costs in hiring new workers (Fernandez et al., 2000). James Coleman (1990, pp. 300–321) championed a second approach to social capital, defined by its function of facilitating certain actions of individuals within a social structure. He emphasized the obligations and expectations, norms and sanctions, trust, and authority relations that arise from social network connectedness. This connectedness is purportedly greater with dense, strong ties and network “closure,” that is, when a group of actors is tied only to others in the group and all ties within the group are characterized by high levels of communication and emotional bonds. Those analysts who followed Coleman’s lead typically studied the value of this type of social control in improving the school performance of children (Coleman, 1988; McNeal, 1999; Morgan & Sorensen, 1999; Sampson et al., 1999; Teachman et al., 1997) or in greater collective benefits to a local community (Hagan et al., 1996; Putnam, 2000; Rosenfeld et al.,

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2001). Less common were studies within corporations showing that workteam cooperation requires coworker’s goodwill and emotional support, and that these social networks benefits are manifested in enhanced work performance, higher employee morale, greater job satisfaction (Flap & Volker, 2001), stronger organizational commitment, and creative solutions to organizational governance issues (Lazega & Pattison, 2001). A third approach to social capital, by Ronald Burt (1992, p. 12), shared aspects of its two predecessors, defining it as both “the resources contacts hold and the structure of contacts in a network.” Ego’s network is access to people (who) with resources, while the network is itself a form of social capital (how). Yet, Burt admitted to ignoring the question of “who” in favor of “how” and addressed the issue with a distinctive social capital measure that he labeled “structural holes.” Based on network brokerage ideas, structural holes are the separations between nonredundant contacts that provide ego with access to information and control opportunities because of unique connections not available through others. Ego’s social capital is created by a network in which ego can broker new connections between otherwise disconnected alters. In this way, Burt’s definition combines access to alters’ resources of information and referrals with the social control aspects of certain network structural configurations. Studies utilizing Burt’s social holes approach had mixed results. Flap and Volker (2001) found that this type of brokerage structure had negative effects on employee satisfaction. Ahuja’s (2000) study of innovation in the chemical industry (measured by patent counts) discovered that having many structural holes was actually associated with a reduced innovation output, but that increased innovation was associated with the high-density ties described by Coleman’s approach. However, Hargadon and Sutton (1997, p. 716) found that “technology brokering” of the kind obtained by locating near structural holes was the primary reason for the success of a U.S. product development firm. Reagans and Zuckerman’s (2001) study of R&D teams concluded that higher team productivity was related to both higher closure (measured by frequency of team communication) and to higher network heterogeneity (measured by the extent to which teams members communicated with colleagues who were outside the team’s organizational tenure distribution). Part of the conflict in the empirical evidence may stem from a lack of full understanding about the mechanisms of social capital. The aforementioned approaches all agree that social capital promotes favorable outcomes by: (1) facilitating flows of information, knowledge, and expertise; (2) exerting influence on agents; (3) certifying credentials; (4) giving emotional support (Lin, 2001a); and (5) providing material resource sharing for costly projects. But, agreement on the beneficial consequences of social capital is easier to come by than is consensus on exactly what constitutes social capital and how it works. To resolve the differences among

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these approaches, analysts might be tempted to define social capital, following Erickson (2001, p. 127), “in the widest sense as the useful aspects of social networks.” Both access to resources and social control of behavior are clearly useful aspects of social networks. But, especially in the hierarchical structures of typical corporations, this definition only adds to the rampant conceptual confusion because authority structures blur important distinctions between the unique benefits of resources and the benefits of social control. Is authority social capital because of it gives an ego better access to the resources of information and influence attached in those positions? Or is authority social capital because it gives greater social control? Taking our lead from organizational theories, we believe that access to resources is the key feature of action within organizational environments, and that the normative aspects of social networks must be considered apart from the concept of social capital. Two definitions within the Bourdieu tradition particularly capture the importance of resources and how they are accessed. Lin (2001b, p. 12) defined social capital as “resources embedded in a social structure which are accessed and/or mobilized in purposive action,” where he defined resources as material or symbolic goods. Lin broke resources into three dimensions: resources embedded in a social structure (embeddedness); accessibility (opportunity); and use. Similarly, Flap and Boxman (2001, p. 168) defined social capital as “the product of: (1) the strength of tie; and (2) the resources of alter, summed over all network members.” They further explained their concept by defining strength of tie as the extent to which alter is prepared to help ego measured as the unweighted sum of four elements: length of time of acquaintance; frequency of contact; intensity of content (kin and friends > others); and frequency of ego’s services to alter (indebtedness). We agree that the emphasis on resources is central in social capital, yet feel much may be gained by including a concept to capture the uncertainty of social relations. Beginning with Granovetter’s (1973) seminal article on the strength of weak ties in accessing information in a job search, much social capital research has examined social tie effects on ego’s access to alters’ network resources. Stronger ties reflect greater intimacy of relationship, more network closure, and a greater willingness of alters to help ego. In contrast, weak ties reflect casual relationships, nonredundant connections, and better access to more numerous and varied resources. Yet, despite the apparent social capital gains that ego could make by using weak ties, studies showed that seeking out nonredundant contacts goes against individual motivation (Mizruchi & Stearns, 2001). The greater the uncertainty of the surrounding social environment, the more people tend to rely on their strong ties (Burt, 1992; Gulati & Gargiulo, 1999; Podolny, 1994). To give a realistic account of how people actually behave in their social relations, the definition of social capital must take into account this probabilistic nature of

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ego accessing the resources of a given alter. Therefore, we define an ego’s social capital as the product of the resources controlled by an alter times the probability that ego could gain access to those resources, summed over all the alters in the ego-network. Resource is the total quantity of goods, services, or information sought by ego that alter controls. The probability of access is ego’s subjective belief about the likelihood that alter will make those resources available for ego’s use upon request for assistance. Formally, ego’s calculation can be expressed as: SCi =

J


R j p ji

j=1

where SCi is ego i’s social capital; Rj is the total resources controlled by alter j; pj is ego’s perceived probability of access to use alter j’s resources; and summation occurs across all J alters to whom ego is directly tied. (The calculus could be easily extended to include second-zone contacts, that is, alters’ alters.) Ego’s subjective probability of access varies from 0 to 1.00, depending on several factors including environmental uncertainty, strength of tie, and strength of location (a term coined by Lin (2001a) to connote Burt’s concept of unique control by structural holes). Thus, our social capital definition draws equal attention to the determinants of whether ego obtains access to resources through social network ties and to the resources themselves, critical to any complex collaboration. By clearly separating alters’ resources from ego’s likely access, we can analytically parse the effects of hierarchical authority structures, flatter workteams, and interorganizational interactions, which were confounded in previous definitions of social capital.

A THEORY OF COMPLEX COLLABORATION This section presents our theory to explain the role of social capital in the complex collaborative relations of interorganizational workteams. After discussing the theory’s scope conditions and assumptions, we state a set of interconnected propositions about factors that affect the ability of a team to access its members’ social capital for use in a project task.

Theoretical Scope and Assumptions The theory’s basic unit of analysis is an interorganizational team whose members are employed by two partnering organizations and are assigned to a joint project

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Fig. 1. Network Relations in Collaborative Teams.

with a single task or goal to be accomplished within a limited period. This narrow theoretical scope could be expanded to encompass teams drawing their participants from multiple partners. More formally defined, a workteam: consists of two or more natural persons, some of whom are employed by a least two autonomous organizations, who identify themselves as members of a work unit; is recognized as a distinct collectivity by others; is constituted for some specific purpose/goal; and remains stable for a delimited period after which it disbands. A typical workteam is an informal arrangement between partner organizations to allocate employees and resources from each of the parent organizations to the project. We exclude formal joint ventures, which involve creating a new organization with its own board of directors and equity. Figure 1 depicts the main relationships in a simplified network graph. Two partnering organizations, Parents A and B, each send some employees to a Workteam. These team members remain employees of their respective organizations and retain work ties to some employees (Alters) at the parents. The Workteam is labeled “(Ego)” because our theory treats the team as a unitary actor in its relationships at both the organizational and individual levels of analysis. A common example of a workteam is a product innovation-oriented, research and development project involving employees of a pharmaceutical corporation and a biotech startup company (Powell et al., 1996). The theoretical scope

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also encompasses teams charged with accomplishing other types of innovative changes, such as an intergovernmental commission, whose members are industry representatives and public agency bureaucrats, that is designed to achieve specific regulatory reforms. Other examples of workteams covered by the theory include: the consortium of European aerospace manufacturing firms that built the Concorde supersonic transport plane; an urban gang strike force whose members come from different law enforcement agencies; and a committee of nonprofit organizations created to investigate and eliminate redundancies in service delivery. Falling outside the theory’s scope conditions are collectivities lacking either interorganizational participants or impermanence. Examples include interdepartmental project teams within a single corporation that use a matrix form of dual authority lines, nonprofit national federations with semi-autonomous chapters, such as the Boys and Girls Clubs, and permanent bodies that coordinate fundraising campaigns, such as the Community Chest and United Way. Our theory of social capital in complex collaborations makes several assumptions about how the parent organizations form a workteam. First, the project goal has a limited life and is not structured as a formal joint venture with equity stakes by the parent organizations. Under these circumstances, the pyramidal authority structure and established policies and procedures typical of a bureaucracy are absent within the team (although they may exist within the parent organizations). Thus, informal social networks become all the more important to accomplishing the workteam’s project goal. Second, all fiscal, material, and human resources allocated from the parent organizations to the team become project-specific assets, that is, the workteam decides how to use its resources, although it remains accountable to the parents for the ultimate project outcome. We note that information does not become a project-specific resource because information is unique in not being consumed through use: if one social actor transmits information to a second actor, the first actor can still use it. Third, team members behave as agents of both their organizations and the team. Team members remain employees of their parent organizations yet act on behalf of the workteam; hence, actions of individual members should be considered actions of the team. A fourth assumption is that team members are not self-interested individuals; that is, they don’t pursue personal goals apart from their team tasks. We recognize that this absence of opportunism may not always be realistic, such as when a team member pursing promotion within her parent organization comes into conflict with the workteam objectives. However, to make the theory tractable, we ignore all complications that might arise from personal motives and actions that diverge from the project goal. In most cases, a workteam’s social capital can be treated as simply the sum of its individual members’ social capital. However, we cannot assume that direct

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aggregation is always the case; rather, sometimes the team social capital may be greater or smaller than this total. For example, if the mix of team members is particularly synergistic, the team may collectively garner more prestige than would expected from a simple addition of individual member prestige. Consequently, the team’s social capital exceeds the sum of the members’ social capital. An example might be a project that draws its team members from diverse backgrounds for a particularly innovative project of high visibility and cutting-edge technology, which could be perceived as enhancing the careers of those persons associated with the project. Likewise, workteam social capital may be less than the sum of members’ social capital if a team project acquires a bad reputation that decreases its total access to resources below the amounts that would otherwise be available to individual members.

Theoretical Propositions The two assumptions and eight propositions comprising our social capital theory of team collaboration address the mechanisms of how a team acquires social capital and how its greater social capital contributes to the success of the project goal. The schematic diagram in Fig. 2 shows the relationships among these propositions. Propositions 1–5 flow directly from the definition of social capital as the product of two components: (1) the resources controlled by an alter in ego’s network, multiplied by; (2) the probability of that ego accesses those resources; then (3) summed over all the alters in ego’s network. Treating a team as a unitary actor, its set of network alters is composed of all the alters to whom the team members are directly connected. We make an initial assumption, based on our definition of social capital, concerning the resource component of team social capital: Assumption 1. The greater the aggregated resources held by all the workteam members’ alters, the higher the team social capital. If every alter’s resources were equally accessible, then a team whose alters hold more resources will have higher social capital than teams with fewer or resourcepoorer alters. In many cases where alters are other employees of the project team’s parent firms, those alters’ resources are constrained by the financial and technological limitations of the parent organizations. An important implication of this assumption is that alters contribute to a team’s social capital only to the extent that team members collectively possess full information about all alter’s resources. If the team is unaware of potentially useful resources held by any alter, then essentially fewer resources are available and subsequently the team’s aggregate social capital is smaller than if all resources were completely and accurately identified.

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Fig. 2. Schematic Diagram of Propositions.

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Our second assumption, also based on our definition of social capital, concerns the probability of access component of team social capital: Assumption 2. The higher the probability of access to the aggregated resources held by all the workteam members’ alters, the higher the team social capital. Given the same resources, the team that can access and mobilize those resources will have higher social capital, or taken the opposite direction, all the resources in the world will do no good unless the team can gain access to them. This consideration is key in understanding the mechanisms of how the resources of the team’s alters actually become resources of the team. The first five theoretical propositions disaggregate this second assumption about team social capital, indicating factors that seem likely to increase the probability that a team could access its alters’ resources for use in pursuit of the project goals: Proposition 1. The greater the number of prior reciprocal exchanges between a workteam and its alters, the greater the probability that the team will gain access to its alters’ resources. Proposition 1 emphasizes that a team builds social capital through a series of mutual resource exchanges between alters and team members extending through time. For example, a team member previously may have established a relationship with an engineer in the parent organization in which they exchanged information and technical advice. As the frequency of such ego-alter exchanges increases over time, we envision these dyadic pathways becoming well-worn and familiar, a habit making future exchanges easier and more comfortable. In addition, feelings of friendship and empathy may grow with these exchanges, making future interaction pleasurable and more likely. This idea has been documented in studies of how trust is built through continual reciprocal exchanges and in research on the importance of trust in business relations (Guseva & Rona-Tas, 2001; Ring & Van de Ven, 1994; Uzzi, 1997). The well-worn paths of these trust relationships provide a counterbalance to the cynical opportunism about which Williamson (1981) wrote. Proposition 2. The more strong locations that a workteam occupies, the greater the probability that the team will gain access to its alters’ resources. Nan Lin (2001a) defined the strength of location in a network by an actor’s proximity to a bridge between distinct network components: the closer an ego is to a bridging tie, the stronger its location. Ronald Burt (1992) operationalized this concept using a measure of structural holes or network constraint. Team members employed by Parent A may have bridging connections to unique alters employed at that parent, thus increasing the probability that the entire workteam could gain access to resources available in that organization. Of course, the team

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members employed by Parent B may also occupy equivalent bridging positions, thereby increasing the probability of accessing that parent’s resources for the project goal. Hence, the higher the proportion of team members who are situated at strong network locations, the more resources the team should be able to obtain from alters, hence the greater its social capital. However, we note that this social capital mechanism might turn into a social liability (Leenders & Gabbay, 1999), for example, if team members perceive that proprietary information of Parent A were unfairly accessed by Parent B through its employees on the workteam. Proposition 3. The less willing a workteam is to incur exchange debt, the lower the probability that the team will gain access to its alters’ resources. Although debt aversion might reflect the aggregated risk-oriented personalities of team members, Proposition 3 mainly emphasizes that team debt aversion results from a collective team perception that it will be unable to reciprocate the obligations created by using alters’ resources for project goals. In other words, the team prohibits its members to ask for help from alters at the parent organizations because the team would be either unwilling or unable to pay back those debts. This debt avoidance may be a particularly difficult problem for collaborative projects that have low priority at both parent organizations, because the team’s resource scarcity lessens its capacity to reciprocate for any aid given by parental alters (Lin, 2001a). Proposition 4. The higher a workteam’s prestige, the higher the probability that the team will gain access to its alters’ resources. Prestige is defined as prominence within a network of asymmetric relations, that is, ties directed to an ego from its alters (Knoke & Burt, 1983). For example, an employee to whom coworkers turn for work advice, but who never seeks their advice, has high prestige in an advice-giving network. Workteam prestige is an aggregation of the work relations directed to the team members from its alters employed at the parental organizations. Several studies of innovation in high technology environments (Podolny et al., 1996; Powell et al., 1996; Stuart, 1999), showed that higher organizational prestige, measured by the number of patent citations received by a firm, predicted the likely future innovation rate. The general conclusion is that organizational prestige both reflects and is a primary determinant of organizational abilities to gain access to critical resources. Proposition 4 expects similar prestige effects in complex collaborations, not only because parent organizations initially allocate more resources to high-priority workteams, but also because the prestige associated with such technological projects leads to a higher likelihood that the team can gain access to additional resources held by its alters in the parent organizations.

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Proposition 5. The stronger a workteam’s ties to alters, the higher the probability that the team will gain access to its alters’ resources. Tie strength indicates the degree of intimacy and emotional commitment in a network relationship, with stronger ties indicative of a subsequently greater willingness by alters to help ego. Flap and Boxman’s (2001) factors of length of time of acquaintance, frequency of contact, and intensity of content (where ego has more intense interactions with kin and friends than with acquaintances and strangers) provide measures of tie strength. Network theorists and researchers have emphasized that strong ties typically provide ego with a smaller range of diverse resources than weak ties. For example, job-related information tends to be highly embedded within strongly interconnected social circles, but job-seekers who mobilize their weak-tie contacts can obtain more useful information via their less-intimate alters and friends-of-friends (Granovetter, 1973; Lin, 2001a; Renzulli et al., 2000). Proposition 5 provides a method of parsing out the two separate effects of tie strength and resources. Assuming that all alters possess equivalent resources, a workteam obtains more social capital through its members’ strong ties to alters in the parent organizations because strong, intimate ties increase the probability of access. However, this proposition should not be taken to imply that in the end strong ties will necessarily result in greater resources for the team than weak ties. Whether weak ties with greater resources or strong ties with fewer resources will result in greater social capital depends on the resources and the tie strength (probability of access) of the actual collaboration. The final theoretical propositions about complex collaboration concern three general mechanisms through which greater social capital affects a workteam’s chances for a successful project outcome. These expectations follow from resource dependence theory, which emphasizes the critical importance of resources for successful organizational and project outcomes. Workteams that obtain more social capital from their network alters can leverage these resources to enhance the project’s prospects for a successful outcome. Proposition 6. The greater a workteam’s social capital, the more resources the team will acquire from its alters. Proposition 6 affirms the commonplace notion of the rich getting richer. Team social capital is the aggregation of information, money, expertise, political influence, and other resources held by all alters that would likely become available for the team’s use on its project. The volume of resources indicates both larger quantities and higher quality of resources crucial for a project’s chances of success, including but not limited to: access to more numerous and more highly skilled technical expertise, enhanced project management software and tools,

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superior scientific and technical information, utilization of production facilities, and priority in production scheduling. Although we present the Proposition 6 as a linear relationship, at some point the marginal increments to success provided by additional alter resources will probably diminish as “resource crowding” occurs. Proposition 7. The greater a workteam’s social capital, the more financial resources the team will obtain from its parent organizations. Interorganizational projects can be usefully viewed as mini-corporations and, as with a workteam’s parent firms, sufficient financial capitalization is essential to the viability of any project. Initial budgets often turn out to be inadequate once a project gets underway and unforeseen obstacles and delays arise. The more social capital that a team obtains from its alters, the better its chances of leveraging additional funds from the parent firms. This mechanism involves the political mobilization of the team’s supporters to lobby the parents to open their purse strings. For example, team members might cash in some IOUs acquired during earlier social exchanges with their alters, persuading the alters to contact their alters throughout the parent corporations on behalf of the team. The more influential a workteam’s network, the greater likelihood that those friends-of-friends would assist the team in lobbying for supplementary budgetary allocations. Proposition 8. The greater a workteam’s social capital, the more efficient the team members’ interactions. Workteam efficiency is defined as achieving the project’s goals with actual direct costs plus transaction costs falling below anticipated expenditures (e.g. coming in on time, under budget, and meeting quality specs). An efficient team makes the optimum feasible allocation of its available resources among project tasks. A team with high social capital can achieve greater efficiencies than a low-social capital team because its numerous alters provide resources that enable faster external communication, better coordination between the team and its parent organizations, reduction of monitoring and supervision costs, and quicker responses to correct unforeseen problems.

CASE EXAMPLES Three case studies of workteams offer an opportunity to observe how these propositions translate to reality. The first case studied the supply chain improvement program implemented by Mayflower Vehicle Systems, a first tier supplier of the United Kingdom automotive industry (Tilson, 2001). Concerns about vehicle manufacturer’s moves towards shared production platforms and the procurement

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of larger orders from fewer suppliers to achieve economies of scale raised concerns about the need to lower prices and raise quality standards. In response to these concerns, the government-led Accelerate Initiative provided financial assistance to first tier companies to collaborate with groups of eight of their own suppliers, along with technical assistance from an external consultant, the Society of Motor Manufacturers and Traders’ Industry Forum. Two improvement projects were carried out by Mayflower: the first involved the laser production of panels for Rolls-Royce and Aston Martin; the second, the production of the grill and mesh surrounds for Agco’s Massey Ferguson tractor fronts. The projects initially prompted feelings of distrust: “There was a bit of ill feeling between the two groups at first. We were saying things but they had already put their (ideas) in place and done it, and we were suggesting something else. . . . It was like we were coming in and spying” (Tilson, 2001, p. 437). “I was sat there the first week or so thinking ‘What am I going to get out of this? OK, I can make a statistic out of a statistic, but what benefit am I going to get from it?’ So at first I was coming back [to our company] and saying to the MD ‘I can’t see what we’re going to get from this. This isn’t going to be any good to us’ ” (Tilson, 2001, p. 438).

However, as the project progressed, the exchange of ideas began to pay off in the form of problems solved and improvements on the shop floor, with one team member commenting, “You could actually see benefits working for you” (p. 438). Tilson concluded that “the benefit of the cross-fertilisation of ideas and sharing of information and expertise were five-way: from supplier to host, host to supplier, and supplier to supplier, and also from Industry Forum to both host and supplier, and that “reciprocity emerges as a critical success factor for nurturing conditions of trust” (pp. 441, 443). Her conclusion gives evidence for our Proposition 1, the importance of the number of prior reciprocal exchanges between a workteam and its alters for continuing access to resources. Tilson also noted the importance of “champions” within the team to “provide support and a steer when needed, to ensure that adequate resources were available, and to remove any political blocks which prevented the smooth operation of the team” (p. 436). These champions provided the team with the strong locations of Proposition 2, which also increase access to resources. The second case analyzed the use of project teams as a means of restructuring research and development in the pharmaceutical industry (Zeller, 2002). As a result of the challenges of longer development times, tremendous increases in R&D spending, and a proliferation of new technologies, pharmaceutical corporations introduced cross-functional project teams to speed up the development of new drugs from discovery to market. Zeller studied both the merger of Ciba-Geigy and Sandoz (each based in Basel, Switzerland) into Novartis, facilitated by hundreds of project teams composed of managers from both Ciba-Geigy and

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Sandoz, as well as subsequent collaborations between Novartis and biotechnology firms. He found evidence for the importance of personal linkages allowing “the development of shared perceptions and the formation of mutual trust” in both types of collaborations (p. 277). Especially interesting was the comparison between the collaboration of Novartis with Hamburg-based Evotec Biosystems and the collaboration of Novartis with Massachusetts-based Vertex Pharmaceuticals. The collaboration with Evotec was to develop the miniaturized and automated high-throughput technology, Evoscreen. Zeller observed that “the collaboration progressed with an intensive exchange of knowledge between both partners,” and “the successful outcome was based on personal relations and business agreements which also took the form of common project teams” (p. 284). Again, the presence of a “champion” was particularly important, especially for Evotec who, in a position of lower power, needed someone in a strong location in Novartis, who could smooth the flow of resources to the project team. With Evotec’s awareness that knowledge could unintentionally flow to its partner, reciprocity of knowledge flows was again important to ensure the trust that enabled resources to continue to flow. The collaboration with Vertex Pharmaceuticals to develop small molecule drugs directed at targets in the kinease protein family was very different. The negotiations before the signing of contracts lasted about six weeks and Zeller concluded that behind the facts of the contract evolved “contradictory social and power relations ranging from trust to control” (p. 285). Despite joint teams and meetings, no researchers were exchanged because Vertex did not want Novartis’ researchers “to have access to information relating to other partnerships” (p. 285). These two opposite approaches to collaboration are probably in part due to corporate culture differences between Europe and the United States and give support to our Proposition 5, the idea that strong ties raise the probability of access to resources. A final case is Walker’s (2002) analysis of the National Museum of Australia construction project, which used a procurement approach that was “both innovative and intended to provide a best practice exemplar project for the 21st century” (p. 16). The Acton Peninsula Project alliance team was surveyed and interviewed extensively during the two-year project, and compared to Business-As-Usual (BAU) results from previous projects. Survey results for the Project alliance team were superior in every instance, and Walker detailed his conclusions about the reasons for the positive results. One factor he identified in poor projects is a “commitment gap” where lack of commitment by leadership and a “what is in it for me or my organization syndrome” diminishes motivation (p. 22). The “help gap” of insufficient quality or quantity of help reduces effective team action. Survey results indicated that, for this construction project, benefits were clear and motivating, and colleagues provided help through informal mechanisms.

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The results again give support to our Proposition 1 about the importance of reciprocal exchanges for continued resource flows. A second factor that Walker identified was that the project’s exemplary nature as a pioneering exercise provided an inherent reason for its success: “People working on that kind of high profile project would naturally feel pride that engenders and supports enthusiasm and commitment” (p. 29). This statement supports Proposition 4, the higher a workteam’s prestige, the higher the probability that the team with gain access to its alters’ resources.

CONCLUSION How do participants in complex collaborations resolve ambiguities and build effective workteams – or fail to build effective teams? The central importance of resources is not new, surely no surprise to experienced interorganizational project managers. Yet, how it is that a team with fewer potential resources can outperform other teams with greater potential resources? Our social capital theory tries to answer this critical question through its emphasis on resources and the uncertainty of social relations. By defining social capital as the product of resources controlled by an alter times the probability that ego could gain access to those resources, summed over all alters in the ego-network, we analytically separated the quantity of alter resources from ego’s likely access. Our approach suggests that, beyond the obvious importance of resources, lies the key factor of the probability with which the team can gain access to those resources. That probability is shaped by several social network variables: the number of prior reciprocal exchanges with team alters; the number of strong locations occupied by team members; the degree of debt aversion of team members; the workteam’s prestige; and the strength of ties between team members and alters. These factors combine with the volume of alter resources to constitute a workteam’s social capital. In turn, greater team social capital raises the chances of a successful project outcome through three mechanisms: use of alters’ resources, additional financial resources from parent firms, and efficient team interactions. In addition to providing an understanding of complex collaborations, our theory explains how social capital achieves the results in the studies cited above and can serve as a basis for resolving the conflicts among these results. Yet we realize this picture is incomplete. One further issue may be additional interaction effects of environmental uncertainty on probability of access. Researchers have shown that, despite the advantages gained in accessing a wider range of resources through weaker ties, under conditions of greater uncertainty, people tend to draw on their stronger ties more often than their weaker connections (Burt, 1992; Gulati &

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Gargiulo, 1999; Mizruchi & Stearns, 2001; Podolny, 1994). In their study of strategic alliances by American, Japanese, and European new materials, automotive products, and industrial automation firms, Gulati and Gargiulo (1999) found that the more complex the networks (measured by the degree of network centralization), the more were organizational decisions guided by considerations of previous good relations and less by anticipated resource gains, even to the point of firms relinquishing resources in favor of sustaining their prior network connections. In other words, the greater the alliance uncertainty, the more likely organizations were to tap their strong connections; whereas, under conditions of lower uncertainty, connections were made through weaker ties providing greater economic benefits. These studies imply an interaction or contingent relationship: the effect of tie strength on probability of team access to alters’ resources (Proposition 5) depends on the degree of project uncertainty. Further, following Burt’s (1992) argument that structural holes obtain their advantage through the uncertainty that is created by the lack of knowledge of resources in otherwise unconnected groups, an interaction also probably occurs between strong locations (Proposition 3) and project uncertainty. That is, the greater the project uncertainty, the greater the effect of strength of location on probability of access to resources. Indeed, project uncertainty may condition every proposition about the probability of team access to alter resources. Our social capital theory of complex collaborations could easily be modified to anticipate and accommodate such intricate relationships.

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MANAGING VALUE AND VULNERABILITY IN COMPLEX COLLABORATIONS: ALLYING WITH COMPETITORS Joseph P. McGill and Michael D. Santoro ABSTRACT We examine collaborative complexity arising from strategic alliances among competitors. In high technology industries, rapidly evolving and modular technologies increase the likelihood that collaborative alliances will develop between partners who also compete with one another. Partnering under these conditions involves choosing collaborative structures that foster the transfer and integration of some resources, while simultaneously protecting other resources from unintended transfer. Using resource-based, transaction cost, and industrial organization economic theories we develop a model to depict the risks and rewards of collaboration under different modes of competitive interdependence. Two dimensions underlie our conceptual model: resource interdependence and competitive interdependence. Resource interdependence is the degree of integration needed for the resources contributed by alliance partners as reflected in the nature of the resources and their cospecialization. Competitive interdependence gauges the similarity between partners in their overall strategic capabilities and customer markets. We

Complex Collaboration: Building the Capabilities for Working Across Boundaries Advances in Interdisciplinary Studies of Work Teams, Volume 10, 263–286 Copyright © 2004 by Elsevier Ltd. All rights of reproduction in any form reserved ISSN: 1572-0977/doi:10.1016/S1572-0977(04)10010-1

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conclude with a discussion of the contingent use of inter-organizational structures to enable partners to balance resource contributions and resource protection in collaborative-competitive relationships.

INTRODUCTION By any measure, the last few decades have witnessed an unprecedented rate of technological innovation from inter-organizational collaborations across government, university, and business organizations (Moore & Simon, 1999). In particular, strategic alliances, defined as ongoing inter-organizational relationships involving the exchange of resources, have increased dramatically in the last twenty years. In 2000 alone an estimated 10,000 alliances were formed worldwide (Schifrin, 2001). Many alliances are focused on the exchange, creation, and development of knowledge-based capabilities, highlighting the expectation that collaborations are a useful way for partners to leverage resources and acquire new capabilities. Fostered by cooperative research legislation in 1984 and 1993 that encouraged intra-industry collaborations, technology alliances at the end of the 1990s had grown 69% over the previous decade (National Science Board, 2002). In this chapter we focus on the value and the vulnerabilities created through collaboration with competitors, that is, collaboration between business firms with similar strategic resources and customer markets. Inter-organizational collaborations are of course not limited to business firms, for example, substantial collaboration occurs in government-university-industry alliances and government-industry research contracts (Duysters & Hagedoorn, 2000; Santoro & Gopalakrishnan, 2000). However, to explore the interesting and complex situation of collaborating with a competitor, we narrow our focus to alliances between commercial firms. We begin by exploring how alliances generate both value and vulnerability, and then examine collaborative and competitive dynamics from three influential perspectives: transaction cost economics (TCE) (e.g. Williamson, 1985); the resource-based view of the firm (RBV) (e.g. Barney, 1991; Wernerfelt, 1984); and industrial-organization economics (IO) (e.g. Porter, 1980). We conclude by discussing a contingency approach to the use of collaboration structures when partners are also competitors. Figure 1 depicts a typology of collaborative complexity according to the twin dimensions of resource interdependence and competitive interdependence. We elaborate on this model as we examine unique combinations of resource and competitive interdependence, and address implications for the choice of collaborative structure and for the creation and capture of value.

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Fig. 2. Relationships Among Key Variables.

To help clarify our typology, Fig. 2 shows the direction of relationships among resource interdependence, competitive interdependence, collaborative complexity, collaborative structure, and value creation and protection. In the following sections we begin with a discussion on the three influential theoretical perspectives that are the focus of this work and their role in strategic alliances. We then elaborate on our proposed typology of collaborative complexity.

VALUE AND VULNERABILITY IN COMPLEX COLLABORATIONS All firms strive to develop or acquire capabilities, which we define broadly as valuable know-how embedded in organizational routines. A rational firm will seek capabilities that provide it with strategic advantages over its competitors, for example, by achieving unique production efficiencies or by being the first to develop or commercialize innovations. Being knowledge-based, the development of capabilities requires a cumulative and path-dependent process of learning through experimentation and experience. Unfortunately, the dynamic competitive environments that characterize high technology industries often require rapid adjustment and development of new capabilities. Significant commitments of time, resources, and attention are needed to build capabilities internally, and this is problematic (Dierickx & Cool, 1989; Teece, 1986). As an alternative to internal development, a firm could seek capabilities through merger and acquisition activity. However the nature of a capability, as something that is embedded in an organization’s routines, makes it difficult to evaluate in advance of an actual acquisition (Barney, 1986). The value of a capability depends upon how easily it can be extracted from a target firm and assimilated by an acquiring firm. Experience shows that acquiring firms using mergers or acquisitions to obtain new capabilities often pay large premiums over the eventual value of the targeted capabilities. Although shareholders of the targeted firms

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might find that their share prices have increased, the acquiring firms fail to achieve strategic and financial objectives in a majority of cases. Studies of merger and acquisition activity show substantial failure rates, reinforcing the finding that difficulties in integrating distinct organizations and cultures frequently result in the destruction of the very capabilities being sought (Madhok, 1997). For these reasons, alliances are attractive options because partners can simultaneously retain control over capabilities while exchanging the know-how that is unique to each partner. Alliances enable partners to exploit the resources they have, acquire new capabilities (Koza & Lewin, 1998; Park et al., 2002; Sakakibara, 1997), and access new markets (Kogut, 1988; Nohria & Garcia-Pont, 1991). In general, alliances provide an attractive alternative to partners who wish to obtain resources and capabilities without the delays and costs of in-house development or the uncertainty of acquisitions. In spite of their attractiveness however, alliances are exchange relationships, and each partner can be expected to try to optimize its contributions and gains from the relationship. There is an inherent tension between cooperating on one hand, and risking unplanned expropriation of one’s capabilities on the other. A partner’s capabilities are especially vulnerable to unintended transfer in alliances involving the development or exchange of tacit knowledge, because of the close cooperation and integration usually fostered in these alliances among research and development team members. Further risks arise when collaborating firms are also current or potential competitors, a frequent occurrence given the modularization and convergence of many technologies and competitive markets. Modularization of technological systems occurs when the evolution and diffusion of a technological architecture enables the creation of standards for the use and substitution of components (Garud & Kumaraswamy, 1995). Eventually, technologies that once emerged as proprietary architectures become diffused through codification of knowledge in forms such as interoperability standards, patents, and licenses. In industries with modular technological architectures, firms may choose to compete in certain architectural components, while cooperating in others. Alliances among competitors often appear around modular architectures, resulting in the formation of alliance constellations that share in the development of new capabilities and a dominant design (Gomes-Casseres, 1996). For instance, the original proprietary control of system architecture in personal computing (e.g. IBM, DEC) has evolved into a highly modular arrangement where software, processing, storage, and input/output devices are provided by a number of firms that may collaborate in one component area and compete in another. Another example, drawn from the communications industry, is the 2002 agreement between competitors Siemens and Motorola to embed Motorola’s wireless platform technology in hand held wireless products

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sold by Siemens. The modular nature of many high technology industries can quickly cause alliances to become complex arrangements requiring substantial management attention to the complementary nature of partners’ goals, resource contributions, and competitive vulnerabilities particularly as a dominant design is established and maintained. Indeed, the high failure rate of alliances is often traced to resource misalignment and misunderstandings between partners (Spekman et al., 1996), suggesting that both scholars and practitioners would benefit from attention to the interdependence of partners’ resource contributions and of their competitive positions.

ECONOMIC PERSPECTIVES Theory and research regarding the economic risks and rewards of strategic alliances have been greatly influenced by three streams: transaction cost economics (TCE) (e.g. Williamson, 1985); the resource-based view of the firm (RBV) (e.g. Barney, 1991; Wernerfelt, 1984); and industrial-organization economics (IO) (e.g. Porter, 1980). TCE suggests that handling transactions within a firm is preferred when the costs of market transactions and producing for markets are relatively high. By comparing the cost of transacting at arm’s length in the market with the cost of integrating the transaction within the firm’s organizational structure, TCE provides a cost-minimization rationale for inter-organizational cooperation. Controlling a transaction within the firm is especially preferred to contracting when specialized investments are made to conduct trade with a particular partner. It is often difficult and costly to write a contract that assesses market-based penalties for a partner’s failure to perform. Because specialized investments are not easily redeployed to other partners or other uses, partner-specific investments may not necessarily create the same value outside the transaction. When a firm does make specialized investments, economic returns depend on the firm’s ability to avoid a partner’s potentially opportunistic behavior, for example, haggling over prices or over the quality or quantity of the resources contributed to the collaboration. When partner-specific investment intensifies, so do the costs of specifying and enforcing an increasing number of contract contingencies, measurements, and penalties designed to guard against opportunism (Grossman & Hart, 1986). In general, the cost to manage a transaction rises with the risk of opportunism, since safeguarding against opportunism requires the investment of time and resources. The need to safeguard against opportunism often leads to the creation of “mutual hostage” arrangements, where partners may make reciprocal and specialized investments across a number of collaborative activities to create credible retaliatory threats. Alternatively, a firm may decide to integrate the transaction within the firm where organizational control precludes the possibility of partner opportunism.

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Alliances are a hybrid, i.e. they are neither a market nor organizational solution to the problems of opportunism (Williamson, 1991). Because alliances are ongoing agreements about mutual contributions and the ownership and distribution of gains, they provide durable incentives to act cooperatively rather than opportunistically (Das & Teng, 2000; Pisano et al., 1988). Because a successful alliance may lead to future collaborative activities, short-term opportunistic behavior may exclude a partner from future alliance opportunities. From the TCE perspective, an alliance creates value whenever it is a more efficient solution to the problem of opportunism than either contracting in the market or integrating the transaction within the organization. The resource-based view (RBV) provides an alternative perspective by viewing firms as bundles of resources, routines, technologies, and capabilities that are of significance when they are also valuable, rare, and difficult-to-imitate (Barney, 2001; Hamel & Prahalad, 1994; Wernerfelt, 1984). Organizational capabilities, or routines (March & Simon, 1958), differ between firms, and when capabilities provide superior coordination of behavior and resources they become valuable (Nelson & Winter, 1982). Capabilities involve the use of tacit knowledge by interrelated individuals and groups working in organizational-specific settings. Consequently capabilities are difficult to trade in markets and difficult to imitate (Barney, 1991). Competitive advantage is achieved when a firm is more adept than its competitors at renewing and reconfiguring valuable capabilities (Teece et al., 1997). In the RBV, alliances are a potential source of value because they enable the exchange of complementary capabilities and resources, often leading to new and unique resource combinations. Building knowledge is at the heart of the RBV, so it is not surprising that firms frequently cite the need to access new technologies as a key reason for forming alliances (Hagedoorn, 1993). The development of new capabilities from an alliance depends upon a partner’s existing knowledge assets and its absorptive capacity, that is, its ability to “recognize, assimilate, and commercialize knowledge information” (Cohen & Levinthal, 1990, p. 128). This underscores how a cumulative base of technological knowledge enables firms to detect opportunities not apparent to others, and leads to the formation of alliances between partners possessing related technological knowledge (Mowery et al., 1996; Stuart & Podolny, 1996). A contrasting view is provided by industrial organizational (IO) economics, in which industry structures develop over time as groups of firms recognize their growing competitive interdependence. The theme of path dependence runs through both the RBV and the IO views. Improvements in the unique capabilities of a firm (RBV) or in its intra-industry position (IO) depend on a process of path-dependent, incremental change. Alternative paths for a firm at a point in time are constrained by the firm’s current routines, coordinative capabilities, and tangible and intangible assets (Teece et al., 1997). As differences evolve among firms in the markets

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they serve and in their resource decisions, market power and profits in an industry become heterogeneously distributed. Firms competing with similar resources in the same markets tend to react similarly to competitive and technological changes, and so begin to recognize their interdependence (Porac et al., 1995; Reger & Huff, 1993). Interdependent firms cluster in strategic groups, and firms within these groups may coordinate activities in order to prevent overinvestment and to create competitive barriers for new industry entrants (Caves & Porter, 1977). More recently, game theoretic approaches to IO have been developed that examine the control of interdependence with suppliers and buyers (Brandenburger & Nalebuff, 1990). These approaches suggest that selective cooperation with competitors under conditions of rationality can reduce dependency on suppliers and spur demand for complementary products in customer markets. Although useful as analytical tools, game theoretic approaches assume that firms have an almost infinite capacity for strategic reorientation and a hyper-rational interpretation of strategic behavior. In fact, strategic decision making is only boundedly rational (March & Simon, 1958; Nutt, 1984), involving cycles of incremental decisions made under significant information and time constraints. In general the IO view suggests that partners may coordinate resource investments through cost-sharing and technology-sharing alliances, thus managing their competitive interdependence. Each of the three preceding theories is concerned with a logic of inter-firm cooperation, but each adopts a different focal point, i.e. the transaction (from TCE), unique firm resources (from RBV), and the industry (from IO). Although differences among the three in foci make these theories somewhat incommensurate at a general level, we believe that these three views can be usefully related in a discussion of the more limited case of collaboration under conditions of competition. For example, it may be particularly necessary for a firm to guard against opportunism (TCE theory) in an alliance involving co-specialized resources, when a partner has the motivation (competitive interdependence from IO theory) and the ability (absorptive capacity and learning, from RBV) to act opportunistically. In the next section we explore interdependence based on the resource contributions and the competitive positions of partners.

RESOURCE INTERDEPENDENCE IN ALLIANCES Broadly speaking, the purpose of any alliance is to employ and leverage resources to improve a firm’s competitive position. More specifically, alliances help firms to adapt to environmental change by exploiting existing resources and by exploring and developing new resources (Koza & Lewin, 1998; March, 1991; Mowery

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et al., 1996). A firm can use alliances to explore basic research or to investigate an emerging technology that might provide or preserve a favorable competitive position. Examples of exploratory alliances might include discovery or early stage investigations in biotechnology, or the development of plastic as a replacement for glass in the optical communications industry. Exploitative alliances, in contrast, focus on increasing the economic returns to existing resources, using collaborations such as manufacturing cost-sharing agreements, second sourcing agreements, and licensing. The adaptive purpose of an alliance, i.e. the exploitative or exploratory nature of an alliance, has important consequences for the types of resources contributed to the alliance and the way those resources are combined. For example, exploratory alliances focus on extending the boundaries of current capabilities, often requiring a deep integration and co-specialization of tacit, knowledge-based resources. Exploitative alliances involve utilizing existing resources in a way that increases economic returns to those resources. As examples, firms may pool similar resources in manufacturing to gain scale economies, or may find new markets for existing technologies through licensing. We define resource interdependence as the degree to which partners’ resource contributions must be integrated because of the resource type and the level of partner co-specialization. In our discussion of resource interdependence we address only those resources contributed by partners to the collaboration, rather than the entire set of resources that characterize particular firms and that may be used outside the alliance.

RESOURCE CO-SPECIALIZATION Resource co-specialization refers to the degree to which unique resource contributions of partners have been co-embedded in the collaboration, that is, the resources have been configured to complement a specific partner and are not easily deployed to alternative uses outside the alliance. A high level of resource co-specialization requires that the resources be coupled through close and frequent coordination between partners, which may involve the co-location of assets or the assignment of personnel from each firm to highly interdependent roles in the alliance (Teece, 1986). Since co-specialized resources can be combined to become valuable, rare, and difficult to imitate, they may enable partners to create and capture above average profits (Barney, 1991; Wernerfelt, 1984). Co-specialized alliances are difficult for competitors to duplicate because of unique, organizationally embedded combinations of knowledge, processes, and outcomes (Rowley et al., 2000). Co-specialized resources must be both complementary and partner-specific. Resources are complementary when partners “bring non-redundant, distinctive

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competencies to the partnership” (Hill & Hellriegel, 1994, p. 595). Resources are partner-specific when partners must mutually adapt resources in order to achieve the goals of the alliance. As an example, consider the 2001 alliance between CuraGen and Bayer Pharmaceuticals where both bioinformatics and pharmacogenomics expertise from CuraGen were integrated with Bayer’s unique expertise in compound development. By co-specializing complementary resources, Bayer and CuraGen have targeted discovery and development of small molecules for treating obesity and diabetes (Signals, 2001). An alliance may involve human co-specialization based on the relational routines established between partnering firms. As partners co-specialize resources, communication among personnel dedicated to the alliance increases, resulting in knowledge sharing routines that create value (Dyer & Singh, 1998). Cospecialization enables the transfer of market, supplier, and competitor information between partners, and individuals learn “who knows what and where critical expertise resides within each firm” (Dyer & Singh, 1998, p. 665). Co-specialized investments, partner-specific skills, capabilities, and routines therefore become a bilateral asset that is difficult for competitors to imitate because of the tacit nature of the routines and relationships between participants (Hamel, 1991). Co-specialized resources offer partners substantial learning opportunities, because partners often have adjacent functional or technological relationships (Dussauge et al., 2000). Learning in adjacent relationships occurs when a firm has a base of knowledge sufficiently related to that of its partner and therefore the firm is able to assimilate information gained through the alliance (Cohen & Levinthal, 1990). For instance, a firm concentrating in manufacturing may acquire knowledge of upstream R&D from alliances with its suppliers or downstream markets through alliances with its distributors. As an example of technological adjacency, consider the 1997 alliance in research and development by Cisco and Alcatel, in which Alcatel agreed to integrate Cisco’s data routing solutions in Alcatel’s public network architecture while Cisco agreed to integrate Alcatel’s private switching technology in Cisco’s data networking solutions. Each firm capitalized on complementary capabilities by positioning existing technologies in new markets. The degree of learning in an alliance depends in part on the intentions and self-interests of partners. Knowledge-based collaborations do not necessarily involve learning from partners, and in fact collaborations may result in divergence between partner knowledge bases rather than convergence (Mowery et al., 1996). Gauging whether a partner’s intention is to internalize or merely to access knowledge is important for decisions about collaboration structure, because some partners may collaborate specifically to expropriate new knowledge while guarding their own (Hamel, 1991; Inkpen & Beamish, 1997).

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Alliances that are not co-specialized may nonetheless provide value to partners. For example, partners may combine similar resources such as manufacturing facilities to share costs and achieve scale or scope economies, or may provide complementary resources that are not partner-specific by combining resources across functional areas such as manufacturing and logistics (Hennart, 1988).

RESOURCE TYPES Researchers have classified resources according to a variety of tangible and intangible characteristics such as physical assets, location advantages, human resources, and organizational and managerial capabilities (Barney, 1991; Williamson, 1985). We adopt the property rights approach proposed by Miller and Shamsie (1996) in which resources can be classified according to the property rights they entail. Firms are concerned with acquiring resources and the claims to residual profits that they entail, so the ability to establish property rights is an important factor in trading, acquiring, and protecting resources. In the property rights approach, property and knowledge-based resources are contrasted. Property-based resources (such as codified knowledge in patents, financial capital, physical resources, distribution channel contracts, etc.) involve rights that are enforced through legal institutions to prevent imitation or appropriation. Because property-based resources are clearly circumscribed, rights can be traded and sold among firms. In contrast, knowledge-based resources are tacit understandings among individuals about how things are done. Knowledge-based resources are embedded in communities of practice clustered in specific functional areas or technology fields, making the transfer of knowledge across boundaries difficult (Bourdieu, 1977; Carlisle, 2002). Particularly in dynamic high technology industries, there are lags in the ability to codify technological knowledge and so this knowledge is often transferable only through close coordination and integration of team members (Cantwell, 1991; March, 1991). Knowledge may have property rights, for example when the knowledge has been codified and can be transferred unilaterally (as with technology licenses). Because the knowledge can be transferred through non-complex arrangements, partners’ resource interdependence is lower. Property-based resources may be leased unilaterally or bilaterally by partners, such as second source manufacturing or cross-licensing agreements for existing products or technologies, entailing few if any resource interdependencies. Alliances involving property-based resources are more capable of specifying the costs, performance contingencies, and distribution of profits prior to beginning alliance activities (Bucklin & Sengupta, 1993). Another form of unilateral leasing is the investment of capital in an alliance

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by one partner in order to lock in options on potential returns (Bowman & Hurry, 1993; McGrath, 1997). In industries with potentially high but volatile returns, such as biotechnology, minority equity investments permit the investing partner to time any further investments, exit the collaboration if needed, or increase investments if the technology proves successful. Firms prefer the real option value of equity investments when technological uncertainty is high. Resource co-specialization and type have independent effects on resource interdependence. For example, resources may be co-specialized without being knowledge-based, as when partners co-locate manufacturing facilities and supply sources. Similarly, partners may contribute knowledge-based resources without partner-specific co-specialization, as with dominant design and standard setting agreements. We expect resource interdependence to be highest with co-specialization of knowledge-based resources and lowest when property-based resources are contributed with no co-specialization. Intermediate levels of interdependence occur when either co-specialization or knowledge-based resources, but not both, are contributed by partners. Together, resource co-specialization and resource type indicate the value of the resource combination, and the vulnerability of partners to unintended spillovers of knowledge.

COMPETITIVE INTERDEPENDENCE IN ALLIANCES The concept of competitive interdependence is rooted in IO economics (Caves & Porter, 1977), where differences in strategies, resources, and markets affect competitive dynamics among firms (Baum & Korn, 1996; Chen, 1996; Gimeno & Woo, 1996b; Peteraf, 1993). We define competitive interdependence as the degree to which a pair of firms possess strategically similar resources and compete in similar markets.

SIMILARITY IN STRATEGIC RESOURCES IO theorizes that because firms share strategic positions as members of strategic groups, members of powerful groups may act together to exert market power, erecting competitive barriers against both new industry entrants and industry incumbents in other groups (Caves & Porter, 1977). In the IO view, groupings of similar firms develop over time based on similar strategic choices for products and markets. Gradually, firms gravitate toward similar industry positions as they develop similar resource, capability, and scale and scope features (Cool & Schendel, 1988; Fiegenbaum & Thomas, 1990). Here, scope refers to the

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breadth or diversity of the markets served by a firm while scale indicates the capacity of a firm to obtain scale economies. Similar resource allocations are made across functional areas, for example, R&D, or manufacturing, or marketing. The similarity of a firm to its competitors in resources and markets is an important dimension of managerial decision making. Indeed, a firm’s managers often direct competitive actions against competitors that are most similar to the firm (Porac et al., 1995; Smith et al., 1997). Symmetries in resource commitments and scope also increase firms’ competitive interdependence and the intensity of their rivalry (Dierickx & Cool, 1989). However, these competitive symmetries may also confer benefits by enabling competitors to collaborate in areas that provide cost advantages (Gomes-Casseres, 1996). Alliances between firms possessing similar resources are likely to produce cost-sharing benefits in manufacturing, distribution, and other areas of commonality (Dussauge et al., 2000; Sakakibara, 1997). When resources contributed by alliance partners are symmetrical, partners are likely to reap mutual benefits through scale and scope economies. Coordination benefits may also arise in technology exchange agreements such as cross licensing. Initial technology investments are likely to produce uncertain and volatile economic returns, so technology exchange alliances create an opportunity for firms to avoid redundant investments and to exploit existing technology resources. Research has shown that technological similarity between firms is associated with an increased likelihood of alliance formation, when those firms have asymmetrical resources (Polodny & Stuart, 1995; Stuart, 1998). On the other hand, alliances between firms with similar bases of knowledge increase the risk that competitors absorb knowledge from the alliance and use it for competitive advantage.

COMPETITIVE MARKET OVERLAP Ideally, an alliance combines resources from two different firms leading to the maximum benefit for both partners while minimizing alliance management costs and the risks from opportunistic behaviors (Gomes-Casseres, 1996). However, there is persuasive evidence that alliances are more likely to fail than to succeed when opportunistic hazards and managerial conflicts are present between partners (Park & Ungson, 1997). Partners may be especially vulnerable when they participate in alliances with rivals, since each partner has only partial knowledge about the others’ ability to capitalize on the knowledge or capabilities gained through the alliance. Alliance partners often have parallel competitive relationships that influence collaborative outcomes. As an example, consider Taligent, formed in the early 1990s as a joint venture between Apple, IBM, and HP to develop a

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new operating system that would reduce these firms’ collective dependence on Microsoft. Among the factors contributing to Taligent’s failure and eventual dissolution in 1997 was that IBM and Apple hedged against opportunism by continuing in-house development of products that would compete with Taligent. Competition between alliance partners may lead to rivalry, which is distinguished by firms’ efforts to occupy mutually incompatible market positions – a zero sum game (Cool & Dierickx, 1993; Peteraf, 1993). When firms are rivals, they often experience reduced market power and lower profits. An alliance between partners who are also market rivals increases the risk of opportunism (Park & Ungson, 1997), especially when those market rivals have similar strategic resources (Gimeno & Woo, 1996a). However it is also the case that in highly concentrated, mature industries, it is possible for alliances between competitively similar firms to exchange information and coordinate competitive activities as with code-sharing alliances in the airline industry (Peteraf, 1993). Research supports the argument that alliances in mature industries are used not only to manage the uncertainty of market demand, but also to control the uncertainty of competitive interdependence among firms (Burgers et al., 1993). In high technology industries such as information and communication technology (ICT), bio-pharmaceuticals, and semiconductors, a large number of markets and technological niches make it likely that partnering firms will vary in resource and market profiles. Consequently, the degree of competitive contact between pairs of firms may vary widely. Multi-market competition between a pair of firms increases with the number of market domains shared and the level of competitive contact in those domains. As the number of markets shared between a pair of firms increases, so does the likelihood that an attack by one firm in a shared market will be met with retaliation by the other in a different market (Feinberg, 1984). As firms come to recognize the mutual threats of retaliatory action they are led to “forebear” competitive attacks on one another. Studies provide support for the argument that more competitive contact between firms reduces rivalry between those firms (Baum & Korn, 1996), while resource similarity may increase rivalry (Gimeno & Woo, 1996a, b). We adopt the IO perspective that competitive interdependence between firms depends upon the combined effects of resource and market similarity.

COLLABORATIVE STRUCTURING Economic Structures Collaborations are motivated by economic interests, but these interests are embedded within social structures that can modify otherwise rational economic

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Fig. 3. Integrative Characteristics of Alliances.

behavioral (Granovetter, 1985). We next examine the effects on collaboration from formal economic structures and social structures. A representative listing of the economic structures of inter-firm collaboration is shown in Fig. 3, arrayed from least to most interdependent. The structures reflect the complexity of integrating resources between organizations and indicate that more integrative structures are used when interdependence among partners increases (Gulati & Singh, 1998). The economic structures provide a way to control and facilitate the underlying processes that are used to integrate the resources contributed by partners. These underlying processes and their integrative nature can be understood as pooled, sequential, and reciprocal (Thompson, 1967). Pooled processes involve standardized contributions of resources that reduce interdependence. Sequential processes require more interdependence because collaborators must follow a defined sequence of contributions in order to achieve objectives. Reciprocal processes require constant monitoring and mutual adjustment, accompanied by more frequent and richer form of communication between collaborators. To illustrate with structures of collaboration, licensing of existing technology is shown as the least interdependent structure since licensors transfer codified, standardized knowledge in a pooled process. More complex combinations occur when partners plan and adjust in sequential processes, for example in the development of manufacturing cost-sharing arrangements involving coordination around sub-assembly and capacity management agreements. The most complex integration occurs when partners integrate knowledge-based resources through close coordination and short cycle, reciprocal processes. Complex integration is illustrated by research agreements involving early stage exploration of new technologies, where needed information and know-how is tacit and distributed among interacting participants. The unified organizational structure of a joint venture, for example, facilitates the coordination and complex integration of resources (Gulati, 1995a; Hamel, 1991), and allows participants to respond to and mutually adjust to changing

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circumstances without requiring the creation of new contract-based structures (Dyer & Singh, 1998). When matched properly to the level of resource interdependence between partners, economic structures help align partners’ incentives. For example, co-specialized resources are often managed under joint venture structures because conflicts over resource contributions or the distribution of gains can be resolved within the venture, without recourse to third party intervention. When contracts are used instead of joint ventures, third party intervention is often required to resolve conflicts, which increases the uncertainty of outcomes for partners. Because ownership of a joint venture is shared between partners, the incentive for any one partner to act opportunistically is dampened. Because of their integrated organizational structure and coordinated management, joint ventures are often preferred to encourage and accelerate the transfer and creation of knowledge between partners. As the rate of technological change in an industry increases, the availability of codified knowledge is further limited and firms must rely on tightly coupled collaborations in order to produce this knowledge out of tacit understandings and routines. However, the tacit nature of knowledge also makes it “vulnerable to unintended transfers” (Das & Teng, 2000, p. 8). That is, because partners may have only a limited understanding of each other’s capabilities, a partner may unintentionally transfer knowledge that is not specified within the alliance agreement but is valuable to another partner.

Social Structures In addition to formal economic structures such as equity ownership, social structures significantly affect the ability of partners to create and protect value in collaborations. Social theories of collaboration can be broadly divided into two research streams based on their focus of inquiry. Social capital theories examine the value that members bring to a collaboration from membership in larger network structures (e.g. Burt, 1992; Chung et al., 2000; Gulati, 1995a), while developmental theories examine dynamics and decision processes within a particular collaboration (e.g. Doz, 1996; Ring & Van de Ven, 1992). In the interests of keeping the discussion manageable, we limit ourselves to processes internal to the collaboration. Collaborations with lower levels of resource interdependence require fewer interactions and often a one-way flow of information is sufficient. However, when partners integrate knowledge-based resources through close cooperation, a number of complex social processes emerge with consequences that may be favorable or unfavorable. Social processes in collaborations evolve as participants

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develop a sense of congruency, or shared understandings, that help align interests (Ring & Van de Ven, 1992). Partners develop shared understandings from their previous collaborations (Gulati, 1995b) and from the trust that develops when they successfully increase the complexity and content of their collaborative activities over time (Doz, 1996). The effect on collaboration from goodwill, or trust, is reflected in multiple studies showing that partners with frequent and multiplex links are more likely to create future alliances (Parkhe, 1993; Saxton, 1997). Podolny (1994) for example, found that the search process for prospective alliance partners is often limited to existing partners. Partner-specific experience establishes future expectations for behavior and lowers the costs of monitoring and control. When partners have no previous experience with each other, concerns may arise regarding the quality and quantity of contributions to the collaboration and the risk of haggling over the eventual distribution of gains. If monitoring and control costs are lowered because of past ties between partners, the use of contracts rather than joint ventures may be more efficient because partners can avoid the lengthy negotiations and high exit costs of a joint venture (Gulati, 1995b). To encourage cooperation and information exchange, firms create a number of integrating organizational structures such as project or product teams, task forces, and research teams. Within these organizational structures firms often encourage social and interpersonal contacts to create a sense of commitment and to facilitate peer-to-peer cooperation. In some cases however, social processes may lead to unfavorable consequences for collaboration. Too much collegiality in teams may cause unintended spillovers of knowledge among team members (Hamel et al., 1989). Research on group dynamics shows that interacting members can develop significant psychological commitment to a group, causing increased communication flows within the group and restricted and defensive control of external information (Janis & Mann, 1977). The professional socialization and commitment of team members may also lead to the sharing of information that is not essential to achieve the goals of the collaboration, and thus could also undermine organizational interests. Identification with professional and research groups may be more salient when participants are suddenly reassigned from their home organizations to participate in project teams (Child & Rodrigues, 2003). To protect valuable information from unintended transfer in inter-organizational collaboration, firms use a number of approaches, including clearly communicating the organization’s collaboration goals to that organization’s team members, periodic job rotation of team members, and opportunities for team members to interact with parent organizations through seminars and debriefing conferences. These re-assimilation structures also create opportunities for knowledge acquired through the collaboration to be processed and internalized within the parent organization.

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COLLABORATIVE COMPLEXITY, STRUCTURE, AND VALUE CREATION We now turn to a discussion of the combinations of resource interdependence and competitive interdependence underlying the typology of collaborative complexity, structure, and value creation shown in Fig. 1. The four configurations of collaborative complexity that result and implications for collaborative structure and subsequent value creation are discussed below.

Less Complex Collaboration – Exploitative Structure (Quadrant I) In this quadrant (Quadrant I), value is created when partners engage in mutual exploitation of existing resources using contractual controls. Minority equity investments are also used when a partner provides cash for a real option position, as is frequently the case with pharmaceutical-biotechnology alliances. Partners face low levels of resource and competitive interdependence, so collaboration focuses on unilateral transfers of property-based resources using contracts or technology licensing agreements. When collaboration involves codified knowledge, resource transfer is a matter of routine. Collaboration may involve the contribution of tacit knowledge by one partner, but without resource co-specialization, again the case with minority equity investments. Partners are concerned with exploiting existing resources to produce economic value, and have recourse to legal institutions to enforce contract terms. Partners are less competitively interdependent, thus they tend to have adjacent functional or technological relationships.

Moderately Complex Collaboration – Coordinative Structure (Quadrant II) In this quadrant (Quadrant II), value is generated when competitors coordinate their contributions in order to exploit resources. Complexity arises from multiple interests in the ownership structure and concerns over the quality and quantity of each partner’s contribution. Competitive interdependence is high, signifying that partners share similar markets and strategically similar resources. However resource interdependence is low because property-based resources are the focus of the collaboration. Collaboration often involves manufacturing cost sharing to achieve scale or scope efficiencies. Since collaboration involves mutual exchange, partners form scale alliances when resource contributions from partners are symmetric, that is, when partners have similar strategic resources and market orientations, as is the case with competitors (Dussauge et al., 2000). If one

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partner contributes a lower level capability than another, scale benefits would not be mutual. Resource contributions are specialized to the industry but not co-specialized among partners, and involve property rights to codified knowledge such as manufacturing processes. Joint venture structure is used to specify resource contributions and to avoid haggling over distribution of any residual value. As an example, in November, 2002, Motorola, STM, Philips, and Taiwan Semiconductor (the world’s largest chip foundry) announced a $1.2B (USD) joint venture to produce 300mm wafers. By concentrating on design and sharing manufacturing costs with its partners, Motorola expected to reduce capital spending by half (Business Week, 2001). Similarly, in May, 2001 Alcatel and Sumitomo entered into a cross-licensing agreement for NZ-DSF technology designed to reduce the dispersion of light transmitted over long haul, high speed optical networks. The exchange enabled Alcatel and Sumitomo to leverage their complementary positions as manufacturers of communication network equipment. Co-specialization between partners is limited because of the modular nature of the technology, which in this case is based on standardized interoperability between cabling, lasers, and transceivers.

Moderately Complex Collaboration – Integrative Structure (Quadrant III) Collaborations in this quadrant (Quadrant III) focus on generating value from the development and/or integration of emerging technologies, often between firms that are asymmetrical in their resources and capabilities. Knowledge-based contributions from individuals are co-specialized and facilitated through team structures that encourage skill-sharing and the exchange of know-how. Partners are less competitively interdependent, thus they tend to have adjacent rather than overlapping functional or technological relationships. The risk of opportunism is controlled through joint venture ownership structures, while unintended knowledge spillovers may be minimized through rotational assignments and frequent opportunities for team members to remain assimilated within the parent organization.

Highly Complex Collaboration – Co-dependent Structure (Quadrant IV) In Quadrant IV, partners are faced with high levels of competitive interdependence accompanied by high levels of resource interdependence. Value is created when partners are able to forego near term competitive behavior and instead concentrate

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on long-term, collective action to create favorable industry outcomes through development of complementary industries and/or technology standards. Alliances in this quadrant are often pre-competitive, involving the establishment of a dominant design and standard setting particularly for emerging technologies. Standard setting alliances involve mutual adjustment and agreement among partners on product design, and often focus on key components of an overall technology architecture (Garud & Kumaraswamy, 1995). For example, IBM, HP, and Microsoft have collaborated to develop and agree on the Simple Object Access (SOAP) standard, which is designed to enable interoperability across web-based services. Coordination in standard setting alliances is made difficult by the risk that one partner may act with guile, and influence the standard toward compatibility with or unique capabilities of that partner’s proprietary technology. Coalitions focused on pre-competitive research and standard setting may strengthen the position of some competitors, while weakening others.

CONCLUSION Much of the collaborative activity we observe between firms is embedded within strategic and competitive industry relationships. Collaboration becomes particularly complex when partners are simultaneously competitors, and evidence suggests that this trend will continue in the future. As an initial step in understanding the sources of complexity in collaborative relationships, we modeled resource interdependence and competitive interdependence between partners and the contingent economic and social structures that create and protect valuable resources in these complex collaborations. For scholars, this chapter offers a midrange theory that integrates multiple perspectives, yet is limited to collaboration under conditions of competition. Testable propositions can be generated from each quadrant of our typology. For example, one could test whether economic and social structures moderate the relationships between the level of collaborative complexity and the ability of a firm to achieve above average returns. There are also implications for managers operating at multiple levels in the firm. Careful orchestration of strategic and project team structures and goals by top management and alliance team managers will help insure that the strategic objectives of the collaboration are met and that these objectives are consistent with the overall objectives of each partnering firm. This notion is punctuated since although partners may collaborate to create and exploit resources and capabilities created in the alliance, each partner must also compete independently based on its own firm-specific resources, skills, and capabilities.

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