Handbook on Innovation and Project Management 9781789901801, 1789901804

Citation preview

HANDBOOK ON INNOVATION AND PROJECT MANAGEMENT

In memory of Rémi Maniak who, through his enthusiasm and relevance, contributed so much to the community of innovation and project researchers

Handbook on Innovation and Project Management Edited by

Andrew Davies Science Policy Research Unit (SPRU), University of Sussex Business School, UK

Sylvain Lenfle Conservatoire National des Arts et Métiers (CNAM – Department of Innovation), France

Christoph H. Loch Cambridge Judge Business School, University of Cambridge, UK

Christophe Midler Centre de Recherche en Gestion-Institut Interdisciplinaire de l’Innovation, CNRS Ecole Polytechnique, Institut Polytechnique de Paris, France

Cheltenham, UK · Northampton, MA, USA

© Andrew Davies, Sylvain Lenfle, Christoph H. Loch and Christophe Midler 2023 Cover image: The UK Pavilion “The Seed Cathedral” by Heatherwick Studio, winner of the Shanghai 2010 World Expo. Photographed by Carsten Ullrich. Flickr license https:// creativecommons.org/licenses/by-sa/2.0/ All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical or photocopying, recording, or otherwise without the prior permission of the publisher. Published by Edward Elgar Publishing Limited The Lypiatts 15 Lansdown Road Cheltenham Glos GL50 2JA UK Edward Elgar Publishing, Inc. William Pratt House 9 Dewey Court Northampton Massachusetts 01060 USA

A catalogue record for this book is available from the British Library Library of Congress Control Number: 2023943043 This book is available electronically in the Geography, Planning and Tourism subject collection http://dx​.doi​.org​/10​.4337​/9781789901801

ISBN 978 1 78990 179 5 (cased) ISBN 978 1 78990 180 1 (eBook)

EEP BoX

Contents

vii

List of contributors

Foreword by Karl T. Ulrich xiv 1

Introduction: building bridges between innovation and project management research 1 Andrew Davies, Sylvain Lenfle, Christoph H. Loch and Christophe Midler

PART I   CONVERGING AND INTEGRATING 2

Bridging project studies and innovation studies: a meta-theoretical approach and research agenda Joana Geraldi and Jonas Söderlund

3

Corporate entrepreneurship and project management Valentine Georget and Rémi Maniak

4

The converging nature of innovation and project management: process, contingency and strategy Vered Holzmann and Aaron Shenhar

36 60

80

5

It’s all a bit fuzzy? The front-end in project and innovation management Michael A. Lewis, Joseph W. Harrison and Jens K. Roehrich

6

“A disputed project identity”: ambiguity and hybridization of exploration and exploitation in complex projects Stéphanie Tillement, Frédéric Garcias and Florence Charue-Duboc

125

Innovation projects in a global world: bridging global innovation management and project management Christophe Midler and Sihem BenMahmoud-Jouini

149

7

101

PART II   BUILDING AND EXTENDING 8

Corporate innovation strategies and multi-project management on lineages and ambidextrous programmes Rémi Maniak and Christophe Midler

168

9

Exploratory projects: the state of the art and a research agenda Sylvain Lenfle

186

10

Managing unforeseeable uncertainty through learning Christoph H. Loch, Svenja C. Sommer and Mengtong Jiang

201

v

vi  Handbook on innovation and project management

11

12

Success factors of project portfolio management and their influence on innovation success Alexander Kock and Hans Georg Gemünden Innovation in project-based organizations Jan van den Ende and Floor Blindenbach-Driessen

219 232

PART III   IMPORTING AND CROSS-FERTILIZING 13

Collaboration and trust in innovative projects Niels Noorderhaven

244

14

A cultural evolution theory of balancing innovative and routine projects Christoph H. Loch, Stylianos Kavadias and Svenja C. Sommer

258

15

Organizing projects for social innovation Stephan Manning and Stanislav Vavilov

274

16

From “lonely projects” to orchestrating project innovation ecosystems Samuel C. MacAulay, Andrew Davies and Mark Dodgson

294

17

Value management of innovation projects: contemporary challenges and perspectives 308 Sophie Hooge and Sylvain Lenfle

18

Blending novelty and tradition in creative projects: how robust project design and conventionality shape the appeal of operatic productions Giulia Cancellieri, Gino Cattani and Simone Ferriani

333

PART IV   CASES AND CONTEXTS 19

Systems engineering as foundation and target for complex system innovation Stephen B. Johnson

356

20

Corporate innovation and agile project management Kate Davis and Jeffrey K. Pinto

375

21

Projects, capabilities and innovation: Rome’s Jubilee as a vanguard project for the Italian Civil Protection Department Eugenia Cacciatori and Andrea Prencipe

393

Digital project capabilities and innovation: insights from the emerging use of platforms in construction Jennifer Whyte, Luigi Mosca and Shanjing (Alexander) Zhou

408

22

23 Index

Innovation and big science projects Mark Dodgson and David Gann

423 434

Contributors

Sihem BenMahmoud-Jouini is Associate Professor at HEC Paris, France, where she teaches innovation management, new product development and project management. Her research focuses on organizational design for innovation and creativity, strategic management of innovation, entrepreneurship and design management. She held the Orange-HEC (2012–2018) research chair on innovation management and globalization. She has published in Creativity Innovation Management, International Journal of Project Management, Journal of Product Innovation Management, Management International and Project Management Journal, among other journals. Her latest book is Management de l’Innovation et Globalisation, Dunod, France. Floor Blindenbach-Driessen has a PhD in management from Erasmus University in the Netherlands. She has 25+ years of experience with bringing about innovative ideas and has published articles in, among others, Research Policy, Journal of Product Innovation Management and IEEE Transactions on Engineering Management. She is the founder of Organizing4Innovation which provides a proven path to success for innovation teams. She has guided hundreds of innovators in creating innovative solutions, leading to millions of dollars in new revenues. Eugenia Cacciatori is Senior Lecturer (Associate Professor) in Management at Bayes Business School, City University of London, UK. Eugenia’s interests are in the organizational processes of innovation, including the role of artefacts such as models, plans and procedures in knowledge creation and exchange, and innovation in project-based contexts. Eugenia’s research has been published in journals such as the Academy of Management Journal, Journal of Management Studies, Organization Studies and Research Policy. She is part of the Centre for Creativity in Professional Practice (City) and the Ethics Community of Digital Society Initiative (UZH). Giulia Cancellieri is Tenure Track Assistant Professor in Business Administration at the Ca’ Foscari University of Venice, Italy. Her research interests include creativity and innovation, social processes of legitimation in cultural industries, strategic management and marketing of cultural organizations. Gino Cattani is Professor of Strategy and Organization Theory at the Stern Business School, New York University, NY. His research interests include creativity and innovation, social evaluation and competitive sensemaking. Florence Charue-Duboc is Professor at École Polytechnique, Palaiseau, France, and research director at CNRS at i3-CRG. Her research work deals with technological innovation management and strategy. She has conducted empirical analysis in diverse firms in various sectors (chemical and pharmaceutical, automotive industry, industrial gas). She has published her work in international journals such as International Journal of Innovation Management, Creativity and Innovation Management, International Journal of Project Organisation and vii

viii  Handbook on innovation and project management

Management, International Journal of Technology Management and Industry and Corporate Change. Andrew Davies is RM Phillips Freeman Chair and Professor of Innovation Management at the Science Policy Research Unit, University of Sussex Business School, Adjunct Professor at BI Norwegian Business School, Norway, Honorary Professor at UCL and Visiting Professor at LUISS University, Rome. His book Projects: A Very Short Introduction, Oxford University Press (2017) was awarded the 2018 Project Management Institute David I. Cleland Literature Award. In 2020 he was awarded an Honorary Fellowship of the Association for Project Management. Kate Davis is Senior Lecturer at Cranfield University, UK, in the School of Management specializing in the areas of strategic organizational project management, consultancy and designing and delivering courses that have a real impact. She has particular expertise in the development and implementation of modules with large student numbers, pioneering the development and deployment of technology to improve teaching and learning. In 2016 she completed her PhD which examines multiple stakeholder perceptions of project success. Mark Dodgson researches innovation. He has published or edited 19 books and over 100 articles on the subject and studied it in over 60 countries. He is currently Executivein-Residence, Saïd Business School, University of Oxford, UK; Visiting Professor, Imperial College London, UK; Broman Scholar, University of Gothenburg, Sweden; and Emeritus Professor, University of Queensland, Australia. He has been on the boards of two multibilliondollar companies and five start-ups. Simone Ferriani is Professor of Entrepreneurship at the University of Bologna, Italy, and at City University of London, UK. His research interests include entrepreneurship, innovation and social networks. He is a lifetime fellow of Clare-Hall, Cambridge University. David Gann is Pro-Vice-Chancellor of Development and External Affairs and Professor of Innovation and Entrepreneurship at the Saïd Business School of the University of Oxford, UK. His publications on innovation management include books such as The Management of Technological Innovation, The Oxford Handbook of Innovation Management, Think, Play, Do: Technology, Innovation and Organisation and The Playful Entrepreneur: How to Adapt and Thrive in Uncertain Times and articles in journals such as Research Policy, Organization Science, Harvard Business Review, California Management Review, MIT Sloan Management Review and Project Management Journal. Frédéric Garcias is Assistant Professor of Management at the University of Lille (IAE Lille), France, and a researcher in the LUMEN laboratory (Lille University Management). He specializes in knowledge-based approaches to organizations and projects. He conducts his research in collaboration with industrial companies and has notably studied the phenomena of forgetting and relearning within new nuclear reactor projects. His work has been published in journals such as M@n@gement, Project Management Journal and Nuclear Technology. Hans Georg Gemünden was Professor of Project Management at BI Norwegian Business School, Norway, from 2015 to 2019 and Professor of Technology and Innovation Management at TU Berlin, Germany, from 2000 to 2015. He has authored over 180 journal articles, 140 book chapters and five books, and published in Organization Science, Research Policy,

Contributors 

ix

Journal of Product Innovation Management, etc. He has been first or second supervisor of 19 habilitations and 165 PhDs; 18 of the first supervised became university professors. Valentine Georget is Lecturer in Management at the Université Côte d’Azur, France, and a researcher at GREDEG (UMR CNRS 7321). After completing her thesis at the i3-CRG laboratory (UMR CNRS 9217) at École Polytechnique on the individual impacts of corporate entrepreneurship, she sought to understand how to reconcile economic profitability with positive socio-environmental impacts for organizations. Through her research, Valentine is interested in the reconciliation of innovation, sustainability and the individual. Joana Geraldi is Associate Professor at Copenhagen Business School, Denmark, and an honourary Senior Researcher at University College London, UK. Joana is intrigued about how projects shape and are shaped in firms and society. Joana advocates for integrating knowledge across fields and works to create insights by bridging fields of study. Joana has published in outlets such as the Journal of Management Studies, International Journal of Project Management and Project Management Journal, and has led several special issues. Joseph W. Harrison is a Doctoral Researcher at the University of Bath, School of Management, UK. Joseph is currently researching the management of scale in major projects. Joseph is a recipient of the Economic and Social Research Council (ESRC) doctoral scholarship (administered by the South West Doctoral Training Partnership). Vered Holzmann is a faculty member at the School of Management and Economics in the Academic College of Tel Aviv Yaffo, Israel, where she also serves as Director of Research, Development and Innovation. Vered received her doctorate from the School of Management, Tel Aviv University. Her research topics include project management, strategy, innovation, entrepreneurship and impact management. She coordinated several international projects in the fields of internationalization in higher education and innovative finance inclusion. Sophie Hooge is Professor of Innovation Management and Engineering Design at Mines Paris – PSL, France. Her research focuses on value management and performance processes in industrial and cooperative contexts of innovation and has been built on various longitudinal partnerships with strategic and operational teams of industrial firms and public institutions for 15 years. She has published her works in international journals such as Journal of Engineering and Technology Management, Creativity and Innovation Management and Project Management Journal. Mengtong Jiang received a PhD in Project Management from the School of Economics and Management of Dalian University of Technology, Dalian, China. Her research interests are in the area of project management, organizational behaviour and value management. She has published in academic journals such as International Journal of Managing Projects in Business, Chinese Journal of Management and Journal of Management Case Studies. Stephen B. Johnson works on several contracts with the National Aeronautics and Space Administration, including Space Launch System Mission and Fault Management, diagnostic and fault management software and systems engineering. He is the general editor for System Health Management: With Aerospace Applications (2011), the author of The Secret of Apollo: Systems Management in American and European Space Programs (2002), and many other articles and books on system health management, systems engineering, space economics, philosophy of technology and space history.

x  Handbook on innovation and project management

Stylianos (Stelios) Kavadias is the Margaret Thatcher Professor of Enterprise Studies in Innovation and Growth at the Cambridge Judge Business School, where he serves as its ViceDean for Faculty and directs its Entrepreneurship Centre. His research on the innovation and growth challenges of organizations, has appeared in HBR, MSOM, and Management Science where he serves as an Associate Editor. Prior to JBS, Stelios was the Steven A. Denning Professor of Technology and Management at Georgia Tech in the USA. Alexander Kock is Full Professor of Technology and Innovation Management at the Technische Universität Darmstadt, Germany. His research interests include innovation and project management, especially managing project portfolios, the front end of innovation and open innovation. Alexander is an editor at the Project Management Journal and has published over 100 journal and conference articles, for example, in Research Policy, Journal of Product Innovation Management, IEEE Transactions on Engineering Management, R&D Management and International Journal of Project Management. Sylvain Lenfle is Professor of Project and Innovation Management at the Conservatoire National des Arts et Métiers (CNAM, Paris). He is also Associate Researcher at the Management Research Center (Ecole Polytechnique) and Associate Professor at the Ecole des Mines (Paris). His works deals with the management of exploratory projects and innovation through field research in organizations or historical research. He has published in academic journals such as Research Policy, California Management Review, Organization Studies, and International Journal of Project Management. Michael A. Lewis is Professor of Operations and Supply Management at the University of Bath, School of Management, UK. His wide-ranging interests include operations/technology strategy, governance, productivity and major projects. He also has a long-standing interest in sustainability and healthcare. He is the author and co-author of numerous journal articles as well as several books including a widely adopted and translated book on operations strategy. Christoph H. Loch is Professor of Operations and Technology Management at Cambridge Judge Business School, where he served as Dean from 2011 to 2021. Before, he was a McKinsey consultant and then a professor at INSEAD. For 35 years he has worked on innovation and project management, including innovation portfolios, management of novel projects, and motivation of professional employees. He has a Master from the Darmstadt Technical University, an MBA from the University of Tennessee Knoxville and a PhD from the Stanford Graduate School of Business. Samuel C. MacAulay is a Senior Lecturer at the University of Queensland’s Business School, Australia. Sam’s research explores how innovation is shaped by business models, how new products and services are created and how organizations gain and sustain competitive advantage. This research has focused on industries spanning from civil engineering to advanced manufacturing and has been published across leading international journals ranging from Project Management Journal to Academy of Management Review. Rémi Maniak was Professor in Innovation Management at École Polytechnique and researcher at CRG I3 CNRS-IP Paris, France. He was Director of the master’s degree in Project Innovation Conception and Director of the education program Innovation Enterprise and Society at the Institut Polytechnique de Paris. He conducted research on innovation project management in

Contributors 

xi

collaboration with various companies, public organizations and think tanks. His last book, coauthored with Nicolas Mottis, was La jungle de l’innovation, comment survivre et prospérer?, Dunod, 2021. Stephan Manning is Professor of Strategy and Innovation at the University of Sussex Business School, UK. He is also a filmmaker. Stephan’s current research focuses on global societal challenges, social innovation and entrepreneurship, and global value chains. Most recently, he has begun studying films and related impact campaigns as vehicles for social change. His research has been published in major journals in the field. For more information, please check out his website: www.stephanmanning.com. Christophe Midler is Emeritus Research Director at the Management Research Center and Professor at Ecole Polytechnique, Paris. He is member of National Academy of Technologies of France and Doctor Honoris Causa at Umea University, Sweden. His research topics are product development, project and innovation strategy and management. He has explored these topics in various industrial contexts, especially automotive industry. He has published his work in journals as Project Management Journal, Research Policy and Industrial and Corporate Change. His last published book is The Innovation Odyssey, Taylor and Francis (2023). Luigi Mosca is a research associate at the Imperial College Business School and an honorary researcher at the John Grill Institute for Project Leadership, University of Sydney. His research interests include organizational configurations, digital transformation and innovative business models, with empirical work on project-based firms, SMEs and digital platforms. Niels Noorderhaven is Emeritus Orofessor of International Management at Tilburg University, Netherlands, and visiting Professor at the University of Antwerp, LUISS University Rome and Zhejiang University. His research focuses on the management of international collaboration between firms, for instance in the form of alliances, joint ventures or mergers and acquisitions. His research has mainly focused on industries like microelectronics, office equipment, airlines, construction and shipbuilding. Niels is a Fellow of the European Academy of Management and currently also serves as Chair of the Board of this association. Jeffrey K. Pinto is the Andrew Morrow and Elizabeth Lee Black Chair in Management Technology with the Black School of Business, Pennsylvania State University, Erie, PA. He has authored or edited 28 books and some 200 scientific papers. He received PMI’s Research Achievement Award in 2009 for outstanding contributions to project management research. In 2017, Jeffrey was honoured with the International Project Management Association’s Research Achievement Award for his research career in project management. Andrea Prencipe is Rector as well as Professor of Organization and Innovation at Luiss University in Rome, Italy. His research focuses on innovation-related issues in organizations and higher education institutions and on project-based organizing. Andrea’s works have been published in such journals as Administrative Science Quarterly, Organization Science and California Management Review as well as with international publishers, e.g. Oxford University Press. He sits on the editorial board of such journals as International Journal of Project Management and Research Policy. His work regularly appears in international newspapers. Jens K. Roehrich is Professor of Supply Chain Innovation at the University of Bath, School of Management, UK. He has carried out research, executive education and competence

xii  Handbook on innovation and project management

development activities with a wide range of public and private organizations in large projects. His research focuses on long-term relationships across public and private organizations with a particular emphasis on the role of contractual and relational governance mechanisms as well as the dark side of relationships such as coordination failures and conflicts. Aaron Shenhar is a PMI Fellow and Professor of Project Management and Leadership. He held positions at the University of Minnesota, Tel Aviv University, Stevens Institute of Technology and Rutgers University. For two decades, he was also an executive in the defence industry. He holds five academic degrees in engineering and management from Stanford University and the Technion in Israel. He was the first recipient of the Project Management Institute Research Achievement Award and a recipient of the IEEE Engineering Manager of the Year Award and IMPA’s Research Achievement Award. Jonas Söderlund is a Professor of Strategy at Linköping University, Sweden, and an Adjunct Professor at BI Norwegian Business School, Norway. He is an Associate Editor of the Project Management Journal and a member of the editorial boards of Human Relations and Organization Studies. He has studied project-based organizing and project-based work and contributed to advancing theories of knowledge integration, liminality and temporality through work published in Research Policy, Organization Studies, Human Relations, Management Learning and the International Journal of Management Reviews. Svenja C. Sommer is Associate Professor in the Operations Management and Information Technology Department at HEC Paris, France, and Academic Director of the MSc in Innovation and Entrepreneurship. Her research aims to improve our understanding of effective management of innovation-related and product development projects. She serves as a Senior Editor for the New Product Development, R&D, and Project Management department of POMS and as an Associate Editor for the Entrepreneurship and Innovation department at Management Science. Stéphanie Tillement is Associate Professor in Sociology at IMT Atlantique, France, and Researcher at LEMNA. She holds the RESOH Chair in Work, Organization and Industrial Safe Performance. Favouring grounded and processual approaches, her research focuses on complex projects’ organization and governance and the collective construction of safe performance in inter-organizational work contexts. She has particularly investigated large-scale projects in the nuclear industry. She has co-edited several books (Springer, PUR) and published in journals such as M@n@gement, Project Management Journal and Nuclear Technology. Jan van den Ende is Professor of Innovation Management and Horticulture Innovation at Rotterdam School of Management, Erasmus University, Netherlands. Jan has published in numerous journals such as Organization Science, Harvard Business Review, Journal of Product Innovation Management and Research Policy. He published the textbook Innovation Management which targeted both students and practitioners (Bloomsbury/Macmillan). He is founder of the New Business Roundtable, in which innovation managers of large companies meet, such as Philips, ING and ASML. Stanislav Vavilov is Assistant Professor of Management at the Dolan School of Business, Fairfield University, CT. Stanislav’s research interests are at the intersection of entrepreneurship support, international development and social entrepreneurship. In particular, he studies the processes that underpin the emergence and formation of novel entrepreneurship support

Contributors 

xiii

infrastructures, especially in transnational contexts. His research has been published in Strategic Organization, Journal of Cleaner Production and Journal of International Management. Jennifer Whyte is a Professor at the University of Sydney, where she is Director of the John Grill Institute for Project Leadership and Head of School of Project Management. Her research explores the changing nature of organizational practices in large scale complex projects, with empirical work on construction, major infrastructure projects, visualization and design. Shanjing (Alexander) Zhou received his PhD at Imperial College London. His research interests lie in innovation strategies, new business models, project management and delivery, digitalization, industrialized construction, smart safety, productivity, and entrepreneurship.

Foreword Karl T. Ulrich The Elgar Handbook on Innovation and Project Management is a groundbreaking publication that explores the theoretical and practical connections between the academic disciplines of project management and innovation studies. As often happens in research communities, both fields have perhaps become somewhat inwardly focused. Further exacerbating the disconnect between the efforts of scholars has been a different relative emphasis on innovation and project management in different global regions. This handbook is the first of its kind to examine innovation and project management in various forms and contexts, from R&D and new products to agile collaboration and infrastructure development. The authors are leading scholars in the fields of innovation and project management, and in this handbook, they introduce new theoretical and empirical research examining how organizations can successfully launch and manage innovative projects in the 21st century. Collectively, they argue that, in order to achieve successful outcomes, project managers must be equipped with the tools, strategies and perspectives needed to drive innovation throughout their projects. This means considering how to leverage emerging technologies, how to create an environment that supports creativity and innovation and how to identify and implement new ideas that can bring value to the project and its stakeholders. The editors have devised an outstanding architecture for the handbook. The volume is structured in a way that makes it accessible to both innovation and project management practitioners and students of the field. The introduction provides an overview of the current state of the project management field and how it has become increasingly inward-focused. They then delve into the key concepts and principles of innovation and project management, including a discussion of how these fields interact and influence one another. Throughout the book, the contributors use real-world examples and case studies to illustrate their points and provide practical insights into how to implement their ideas in a variety of settings. Some of the critical topics covered include: • • • • • •

The role of innovation in project management. The importance of creating a culture of innovation in project teams. Techniques for encouraging creativity and idea generation in projects. Approaches to measuring and assessing the impact of innovation on projects. Strategies for fostering collaboration and teamwork in innovation-driven projects. Methods for managing risk and uncertainty in innovative projects.

The Handbook is an important resource for anyone who is interested in bringing the fields of innovation and project management back together. Whether you are a seasoned project manager looking to add a new dimension to your work or a student just starting out in the field, this book will provide you with the insights, tools and strategies you need to be successful in today’s rapidly changing and highly competitive business environment. Karl T. Ulrich CIBC Endowed Professor The Wharton School Philadelphia, PA xiv

1. Introduction: building bridges between innovation and project management research Andrew Davies, Sylvain Lenfle, Christoph H. Loch and Christophe Midler

INTRODUCTION This inaugural edition of the Elgar Handbook on Innovation and Project Management is the first of its kind to explore the theoretical and practical connections between the management of innovation and projects. The Handbook examines the management of innovative projects in various forms (e.g. R&D, new product development, agile, collaboration, trust and ambidexterity) and diverse contexts (e.g. aerospace, defence, automotive, nuclear power, cultural industries, social innovation and urban railway systems). It introduces new theoretical and empirical research by leading scholars examining how organizations launch and manage innovative projects to compete in global markets and tackle some of the immense economic, social and environmental challenges facing organizations and societies in the 21st century. In this introductory chapter, we begin by suggesting that the ability to successfully conceive and execute innovative projects is increasingly important to the survival and prosperity of organizations – firms, start-ups, government bodies, NGOs and many others – particularly when conditions are increasingly uncertain, complex and rapidly changing. We then briefly explain how project management and innovative studies emerged and developed as two largely distinct literatures, offering quite different conceptual insights and contrasting practical guidance on how to manage innovative projects. Next, we introduce key theoretical research developed by pioneering scholars working at the interface between innovation and project management. We then provide a summary of the chapters in the four parts of the Handbook and how they advance our thinking by exploring synergies and building bridges between innovation, project management and adjacent research. We end by identifying promising new avenues of research to improve our understanding and offer practical guidance on how to manage innovative projects in the future.

MANAGING INNOVATIVE PROJECTS: A KEY CHALLENGE FACING ORGANIZATIONS IN THE 21ST CENTURY Projects bring together people and other resources in a temporary organization to produce novel, one-off or highly customized products, services, outcomes or events as diverse as aircraft, operas, the Olympics or new processes and capabilities within an organization. But they play an even more fundamental role as the engine of innovation – developing and implementing novel ideas – in globally competitive markets. Firms depend on projects to undertake exploratory R&D, develop novel technologies, design, test and deploy new products and 1

2  Handbook on innovation and project management

services, launch entrepreneurial start-ups and internal corporate ventures, introduce new processes and organizational changes and implement entirely new business models. As new ideas proliferating rapidly across the internet are more easily shared or copied, product life cycles become shorter in some industries and others face major technological disruptions, firms rely on projects to create new products and services before existing ones become obsolete across industries (e.g. smart phones, aviation, electric vehicles, renewable energy and digital platforms). Projects are also used to tackle sustainability strategies and the political, supply chain and trade disruptions affecting a growing number of industries in recent years. As a result, many firms are now run like a collection of projects to create flexible, faster and flatter structures focused on problem-solving and innovation. Whereas projects in the private sector are undertaken by firms to gain competitive advantage and increase profitability and shareholder wealth, those in the public sector are created to maximize public welfare, create social value or address societal challenges. In many cases, the profit and non-profit boundary is blurred in projects involving multiple public, private and hybrid organizations (e.g. NGOs and research institutes) in developed and developing countries. Governments, manufacturers, international bodies, universities, consultancies and other organizations often collaborate in large, inter-organizational projects to tackle complex, urgent and challenging social, political and ecological problems (e.g. retrofitting homes and workplaces in cities, providing humanitarian aid or dealing with ecological disasters) and achieve transformational societal missions (e.g. space exploration, vaccine development and nuclear fusion). Projects, Innovation and Operations Until the late 20th century, many large firms became successful by improving productive operations rather than projects (Peters and Waterman, 1982). Designed to perform standardized routines in stable, predictable and growing markets, high-volume operations created value for organizations over the past century through a stream of advances in mass production, such as Henry Ford’s assembly line, Frederick W. Taylor’s scientific management, Total Quality Management, lean production and mass customization (although continuous improvement and gradual change have always been important competitive tools). Formal, bureaucratic and mechanistic forms of large-scale organization were established to deal with routine operations performed by engineering, manufacturing, sales and other functional units. Firms that had previously focused on improving their operations, however, struggled to adapt to an increasingly volatile, rapidly changing and uncertain environment in the 1970s and 1980s. They could no longer survive by only improving their operations and began to focus on projects to unlock new sources of innovation and competitive advantage (Peters and Waterman, 1982). Concepts introduced to describe project-based organizations as organic (Burns and Stalker, 1961), adaptive (Bennis, 1966) adhocracies (Toffler, 1970; Mintzberg, 1979) were ideas borne from more turbulent conditions and the incessant pressure to innovate and change. The project-based firm (Gann and Salter, 2000 Whitley, 2006), project-based organization (Hobday, 2000; Lundin et al., 2015) and post-bureaucratic organization (Kellog et al., 2006) are some of the more recent attempts to capture the variety of innovation-oriented forms of project organizing. It may be misleading to suggest, however, that projects are simply displacing operations as the dominant form of organization in the 21st century, as some authors claim (Shenhar

Introduction 

3

and Dvir, 2007; Neito-Rodriguez, 2021), when projects have become even more closely coupled with different types of productive operations (Benghozi et al., 2000; Le Masson et al., 2010). As illustrated in Figure 1.1, upstream R&D projects create new knowledge of materials, technologies and intangible services that are eventually incorporated downstream in new product development projects (Imaï et al., 1985; Wheelwright and Clark, 1992). New ideas, technologies, materials and practices are combined, tested and implemented in new product development projects before moving further downstream into various stages of production from low- (unit and batch) to high-volume (mass and continuous flow) operations. From this perspective, new product and new process development projects are the “engine of innovation” (Randolph and Posner, 1988; Bowen et  al., 1994; Rosenbloom and Spencer, 1996; Midler and Navarre, 2004) driving all productive operations, and the unit stage of novel, one-off and highly customized production is entirely based on projects (Davies and Hobday, 2005), such as capital goods, architecture, advertising, consulting and sporting events. As the pace of innovation accelerated in the late 20th century, batch and mass production operations supported by digital technologies had to become more flexible to produce an increasing variety of products at lower costs. In recent years, many mass-producers – IBM, Renault and CocoCola among others – have outsourced high-volume manufacturing operations and become orchestrators of a network of external suppliers involved in product development projects. Innovative Projects Past and Present Until scholars began to recognize that innovation requires project forms of organization, general management theory had surprisingly little or nothing to say about the subject. Yet projects have always been important throughout history as the organizational form used to launch new ventures, develop new technologies and coordinate multiple parties involved in any largescale endeavour, such as building the first canal, railway and telegraph networks (Scranton, 2015; Davies, 2017). In a new synthesis of public and private power, scientists, politicians,

Continuous Flow Mass Production

R&D Projects

New Product Development Projects

Mass Customization Large Batch Small Batch Unit/Project

Note:   project-based activities shaded in grey.

Figure 1.1  Projects, innovation and operations

4  Handbook on innovation and project management

engineers and contractors collaborated on construction, energy and transportation projects, often on a gigantic scale, such as the American Pacific Railway or the Panama Canal, creating the infrastructure underpinning the rise of modern industrial societies in the 19th and early 20th centuries (Berman, 1982). Projects really came of age, however, during and after the Second World War when new forms of project and matrix structures and the “systems approach” to project management were created to develop America’s radically new weapons and space exploration technologies, such as the Manhattan Project that produced the world’s first atomic bomb in 1945, the Atlas and Polaris ballistic missiles in the 1950s and NASA’s Apollo moon landing in the 1960s (Sayles and Chandler, 1971; Sapolsky, 1972; Johnson, 1997; Hughes, 1998). America’s aerospace-generated systems approach to project management quickly spread since the 1960s to most other organizations and industries elsewhere in the world involved developing innovative new products and services, building complex systems, infrastructure, buildings and other assets, and trying to solve some of the grand challenges facing societies, such as the climate emergency and ecological destruction (Morris, 1994, 2013; Hughes, 2004). For example, the Apple New Product Process (ANPP) for developing and bringing breakthrough innovations to market, such as the iMac and iPhone, is based on NASA’s systems approach to project management used for the Apollo moon landing in the 1960s. A vast array of innovative projects are behind the accelerated pace of Schumpeterian “creative destruction” in the 21st century. Established industries dominated by a few global firms have already been transformed by revolutionary new product development projects led by outsiders with the imagination and insight to anticipate what customers in the future might value and desire, such as Amazon’s dominance of retail, Apple’s iPhone or the phone-based MPESA payment system. The creation of entirely new industries (e.g. nuclear fusion, hyperloop transportation and hydrogen low-carbon energy) is often initiated by large, complex inter-organizational R&D projects sharing people, resources and facilities often located in many countries. Construction, architecture and other project-based industries that have been less susceptible to disruption are finally being opened to up an influx of new digital technologies and practices. Frank Gehry, for example, adopted project software originally used in aerospace to design some of the world’s most iconic buildings, starting with the Guggenheim Museum in Bilbao, Spain. New types of project-based organizations have emerged in recent years focused entirely on working in overlapping, collaborative projects to generate ideas, experiment and produce novelty, such as Thomas Heatherwick’s London design studio’s innovations ranging from products (e.g. London’s fuel-efficient bus) to experimental buildings (e.g. the UK Pavilion at the 2010 World Expo in Shanghai) and urban spaces (e.g. Little Island in New York). Most importantly, many innovative projects are underway and urgently needed to solve some of the most pressing problems and grand challenges of our time, such as designing the zero-carbon, energy-efficient infrastructure or developing vaccines at a rapid pace to prevent the next global pandemic. Project Society and Challenge of Innovation “Projectification” is the term used to describe the far-reaching and ongoing transformation of work and daily life brought about by the spread of project organizing since the mid-1960s from traditional project-based industries (e.g. construction, civil engineering, defence and aerospace) to almost every part of society (Midler, 1995, 2019a). More recently labels such the

Introduction 

5

“project society” (Boltanski and Chiapello, 2005; Lundin et al., 2015) and “project economy” (Nieto-Rodriquez, 2021) have been proposed to underline the significance of this global phenomenon. Although exact data is difficult to obtain, an indicator of the global economic activity undertaken as projects is fixed capital formation, which has been increasing steadily as a percentage of global GDP. World Bank data in 2015 indicated that 23 per cent of the world’s $114 trillion GDP is fixed capital formation (construction, infrastructure and capital goods), which is almost entirely project-based, and in some newly industrializing countries the figure is much higher – 31 per cent in India and 46 per cent in China (Davies, 2017). The extent of projectification, however, is likely to be much greater as these figures fail to capture the growing share of project work in organizations involving all non-routine work with a specified target, such as R&D, new product development, organizational change and other initiatives. In Germany, for example, projects were estimated to account for 33 per cent of total GDP in 2013 (Schoper et al., 2018) and as much as 41 per cent in 2019 (Neito-Rodriguez, 2021). In recent years, many innovations have been applied to improve the performance of projects in one industry before spreading to others, such as new product development in automotives based on heavyweight project management and concurrent engineering (Clark and Fujimoto, 1991), digital technologies offering a “single source of information” to coordinate complex projects in aerospace, collaborative models of integrated project delivery in construction (Whyte, 2019) and agile development in software (Boehm, 1988). Despite efforts to increase productivity by learning from the experience of executing an ever-increasing number of projects, surprisingly few achieve their cost, time, quality and longer-term objectives. In their study of 600 projects in public, private and non-profit sectors, for example, Shenhar and Dvir (2007) found that 85 per cent failed to achieve their time and cost objectives. Efforts to improve performance are even more challenging when projects are highly innovative in rapidly changing and uncertain environments. When we turn to the literature to understand how to improve the management of innovative projects, however, we find two distinct fields of study – “project management” and “innovation studies” – with entirely different scholarly motivations offering opposing interpretations and conflicting advice. Some of the key differences between project and innovation management are summarized in Table 1.1.

HOW “INNOVATION” IS CONCEPTUALIZED IN PROJECT MANAGEMENT The origins of project management can be traced back to the 1950s and 1960s when scientists, engineers and managers working on large American defence and aerospace projects began to articulate and codify the new systems approach comprising a cluster of interrelated developments in project management, systems engineering and operations research (Johnson, 1997; Hughes, 1998). Systems Approach to Project Management: Controlled Stage-Gate Process After the great breakthrough projects of the 1950s, which produced a few spectacular successes but also many failures, in spite of virtually unlimited budgets (Art 1972), an explicitly more disciplined and “professional” approach to project control was developed under the

6  Handbook on innovation and project management

Table 1.1  Comparing innovation and project management: key differences Project management

Innovation management

Theoretical foundations

Single (systems theory)

Multiple (e.g. contingency theory, evolutionary theory, industrial economics, behavioural theory of firm)

Approach

Optimizing, fixed, stage-gate process based

Adaptive, emergent, contingent structure based

View of projects

Projects are similar

Projects differ

Goal

Getting task completed on time, within budget and requirements for client

Achieving business results in existing and new markets

Definition of success

Achieving project goals, intolerance of failure

Achieving business strategy, tolerant of failure

Management style

One size fits all

Adapt to variation in the environment

Managerial level

Middle management/project management

Top management

Tasks

Predictable or plannable, linear (controlled sequential stages)

Uncertain, complex, non-linear, interdependent (sequential, concurrent and parallel)

Planning

Plan at the outset and replan as needed, put things back on track

Plan, replan and adjust over time to changes in the environment

Approach to uncertainty

Focus on negative risk, methods of risk management, controlling progress, avoiding deviations

Focus on opportunities, positive risk, risk willingness

Management focus

Operational, tools and techniques

Strategy, design and structures, as well as processes and tools

Environment influence

Minimal, detached after project is launched

Affects projects as structure and process during planning and execution

Secretary of Defense Robert McNamara. Project management tools, techniques and organizations (e.g. pure project and matrix structures) were created to combine functional and project lines of authority, integrate specialized knowledge and deliver complex, novel projects on time, to budget and according to specification (Sayles and Chandler, 1971; Johnson, 2002). Indeed, project management is aptly described as a key innovation in how innovation can be accomplished (Gemünden et al., 2013). Systems engineering techniques were developed to coordinate the design, development and integration of complex technological systems (Sapolsky, 1972). Operations research emerged as a discipline to analyse military operations within which projects were conceived and executed. Articles on project management began to appear in journals (Gaddis, 1959), the first textbooks on the subject were published (e.g. Cleland and King, 1968) and professional project management associations were founded in the United States and Europe – including the International Project Management Association (IPMA) in 1967, the Project Management Institute (PMI) in 1969 and the Association for Project Management (APM) in 1972.

Introduction 

7

From its foundation as a discipline in the 1960s until very recently, project management research and practice have been dominated by the assumption that there is a standardized “one-size-fits-all” model applicable to the management of all types of projects (e.g. Project Management Body of Knowledge [PMBoK]). Advocates of project management emphasized its practical importance and the need for people trained in highly standardized guidelines, processes and bodies of knowledge, such as the PMI’s PMBoK (PMI, 2021). Although definitions vary, most project management textbooks and handbooks agree that projects can be defined as unique, one-time endeavours undertaken to produce a novel, one-off product, event or outcome (Cleland and King, 1968; Maylor, 2005; Pinto, 2010). Projects range in size from large inter-organizational endeavours (such as the multinational project established in the 1990s to launch the International Space Station) to small projects undertaken by a department, group or individuals in an organization. Success is traditionally measured in terms of whether projects achieve a predefined goal within time, cost and quality – the so-called “iron triangle” of project management. Projects are sometimes defined as complex because they incorporate many interacting parts and functions, with inputs from members in various departments or other organizations. Projects are temporary because they have a start and end date and dissolve on completion of the task. According to the standardized model, projects should be planned, controlled and managed in life cycle stages – the “stage-gate” approach originating in NASA’s Phased Project Planning in the 1960s – from initiation through execution to commissioning and handover, involving many tasks performed sequentially in distinct order, with some overlapping or undertaken in parallel over time. Requirements and resources can be defined at the outset (e.g. work packages, contingencies, cost and schedule estimates) and projects are executed as planned. Various tools and techniques are employed to reduce risks and uncertainty and by efforts to control and manage projects within time, cost and quality constraints. Projects versus Operations While project management is often treated as a management discipline in its own right (Morris, 1994; Morris et al., 2011), it is also part of the broader discipline of operations management, where it applies to the unique, one-off production stage end of a spectrum from low to high-volume operations producing standardized products and services for mass markets (Wheelwright and Clark, 1992; Browning, 2017). Project management textbooks, by contrast, often draw a sharp distinction or dichotomy between unique, discrete and non-repetitive projects and standardized, ongoing and routine operations. Until recently, projects were often considered to be the “antithesis of repetition” and ideally suited for achieving innovation and change (Pinto, 2010, 25–27). Despite recognizing that some projects contain “repetitive elements” (PMI, 2008, 5) and that “the process by which it is delivered is often repeated over time” (Maylor, 2005, 5), most scholars and professional bodies emphasized that this element of repetitiveness does not undermine the “fundamental uniqueness of project work” (PMI, 2008, 5). Perhaps because projects are defined in a singular way as entirely novel and unique, the literature rarely distinguishes between projects based on their degree of novelty (a core attribute of innovation) and associated uncertainty. In practice, however, innovation undertaken by projects varies considerably from largely predictable and known incremental changes or adjustments to products and services at one end of a spectrum to far-reaching radical changes and breakthrough innovations that are new to the world at the other end. As the degree of novelty

8  Handbook on innovation and project management

increases, projects become increasingly uncertain, particularly but not only during the “frontend” planning phase when they involve fuzzy, ill-defined customer requirements, unknown technological possibilities and many other contingencies that cannot be foreseen at the outset and may disrupt carefully prepared plans during execution. Different types of project organizations and processes are, therefore, required to match varying degrees of innovation. As we will see below, several scholars have suggested that traditional project management structures, processes and techniques designed for stability and predictability are unable to deal with increasingly novel, changing and unpredictable projects (Pich et  al., 2002; Loch et al., 2006; Shenhar and Dvir, 2007). Revisiting the historical origins of project management, Lenfle and Loch (2010) challenge the underlying assumption of the discipline that the control, phased-based standardized model was developed and widely used on the Manhattan, Atlas, Apollo and other systems. They show that these projects had to be flexible and adaptive to deal with unforeseeable uncertainties and developed many techniques (not considered in traditional project management) to experiment and test alternative solutions, such as the parallel development of new technologies and experiential learning from the feedback gained during project execution. Project Management Embraces Theory Over the past few decades, there have been several attempts to import theories from other disciplines to develop a more rigorous understanding of project management (Söderlund, 2011). Although innovation may not always take centre stage, this work is important because it provides conceptual background for several chapters in this Handbook and research seeking to build bridges between project management and innovation. In the 1980s, some prominent scholars working inside the discipline began to criticize the traditional model of project management for an almost obsessive focus on execution and failure to consider the key strategic conditions – including technological and organizational innovation – shaping how projects are successfully planned and delivered in different organizational and institutional contexts (Morris and Hough, 1987). Morris (1994) advocated the need for a new paradigm – the “management of projects” – to understand how projects are managed in their entirety from front-end definition, through execution to commission, start-up and operations. Morris (1994 and 2013) suggested that innovation and organization theory (e.g. Burns and Stalker, 1961) provide useful frameworks for identifying how project organizations are configured in various ways to address different technological and market environments. Many other leading scholars have since attempted to reinvigorate the field of project management by developing a broader, more theoretically informed view of the subject (Morris et al., 2011), striving for greater disciplinary recognition for scholarly research by improving the quality of academic journals particularly the International Journal of Project Management and Project Management Journal. In the 1990s, a growing number of scholars working outside the discipline have become increasingly interested in understanding how projects are organized, but widely dissatisfied with how they are conceptualized in the traditional project management literature. In what is now known as “project studies” (Geraldi and Söderlund, 2018), this research first emerged in Scandinavia and France when scholars drew upon organization theory to provide new insights and perspectives on how organizations work together in “temporary” projects and how projects are embedded in “permanent” organizations (Midler, 1993; Giard and Midler, 1993;

Introduction 

9

Lundin and Söderholm, 1995; Jolivet and Navarre, 1996). Concerned with understanding how projects evolve in different contexts, project studies emphasize that projects both shape and are shaped by the wider development of organizations, globalization, networks, fields, industries and societies. This work recognizes that “no project is an island” (Engwall, 2003): what happens inside a project must be understood in its broader organizational context and in relation to past, current and future projects. Project studies have grown and diversified since the late 1990s to encompass other disciplines such as economic geography (Grabher, 2001) and perspectives such as network theory (Manning and Sydow, 2011; Manning, 2017) and institutional theory (Söderlund and Sydow , 2019). This is particularly evident in research exploring the link between projects and innovation (e.g. Midler, 1995; Lindkvist et al., 1998; Hobday, 2000; Gann and Salter, 2000; Lenfle, 2016), organizational learning (Lundin and Midler, 1998; Brady and Davies, 2004), experimentation (Gillier and Lenfle, 2019; Ben Mahmoud-Jouini and Midler, 2020), design theory (Lenfle, 2016), and digitally enabled project delivery models (Whyte, 2019). Several seminal contributions on the dilemmas and challenges of temporary organizing can be found in two special issues of Organization Studies (Sydow et al., 2004; Bakker et al., 2016). Since the early 2000s, scholars applied various theoretical perspectives to understand the novel governance, organizational and institutional arrangements for managing increasingly large-scale, global megaprojects and their role as vehicles for transformational change. First, a study of 60 complex and uncertain “large-engineering projects” (e.g. offshore oil platforms, hydroelectric dams and subways) around the world found that front-end strategizing, new forms of governance and careful risk management contributed more to successful outcomes than conventional execution-oriented project management (Miller and Lessard, 2000). Second, a growing body of research on “megaprojects” that cost US$1 billion or more – including “Big Science” R&D projects (e.g. the Large Hadron Collider) behind breakthroughs in science and radical technological innovation – has found that such projects are frequently late and over budget because of inadequate front-end planning and behavioural bias, primarily due to unrealistic assumptions and overly optimistic expectations about initial budgets and schedules (Flyvbjerg et al., 2003; Flyvbjerg, 2014, 2017) but also political tensions about partial goals (Jimoh et al., 2022). Third, another stream of research examines the range of traditional and new institutional arrangements for “global projects” (e.g. energy and transportation infrastructure) and how stakeholder alignment and political conflicts are addressed when various parties become involved in large, temporary cross-national, public–private partnerships (Scott et al., 2011; Levitt et al., 2019). Despite efforts to rethink the foundations of the discipline, the development and adoption of new theories have been slow and erratic (Huff, 2016). Many project management professionals and academics teaching the subject in business schools and engineering departments continue to promote the standardized model and fail to distinguish between projects according to their degree of innovation and uncertainty and ignore the context which shapes their development. Project management associations, in particular, tend to adhere to the normative view of how a project ought to be managed (as described in various bodies of knowledge), rather than the manifold ways in which they actually occur and are managed in different contexts around the world. Project Novelty, Complexity and Flexibility The classic view of “how projects ought to be managed in general” was, however, flawed almost from the outset. In the study that is often cited as coining the term “stage gate process”

10  Handbook on innovation and project management

(see next section), Cooper (1983, 5) conceded early on that “the new product manager is … faced with the complex task of managing a highly uncertain endeavor where many things must be done properly and a single miscue can spell disaster”. This statement is compatible with the view that projects represent “bundles” of challenges that do not all pull in the same direction. Despite recognizing that different challenge configurations must be treated differently, the stage-gate blueprint ended up being used as a single standard process for handling projects. But work in the early 21st century clearly spread the realization (rediscovering what the RAND analysts knew in the 1950s; see Lenfle and Loch, 2010) that different projects require different processes (e.g., Shenhar and Dvir, 2007; Loch et al., 2006). This is illustrated in Figure 1.2, which shows that the demands on project management flexibility differ depending on the extent of the novelty of the territory that the project attends to (lower horizontal axis) and on the extent of stakeholder demands and complexity (upper horizontal axis). The increasing novelty of the terrain is associated with decreasing knowledge and related to uncertainty and unpredictability, which range from risk, where only the magnitudes of known variables “tremble”, to unforeseeable uncertainty where neither risk factors nor actions can be foreseen. Novelty may stem from customer novelty (including “users” such as government agencies), technical novelty, regulatory novelty (including sustainability), system novelty (including integrating existing components with new interdependencies) or process novelty (including the supply chain). Novelty implies a demand for flexibility, including the ability to deviate from a plan fixed at the outset requiring iteration (or plan adjustments), parallel trials or redundancy (e.g. overdesign to enable more outcomes, so changes in the terrain can be accommodated). All three are managerial choices that represent sources of flexibility. Flexibility is required to adjust not only to unforeseen or unforeseeable events but also to sensitivities and changing desires.

Figure 1.2  Project management flexibility is demanded by novelty and complexity (dotted line refers to stakeholder complexity and solid line refers to territory)

Introduction 

11

For example, we may know exactly what different configurations an innovative project aims to produce, and yet still need to change the plan when stakeholders simply insist on it and use their bargaining power to force through a change, even if that change results in poor performance. Stakeholder change management requirements for flexibility in the project are, therefore, quite different from the implications of uncertainty (the U-shaped dotted curve). A single stakeholder or small coalition may have sufficient power to force through any significant changes, whereas when there are several stakeholders, the priorities and interests of each entity may play off against each other resulting in a so-called “average” outcome and less need to change plans. When stakeholders become numerous and influence one another in unpredictable ways, “taste swings” may occur requiring significant changes and considerable flexibility for the project to proceed. Complexity has a similar effect. Indeed, stakeholder involvement in a project may be considered a special instance of complexity. When complexity is low, participants are more likely to agree to proposed changes that are easily implemented. As the system becomes complex, stability is required to prevent the possible cascade of changes that might disrupt a project. When complexity is very high (a “deeply complex system”), even small changes, wobbles or overlooked interactions, especially over the long timeframes that highly complex projects often take, can cause the whole system to shift. When such deep complexity causes uncertainty, flexibility is increasingly necessary to absorb the inevitable, far-reaching changes. As Figure 1.2 illustrates, when two projects are situated at different positions in this uncertaintycomplexity space, they require different levels of planning and execution flexibility and different project processes to be able to respond to the demands of their environments. Before looking at recent research that bridges the innovation and project management literatures, let us first consider the ways in which projects have been treated in some of the classic and influential contributions to the innovation management literature. In describing innovation research as providing an “outside view of project management”, let us remind the reader that the separation between the two literatures has never been complete. Even the earlier-mentioned article that coined the term “stage-gate process”, Cooper (1983) was a study of product development (innovation), and the most popular product development textbook (Ulrich and Eppinger, 2012) has a whole chapter on project management as the primary means of getting product development done.

HOW “PROJECTS” ARE CONCEPTUALIZED IN INNOVATION STUDIES Unlike project management, scholars interested in innovation have not been constrained by the need to create a standardized and universally applicable body of knowledge. Informed by a variety of theoretical perspectives, the field of innovation studies is concerned with understanding the sources and dynamics of innovation (Abernathy and Utterback, 1978; Utterback, 1994) and how organizations implement new combinations of novel ideas, existing knowledge and routines to achieve successful innovative outcomes (Nelson and Winter, 1982), such as new products, services, processes, forms of organizing and business models. Firms require dynamic capabilities to adapt, integrate and recombine internal and external resources, routines and competencies to manage innovation and keep pace with rapidly changing environments (Teece, 2009). As knowledge is imperfectly shared over time and geographies and

12  Handbook on innovation and project management

across people, organizations and societies, existing and well-established ideas from one firm or industry often appear new and creative as they change form and combine with other ideas to provide innovative solutions to problems found in another firm or industry (Hargadon and Sutton, 1997). Diverse Theoretical Foundations of Innovation Studies The origins of innovation studies (like project management) can be traced back to the 1950s and 1960s when government-sponsored large-scale projects were established in the United States to create complex military weapons and defence systems. Economists and social scientists at the RAND Corporation sought to understand how to improve innovation in complex projects, such as intercontinental ballistic missiles and fighter jets, which were highly uncertain in cost, time, quality and operational outcomes (Klein and Meckling, 1958). RAND studies identified the uncertainties associated with innovative projects and discrepancies between estimated and actual costs and time spent on projects (Peck and Scherer, 1962). The connection between innovation and project organizations became the focus of research for scholars working in a variety of fields from the early 1960s, such as organizational theory (Burns and Stalker, 1961), industrial economics (Freeman, 1974), product development (Cooper, 1985), operations management (Wheelwright and Clark, 1992), entrepreneurship (Kanter, 1990), strategy (Christensen, 1997) and organizational design (O’Reilly and Tushman, 2004). Despite working in different disciplines and on different topics, all of these contributions share the view that selecting, organizing and managing projects is the key to successful innovation. Scholars responsible for developing contingency theory in the 1960s challenged the prevailing view that there is “one best way to organize” applicable to all industries (Woodward, 1965) and suggested that innovative project-based organizations require “organic” or “ad hoc” structures to deal with novel, uncertain, complex and fast-changing environments (Burns and Stalker, 1961; Lawrence and Lorsch, 1967). Innovation is a core task performed in projects by producers of novel or highly customized products, services or events (e.g. aerospace, defence, telecoms, construction, advertising, film-making, consulting and complex capital goods) (Woodward, 1965; Hobday, 1998, 2000). Everything these project-based organizations do either internally for themselves (e.g. NASA) or for external customers (e.g. IBM) is accomplished through projects (Mintzberg, 1979). Project Uncertainty and the Innovation Process In his work on industrial innovation, Freeman (1974) emphasized that one of the main difficulties facing firms is managing the risks and uncertainties associated with R&D and innovation projects. Following Knight’s (1921) classic distinction, Freeman (1974) suggested that innovation involves projects ranging from truly uncertain (unmeasurable uncertainty) to less risky (or measurable uncertainty) and more predictable ones. Subsequent research has shown that traditional risk management and contingency planning may work well for stable projects facing foreseeable uncertainties, whereas prototype testing, pilot plant production, iterative learning from experience and parallel trials with alternative technologies may be required for highly innovative projects facing unforeseeable uncertainties (Abernathy and Rosenbloom, 1969; Pich et al., 2002; Loch et al., 2006).

Introduction 

13

A portfolio approach helps firms select projects by offsetting a few large, uncertain investments in radical innovation against a large number of less risky endeavours (Cooper et al., 1997; Kock et al., 2015). Bottom-up, small-scale and unofficial innovation projects are sometimes undertaken by adventurous people and teams that deliberately circumvent strict portfolio evaluation criteria. Firms often engage in “bootlegging” by tacitly accepting or even encouraging under-the-table, covert innovative projects, which might not be undertaken because they involve such a high degree of uncertainty (Schön, 1963; Freeman and Soete, 1997; Augsdörfer, 2005; Criscuolo et al., 2014). Building on NASA’s approach to project planning in the 1960s, Cooper (1985) suggested that the process of taking a new idea from concept to implementation resembles a funnel with a series of stage gates in a project life cycle from the “fuzzy” conceptual, ideation phase through product definition and development to testing, launch and production (Cooper, 1985; Cooper and Kleinschmidt, 1987). In recent years, many large firms have shifted from a closed model of innovation where the product development funnel is largely in-house to a more open model formed with multiple parties in inter-organizational projects – such as Proctor & Gamble, Intel, Google and Netflix – which leverage internal and external sources of ideas to create innovative solutions to well-formulated problems (Chesbrough, 2003; Dahlander and Gann, 2010; Chesbrough et al., 2014). Innovative projects often fail to make it across “the valley of death” when they move from the creative, uncertain front-end stage of R&D into what is often the more rigid, risk-averse product development stage (Midler, 2019b). In the pharmaceutical industry, for example, drugs that make a real impact on diseases, such as Alzheimer’s and other forms of dementia, depend on nourishing exploratory, scientific research and development in laboratories and then helping promising projects move across through a stringent regulatory process into clinical trials and large-scale production. Revolutionizing New Product Development Pioneering research showed how product development was revolutionized by new lean development approaches established by Japanese car manufacturers (e.g. Toyota and Honda) in the 1970s and 1980s (Wheelwright and Clark, 1992; Clark and Fujimoto, 1991; Womack et  al., 1990). Japanese firms in electronic consumer goods industries (e.g. Fuji and Canon) introduced the “overlay” approach for developing new products in overlapping or concurrent phases (Takeuchi and Nonaka, 1986; Clark and Fujimoto, 1991; Eisenhardt and Tabrizi, 1995; Terwiesch and Loch, 1999), combining flexibility in product design with the acceleration in pace offered by lean development. Using the overlay approach, product development teams absorb new information and engage in iterative, trial-and-error learning and adaptive process to narrow down the number of design alternatives they have to consider. In more recent research, Edmondson (1999, 2012) suggests flexible product development projects engage in a process of “teaming” to deal with uncertainties facing innovative projects, with leaders who build the “psychological safety” required to tolerate the failures that come with experimentation and embrace the conflict that often arises when diverse groups of people with different priorities and values work together. The typology of innovation projects developed by Wheelwright and Clark (1992) is still influential and widely used to understand how innovation is managed in fast-paced, uncertain and globally competitive markets (Shenhar and Dvir, 2007; Midler, 2019a). Derivative,

14  Handbook on innovation and project management

platform and breakthrough projects are distinguished according to the degree of novelty in products and processes on a continuum from incremental to radical innovation. At the incremental end of the spectrum, derivative projects undertake cost reductions or minor adjustments to existing products or processes. On the other end, breakthrough projects are highly uncertain because they create radically new processes or untried products, leading to revolutionary improvements in productivity (e.g. Toyota’s just-in-time system of manufacturing) or the creation of entirely new markets (e.g. the introduction of Apple’s iPhone in 2007). Situated in the middle, platform projects create new processes or products for customers in existing markets, such as each new generation of iPhone. Wheelwright and Clark’s (1992) four-part classification of team structures – functional, lightweight, heavyweight and autonomous – has also profoundly shaped how contemporary scholars understand the types of organization required for innovative projects (e.g. Hobday, 2000; Shenhar and Dvir, 2007). An autonomous team structure, for example, is set up to deal with unforeseeable uncertainties associated with breakthrough projects, such as integrating new technologies and anticipating unknown user needs and future operational requirements. Keeping the structure separate poses less of a threat to the mainstream business and provides the autonomy needed to develop the new technology without becoming overly constrained by established fiefdoms, formal plans, board approval or bureaucratic procedures that might constrain efforts to change direction. A heavyweight project manager has full control of resources and people from different functional groups working in permanently co-located integrated teams for the duration of the project. For example, pioneered by Lockheed Martin, the American aerospace and defence manufacturer, so-called “Skunkworks” project organizations were established as autonomous structures to develop high-technology systems in the utmost secrecy, such as the U-2 spy plane and F-117 Stealth Fighter, far removed from the mainstream organization and the influence of established routines, rules and procedures which might otherwise inhibit innovation (Rich and Janos, 1994). Contrasting Types of Innovative Projects Many well-known scholars have suggested that contrasting types of innovative projects are required for existing or new markets. Kanter (1990) argued that “mainstream projects” make enhancements (derivative) to existing products or create new ones (platform) for customers with stable preferences and predictable requirements in established markets. Firms are successful in mainstream projects because they depend on proven technologies and listen to their customers before developing new and improved products or services. Projects can be carefully planned and schedules developed before action is taken because firms have a history and experience base in the market, providing fairly accurate data for predictions about future market requirements. However, ongoing investments and commitments designed to keep mainstream projects flowing also make it difficult to change direction when products become obsolete or markets stagnate and decline. Firms launch “newstream projects” to imagine new possibilities and create the (breakthrough) innovation needed to change direction and open up entirely new markets. Because firms have little or no experience in the new offering and there are no existing customers to listen to, forecasts about customer needs are impossible to produce, project schedules are unrealistic and costs are likely to overrun. Action must be taken during the front end before plans are developed to recognize dimly perceived opportunities and tasks adjusted

Introduction 

15

to address unforeseen circumstances while the project is underway. Existing knowledge is applied where possible, but new ideas are often nurtured and developed through random and intuitive insights. The purpose of the project is clarified through experimentation to discover “what is possible and what might be possible” (Huff, 2016, 14). Flexibility, speed and multiple approaches undertaken in parallel are required to make sense of evolving customer requirements and poorly understood technologies (Eisenhardt and Tabrizi, 1995; Loch et al., 2001). For example, Apple was a successful computer and music software firm when it entered the established mobile industry dominated by a few large, well-established manufacturers. To mitigate the immense uncertainty associated with its breakthrough innovation, Apple secretly developed two phones in parallel, one based on the iPod nano (code name P1) and the other multi-touch phone based on a tablet (P2). After a few months of testing prototype phones, the more uncertain but potentially promising multi-touch P2 was selected and introduced in 2007 (Kahney, 2014). Christensen (1997) makes a similar distinction between types of technological projects. Whereas “sustaining technologies” require projects to improve the performance of products and services valued by existing customers, “disruptive technologies” ultimately promise to open new and rapidly growing markets, although they may not be valued by customers in the near term. Christensen (1997) identified the electric vehicle as the car industry’s disruptive technology and recommended that General Motors establish a small, separate project-based organization to nurture, develop and commercialize the new technology. However, the industry was eventually disrupted when Tesla, a start-up from outside the industry, established a small project team with its own office in Elon Musk’s SpaceX factory to develop and commercialize the Model S electric car. Building on March’s (1991) well-known distinction between exploration and exploitation, O’Reilly and Tushman (2004) suggest that firms need ambidextrous organizational designs (often based on effective portfolio management) to “exploit” current projects (e.g. derivative and platform) for existing customers markets while launching breakthrough projects to “explore” new technologies and open up new market opportunities (Raisch et al., 2009; Tushman et  al., 2010). The most effective breakthrough projects share resources with the mainstream organization and are tightly integrated with mainstream organization, but are geographically and organizationally separate to ensure that the freedom required to develop and implement new ideas is not constrained by established organizational priorities and procedures. For example, Apple’s product development remained inside the organization but was established as a small team of talented designers with the autonomy of an outside consultancy firm to select and work on multiple breakthrough projects. Incorporating these contributions and more recent insights, innovation management emerged as the distinct discipline and fairly coherent field of management research with a growing number of textbooks offering theoretical insights and practical guidance on how innovative projects can be more successfully managed (e.g. Tidd et al., 2001; Dodgson et al., 2008; Schilling, 2020). Significant work on innovative projects has appeared in a range of management journals such as California Management Review (e.g. Clark and Wheelwright, 1992), Organization Science (e.g. Hoegl and Gemünden, 2001), Research Policy (e.g. Hobday, 2000) and Journal of Product Innovation Management (e.g. Edmondson and Nembhard, 2009). In recent years, research has expanded beyond traditional classifications of innovative projects based on product/process, incremental/radical, open/closed and sustaining/disruptive dichotomies to include business model innovation, service innovation, platforms, ecosystems

16  Handbook on innovation and project management

and sharing economy platforms (e.g. crowdsourcing). We now consider efforts to explore the synergies between the fields of innovation and project management.

RESEARCH BRIDGING INNOVATION AND PROJECT MANAGEMENT As we have seen, project management and innovation studies have common roots in American defence and aerospace projects of the 1950s and 1960s. At the time, both were perceived to be strongly interrelated domains (Lenfle and Loch, 2010) and contemporaries may have been surprised to discover many years later that project management and innovation studies became increasingly specialized disciplines, following largely self-contained trajectories of scholarly and practical development. Joint Roots and Contrasting Trajectories An important study of weapons systems projects in the early 1960s conducted by RAND researchers identified two contrasting models for identifying and managing the uncertainties surrounding highly innovative projects (Klein and Meckling, 1958), which would characterize an ideological divide between project management and innovation studies lasting for decades (Brady and Hobday, 2011; Davies, 2014; Davies et al., 2018). Widely practised in project management, the “optimizing model” assumes that rational planning, formal processes and analytical techniques applied at the start of the project are able to predict future conditions and reach a decision about the optimal end product from a range of alternatives. Influential in innovation studies, the “adaptive model” recognizes that innovative projects are fundamentally uncertain, because unexpected situations may arise that cannot be fully known at the outset, such as new technologies, strategic factors and a changing operational environment. The adaptive model emphasizes the importance of intuitive judgement, informal processes and learning gained from trial-and-error experience and the need to experiment, test and evaluate alternatives before selecting the preferred solution. Despite sharing the same roots, over the subsequent years, the two disciplines failed to recognize each other’s contribution to a shared research agenda and there was little incentive to overcome the fragmentation of research by learning from each other and integrating the different bodies of knowledge (Davies et al., 2018). Researchers specializing in project management were stimulated by the urgent need to provide firms in many industries with practical guidance based on standardized bodies of knowledge. As we have seen, scholars working inside and outside the discipline eventually became dissatisfied with project management’s focus on execution-oriented practical knowledge and initiated new streams of theoretical research to move beyond the optimizing model, such as the management of projects paradigm and project studies. While innovation studies emerged from a variety of disciplines and theoretical perspectives, many researchers shared a common interest in understanding how different types of innovative projects are organized to deal with varying degrees of uncertainty. By the 1990s, innovation management had emerged as a specialized body of theoretical and practical knowledge published in textbooks (e.g. Tidd et al., 2001) and handbooks (e.g. Dodgson et al., 2014). Although the two disciplines became increasingly isolated from each other, project management and innovation studies are considered neighbouring disciplines because they often refer to the same concepts (projects, innovation, novelty and uncertainty) and have overlapping

Introduction 

17

empirical domains (e.g. R&D and new product development) and topical interests (e.g. the climate emergency grand challenge) (Davies et  al., 2018). In recent years, scholars working in the two disciplines have slowly begun to acknowledge each other’s contributions and recognize the benefits of importing, exporting and sharing theories and concepts to promote the inter-disciplinary collaborative research needed to tackle changing empirical realities and societal challenges (Davies et al., 2018). For example, a special issue in 2016 of the Project Management Journal was produced to showcase research bridging the two domains and integrating theory and practice (Midler et al., 2016). The Project Management Journal also published a special issue on exploratory projects (Lenfle et al., 2019). The Journal of Operations Management has published articles on innovation and project management since its foundation in 1980 but created a new department for Innovation and Project Management in 2019 in recognition of the growing importance of both domains and the connections between them (Mishra and Browning, 2020). Reconnecting and Developing Domains of Knowledge In the early 2000s, two early and significant contributions attempted to create a new synthesis and integrated framework for innovation and project management research. An evolutionary approach for coping with the uncertainty surrounding innovative projects is developed by Loch, DeMeyer and Pich in Managing the Unknown (2006) and other articles (e.g. Pich et al., 2002; Loch and Sommer, 2019). Following an “instructionist” approach, traditional project management is sufficient as long as task scheduling, risk management and contingency planning can trigger the actions needed to deal with foreseeable events and predictable future conditions. Different strategies are required, however, when projects face unforeseeable uncertainties including “learning” to conduct new planning and change direction when the project is underway and “selectionism” to identify the best candidate from multiple solutions explored in parallel (e.g. Lenfle, 2011). A contingency model grounded in innovation theory is developed by Shenhar and Divir in their book Reinventing Project Management (2007) and various articles (e.g. Shenhar, 2001) to move beyond the conventional one-size-fits approach. Projects vary depending on where they are positioned in a diamond model comprising four different dimensions: system complexity, technological uncertainty, market novelty and pace. The model identifies the right approach required to manage the particular mix of variables facing each project. As we will see in this Handbook, an increasing number of scholars are now conducting research on these overlapping domains, revisiting existing concepts, introducing new theoretical perspectives and challenging our current understanding. In Figure 1.3, we include an important third domain to capture how other disciplines (e.g. organization studies, institutional theory and strategy) and the field of project studies are increasingly connected to research on innovation and project management. Here we highlight four streams of wellestablished research crossing the domains. First, research on R&D and new product development has evolved to deal with the more dynamic and innovative projects of the 21st century, such as the new forms of concurrent product development projects driven by deadlines (Lindkvist et al., 1998; Midler, 2019b), the exploratory nature of research-intensive technology projects (Lenfle, 2008, 2016), the role of dynamic capabilities in selecting and sharing innovative design features across multiple products (Maniak and Midler, 2014; Maniak et al., 2014), managing projects to achieve disruptive

18  Handbook on innovation and project management

Other disciplines (e.g. strategy) & fields (e.g. project studies)

Project Management

Innovation Management

Figure 1.3  Overlapping domains of knowledge innovation (von Pechmann et al., 2015) and the role of ambidexterity in project management (Turner et al., 2014). Hatchuel and Weil’s (2009) research on design theory and creative collective action, emphasizing the dialectic between the exploration of breakthroughs concepts and construction of new knowledge, provides a valuable conceptual framework for understanding exploration projects (Lenfle, 2016) and cross-project learning (Maniak and Midler, 2014). Second, research on organizational capabilities, routines and learning in projects has shown that innovation requires project-based organizations or firms (Hobday, 2000; Gann and Salter, 2000; Whitley, 2006); how vanguard projects are launched to explore changing market conditions and innovative opportunities (Brady and Davies, 2004; Lenfle, 2008); and how project capabilities are honed, developed and exploited by transferring knowledge and learning from one project to the next (Lundin and Midler, 1998; Lundin et al., 2015; Prencipe and Tell, 2001; Söderlund, 2005; Davies and Brady, 2016) to obtain “economies of repetition” (Davies and Brady, 2000). Organizations may follow two action trajectories (based on contrasting degrees of repetitiveness) by performing routines to get repetitive things done or pursuing “creative projects” to achieve new things through innovation (Obstfeld, 2012). Third, research suggests that organizations responsible for complex projects build or acquire capabilities in systems integration to coordinate the design, production and integration of component parts of the product or system architecture (Hobday, 1998; Brusoni and Prencipe, 2001; Prencipe et  al., 2001; Davies et  al., 2009; Tuertscher et  al., 2014; Whyte and Davies, 2021). Modular product platforms based on standardized design interfaces and interoperable “plug and play” components may help to minimize the risks of integration (Sosa et al., 2004; Von Pechmann et  al., 2015) and facilitate the coordination of interdependent organizations (Jacobides et  al., 2018) involved in each project. Apple, Amazon and Google, for example, have developed digital platforms of interchangeable modules that can be updated and transferred from one project to the next. Platform strategies have recently migrated from digital to more traditional industries, such as automotive, shipping, construction and space exploration. For example, whereas NASA has traditionally treated each rocket launch as a one-off, bespoke project, SpaceX treats each rocket as a platform of interoperable component technologies that can be reused and replicated at lower cost across multiple projects (Ansar and Flyvbjerg, 2022).

Introduction 

19

Fourth, research has explored how innovation has been applied to plan, design and execute megaprojects. Flexible architectures, modular designs and integrated project teams provide the adaptability required to accommodate evolving requirements (Gil and Tether, 2011) and unexpected interdependencies (Tee et  al., 2018). The innovative potential of a megaproject may be enhanced by developing the absorptive capacity to incorporate new and evolving technologies (Gil et al., 2012) and dynamic capabilities required to balance the need for stability and change in a large, complex megaproject (Davies et al., 2016; Davies et al., 2017). In a collaboration between researchers and practitioners, an open innovation strategy and digital platform were developed and applied to introduce new ideas, technologies, materials and practices while London’s Crossrail railway megaproject was underway (Davies et  al., 2014). Research also identifies some of the new delivery models (Davies et al., 2019) and simple rules for innovation in megaprojects required to limit goal tensions and politics (Jimoh et al., 2022) and to address unforeseeable uncertainties and opportunities to improve performance (Davies et al., 2017).

INNOVATION AND PROJECT MANAGEMENT: INTEGRATED RESEARCH THEMES AND PERSPECTIVES In developing the idea and our ambition for the Handbook, we were mindful of the need to encourage the authors to develop and apply new theoretical perspectives to integrate research on innovation and project management, cross-fertilize ideas between the two domains and offer practical guidance on how to manage innovative projects in real-world settings. The chapters were carefully selected because the authors have made significant scholarly contributions that traverse the two domains and are highly committed to developing a new, more integrated research agenda. The Handbook is divided into four parts to account for the variety of perspectives, conceptual contributions and case studies with practical examples of how innovative projects are organized and managed. Some chapters are relevant to all parts of the Handbook and are allocated according to their primary contribution. Part I: Converging and Integrating The chapters in the first part, following this chapter, consider the convergence of innovation, project management and closely related disciplines and discuss integrated perspectives, models and frameworks that straddle the different domains. •

•

The intersection between research on innovation studies and project studies has crossfertilized and generated many new theoretical ideas, concepts and frameworks. However, important cross-disciplinary and inter-disciplinary research in these overlapping domains can be extended further by a meta-theoretical framework and new research agenda proposed by Geraldi and Söderlund (Chapter 2). Georget and Maniak (Chapter 3) examine the evolution of two distinct disciplines – corporate entrepreneurship and project management – and consider how each conceptualizes the role of innovation in the organization and strategy of the firm. Despite some differences in approach, there are many similarities between the two disciplines and opportunities for cross-fertilization leading to a more integrated model of innovation.

20  Handbook on innovation and project management

•

•

•

•

While scholars in the separate research communities interested in projects and innovation have not always engaged in a fruitful interaction, Holzmann and Shenhar (Chapter 4) suggest that they are actually addressing two sides of the same process: developing and implementing new ideas. They present an integrated theoretical and practical model for examining the processes, contingencies and strategies of this combined innovation/ project effort. In a review of the literature, Lewis, Harrison and Roehrich (Chapter 5) focus on one key concept – the fuzzy “front-end” of projects or the innovation process – which appears extensively in research on innovation and project management. The chapter explores opportunities for the two domains to share insights about how to conceptualize the front end and identifies promising avenues for future research. Tillement, Garcias and Charue-Duboc (Chapter 6) explore how the concepts of exploration and exploitation are used differently in the literatures on innovation management and project management. A case study of the first French Generation IV nuclear reactor illustrates how the dynamics of “exploration and exploitation” are entangled in some largescale “hybrid projects”. The case identifies the tensions associated with this entanglement and how the “identity” of the project was disputed by major stakeholders (managers and government) leading to its eventual postponement. In their study of the internationalization of innovation projects in multinational corporations (MNCs), Midler and BenMahmoud-Jouini (Chapter 7) seek to bridge two streams of distinct but complementary research on global innovation management (GIM) and global innovative projects (GIP). Whereas GIM emphasizes the innovation strategy, capabilities and organization of the MNC’s spatially dispersed local-global activities, GIP addresses the management of innovative global projects. The two approaches are complementary and mutually supportive because the global innovation strategy of the MNC is implemented through projects and innovation projects play a reciprocal role in defining the innovation strategy and the dynamics of an MNC’s organization.

Part II: Building and Extending The second part of the Handbook includes chapters that build on and extend existing concepts, frameworks and ideas that have already developed connections between innovation and project management research. •

•

“Lineage management” and “ambidexterity” examined by Maniak and Midler (Chapter 8) are two recent strategies to manage innovative projects and overcome the limitations of multi-project management methodologies, project portfolio management and common product platforms introduced in the 1990s. Lineage management involves creating disruptive offers by progressively capitalizing on a series of projects generated by a trajectory of innovations and adapting to take advantage of learning accumulated along the way. Ambidexterity strategies are used to manage innovative projects by “exploring”, developing and accelerating breakthrough innovations, while “exploiting” committed project resources. In a review of research on “exploratory projects”, Lenfle (Chapter 9) identifies how project management has neglected to fully account for how projects are organized and managed to tackle “unknown unknowns”. A future research agenda for exploratory projects is

Introduction 

•

•

•

21

proposed outlining the need for new case studies, management tools and methods design, governance and portfolio management, and a theory of agency for projects facing unforeseeable uncertainties. Building on prior research on novel projects facing unforeseeable uncertainties, Loch, Sommer and Jiang (Chapter 10) consider two automotive projects – rapid manufacturing and flying vehicle projects – combining new and evolving technologies and applying them to new uses and markets. The cases illustrate that a “Project Learning Process” for novel projects must be identified at the outset as a valuable activity in its own right, but that it will accomplish nothing unless accompanied by a long-term vision, which is agreed upon and authorized by top management. In their study of “project portfolio management”, Kock and Gemünden (Chapter 11) emphasize that portfolio management for innovation projects is challenging because firms pursue several and often conflicting goals in uncertain markets. A decision-making model is proposed to identify success factors for the different groups of stakeholders involved in innovation projects with varying degrees of innovativeness (derivative, platform and breakthrough) and contingent on various interdependencies between projects and the environment. Van Den Ende and Blindenbach-Driessen (Chapter 12) show how “project-based organizations” have advantages over mass production firms because they are less focused on improving operational efficiency and more equipped to perform organization-driven proactive and client-driven responsive innovation. As an alternative to relying on an innovation manager to develop, select and organize innovative projects, firms can achieve “ambidexterity” by establishing a separate unit in a project-based organization to undertake exploratory, proactive radical innovation, sheltered from the demands of operational units.

Part III: Importing and Cross-Fertilizing The third part of the Handbook includes chapters that have imported theories, concepts and frameworks from outside the domains of innovation and project management to cross-fertilize ideas and stimulate new thinking. •

•

Building on the concepts of “collaboration” and “trust” developed by scholars working outside the domains of innovation and project management, Noorderhaven (Chapter 13) discusses how trust can stimulate positive outcomes by enabling collaboration between participants in innovative projects. Because trust and collaboration are so closely connected and it is difficult to ascertain which comes first, Noorderhaven suggests they are best conceived as mutually reinforcing and together form a “positive spiralling effect” on the performance of innovative projects. In an ambitious and creative effort to draw upon theories of culture found in anthropology, organizational theory and evolutionary biology, Loch, Kavadias and Sommer (Chapter 14) develop a “cultural evolution model”. While partially codified, project management practices are socially learned evolving bodies of knowledge or culture. The model is used to show how the ambidexterity required to balance innovative and routine projects is not simply determined by high-level managerial goals but may evolve culturally in a dynamic interactive process of top-down strategy and bottom-up project learning and evolutionary pressures.

22  Handbook on innovation and project management

•

•

•

•

Informed by case study examples of international development, film production and event organizing, Manning and Vavilov (Chapter 15) identify how the challenges of “social innovation” (ideas, methods and practices that address social problems and large-scale, societal grand challenges) may be stimulated and mitigated by three dimensions of project-based organizing: project entrepreneurship (individual), project capabilities (organizational) and project networks (inter-organizational). Drawing upon recent literature on project ecologies and innovation ecosystems, MacAulay, Davies and Dodgson (Chapter 16) introduce the concept of “project innovation ecosystems” to explain a new approach to creating and capturing value through innovation in large, complex projects. A case study of London’s Crossrail railway infrastructure project identified how a “meta-organization” was established to orchestrate innovation and reveals how research on project innovation ecosystems can inform the study of innovation and project management. Hooge and Lenfle (Chapter 17) consider how the concept of “value management” has been applied since the 1960s to model the benefits whilst minimizing the costs of innovative projects for customers. The process of constructing value for new product development has been enriched in recent years by a variety of new tools to help both project and strategic managers evaluate the future benefits of not-yet-existing products and services. As societies face climate change, biodiversity decline and other challenges, models of value management going beyond conventional monetary measures of performance (profit and technological abundance) are needed to address the generative, desirable and attractive value of the unknown. In a fascinating in-depth empirical study of Italian opera (an example of a creative industry) where each show is a project, Cancellieri, Cattani and Ferriani (Chapter 18) argue that opera houses face the challenge of demonstrating that each production must be “familiar” (satisfying the expectation of audiences), whilst demonstrating “novelty” (provoking surprises to entertain audiences). Pursuing a “robust design strategy” allows the opera houses to reconcile novelty and familiarity, a tension which may apply to new product development in many other industries where organizations have to both preserve and deviate from a traditional product design, such as Volkswagen’s New Beetle.

Part IV: Cases and Contexts The fourth part of the Handbook includes chapters that consider how our understanding of innovation and project management can be developed further by investigating rich case studies and new contexts to illuminate novel processes and practices and provide many valuable insights for new lines of theoretical and empirical inquiry. •

Johnson (Chapter 19) provides an in-depth historical analysis of how systems engineering has been overlooked and often ignored, but has always been and remains one of the core capabilities developing in tandem with project management to manage large, complex technological projects. Since its origins in the weapons systems projects of the Second World War and the Cold War, systems engineering has evolved to incorporate computerbased modelling and simulation techniques now used to develop today’s complex technological innovations.

Introduction 

•

•

•

•

23

Davis and Pinto (Chapter 20) consider how the agile methodology which originated in the software industry around 20 years ago has become widely adopted by other projectbased organizations to drive innovation. In contrast to the traditional sequential waterfall approach to project management, agile offers flexibility, mutual problem-solving and customer-focused innovative solutions. Organizations must overcome significant challenges when transitioning from waterfall to agile and recognize that while agile has worked well in some industries with frequently changing requirements, it is no “silver bullet remedy” for project failure. In an interesting case study of the Italian Civil Protection Department, Cacciatori and Prencipe (Chapter 21) identify how “project capabilities” were developed to handle major public events, focusing on the celebration in Rome of the Jubilee of the Catholic Church in 2000. Social networks and artefacts formed in this vanguard project helped develop project capabilities for future events. The authors identify a promising avenue for future research exploring the micro-foundations of project capabilities. Illustrated by a programme of research on the UK construction industry, Whyte, Mosca and Zhou (Chapter 22) examine how project-based firms deploy digital information, technologies and platforms to create new sources of innovation and competitive advantage. They suggest that project capabilities are enhanced by the development of digitally enabled product platforms used to manage a large portfolio of projects and extended supply chains including manufacturers of modular components. Since the Second World War, “Big Science” projects have been major contributors to industrial innovation and economic growth. In an in-depth case study of fusion power, Dodgson and Gann (Chapter 23) show how highly ambitious large-scale science projects stimulate far-reaching innovation upstream and downstream in industries, including the development of new data and digital technologies, complex manufacturing and largescale construction capabilities.

NEW DIRECTIONS FOR RESEARCH The chapters in this book provide an important benchmark for research on innovation and project management and offer numerous ideas and suggestions about interesting empirical contexts for further study, as well as importing new theories (e.g. practice, neoinstitutional and cultural theories) and developing novel conceptual insights and methodological approaches. Despite these and some important early contributions, we are aware that research connecting and transcending the domains is still evolving so we now offer some new, exciting directions for empirical and theoretical work that might serve as a guide for future research. Artificial Intelligence and Digital Platforms The first direction research might consider is the impact of disruptive digital technological innovation on the process of managing projects. Dramatic improvements in software and data analytics afforded by artificial intelligence (AI) provide more accurate, complex and reliable information and opportunities for machine learning. As studies of firms such as Amazon, Airbnb, Uber and Netflix have shown, AI changes the way organizations gather and use data,

24  Handbook on innovation and project management

react to new information, make strategic decisions and execute interrelated operational tasks (Iansiti and Lakhani, 2020). Amazon, for example, has redesigned its entire organization, evolving from highly specialized functional units supported by disconnected IT systems, into a modular, distributed structure integrated by a common AI platform. Organizations with AI-enabled architectures deploy small, agile project teams with the data science, engineering and product development capabilities needed to integrate data across functional silos and establish new digital connections between networks of organizations working in open, distributed innovation projects. It will be interesting to discover how AI capabilities are used to design new flexible, project-based organizational architectures, integrate tasks across temporary and permanent organizational boundaries, adapt and respond in real time to unforeseen events and provide more sophisticated predictions about opportunities, risks and future conditions. Using AI and digital technologies to coordinate across boundaries in spatially dispersed projects may be particularly challenging, however, because recent research suggests that remote work during the COVID-19 pandemic has not produced the improvements in collaboration that many expected (Yang et al., 2021). Complex Innovation Ecologies and Ecosystems The second direction research might consider is how projects form part of an ecology of knowledge, capabilities and resources dispersed across many entities (Grabher, 2001; von Pechman et  al., 2015) and ecosystems of distinct, but interrelated organizations (Adner and Kapoor, 2010; Jacobides et  al., 2018) involved in the coordination of complex technological systems (Tuertscher et al., 2014) and inter-organizational projects (Malherbe, 2022). Dougherty (2011, 2016, 2017), for example, suggests that the ecology of a complex innovation system encompasses the entire public and private organizations and agencies with the knowledge capabilities to support multiple innovation projects (Dougherty, 2011). The ecology is orchestrated to discover emerging innovations by generating new products and services, integrating knowledge, strategically framing innovation for the long term and enabling appropriate forms of governance. Projects play a central role in this ecology-wide innovation process. Project innovators search, select and combine elements of emerging solutions, and project work “is very hands-on, concrete, embodied, iterative, and multi-functional, but occurs in large networks because emergent knowledge is noisy, fragmented and far flung” (Dougherty, 2016, 14). For example, the development of the Oxford AstraZeneca (Gilbert and Green, 2021) and Pfizer BioNTech (Boural, 2021) vaccines for COVID-19 at an unprecedently rapid pace demonstrated that multifaceted uncertainties can be overcome when project teams, connecting people working in many different countries, organizations and agencies, persist with innovation work as problems evolve. Tackling Grand Challenges The third broad direction for research is how innovative projects will be organized to tackle the grand challenges facing societies in the 21st century, such as climate change, biodiversity loss, future global pandemics and societal inequality. Complex, highly uncertain and often global in scale, grand challenges are sometimes defined as “wicked problems” because they are difficult to define and resistant to simple solutions (Rittel and Webber, 1973) and “evaluative” because actors have different views about what the problem is and how it can

Introduction 

25

be solved, and new concerns arise as problems are being tackled (Ferraro et al., 2015). When conditions are volatile and the future is so unpredictable, organizations are equipped to deal with grand challenges when they develop a variety of innovative responses to multiple scenarios (Augustine et  al., 2019). Private, public, not-for-profit and hybrid organizations, for example, are developing solutions ranging from incremental (e.g. renewable energy) to radical innovations (e.g. small modular reactors) for climate change adaptation and mitigation (Howard-Grenville et  al., 2014). Developing multiple, radical technological solutions (e.g. geoengineering) on a global scale may provide a more robust understanding of the distant future, including opportunities to envision breakthrough innovations and imagine disruptive alternatives to the status quo (Augustine et al., 2019), but delay immediate action and localized near-term solutions using proven, well-established technologies (Wright et  al., 2013). Resistant to “easy fixes” provided by a single organization, grand challenges require a collective, multi-actor process of “distributed experimentation” (Ferraro et al., 2015) and ongoing coordinated and collaborative efforts (Howard-Grenville et al., 2014). Research is clearly needed to understand the extent to which grand challenges will precipitate novel forms of project organizing and new types of projects networks, including how multiple organizations will work together in large, inter-organizational innovation projects and engage in the participatory approaches needed to solve the urgent, intractable problems facing societies. In addition to research on innovation ecologies and ecosystems, we think two promising theoretical frameworks – innovation mission policies and multi-level transitions – may help scholars understand how innovative projects might be organized to tackle grand challenges. Missions and Moonshots Research might consider the role played by large-scale projects in achieving mission-oriented innovation policies, such as tackling climate change (Kattel and Mazzucato, 2018; Mazzucato, 2021). Inspired by NASA’s Apollo programme in the 1960s, a mission is a “moonshot” innovation policy to imagine a desirable future, set an ambitious target and galvanize the innovation across public and private sectors required to achieve it (Mazzucato, 2021), such as the European Green Deal. Defined and led by government, a mission steers and coordinates cross-sectoral private investment, experimentation and risk-taking innovation. Despite the analogy with the Apollo programme, however, this policy research provides surprisingly little guidance on how projects can be designed and coordinated to achieve a societal mission. More recent research has attempted to readdress this gap by showing how megaprojects can be an important policy instrument geared towards shaping the market for a green energy transition in South Africa (Andreoni et al., 2022). Several leading scholars claim, however, that the Manhattan and Apollo projects offer inappropriate models for guiding innovation policy because the challenges of combating climate change are quite different and even more daunting than the wartime development of the atomic bomb or moon landing (Mowery et al., 2010) and because of a fundamental lack of agreement on what should be done (and what sacrifices might be expected from whom). America’s Manhattan and Apollo projects were funded and centrally managed by government to produce “big-push” technological solutions for a sole, nationally based customer, in a “closed system” with little or no interference from external stakeholders (Sayles and Chandler, 1971; Edwards, 1996). Developing climate-change solutions to tackle the open, emergent and pervasive extent

26  Handbook on innovation and project management

of global warming, by contrast, will require “multiple moonshots” that are decentralized and systemic in nature to reflect the complexity of the challenge (Mowery et al., 2010). Whereas the Manhattan and Apollo projects did not require broad market adoption, climate change innovations will require extensive, often disruptive changes in consumer behaviour and incentives to induce widespread adoption (Hargadon, 2010). Future research might consider how large portfolios of projects are coordinated to achieve societal missions by generating and implementing multiple solutions ranging from audacious supply-side breakthroughs to incremental, locally adapted innovations that serve the needs of a great variety of users. Transitioning to a Sustainable Future Future research might also explore how innovative projects initiate, enable and implement transitions to a sustainable future, such as shifting from a reliance on fossil fuels to renewable energy (Geels, 2010). Drawing inspiration from evolutionary theories of innovation (e.g. Nelson and Winter, 1982; Utterback, 1994) and other perspectives, scholars have developed a multi-level perspective (MLP) comprising niche, regime and landscape levels (Kemp et al., 1998; Geels, 2004, 2010; Geels and Schot, 2007). At the micro level, technological “niches” induce change from the bottom up by introducing radical but initially unstable and low-performing innovations, often developed by outsiders or peripheral actors. At the meso level, the socio-technical “regime” encompasses the actors, organizational networks and institutions surrounding an established technology. Shared, stable and aligned sets of rules, routines and regulations direct the behaviour of actors and innovative activities are locked in a trajectory of incremental improvements (e.g. increasing the fuel efficiency of cars). Radical alternatives to established regimes are nurtured and developed in protected niches that shield vulnerable, emerging technologies from direct market pressures, such as sheltered autonomous teams, skunk works and breakthrough projects within firms (Schot and Geels, 2008). At the macro level, changes in the “landscape” (macro political economy and cultural patterns) often occurring over decades, such as growing societal awareness and concerns about climate change, can eventually exert a “top-down” exogenous pressure to change existing regimes or promote neglected niche technologies (e.g. the world’s first offshore wind power farms introduced in Denmark in the 1990s). Transitions occur through interactions within and between levels but often commence when radical innovations emerge from sheltered niches to challenge an existing dominant design (e.g. the first electric vehicles) and lead to a far-reaching transformation of the prevailing socio-technical regime. A transition is brought to a close when the regime stabilizes around a new constellation of technologies, actors, rules, routines and institutions. Despite providing helpful insights on sustainability transitions, early MLP research failed to fully grasp the role of agency (i.e. what actors actually do in projects) in leading transitions (Smith et al., 2005; Genus and Cole, 2008). Actors participating in niche projects are not necessarily “locked in” by a selection environment or waiting for exogenous pressures to “unlock them”, but mindfully create and navigate pathways to an emergent future (Garud and Gehman, 2012). Future research might, therefore, benefit from understanding how transitions are activated, enabled and regenerated by “project-oriented agency” (Lenfle and Söderlund, 2022) and how projects may encompass niche and regime change. Whereas prior MLP research emphasized how sheltered niche projects incubate and initiate innovation leading to subsequent regime change, research might explore how high-visible megaprojects are designed to drive sustainability

Introduction 

27

transitions by integrating novel technologies, overcoming organizational resistance and implementing new innovation policies (or missions), such as the UK’s net-zero plans for megaprojects that will decarbonize the energy sector (Sovacool et al., 2022).

CONCLUSION The Handbook provides new perspectives and insights on research on traversing innovation and project management. With 23 chapters from leading scholars, the Handbook highlights efforts to cross-fertilize ideas from the two domains, share and create new concepts, and borrow theories from other disciplines to assist empirical research and develop a more integrated research agenda. We encourage scholars inspired by the Handbook to engage with practitioners and provide them with valuable ideas and the practical guidance needed to solve pressing real-world problems and grand challenges facing organizations and societies in the coming years, particularly in developing countries which are poorly addressed in prior literature. Our ambition has been to produce a scholarly book with practical implications that is a must-read for anyone embarking on research, practice or study of innovation and project management, and wants to understand the two domains (as they once were many years ago) as integrated in theory and practice and closely connected to other disciplines and fields.

REFERENCES Abernathy, W.J. and Rosenbloom, R.S. (1969). Parallel strategies in development projects. Management Science, 15(10), 486–505. Abernathy, W.J. and Utterback, J.M. (1978). Patterns of industrial innovation. Technology Review, 14(1), 40–47. Adner, R. and Kapoor, R. (2010). Value creation in innovation ecosystems: How the structure of technological interdependence affects firm performance in new technology generations. Strategic Management Journal, 31, 306–333. Andreoni, A., Creamer, K., Mazzucato, M., and Steyn, G. (2022). How can South Africa advance a new energy paradigm? A mission-oriented approach to megaprojects. Oxford Review of Economic Policy, 38(2), 237–259. Ansar, A. and Flyvbjerg, B. (2022). A platform approach to space exploration. Harvard Business Review. https://hbr​.org​/2022​/11​/a​-platform​-approach​-to​-space​-exploration​?autocomplete​=true Art, R.J. (1972). Why we overspend and underaccomplish. Foreign Policy 6(Spring), 95–114. Augsdorfer, P. (2005). Bootlegging and path dependency. Research Policy, 34(1), 1–11. Augustine, G., Soderstrom, S., Milner, D., and Weber, K. (2019). Constructing a distant future: Imaginaries in geoengineering. Academy of Management Journal, 62(6), 1930–1960. Bakker, R.M., DeFillippi, R.J., and Sydow, J. (2016). Temporary organizing: Promises, processes, problems. Organization Studies, 37(12), 1703–1719. Benghozi, P.J., Charue-Duboc, F., and Midler, C. (Eds.). (2000). Innovation-based competition and design systems dynamics: Lessons from French innovative firms and organizational issues for the next decade. Paris, France: Editions L’Harmattan. Ben Mahmoud-Jouini, S. and Midler, C. (2020). Unpacking the notion of prototype archetypes in the early phase of an innovation process. Creativity and Innovation Management, 29, 49–71. Bennis, W. (1966). Beyond bureaucracy: Essays on the development and evolution of human organization. San Francisco: Jossey-Bass Publishers. Berman, M. (1982). All that is solid melts into air: The experience of modernity. New York: Verso. Boehm, B. (1988). A spiral model of software development and enhancement. Computer, 21(5), 61–72. Boltanski, L. and Chiapello, E. (2005). The new spirit of capitalism. London: Verso.

28  Handbook on innovation and project management

Bourla, A. (2021). The CEO of Pfizer on developing a vaccine in record time. Harvard Business Review, May–June, 34–39. Bowen, K., Clark, K., Holloway, C., and Wheelwright, S. (1994). The perpetual enterprise machine: Seven keys to corporate renewal through successful product and process development. Oxford: Oxford University Press. Brady, T. and Davies, A. (2004). Building project capabilities: From exploratory to exploitative learning. Organization Studies, 25(9), 1601–1621. Brady, T. and Hobday, M. (2011). Projects and innovation: Innovation and projects. In P.W.G. Morris, J.K. Pinto, and J. Söderlund (Eds.), The Oxford handbook of project management (pp. 273–294). Oxford: Oxford University Press. Browning, T.R. (2017). Project design and management. In M.K. Starr and S.K. Gupta (Eds.), The Routledge companion to production and operations management (pp. 214–233). New York: Routledge. Brusoni, S. and Prencipe, A. (2001). Unpacking the black box of modularity: Technology, products, and organization. Industrial and Corporate Change, 10(1), 179–205. Burns, T. and Stalker, G.M. (1961). The management of innovation. Oxford: Oxford University Press. Chesbrough, H. (2003). Open innovation: The new imperative for creating and profiting from technology. Boston: Harvard Business School Press. Chesbrough, H., Vanhaverbeke, W., and West, J. (2014). New frontiers in open innovation. Oxford: Oxford University Press. Christensen, C. (1997). The innovator’s dilemma: When new technologies cause great firms to fail. Boston: Harvard Business School Press. Clark, K. and Fujimoto, T. (1991). Product development performance. Strategy, organization and management in the world auto industry. Boston: Harvard Business School Press. Clark, K. and Wheelwright, S. (1992). Organizing and leading heavyweight development teams. California Management Review, 34(3), 9–28. Cleland, D.I. and King, W.R. (1968). Systems analysis and project management. New York: McGraw Hill. Cooper, R.G. (1983). A process model for industrial new product development. IEEE Transactions on Engineering Management, 2(1), 2–11. Cooper, R.G. (1985). Selecting winning new product projects: Using newprod system. Journal of Product Innovation Management, EM-30(1), 34–44. Cooper, R.G., Edgett, S.J., and Kleinschmidt, E.J. (1997). Portfolio management in new product development: Lessons from the leaders – I. Research-Technology Management, 40(5), 16–28. Cooper, R.G. and Kleinschmidt, E. (1987). New products: What separates winners from losers? Journal of Product Innovation Management. 4(3), 169–184. Criscuolo, P., Salter, A., and ter Wal, A.L.J. (2014). Going underground: Bootlegging and individual innovative performance. Organization Science, 25(5), 1287–1571. Dahlander, L. and Gann, D. (2010). How open is innovation? Research Policy, 39(6), 699–709. Davies, A. (2014). Innovation and project management. In M. Dodgson, D. Gann, and N. Phillips (Eds.), The Oxford handbook of innovation management (pp. 625–647). Oxford: Oxford University Press. Davies, A. (2017). Projects: A very short introduction. Oxford: Oxford University Press. Davies, A. and Brady, T. (2000). Organisational capabilities and learning in complex product systems: Towards repeatable solutions. Research Policy, 29, 931–953. Davies, A. and Brady, T. (2016). Explicating the dynamics of project capabilities. Special issue: Festschrift for Peter Morris. International Journal of Project Management, 34, 314–327. Davies, A., Dodgson, M., and Gann, D. (2016). Dynamic capabilities for complex projects: The case of London Heathrow Terminal 5. Project Management Journal, 47(2), 26–46. Davies, A., Dodgson, M., Gann., D., and MacAulay, S. (2017). Five rules for managing large, complex projects. MIT Sloan Management Review, 59(1), 73–78. Davies, A., Gann, D., and Douglas, T. (2009). Innovation in megaprojects: Systems integration at London Heathrow Terminal 5. California Management Review, 51(2), 101–125. Davies, A. and Hobday, M. (2005). The business of projects: Managing innovation in complex products and systems. Cambridge: Cambridge University Press.

Introduction 

29

Davies, A., MacAulay, S., and Brady, T. (2019). Delivery model innovation: Insights from infrastructure projects. Special issue: Innovation in infrastructure delivery models. Project Management Journal, 50(2), 1–9. Davies, A., MacAulay, S., DeBarro, T., and Thurston, M. (2014). Making innovation happen in a megaproject: London’s Crossrail suburban railway system. Project Management Journal, 45(6), 25–37. Davies, A., Manning, S., and Söderlund, J. (2018). When neighbouring disciplines fail to learn from each other: The case of innovation and project management research. Research Policy, 47(5), 965–979. Dodgson, M., Gann, D., and Phillips, N. (Eds.). (2014). The Oxford handbook of innovation management. Oxford: Oxford University Press. Dodgson, M., Gann, D., and Salter, A. (2008). The management of technological innovation: Strategy and practice, Oxford: Oxford University Press. Dougherty, D. (2011). Organizing ecologies of complex innovation. Organization Science, 22(5), 1214–1223. Dougherty, D. (2016). Taking advantage of emergence: Proactively innovating in complex innovation systems. Oxford: Oxford University Press. Dougherty, D. (2017). Organizing for innovation in complex innovation systems. Innovation, Organization & Management, 19(1), 11–15. Edmondson, A.C. (1999). Psychological safety and learning behavior in work teams. Administrative Science Quarterly, 44(2), 350–383. Edmondson, A.C. (2012). Teaming: How organizations learn, innovate, and compete in the knowledge economy. San Francisco: Wiley. Edmondson, A.C. and Nembhard, I.M. (2009). Product development and learning in project teams: The challenges are the benefits. Journal of Product Innovation Management, 26(2), 123–138. Edwards, P. (1996). The closed world. Computers and the politics of discourse in cold war America. Cambridge, MA: The MIT Press. Eisenhardt, K.M. and Tabrizi, B.N. (1995). Accelerating adaptive processes: Product innovation in the global computer industry. Administrative Science Quarterly, 40, 84–110. Engwall, M. (2003). No project is an Island: Linking projects to history and context. Research Policy, 32, 798–808. Ferraro, F., Etzion, D., and Gehman, J. (2015). Tackling grand challenges pragmatically: Robust action revisited. Organization Studies, 36(3), 363–390. Flyvbjerg, B. (2014). What you should know about megaprojects and why: An overview. Project Management Journal, 45(2), 6–19. Flyvbjerg, B. (2017). The Oxford handbook of megaproject management. Oxford: Oxford University Press. Flyvbjerg, B., Bruzelius, N., and Rothengatter, W. (2003). Megaprojects and risk: An anatomy of ambition. Cambridge: Cambridge University Press. Freeman, C. (1974). The economics of industrial innovation. Harmondsworth: Penguin Books Ltd. Freeman, C. and Soete, L. (1997). The economics of industrial innovation (3rd ed.). London: Pinter. Gaddis, P.O. (1959). The project manager. Harvard Business Review, May–June, 89–97. Gann, D.M. and Salter, A. (2000). Innovation in project-based, service-enhanced firms: The construction of complex products and systems. Research Policy, 29, 955–972. Garud, R. and Gehman, J. (2012). Metatheoretical perspectives on sustainability journeys: Evolutionary, relational and durational. Research Policy, 41, 980–995. Geels, F.W. (2004). From sectoral systems of innovation to socio-technical systems: Insights about dynamics and change from sociology and institutional theory, Research Policy, 33, 897–920. Geels, F.W. (2010). Ontologies, socio-technical transitions (to sustainability), and the multi-level perspective, Research Policy, 39, 495–510. Geels, F.W. and Schott, J. (2007). Typology of sociotechnical transition pathways. Research Policy, 36, 399–417. Gemünden, H.G., Huemann, M., and Martinsuo, M. (2013). Editorial: A social innovation that is changing our world of thinking and acting. International Journal of Project Management, 31, 791–793.

30  Handbook on innovation and project management

Genus, A. and Coles, A. (2008). Rethinking the multi-level perspective of technological transitions. Research Policy, 37, 1436–1445. Geraldi, J. and Söderlund, J. (2018). Project studies: What is it, where is it going. International Journal of Project Management, 36(1), 55–70. Giard, V. and Midler, C. (1993). Pilotages de projets et enterprises, diversités et convergences (Project management and firms, variety and convergencies). Paris: Economica. Gil, N., Miozzo, M., and Massini, S. (2012). The innovation potential of new infrastructure development: An empirical study of Heathrow airport’s T5 project, Research Policy, 41, 452–466. Gil, N. and Tether, B. (2011). Project risk management and design flexibility: Analysing a case and conditions of complementarity. Research Policy, 40, 415–428. Gilbert, S. and Green, C. (2021). Vaxxers: Inside the story of the Oxford AstraZeneca vaccine and the race against the virus. London: Hodder & Stoughton. Gillier, T. and Lenfle, S. (2019). Experimenting in the unknown: Lessons from the Manhattan project. European Management Review, 16(2), 449–469. Grabher, G. (2001). Ecologies of creativity: The village, the group, and the heterarchic organisation of the British advertising industry. Environment and Planning A, 33, 351–374. Hargadon, A. (2010). Comment, technology policy and global warming: Why new innovation models are needed. Research Policy, 39, 1024–1026. Hargadon, A. and Sutton, R.I. (1997). Technology brokering and innovation in a product development firm, Administrative Science Quarterly, 42(4), 716–749. Hatchuel, A. and Weil, B. (2008). C-K design theory: An advanced formulation. Research in Engineering Design, 19(4), 181–192. Hobday, M. (1998). Product complexity, innovation and industrial organization. Research Policy, 26, 689–710. Hobday, M. (2000). The project-based organization: An ideal form for management of complex products and systems. Research Policy, 29, 871–893. Hoegl, M. and Gemünden, H.G. (2001). Teamwork quality and the success of innovative projects: A theoretical concept and empirical evidence. Organization Science, 12(4), 435–449. Howard-Grenville, J., Buckle, S., Hoskins, B., and George, G. (2014). Climate change and management. Academy of Management Journal, 57(3), 615–623. Huff, A.S. (2016). Project innovation: Evidence-informed, open, effectual, and subjective. Project Management Journal, 47(2), 8–25. Hughes, T.P. (1998). Rescuing prometheus. New York: Pantheon Books. Hughes, T.P. (2004). Human-built world: How to think about technology and culture. Chicago: The University of Chicago Press. Iansitit, M. and Lakhani, K.R. (2020). Competing in the age of AI: Strategy and leadership when algorithms and networks run the world. Boston, MA: Harvard Business Review Press. Imaï, K., Nonaka, I., and Takeuchi, H. (1985). Managing the new product developement process: How Japanese companies learn and unlearn. In K. Clark, R. Hayes, and C. Lorenz (Eds.), The uneasy alliance: Managing the productivity–technology dilemma (pp. 337–376). Boston: Harvard Business School Press. Jacobides, M.G., Cennamo, C., and Gawer, A. (2018). Towards a theory of ecosystems. Strategic Management Journal, 39(8), 2255–2276. Jimoh, I.F., Loch, C.H., and Sengupta, K. (2022). How megaprojects are damaging Nigeria and how to fix it: A practical guide to mastering very large government projects. London: Palgrave Macmillan. Johnson, S.B. (1997). Three approaches to big technology: Operations research, systems engineering, and project management. Technology and Culture, 38(4), 891–919. Johnson, S.B. (2002). The secret of Apollo. Systems management in American and European space programs. New Series in Nasa History. Baltimore: John Hopkins University Press. Jolivet, F. and Navarre, C. (1996). Large-scale projects, self-organizing and meta-rules: Towards new forms of management. International Journal of Project Management, 14(5), 265–271. Kahney, L. (2014). Jony Ive: The genius behind apple’s greatest products. London: Portfolio Penguin. Kanter, R.M. (1990). When elephants learn to dance: Mastering the challenges of strategy, management, and careers in the 1990s. London: Unwin Paperbacks.

Introduction 

31

Kattel, R. and Mazzucato, M. (2018). Mission-oriented innovation policy and dynamic capabilities in the public sector. Industrial and Corporate Change, 27(5), 787–801. Kellogg, K.C., Orlikowski, W.J., and Yates, J. (2006). Life in the trading zone: Structuring coordination across boundaries in postbureaucratic organizations. Organization Science, 17(1), 22–44. Kemp, R., Schot, J., and Hoogma, R. (1998). Regime shifts for sustainability through processes of niche formation: The approach of strategic Niche management. Technology Analysis and Strategic Management, 10(2), 175–195. Klein, B. and Meckling, W. (1958). Application of operations research to development decisions. Operations Research, 6, 352–363. Knight, F.H. (1921). Risk, uncertainty and profit. New York: Dover Publications. Kock, A., Heising, W., and Gemünden, H.G. (2015). How ideation portfolio management influences front-end success. Journal of Product Innovation Management, 32(4), 539–555. Lawrence, R. and Lorsch, J.W. (1967). Organization and environment. Managing differentiation and integration. Boston: Irwin. Le Masson, P., Weil, B., and Hatchuel, A. (2010). Strategic management of innovation and design. Cambridge: Cambridge University Press. Lenfle, S. (2008). Exploration and project management. International Journal of Project Management, 26(5), 469–478. Lenfle, S. (2011). The strategy of parallel approaches in projects with unforeseeable uncertainty: The Manhattan case in retrospect. International Journal of Project Management, 29(4), 359–373. Lenfle, S. (2016). Floating in space? On the strangeness of exploratory projects. Project Management Journal, 47(2), 47–61. Lenfle, S. and Loch, C. (2010). Lost roots: How project management came to emphasize control over flexibility and novelty. California Management Review, 53(1), 32–55. Lenfle, S., Midler, C., and Hällgren, M. (2019). Exploratory projects: From strangeness to theory. Project Management Journal, 50(5), 519–523. Lenfle, S. and Söderlund, J. (2022). Project-oriented agency and regeneration in socio-technical transition: Insights from the case of numerical weather prediction (1978-2-15). Research Policy, 51(3), 104455. Levitt, R.E., Scott, W.R., and Garvin, M.J. (2019). Public-private partnerships for infrastructure development: Finance, stakeholder alignment, governance. Cheltenham: Edward Elgar. Lindkvist, L., Söderlund, J., and Tell, F. (1998). Managing product development projects: On the significance of fountains and deadlines. Organization Studies, 19(6), 931–951. Loch, C.H., DeMeyer, A., and Pich, M.T. (2006). Managing the unknown: A new approach to managing high uncertainty and risk in projects. Hoboken, New Jersey: John Wiley and Sons. Loch, C.H. and Sommer, S. (2019). The tension between flexible goals and managerial control in exploratory projects. Project Management Journal, 50(5), 524–537. Loch, C.H., Terwiesch, C., and Thomke, S. (2001). Parallel and Sequential testing of design alternatives. Management Science, 47(5), 663–678. Lundin, R.A., Arvidsson, N., Brady, T., Ekstedt, E., Midler, C., and Sydow, J. (2015). Managing and Working in Project Society. Cambridge: Cambridge University Press. Lundin, R.A. and Midler, C. (Eds.). (1998). Projects as arenas for renewal and learning processes. Norwell, MA: Kluwer. Lundin, R.A. and Söderholm, A. (1995). A theory of the temporary organization. Scandinavian Journal of Management, 11(4), 437–455. Malherbe, M. (2022). Cooperating in interorganizational innovation projects: Toward a better understanding of coupling with the permanent ecosystem. International Journal of Project Management, 40, 871–885. Maniak, R. and Midler, C. (2014). Multiproject lineage management: Bridging project management and design-based innovation strategy. International Journal of Project Management, 32, 1146–1156. Maniak, R., Midler, C., Beaume, R., and von Pechmann, F., (2014). Featuring capability: How carmakers organize to deploy innovative features across products. Journal of Product Innovation Management, 31(1), 114–127. Manning, S. (2017). The rise of project network organizations: Building core teams and flexible partner pools for interorganizational projects. Research Policy, 46(8), 1399–1415.

32  Handbook on innovation and project management

Manning, S. and Sydow, J. (2011). Projects, paths and practices: Sustaining and leveraging projectbased relationships. Industrial and Corporate Change, 20(5), 1369–1402. March, J. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71–87. Maylor, H. (2005). Project management. Harlow: Prentice Hall. Mazzucato, M. (2021). Mission economy: A moonshot guide to changing capitalism. Padstow: Allen Lane. Midler, C. (1993). L’Auto qui n’existait pas: Management de projets et transformation de l’entreprise. Paris: InterEditions. Midler, C. (1995). “Projectification” of the firm: The Renault case. Scandinavian Management Journal, 11(4), 363–375. Midler, C. (2019a). Projectification: The forgotten variable in the internationalization of firms’ innovation processes. International Journal of Managing Projects in Business, 12(3), 545–564. Midler, C. (2019b). Crossing the valley of death: Managing the when, what, and how of innovative development projects. Project Management Journal, 50(4), 1–13. Midler, C., Killen, C.P., and Kock, A. (2016). Project and innovation management: Bridging contemporary trends in theory and practice, guest editorial. Project Management Journal, 47(2), 3–7. Midler, C. and Navarre, C. (2004). Project management in the automotive industry. In P.W.G. Morris and J.K. Pinto (Eds.), The Wiley guide to managing projects (pp. 1368–1388). London: John Wiley & Sons. Miller, R. and Lessard, D. (2000). The strategic management of large engineering projects: Shaping institutions, risks, and governance. Cambridge, MA: MIT Press. Mintzberg, H. (1979). The structuring of organizations. New York: Prentice Hall. Mishra, A. and Browning, T.R. (2020). Editorial: The innovation and project management department in the Journal of Operations Management. Journal of Operations Management, 66, 616–621. Morris, M., Pinto, J., and Söderlund, J. (2011). Introduction: Towards the third wave of project management. In M. Morris, J.K. Pinto, and J. Söderlund (Eds.), The Oxford handbook of project management (pp. 1–11). Oxford: Oxford University Press. Morris, P.W.G. (1994). The management of projects. London: Thomas Telford. Morris, P.W.G. (2013). Reconstructing project management. Chichester: John Wiley & Sons. Morris, P.W.G. and Hough, G.H. (1987). The anatomy of major projects. Chichester: John Wiley & Sons. Mowery, D.C., Nelson, R.R., and Martin, B.R. (2010). Technology policy and global warming: Why new policy models are needed (or why putting new wine in old bottles won’t work), Research Policy, 39, 1011–1023. Nelson, R.N. and Winter, S.G. (1982). An evolutionary theory of economic change. Cambridge, MA: The Belknap Press of Harvard University Press. Nieto-Rodriguez, A. (2021). The project economy has arrived. Harvard Business Review, November– December, 38–45. Obstfeld, D. (2012). Creative projects: A less routine approach toward getting new things done. Organization Science, 23(6), 1571–1592. O’Reilly, C.A. and Tushman, M.L. (2004). The ambidextrous organization. Harvard Business Review, 82(4), 74–81. Peck, M.J. and Scherer, F.M. (1962). The weapons acquisition process: An economic analysis. Boston: Harvard University Press. Peters, T. and Waterman, R.H. (1982). In search of excellence: Lessons from America’s best-run companies. London: Profile Books. Pich, M.T., Loch, C.H., and DeMeyer, A. (2002). On uncertainty, ambiguity and complexity in project management. Management Science, 48(8), 1008–1023. Pinto, J.K. (2010). Project management: Achieving competitive advantage. Boston: Pearson. PMI (Project Management Institute). (2021). A guide to the project management body of knowledge (PMBoK Guide) (7th ed.). Pennsylvania: PMI. Prencipe, A., Davies, A., and Hobday, M. (2003). The business of systems integration. Oxford: Oxford University Press. Prencipe, A. and Tell, F. (2001). Inter-project learning: Processes and outcomes of knowledge codification in project-based firms. Research Policy, 30, 1373–1394.

Introduction 

33

Raisch, S., Birkinshaw, J., Probst, G., and Tushman, M. (2009). Organizational ambidexterity: Balancing exploitation and exploration for sustained performance. Organization Science, 20(4), 685–695. Randolph, W.A. and Posner, B.Z. (1988). What every manager needs to know about project management. Sloan Management Review, 65, 65–73. Rich, B. and Janos, L. (1994). Skunk works. A personal memoir of my years at lockheed. Boston: Little, Brown and Company. Rittel, H.W.J. and Webber, M.M. (1973). Dilemmas in a general theory of planning. Policy Sciences, 4, 155–169. Rosenbloom, R. and Spencer, W. (1996). Engines of innovation. US industrial research at the end of an era. Boston: Harvard Business School Press. Sapolsky, H.M. (1972). The polaris system development: Bureaucratic and programmatic success in government. Cambridge, MA: Harvard University Press. Sayles, L. and Chandler, M.K. (1971). Managing large systems. New York: The Free Press. Schilling, M.A. (2020). Strategic management of innovation (6th ed.). New York: McGraw-Hill Education. Schön, D. (1963). Champions for radical innovation. Harvard Business Review, March–Apri), 77–86. Schoper, Y-G., Wald, A., Ingason, H.T., and Fridgeirsson, T.V. (2018). Projectification in Western economies: A comparative study of Germany, Norway and Iceland. International Journal of Project Management, 36, 71–82. Schot, J. and Geels, F. (2008). Strategic niche management and sustainable innovation journeys: Theory, findings, research agenda, and policy. Technology and Strategic Management, 20(5), 537–554. Scott, R.W., Levitt, R.E., and Orr, R.J. (2011). Global projects: Institutional and political challenges. Cambridge: Cambridge University Press. Scranton, P. (2015). Projects as a focus for historical analysis: Surveying the landscape. History and Technology, 30(4), 354–373. Shenhar, A.J. (2001). One Size does not fit all projects: Exploring classical contingency domains. Management Science, 47(3), 394–414. Shenhar, A.J. and Dvir, D. (2007). Reinventing project management: The diamond approach to successful growth and innovation. Boston: Harvard Business School Press. Smith, A., Stirling, A., and Berkhout, F. (2005). The governance of sustainable socio-technical transitions. Research Policy, 34, 1491–1510. Söderlund, J. (2005). Developing project competence: Empirical regularities in competitive project operations. International Journal of Innovation Management, 9(4), 451–480. Söderlund, J. (2011). Pluralism in project management: Navigating the crossroads of specialization and fragmentation. International Journal of Management Reviews, 13, 153–176. Söderlund, J. and Sydow, J. (2019). Projects and institutions: Towards understanding their mutual constitution and dynamics. International Journal of Project Management, 37, 259–268. Sosa, M., Eppinger, S., and Rowles, C. (2004). The misalignment of product architecture and organizational structure in complex product development. Management Science, 50(12), 1674–1689. Sovacool, B.K., Geels, F.W., and Iskandarova, M. (2022). Industrial clusters for deep decarbonization: Net-zero megaprojects in the UK offer promise and lessons. Science, 378(6620), 601–604. Sydow, J., Lindkvist, L., and DeFillippi, R.J. (2004). Project-based organizations, embeddedness and repositories of knowledge: Editorial. Organization Studies, 25(9), 1745–1769. Takeuchi, H. and Nonaka, I. (1986). The new new product development game. Harvard Business Review, 64, 137–146. Tee, R., Davies, A., and Whyte, J. (2018). Modular designs and integrating practices: Managing collaboration through coordination and cooperation. Research Policy, 48(1), 51–61 Teece, D. (2009). Dynamic capabilities and strategic management. Oxford: Oxford University Press. Terwiesch, C. and Loch, C.H. (1999). Measuring the effectiveness of overlapping development activities. Management Science, 45, 455–465. Tidd, J., Bessant, J., and Pavitt, K. (2001). Managing innovation: Integrating technology, market and organizational change. Chichester: John Wiley & Sons. Toffler, A. (1970). Future shock. New York: Bantam Books. Tuertscher, P., Garud, R., and Kumaraswamy, A. (2014). Justification and interlaced knowledge at ATLAS, CERN. Organization Science, 25(6), 1579–1608.

34  Handbook on innovation and project management

Turner, N., Maylor, M., and Swart, J. (2014). Ambidexterity in projects: An intellectual capital perspective. International Journal of Project Management, 33(1), 177–188. Tushman, M.L., Smith, W., Chapman-Wood, R., Westerman, G., and O’Reilly, C. (2010). Organizational designs and innovation streams. Industrial and Corporate Change, 19(5), 1331–1366. Ulrich, K.T. and Eppinger, S.D. (2012). Product design and development (5th ed.). New York: McGrawHill Irwin. Utterback, J.M. (1994). Mastering the dynamics of innovation: How companies can seize opportunities in the face of technological change. Boston: Harvard Business School Press. Von Pechmann, F., Midler, C., Maniak, R., and Charue-Duboc, F. (2015). Managing systemic and disruptive innovation: Lessons from the Renault zero emissions initiative. Industrial and Corporate Change, 24(3), 677–695. Wheelwright, S. and Clark, K. (1992). Revolutionizing product development. Quantum leaps in speed, efficiency and quality. New York: The Free Press. Whitley, R. (2006). Project-based firms: New organizational form or variations on a theme? Industrial and Corporate Change, 15(1), 77–99. Whyte, J. (2019). How digital information transforms project delivery models. Project Management Journal, 50(2), 177–194. Whyte, J. and Davies, A. (2021). Reframing systems integration: A process perspective on projects. Project Management Journal, 52(3), 237–249. Womack, J.P., Jones, D.T., and Roos, D. (1990). The machine that changed the world. New York: Macmillan Publishing Company. Woodward, J. (1965). Industrial organization: Theory and practice. Oxford: Oxford University Press. Wright, C., Nyberg, D., De Cock, C., and Whiteman, G. (2013). Future imaginings: Organizing in response to climate change. Organization, 20(5), 647–658. Yang, L., Holtz, D., Jaffe, S., Suri, S., Sinah, S., Weston, J., Joyce, C., Shah, N., Sherman, K., Hecht, B., and Teevan, J. (2021). The effects of remote work on collaboration among information workers. Nature Human Behaviour, 6(1), 43–54.

PART I CONVERGING AND INTEGRATING

2. Bridging project studies and innovation studies: a meta-theoretical approach and research agenda Joana Geraldi and Jonas Söderlund

INTRODUCTION Innovation studies and project studies have much to share, and in the last few years, these two disciplines have constructed fruitful cross-disciplinary bridges (Zahra and Newey, 2009) that have become a domain of knowledge and research in itself. This is most evident in various studies of so-called innovation projects (Davies et al., 2018), specifically those addressing the nature and process of projects that deliver new products and services (Shenhar and Dvir, 2007). This is no small feat, as cross-fertilization between domains is a well-known challenge (Knudsen, 2003; Raasch et  al., 2013). Indeed, the very assumptions supporting cross- and interdisciplinary work have been severely questioned (Brewer, 1999; Jacobs and Frickel, 2009) and voices have been raised that specialization might be favourable over attempts to cross the fences. Yet, despite the identified challenges and critique, there is an overall agreement that cross-fertilization is highly needed, especially as contemporary societal challenges, such as climate change, peace and development, biodiversity and social inequality, are genuinely multi-faceted and require collaboration among and across several specialized disciplines and domains of knowledge (e.g. Garud and Gehman, 2012). Thus, considering these modern-day and pressing challenges, the question becomes not of whether but of how to establish fruitful bridges across specialized fields of knowledge. Davies, Manning and Söderlund (2018) argue that meta-theories, such as learning and practice theories, represent noteworthy approaches to promote cross-fertilization across fields in general and to develop the fields of innovation and project studies, in particular. Such metatheories, they argue, may foster providential cross-fertilizations because they offer a “generic language that is applicable across empirical domains” (2018, 972) while also encouraging “scholars to question established assumptions and adapt theorizing to changing empirical realities, rather than adhere to narrow ideologies” (2018, 974). Meta-theories also avoid incommensurability and may foster genuine dialogue between academic fields. Accordingly, exploring common theoretical foundations could offer a more comprehensive framework to facilitate the search for appropriate and fruitful meta-theories for cross-fertilization. In Geraldi and Söderlund (2018), we suggested such a framework targeting project studies. Our framework was aimed at generating novel research ideas and questions spanning multiple levels of inquiry while capturing the value of different perspectives and theoretical foundations. The framework was based on the juxtaposition of Habermas’ (1972) three knowledge-constitutive interests and three levels of analysis: micro (individual), meso (project) and macro (organizations/firms and society). In this chapter, we build on this framework 36

Bridging project studies and innovation studies  37

and integrate it with the work of Davies et al. (2018) to suggest a meta-theoretical framework and research agenda extending the bridge between innovation studies and project studies.

OUR APPROACH We explore the bridge between the fields of innovation studies and project studies through an inclusive framework and research agenda. In the next paragraphs, we explore each aspect of our approach. The fields of project studies and innovation studies. Project studies is an academic field interested in the management of projects, the nature of project-based organizing and projectbased work. It is a relatively clearly defined scholarly community of researchers and educators with an interest in practical and theoretical issues in and around projects. Project studies is concerned with projects as a different form of organizing that starts with an institutionalized death sentence (Lundin and Söderholm, 1995). As such, research explores why projects exist, how they behave and what impact they have on individuals, teams, organizations and society (Söderlund, 2004). In the last decades, the field has moved from projects as the primary level of analysis to a wider context, opening up alternative levels of analysis within and beyond organizations. The field has also diversified from technocratic forms of knowledge often hosted by engineering schools to more sociologically informed inquiries, embracing alternative ontologies and epistemologies. The field’s core journals – International Journal of Project Management, Project Management Journal and International Journal of Managing Projects in Business – focus predominantly on the micro and meso levels of projects, with most papers addressing managerial, governance and organizational practices in and around projects. Likewise, we refer to the academic community studying innovation in its broader sense as the field of innovation studies (Dodgson et al., 2014). The field of innovation studies is concerned with understanding the development and dissemination of newness and improvement. From the Schumpeterian perspective, this may include the development of new products, new processes and new organizational procedures (Fagerberg et  al., 2005, 4). More recent accounts have called for a stronger focus on the aspects, levels and types of management to increase our general understanding of innovation as a process and outcome (Dodgson et al., 2014). Innovation studies have underlined the importance of the management and organization of technology and innovation as an important realm of its domain of knowledge. This has included studies of capabilities, resources and systems for generating innovation (Dodgson et  al., 2014). The field’s core journals (with the highest AJG ranking) – Research Policy and Journal of Product Innovation Management – explicitly focus on the macro and meso levels of innovation, with most papers addressing policy, systems, transition and the diffusion of innovation. Both project studies and innovation studies have experienced rapid growth in the number of scholars and publications (Davies et  al., 2018; Fagerberg and Verspagen, 2009). Several research units (centres, institutes, departments, etc.) focusing on innovation have been established over the past two decades. Similar developments are observed within project studies although perhaps not with the same magnitude. The development of project studies and innovation studies as separate scientific fields is part of a broader trend towards phenomenafocused research and an increasing specialization and diversification of knowledge, which could potentially blur traditional knowledge boundaries and lead to new challenges (Fagerberg and Verspagen, 2009).

38  Handbook on innovation and project management

The bridge. Innovation studies and project studies have much in common. Davies et  al. (2018) point out the fields’ common history within the management of novelty and uncertainty and the study of large-scale defence projects in the 1940s and 1950s (Morris, 1994). Both fields are still interested in the study of highly innovative projects (Davies et al., 2018, 966), but there are also several other connections when considering innovation in, around and through projects, most notably: • •

•

Innovation in the management of projects, such as the development of new project management approaches and technologies based on algorithms (Stingl and Geraldi, 2021). Innovation around projects, including project capabilities in project-based organizations, project governance by project owners and the development of collaborative ecosystems for projects (Davies and Brady, 2000; Grabher, 2004; Söderlund, 2005; Söderlund and Tell, 2009). Innovation through projects, that is, the products and services generated by highly innovative projects, often referred to as breakthrough projects (Wheelwright and Clark, 1992), exploration projects (Lenfle, 2008) or vanguard projects (Frederiksen and Davies, 2008).

The intersections proposed here are not meant to be restrictive. A bridge between knowledge areas is alive and continuously under construction (Locatelli et  al., 2023). It is not us but scholars addressing innovative projects and innovation in projects who will construct and reconstruct this bridge through their research. Inclusive approach. To begin with and in the very pursuit of cross-fertilization, we promote an integrative understanding of both project studies and innovation studies. We contend that current views of cross-fertilizations across these two fields have largely been restricted to a few exceptions. However, such restricted views might overshadow other opportunities for fruitful cross-fertilization. Therefore, we propose an inclusive and integrative research agenda for the study of innovation in, on, around and through projects, under the general heading of “innovation in projects and projects in innovation” (Brady and Söderlund, 2008). This inclusive approach may foster a productive dialogue between innovation studies and project studies that extends the different theoretical foundations present in both domains. However, such extensions should avoid the incommensurability and the challenges of “encapsulation” (Davies et al., 2018). Therefore, we build on Habermas’ theory of knowledge-constitutive interests as a reflexive meta-theoretical lens to foster new bridges at the intersection between innovation and project studies within each of the three ways of knowing as well as an understanding of what is valued in research. According to Habermas, human interests guide the structures of work and authority and influence how people think, enquire and create knowledge of the world. In that respect, knowledge is never neutral but is rather a reflection of interests. Habermas presents three knowledge-constitutive interests rooted in human existence as a social and biological species. In the following, we summarize these interests and highlight how they are visible in research on innovation and projects. Technical (type 1) refers to the desire to control one’s environment and the attempt to solve problems. This interest refers to the anthropologically deep-seated interest to control and predict the environment, which frequently motivates positivistic research and the study of

Bridging project studies and innovation studies  39

law-like regularities to uncover the “truth” and verified facts. Accordantly, this knowledgeconstitutive interest tends to view science as predominantly instrumental and objective. In project studies, empirical work is usually quantitative, based on surveys, controlled observations and laboratory studies, some of them crossing industrial sectors and different types of projects. The objective is to identify commonalities between projects that increase project success (or other performance variables). Understanding (type 2) attempts to interpret the world around us and understand oneself and others. The interpretive or cultural-hermeneutic sciences are, to a great extent, driven by the practical interest of maintaining or increasing oneself and achieving a mutual understanding in life. It is frequently embedded in the pragmatic human need to communicate with others and develop an intersubjective understanding of their contexts and relationships. “Truth” here is, to a greater extent, conceptualized as consensus and is largely coherence-oriented: something is considered true if multiple people consider it to be true. Empirical work tends to be qualitative, for example, single or multiple case studies, ethnography and often building on grounded theory or abductive approaches. Core objectives are to compare different contexts, practices or project types and understand and explain the differences while also respecting them as different. Emancipatory (type 3) intends to rectify that which is seen to be unjust and to challenge and change the status quo. This interest is aimed at the realization of autonomy from defective actions and utterances arising from social relations of power, domination and alienation, and hence, with a core interest in the desire to overcome dogmatism, compulsion and domination. Therefore, Habermas suggests a third human interest centring on self-reflection and reasoning. However, Habermas’ emancipation is not about critical reflection for its own sake. His emphasis is on the potential for transformation through human reasoning rooted in language and discourse analysis. The role of the researcher is markedly different. Here, the researcher becomes more of a political actor, be it through the choice of research topics or his or her direct intervention in the researched context. Empirical work is more diverse, with a bias towards qualitative work. Engaged scholarship and action research are common among type 3 scholars, yet these methods are by no means only used in emancipatory research. Due to their critical stance, publications within type 3 research are typically essay-like rather than classic academic papers. We explore these three knowledge-constitutive interests across three levels of analysis to exemplify and concretize our arguments. At the micro level, research is concerned with individuals and teams working on projects. In this case, this relates to innovative behaviour in projects and how individuals create innovative ideas. The meso level addresses challenges related to the project, in particular, project management processes, practices and modes of organizing. This also relates to various interpersonal dialogues and team-level issues that drive innovation. Finally, the macro level addresses challenges at the societal and corporate levels. This relates to research into technological transition and the nature of the diffusion of innovation in project-based industries. By juxtaposing the different levels of analysis with the three knowledge-constitutive interests, we identify a broad spectrum of research opportunities within the domain of innovation and project studies. Table 2.1 gives a flavour of different potential research topics. While we aim to be inclusive, we do not offer a complete research agenda. Instead, our emphasis is primarily on the development of novel and interesting research ideas over a claim of systematic coverage of past research or avenues for future research.

40

Research aimed at identifying and predicting successful projects, critical success factors in innovation projects and best practices of successful innovation projects. Research aimed at identifying and predicting who would be successful in innovation and how they would lead projects successfully.

Meso level: Projects as the focal level of analysis

Micro level: Individuals as the focal level of analysis

Level of Macro level: Society/industry/(inter-)firm Research aimed at analysis as the focal level of analysis identifying and predicting what makes innovations successful through projects in society and firms.

Type 1: Predict and control – searching for commonalities across individuals, projects and industries that increase performance

Research aimed at problematizing how collectives are developed to organize for innovation, how certain perspectives are blocked, how certain values are marginalized and how certain groups possess the power to influence, for instance, gender studies and minority studies. Research aimed at problematizing the role of the leader in innovation, questioning the role of individual workers in innovation. Research aimed at understanding the role and work of champions, inner motivation, experience and learning.

Research aimed at problematizing top management support and government involvement in innovation projects.

Type 3: Critique and reconstruct – problematizing the commonalities and differences within individuals, projects and industries

Research aimed at understanding the processes and challenges facing innovation projects, addressing the evolution of these projects.

Research aimed at understanding the interaction between top management and project management in innovation projects.

Type 2: Understand – explaining the differences between individuals, projects and industries

Knowledge-constitutive interests

Table 2.1  Overview of the three streams of work and potential avenues for future research

Bridging project studies and innovation studies  41

MICRO LEVEL At the micro level, research takes the individual and the small group as the focal point of analysis; that is, it explores individual- and team-level properties and the practices and doings of the individuals engaged in innovation projects. Work on project teams is also clustered here if they take the individual’s vantage point and investigate the actions and interactions among individuals. Such research includes investigations into individual learning, competencies and skills, agency, personality, engagement, motivation, individual emotions and decision-making, career development within and across projects, organizational and national borders, as well as team interaction and team cognition. It also encompasses studies of communication patterns among participants in innovative projects (e.g. Katz and Allen, 1985). Project studies offer a wealth of research at the micro level across knowledge-constitutive interests, from quantitative studies exploring the skills and competencies of project managers (e.g. Crawford et al., 2006b; Müller et al., 2012; Pinto and Patanakul, 2015) and project workers (Borg and Söderlund, 2015) to critical studies of the individual implications of the projectified society (Jensen et al., 2016; Packendorff and Lindgren, 2014). This parallels the developments of “the project manager” as a profession, from the early portrayal of its struggles (Gaddis, 1959; Pinto and Kharbanda, 1995) to the increased professionalization and everlarger numbers of members of professional associations in project management (Crawford et al., 2006a; Hodgson, 2004). Such a development called for a stronger focus on what makes a “good project manager” and what the implications for choosing project management as a career path are, both within (Bredin and Söderlund, 2013; Engwall and Jerbrant, 2003; Konstantinou, 2015) and across organizations (Berglund et al., 2020; Manning and Sydow, 2011). More recently, researchers have turned their attention to the roles and characteristics of the project manager to dynamic interactions within projects. This stream of research includes balanced project leadership (Drouin et al., 2021; Lloyd-Walker and Walker, 2011; Sergeeva and Kortantamer, 2021), boundary work (Stjerne and Svejenova, 2016), as well as studies on individual emotions and sensemaking in project teamwork (Lindgren et al., 2014; Musca et al., 2014). While the micro level is perhaps not as central to the innovation studies community, it is relevant and has received attention from some innovation scholars. Notably, Ralph Katz and Thomas J. Allen played key roles in driving research on the individual in innovation, how teams interact to identify and process relevant information, and how people communicate to facilitate innovative behaviour and processes. One of the most important contributions within this area is probably Katz’s collected readings on “The Human Side of Managing Technological Innovation”, which features several seminal contributions on the micro-level factors of innovation (Katz, 1997). Moreover, the variety of individual roles and personal interactions is discussed, for example, when exploring the inventor/innovator (Dodgson, 2011; Gorman and Carlson, 1990; Israel and Rosenberg, 1991). Other studies have moved beyond the simple recognition that innovation is an act of brilliance by the lonely inventor or organization into how innovation happens in interactions, such as brokering (Hargadon, 2014), social networks (Kastelle and Steen, 2014) or conflicts. For example, Tushman and Katz (1980) opened a line of inquiry into the role of gatekeepers, who act as intermediaries of knowledge and information sources. Along these lines, Hargadon (2003) demonstrated that innovation is an act of recombination of ideas, people and technologies. He highlighted the importance of “technology brokering” and the networked and social nature of innovation at the micro level.

42  Handbook on innovation and project management

Subsequent works have addressed how recombinations occur at multiple levels, underlining the importance of a multilevel analysis of innovation, which embeds the role of the individual into their contexts – in particular, organizational and institutional contexts. An example is the work on dynamic capabilities, a core analytical lens in innovation studies, which also explores the micro level indirectly as it studies “resources” and their capabilities (Dodgson et al., 2014). The bridge between innovation studies and project studies at the micro level is perhaps particularly relevant because it explores the role of the individual in the innovation project, thereby making it possible to shed light on the micro level of innovation and the role of individual agency in the innovation process. The focus on individuals in a project context would thereby improve our understanding of not only agency in innovation but also how individuals establish project-oriented agency and thus generate collective action in complex industries where action is dependent on the contribution of many individuals and stakeholders (Lenfle and Söderlund, 2022). The importance of agency in innovation has been addressed in several recent studies of socio-technical transition (Geels, 2020, Geels et al., 2023), which has become an influential stream of research within innovation studies. Predicting and Designing Behaviours With an interest in control and prediction, type 1 research strives to find commonalities at the micro level and attempts to use the knowledge to create more predictable positive outcomes. Typical type 1 research at the micro level explores the skills and competencies of successful project managers for innovative projects. A fruitful source of inspiration for further research in this area is organizational psychology and social psychology. This field of work predominantly pursues technical knowledge-constitutive interests (Stingl and Geraldi, 2021) and addresses a variety of questions and a solid theoretical foundation. We present two ideas that seem particularly relevant to explore further. Our first idea for research is the nature and promotion of agency. If innovation is about implementing inventions in practice, it draws on action and an understanding of what triggers action in certain situations. In many industries, projects are a vehicle through which such action and interaction come to fruition, as innovation requires collaboration among people with different expertise. Yet, as we bring this reflection to the micro level, agency becomes the engine of innovative projects (Frederiksen and Davies, 2008). Therefore, future research could explore how agency functions in innovative projects and the role that projects play in generating agency among diverse players in complex industries. It also seems relevant to compare how situations differ along these lines and how project-oriented agency varies across contexts, for instance, if certain environments and conditions promote agency more than others. Suitable meta-theories for such endeavours abound, agency theory being the most obvious starting point (Emirbayer and Mische, 1998), yet other theories within motivational psychology, commitment, involvement, and the like could also be sources of theoretical inspiration. A second line of research could draw inspiration from laboratory studies and explore, for instance, how individuals judge the time to let go of the project as opposed to fighting and getting benefits “at the end”. This research would explore the cognitive abilities and traits of individuals in identifying opportunities for innovation. Questions may include: How do people differentiate the “sunk cost fallacy” from “optimistic hope”? Such judgement calls are essential in innovation projects because, on the one hand, persistence often plays an important role in innovation (Hirschman, 1967; Kreiner, 1995; Schilling, 2018a). Yet, on the other

Bridging project studies and innovation studies  43

hand, decision makers sometimes wait too long to terminate a failing project (Ross and Staw, 1993; Winch, 2013). Inspiration for theoretical foundations for such research can be found in, for example, cognitive psychology, such as theories related to heuristics (Gigerenzer and Gaissmaier, 2011) or prospection (Baumeister et al., 2016). Understanding Emotions and Relationships Type 2 research at the micro level searches, considers and explains differences between individuals. Here, typical studies are the stories of accomplished innovators and their various roles in shaping projects and society. For example, Schilling (2018b) analyses the story of eight prominent breakthrough innovators, from Albert Einstein to Elon Musk, and explores why these “outliers” were successful serial innovators. Some studies have followed a similar path by exploring in depth the lifework and achievements of famous innovators, such as Thomas Edison (Israel and Rosenberg, 1991), Alexander Graham Bell (Gorman and Carlson, 1990) and Josiah Wedgwood (Dodgson, 2011). Such studies generally provide an interesting and in-depth view of how these innovators work, how they work with ideation and how they collaborate with other innovators and experts. Further studies in this area could find inspiration from behavioural sciences, philosophy, anthropology and sociology, particularly those drawing on ethnographic and other observational methods. Such fields are geared towards interpreting the world around us and understanding oneself and others, and they provide solid theoretical foundations for future research. In the following paragraphs, we present two ideas for future research. Our first idea centres on the role of emotions in innovative projects. Innovation processes are oftentimes marked by relatively extreme “ups and downs” and a need for persistence (Schilling, 2018b). How do project managers and other team members and decision-makers in innovative projects cope with the emotional labour associated with such innovative processes? How does this evolve over time and in different kinds of innovative projects? These research questions open a variety of more specific research opportunities exploring, for example, how individuals feel after the project has crashed and how they mobilize energy and strength to move on to other projects, that is, to create a new passage into a new project. Why are some individuals more resilient than others in coping with failed projects? What kinds of coping mechanisms do they rely on to be able to embark on new innovative projects? This avenue of research could explore innovators and project managers of innovative projects behind closed doors and tell the intricate, detailed stories of their projects intertwined with their emotional labour to better understand the inner life of innovative projects. In a way, such study would bring academic rigour to Tracy Kidder’s brilliant novel – The Soul of a New Machine (Kidder, 1981) – and make us aware of the emotional and motivational turmoil of some radical innovative projects that depart from conventional wisdom and practice. Second, open innovation has become increasingly critical for innovative projects (Igartua et  al., 2010; Lopez-Vega et  al., 2016). However, it puts individual members of the project, including but not limited to the project manager, in complex ethical and potentially problematic situations. Our second idea, therefore, centres on exploring decisions, decision rights, loyalty and ethics in open innovation (Gambardella and Panico, 2014). Drawing on the work of moral philosophy, researchers could explore how innovators and project managers define and redefine fairness through acts of reciprocity or generosity. For example, Vedel and Geraldi (2020) explored the role of the stranger, a university researcher, in drug development in a

44  Handbook on innovation and project management

large pharmaceutical firm. The case is interesting in this context, as the researcher was also an inventor, pushing his discoveries into practice through collaboration with the pharmaceutical company. However, while developing close relationships with senior managers of the pharmaceutical company, he also acted as a “stranger”, safeguarding his interests, and in particular, the potential profit from the innovation. How did the stranger actually feel about the collaboration and its many different faces? How can one define loyalty in such contexts? How does one decide what to share in open innovation processes while maintaining close relationships to facilitate productive collaborations? Surfacing the Precarity of Project-Based Work Type 3 research at the micro level espouses and criticizes the silently accepted assumptions of our current ways of working on innovative projects. As Habermas argues, the point of emancipatory research is not only to problematize and criticize but to help transform the status quo – and to offer new alternatives for a more promising future. Typical type 3 studies explore the precariat of project-based work and how innovators and project managers carry the risks of innovation as individuals, not as a society or larger corporations. Research methods are varied, yet with a bias towards qualitative studies, such as auto-ethnography, engaged scholarship and action research. Within project studies, we can highlight the work of Lindgren and Packendorff (see, for instance, Berglund et al., 2020), although their studies have addressed contexts in which highly specialized individuals collaborate in processes requiring high levels of creativity. In the following paragraphs, we propose two additional research ideas. First, research could explore the so-called dark side of innovation (Locatelli et al., 2022) to individuals. The research could go in several different directions. On the one hand, it could explore actual unethical and even illegal practices surrounding innovation processes and how individuals decide and act within those boundaries. For example, Bas van Abel launched FairPhone to inform users of the dark practices behind the supply chain of our day-to-day devices, including sourcing metals in war-ravaged regions, and provide fair alternatives. Yet, in this programme of work, he and his team faced difficult trade-offs and had to make compromises in the actual fairness of their phones. Future research could expose such dark sides of innovation projects and help individuals cope with their hard choices. Work on moral philosophy can offer a solid theoretical foundation for such an endeavour. Another suggestion could be to explore diversity in innovation projects. For example, as we glorify certain types of innovators and project managers, who are excluded? Who has the power to decide on new kinds of innovative projects and how do they use that power? What are the gender characteristics and implications of such projects? Do more feminine traits, such as collaboration, generosity and care, find space in fiercely competitive innovation projects? What are the longer-term consequences of a male-dominant form of innovation? What are the more general preconditions of diversity in such projects? How is diversity addressed, suppressed and maybe surpassed – and how does it contribute to or hinder innovation? What kind of innovation is particularly promoted and why?

MESO LEVEL At the meso level, research has the project as the focal level of analysis; that is, it explores work on projects and their management as well as how projects embed, facilitate and create

Bridging project studies and innovation studies  45

innovation. Topics include but are not restricted to why projects exist, how they behave, are organized and create value, and what is considered value and to whom (Söderlund, 2004). In many ways, studies in this area are clearly at the core of project studies and are central to innovation studies too. Accordantly, research at the meso level abounds both in innovation and project studies as well as in the existing bridge between the two. The bodies of work are too broad and diverse to provide a more nuanced picture. In project studies, research varies from the use of tools, processes, practices and routines to the understanding of how projects unfold over time from their inception to their ending. In innovation studies, the meso level has been addressed primarily as a form of organizing and as a context for innovation. This includes work on breakthrough projects, the challenges that those projects face, learning processes in and across projects, combinations of technologies within projects and various management approaches to facilitate innovation work. In the following sections, we will explore some of the current studies in each research type and propose ideas for future studies. Project studies and innovation studies deserve to be connected at the meso level. This is the bulk of the study in both areas, and the research questions and preoccupations are similar, making this connection probably easier to achieve. It is therefore no surprise that most studies on the intersection between project and innovation studies are at the meso level. However, there is room for further exploration, particularly as we delve into different knowledge-constitutive interests. Identifying Commonalities across Innovations in Projects Type 1 research searches for what is common across innovative projects and innovations in projects. It aims to identify particular effective teamwork characteristics (Hoegl and Gemünden, 2001; Malach‐Pines et al., 2009), organizing practices (e.g. Kock et al., 2020; Raz et al., 2002; Teller et al., 2012), strategies and capabilities at the team and project levels that are more likely to lead to higher performance. Despite the wealth of research in this area, we suggest two additional ideas for future studies. First, we would encourage more research on the role of innovation technology (Dodgson and Gann, 2014) in general and visual practices in particular (Comi and Whyte, 2018) in innovation projects. With a few exceptions (see e.g. Killen et al., 2020; Yakura, 2009), most of the studies in this area have focused on the firm (Comi and Whyte, 2018; Whyte et al., 2008) and portfolio levels (Geraldi and Arlt, 2015; Killen, 2013; Killen et al., 2020). However, visualizations and other innovation technologies also abound at the project level and impact projects’ innovation processes, as they enable new forms of collective and innovative work across disciplines (Dodgson et al., 2005; Dodgson and Gann, 2014). Yet, not enough research has addressed the role of these visualizations in social interactions, as well as their role in helping to understand and manage the uncertainty and complexity embedded in projects. This research seems particularly important now, in times of rapid technological development and advancements in visualization technology. Indeed, the possibilities for visualizations and other virtual innovation technologies have been developing for years (Dodgson et al., 2013), but their development and deployment were accelerated, particularly after the COVID-19 pandemic. With the pandemic, there has been a rise in online work, which has altered the nature of some visualizations. This is important as our main source of data remains discursive despite a visual turn in our projects, organizations and society (Boxenbaum et al., 2018). Materiality and multi-modality are examples of theoretical inspirations to ground such studies, which could add insights into how visualization techniques interact with physical objects

46  Handbook on innovation and project management

and how different types of visualization techniques might be needed to grasp a complex innovation situation. Our second idea for research is to explore the role of algorithms as an innovation in the actual management of projects. To date, research on algorithms in a broad sense has been confined to repetitive operations. Yet, projects could also benefit from algorithms, be it to optimize their repetitive tasks (Brady and Davies, 2004) or to help in controlling project progress and minding information from reporting (Stingl and Geraldi, 2021). A few projects are starting to use algorithms and develop capabilities in this area (Whyte, 2019). More research could explore how this innovates project management processes and with what implications. New Forms of Innovative Projects Type 2 research looks for outlier projects – special cases that show possibilities rather than probabilities for new forms of managing and organizing innovation in projects and innovative projects. This research is at the core of what Davies et  al. (2018) discussed as the bridge between innovation and project studies. Examples abound in this very handbook. We see opportunities by connecting the research with current societal trends and challenges. For example, as discussed earlier, digitalization and the role of artificial intelligence are significantly changing the nature of work and innovation, such as digitalization and our grand challenges – including ageing, climate change and diversity. The pharmaceutical industry uses algorithms abundantly to create and test the resilience of new potential compounds. Digitalization transformed the financial industry completely, as algorithms opened possibilities for new investment strategies. Innovative IT projects became central to this financial transformation. Such contexts are attractive for type 2 meso-level research due to their peculiar interaction with technology and projects. Along these same lines of digitalization and artificial intelligence, it seems important to address new forms of organizing innovative projects. Agility has become a key term in both innovation studies and project studies, and it continues to attract the interest of both scholars and practitioners. However, agility changes shape and is implemented differently in different contexts. It would be interesting to further explain how these differences emerge, what effects they have and how new forms of agility are developed in different contexts. These are two examples of innovation in (innovative) projects through new organizational approaches and novel technologies. In more general terms, it seems important to address how innovative projects embrace new technology and create options to reap the benefits of new technology. Further developments evoking the concept of dynamic capabilities could be particularly relevant in this regard. By dynamic capabilities, we mean “the strategic innovation processes used to adapt, integrate, and reconfigure a firm’s internal and external competences, resources, and routines in response to rapidly changing and volatile conditions” (Davies et al., 2016, 26). Despite existing work on dynamic capabilities within (Davies et al., 2016) and across (e.g. Brady and Davies, 2004; Cattani et al., 2011; Söderlund and Tell, 2009) projects, more can be done on exploring how dynamic capabilities evolve and develop in the course of a project and in interaction with innovative technologies that are changing working practices around the globe as economies reorganize in a post-pandemic context.

Bridging project studies and innovation studies  47

Surfacing the Hidden Dimension of an Innovative Project Type 3 research at the meso level espouses, criticizes and transforms the silently accepted assumptions about how innovation and projects are organized. Methodologies vary with a bias towards qualitative and engaged studies, such as engaged scholarship and action research. Typical studies in this area examine the dark side of innovation projects and innovation in projects. For example, van Marrewijk et al. (2016) examined how innovation in project roles led to conflicts in the Panama Canal project (van Marrewijk et al., 2016). Although the authors did not explicitly discuss innovation, it was the change in the roles between the United States and its Panama partners that culminated in myriad conflicts in the inter-organizational relationship. The authors used the case study methodology but were also involved in the project, consulting and observing the work for long periods. Such engagement provides a deep understanding of the context required for transformative research. The so-called “Making Projects Critical” network, founded by Svetlana Cicmil and Damian Hodgson, led the work on type 3 research in project studies. Much of this work and the first range of papers and ideas were published in a much-cited book published in 2006, edited by Cicmil and Hodgson (Hodgson and Cicmil, 2006). However, as with the micro level, the work is not particularly focused on innovation contexts and reflects on the precarious situation of this context and what it means for the individual. In the following paragraphs, we propose two research ideas. Both innovation studies and type 3 (emancipation) are grounded in an interest in changing the status quo. Future research can explore how type 3 research in projects is actually an innovative process. This methodological line of inquiry could explore how methods within innovation studies, such as co-creation, can be used as a methodology for emancipatory research, where one first unveils silently accepted assumptions and then explores possibilities for changes in, for example, utopian workshops. Emerging research on a distant future grounded on temporality or imaginaries can offer theoretical inspiration to guide research (Milner, 2019; Schultz and Hernes, 2020). More generally, it seems important to continue along the lines of documenting projects as political instruments. An example is exploring the processes through which they create powerful positions and how they block certain interests or positions in favour of others. It would then also be crucial to explore processes of inclusion and exclusion in innovation projects of certain stakeholder groups, interests and employees – and how projects respond to such concerns and evolve together with them.

MACRO LEVEL At the macro level, research explores the relationship between projects and their wider context – both in terms of the firms related to projects and more widely how projects interact with society. This research could also look upon even broader issues involving the relationship between some projects, project-intensive industries and the character of project society (Lundin et al., 2015). In this regard, the macro level is dedicated to projects in and for society. This line of research explores questions of strategy, governance and governmentality, project portfolios and multi-project organizations, project networks and project ecologies, and many other elements of an emerging project society (Boltanski and Chiapello, 2006).

48  Handbook on innovation and project management

A wealth of research in innovation studies is dedicated to this level of analysis, such as work on innovation systems and innovative states (e.g. Edquist et al., 2000). Research Policy, a core journal in the classic innovation field, is dedicated exactly to the interaction between innovation and its societal context and explicitly asks for research policy implications. Later work has taken a strong policy orientation with Freeman’s classic work on the economics of industrial innovation that shaped the field during the 1970s (Freeman, 1974) as a prime source of inspiration. Key works within innovation studies have addressed the factors influencing investment in R&D and innovation, the sources of innovation, and the great differences across industries and sectors concerning innovation (see, for instance, Pavitt, 1984). Some scholars have addressed technological, institutional and economic change and suggested a systematic analysis of innovation across different contexts (Rosenberg and Frischtak, 1984). They subsequently worked on the “national systems of innovation” (Lundvall, 2016) that favoured a holistic approach to the study of innovation, emphasizing the role of interactions among actors. More recent works within innovation studies have emphasized the centrality of sociotechnical transition (Geels, 2020). However, they have paid less attention to the micro-level of innovation and the study of project-oriented agency (Lenfle and Söderlund, 2022). Project studies also count, with a large body of work dedicated to the management of the institutional context of projects (Morris and Geraldi, 2011), project society (Jensen, 2012; Lundin et  al., 2015), project ecologies (Grabher, 2002; Sydow and Staber, 2002), governance of projects (Ahola et  al., 2014), multi-project management and portfolio management (Hobday, 2000; Martinsuo, 2013; Midler, 1995; Teller et al., 2012) and project strategy (Artto et al., 2008). Another line of research, mentioned earlier, focuses on the nature and capabilities of the project-based firm, addressing such aspects as project capabilities, organizational structures and learning mechanisms (Davies and Brady, 2000; Hobday, 2000; Söderlund and Tell, 2009). The macro level has also been studied explicitly at the intersection between innovation and project studies, but more work in this area is welcomed and required. Identifying Contingencies and Designing Contexts for Innovation Projects Type 1 research searches for commonalities in project and innovation contexts that are more likely to lead to higher performance. Commonalities can be in a diversity of areas, for example, governance mechanisms and organizational practices, such as forms of organizing portfolios (inter-organizational) and contractual agreements. The research is mostly quantitative; yet, it includes not only surveys but also archival data on, for instance, innovation records and econometrics. In project studies, the research is dedicated to multi-project firms and project portfolio management. The study is mostly done within the firm, in such areas as R&D, new product development and IT contexts (Brown and Eisenhardt, 1997; Martinsuo et al., 2014). As with the work at the meso level, the body of work here is extensive and exhaustive; therefore, developing new research ideas is challenging, particularly at the more generic level targeted by this chapter. Having said that, we propose research ideas based on new developments within society that open space for new forms and new contexts for research. We suggest studies based on archival data and social media data. The field of innovation has a strong tradition of such methodologies, but this is not the case in project studies (with a few exceptions, such as Lenfle and Loch, 2010). With the increasing use of platforms for innovative endeavours, some innovative project practices moved online and were partly transformed

Bridging project studies and innovation studies  49

by the myriad of other opportunities emerging from online formats. Researchers can make use of the digital traces left from such an online format (opening difficult questions related to GDPR – General Data Protection Regulation – and research ethics). The quantitative aspects of archival data can be used to explore commonalities between different platforms or sectors. Advanced data mining tools also open incredible opportunities for data analysis and research, which, to our knowledge, are still to be explored at the intersection between projects and innovation studies. Understanding the Role of Societal Innovation in Projects Type 2 research at the macro level pertains to and explains the differences between project ecosystems and contexts. Examples of research in this area are the works of Sydow and Staber (2002) and Grabher (2002), which draw on network theory and economic geography to examine the institutional embeddedness of projects. Others are those of Manning and Sydow (2011) on project networks and how project networks create consistencies across projects or that of Whyte (2019) exploring the digital revolution in megaproject ecosystems. It is not difficult to find examples of outstanding work in this area; therefore, proposing new research requires looking at new developments in our society and the emergence of interesting new phenomena to address (von Krogh et al., 2012). One such development that is making us curious is the rise of blockchain technology. It creates opportunities for new forms of organizing – like autonomous organizations that facilitate contracting between people with very limited constraints in terms of geographical location, size and even legal frameworks. This form of organizing is still alien to most of us but presents an opportunity for future studies, as it constitutes, in itself, an innovation in forms of (project) organizing. Another feature would be to look at the evolution of projects spanning industries to drive new kinds of innovation across established, mature industries. How are these actors interacting to establish a platform for collaboration, what technologies are used and why? How are the different players’ diverse institutional requirements influencing collaboration and demands on project collaboration? A particularly promising line of work in this area is exploring the role of projects in socio-technical transitions. In the innovation literature, the so-called multilevel perspective (MLP) has marked the study of socio-technical transitions (Geels, 2002, 2011). This perspective identifies various pathways in which socio-technical transitions take place, where scaling niche innovation levels and landscape development pressures in current regimes culminate in a transition into new socio-technical regimes. As mentioned earlier, projects and project-oriented agency (Lenfle and Söderlund, 2022) are vehicles that enable such transitions, both in terms of niche innovations and changes within the regime. Future research adds to emerging contributions (e.g. Sovacool and Geels, 2021; Turnheim and Geels, 2019) and explores the role of megaprojects in socio-technical transformations and the forms of integrating projects in niche developments, among several other topics. Surfacing the Political Dimension in and around Innovation Projects To espouse, critique and transform the status quo, type 3 research at the macro level draws on engaged research methodologies. In some regards, a notable example of research in this quadrant is the Brighton Group and their work on complex products and systems (see, for instance, Hobday, 2000). Their work started focusing on the firm, particularly multi-project

50  Handbook on innovation and project management

organizations, and what they require to support the development of complex and innovative systems, such as factories and infrastructure. The work then moved on to explore the megaproject ecosystems they had observed to be developing over the last decades in the United Kingdom. The group of researchers and their ramifications across the UK have been leading the research in the area while also maintaining strong connections with practice and advising the government and firms. Therefore, they offer a good example of engaged scholarship. Having said that, there is not as much research building on critical studies more firmly and developing work that is not only engaged but also more critical towards current forms of organizing (Courpasson, 2013; Van de Ven, 2007). In the following paragraphs, we propose two research ideas. First, the politics of innovative projects could be further explored. In line with the work of Clegg and colleagues (2002) on project governmentality in the construction industry, future studies could delve into the political arenas involved in the development of a context for innovative projects. They could do this by, for instance, exploring the work of UN officials building (or failing to build) conditions for democratic governments in countries struggling with autocratic regimes. Second, we encourage more work that takes alternative perspectives on project ecosystems to the firm and its intrinsic interest in making profits. As we turn our attention to (innovative) projects for society, we encourage a Hirschman’s glance into projects as something that helps a country develop beyond its current situation not because of its circumstances but because of “what a country does and of what it becomes as a result of what it does” (Hirschman, 1967, 4). In this way, “it affords hope to a country with the ‘wrong’ endowment provided only it finds the ‘right’ projects” (Hirschman, 1967, 5). Future research with this perspective and in developing countries would be refreshing and valuable, both theoretically and societally.

DISCUSSION The fields of project studies and innovation studies have been separated for many years but are now becoming increasingly intertwined (Davies et al., 2018). The bridge between these two disciplines is an important source of theorizing, with potential implications to practice on topics relating to, for example, disciplined flexibility (Sapolsky, 1972) and ambidextrous leadership (O’Reilly and Tushman, 2004). While the bridge has already led to fruitful research and collaborations, there is still much to do. In this chapter, we have identified opportunities for further research by reflecting on how three knowledge-constitutive interests play out at three key levels of analysis in and across the two fields. This exercise has three main implications for future research. First, when comparing and contrasting the fields, we noted promising opportunities for extending each field – project studies and innovation studies. One of the most promising opportunities for cross-fertilization is to make the field of project studies more concerned with the macro level. Research at the macro level has played a key role in innovation studies since the days of Joseph Schumpeter, and the work by the pioneers in innovation studies together with OECD and national governments. An example is Christopher Freeman, one of the most influential scholars in innovation studies, whose research was instrumental in governments’ collection of statistics on investments in research and development. In that regard, innovation studies were early on influenced by research within economics and political science to a

Bridging project studies and innovation studies  51

much greater extent than project studies and have continued to address macro-level concerns through research on technological transition, technological regimes and national systems of innovation. This is an area where project studies have, so far, only been marginally addressed, although several scholars have called for more studies of the project society (Jensen et al., 2016; Lundin et al., 2015) and the nature of the project economy (Flyvbjerg, 2014; Styhre, 2020). Moreover, studies at the project level, for instance, on megaprojects, have called for greater awareness of urban planning, the effects of megaprojects and their influence on economic growth (Flyvbjerg, 2014), and the creation of viable and innovative project ecologies (Grabher, 2004). That said, if innovation studies have historically been more aware of issues related to the macro and meso levels, project studies have in the past had a much stronger orientation towards the micro level. Several larger research programmes in projects have addressed issues associated with project leadership, shared and balanced leadership in projects, the role of the project leader and the life and learning of project workers– all examples of greater care and interest for the individual worker engaged in projects. That same interest could strengthen existing research in innovation studies to better understand the people in innovation, their emotions, skills, intuition, socio-material practices and interrelationships. Such work would complete studies of innovation practices (Dodgson, 2017). Moreover, innovation scholars could build on and continue to address issues such as work conditions that foster innovation, how innovation projects are developed to create new interlanguages (Lenfle and Söderlund, 2019) and how projects evolve to ensure a project-oriented agency that seems critical for innovation. How opportunities for innovation or landscape pressure are materialized and constructed at the individual and team levels would offer a better understanding of how macro factors of innovation play out at the micro level. Innovation and project studies can build on this awareness and potential extension of under-explored levels of analysis to explore the interplay between micro, meso and macro levels. In that respect, our chapter highlights the fact that different disciplines can have strengths concerning their primary level of analysis, and an awareness of the levels of analysis might spur improved cross-fertilization and mutual learning. Second, it also seems important to reflect more on which theories would better equip us to bridge these disciplines. Our chapter focused on knowledge-constitutive interests, each of which offers a variety of meta-theories. We briefly mentioned some enlightening theories throughout the chapter. We now return to some of them. Institutional theory has already played an important role in advancing both innovation studies and project studies (Granqvist and Gustafsson, 2016; Hargadon, 2014; Söderlund and Sydow, 2019). This has spurred much interest from both innovation and project scholars to, for instance, better understand how innovative projects handle institutional exceptions (Scott et  al., 2011), how they cope with institutional complexity (Pemsel and Söderlund, 2020) and how they might operate as institutional entrepreneurs (Sydow and Söderlund, 2023). Learning/knowledge theories have also had a huge impact in creating a better understanding of essential learning mechanisms and capability-building processes (Sydow et al., 2004), what problems are involved in learning across projects and why projects seem to repeat the same mistakes over and over again (Flyvbjerg et al., 2009). More recently, scholars from the two fields have called for further research in the area of imperfect projects and how they may spur breakthroughs (Rehn and Lindahl, 2012). Practice theories have also played a much more important role in informing our understanding of the dialectic between structure and agency (Bourdieu, 1990). An

52  Handbook on innovation and project management

important point with practice theories has been to link practical understanding and the explicit formulations and principles that enjoin people to perform specific actions (Schatzki, 2006). Similar ideas could be applied to our understanding of what shapes innovation and creativity in innovative projects and what problems are associated with the emergence of innovation in innovative projects. Moving on, we should continue reflecting on emerging theories that could play a significant role in bridging these two disciplines. Finally, besides the inspiration of meta-theories, there is also an opportunity for more theorizing and a long-term commitment to the development of new theories on the bridge between innovation studies and project studies. Innovation and projects are intertwined in myriad ways, and in each lies the seeds for new theorizing. Innovation in projects is theoretically challenging as innovation takes place in a transitory type of organization. How and why does innovation happen in projects? What kinds of opportunities and challenges emerge in innovation in projects? How do they differ from other kinds of learning processes? Research on innovation around projects has been the focus of some of the core academics leading this intersection, including project capabilities in project-based organizations, the study of owners and the development of a fruitful ecosystem for projects (Davies and Brady, 2000; Grabher, 2004; Söderlund, 2005; Söderlund and Tell, 2009). There are opportunities for further theorizing, particularly when exploring the financial and economic perspectives of innovation projects (Styhre, 2020). Finally, innovation through projects will have increasing relevance for society. They are needed to address grand challenges, such as climate change, an ageing population and inequality. In this regard, a problem-centric research agenda is useful to build on the strengths of cross-fertilization of knowledge to act on our contemporary wicked problems (e.g. Garud and Gehman, 2012). In this regard, we hope for passionate scholarship (Courpasson, 2013) and responsible management research (Bamberger, 2020) that more directly address issues that people care about and that influence their lives, not necessarily those that address practitioners’ concerns.

CONCLUSION This chapter has suggested an inclusive research agenda and a meta-theoretical framework for cross-fertilization across innovation studies and project studies. In particular, the chapter offers an agenda for systematic research into the nature and process of innovative projects in which both researchers from innovation studies and project studies could participate. We identified nine areas of research and suggested several openings for future research. If successful, this would make innovation scholars more aware of the agency and individual dimensions and better understand the significance and various roles of innovative projects. Concomitantly, the suggested research agenda encourages project scholars to be more aware of the macro-level concerns of projects, their impact and institutional connections. Ultimately, we hope that this framework will lead the way for both better developments of innovation studies and project studies and their mutual progress and cross-fertilization over time. More generally, this chapter advocates inter- and cross-disciplinary research. Our suggested bridge between innovation studies and project studies indicates that management and organization studies would benefit from more integration across our sub-field silos. Such integration not only encourages scholars to explore phenomena from alternative angles but also, hopefully, to ask more daring questions.

Bridging project studies and innovation studies  53

ACKNOWLEDGEMENTS This chapter is based on the authors’ prior work that draws on Habermas’ writing and develops the notion of project studies as an umbrella concept to encompass studies of project-based organizations, projects and project-based work. This work has been published in Geraldi and Söderlund (2016, 2018). The authors are grateful for comments from the editors and the reviewers.

REFERENCES Ahola, T., Ruuska, I., Artto, K., and Kujala, J. (2014). What is project governance and what are its origins? International Journal of Project Management, 32(8), 1321–1332. https://doi​.org​/10​.1016​/j​ .ijproman​.2013​.09​.005 Artto, K., Martinsuo, M., Dietrich, P., and Kujala, J. (2008). Project strategy: Strategy types and their contents in innovation projects. International Journal of Managing Projects in Business, 1(1), 49–70. https://doi​.org​/10​.1108​/17538370810846414 Bamberger, P. (2020). Response to Dennis Tourish’s “the triumph of nonsense in management studies.” Academy of Management Learning and Education, 19(2), 240–242. https://doi​.org​/10​.5465​/AMLE​ .2020​.0130 Baumeister, R.F., Vohs, K.D., and Oettingen, G. (2016). Pragmatic prospection: How and why people think about the future. Review of General Psychology, 20(1), 3–16. https://doi​.org​/10​.1037​/ gpr0000060 Berglund, K., Lindgren, M., and Packendorff, J. (2020). The worthy human being as prosuming subject: “Projectified Selves” in emancipatory project studies. Project Management Journal, 51(4), 367–377. https://doi​.org​/10​.1177​/8756972820930534 Boltanski, L., and Chiapello, E. (2006). The new spirit of capitalism. International Journal of Politics, Culture, and Society, 18(3–4), 161–188. https://doi​.org​/10​.1007​/s10767​- 006​-9006​-9. Borg, E. and J. Söderlund (2015): Liminality competence: An interpretative study of mobile project workers’ conception of liminality at work, Management Learning, 46(3), 260–279. Bourdieu, P. (1990). The logic of practice. Palo Alto: Stanford University Press. Boxenbaum, E., Jones, C., Meyer, R.E., and Svejenova, S. (2018). Towards an articulation of the material and visual turn in organization studies. Organization Studies, 39(5–6), 597–616. https://doi​.org​/10​ .1177​/0170840618772611 Brady, T., and Davies, A. (2004). Building project capabilities: From exploratory to exploitative learning. Organization Studies, 25(9), 1601–1621. https://doi​.org​/10​.1177​/0170840604048002 Brady, T., and Söderlund, J. (2008). Projects in innovation, innovation in projects selected papers from the IRNOP VIII conference. International Journal of Project Management, 26(5), 465–468. https:// doi​.org​/10​.1016​/j​.ijproman​.2008​.06​.007 Brewer, G.D. (1999). The challenges of interdisciplinarity. Political Sciences, 32(4), 327–337. Brown, S.L. and Eisenhardt, K.M. (1997). The art of continuous change: Linking complexity theory and time-paced evolution in relentlessly shifting organizations. Administrative Science Quarterly, 42(1), 1. https://doi​.org​/10​.2307​/2393807 Cattani, G., Ferriani, S., Frederiksen, L., and Täube, F. (2011). Project-based organizing and strategic management: A long-term research agenda on temporary organizational forms. In Advances in strategic management (Vol. 28, pp. xv–xxxix). https://doi​.org​/10​.1108​/S0742​-3322(2011)0000028004 Clegg, S.R., Pitsis, T.S., Rura-Polley, T., and Marosszeky, M. (2002). Governmentality matters: Designing an alliance culture of inter-organizational collaboration for managing projects. Organization Studies, 23(3), 317–337. https://doi​.org​/10​.1177​/0170840602233001 Comi, A. and Whyte, J. (2018). Future making and visual artefacts: An ethnographic study of a design project. Organization Studies, 39(8), 1055–1083. https://doi​.org​/10​.1177​/0170840617717094 Courpasson, D. (2013). On the erosion of “Passionate Scholarship.” Organization Studies, 34(9), 1243– 1249. https://doi​.org​/10​.1177​/0170840613502292

54  Handbook on innovation and project management

Crawford, L., Morris, P., Thomas, J., and Winter, M. (2006a). Practitioner development: From trained technicians to reflective practitioners. International Journal of Project Management, 24(8), 722–733. https://doi​.org​/10​.1016​/j​.ijproman​.2006​.09​.010 Crawford, L., Pollack, J., and England, D. (2006b). Uncovering the trends in project management: Journal emphases over the last 10 years. International Journal of Project Management, 24(2), 175– 184. https://doi​.org​/10​.1016​/j​.ijproman​.2005​.10​.005 Davies, A. and Brady, T. (2000). Organisational capabilities and learning in complex product systems: Towards repeatable solutions. Research Policy, 29(7–8), 931–953. https://doi​.org​/10​.1016​/S0048​ -7333(00)00113-X Davies, A., Dodgson, M., and Gann, D. (2016). Dynamic capabilities in complex projects: The case of London Heathrow Terminal 5. Project Management Journal, 47(2), 26–46. https://doi​.org​/10​.1002​/ pmj​.21574 Davies, A., Manning, S., and Söderlund, J. (2018). When neighboring disciplines fail to learn from each other: The case of innovation and project management research. Research Policy, 47(5), 965–979. https://doi​.org​/10​.1016​/j​.respol​.2018​.03​.002 Dodgson, M. (2011). Exploring new combinations in innovation and entrepreneurship: Social networks, Schumpeter, and the case of Josiah Wedgwood (1730–1795). Industrial and Corporate Change, 20(4), 1119–1151. https://doi​.org​/10​.1093​/icc​/dtr021 Dodgson, M. (2017). Innovation in firms. Oxford Review of Economic Policy, 33(1), 85–100. https://doi​ .org​/10​.1093​/oxrep​/grw034 Dodgson, M. and Gann, D. (2014). Technology and innovation. In M. Dodgson, D. Gann, and N. Phillips (Eds.), The Oxford handbook of innovation management. Oxford University Press, 375–393. Dodgson, M., Gann, D.M., and Phillips, N. (2014). Perspectives on innovation management. In M. Dodgson and D.M. Gann (Eds.), The Oxford handbook of innovation management (pp. 3–25). Oxford: Oxford Univeristy Press. Dodgson, M., Gann, D., and Phillips, N. (2013). Organizational learning and the technology of foolishness: The case of virtual worlds in IBM. Organization Science, 24(5), 1358–1376. Dodgson, M., Gann, D., and Salter, A. (2005). Think, play, do: Technology, innovation and organization. Oxford: Oxford University Press. Drouin, N., Sankaran, S., van Marrewijk, A., and Müller, R. (2021). Megaproject leaders: Reflections on personal life stories. Cheltenham: Edward Elgar Publishing. Edquist, C., Eriksson, M.-L., and Sjögren, H. (2000). Collaboration in product innovation in the East Gothia regional system of innovation. Enterprise and Innovation Management Studies, 1(1), 37–56. https://doi​.org​/10​.1080​/146324400363518 Emirbayer, M. and Mische, A. (1998). What is agency? American Journal of Sociology, 103(4), 962–1023. Engwall, M. and Jerbrant, A. (2003). The resource allocation syndrome: The prime challenge of multiproject management? International Journal of Project Management, 21(6), 403–409. https://doi​.org​/ 10​.1016​/S0263​-7863(02)00113-8 Fagerberg, J., Mowery, D.C., and Nelson, R.R. (2005). The Oxford handbook of innovation. Oxford: Oxford University Press. Fagerberg, J. and Verspagen, B. (2009). Innovation studies – the emerging structure of a new scientific field. Research Policy, 38(2), 218–233. https://doi​.org​/10​.1016​/j​.respol​.2008​.12​.006 Flyvbjerg, B. (2014). What you should know about megaprojects and why : An overview. Project Management Journal, 45(2), 6–19. https://doi​.org​/10​.1002​/pmj Flyvbjerg, B., Garbuio, M., and Lovallo, D. (2009). Delusion and deception in large infrastructure projects: Two models for explaining and preventing executive disaster. California Management Review, 51(2), 170–193. https://doi​.org​/10​.1225​/CMR423 Frederiksen, L. and Davies, A. (2008). Vanguards and ventures: Projects as vehicles for corporate entrepreneurship. International Journal of Project Management, 26(5), 487–496. https://doi​.org​/10​ .1016​/j​.ijproman​.2008​.05​.006 Freeman, C. (1974). The economics of industrial innovation. Oxfordshire: Routledge. Gaddis, B.P.O. (1959). The project manager. Harvard Business Review, May–June, 89–97. Gambardella, A. and Panico, C. (2014). On the management of open innovation. Research Policy, 43(5), 903–913. https://doi​.org​/10​.1016​/j​.respol​.2013​.12​.002

Bridging project studies and innovation studies  55

Garud, R. and Gehman, J. (2012). Metatheoretical perspectives on sustainability journeys: Evolutionary, relational and durational. Research Policy, 41(6), 980–995. https://doi​.org​/10​.1016​/j​.respol​.2011​.07​ .009 Geels, F.W. (2002). Technological transitions as evolutionary reconfiguration processes: A multi-level perspective and a case-study. Research Policy, 31(8–9), 1257–1274. https://doi​.org​/10​.1016​/S0048​ -7333(02)00062-8 Geels, F.W. (2011). The multi-level perspective on sustainability transitions: Responses to seven criticisms. Environmental Innovation and Societal Transitions, 1(1), 24–40. https://doi​.org​/10​.1016​ /j​.eist​.2011​.02​.002 Geels, F.W. (2020). Micro-foundations of the multi-level perspective on socio-technical transitions: Developing a multi-dimensional model of agency through crossovers between social constructivism, evolutionary economics and neo-institutional theory. Technological Forecasting and Social Change, 152, 119894. https://doi​.org​/10​.1016​/j​.techfore​.2019​.119894 Geraldi, J. and Arlt, M. (2015). Visuals matter: Designing and using effective visual representations to support project and portfolio decisions. Philadelphia: PMI. Geraldi, J. and Söderlund, J. (2016). Project studies and engaged scholarship: Directions towards contextualized and reflexive research on projects, International Journal of Managing Projects in Business, 9(6), 767–797. Geraldi, J. and Söderlund, J. (2018). Project studies: What it is, where it is going. International Journal of Project Management, 36(1), 55–70. https://doi​.org​/10​.1016​/j​.ijproman​.2017​.06​.004 Gigerenzer, G. and Gaissmaier, W. (2011). Heuristic decision making. Annual Review of Psychology, 62(1), 451–482. https://doi​.org​/10​.1146​/annurev​-psych​-120709​-145346 Gorman, M.E. and Carlson, W.B. (1990). Interpreting invention as a cognitive process: The case of Alexander Graham Bell, Thomas Edison, and the Telephone. Science, Technology, and Human Values, 15(2), 131–164. https://doi​.org​/10​.1177​/016224399001500201 Grabher, G. (2002). Cool projects, boring institutions: Temporary collaboration in social context. Regional Studies, 36(3), 205–214. https://doi​.org​/10​.1080​/00343400220122025 Grabher, G. (2004). Temporary architectures of learning: Knowledge governance in project ecologies. Organization Studies, 25(9), 1491–1514. https://doi​.org​/10​.1177​/0170840604047996 Granqvist, N. and Gustafsson, R. (2016). Temporal institutional work. Academy of Management Journal, 59(3), 1009–1035. Habermas, J. (1972). Knowledge and human interest. Cambridge: Polity Press. Hargadon, A. (2003). How breakthroughs happen: The surprising truth about how companies innovate. Boston: Harvard Business School Press. Hargadon, A. (2014). Brokerage and innovation. In M. Dodgson, D.M. Gann, and N. Phillips (Eds.), The Oxford handbook of innovation management (pp. 163–180). Oxford: Oxford University Press. Hirschman, A.O. (1967). Development projects observed. New York: Brookings Institution Press. Hobday, M. (2000). The project-based organisation: An ideal form for managing complex products and systems? Research Policy, 29(7–8), 871–893. https://doi​.org​/10​.1016​/S0048​-7333(00)00110-4 Hodgson, D.E. (2004). Project work: The legacy of bureaucratic control in post-bureaucratic organization. Organization, 11(1), 81–100. https://doi​.org​/10​.1177​/1350508404039659 Hodgson, D.E. and Cicmil, S. (2006). Making projects critical. London: Palgrave Macmillan. Hoegl, M. and Gemünden, H.G. (2001). Teamwork quality and the success of innovative projects: A theoretical concept and empirical evidence. Organization Science, 12(4), 435–449. https://doi​.org​/10​ .1287​/orsc​.12​.4​.435​.10635 Igartua, J.I., Garrigós, J.A., and Hervas-Oliver, J.L. (2010). How innovation management techniques support an open innovation strategy. Research-Technology Management, 53(3), 41–52. https://doi​.org​ /10​.1080​/08956308​.2010​.11657630 Israel, P. and Rosenberg, R. (1991). Patent office records as a historical source: The case of Thomas Edison. Technology and Culture, 32(4), 1094. https://doi​.org​/10​.2307​/3106163 Jacobs, J.A. and Frickel, S. (2009). Interdisciplinarity: A critical assessment. Annual Review of Sociology, 35(1), 43–65. https://doi​.org​/10​.1146​/annurev​-soc​- 070308​-115954 Jensen, A.F. (2012). The project society. Aarhus: Aarhus Universitetsforlag. Jensen, A.J., Thuesen, C., and Geraldi, J. (2016). The projectification of everything: Projects as a human condition. Project Management Journal, 47(3), 21–34.

56  Handbook on innovation and project management

Kastelle, T. and Steen, J. (2014). Brokerage and innovation. In M. Dodgson, D.M. Gann, and N. Phillips (Eds.), The Oxford handbook of innovation management (pp. 102–120). Oxford: Oxford University Press. Katz, R. (1997). The human side of managing technological innovation. Oxford: Oxford University Press. Katz, R. and Allen, T.J. (1985). Project performance and the locus of influence in the R&D matrix. Academy of Management Journal, 28(1), 67–87. https://doi​.org​/10​.2307​/256062 Kidder, T. (1981). The soul of a new machine. San Fransisco: Back Bay Books. Killen, C.P. (2013). Evaluation of project interdependency visualizations through decision scenario experimentation. International Journal of Project Management, 31(6), 804–816. https://doi​.org​/10​ .1016​/j​.ijproman​.2012​.09​.005 Killen, C.P., Geraldi, J., and Kock, A. (2020). The role of decision makers’ use of visualizations in project portfolio decision making. International Journal of Project Management, 38(5), 267–277. https://doi​.org​/10​.1016​/j​.ijproman​.2020​.04​.002 Knudsen, C. (2003). Pluralism, scientific progress, and the structure of organization theory. In H. Tsoukas and C. Knudsen (Eds.), The Oxford handbook of organization theory (pp. 262–288). Oxford University Press. Kock, A., Schulz, B., Kopmann, J., and Gemünden, H.G. (2020). Project portfolio management information systems’ positive influence on performance–the importance of process maturity. International Journal of Project Management, 38(4), 229–241. Konstantinou, E. (2015). Professionalism in project management: Redefining the role of the project practitioner. Project Management Journal, 46(2), 21–35. https://doi​.org​/10​.1002​/pmj​.21481 Kreiner, K. (1995). In search of relevance: Project management in drifting environments. Scandinavian Journal of Management, 11(4), 335–346. https://doi​.org​/10​.1016​/0956​-5221(95)00029-U Lenfle, S. (2008). Exploration and project management. International Journal of Project Management, 26(5), 469–478. https://doi​.org​/10​.1016​/j​.ijproman​.2008​.05​.017 Lenfle, S. and Loch, C. (2010). Lost roots: How project management came to emphasize control over flexibility and novelty. California Management Review, 53(1), 32–55. https://doi​.org​/10​.1525​/cmr​ .2010​.53​.1​.32 Lenfle, S. and Söderlund, J. (2019). Large-scale innovative projects as temporary trading zones: Toward an interlanguage theory. Organization Studies, 40(11), 1713–1739. https://doi​.org​/10​.1177​ /0170840618789201 Lenfle, S. and Söderlund, J. (2022). Project-oriented agency and regeneration in socio-technical transition: Insights from the case of numerical weather prediction (1978–2015). Research Policy, 51(3), 104455. https://doi​.org​/10​.1016​/j​.respol​.2021​.104455 Lindgren, M., Packendorff, J., and Sergi, V. (2014). Thrilled by the discourse, suffering through the experience: Emotions in project-based work. Human Relations, 67(11), 1383–1412. https://doi​.org​/10​ .1177​/0018726713520022 Lloyd-Walker, B. and Walker, D. (2011). Authentic leadership for 21st century project delivery. International Journal of Project Management, 29(4), 383–395. https://doi​.org​/10​.1016​/j​.ijproman​ .2011​.02​.004 Lopez-Vega, H., F. Tell and W. Vanhaverbeke (2016). Where and how to search? Search paths in open innovation. Research Policy, 45(1), 125–136. Locatelli, G., Konstantinou, E., Geraldi, J., and Sainati, T. (2022). The dark side of projects: Dimensionality, research methods and agenda. Project Managemant Journal, 53(4), 367–381. Lundin, R.A., Arvidsson, N., Brady, T., Ekstedt, E., Midler, C., and Sydow, J. (2015). Managing in Project Society. Cambridge University Press. Lundin, R. A. and Söderholm, A. (1995). A theory of the temporary organization. Scandinavian Journal of Management, 11(4), 437–455. Lundvall, B.-Å. (2016). National systems of innovation: Towards a theory of innovation and interactive learning. In Bengt-Åke Lundvall (Ed.), The learning economy and the economics of hope. London: Anthem Press. Malach‐Pines, A., Dvir, D., and Sadeh, A. (2009). Project manager‐project (PM‐P) fit and project success. International Journal of Operations and Production Management, 29(3), 268–291. https:// doi​.org​/10​.1108​/01443570910938998

Bridging project studies and innovation studies  57

Manning, S. and Sydow, J. (2011). Projects, paths, and practices: Sustaining and leveraging projectbased relationships. Industrial and Corporate Change, 20(5), 1369–1402. https://doi​.org​/10​.1093​/ icc​/dtr009 Martinsuo, M. (2013). Project portfolio management in practice and in context. International Journal of Project Management, 31(6), 794–803. https://doi​.org​/10​.1016​/j​.ijproman​.2012​.10​.013 Martinsuo, M., Korhonen, T., and Laine, T. (2014). Identifying, framing and managing uncertainties in project portfolios. International Journal of Project Management, 32(5), 732–746. https://doi​.org​/10​ .1016​/j​.ijproman​.2014​.01​.014 Midler, C. (1995). “Projectification” of the firm: The Renault case. Scandinavian Jouanl of Management, 11(4), 363–375. https://doi​.org​/10​.1016​/0956​-5221(95)00035-T Milner, D. (2019). Constructing a distant future: Imaginaries in geoengineering. Academy of Management Journal, 62(6), 1930–1960. Morris, P.W.G. (1994). The management of projects. Thomas Telford. Morris, P.W.G. and Geraldi, J. (2011). Managing the institutional context. Project Management Journal, 42(6), 20–32. https://doi​.org​/10​.1002​/pmj Müller, R., Geraldi, J., and Turner, J.R. (2012). Relationships between leadership and success in different types of project complexities. IEEE Transactions on Engineering Management, 59(1), 77–90. Musca, G.N., Mellet, C., Simoni, G., Sitri, F., and de Vogüé, S. (2014). “Drop your boat!”: The discursive co-construction of project renewal. The case of the Darwin mountaineering expedition in Patagonia. International Journal of Project Management, 32(7), 1157–1169. https://doi​.org​/10​.1016​/j​.ijproman​ .2014​.02​.006 O Reilly, C.A. and Tushman, M.L. (2004). The ambidextrous organization. Harvard Business Review, 82(4), 74–83. Packendorff, J. and Lindgren, M. (2014). Projectification and its consequences: Narrow and broad conceptualisations. South African Journal of Economic and Management Sciences, 17(1), 7–21. Pavitt, K. (1984). Sectoral patterns of technical change: Towards a taxonomy and a theory. Research Policy, 13(6), 343–373. https://doi​.org​/10​.1016​/0048​-7333(84)90018-0 Pemsel, S. and Söderlund, J. (2020). Who’s got the time? Temporary organising under temporal institutional complexity (Issue Tensions and paradoxes in temporary organizing, pp. 127–150). https://doi​.org​/10​.1108​/S0733​-558X20200000067012 Pinto, J.K. and Kharbanda, O.P. (1995). Lessons for an accidental profession. Business Horizons, 38, 41–50. https://doi​.org​/10​.1016​/0007​-6813(95)90054-3 Pinto, J.K. and Patanakul, P. (2015). When narcissism drives project champions: A review and research agenda. International Journal of Project Management, 33(5), 1180–1190. https://doi​.org​/10​.1016​/j​ .ijproman​.2015​.01​.013 Raasch, C., Lee, V., Spaeth, S., and Herstatt, C. (2013). The rise and fall of interdisciplinary research: The case of open source innovation. Research Policy, 42(5), 1138–1151. https://doi​.org​/10​.1016​/j​ .respol​.2013​.01​.010 Raz, T., Shenhar, A.J., and Dvir, D. (2002). Risk management, project success, and technological uncertainty. RandD Management, 32(2), 101–109. Rehn, A. and Lindahl, M. (2012). Muddling through in innovation – On incremental failure in developing an engine. Journal of Business Research, 65(6), 807–813. https://doi​.org​/10​.1016​/j​.jbusres​ .2010​.12​.020 Rosenberg, N. and Frischtak, C.R. (1984). Technological innovation and long waves. Cambridge Journal of Economics, 8(1), 7–24. Ross, J. and Staw, B.M. (1993). Organizational escalation and exit: Lessons from the Shoreham Nuclear Power Plant. Academy of Management Journal, 36(4), 701–732. https://doi​.org​/10​.2307​/256756 Sapolsky, H. (1972). The polaris system development. Harvard University Press. Schatzki, T.R. (2006). On organizations as they happen. Organization Studies, 27(12), 1863–1873. https://doi​.org​/10​.1177​/0170840606071942 Schilling, M.A. (2018a). Strategic management of technological innovation. McGraw Hill. Schilling, M.A. (2018b). Quirky: The remarkable story of the traits, foibles, and genius of breakthrough innovators who changed the world. Hachette. Schultz, M. and Hernes, T. (2020). Temporal interplay between strategy and identity: Punctuated, subsumed, and sustained modes. Strategic Organization, 18(1), 106–135. https://doi​.org​/10​.1177​ /1476127019843834

58  Handbook on innovation and project management

Scott, W.R., Levitt, R.E., and Orr, R.J. (2011). Global projects: Institutional and political challenges. In Global projects: Institutional and political challenges. Cambridge: Cambridge University Press. Sergeeva, N. and Kortantamer, D. (2021). Enriching the concept of authentic leadership in project-based organisations through the lens of life-stories and self-identities. International Journal of Project Management, 39(7), 815–825. https://doi​.org​/10​.1016​/j​.ijproman​.2021​.09​.001 Shenhar, A. and Dvir, D. (2007). Project management research - The challenge and opportunity. Project Management Journal, 38(2), 93–99. https://doi​.org​/10​.1109​/ EMR​.2008​.4534315 Söderlund, J. (2004). Building theories of project management: Past research, questions for the future. International Journal of Project Management, 22(3), 183–191. https://doi​.org​/10​.1016​/S0263​ -7863(03)00070-X Söderlund, J. (2005). Developing project competence: Empirical regularities in competitive project operations. International Journal of Innovation Management, 9(4), 451–480. https://doi​.org​/10​.1142​ /S1363919605001344 Söderlund, J. and Sydow, J. (2019). Projects and institutions: Towards understanding their mutual constitution and dynamics. International Journal of Project Management, 37(2), 259–268. https:// doi​.org​/10​.1016​/j​.ijproman​.2019​.01​.001 Söderlund, J. and Tell, F. (2009). The P-form organization and the dynamics of project competence: Project epochs in Asea/ABB, 1950-2000. International Journal of Project Management, 27(2), 101– 112. https://doi​.org​/10​.1016​/j​.ijproman​.2008​.10​.010 Sovacool, B.K. and Geels, F.W. (2021). Megaprojects: Examining their governance and sociotechnical transitions dynamics. Environmental Innovation and Societal Transitions, 41, 89–92. https://doi​.org​ /10​.1016​/j​.eist​.2021​.10​.002 Stingl, V. and Geraldi, J. (2021). A research agenda for studying project decision-behaviour through the lenses of simple heuristics. Technological Forecasting and Social Change, 162, 120367. https://doi​ .org​/10​.1016​/j​.techfore​.2020​.120367 Stjerne, I.S. and Svejenova, S. (2016). Connecting temporary and permanent organizing: Tensions and boundary work in sequential film projects. Organization Studies, 37(12), 1771–1792. Styhre, A. (2020). Thinly and thickly capitalized projects: Theorizing the role of the finance markets and capital supply in project management studies. Project Management Journal, 51(4), 378–388. https://doi​.org​/10​.1177​/8756972820931278 Sydow, J., Lindkvist, L., and DeFillippi, R. (2004). Project-based organizations, embeddedness and repositories of knowledge: Editorial. Organization Studies, 25(9), 1475–1489. https://doi​.org​/10​.1177​ /0170840604048162 Sydow, J. and Söderlund, J. (2023): Organizing complex projects from neo-institutional perspectives. In D. Cao, M. Brunet, and G. Winch (Eds.), Research handbook on complex project organizing (pp. 89–98). Cheltenham: Edward Elgar. Sydow, J. and Staber, U. (2002). The institutional embeddedness of project networks: The case of content production in German television. Regional Studies, 36(3), 215–227. https://doi​.org​/10​.1080​ /00343400220122034 Teller, J., Unger, B.N., Kock, A., and Gemünden, H.G. (2012). Formalization of project portfolio management: The moderating role of project portfolio complexity. International Journal of Project Management, 30(5), 596–607. https://doi​.org​/10​.1016​/j​.ijproman​.2012​.01​.020 Turnheim, B. and Geels, F.W. (2019). Incumbent actors, guided search paths, and landmark projects in infra-system transitions: Re-thinking Strategic Niche Management with a case study of French tramway diffusion (1971–2016). Research Policy, 48(6), 1412–1428. https://doi​.org​/10​.1016​/j​.respol​ .2019​.02​.002 Tushman, M.L. and Katz, R. (1980). External communication and project performance: An investigation into the role of gatekeepers. Management Science, 26(11), 1071–1085. https://doi​.org​/10​.1287​/mnsc​ .26​.11​.1071 Van de Ven, A.H. (2007). Engaged scholarship: A guide for organizational and social research. Oxford: Oxford University Press. Van Marrewijk, A., Ybema, S., Smits, K., Clegg, S., and Pitsis, T. (2016). Clash of the Titans: Temporal organizing and collaborative dynamics in the Panama Canal megaproject. Organization Studies, 37(12), 1745–1769. https://doi​.org​/10​.1177​/0170840616655489

Bridging project studies and innovation studies  59

Vedel, J.B. and Geraldi, J. (2020). A “stranger” in the making of strategy: A process perspective of project portfolio management in a pharmaceutical firm. International Journal of Project Management, 38(7), 454–463. https://doi​.org​/10​.1016​/j​.ijproman​.2020​.03​.003 Von Krogh, G., Rossi-Lamastra, C., and Haefliger, S. (2012). Phenomenon-based research in management and organisation science: When is it rigorous and does it matter? Long Range Planning, 45(4), 277–298. https://doi​.org​/10​.1016​/j​.lrp​.2012​.05​.001 Wheelwright, S.C. and Clark, K.B. (1992). Revolutionizing product development: Quantum leaps in speed, efficiency, and quality. New York: The Free Press. Whyte, J. (2019). How digital information transforms project delivery models. Project Management Journal, 50(2), 177–194. https://doi​.org​/10​.1177​/8756972818823304 Whyte, J., Ewenstein, B., Hales, M., and Tidd, J. (2008). Visualizing knowledge in project-based work. Long Range Planning, 41(1), 74–92. https://doi​.org​/10​.1016​/j​.lrp​.2007​.10​.006 Winch, G.M. (2013). Escalation in major projects: Lessons from the channel fixed link. International Journal of Project Management, 31(5), 724–734. https://doi​.org​/ http:/​/dx​.doi​.org​/10​.1016​/j​.ijproman​ .2013​.01​.012 Yakura, E.K. (2009). Charting time: Timelines as tempral boundary objects. Academy of Management Journal, 45(5), 956–970. https://doi​.org​/10​.2307​/3069324 Zahra, S.A. and Newey, L.R. (2009). Maximizing the impact of organization science: Theory-building at the intersection of disciplines and/or fields. Journal of Management Studies, 46(6), 1059–1075. https://doi​.org​/10​.1111​/j​.1467​- 6486​.2009​.00848.x

3. Corporate entrepreneurship and project management Valentine Georget and Rémi Maniak

INTRODUCTION Corporate entrepreneurship (CE) is not a new concept; it has been around since the 1960s. Though it has been abandoned since the 1980s because of the lack of professionalism in corporate venturing management, the uncertain environment in which organizations are immersed today implies the re-appearance of this concept and its institutionalization within the companies. The concept of corporate entrepreneurship seems to hold great promise. At first glance, it seems to reconcile the advantages of a large company – with its effects of scale, its R&D power, its international presence, etc. – and of entrepreneurship – with its possibilities of creativity, agility, reactivity, etc. However, one could also see it as “an old wine in a new bottle” because in many ways the process of corporate entrepreneurship is similar to that of project management (PM). In both cases, processes start from a concept or an idea and build a temporary organization capable of transforming this initial idea into a new product or a new service, potentially having an impact on the company’s strategy and organization. This apparent similarity requires a more in-depth analysis of the differences and similarities between these two schools of thought. This is what this chapter proposes to do. In the first section, we will give a brief overview of these two disciplines and the evolution of their questioning. Especially, we show that contrary to what one might think, most of the work in these two fields does not focus on the tools and processes for optimizing innovation processes, but rather on the articulation of innovation processes with the organization and structure of the firm, and with its strategy. In a second step, we study in a symmetrical and systematic way the similarities and differences between the two schools of thought, focusing on these two variables – organization and strategy. What can we learn from a reconciliation between these two fields? We will show both a strong proximity and elements of differentiation, suggesting avenues for further models of innovation management integrating these two approaches. This chapter is based on our own experience in accompanying several dozen projects over the past 20 years, and on studies and articles published on this subject, both concerning traditional projects and emerging corporate entrepreneurship projects.

TWO CONCEPTS TO MANAGE THE INNOVATION PROCESS Project Management (PM): From Dinosaur to Innovative Companies A dinosaur mythology not agile enough The collective unconscious has the idea that certain established companies may see their dominant position decline or even disappear with the entry of new actors who are supposed 60

Corporate entrepreneurship and project management  61

to be more agile and do not have to deal with bureaucratic red tape. The reality is often quite different. The most obvious case is that of Kodak, taught at universities around the world. This is a blatant example of a large company unable to reinvent itself in the face of a brutal change in the environment – the transition from film to digital photography – leaving room for new players in this market (Sony, HP, Canon, etc.), benefiting from solid assets that are key in this new market (sensors, electronics). Another example often shown is Nokia, a long-dominant actor in the cell phone market, notably following its victory over Motorola, but which had to bow to Apple’s technologies and business model. In both cases, the new entrants are not startups but established companies. If we look for startups that have currently disrupted an established market and its dominant players, there are far fewer examples. SAP, the market leader in business software, has indeed been challenged by solutions like SalesForce, but SAP is far from dead. Tesla has attacked a highly capital-intensive market – the automotive industry – with extraordinary capitalization despite rather chaotic financial results. It’s the same for aerospace, with SpaceX clearly outperforming established companies in the launch vehicle market, and for Palantir in the artificial intelligence market. Here again, these adventures are not startups; this would not have been possible without state aid or the fortune of a few billionaires. We can also note that the domination of digital monopolies such as the GAFAMs, presented as successful startups, is finally today due less to the intrinsic quality of their offers and more to their rents on markets with strong network externalities (Eisenmann et al., 2006). It should also be noted that they have the capacity to absorb innovative initiatives that could harm them (Bourreau and Perrot, 2020). Even so, the old literature on innovation has given many arguments to show how quickly dominant players can disappear to the benefit of new entrants. However, core competencies can become core rigidities since the organization structure always implies developing the same kinds of products, regardless of the evolution of the market or technological environment (Leonard-Barton, 1992). Literature focused on product architectures confirm this inertia and the structural advantage of newcomers over incumbents (Henderson and Clark, 1990), and that the current digitalization of the economy and the standardization of protocols and modules favour small actors against integrators (Fine, 1998; Jacobides et al., 2007). The literature about the ecology of population invites us to consider large firms in their dimension of inertia much more than in their agility. Relying on the dominating school of thought of the resource-based view (Penrose, 1959; Wernerfelt, 1984), even if the concept of dynamic capabilities (Eisenhardt and Martin, 2000; Teece, 2007; Teece et al., 1997) is now more than established, i.e. the ability of a firm to modify its routines to adapt to the evolution of the environment, there is very little evidence about the ability of incumbents to achieve it. In the end, it is difficult to explain the reality of the debate between startups and large established organizations with the theoretical “glasses” constructed in the 1970s–1990s, which is not surprising. It is indeed at this precise moment that the first studies on modern project management were born. The aim was to find processes and organizations capable of renewing themselves, whether in terms of products or internal routines. Project management as a vector of innovation Obviously, practices and theories have largely dealt with these weaknesses by identifying management principles and theories that allow them to be overcome.

62  Handbook on innovation and project management

As far as project management is concerned, the discipline was born in the 1950s as a way of controlling projects that came from top management or political decisions (missiles, Apollo, etc.) that required the involvement of several thousand or tens of thousands of individuals. These methods were perfected until the 1990s. At this time, in the OECD countries, medium and large companies faced new international competition and market saturation and had to switch from a demand-driven economy to a supply-driven economy. From then on, projects were no longer simply a way of controlling the complexity of a development process, but the framing of collective actions aimed at exploring new markets, new technologies or new architectures. The discipline has therefore moved closer to the discipline of innovation to integrate components related to uncertainty and serendipity (Lenfle, 2008; Lenfle and Loch, 2010). Since then, the rapprochement with innovation management has become more pronounced, incorporating more organizational and strategic variables (Andriopoulos and Lewis, 2009; Benner and Tushman, 2003; Maniak et al., 2014; O’Reilly and Tushman, 2004; Tushman and O’Reilly, 1996). This field of innovation management was itself built with strong ties to project management, without these disciplines assuming their commonalities (Davies et al., 2018). Thanks to these first studies – dating from the 1950s to 1960s – often dealing with innovation in projects (Klein and Meckling, 1958; Lawrence and Lorsch, 1967), the field has gradually structured itself around organizational variables – the relationship between firm-level and project-level (Clark and Wheelwright, 1992; Midler, 1995; Mintzberg and McHugh, 1985; Wheelwright and Clark, 1992) – and the underlying product planning strategy, especially in terms of learning dynamics (Maniak et al., 2014; Marsh and Stock, 2003, 2006; Nonaka, 1991, 1994; Nonaka et al., 1995). Theories, vocabularies and recommendations of innovation and project schools of thought are converging. This could be traced back to Klein and Meckling’s (1958) landmark paper contrasting “Mr Optimizing” (standard PM) and “Mr Sceptic” approaches to project management. Whereas Shenhar and Dvir (2007) demonstrate the fallacy of the “one size fits all” approach and Brady and Davies (2004) propose the notion of “vanguard exploratory projects”, Sommer and Loch (2004) develop a theory of project management under unforeseeable uncertainties (or unknown unknowns). Lenfle and Midler (2009) introduced the concept of “exploratory projects”, which deal with exploration, creativity and flexibility and also a strong discipline in the management of such projects (Lenfle and Midler, 2009). Nowadays, it is common to read project management articles discussing ambidexterity (Kock and Gemünden, 2019), effectuation or open-innovation (Huff, 2016) concepts. As can be seen from this summary, both disciplines have relatively converged towards the integration of project logic, innovation logic and organizational logic. Entrepreneurship has followed the same dynamic. Corporate Entrepreneurship: Innovation as a Personified Emerging Disruption Success stories that feed a mythology of superheroes For several years, entrepreneurship has been a key area for action and reflection. This is particularly corroborated by innovation indicators. Historically, the measurement of innovation was based on productivity gains, number of patents, then number of new offerings, and now on number of new startups created by a specific company or in a specific region.

Corporate entrepreneurship and project management  63

Silicon Valley has played a major role in this paradigm shift. GAFAM – to name a few – have fueled a mythology of the hero who starts with a great idea and gradually develops a “unicorn”. Jeff Bezos, Bill Gates, Mark Zuckerberg and Steve Jobs are obvious examples of creating empires from individual initiatives and then remaining at the head of the company. In the collective unconscious, this factor is decisive in the success of the company in the short and long term. To be convinced of this last point, just follow the saga between Apple and Steve Jobs. The decline of the company in the early 1990s was largely associated with the dismissal of the founder, the success at the end of the 1990s was largely associated with his return, and finally, his death in 2011 raised many questions about the ability of the company to continue to offer innovative and revolutionary products such as the iPhone or the iPad. This personification of the innovation process does not stop in Silicon Valley. For example, in China, Alibaba’s success is largely associated with its founder Jack Ma. He is considered a visionary and a quasi-guru and has been at the head of the company for a long time at each of its decisive stages. These adventures point to an extreme situation, where the idea precedes the creation of a company, where the founder is the initiator of the concept, and routines appear as the scaleup proceeds. There are also examples of innovative initiatives carried out within an existing company. These initiatives have been supported by top management in a variety of ways. There are cases where the internal initiative is not supported by top management. The most famous example is certainly that of Toshiba (Abetti, 1997). The laptop project was initiated by an internal engineering team. This team presented the project twice to the top management, with a refusal each time. The team continued to work on the project informally, with the support of their direct managers. The company finally launched the product by creating the market, in which it remained dominant for almost ten years. The example of the Twingo project at Renault is also emblematic of this bottom-up rise in power, against part of the hierarchy (Midler, 1995). Even if several internal-entrepreneurial projects could be hidden by employees or top management for many reasons, organizations understand the importance of systematizing and democratizing innovation processes. The systematization of corporate entrepreneurship has followed three waves: a wild wave and two systematized waves. Before the 1980s, companies were looking to invest in ventures within the company, like venture capitalists, but this concept was abandoned for the next 20 years because the companies simply could not muster the hardnosed discipline that VCs apply, as they cold-bloodedly stop a venture even if the entrepreneur has brilliant strategic arguments. Since the 2000s, companies have been taking a renewed interest in this concept, which allows them to innovate and renew their strategy in an increasingly uncertain environment (Sharma and Chrisman, 2007). Indeed, to face environmental changes and competitive markets, organizations need to innovate and propose innovative concepts to their customers to stay in the race or to get “back in the race”. So, they have been creating a favourable environment to innovate by internalizing the entrepreneurial process. These processes allow every employee/every “human resource” (Høyrup, 2010, 2012; Smith et al., 2012) to propose their own innovative concepts in order to bring them to the fore and retain only the most promising. After this first phase of ideation, firms need to organize and manage the project with dedicated processes. Google is the best-known example and has set up a management system where each employee can work one day a week on a personal or collective project, which he

64  Handbook on innovation and project management

or she can propose to the top management. This system has given birth to innovations such as AdSense, Gmail and Google News. Corporate entrepreneurship allows organizations to reinvent themselves (Sharma and Chrisman, 1999; Stopford and Baden-Fuller, 1994), to innovate – incrementally and disruptively (Sharma and Chrisman, 1999; Stopford and Baden-Fuller, 1994) – and to gain in productivity (Phan et al., 2009). From a theoretical point of view, entrepreneurship has progressively asserted itself as a scientific discipline with solid roots and real academic recognition. For example, if we take the 500 journals with the highest h-index scores, 22 contain the title “entrepreneurship” or “small venture”, while “innovation” appears 18 times and “project” only eight times. “Strategic entrepreneurship journal” has the same h-index as “project management journal”. If we use the SJR indicator, which is certainly better adapted to “rising” themes, “strategic entrepreneurship journal” is now ranked tenth worldwide. Within this general shift of focus towards startups, we have seen a rise in the importance of the corporate entrepreneurship (CE) theme. According to Scopus, the number of corporate entrepreneurship publications has sharply increased in recent years (273 documents were listed on Scopus in 2020, while only 139 documents in 2015). At first glance, corporate entrepreneurship is very similar to project management, in that it is an entrepreneurial-based process involving one or more individuals, conducted within an existing organization in order to “create a new organisation or instigate strategic renewal or innovation within that organization” (Antoncic and Hisrich, 2001; Basso, 2006; Christensen and Maskell, 2003; Chua et al., 1999: 18; Delić et al., 2016; Sharma and Chrisman, 2007; Zahra, 1991). Through the description of this process, most studies have been focused on an individualcentric approach (Antoncic and Hisrich, 2003; Hisrich, 1990; Martiarena, 2013; Pinchot III, 1985; Zenovia and Maier, 2011) by studying the main actor of CE process: the intrapreneur (Mohedano-Suanes and Benítez, 2018), who is literally an internal entrepreneur (Bager et al., 2010; Zenovia and Maier, 2011) and can form an entrepreneurial group within the organization capable of persuading others, altering their behaviour and influencing the creation of a new corporate venture (Stopford and Baden-Fuller, 1994, 522). In recent years, CE has become more professional and institutionalized within companies through the creation of specialized entities, such as i-Lab (Air Liquide) and Intrapreneur Studio (Orange). Thus, the purely individual conception of the works council is moving to a more collective perspective (Bierwerth et al., 2015; Chang et al., 2019). So, this field evolved (1) from strictly marginal business development to a more innovative and intrusive initiative on strategy and organization (Bosma et al., 2010) and (2) from an individual-centric to a more collective perspective (Bierwerth et al., 2015; Chang et al., 2019). To encourage CE initiatives throughout the organization, companies need to manage it and create conditions to allow it. For example, literature insists on the importance of the diffusion of a corporate culture that allows failure (Alpkan et al., 2010; Euchner, 2016; Kuratko, 2005) and of giving employees autonomy to propose their ideas (Hansen et al., 2017; Kuratko, 2005). Furthermore, we assist the emergence of some entities inside the organizations. Generally, these entities are composed of a dedicated managerial team and dedicated processes. Although these processes are specific to organizations, the CE process is generally divided into three main phases: the ideation phase, development phase and exit phase (Jung, 2018). Like entrepreneurship with venture capitalists, the transition from one phase to another depends on the company’s selection committee (Pandey and Tewary, 1979).

Corporate entrepreneurship and project management  65

On strategy, the theme of effectuation (Midler and Silberzahn, 2008; Sarasvathy, 2001) has progressively imposed itself. In this paradigm, and contrary to a fairly widespread idea, the entrepreneur should not protect his idea and wait until he has enough money or networks to launch, but rather disseminate his idea from the outset, in order to induce a social mechanism allowing him to both strengthen his assets and redirect his initial idea towards more promising avenues (Huff, 2016; Parker et al., 2021; Sarasvathy, 2001). At the organizational level, the notion of entrepreneurial orientation has been studied in the CE literature as the ability of an organization to generate innovative behaviours and as the ability to take risks or be proactive (Covin and Lumpkin, 2011; Fayolle et al., 2010; Morris et al., 2010; Slevin and Covin, 1990). CE can also act on the organization itself to enable it to become more attentive and responsive to changes in the environment (Slevin and Covin, 1990; Zahra, 1991). What about Crossing the Two Approaches? Several studies have attempted to explore the link between the disciplines and theoretical fields of CE and PM (Huff, 2016; Nguyen et al., 2018). Some works have pointed to some common genes, notably via cross-citation studies (Fonrouge et al., 2018), or a theoretical and systematic analysis of the links between these two schools of thought (Kuura et al., 2014). Also noteworthy is work on the use of effectuation logic within projects (Huff, 2016; Nguyen et al., 2018). The study by Kuura et al. (2014) provides a unique historical analysis of the emergence and then points of connection between these two disciplines. Several concepts have gone beyond the boundaries and crossed the two theoretical fields. Strategically, some concepts have also linked streams of thought, for example, the notion of the vanguard project, which describes a disruptive project that opens the way for other projects to follow the first breakthrough (Frederiksen and Davies, 2008). The current of thought initiated by Slevin and Covin (1990) has often been at the intersection, notably via the concept of “entrepreneurial orientation”, but also new product development. The point is also to give entrepreneurs project management methods. Ambidexterity can also play the role of an intermediate concept between these two currents of thought. Recent developments have integrated this concept with project management, showing that exploration and exploitation activities can be carried out and coordinated as a programme of a project portfolio with different maturity levels and perspectives (Midler et al., 2019). The issue of CE is also largely correlated to the ambidexterity issue, insofar as the spaces of freedom granted to employees by top management can vary widely, and the “bottom-up” devices put in place can either be integrated into the permanent organization (contextual ambidexterity) or sent to an ad hoc or integrating structure of other similar initiatives (structural ambidexterity). On the organizational level, some studies have shown that in the face of a traditional project management process – carried out internally, starting from a given objective – other forms of more bottom-up innovation processes can appear, such as when the company keeps control over the definition of the initial concept while leaving the constitution of a social network and a learning dynamic around the project free and non-programmatic (Svejvig and Andersen, 2015). Either the questioning emerges from a problem or an opportunity experienced by the

66  Handbook on innovation and project management

organization, and the way in which this aim can be achieved can also find its own way within the organization. This model is then defined as “subjective project management” (Huff, 2016). As we have seen, there are many points of convergence between the two disciplines. These similarities are not so much about the tools and processes used but about the issues related to the articulation of the underlying innovation processes with the underlying organizational and strategic dynamics. PM and CE: Differences, Similarities and Complementarity Reading the previous paragraphs, one might think that the similarities outweigh the differences and that these two disciplines are almost confused, each constituting “the old wine in a new bottle” for the other. In this section, we will analyse the similarities and differences between them and show their complementarity. The analysis will be systematic, successively questioning the organizational and strategic aspects of both concepts, both statically – with a focus on a single initiative, a project – and dynamically – notably via the articulation with existing or following initiatives and projects. What about Organizational Issues? Wondering about organizational issues orients the analysis towards several questions. • • •

First, what about management? Is there a project manager? How is he empowered and on which scope and time? How is the project team defined? Second, what about the design principles? Which activities must be carried out during the project, and what’s next after the project? Third, what are the linkages between the project and the permanent organization and structure, for example ranging from a contextual initiative with a barycentre within the functional departments to a project-oriented process which involves a certain degree of autonomy of the initiative regarding the traditional structure?

Management issues: is there a project manager/team onboard? Who is in charge? Authors like Burns and Stalker (1963) were certainly the first to show that – in highly changing contexts such as the electronics industry – “mechanistic” companies (those that applied the principles of bureaucracy to the letter) were outclassed by “organic” companies, which privileged processes over procedures and had a fairly unstable product range and variable team geometry. The principles of the “organic” company as described by the authors are (1) a continual redefinition of individual tasks, (2) participation of each employee beyond the limits of his or her responsibilities, (3) a complex network of control, authority and communication, (4) democratization of knowledge and (5) transversal and lateral communication modes (Burns and Stalker, 1963). The two concepts – PM and CE – obey this injunction, with different answers. Project management has developed a variety of models, particularly in relation to new product development. The different models can be positioned on a continuum between situations where the project activity takes over the activity of the business units and functional expertise and situations where the opposite occurs (Allen, 2001). The model called “heavyweight project management” corresponds more to the second situation (Clark and Fujimoto, 1991).

Corporate entrepreneurship and project management  67

In this model, the project manager is the one in charge of the convergence of the project with its initial objective. He/she is generally not the initiator of the initial concept or the functional specifications. The initial concept, process and project team are allocated to him/her a priori. Much of the work on PM has focused on ways of motivating and empowering these teams within the convergence process and pacifying the relationships between the functional units and the projects that draw resources from these units to feed them. The “heavyweight” or “tiger team” model gives primacy to the project over the business units from the very beginning when the project is being formalized. The corporate entrepreneurship approach differs greatly from this dynamic. First, the project manager – the intrapreneur (Antoncic and Hisrich, 2001; D’Amboise and Verna, 1993) – is not named but is emergent. He/she is the one who comes up with the initial idea (ideation phase), identifies with and invests personally in the project (Antoncic and Hisrich, 2001). Finally, the intrapreneur becomes almost unintentionally the leader of the project that comes from his/her inspiration (Bouchard and Fayolle, 2017). The team dynamics are also different. As in the effectual approach to entrepreneurship, the challenge at the beginning of the project is to progressively integrate relevant, competent people who are sufficiently interested in the initiative to devote time to it and to negotiate with their hierarchy on the time that will be devoted to the project and not to the functional activity (Bouchard and Fayolle, 2017). The challenge of the intrapreneur is to find time resources and competencies through his/her own network to pursue the project. In some cases, the intrapreneur can rely on a CE device, which provides methodologies, a support frame and a pre-existing network on which he/she can rely. To move from an ideation phase to a project development phase, the project must be selected by a selection committee, generally composed of top managers. From a sociological perspective, we can say that the two approaches are quite similar. Innovation dynamics within firms involve being able to explain complex social issues, and so require integrating several bodies of knowledge or disciplines (Antoncic and Hisrich, 2001; Auer Antoncic and Antoncic, 2011; Berggren et al., 2011; Kuratko, 2005). Pollack (2007, 267) points out that, in addition to the “hard paradigm” of project management based on positivist and realist philosophies which emphasize control, there is growing acceptance of a “soft paradigm” that attends to the social process, interpretivist philosophies and learning. We find here the initial definitions of the project manager and the project team. The role of the project manager is to embody the identity of the project and to have a strong influence on the general management and on the participants and allies useful for project development. In the context of PM, the project team is formed in an ex-ante and authoritarian way, whereas, in the context of a CE project, the project team is created in an ex-post and democratized manner. On a dynamic multi-project level, the two approaches seem quite similar, with a few differences. In the case of PM, the project manager and his/her team are generally not responsible for parallel or subsequent projects. The notable exception is when, as in civil engineering, there are career paths that focus on project management, where the project manager may be reappointed. Another exception may be in platform management (Cusumano and Nobeoka, 1998) or lineage management (Kock and Gemünden, 2019; Midler, 2013) where the team is responsible for parallel projects to organize cross-project synergies and capitalization on a sequence of similar projects. In the case of CE, the project and its team are focused on the initial project, with little responsibility for linking to other projects or aligning the project with parallel or future

68  Handbook on innovation and project management

projects. This is more the role of the CE device. It may seem rather illusory to apply a priori control policies (platforms or project portfolios) to them because CE projects are not meant to fit into boxes but to initiate or experiment with new markets, new routines, etc. On the other hand, in dynamics, it is clear that the company will have to effectively apply or invent methods of controlling the actual profitability of the project and apply the theories and methods of project line management so that the profitability of the project is not limited to the profitability of the first exotic project, at the risk of seeing the CE devices disappear. Design issues: how to frame the development of these initiatives? The entrepreneurial logic of design management tends to be applied to CE logic. The studied systems favoured clearly tools and methodologies such as design thinking, lean startup, coaching, mentoring, proof of concept (POC) or agility. At first glance, these methods seem to be far removed from project management methodologies as described in the PMBOK (PMI, 2004) and its updates. The methodologies for controlling costs, deadlines and quality, structuring the project in work packages (WBS), GANTT or PERT planning, concurrent engineering, etc. are not frequently used. All these methods are not frequently used in CE projects, which are often managed in a more “agile” way. And even better, these projects claim not to use these old methodologies to maintain a “startup spirit”. However, on closer inspection, the PM and CE approaches are quite similar because they are based on the same pillar: learning-based management. Regarding PM, classical methodologies have progressively focused on control, to the detriment of innovation (Lenfle and Loch, 2010). But the roots of project management are not focused on control but on innovation. Let’s take two examples. Concurrent engineering was born in the 1990s with the objective of tracing upstream all the information and potential problems that would have occurred sooner or later during development (Carter and Baker, 1992; Clark and Fujimoto, 1991). For example, prototyping or using numerical simulation tools can avoid quality problems at the end of development, thus saving time and money (Thomke, 2001; Thomke and Fujimoto, 2000). Another example is the fact of integrating users into the design loop, which allows rapid learning about usage and avoids unpleasant surprises (Von Hippel, 1986). Concurrent engineering is essentially about coordination under complexity. It was forbidden by the DoD in the 1960s because “if someone already runs ahead without knowing yet what the input activity has come up with, it risks having to redo things and wasting resources”. Concurrent engineering is about the choreography under the circumstances of which a downstream activity can start without upstream being finalized – do we need to know the end result or an interim result, or can we try out under daily updates from upstream? There is a whole literature in PM about complexity and coordination, mostly in engineering but also in organizations (Eppinger, 1991; Terwiesch et al., 2002). Indeed, methodologies used in entrepreneurship and CE follow these principles (Nowacka et al., 2020). For example, concurrent engineering refers both to design thinking in the need to involve the customer as early and as centrally as possible in the innovation process and to the principles of agility and lean startup insofar as these methodologies are essentially oriented towards rapid learning loops about client uses (Nowacka et al., 2020). Agility also refers to the principles of organizing and reorganizing teams in a rapid manner, adapted to the specificities of the project. This is no different from the old principles laid down by Burns and Stalker (1963), on which project management was based at the beginning (Burns and Stalker, 1963).

Corporate entrepreneurship and project management  69

The organization of a project, whether emergent or induced by top management, must therefore be driven not by tasks or schedule, but by the speed and depth of learning achieved during the project (Midler et al., 2017). If we switch the analysis to a dynamic level, the logic remains the same. The idea is once again to use the initial strength of the vanguard project to decline new offers. From the point of view of design principles, this refers to the need to make explicit the design “meta-rules” that made the first project successful, i.e. the project mindset, the possible action variables, which sometimes go totally against the design standards of the core company (Jolivet et al., 2003; Midler, 2013). This explicitness is particularly difficult, first because once the initial project is completed, everyone wants to close the deal and embark on new challenges, not necessarily to extend the pleasure to related products or services. Secondly, the identification of meta-rules is clearly difficult, especially since most of them are tacit (Nonaka, 1991). It is also difficult to have the structures and governance adapted to this type of multi-project policy. Nevertheless, it can be emphasized that these lineage strategies are certainly difficult in the context of project management but are even more so in the case of CE. Indeed, from the moment when the orientation of projects isn’t defined by management (or marginally) but by employees, it is more difficult to create a lineage that will continue to question the current strategy and organization. Moreover, some companies have modified their CE process by focusing the ideation phase on concrete problems encountered by the company and their employees, questioning all their human resources to find solution(s). Corporate issues: what are the links between projects and organization? PM or CE initiatives must be articulated with the permanent organization (Loch and Sommer, 2019). To increase the legitimacy of a CE project, it needs to be supported by top management. Obviously, budgets and decisions must be obtained; this necessarily requires a minimum of legitimacy and visibility within the organization. Furthermore, the project needs internal and external resources (Basso et al., 2009; Bouchard and Fayolle, 2017; Huff, 2016) in order to exist and develop. On this point, the work in project management has clearly defined the situation. Initially, projects were troublemakers in a world dictated by business units or functions. The need for renewal (Chua et al., 1999), which has increased considerably over the last 30 years, has gradually shifted the barycentre to achieve a balance between functional activities and project activities, which have been added to the functions. The diffusion of the concept of new product development, defining a spectrum of organizational configurations with a balance of power between functional expertise and project management logic, was clearly a decisive step in this dynamic (Brown and Eisenhardt, 1995; Clark et al., 1987; Clark and Fujimoto, 1991; Clark and Wheelwright, 1992). In this spirit, it was necessary to assert the transversal role of the project manager, who should have a hierarchical weight at least equivalent to that of the functional directors. It was also a question of ensuring that the players in the functional departments were involved in the projects and committed themselves beyond giving expert advice. The model that was built in this way enabled organizations to transform themselves from production machines to development machines. The function of the project manager has thus been defined and legitimized a priori throughout the organization. On this point, CE differs widely. At the beginning of a CE project, there is only one individual, or at best a small team, coming from an unknown employee, but who carries a promising

70  Handbook on innovation and project management

concept. At this stage, he has absolutely no legitimacy. Fortunately, there are more and more initiatives coming from the top management, which aim at bringing out ideas from all or part of the company, in order to improve the current processes or to create new offers. The role of top management – generally represented by a team of management in charge of the CE device – is then to select the ideas and give a small budget to the project to see if the project can deliver on its promises. The role of top management is key in CE and PM. In the case of PM, this support is defined a priori and continues to be built throughout the project development. In the case of CE, the project starts before the support of top management and must show its interest before obtaining the necessary support. This support is essential, especially since the project will transform the established organization to different degrees, by calling into question its functioning or its product lines and by generating “organizational antibodies” that may call the project into question. Beyond the strategic aspect, which will be studied later, and if we want to draw a parallel with the principles of project management, the most important thing is to see to what extent these individuals are really empowered. Being selected in a competition for the best ideas is certainly not enough. Beyond what this new project leader can achieve, he/she must build a network of allies (Stopford and Baden-Fuller, 1994) to enable his/her initiative to unfold (Bouchard and Fayolle, 2017). In this dynamic, two paths are open. Either the intrapreneur finds enough allies internally to make the project succeed, or he/she must turn to the outside world to make it happen. Here we find the dichotomy studied by Huff between projects that, even if specified internally, can find internal or external support (Huff, 2016). It is clear that some intrapreneurs, faced with the lack of hierarchical support or the inability to federate a sufficient number of allies, turn to the external and go so far as to carry out an “inside-out” open innovation process to create an external startup (Chesbrough and Brunswicker, 2013). Concerning CE projects, the intrapreneur must build an “emergent team” around his/her individual initiative (Bouchard and Fayolle, 2017; Mohedano-Suanes and Benítez, 2018; Stopford and Baden-Fuller, 1994). These people will follow a much more difficult path than the emerging project leader. Indeed, even if they are interested, they have no mandate to dedicate time to the project (Bouchard and Fayolle, 2017); this process is based on “organizational slack” (Herold et al., 2006). We find here the roots of the project manager, who even without hierarchical authority, succeeds in having an influential role by allowing these emerging teams to progressively affirm their attachment to the project and to negotiate with their hierarchy to devote time and resources to it. This process of progressive interest is well known, especially in the sociology of innovation (Akrich et al., 1988). On the dynamic level, once projects are completed, the same question arises for CE and PM: how to maintain the initial energy to decline the first success in other “cousin” initiatives? In both cases, the continuity of this process could be embodied in the continuity of the teams (Midler, 2013) or through a more diffuse process of remobilization and the reconstitution of a new network of actors (Christiansen et al., 2010). The question of ambidexterity also arises in both cases. Should CE or PM projects be developed and deployed in the permanent organization – contextual ambidexterity – or in an ad hoc organization – structural ambidexterity? What are the routines to be invented and deployed? How can we articulate these activities that we want to rationalize and put under a process without losing the initial spirit of innovation? Even if it seems that building an innovation structure specifically adapted to the DNA of the first launch from scratch is easier to achieve

Corporate entrepreneurship and project management  71

than modifying the organizational routines of a large organization in place, this choice implies many disadvantages: lack of legitimacy, lack of resources, lower impact capacity, etc. This question of ambidexterity raises strategic issues, which we will now analyse. What about Strategic Issues? Linkage with corporate strategy In the first approach, the relationship between project and strategy can be described as topdown projects (PM) or bottom-up projects (CE). In the first case (top-down), the project follows the deliberate strategy of the company. The launch of the project is triggered by an analysis of existing opportunities. This analysis is based on investigations conducted by specialists in business, marketing, foresight, design, etc. Based on these elements, top management decides to launch this or that project and defines its main lines. It is then up to the dedicated management structures to define the functional specifications of this request. Based on these specifications, the development teams are mobilized to produce specifications ranging from the most general (system) to the most detailed (component, computer code). These teams, or others, are responsible for the actual integration of these elements into a complete system, the coherence of which must be checked against the initial request. We can therefore say that even if its role as a trigger is important, it is not really top management that decides on the launch or the completion of the project, but several dedicated departments that prescribe and carry out this work. The role of top management is above all to check that the proposed opportunities are consistent with the company’s strategy. However, the literature contains numerous articles that point out that the strategy is not a fixed framework that must be adhered to, but can evolve according to the information that is fed back to it, the failure or success of certain offers, or a diagnosis of the company’s resources and skills (Burgelman, 1983, 1994; Dougherty and Hardy, 1996). The top-down approach is therefore not so pronounced because the decision-making system passes through middle management and dedicated departments, and the strategy can evolve according to the inputs given. In the case of bottom-up projects (CE), the situation is not so different. Ideas and motivations for the creation of a new project are also made upstream and then presented to top management in a more or less direct way – according to idea challenges directly ordered by top management or through middle management – and it is up to him/her to decide to select and allocate resources to certain projects (generally through the CE device). The only difference is the services mobilized. Whereas in PM, the actors involved in the appraisal of the opportunity are clearly identified and structured, in the case of CE, this appraisal can be carried out by people or teams that do not belong to these structures. Indeed, this is generally the role of specialized innovation entities. Moreover, even if some of the mechanisms allow a maximum degree of freedom for the expression of needs for the launch of a CE project, there are also calls for projects that are more closely defined by top management, which will, for example, decide to define priority themes, markets or technologies, and in which the projects will have to fit (Bager et al., 2010). Now, consider this question from a dynamic perspective. Basically, beyond its initial coherence with the explicit strategy of the company, the dynamics of the project can participate in updating or even questioning the strategy of the company, understood as the definition of the offers and markets targeted by the company. These projects – PM or CE – could be considered vanguard projects, as vectors of diversification. “We argue that some vanguard projects serve

72  Handbook on innovation and project management

as an initial corporate entrepreneurial device for responding to and creating innovation in technologies and markets” (Frederiksen and Davies, 2008, 487). In this context, a company can press the gas pedal and deploy innovation beyond the initial ambition. The “scale up” thus consists of moving from a relatively modest initiative, with a small team and in niche and often local markets, to the deployment of the innovation on a broad geographical basis or the expansion of niche markets to mass markets. For startups, it is a matter of organizing themselves to set up new processes and routines, developing new resources, both human and financial, a stabilized organization, etc. The challenge is major. This is where the issue of ambidexterity reappears. The situation is quite similar if the innovative projects (PM or CE) have been developed within the permanent organization (contextual ambidexterity) or in a structure dedicated to innovative projects (structural ambidexterity). In both cases, the challenge is either (1) to express the full potential of the project in a dedicated structure or (2) to legitimize the project’s output to the business units involved and to ensure that this output is integrated into internal routines as “the development of routines, standard operating procedures and the establishment of an administrative framework for the new venture” (Burgelman, 1983, 1363). A priori, this choice may depend on the degree of radicalness of the innovative project. Existing organizations are certainly better equipped to develop products that are not very innovative. They have development routines that constitute dynamic capacities that allow them to reproduce the act of innovation on a regular basis, with this aptitude constituting a real dynamic capacity that allows them to survive in the medium and long term (Brown and Eisenhardt, 1995, 1997; Eisenhardt and Martin, 2000). For more radical innovations, the permanent organization is ill-equipped to deploy the innovation because neither the routines nor the resources or skills nor the organizational architecture is adapted to integrate the innovation into the traditional regime. That’s why some projects could be “spin-offed” and continue their development outside of the organization. CE literature also tackled the relation between the emerging project and the company’s assets. For example, Covin and Miles (1999) state that CE can stand as “corporate rejuvenation”, boosting or reorienting the assets of the company. One can also see the difference between (1) “sustained regeneration”, involving the continuous introduction of new products aimed at the same or similar markets and involving largely similar families of technologies to achieve competitive differentiation or (2) more intrusive “strategic renewal’, such as “redefinition of industry domain”, or looking at to what extent the CE project highlighted new business areas where there is still no demand (Frederiksen and Davies, 2008). At this stage, it is still up to top management to make these decisions, through regular committees. They also have the option of stopping the project or not pursuing it, or inserting this initiative into the dynamics of the company’s other projects. Linkage with other projects The platform, programme and ambidextrous programme models organize a priori coordination between different projects. In the programme and platform models, the aim is to coordinate different projects to achieve a more global objective. A relatively macro-goal is defined (e.g. the organization of the Olympic Games) by a strategic entity, and programme and platform management methods aim to orchestrate these different projects so that they complement each other in order to achieve this overall objective. The PM model fits well with these models because once this macro-plan and the sub-projects are defined, PM takes over and enters the

Corporate entrepreneurship and project management  73

execution phase. Programmes articulate projects with the same level of radicality towards an objective of low or medium radicality; ambidextrous programmes articulate projects with different maturities and degrees of radicality with an objective of the global transformation of the enterprise. It is therefore understandable that CE is hardly compatible with these models. From the moment that ideas can come from all over the place and be articulated with other projects in a null, random or accidental way, it is difficult to achieve a priori coordination. The lineage model organizes a posteriori coordination between the different projects. Based on a first vanguard project, the goal is to continue the effort by seizing the assets built by this first project, by organizing a series of “cousin” projects that will have a variable impact on the transformation of the organization and the product strategy. This model works for both PM and CE. Whether ideas emerge from non-predetermined individuals or teams, or from market analyses performed by specialized departments or top management, the project can play a vanguard project role. Whether or not the company decides to pursue this first innovative initiative does not depend on how the concept was determined in the first place. On the other hand, the goal pursued also differs between the models. The platform policy has a clear objective of cost reduction. For example, industrial product platforms such as the automotive industry aim to minimize the diversity of components and systems within a product family. The main objective of the lineage model is to create value by increasing the value of each product over time while following a policy of cost minimization between projects. The portfolio management model also tends to maximize the cost/value ratio in a logic of demographic management and profitability optimization within a portfolio of projects that is balanced in terms of profit expectancy. Programme models are primarily concerned with the technical coordination of projects to ensure that, once assembled, the final objective is achieved. On this question of the objective pursued, the CE and PM models are relevant and similar. Ideas, whether they come from the top or the bottom, can have objectives of cost reduction, value creation or both.

CONCLUSION In the end, one can say that it is a great pity that these two literatures discuss so little between them. This theoretical distinction between the two schools of thought suggests that CE and PM are more opposed than they are close. It is true that one might think that there is nothing to compare between emergent projects led by internal entrepreneurs who rely on ad hoc processes and top-down projects regulated by strategic and prospective studies, and which rely on strict project management processes. This chapter was a an attempt to explain these differences and to identify the similarities and complementarities between the two approaches, summarized in Table 3.1. The major difference is obviously the origin of the ideas that give rise to the projects. In the case of CE, ideas can come randomly. Even though calls for ideas, which remain the main mechanism for initiating intrapreneurial projects, may involve some framing, the people who carry these ideas may belong to any organizational unit and the ideas may be radical or incremental from a market or technology perspective. Another difference relates to the organization of the project. The established project management processes organize a priori a pre-selection of project managers, who sometimes

74  Handbook on innovation and project management

Table 3.1  Table summary of results Corporate entrepreneurship

Project management

Goal

Creating something new

Creating something new

Type of company

Large firms, SMEs

Large firms, SMEs

Source of project ideation

From individual or self-appointed team

People from strategy, product planning or R&D

Project selection

Top management or business unit sponsor

Top management or PMO

Project manager

Ideator

Professional project manager

Project team

Ad hoc self-organizing and emerging team

Ex-ante/formal predefined team

Project routines

Ad hoc emerging routines at the beginning, then execution through project development routines

Ex-ante predefined project management routines

Project methods

Agility methods

Control methods

Portfolio management

A posteriori coordination

A priori coordination

belong to human resources departments dedicated to this function. They involve people with functional expertise according to routines that make it possible to anticipate a priori the composition of the project team. In CE, the project manager is self-appointed by the idea he or she is carrying, and the team is put together in a more ad hoc manner, according to the specificities of the concept and the social network of the intrapreneur. But there are many similarities. Both currents of thought deal with the same question: how to deal with coordination and complexity? In both cases, they are attempts to frame this problem within the framework of innovative initiatives, starting each time with new ideas and concepts, and to organize collectives to go from the idea to the execution and then to the market launch or scale-up. CE and PM also rely on the same logic, which combines the creation of powerful learning mechanisms with a milestone sequence that forces the decision to finalize the project. Next, it would be wrong to think that CE projects are totally emergent and PM projects totally top-down. It is only the prescribers that change. In the case of PM, the prescribers belong to well-defined functions, such as expert functions in strategy, foresight, marketing or R&D, who submit product strategies to the general management, which approves or redirects them. In the case of CE, the prescribers are less well known and less instituted and may be individuals, middle management or internal sponsors, who also suggest development projects to top management, whose role is to validate or not their relevance. At a multi-project level, we understand that intrapreneurial projects cannot be extracted from any rationality at the project portfolio management level. The logic of portfolio management requires that CE projects complement an existing portfolio and contribute to its overall balance. So, we can say that those deliberate projects can be partially emergent, and emergent projects can symmetrically be influenced by a deliberate strategy portfolio of projects. The two approaches are also complementary. Once again, it would be wrong to believe that CE processes are emergent and chaotic, whereas development processes are highly structured. On the one hand, CE also needs processes to avoid constantly reinventing the wheel. For

Corporate entrepreneurship and project management  75

this purpose, it can rely on the literature concerning the management of exploration projects, which offers a framework allowing both control and flexibility. On the other hand, we can consider that the two approaches can follow each other in time, CE can constitute an initial phase of ideation and exploratory project management, but at a given moment in the process, the company must seize the project and switch to PM mode, focused on execution. It is precisely this last point that makes corporate entrepreneurship stronger than entrepreneurship because it relies on the power of the company, its assets, its expertise and its processes.

REFERENCES Abetti, P.A. (1997). The birth and growth of Toshiba’s laptop and notebook computers: A case study in Japanese corporate venturing. Journal of Business Venturing, 12(6), 507–529. Akrich, M., Callon, M., and Latour, B. (1988). À quoi tient le succès des innovations ? Gérer et Comprendre, 97(11–12), 4–29. Allen, T.J. (2001). Organizing for product development. Available at SSRN: https://ssrn​.com​/abstract​ =297304 Alpkan, L., Bulut, C., Gunday, G., Ulusoy, G., and Kilic, K. (2010). Organizational support for intrapreneurship and its interaction with human capital to enhance innovative performance. Management Decision, 5(48), 732–755. Andriopoulos, C. and Lewis, M.W. (2009). Exploitation-exploration tensions and organizational ambidexterity: Managing paradoxes of innovation. Organization Science, 20(4), 696–717. Antoncic, B. and Hisrich, R.D. (2001). Intrapreneurship: Construct refinement and cross-cultural validation. Journal of Business Venturing, 16(5), 495–527. Antoncic, B. and Hisrich, R.D. (2003). Clarifying the intrapreneurship concept. Journal of Small Business and Enterprise Development, 10(1), 7–24. Auer Antoncic, J. and Antoncic, B. (2011). Employee satisfaction, intrapreneurship and firm growth: A model. Industrial Management & Data Systems, 111(4), 589–607. Bager, T., Ottosson, H., and Schott, T. (2010). Intrapreneurs, entrepreneurs and spin-off entrepreneurs: Similarities and differences. International Journal of Entrepreneurship and Small Business, 10(3), 339–358. Basso, O. (2006). Peut-on manager les intrapreneurs? Revue Française de Gestion, 9, 225–242. Basso, O., Fayolle, A., and Bouchard, V. (2009). L’orientation entrepreneuriale. Revue Française de Gestion, 5, 175–192. Benner, M.J. and Tushman, M.L. (2003). Exploitation, exploration, and process management: The productivity dilemma revisited. Academy of Management Review, 28(2), 238–256. Berggren, C., Bergek, A., Bengtsson, L., Hobday, M., and Söderlund, J. (2011). Knowledge integration and innovation: Critical challenges facing international technology-based firms. Oxford University Press. Bierwerth, M., Schwens, C., Isidor, R., and Kabst, R. (2015). Corporate entrepreneurship and performance: A meta-analysis. Small Business Economics, 45(2), 255–278. Bosma, N.S., Stam, F.C., and Wennekers, A.R.M. (2010). Intrapreneurship: An international study. Scales. Bouchard, V. and Fayolle, A. (2017). Corporate entrepreneurship. Routledge. Bourreau, M. and Perrot, A. (2020). Digital platforms: Regulate before it’s too late. Notes du Conseil Danalyse Economique, 60(6), 1–12. Brady, T. and Davies, A. (2004). Building project capabilities: From exploratory to exploitative learning. Organization Studies, 25(9), 1601–1621. Brown, S.L. and Eisenhardt, K.M. (1995). Product development: Past research, present findings, and future directions. Academy of Management Review, 20(2), 343–378. Brown, S.L. and Eisenhardt, K.M. (1997). The art of continuous change: Linking complexity theory and time-paced evolution in relentlessly shifting organizations. Administrative Science Quarterly, 42(1), 1–34.

76  Handbook on innovation and project management

Burgelman, R.A. (1983). Corporate entrepreneurship and strategic management: Insights from a process study. Management Science, 29(12), 1349–1364. Burgelman, R.A. (1994). Fading memories: A process theory of strategic business exit in dynamic environments. Administrative Science Quarterly, 39(1), 24–56. Burns, T. and Stalker, G.M. (1963). The management of innovation (Tavistock). Harcourt Brace Orlando. Carter, D. and Baker, B. (1992). Concurrent engineering: The product development environment for the 1990s. Addison-Wesley Publ. Comp. Chang, Y.-Y., Liu, Y.P., and Chang, C.-Y. (2019). A multilevel examination of entrepreneurial orientation and corporate entrepreneurship: The joint impact of unit-level social capital and firm-level transformational leadership. Entrepreneurship Research Journal, 9(4), 1–19. Chesbrough, H. and Brunswicker, S. (2013). Managing open innovation in large firms. Berkeley, CA: Fraunhofer Verlag. Christensen, J.F. and Maskell, P. (2003). The industrial dynamics of the new digital economy. Edward Elgar Publishing. Christiansen, J.K., Varnes, C.J., Gasparin, M., Storm-Nielsen, D., and Vinther, E.J. (2010). Living twice: How a product goes through multiple life cycles. Journal of Product Innovation Management, 27(6), 797–827. Chua, J.H., Chrisman, J.J., and Sharma, P. (1999). Defining the family business by behavior. Entrepreneurship Theory and Practice, 23(4), 19–39. Clark, K., Chew, W., and Fujimoto, T. (1987). Product development in the world auto industry. Brookings Papers on Economic Activity, 18(3), 729–771. Clark, K.B. and Fujimoto, T. (1991). Product development performance: Strategy, organization and management in the world auto industry. Harvard Business School Press. Clark, K.B. and Wheelwright, S.C. (1992). Organizing and leading “heavyweight” development teams. California Management Review, 34(3), 9–28. Covin, J.G. and Lumpkin, G.T. (2011). Entrepreneurial orientation theory and research: Reflections on a needed construct. Entrepreneurship Theory and Practice, 35(5), 855–872. Covin, J.G. and Miles, M.P. (1999). Corporate entrepreneurship and the pursuit of competitive advantage. Entrepreneurship Theory and Practice, 23(3), 47–63. Cusumano, M.A. and Nobeoka, K. (1998). Thinking beyond lean. Free Press. D’Amboise, G. and Verna, G. (1993). De l’entrepreneur à l’intrapreneur. GESTION 2000, 9, 1–13. Davies, A., Manning, S., and Söderlund, J. (2018). When neighboring disciplines fail to learn from each other: The case of innovation and project management research. Research Policy, 47(5), 965–979. Delić, A., Alibegović, S., Đonlagić, and Mešanović, M. (2016). The role of the process organizational structure in the development of intrapreneurship in large companies. Naše Gospodarstvo/Our Economy, 62(4), 42–51. Dougherty, D. and Hardy, C. (1996). Sustained product innovation in large, mature organizations: Overcoming innovation-to-organization problems. Academy of Management Journal, 39(5), 1120–1153. Eisenhardt, K.M. and Martin, J.A. (2000). Dynamic capabilities: What are they? Strategic Management Journal, 21(10–11), 1105–1121. Eisenmann, T., Parker, G., and Van Alstyne, M.W. (2006). Strategies for two-sided markets. Harvard Business Review, 84(10), 92. Eppinger, S.D. (1991). Model-based approaches to managing concurrent engineering. Journal of Engineering Design, 2(4), 283–290. Euchner, J. (2016). Emerging models for corporate innovation: Insights from the IRI 2015 strategy forum. Research-Technology Management, 59(1), 56–60. Fayolle, A., Basso, O., and Bouchard, V. (2010). Three levels of culture and firms’ entrepreneurial orientation: A research agenda. Entrepreneurship and Regional Development, 22(7–8), 707–730. Fine, C. (1998). Clockspeed. Perseus Books. Fonrouge, C., Bredillet, C., and Fouché, C. (2018). Entrepreneurship and project management relationships: So far so good? Dialogic conversation and Luhmannian perspective. International Journal of Managing Projects in Business, 12(1), 6–24. Frederiksen, L. and Davies, A. (2008). Vanguards and ventures: Projects as vehicles for corporate entrepreneurship. International Journal of Project Management, 26(5), 487–496.

Corporate entrepreneurship and project management  77

Hansen, K., Amundsen, O., Aasen, T.M.B., and Gressgård, L.J. (2017). Management practices for promoting employee-driven innovation. In Workplace innovation (pp. 321–338). Springer. https:// link​.springer​.com​/chapter​/10​.1007​/978​-3​-319​-56333​-6​_19 Henderson, R.M. and Clark, K.B. (1990). Architectural innovation: The reconfiguration of existing product technologies and the failure of established firms. Administrative Science Quarterly, 35(1), 9–30. Herold, D.M., Jayaraman, N., and Narayanaswamy, C.R. (2006). What is the relationship between organizational slack and innovation? Journal of Managerial Issues, 372–392. Hisrich, R.D. (1990). Entrepreneurship/intrapreneurship. American Psychologist, 45(2), 209. Høyrup, S. (2010). Employee-driven innovation and workplace learning: Basic concepts, approaches and themes. London: SAGE Publications. Høyrup, S. (2012). Employee-driven innovation: A new phenomenon, concept and mode of innovation. In Høyrup, S., Bonnafous-Boucher, M., Hasse, C., Lotz, M., Møller, K. (eds), Employee-driven innovation (pp. 3–33). Springer. Huff, A.S. (2016). Project innovation: Evidence-informed, open, effectual, and subjective. Project Management Journal, 47(2), 8–25. Jacobides, M.G., Baldwin, C.Y., and Dizaji, R. (2007). From the structure of the value chain to the strategic dynamics of industry sectors. In Presentation slides from academy of management annual meeting. Jolivet, E., Laredo, P., and Shove, E. (2003). Managing breakthrough innovations: Theoretical implications from – and for – the sociology of science and technology. In ASEAT conference – Knowledge and economic and social change. New Challenges to Innovation Studies, Manchester. Jung, S. (2018). Cooperating with start-ups as a strategy: Towards corporate entrepreneurship and innovation. In André Presse & Orestis Terzidis (eds.), Technology entrepreneurship (pp. 283–298). Springer. Klein, B. and Meckling, W. (1958). Application of operations research to development decisions. Operations Research, 6(3), 352–363. Kock, A. and Gemünden, H.G. (2019). Project lineage management and project portfolio success. Project Management Journal, 50(5), 587–601. Kuratko, D.F. (2005). The emergence of entrepreneurship education: Development, trends, and challenges. Entrepreneurship Theory and Practice, 29(5), 577–597. Kuura, A., Blackburn, R.A., and Lundin, R.A. (2014). Entrepreneurship and projects – Linking segregated communities. Scandinavian Journal of Management, 30(2), 214–230. Lawrence, P.R. and Lorsch, J.W. (1967). Differentiation and integration in complex organizations. Administrative Science Quarterly, 12(1), 1–47. Lenfle, S. (2008). Exploration and project management. International Journal of Project Management, 26(5), 469–478. Lenfle, S. and Loch, C. (2010). Lost roots: How project management came to emphasize control over flexibility and novelty. California Management Review, 53(1), 32–55. Lenfle, S. and Midler, C. (2009). The launch of innovative services: Lessons from automotive telematics. Research Policy, 38(1), 156–169. Leonard-Barton, D. (1992). Core capabilities and core rigidities: A paradox in managing new product development. Strategic Management Journal, 13 (Special Issue: Strategy Process: Managing Corporate Self-Renewal), 111–125. Loch, C. and Sommer, S. (2019). The tension between flexible goals and managerial control in exploratory projects. Project Management Journal, 50(5), 524–537. Maniak, R., Midler, C., Lenfle, S., and Pellec-Dairon, M. (2014). Value management for exploration projects. Project Management Journal, 45(4), 55–66. Marsh, S.J. and Stock, G.N. (2003). Building dynamic capabilities in new product development through intertemporal integration. Journal of Product Innovation Management, 20(2), 136–148. Marsh, S.J. and Stock, G.N. (2006). Creating dynamic capability: The role of intertemporal integration, knowledge retention, and interpretation. Journal of Product Innovation Management, 23(5), 422–436. Martiarena, A. (2013). What’s so entrepreneurial about intrapreneurs? Small Business Economics, 40(1), 27–39.

78  Handbook on innovation and project management

Midler, C. (1995). “Projectification” of the firm: The Renault case. Scandinavian Journal of Management, 11(4), 363–375. Midler, C. (2013). Implementing a low-end disruption strategy through multiproject lineage management: The Logan case. Project Management Journal, 44(5), 24–35. Midler, C., Jullien, B., Lung, Y., and Ghosn, C. (2017). Rethinking innovation and design for emerging markets: Inside the Renault Kwid project. Auerbach Publications. Midler, C., Maniak, R., and de Campigneulles, T. (2019). Ambidextrous program management: The case of autonomous mobility. Project Management Journal, 50(5), 571–586. Midler, C. and Silberzahn, P. (2008). Managing robust development process for high-tech startups through multi-project learning: The case of two European start-ups. International Journal of Project Management, 26(5), 479–486. Mintzberg, H. and McHugh, A. (1985). Strategy formation in an adhocracy. Administrative Science Quarterly, 30(2), 160–197. Mohedano-Suanes, A. and Benítez, D.G. (2018). Intrapreneurs: Characteristics and behavior. In Tur Porcar, A., Ribeiro Soriano, D. (eds), Inside the mind of the entrepreneur (pp. 109–119). Springer. Morris, M.H., Kuratko, D.F., and Covin, J.G. (2010). Corporate entrepreneurship & innovation. Cengage Learning. Nguyen, N.M., Killen, C.P., Kock, A., and Gemünden, H.G. (2018). The use of effectuation in projects: The influence of business case control, portfolio monitoring intensity and project innovativeness. International Journal of Project Management, 36(8), 1054–1067. Nonaka, I. (1991). The knowledge-creating company. Harvard Business Review, 69(6), 96–104. Nonaka, I. (1994). A dynamic theory of organizational knowledge creation. Organization Science, 5(1), 14–37. Nonaka, I., Nonaka, I., Ikujiro, N., and Takeuchi, H. (1995). The knowledge-creating company: How Japanese companies create the dynamics of innovation. Oxford University Press. Nowacka, U., Głębocki, R., and Gil, A. (2020). Creating intrapreneurship as an area of corporate entrepreneurship. Society. Integration. Education. Proceedings of the International Scientific Conference, 6, 717–730. O Reilly, C.A. and Tushman, M.L. (2004). The ambidextrous organization. Harvard Business Review, 82(4), 74–83. Pandey, J. and Tewary, N.B. (1979). Locus of control and achievement values of entrepreneurs. Journal of Occupational Psychology, 52(2), 107–111. Parker, J., Corner, P.D., Woodfield, P.J., and Singh, S. (2021). Developing endogenous innovations: Corporate entrepreneurship and effectuation. Entrepreneurship Research Journal, 11(1). Penrose, L.S. (1959). Self-reproducing machines. Scientific American, 200(6), 105–117. Phan, P.H., Wright, M., Ucbasaran, D., and Tan, W.-L. (2009). Corporate entrepreneurship: Current research and future directions. Journal of Business Venturing, 24(3), 197–205. Pinchot III, G. (1985). Intrapreneuring: Why you don’t have to leave the corporation to become an entrepreneur. PMI. (2004). A guide to the project management body of knowledge. Pennsylvania: Project Management Institute. Pollack, J. (2007). The changing paradigms of project management. International Journal of Project Management, 25(3), 266–274. Sarasvathy, S.D. (2001). Causation and effectuation: Toward a theoretical shift from economic inevitability to entrepreneurial contingency. Academy of Management Review, 26(2), 243–263. Sharma, P. and Chrisman, J. (1999). Entrepreneurship theory and practice, toward a reconciliation of the definitional issues in the field of corporate entrepreneurship. Journal of Business and Management, 20(9), 31–41. Sharma, P. and Chrisman, S.J.J. (2007). Toward a reconciliation of the definitional issues in the field of corporate entrepreneurship. In Cuervo, Á., Ribeiro, D., Roig, S. (eds), Entrepreneurship (pp. 83–103). Springer. Shenhar, A.J. and Dvir, D. (2007). Reinventing project management: The diamond approach to successful growth and innovation. Harvard Business Review Press. Slevin, D.P. and Covin, J.G. (1990). Juggling entrepreneurial style and organizational structure. MIT Sloan Management Review, 31(2), 43.

Corporate entrepreneurship and project management  79

Smith, P., Ulhøi, J.P., and Kesting, P. (2012). Mapping key antecedents of employee-driven innovations. International Journal of Human Resources Development and Management, 12(3), 224–236. Sommer, S.C. and Loch, C.H. (2004). Selectionism and learning in projects with complexity and unforeseeable uncertainty. Management Science, 50(10), 1334–1347. Stopford, J.M. and Baden-Fuller, C. W. (1994). Creating corporate entrepreneurship. Strategic Management Journal, 15(7), 521–536. Svejvig, P. and Andersen, P. (2015). Rethinking project management: A structured literature review with a critical look at the brave new world. International Journal of Project Management, 33(2), 278–290. Teece, D.J. (2007). Explicating dynamic capabilities: The nature and microfoundations of (sustainable) enterprise performance. Strategic Management Journal, 28(13), 1319–1350. Teece, D.J., Pisano, G., and Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509–533. Terwiesch, C., Loch, C.H., and Meyer, A.D. (2002). Exchanging preliminary information in concurrent engineering: Alternative coordination strategies. Organization Science, 13(4), 402–419. Thomke, S. (2001). Enlightened experimentation. The new imperative for innovation. Harvard Business Review, 79(2), 66–75. Thomke, S. and Fujimoto, T. (2000). The effect of “front-loading” problem-solving on product development performance. Journal of Product Innovation Management: An International Publication of the Product Development & Management Association, 17(2), 128–142. Tushman, M.L. and O’Reilly III, C.A. (1996). Ambidextrous organizations: Managing evolutionary and revolutionary change. California Management Review, 38(4), 8–29. Von Hippel, E. (1986). Lead users: A source of novel product concepts. Management Science, 32(7), 791–805. Wernerfelt, B. (1984). A resource-based view of the firm. Strategic Management Journal, 5(2), 171–180. Wheelwright, S. and Clark, K. (1992). Revolutionizing product development. The Free Press. Zahra, S.A. (1991). Predictors and financial outcomes of corporate entrepreneurship: An exploratory study. Journal of Business Venturing, 6(4), 259–285. Zenovia, C.P. and Maier, V. (2011). Entrepreneurship versus intrapreneurship. Journal Review of International Comparative Management, 12(5), 971–980.

4. The converging nature of innovation and project management: process, contingency and strategy Vered Holzmann and Aaron Shenhar

INTRODUCTION Society’s endless quest for humanity’s life improvement is manifested in at least two separate, though related, concepts: innovation and projects. Innovation deals with the transformation of new ideas into real valuable outcomes or outputs (Schumpeter, 2010), while projects represent the organized efforts that turn these ideas into successful creations (Kerzner, 2017). Obviously, there is a strong link between the two. However, from a scholarly perspective, the current knowledge, research and frameworks found in academic publications have been at times disjointed. The two corresponding groups of scholars have often published their studies in different journals, presented at different conferences, used two different knowledge bases and, notably, failed to learn from each other (Davies et al., 2018). In reality, however, the two concepts seem to represent two parts of the same process – the process of getting ideas to markets and to the hands of customers and users. Furthermore, in most practising organizations, innovation and projects are strongly linked, often performed by the same people, who are jointly attempting to achieve the same goals. In this chapter, we address the link between innovation and projects and suggest looking at them as two parts of the same consolidated process – the process by which society and its organizations turn ideas into new realities. We believe it may be helpful to even coin a new name for it; however, at this time, we will still call the combined effort the innovation/project process. We argue that consolidating the two fields would greatly deepen our insights into humanity’s creative forces, open up new research opportunities and speed up implementation efforts in most companies. We will discuss the separate interests of the two communities, before dealing in more detail with the suggested combined process. Such a process begins always with an idea and ends with the delivery of a product into the hands of customers and users. The main body of this chapter is dedicated to four themes: first, we discuss the organizational process that is typically applied in furnishing a new creation. For each step in the process, we outline the kind of work performed, who is involved, what expertise is needed, what we know about it and, finally, what kind of future research is needed or expected. Second, since “one size does not fit all”, we review the relevant theory of contingency, which would be useful for adapting management to contexts, and suggest a unified contingency framework for future studies and practices. Third, we address the business-related strategy issues relevant to innovations and projects by using a recently developed framework for an innovation/project strategy. Finally, we discuss the implementation aspects of a combined innovation/project process, as well as potential areas for future research. 80

The converging nature of innovation and project management  81

THE PARALLEL EVOLUTION OF PROJECT AND INNOVATION MANAGEMENT RESEARCH The concept of project management was first developed in the military and construction and was a major objective of the engineering discipline. Famous projects became the subjects of books and studies, which often described the lessons and difficulties involved in building and operating them. Typical early stories involved railway or canal projects (Davies et al., 2014; Koeppel, 2009), famous buildings such as the Empire State Building (Birch, 2006) or space programmes such as the Apollo Moon Landing (Gisler and Sornette, 2009). However, projects were often discussed as “one shot”, with limited interest in proximity fields or the permanent organizations which undertook them. Evidently, the link between projects and the innovations they represented as well as their competitiveness (e.g., Schumpeter, 2010) had little place. The concepts of innovation as a disciplinary field and its association with competitiveness were introduced in the 1980s and 1990s with famous studies on product development and product differentiation (Clark and Wheelwright, 1992; Fujimoto, 1992), together with discussions on the relationships between projects and their permanent organizations (Midler, 1995). Although as mentioned, project management and innovation were often considered separate fields, a few authors have nevertheless demonstrated the impacts of these fields on each other or the relationship of a parent organization on its projects. For example, Davies et al. (2014) have shown how a deliberate innovation process could improve the performance of mega infrastructure projects. Using lessons from London’s Crossrail Railway system, they identified four windows of opportunity where an appropriate innovation strategy can drive innovation in a megaproject: fist, during the front end of the project, second, during the contract engagement period, third, during the execution period, taking advantage of mutual engagements among multiple parties and, finally, at the back end, where ideas can be combined with lessons from other projects to improve learning and performance. Another notable contribution was Engwall’s (2003) “No Project Is an Island” study that used two major engineering efforts – the hydropower and transmission projects – to address the importance of analysing the interior processes of a project in relation to its historical and environmental context. To do that, Engwall analysed experiences from past projects, organizational politics during the pre-project phases, parallel courses of events during the execution period, ideas about the post-project future, and institutional norms, values and routines of the project’s organizational context. Clearly, no discussion of the links between innovation and project management can be completed without mentioning Robert Cooper’s work on project portfolio management or his Stage-Gate process (Cooper, 2017; Cooper et  al., 1997). Cooper asserted that portfolio management has three major goals: maximizing the value of the portfolio, building a balance in the portfolio and linking the project to the business strategy. He also advocated dividing a project’s process into gate decisions, where at each gate a choice is made between “killing” the project or moving it forward, based on the chances of its business success. Finally, as Shenhar et al. (2020) have shown, any innovation success depends, primarily, on setting up the right project for realizing it. As these and several other studies demonstrate, the boundaries between projects and innovation are gradually blurring, whereas the associated organizational efforts are often hard to distinguish. Hence as we move forward, we advocate combining these disciplines into one field, calling it together the innovation/project effort.

82  Handbook on innovation and project management

To support the merging of the two disciplines, we must establish a set of joint frameworks that could be used by future researchers and managers. Yet, we must first revisit the commonly used definitions of innovation and projects and show why one combined definition is appropriate.

REVISITING THE DEFINITIONS – THE COMBINED DEFINITION OF INNOVATION/PROJECTS Multiple definitions of innovation were offered in the past. For example, Crossan and Apaydin (2010) defined innovation as production or adoption, assimilation, and exploitation of a value-added novelty in economic and social spheres; renewal and enlargement of products, services, and markets; development of new methods of production; and establishment of new management systems. Innovation is both a process and an outcome.

The UK Department of Trade and Industry defined innovation as “the successful exploitation of new ideas” (DTI, 2003). However, for the purpose of this chapter, we adopt Cropley’s (2006) simple definition: “Innovation is the process of commercializing the novel product”. Similarly, several definitions of a project have been offered: for example, the Project Management Institute has defined a project as “a temporary endeavor undertaken to create a unique product, service, or result” (2017). Other, more specific definitions have identified a project as both a process and an organization, leading Shenhar et al. (2020) to adopt the following simple definition: “A project is a temporary organization and process set up to create new value in the world”. Notably, both kinds of definitions are highlighting the creation of valuable change in the world, and as such, they are largely indistinguishable. On one hand, as mentioned, there is no successful innovation without a project, and on the other hand, since every project is based on an idea for building a new reality, each project can appropriately be considered an innovation. Therefore, we suggest using the following combined and simple definition: “an innovation/project is the commercialization of an idea”, where commercialization is perceived in its broad sense, namely, an idea that has led to a successful and useful outcome. As mentioned, the following three sections are dedicated to the three proposed frameworks and models for portraying the process, contingency and strategy of a combined innovation/ project effort.

THE INNOVATION/PROJECT PROCESS MODEL Different models of the innovation process have been offered since the middle of the 20th century (e.g., Myers and Marquis, 1969). Early on, a three-phase model was offered by Utterback (1971): idea generation, problem solving and implementation. Later models have expanded into specific steps such as proposal, selection, design, planning, building or testing (e.g., Cooper

The converging nature of innovation and project management  83

and Kleinschmidt, 1986; Salerno et  al., 2015). Our suggested combined generic process of innovation/project is depicted in Figure 4.1. The different phases and the different steps in the process are mostly distinguished by the type of work and expertise needed. In a similar way to Utterback’s (1971) framework, this extended model can be divided into three major phases: 1. The idea management phase – often called the “Fuzzy Front End of Innovation” (Edkins et al., 2013; Koen et al., 2001; Verworn et al., 2001) or “the pre-project phase” (Gassmann and von Zedtwitz, 2003; Verganti, 1997). This is the initiation stage of any innovation, where opportunities are identified and concepts are developed prior to entering a formal realization or development phase. At this stage, things are still quite informal and undeveloped; ideas are encouraged, collected and discussed, while many are tossed away, and only a few are confirmed for moving on. It includes the initial idea generation, idea testing, proposal and project selection. 2. The product realization phase – at this stage, a formal project is established, a project manager and a team are selected, the project scope, budget and schedule are set, the product is designed and developed and a formal process of review and control is established for building, testing and approval of the final product. 3. The product commercialization phase – this is where the innovation product is getting ready for implementation. The effort at this phase is focused on introducing the product to the market and establishing support for its extended lifecycle. Improvements are made, and next generations defined – including intermediate spinoffs, or derivatives, as well as higher- and lower-end versions. Table 4.1 summarizes the kind of activities in each step, who is involved, what is known and what still needs further study.

Figure 4.1  The innovation/project process

84

Activities (kind of work)

Ideas are collected based on needs, experience, availability of technology, market surveys, etc. Potential ideas are collected and saved for review, including reverse engineering of competitors. Databases of ideas are created.

Ideas are discussed and assessed based on specific company criteria, such as value creation, chance of success, availability of resources, etc.

Detailed proposals are written, with detailed assessment of expected benefits and value, resources and expertise needed, as well as risks. Comparisons to competitors’ products and competing proposals are made.

Phase

Idea generation

Idea testing and internal promotion of ideas

Proposal Initiators and champions are assisted by marketing and finance experts to prepare appealing proposals.

Idea generators and professional testing personnel. Idea champions may be needed to sell the idea inside, at a time when ideas are still vulnerable and need support.

Anyone – engineers, customers, competitors, as well as crowd responders in open innovation market. Highly creative people often produce most ideas. Gatekeepers scan markets and previous studies and adopt ideas from outside sources.

Expertise (who is involved)

Table 4.1  The innovation/project steps along the process

Companies develop their own proposal formats. Most proposals present financial projections and expected sales, compared to expenses and budgets.

Idea generators, idea champions and gatekeepers are different kinds of people.

Ideas should be looked for everywhere; open innovation should be encouraged.

What is known

More developed strategic review frameworks are needed. Such frameworks need to address the proposal’s competitiveness beyond common financial estimations. Proposals also need to be focused on specific project types and their impact on project management.

More tools, techniques and criteria for idea review are needed. Strategic considerations need to be added to assess selection of specific ideas.

How to identify the most creative people? How to build better techniques to stimulate the creation of more ideas?

Future research and development needed

85

Proposals are reviewed for acceptance, modification or elimination. A final proposal is approved for implementation.

Functional requirements are prepared for product development. Technical specifications are determined.

Project planning is conducted to determine scope, cost, schedule and method of work, as well as resources needed and risks involved.

Product design is conducted to determine building and testing instructions.

Project selection

Requirements/specs

Planning

Design Product designers with the support of design tools and design experts.

Project teams and planning experts from planning and budgeting groups.

Proposers, idea generators, business experts and relevant experts discussing and writing final requirements and technical specifications.

Proposers, idea generators and selection teams consisting of executive teams, including relevant experts.

Design methods should include the impact of designed products on competitiveness and company strategies.

Teams follow traditional planning techniques, agile approaches or hybrid methodologies. However, often teams do not dedicate enough time to planning.

There is still no standard format to write requirements and specs. Formats are based on specific industries.

Selections are mostly based on numbers and expected sales. Proposers are typically too optimistic while trying to show the positive sides of the project.

(Continued)

Based on contingency and uncertainty of the project, design may need to be repeated and often require redesigns and iterations.

Strategic planning frameworks and tools are missing. Specific project types and contingency considerations are needed in project planning processes.

Requirements and specifications need to be considered in light of strategy, in addition to the standard technical details.

Selection frameworks should be based on strategic considerations, competitive advantages and business objectives, as well as specific project types and the impact of project implementation.

86

Activities (kind of work)

Product is built according to design decisions and testing to determine if it meets specifications and requirements and is ready for production. If deviation is found, a redesign decision may be needed.

The product is built in its newly established production line and is continuously tested to keep manufacturing within production tolerance. Deviations are corrected if found. Early marketing activities are initiated.

Product launch, as well as marketing and advertising campaigns, is initiated.

The product is built with continuous monitoring of customer feedback and decisions about improvements or timing for a next generation.

Phase

Build/test

Production

Commercialization

Support/improve

Table 4.1   (Continued)

Ongoing maintenance by product experts and sales support teams.

Marketing and sales forces.

Production teams with inputs from designers. Marketing and business experts are involved in early activities.

Design teams, developers or technicians and QA personnel are collaborating in the product building, assembly and testing process.

Expertise (who is involved)

Ongoing maintenance and support teams learn from customers’ experiences and respond to competitors’ products with continuous improvement and upgrades.

Marketing and distribution practices are established based on specific markets and industry.

DevOps models are applied to create an integrative and continuous process from development to operation.

The transition from design to build and test often leads to an iterative process that requires effective internal and external communication.

What is known

Technological advancements and market preferences are dynamic and lead to shorter product life cycles. More studies on industryspecific support efforts to learn from best-in-class leading companies.

More studies on industry-specific commercialization efforts and best practices.

Strategic tools for building a balance between introducing new products and maintaining production efficiency. Develop industry-dependent production practices.

Implementation may be impacted by contingency considerations with appropriate rebuilding efforts.

Future research and development needed

The converging nature of innovation and project management  87

A CONTINGENCY MODEL FOR INNOVATION/PROJECTS What Is Contingency Theory There are different types of innovations and different types of projects, and obviously, “one size does not fit all” (Shenhar, 2001). Specific types of innovations and projects have continuously occupied the minds of researchers in the two areas, often utilizing separate frameworks. However, for a joint process, it would be useful to create one model to distinguish between different kinds of innovation/projects. The appropriate theory for that is called contingency theory, and it was first introduced in the 1960s, primarily addressing organizations, rather than projects or innovations. Classical contingency theory asserts that different conditions might require different organizational characteristics and that the effectiveness of the organization is contingent upon the amount of congruence or goodness of fit between structural and environmental variables (Drazin and Ven, 1985; Lawrence and Lorsch, 1967; Pennings, 1992). Burns and Stalker (1961) were the first to suggest a distinction between incremental and radical innovation, in the context of organizations, which were characterized as either organic or mechanistic. A mechanistic organization was described as formal, centralized, specialized bureaucratic, structured by many authority levels, and maintains only a minimal level of communication. An organic organization, in contrast, was characterized as informal, decentralized, having just a few authority levels, and typically using extensive levels of communication. According to the early theorists, organic organizations would better cope with uncertain and complex environments while mechanistic organizations predominate in simple, stable and more certain environments. It took, however, several decades until classical contingency theory was extended to projects (Turner and Cochrane, 1993; Shenhar, 2001; Pich et al., 2002). We begin with innovation frameworks, then address projects and, finally, discuss a combined contingency theory for the innovation/project world. Innovation Contingency The most famous way to distinguish between innovation efforts was indeed the classical distinction between incremental and radical innovation, corresponding to the extent of change introduced (Myers and Marquis, 1969). They have also added system innovation as a third class. A similar distinction was offered later by March (1991), who distinguished between exploitation and exploration learning for technological innovation. Henderson and Clark (1990) extended the theory to four types of innovation: (1) radical innovation, which “establishes a new dominant design and, hence, a new set of core concepts in components that are linked together in a new architecture”; (2) incremental innovation, which “refines and extends an established design, where improvements occur in individual components, but the underlying core design remains the same”; (3) architectural innovation, which is based on “reconfiguration of an established system, linking existing components in a new way”; and (4) modular innovation “that changes the core design concepts of a technology”. Another dominant work is Christensen’s “Innovator’s Dilemma” (1997), which investigated the concept of disruption. Christensen observed that successful companies often continue building on their past success with existing technology in their main businesses, while

88  Handbook on innovation and project management

ignoring the threats of disruptive new technologies, eventually, at times, driving past leaders out of business. An attempt to organize the various concepts of innovation in an orderly way was introduced by Gatignon et al. (2002), who presented innovation in terms of its hierarchical position (locus) within the product (core or peripheral), its type (architectural or generational) and its characteristics (competence enhancing or destroying, and incremental or radical). Project Contingency The project management literature has been more practical in its search for classifying project types and identifying ways to manage them. For example, Turner and Cochrane (1993) have discussed the uncertainties in projects by indicating uncertainty in the market (or in the objectives) and uncertainty in the solution (or in the technology). Similarly, Pich et al. (2002) have distinguished between means uncertainty and solutions uncertainty and identified their most appropriate management systems. The lowest levels of uncertainty should be addressed by what they called planned projects, somewhat higher levels by learning projects, then parallel and finally selectionist projects. For each level, they defined the optimal planning and monitoring systems, coordination and information systems, as well as incentives. Shenhar (2001) and Shenhar and Dvir (2007) have offered a refinement to classical contingency theory and introduced a four-dimensional framework – the “Project Diamond” – for the classification of projects. The framework includes novelty, technology, complexity and pace (titled NTCP) as its major dimensions. They suggested that the Diamond Model could broaden existing frameworks by providing planning and execution guidelines to project managers on how to optimally adapt a specific management style to each project effort. Each dimension of the Diamond Model is refined into four different project types (Shenhar et al., 2016) (Figure 4.2). We show later how this model could be used for linking the innovation and project management disciplines. The novelty dimension represents how familiar the market is with the new product and its use, impacting the extent to which initial requirements can be defined. The technology dimension is determined by the newness of the technology used for developing or producing a product or, conversely, its maturity at a project’s onset. The complexity dimension reflects the level of a product’s complexity, as well as the complexity of the organizational efforts required to complete its design and production. Finally, the pace dimension indicates how acute the project’s time constraint is. Pace represents the available time frame or, conversely, the project’s urgency. Table 4.2 includes the specific project types on each of the diamond’s four dimensions. The Diamond Model instructs managers on how to adopt preferred managerial practices for each type of project (Shenhar and Dvir, 2007). Figure 4.3 presents a summary of the main implications for project management of each dimension. The impact of novelty (or market uncertainty) on project management is the ability to determine the final product’s requirements. Notable, market research is only reliable for lower levels of novelty with sufficient information on previous products. At the highest level, newto-the-world, there is less need for market research, since as experience proved: “markets that do not exist cannot be analyzed” (Christensen, 1997). The technology dimension impacts the amount of investment and time needed for developing the final product. Higher levels require more cycles of “design-build-test” and a later time

The converging nature of innovation and project management  89

Figure 4.2  The Diamond Model – a unified framework

Table 4.2  The innovation/project diamond classifications Dimension

Project types (definitions)

Novelty

1 – Derivative (Improvement) 2 – Platform (A new generation in an existing product line – e.g., new car model) 3 – New-to-the-market (Adopting an existing product to a different market – e.g., first PC) 4 – New-to-the-world (Product never existed before)

Technology

1 – A Type – low-tech (No new technology) 2 – B Type – medium-tech (Some new technology) 3 – C Type – high-tech (All or mostly new but existing technologies) 4 – D Type – super-high-tech (Project will use non-existing technologies at project initiation)

Complexity

1 – Component/material (An element or material in a subsystem) 2 – Assembly (A subsystem – performing a single function) 3 – System (A collection of subsystems – performing multiple functions) 4 – Array (System of systems – a widely dispersed collection of systems serving a common mission)

Pace

1 – Regular (Delays not critical) 2 – Fast/competitive (Time to market is a competitive advantage) 3 – Time-critical (Completion time is critical to success, window of opportunity) 4 – Blitz (Crisis project)

90  Handbook on innovation and project management

Figure 4.3  Managerial implications of the four dimensions of the diamond of design freeze. At the highest level of super-high-tech where technology does not exist at the project’s launch, a small-scale prototype must be built for testing the new technology (Shenhar and Dvir, 2007). The complexity dimension requires adopting the project’s organization, as higher levels require larger organizations, more formality, coordination and documentation. Finally, the pace dimension impacts the project’s time management. A higher pace requires higher autonomy and less bureaucracy for project teams. The highest blitz projects are often crisis projects where a pure project structure is the best and fastest solution. In the next section, we show how these guidelines relate to different kinds of innovation and how organizations could match a specific kind of innovation to the most appropriate project. A Unified Project and Innovation Contingency Framework The Diamond Model could be used early on during the front-end analysis of an innovation, even before it is approved as a formal project. It may assist teams in crystallizing the uniqueness of an innovation and selecting the optimal management approach. It could then be used later, during the remaining steps of the project. The different kinds of innovation mentioned earlier could be mapped onto the corresponding dimensions of the Diamond Model (see Figure 4.4). For example, the classical distinction between incremental and radical innovation is represented twice in this model. They are expressed by the levels of uncertainty (or newness) of the product in the market along the novelty dimension (Pisano, 2015) and by the uncertainty of the technology along the technology dimension (Rotolo et al., 2015). Derivatives and platforms on the novelty dimension stand for low levels of market uncertainty when customer needs are well-known and market research is highly useful. However, new-to-the-market and new-to-the-world represent radical market innovations, in cases when markets are still unfamiliar with the product, requirements can

The converging nature of innovation and project management  91

Technology

Array

Radical Technological Innovation

Super-High-Tech

Incremental Technological Innovation

Medium-Tech

High-Tech

Incremental Market Innovation

Radical Market Innovation

Low-Tech

System Assembly Component

Complexity Derivative Platform

New to Market

New to World

Novelty

Regular

Architectural System Innovation

Modular Innovation

Fast/Competitive

Time-Critical

Blitz

Time-paced Innovation Crisis Management

Pace

Figure 4.4  The joint framework of innovation and project management still not be written and market research is essentially useless. Instead, market trials are necessary before final requirements are determined. On the technology dimension, the two lowest levels of low-tech and medium-tech correspond to an incremental technological innovation, while the high- and super-high-tech levels correspond to a radical one. Specifically, high- and super-high-tech require using new, advanced technologies that are either new to the organization or, in extreme cases, still unavailable. With excessive uncertainty and risk, they require long development periods and testing – and particularly, at the highest levels of super-high-tech, the development of non-existent technologies as part of the project’s effort. The disruption phenomenon can also be recognized twice in this model. First, there are two types of market disruption: the lowest level is new-to-the-market, where a product has been adopted from another market into a new one, and then new-to-the-world, where no one has ever seen the product before. Also, there are two types of technology disruption: high-tech and super-high-tech, which require increasing periods of development, many design cycles and substantial market testing before a complete product is ready for delivery. The innovation literature has also addressed complexity aspects. It was typically dealing with structures and complexities of products and their components or modules, often called modular innovation (Henderson and Clark, 1990; Oyama et al., 2015). In the project world, these initiatives correspond to the component or assembly levels on the diamond’s complexity axis. Larger initiatives, often called architectural system innovations, involve developing or improving entire systems or collections of systems, and lead to higher degrees of complexity as represented by the system and array levels (Shenhar and Holzmann, 2017).

92  Handbook on innovation and project management

Finally, the pace dimension represents the importance of the available time frame for completing a project. While regular-pace projects have no time constraints, the fast/competitive level involves an extensive effort to complete a project ahead of competitors, called in innovation terms a time-based strategy (Eisenhardt and Tabrizi, 1995). The two highest pace levels are time-critical, where meeting the deadline is detrimental to success, and blitz (emergency) projects where every moment counts for getting out of a crisis. Managing Innovation/Projects in a VUCA World Today’s turbulent and competitive environment is often characterized as the VUCA world, standing for volatile, uncertain, complex and ambiguous (Barber, 1992). The VUCA world is chaotic, fast-changing, unstable and often unpredictable (Millar et al., 2018). In this world, things change fast and often, in an unpredictable way. Many things are still unknown, a large number of unexpected factors play a role and many options are still possible. The VUCA world requires future research for identifying responses to its four distinct components. Specifically, high levels of volatility may require getting ready for immediate response to change, high uncertainty may need the ability to tolerate long periods of undecided actions and deal with delayed decisions, high complexity would require higher levels of relationships for complex interdependencies and high levels of ambiguity would warrant widely open responses to unclear situations. In sum, the VUCA world requires extensive ongoing communication and collaboration, high adaptability and agility and an open culture for tolerating constant change. Additional Contingency Dimensions Additional research may also be needed to define specific areas for adapting companies’ innovation/project activities. In addition to market and technological uncertainties, possible areas for contingency may include the environment, geography, politics, culture, language or financial and economic uncertainties. Similarly, additional complexities may be investigated by looking at global networks, communication issues, standardization or local-base unique complexities. Obviously, more research would be needed to address these challenges.

THE INNOVATION/PROJECT STRATEGY What Exactly Is Strategy The term strategy (from Greek strategia – “the art of the general”) is typically considered as a specific plan to achieve long-term goals. In the traditional military context, strategy simply means how we are planning to win the war or battle. However, apart from the military, strategy is used today in many other environments, among them sports, game theory and, quite often, business. In the business context, Porter (1985) defined strategy “as the formula for how a business is going to compete”. And Mintzberg (1987) uses the five P words to describe strategy: plan, pattern, position, ploy and perspective.

The converging nature of innovation and project management  93

Most writings and studies about strategy deal with the strategy of an entire company or business. It typically relates to the common idea about how a business is competing and how it is achieving long-term competitive advantage. Over time, most companies are refining their long-term strategy to strengthen their competitive pattern. They are not changing strategy often and are recognized for their “way of competing”. For example, Apple’s strategy is highquality products, ease of use, attractive design and exceptional service, while Amazon’s strategy is offering a wide range of choices, one-click convenient ordering and quick delivery everywhere. Macrostrategy versus Microstrategy For the benefit of our discussion, we suggest making a distinction between two types of strategy – macrostrategy and microstrategy. Macrostrategy means the at-large strategy of a company or business. It is mostly stable and characteristic of the competitive pattern of a business over time. Microstrategy, in contrast, is the specific strategy of a unique product or a project that is creating this product. It is also flexible and could change more often. A product’s microstrategy is defined as the specific way in which the product is built to achieve competitive advantage over competing products (and normally designed to support the higher macrostrategy of the business or company). Microstrategy is based on a collection of properties and activities that would support the product’s business success. Typical strategies of products may exhibit a combination of advantages, such as low cost, better performance, product advantage, product aesthetics and design, advanced features, high quality, ease of use, low maintenance and compatibility with industry standards. Earlier generations of scholars were often less concerned with the business aspects of running a project and with moving from corporate strategy to project strategy (Morris and Jamieson, 2005). However, it has often been claimed that the traditional emphasis on meeting time, budget and project performance wasn’t sufficient to guarantee the organizational business objectives (Davies and Hobday, 2005; Shenhar and Dvir, 2007; Williams, 2005). Eventually, a new approach emerged, collectively called “strategic project management” (Artto et al., 2008; Cleland, 1998; Jugdev, 2004; Miller and Lessard, 2001; Shenhar, 2004). Strategic project management is based on the realization that projects are, most of the time, initiated to achieve business results (Pennypacker and Dye, 2002) and that a project’s implementation process should be better aligned with the higher enterprise strategy. This claim implies that organizations, project teams, project managers and executives must better learn how to focus project execution on achieving better business results aligned with their mother organization (Cleland, 1998; Shenhar, 2004). That realization highlighted the need to define and use a new concept - project strategy, or as we defined it, microstrategy (Artto et al., 2008; Patanakul and Shenhar, 2012). What Is Project Strategy – the Microstrategy? How to define the project’s strategy A project’s outcome, its product, could only win if it would be attractive to customers and buyers, in other words, having some competitive advantage, or sufficient value even in a noncompetitive environment.

94  Handbook on innovation and project management

Using three of the five “Ps” from Mintzberg’s model (1987), a project’s strategy will include a “perspective” (the background, the reason and the general idea), a “position” (what we want to achieve and how we will know that we have achieved it) and a “plan”, or guidelines (that is, what we need to do in order to achieve what we hope to). In simple words, a project strategy will include the following three parts: the “why”, the “what” and the “how” to create the best competitive advantage and the highest value from the project. More formally, we define a project strategy as “the project perspective, position, and the guidelines on what to do and how to do it; to achieve the highest competitive advantage and the best value from the project” (Patanakul and Shenhar, 2012). These three parts are divided into eight implementable components: business background, business objective, strategic concept, product definition, competitive advantage/value, success and failure criteria, project definition and strategic focus (see Figure 4.5). The following discussion describes these elements in more detail. The three parts of project strategy The first “P” is the perspective part of project strategy. It presents the background, the environment and the reason “why” we initiate the project, the overall objective and the concept that will guide the project’s experience. It includes the business background, the business objective and the strategic concept (what are we competing on?). The second “P” is the position that will be obtained after the project has been completed. The position part describes “what” we want to achieve once the project has been completed. It is the new “state of the world” after the project ends. The position includes the product definition, the competitive advantage/value that is created by the project and the success and failure criteria (how do we assess the project’s success?) (Shenhar et al., 2001). The third “P” is the “how” – how we are going to make this happen, i.e., the “plan” of action and the behaviour that is needed to get there. The guidelines include the project definition and

Project Strategy: the project perspective, position, and the guidelines on what to do and how to do it; to achieve the highest competitive advantage and the best value from the project

Perspective “Why”

Position “What”

Guidelines “How”

Business Background

Product definition

Project Definition

Business Objective

Competitive Advantage/Value

Strategic Focus

Strategic Concept

Success/Failure Criteria

Figure 4.5  The Structure of a project’s strategy

The converging nature of innovation and project management  95

the strategic focus (guidelines for behaviour and how to establish an environment of relentless pursuit of competitive advantage) (Poli, 2006). Summary – the strategy questions and answers Table 4.3 provides a summary of the project strategy framework in terms of the questions that each component is answering and the detailed answers.

SUMMARY Lessons and Implementation Recommendations From an implementation perspective, the combined frameworks presented in this article could serve as a management tool for helping executives and their innovation and project teams focus on the important critical aspects of an innovation effort during all phases of the effort. Here are a few recommendations. First, at the pre-approval stage, while an innovative idea is still being considered, project experts should be involved as early as possible. Executives should not assume that once they make a strategic decision, their project teams will figure it out. In addition to assessing business opportunities and expected benefits, executives must ask questions about the level of difficulty and challenge involved in the execution, as well as assess the expertise and critical resources needed to bring the idea to market. The best-fit management style should be selected, by determining levels of novelty, technology, complexity and pace, as well as other characteristics of the innovation and its required project. Combined teams should assess the implications of these characteristics on execution time, resources, challenges and the critical skills needed. In some cases, initiatives would ultimately not be approved due to higher-than-usual difficulties in their execution. Second, during the formal approval stage of the effort, a project team must coordinate with business and marketing executives to guarantee all critical aspects of the project are addressed before it is launched. At least three major aspects must be addressed clearly: the project’s strategic vision, a strong alignment and commitment between project participants and a clear execution plan that is appropriately tailored to the project’s levels of uncertainty and complexity, including resources, organization and process, as well as the right talents (Shenhar and Holzmann, 2017). The alignment should proceed through the execution phase. Innovation success depends on the ongoing adaptation of business decisions, marketing activities and execution processes and adjusting them to dynamic changes in the environment and technology. Changes may include increased resources, allocating new people or adding unplanned activities. Third, the appropriate project strategy should be selected and its components addressed carefully. Teams must be certain they are able to create real value and implement a sense of continuous pursuit of competitive advantage in their project. Despite this chapter’s recommendation for a unified model of projects and innovation, we should still recognize cases where unique models may be appropriate. Among them, we should mention some unique initiatives of exploration projects, where neither technologies nor customer requirements are known at the start of the project (e.g., Lenfle, 2008, 2012), or

96  Handbook on innovation and project management

Table 4.3  The elements of project strategy

Perspective – “why”

Position – “what”

Guidelines – “how”

Project strategy components

Questions

Details

Business background

Why are we doing the project? What is the business perspective and motivation?

Who is the customer/user? What is the need? How do we address this need? What is the business opportunity?

Business objective

What do we want to achieve?

What is the ultimate goal to be achieved after project completion?

Strategic concept

Why will the project support the company’s business strategy? What is the general strategic competitive idea?

What is the guiding strategic principle that would dominate the project’s plan and execution and will support the company’s strategy?

Product definition

What is the product that will be created or produced by the project?

What are we producing? What kind of product is it? What are the concept of operation and its major product characteristics?

Competitive advantage/value

How good is it? Why is it better? Why would the customer buy? What is the value for us?

What is the advantage to customer/ user over: - Competitors? - Previous products? - Alternative solutions? What is the product cost/ effectiveness? How would we benefit?

Success and failure criteria

What are the expectations? How to assess success? What can go wrong?

What are the success dimensions and measures? What are the major risks and their consequences?

Project definition

How do we do it? What is the project?

Project scope. Project deliverables. Project type – classification. Project leader, project team. Resources.

Strategic focus

How do we behave? What do we do to achieve CA/V? How do we create in this project the relentless pursuit of competitive advantage/value?

Guidelines for behaviour. Policy for managing and leveraging: - Company competencies. - Professional expertise. - Internal synergy. - External alliances.

The converging nature of innovation and project management  97

highly experimental medical research, where no real solutions have been offered and no clear goals have been set (e.g., Varmus, 2006). We realize that not all areas of research are yet ready to adopt the established frameworks of either project management or innovation, and they will continue exploring issues in their old-trusted ways.

CONCLUDING REMARKS AND FORTHCOMING STUDIES In conclusion, we may be moving to an interdisciplinary world, where teams require the involvement of different professions for joint solutions to modern life challenges. Future research communities are required to follow this trend and be able to study multidisciplinary and interdisciplinary problems. For this reason, our models, which tried to combine the frameworks of innovation and project management, may be useful for improved practices and future studies. This idea fits well with contemporary trends of cross-learning among fields when a single discipline is often unable to find a solution on its own. The integration of innovation and project management becomes essential for most companies. This chapter offered several lessons for future researchers as well as practitioners: since no innovation can succeed without a sound project, future studies should continue acknowledging this merge and keep studying the entire innovation and project cycles while coming up with more insights to improve our understanding of the combined process. Similarly, industry leaders should continue forming combined and multidisciplinary teams to deal with the entire process. Switching gears to another team when an initiative is moving downstream is counterproductive and inefficient. Project teams need to understand the extent of innovation that is driving their project and accordingly adjust their execution plans. Specifically, since many projects today involve new development, performed in short cycles, project managers need to know the impact of uncertainty – in technology, markets or both – on their projects and learn how to prepare and deal with it effectively. The process, diamond and project strategy models of innovation/project presented here may prove useful for future researchers as well as teams and organizations. Our models offer new ways to deal with unanswered questions, such as how to reduce the uncertainty at the onset of the process, how to organize the innovation project in the most appropriate way or how to build the best winning product for the marketplace. Modern innovations do not have to fail so often, and more value should be created from the many good ideas that have failed in the past due to weak execution. Companies could expand and invest more learning into the complex and integrative nature of their innovation/projects. They could learn how to establish innovation and project management as one combined and effective process, where joint teams are functioning together, contributing the best of their knowledge to such a complex but highly promising process. The models presented in this chapter may serve as useful management techniques for better integration and improved innovation successes.

REFERENCES Artto, K., Kujala, J., Dietrich, P., and Martinsuo, M. (2008). What is project strategy? International Journal of Project Management, 26(1), 4–12. Barber, H.F. (1992). Developing strategic leadership: The US army war college experience. Journal of Management Development, 11(6), 4–12.

98  Handbook on innovation and project management

Birch, E.L. (2006). New York City: Super-capital–not by government alone. In D. Gordon (Ed.), Planning twentieth century capital cities (pp. 269–285). London: Routledge. Burns, T. and Stalker, G.M. (1961). The Management of Innovation. London: Tavistock. Christensen, C. (1997). The Innovator’s Dilemma. Harvard Business School Press. Clark, K.B. and Wheelwright, S.C. (1992). Organizing and leading “heavyweight” development teams. California Management Review, 34(3), 9–28. https://doi​.org​/10​.2307​/41167421 Cleland, D.I. (1998). Strategic project management. In J.K. Pinto (Ed.), Project Management Handbook (pp. 27–54). San Francisco, CA: Jossey-Bass Publishers. Cooper, R.G. (2017). Idea-to-launch gating systems: Better, faster, and more agile: Leading firms are rethinking and reinventing their idea-to-launch gating systems, adding elements of Agile to traditional Stage-Gate structures to add flexibility and speed while retaining structure. ResearchTechnology Management, 60(1), 48–52. Cooper, R.G., Edgett, S.J., and Kleinschmidt, E.J. (1997). Portfolio management in new product development: Lessons from the leaders—I. Research-Technology Management, 40(5), 16–28. Cooper, R.G. and Kleinschmidt, E.J. (1986). An investigation into the new product process: Steps, deficiencies, and impact. Journal of Product Innovation Management, 3(2), 71–85. Cropley, D.H. (2006). The role of creativity as a driver of innovation. 2006 IEEE International Conference on Management of Innovation and Technology, 2, 561–565. Crossan, M.M. and Apaydin, M. (2010). A multi‑dimensional framework of organizational innovation: A systematic review of the literature. Journal of Management Studies, 47(6), 1154–1191. Davies, A. and Hobday, M. (2005). The Business of Projects: Managing Innovation in Complex Products and Systems. Cambridge University Press. Davies, A., MacAulay, S., DeBarro, T., and Thurston, M. (2014). Making innovation happen in a megaproject: London’s crossrail suburban railway system. Project Management Journal, 45(6), 25–37. Davies, A., Manning, S., and Söderlund, J. (2018). When neighboring disciplines fail to learn from each other: The case of innovation and project management research. Research Policy, 47(5), 965–979. Drazin, R. and van de Ven, A.H. (1985). Alternative forms of fit in contingency theory. Administrative Science Quarterly, 30(4), 514. https://search​.proquest​.com​/docview​/1301308224 DTI. (2003). Innovation Report. Competing in the Global Economy: The Innovation Challenge. Eisenhardt, K.M. and Tabrizi, B.N. (1995). Accelerating adaptive processes: Product innovation in the global computer industry. Administrative Science Quarterly, 40(1), 84–110. Engwall, M. (2003). No project is an island: Linking projects to history and context. Research Policy, 32(5), 789–808. Fujimoto, L. (1992). Lessons from Abroad in rural community revitalization: The one village, one product movement in Japan. Community Development Journal, 27(1), 10–20. https://doi​.org​/10​.1093​ /oxfordjournals​.cdj​.a038571 Gassmann, O. and von Zedtwitz, M. (2003). Innovation processes in transnational corporations. In L.V. Shavinina (Ed.), The International Handbook on Innovation (pp. 702–714). Oxford, UK: Elsevier Science & Technology. Gatignon, H., Tushman, M.L., Smith, W., and Anderson, P. (2002). A structural approach to assessing innovation: Construct development of innovation locus, type, and characteristics. Management Science, 48(9), 1103–1122. Gisler, M. and Sornette, D. (2009). Exuberant Innovations: The Apollo Program. Springer. Henderson, R.M. and Clark, K.B. (1990). Architectural innovation: The reconfiguration of existing product technologies and the failure of established firms. Administrative Science Quarterly, 35(1), 9–30. Jugdev, K. (2004). Through the looking glass: Examining theory development in project management with the resource-based view lens. Project Management Journal, 35(3), 15–26. Kerzner, H. (2017). Project management: A Systems Approach to Planning, Scheduling, and Controlling (12th ed.). John Wiley and Sons. Koen, P., Ajamian, G., Burkart, R., Clamen, A., Davidson, J., D’Amore, R., Elkins, C., Herald, K., Incorvia, M., and Johnson, A. (2001). Providing clarity and a common language to the “fuzzy front end.” Research-Technology Management, 44(2), 46–55. Koeppel, G. (2009). Bond of Union: Building the Erie Canal and the American Empire. Cambridge, MA: Da Capo Press. ISBN 978-0-306-81827-1.

The converging nature of innovation and project management  99

Lawrence, P.R. and Lorsch, J.W. (1967). Differentiation and integration in complex organizations. Administrative Science Quarterly, 12(1), 1–47. http://www​.econis​.eu​/ PPNSET​?PPN​= 470123613 Lenfle, S. (2008). Exploration and project management. International Journal of Project Management, 26(5), 469–478. Lenfle, S. (2012). Exploration, project evaluation and design theory: A rereading of the Manhattan case. International Journal of Managing Projects in Business, 5(3), 486–507. March, J.G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71–87. Midler, C. (1995). “Projectification” of the firm: The Renault case. Scandinavian Journal of Management, 11(4), 363–375. https://doi​.org​/10​.1016​/0956​-5221(95)00035-T Millar, C.C.J.M., Groth, O., and Mahon, J.F. (2018). Management innovation in a VUCA world: Challenges and recommendations. California Management Review, 61(1), 5–14. Miller, R. and Lessard, D.R. (2001). The Strategic Management of Large Engineering Projects: Shaping Institutions, Risks, and Governance. MIT Press. Mintzberg, H. (1987). The strategy concept I: Five Ps for strategy. California Management Review, 30(1), 11–24. Morris, P.W.G. and Jamieson, A. (2005). Moving from corporate strategy to project strategy. Project Management Journal, 36(4), 5–18. Myers, S. and Marquis, D.G. (1969). Successful Industrial Innovations. Washington, DC: National Science Foundation. Oyama, K., Learmonth, G., and Chao, R. (2015). Applying complexity science to new product development: Modeling considerations, extensions, and implications. Journal of Engineering and Technology Management, 35, 1–24. Patanakul, P. and Shenhar, A.J. (2012). What project strategy really is: The fundamental building block in strategic project management. Project Management Journal, 43(1), 4–20. Pennings, J.M. (1992). Structural contingency theory: A re-appraisal. In B.M. Staw and L.L. Cummings (Eds.), Research in Organization Behavior, XIV (pp. 267–309). Greenwich: JAI Press. Pennypacker, J.S. and Dye, L.D. (2002). Project Portfolio Management and Managing Multiple Projects: Two Sides of the Same Coin. New York: Marcel Dekker. Pich, M.T., Loch, C.H., and de Meyer, A. (2002). On uncertainty, ambiguity, and complexity in project management. Management Science, 48(8), 1008–1023. https://doi​.org​/10​.1287​/mnsc​.48​.8​.1008​.163 Pisano, G.P. (2015). You need an innovation strategy. Harvard Business Review, 93(6), 44–54. PMI. (2017). A Guide to the Project Management Body of Knowledge (PMBOK guide) (6th ed., Vol. 2). Project Management Institute. Poli, M. (2006). Project Strategy: The Path to Achieving Competitive Advantage/Value. Stevens Institute of Technology. Porter, M.E. (1985). Competitive Advantage: Creating and Sustaining Superior Performance. New York: FreePress. Rotolo, D., Hicks, D., and Martin, B.R. (2015). What is an emerging technology? Research Policy, 44(10), 1827–1843. Salerno, M.S., de Vasconcelos Gomes, L.A., da Silva, D.O., Bagno, R.B., and Freitas, S.L.T.U. (2015). Innovation processes: Which process for which project? Technovation, 35, 59–70. Schumpeter, J.A. (2010). Capitalism, Socialism and Democracy. Routledge. Shenhar, A. (2001). One size does not fit all projects: Exploring classical contingency domains. Management Science, 47(3), 394–414. https://doi​.org​/10​.1287​/mnsc​.47​.3​.394​.9772 Shenhar, A. (2004). Strategic Project Leadership® toward a strategic approach to project management. R&D Management, 34(5), 569–578. Shenhar, A. and Dvir, D. (2007). Reinventing Project Management: The Diamond Approach to Successful Growth and Innovation. Harvard Business Review Press. Shenhar, A., Dvir, D., Levy, O., and Maltz, A.C. (2001). Project success: A multidimensional strategic concept. Long Range Planning, 34(6), 699–725. https://doi​.org​/10​.1016​/S0024​-6301(01)00097-8 Shenhar, A. and Holzmann, V. (2017). The three secrets of megaproject success: Clear strategic vision, total alignment, and adapting to complexity. Project Management Journal, 48(6), 29–46. Shenhar, A., Holzmann, V., Dvir, D., Shabtai, M., Zonnenshain, A., and Orhof, O. (2020). If you need innovation success, make sure you’ve got the right project. IEEE Engineering Management Review, 48(1), 113–126.

100  Handbook on innovation and project management

Shenhar, A., Holzmann, V., Melamed, B., and Zhao, Y. (2016). The challenge of innovation in highly complex projects: What can we learn from Boeing’s Dreamliner experience? Project Management Journal, 47(2). https://doi​.org​/10​.1002​/pmj​.21579 Turner, J.R. and Cochrane, R.A. (1993). Goals-and-methods matrix: Coping with projects with ill defined goals and/or methods of achieving them. International Journal of Project Management, 11(2), 93–102. https://doi​.org​/10​.1016​/0263​-7863(93)90017-H Utterback, J.M. (1971). The process of technological innovation within the firm. Academy of Management Journal, 14(1), 75–88. Varmus, H. (2006). The new era in cancer research. Science, 312(5777), 1162–1165. Verganti, R. (1997). Leveraging on systemic learning to manage the early phases of product innovation projects. R&D Management, 27(4), 377–392. Verworn, H., Herstatt, C., Verworn, Dipl.-I.B., Cornelius Herstatt, P., and Verworn, B. (2001). The “Fuzzy Front End” of Innovation. www​.tu​-harburg​.de​/tim Williams, T. (2005). Assessing and moving on from the dominant project management discourse in the light of project overruns. IEEE Transactions on Engineering Management, 52(4), 497–508.

5. It’s all a bit fuzzy? The front-end in project and innovation management Michael A. Lewis, Joseph W. Harrison and Jens K. Roehrich

INTRODUCTION It is almost axiomatic that project “front-end” (PFE) activities are critical to project performance (Morris, 1987; Miller and Hobbs, 2005; Samset, 2010). A widely cited World Bank study (1996) of 1,125 major projects suggested strong support for the value of a rigorous PFE when it found that 80 per cent of projects with a satisfactory “quality at entry” were successful. At the same time, the finding that only 35 per cent of those with an unsatisfactory quality at entry achieved success also confirmed that many projects proceed irrespective of PFE evaluations – and that they are far from accurate. The general message, that “improved” frontend management is likely to pay off in a wider life cycle perspective (Miller and Lessard, 2000), has meant that the PFE has been a sustained focus for project practice and scholarship (Williams et al., 2020; Morris, 20161). In short, the PFE exists before project boundaries are crafted at a time where there are “governing processes at play” but, typically, no “plans nor formal contracts to govern the actions and relationships of the parties involved” (Hellström et  al., 2013, 712). Small wonder that such temporal and material ambiguity, paradox even (Samset and Volden, 2016), has led to confusion and tautology. This has, in turn, created the impression that it is under-researched (Samset and Volden, 2016) despite a recent PFE literature review (Williams et al., 2019) identifying 524 related papers. This level of interest shows no sign of abating (e.g. Babaei et al., 2021). So, what is the intent of this chapter? There is clearly scope for further PFE study but here, rather than revisit the excellent review work already completed, we build on the project studies tradition of knowledge creation at field boundaries by engaging with the adjacent innovation/ new product development (NPD) literature and, more specifically, the front-end of innovation (FEI) literature as a comparative lens for (re-)considering the meaning and management of the PFE. This is another opportunity to bridge the innovation and project management fields that, as Davies et al. (2018) note, have long been (artificially?) separated, with complex, sometimes conflicting relations. There are many similarities between the PFE and the FEI, the very first phase of the NPD process that starts with the discovery of an opportunity or a raw idea for product innovation (idea-generating: Van den Ende et al., 2014) and ends when the GO decision is made to develop a new product. (Eling and Herstatt, 2017, 864, emphasis added)

Early work suggested that the FEI was crucial for innovation success (Cooper and Kleinschmidt, 1987; Cooper, 1988) with later studies confirming that FEI effectiveness can significantly influence the likelihood of later success for innovation projects (Khurana and Rosenthal, 1997; Backman et al., 2007). Given the subsequent projectification (Midler, 1995) 101

102  Handbook on innovation and project management

of NPD, frontloading – “a strategy … to improve development performance by shifting the identification and solving of [design] problems to earlier phases of a product development” (Thomke and Fujimoto, 2000, 132) – was widely perceived to be a best practice. Markham (2013) observed that product performance – time to market, market penetration and financial performance – was positively associated with FEI activities – including the use of a formal front-end process, integrating marketing/R&D (cf. Moenaert et al., 1995), concept development work and the presence of a champion. Jordan et al. (1988) argued that 15 per cent of time and resources should be spent on front-end work, Miller and Lessard (2000) suggested up to 35 per cent and more recent research suggests that as much as 50 per cent of total innovation development time is attributable to FEI (Jensen, 2017). Although this categorical distinction is made between FEI and standard NPD practices (i.e. the FEI is different and so should be managed differently) it remains, like PFE, ambiguous in its details. To capture this, Reinertsen and Smith (1991) applied the term fuzzy to this indistinct, informal, unstructured, chaotic (O’Brien, 2020) phase “before a project enters formal development” (Frishammar et al., 2016, 179). The chapter is structured as follows. We begin by summarizing the core elements of extant PFE and FEI studies. Then, we compare them to identify additive insights and unresolved issues. The final section brings together our discussion by addressing limitations and reflects on the challenge of “fuzziness” that prompts avenues for fruitful further investigations.

THE FRONT-END? As a combination of nouns, front and end suggest ideas related to the forward-facing part of anything, and the limit or last part of something, language that brings ideas of “boundaries” strongly to mind (e.g. crossing into the “determinate” project phase [Winch, 2014]). Moreover, the idea of the front is often used synonymously with a more temporal perspective – the early or initial clock time of a project – the beginning (Lundin and Söderholm, 1995). This is not a trivial conceptual challenge; the beginning of things has long been a source of scholarly fascination. In his De primo et ultimo instant (1320?) for example, scholastic philosopher and logician Walter Burley developed Aristotle’s work (in book VIII of The Physics, 4th century BC) and proposed an elaborate classification of different kinds of beginning and ceasing. Likewise, the notion of fuzziness is suggestive of what anthropologists call liminality (from the Latin līmen, meaning “a threshold”) in descriptions of rites of passage. During liminal periods of all kinds, social hierarchies may be reversed or temporarily dissolved, continuity of tradition may become uncertain and future outcomes – once taken for granted – can be thrown into doubt. In addition to (or absence of?) a more profound philosophical debate, there is also basic confusion over terminology and reflections of different points of view (and units of analysis). The Project Front-End (PFE) In their comprehensive review of the PFE literature, Edkins and Smith (2012) found no real agreement on any specific definition but did note, intriguingly, that despite a lack of clarity about the focal phenomenon, there is agreement (and evidence) that it was one of the primary points where strategic success or failure for the project is set. As Williams et al. (2019) rightly

The front-end in project and innovation management  103

stress in their own “what is the front-end” writing, the PFE’s definition is inextricably bound up with the definition of what a “project” is.2 The PFE is identified as the greatest opportunity for value creation (Artto et al., 2016) and by extension setting up value appropriation, and frequently, axiomatically even, where the seeds of failure are sown (Morris, 2013). It is where the “project will typically lock in many aspects of what will be the final project configuration” (Scott and Levitt, 107). The PFE is “where” most aspects of the project will be “frozen” (or at least strict areas of measurements/acceptance will be determined) as key requirements and taken forward into execution. Arguing that the PFE is where complexity and uncertainty are high(est) and information most limited, Williams et al. (2019) offer an interesting figure (Figure 5.1) which presents the PFE in terms of the relationship between the permanent and temporary organizations. Critically, it makes clear, at least by implication, that the project “bookends”, whilst both critical to overall value creation, are very different in character and composition. Remember the now classic project management case of Heathrow Airport Terminal 5 moving from a very successful (in terms of time, cost, quality and wider learnings) project into a “national disaster” at opening with “cancellation of numerous flights and thousands of lost bags requiring manual sorting before being returned to their owners” (Brady and Davies, 2010, 151). Back to the project front-end, Williams et al. (2019) side-step the need for a specific definition by listing instead those “developments” that need to occur “before” a project starts and that by inference must, in at least some fashion, constitute some aspects of the “front-end”. Adapting their summary, the PFE is where: 1. Initial ideas emerge, raising issues such as where the idea comes from (e.g. a powerful actor), what it is based on (e.g. standard solutions), whose interests it would serve, who would pay for it, how it is situated within a wider strategy/project portfolio, etc. 2. Underlying problems and needs are analysed and contextualized and complexity becomes clearer. A key part of this is revealing and clarifying stakeholder preferences and incentives, either through deliberate or emergent processes.

Source:   from Williams et al., 2019.

Figure 5.1  PFE in relation to permanent and temporary organizations

104  Handbook on innovation and project management

3. Initial estimates of costs and benefits are made – although these will be revised as different conceptual alternatives are considered. The focus is often on the final cost estimate (the budget) and is a key arena for the manifestation of optimism bias and strategic misrepresentation. There is, by definition, limited essential information as the project is still prospective, and to varying degrees (depending on project type) ill-defined. By corollary, because uncertainty is at its highest, there will be an abundance of irrelevant (and uncertain, judgmental, etc.) information – some of which may be more precise and detailed than (subsequently) essential information. There appear to be some distinct processual characteristics (from ideation, via clarification of concepts, to greater formalization) where the project “foundation is laid” but they stress that it is far from linear. In their influential discussion of the challenges facing public investment projects, Samset and Volden (2016, 311), point out that recognizing the importance of the front-end decision-making phase is a crucial part of strong project governance because “many … problems can be interpreted in terms of deficiencies in the analytical or political processes preceding the final decision to go ahead”. Detailing the Norwegian Ministry of Finance’s mandatory quality-at-entry gates for large public investment projects, they offer a similar model of the (major project) PFE, reviewing (a) the conceptual solution (“before” any political executive decision to start the pre-project) and (b) the cost and steering frames (before the project is submitted to Parliament for approval and funding). The Fuzzy Front-End of Innovation The growth of practical interest (“executive anxiety” [Harvey et  al., 2015]) and scholarly research into the FEI has been a consistent theme for more than 30 years (Evanschitzky et al., 2012). Eling and Herstatt (2017) in their FEI Special Issue identified 85 studies published in the Journal of Product Innovation Management3 (JPIM) since the first issue in 1984. The FEI refers to the set of activities used to identify and screen viable candidates for new product development (Koen et  al., 2001). Various attempts have been made to define what Cooper (1996) called the “up-front homework” of NPD and lots of different terminology has been used, including “early”, “idea”, “discovery” or “pre-development” stage/tasks. More specifically, Koen et al. (2001), like many/most other authors,4 define the FEI in terms of its activities. They propose a model, built around the classic change management “engine” (2001, 49) of senior and executive-level management support, that highlights five interacting elements: 1. Opportunity identification. Driven by the short- and/or long-term goals of the business, this is a formally and informally creative process. 2. Opportunity analysis. The iterative process of assessing opportunities; to give a sense of the specificity of this element, practices like competitive intelligence and trend analyses are proposed. 3. Idea genesis. The process where ideas are “built upon, torn down, combined, reshaped, modified and upgraded” (Koen et  al., 2001, 50). This still essentially creative element is where greater specificity is advocated, via direct customer/user contact and ties with cross-functional teams, as well as collaboration with other companies and institutions. The output is typically a more completely developed description of an idea or product/ service concept.

The front-end in project and innovation management  105

4. Idea selection. Formalized project selection and resource allocation may be difficult due to limited information and understanding at this point but selection (including via financial return) in the FEI can be considered analogous to an option portfolio or more simply, a “betting process” (Reinertsen, 1999). 5. Concept (and technology) development. Koen et al. (2001) describe this as the most formal stage but note that the formality of this business case activity will vary according to the nature of the opportunity (e.g. new market, new technology and/or new platform). Koen et al. (2001) stress that this is an iterative process, presenting a circular shape for the front-end elements, later echoed in Cooper and Kleinschmidt (2007) who argued that keeping a flexible and scalable set of possible options “open” was vital to innovation success.

CONNECTED THEMES As well as related definitional challenges, and – despite any consequential ambiguity – the shared (axiomatic?) assertion that the front-end “really matters” in terms of ultimate performance, other connections are clear from reading the two literatures side by side. Both, for example, are heavily influenced by normative questions of how to use different technologies and methods to improve (e.g. to go faster [Saff and Ernst, 2003] or to better share knowledge [Akbar and Tzokas, 2012]) in this critical phase. In this section, we explore three areas where cross-reading adds insights for scholars and practitioners alike. Process The PFE and FEI both give a significant role to (stage) gates or reviews as critical elements of the process (Ulrich and Eppinger, 2004). There have been many attempts, since the description of best practice methodology implemented at AlliedSignal and Alcor (Smith et al., 1999), to define formal FEI processes. Stage Gate™ models, for example, have been expanded (Cooper and Kleinschmidt, 1986; Cooper, 1990) to include consideration of the stages before the stages (Gate 0, pre-Gate 05, etc.) and address more ambiguous issues such as ideation and technological uncertainty (Cohen et al., 1998). We summarized one of the most sophisticated, by Koen et  al. (2001), in the second section. Gaubinger and Rabl (2014) critique Cooper’s (1990) Stage-Gate Model and Khurana and Rosenthal’s (1997) three-phase front-end model for lack of flexibility because of their linear approach and lack of feedback loops. Others agree that FEI tasks are unlikely to occur in a sequential manner (Griffin et al., 2012) but have suggested alternative formalizations. Eling et al. (2014), for example, note that FEI tasks are like the steps of a general creativity process: (1) problem identification and preparation; (2) problem-solving or idea generation (incubation and illumination); and (3) solution verification and implementation (Wallas, 1926; Amabile, 1983; Lubart, 2001). On the other hand, more iterative approaches such as the new concept development (NCD) model we described in the second section now exist. Koen et al. (2001) recognize idea generation as iterative and unstructured (Pereira et al., 2017), often cutting across multiple phases. Such models are not deterministic of course; Cooper’s later models are centred around what he labels “fuzzy gates”, such that tasks associated with subsequent stages can be carried out prior to a gate decision. Given the FEI setting, an associated portfolio decision includes the

106  Handbook on innovation and project management

allocation of resources and relative risks to different projects with implications for the range of gates that only have to be passed at certain process stages. Koen et al. (2001) see refinement and screening, forms of “information processing” (Reid and De Brentani, 2004) as key to the FEI (Griffiths-Hemans and Grover, 2006). Martinsuo and Poskela (2011) and various authors have generated large lists of quantitative/qualitative evaluation and selection methods found in practice and research, including question lists (Hall and Nauda, 1990; Cooper et al., 2002), scoring models (Henriksen and Traynor, 1999) and analytic hierarchy processes (Calantone et al., 1999; Englund and Graham, 1999) as well as various mathematical models (Loch et al., 2001). Contrasting private and public PFEs, it is important to note that governments often embrace the idea of public–private partnerships (PPPs) on the basis that the bundling effects of bringing together the financing, designing, constructing and operating parts (Grimsey and Lewis, 2005; Barlow et al., 2013) will secure better value for money than traditional public procurement options. Relatedly, there is some discussion of the benefits that accrue from the relatively enhanced capabilities that many industrial firms have for ex-ante (forecasting) and ex-post (sales, user satisfaction, etc.) information processing (evaluation). Ultimately, as Christiansen and Varnes (2008) found, in practice managers are rather flexible in how they use methods and interpret such evaluations (Loch, 2000). This is unsurprising given that the implementation of useful and flexible process models – Cooper’s (1994) third-generation model offers a stagegate process with flexible gates and fluid stages – is likely to be more difficult than those with simple flows and specific recommended actions for employees. Interestingly, Reid and De Brentani (2004) differentiated between early-stage and latestage FEI processes and argued that the process differs for incremental and radical innovation (cf. Koen et al., 2014a). They proposed a model of the fuzzy front-end for discontinuous innovation in terms of boundaries to be crossed, the roles played at these “interfaces” by key individuals and the general flow of information. Although this model predates much of the subsequent open innovation (OI) literature (e.g. Dahlander and Gann, 2010), the movement of unstructured information across the boundary between the environment and the organization is clearly the “front of the front”. Figure 5.2 is an adaptation of this model that clearly

Source:   based on Reid and De Brentani, 2004, 178.

Figure 5.2  The fuzzy FEI for discontinuous innovation

The front-end in project and innovation management  107

illustrates how the “interface between the organization and a commitment to a specific project” (Reid and De Brentani, 2004, 181) is seen as the end point of the fuzzy phase. Reflecting on processual (time and tempo) concerns raises an interesting point of distinction between FEI and PFE. Much of the PFE literature emphasizes spending more time (and resources) – frontloading – on this phase, in part, reflecting the assumed temporary and oneoff nature of much project work (cf. Stjerne and Svejenova, 2016). In contrast, the permanence/embeddedness and repetition (cumulative learning?) associated with organizational innovation have led to discussions of either greater speed/less time at the FEI or even abandonment of this stage-based conceptualization. For example, developments such as platform strategies (Beaume et  al., 2009), have significantly changed the way firms think about the innovation process and, correspondingly, the meaning and management of the FEI. Analysis of the widespread industrial use of dedicated, semi-autonomous advanced engineering units, for example, concludes that they are not necessarily working on exploration activity before NPD (Maniak et al., 2013, 123), but rather supporting innovation/integration as a continuous process, a tangible manifestation of what Marsh and Stock (2003) called an “intertemporal integration” perspective. People Building on this discussion of boundary-spanning roles, there are many studies on the characteristics and behaviours of individuals in the FEI (e.g. Reid and De Brentani, 2004; Salter et al., 2015). If FEI work is (more) creative and nondeterministic than other NPD work then the requisite skills, capabilities and personalities even are likely to be different. Reid and De Brentani (2004), for example, highlighted three (indistinct?) roles critical in the front-end of discontinuous innovations: “boundary spanners”, “gatekeepers” (cf. Macdonald and Williams, 1994) and “pattern recognisers” (cf. Song and Montoya-Weiss, 1998). There are also myriad questions about team and group structure. For example, if an opportunity is worth exploring, FEI models often argue small teams should be assigned to investigate (Kim and Wilemon, 2002), most effectively by combining skills in market (Montoya-Weiss and O’Driscoll, 2000), competitive (Bacon et al., 1994) and technological (Verworn, 2006) analysis. In large organizations with an innovation portfolio, the team should also include skills to determine fit with existing business plans (Khurana and Rosenthal, 1998). Schmidt et al. (2009) in a survey of middle managers involved in NPD found that review proficiency (i.e. proficiency in using market, technical and financial criteria) at the idea screening gate was positively associated with new product performance at the company level. Similarly, Edkins et al. (2013, 79) found a wide range of individuals and team structures involved in the PFE. They highlight how the need to deal with “diversity of input whilst managing a fluid process and answering to the situational governance” likely requires a different managerial approach from that of the prototypical execution-orientated PM and this should lead to the appointment of managers who have a breadth of skills, including excellent interpersonal skills, that span “not only project management, but also the sponsor’s business and the key players and factors impacting from the external environment”. This normative recommendation aside, they recognize that finding and placing such people in PFE roles is often extremely difficult, given the uncertainties involved (including the probability of any individual project not going ahead) and the corresponding psychological and social pressures (Williams and Samset, 2010). There will be an elevated role for forming, shaping and giving voice to

108  Handbook on innovation and project management

goals – establishing and “selling” a vision – and motivating and influencing others to follow in the realization of that vision – doing what needs to be done to fill out that vision and deliver. There is also behavioural project research, stressing that projects are carried out by human actors, with potentially conflicting interests and difficult personalities (Goldratt, 1997; Maylor, 2001; Clegg and Courpasson, 2004) and, as Stingl and Geraldi’s (2017) structured literature review highlights, it addresses a wide range of PFE-associated issues, including “gold plating” or over-specification (Shmueli et al., 2015), escalation of commitment (Keil et al., 2000; Du et al., 2006; Jani, 2008, 2011; Hällgren, 2010; Martinsuo et al., 2013; Meyer, 2014) and over-optimistic6 planning and forecasting (Kutsch et al., 2011; Son and Rojas, 2011; Flyvbjerg, 2014). In one of the very few studies to consider the behavioural impact of this project phase, Long et al. (2020) conclude (from experimental work) that sunk cost bias dominates later, with status quo bias and gain-seeking preferences more important at the beginning of a project. Networks The role of suppliers in the front-end is another shared concern. Based on repeated observations in many industry sectors but particularly the automotive industry (Dyer, 1996a; Caputo and Zirpoli, 2001), supplier involvement in the FEI is associated with reduced development cost and lead time, improved product quality, easier and earlier access to innovative technologies and reduced opportunistic behaviour of suppliers (Primo and Amundson, 2002). Dyer (1996b) labelled this “pre-sourcing”, choosing suppliers early in the (vehicle’s) concept‐development stage and giving them significant, if not total, responsibility for designing a given component or system. FEI research has noted the importance of supplier evaluation (technical and financial) as a necessary precursor to successful early integration and collaboration (Chen et  al., 2006). There have been similar developments in the PFE, unsurprisingly, given the aforementioned auto-centred discussions, often linked to ideas of lean project delivery7 (Mesa et al., 2019) – for example, attempts in the construction industry to introduce a contractor’s expertise and advice much earlier in the project lifecycle, so-called early contractor involvement (ECI), than has traditionally been the case (Mosey, 2009). There have also been more pessimistic reflections. Winch (2013) proposed a process model of strategic misrepresentation in projects whereby a façade of performance optimism could be maintained by, for example, scapegoating contractors. The role of suppliers also raises interesting practical – e.g. which tools to support cross‐ company coordination (Cigolini et al., 2004) – and conceptual questions about the successful transfer of novel knowledge across organizational boundaries. For example, numerous studies find that these knowledge collaborations are informal, even when crossing organizational boundaries. This reinforces the significant role of (social) network characteristics and performance (Phelps et al., 2012). Interestingly, both “weak” and “strong” social ties have been identified as important for idea generation (Van den Ende et al., 2014; Gupta and Maltz, 2015). For example, in their analysis of six collaborative research projects (CRPs) with “suppliers” such as universities working at the front-end of radical innovation, Takahashi et al. (2018) found that relational (tie strength) and structural characteristics (network range) of the collaborative network are important determinants of knowledge transfer. A surprising finding in their study is that communities of practice (networks of knowledge experts who are not members of the team) are as important as teams in FEI success, which “points to the importance of effective collaboration outside the team” (Koen et al., 2014b, 27).

The front-end in project and innovation management  109

IT’S ALL (STILL) A BIT FUZZY? Having reviewed key defining characteristics of the front-end, in this section we turn to some of the ongoing challenges, pragmatic and conceptual, in considering the front-end. Formalization The conflict between creativity and systematization (Verworn and Herstatt, 1999) is an enduring one in both the project and innovation management worlds. Since Quinn (1985) talked of “controlling the chaos” and Brown and Eisenhardt (1998) highlighted the need for a “dissipative equilibrium” between chaos and bureaucracy, the innovation management world has sought the ideal regime that balances formal and free exploration. The interest in FEI is partly a consequence of the widespread adoption of formalized new product development (NPD) and innovation processes. Koen et al. (2001) in their (definitive sounding) “Providing clarity and a common language to the ‘fuzzy front-end’”, make this comparison explicit. What comes before the “prescribed set of activities and questions to be answered” during NPD is, by comparison, “chaotic, unpredictable, and unstructured” (Table 5.1). In other words, FEI, like PFE, is in large part defined by what it is not. Such an apophatic process may offer some insights, but it leaves significant questions unresolved. For example, what is the appropriate balance between flexibility and creativity (e.g. weakly defined processes and targets) on the one hand and structure and bureaucracy (e.g. welldefined processes and specific targets) on the other? Van der Duin et  al. (2014) observed formal FEI processes leading to both efficient (e.g. nudge to complete all relevant activities), and inefficient (e.g. pressure towards unnecessary/overanalysed) outcomes. Too much structure kills creativity, while too little affects other performance attributes (Gassmann et  al., 2016). Kagan et al. (2017), for example, found that teams perform worse when they can decide when to transition from ideation to execution in NPD projects. Herstatt and Verworn (2007) stressed the importance of a situation-appropriate balance – incorporating wider project and Table 5.1  Comparing FEI and “normal” NPD projects Fuzzy FEI

NPD project

Nature of work

Experimental, often chaotic. Difficult to plan eureka moments.

Structured, disciplined and goaloriented with a project plan.

Commercialization

Date unpredictable.

Definable.

Funding

Variable. In the initial phases, many projects may be “bootlegged”, while others will need funding to proceed.

Budgeted.

Revenue expectations

Often uncertain. Sometimes done with a great deal of speculation.

Believable and with increasing certainty, analysis and documentation as the product release date gets closer.

Activity

Both individual and team in areas to minimize risk and optimize potential.

Multi-functional product and/or process development team.

110  Handbook on innovation and project management

contextual factors – between structured processes and sufficient room for creativity. Similarly, Kock et al. (2015) concluded that increased FEI performance is associated with a balance of process formalization, ideation strategy and creative encouragement. Eling and Herstatt’s (2017) review suggested some fascinating “open” questions regarding the formalization of FEI. For example, the literature does not offer many insights on how to formally organize and manage the FEI for systemic innovations (which only generate value if accompanied by complementary innovations in the wider ecosystem and are thus highly interdependent [Takey and Carvalho, 2016]). Indeed, even the definition of formalization remains vague. For example, there is a limited distinction made between the formalization of the whole FEI process (e.g. Kock et al., 2015), the formalization of distinct FEI activities (e.g. Martinsuo and Poskela, 2011) and the application of specific formal methods or tools (e.g. Seidel and Fixson, 2013). Boulding et al. (2017), for example, show that the framing of review points (i.e. explicitly discussing the option of abandonment in a future review) can lead to more frequent/appropriate project abandonment decisions, but the recent Long et al. (2020) study suggests that the conventional advice that “a higher level of monitoring may curb escalation” (Schmidt and Calantone, 2002, 114) could be wrong and that fewer reviews may lead to better abandonment decisions. Relating this to the PFE, it has been found that the logic that underpins stage gate evaluations can lead to a kind of inflexibility that will have negative effects, especially on exploratory projects that have the function of preparing strategic disruptions (Christensen et  al., 2008). Some authors compare this front-end challenge to the so-called “valley of death” (Markham et  al., 2010) or chasm (Moore and McKenna, 1999), faced by innovations that must navigate formal development gates to reach real customers/markets. The consequence is not always that innovative ideas fall at overly harsh gates but that they are also distorted or downgraded. PFE concerns about strategic misrepresentation, the “deliberate use of misleading or false information for political purposes or agency issues” (Pinto, 2014, 378), are clearly related, but with different consequences. In part, this reflects a difference in classification, between a permanent organization launching multiple innovation projects and the temporary organization delivering a “one-off” transformation. In this setting, once a project is “started” it is more likely to continue receiving funds, and then the PFE becomes a critical juncture where strategic misrepresentation can flourish, especially if normalized (i.e. not seen as unethical), driven by a range of factors including self-interest (opportunism), asymmetrical information, differences in risk preferences and time horizons and vague accountability (Flyvbjerg et al., 2009). Wachs (1989) discussed how the most effective planner is sometimes the one who can cloak advocacy in the guise of scientific or technical rationality. In contrast with the perfected process settings described in much FEI work, Pinto (2014) identified (commonplace) dysfunctional project environments as encouraging strategic misrepresentation. In such environments, “deviation” is “normalized” and dysfunctional behaviours like systematic overpromising become the only “realistic” behaviours. Uncertainty and Equivocality Uncertainty reduction is explicit in nearly all front-end discussions; firms/projects/people react to a perceived level of environmental change and uncertainty by gathering more information.

The front-end in project and innovation management  111

Uncertainty is defined as an exogenous variable that describes the situation of missing information at the front-end – an environmental circumstance that managers cannot control (Zhang and Doll, 2001; Song et  al., 2007). This definition is in line with that of Galbraith (1974) and with information processing theory (IPT), the difference between required and available information, and advocates for firms/projects/people to reduce information asymmetry. Thus, the more “radical” a project is, the more uncertainty there is in the early stages (Verworn et al., 2008). Geraldi and Adlbrecht (2007) termed this “complexity of faith”, requiring project managers to act as “priests”, convincing the team and stakeholders to have faith in the project (Waterman and Peters, 1982), but not necessarily be closed to criticism (March, 2006). Examples from NPD include Tatikonda and Rosenthal’s (2000) article on task uncertainty and Shenhar and Dvir’s (1996) typology of projects based on technological uncertainty and system scope. Little (2005) applied this combination to IT projects, and Dietrich (2006) applied it to organizational change. Much of this work has focused on undoubtedly “fuzzy” questions such as product definition (a proxy for uncertainty reduction via processual work to better understand technical properties), development time, costs, market, risk and organizational fit (Kim and Wilemon, 2002). Arguably less attention has been given to the equally important concept of equivocality (another key concept of IPT), although it is a defining characteristic of many front-ends (Burström and Wilson, 2018) and has different consequences for practice. Equivocality means ambiguity, the existence of multiple and conflicting interpretations about a situation and/or information available to actors (Weick, 1979, Daft and Macintosh, 1981). High equivocality, often the result of complicated settings, “presumes a messy, unclear field and an information stimulus that may have several interpretations” (Daft and Lengel, 1986, 554). There will be ambiguity in goals (Turner and Cochrane, 1993; Williams and Samset, 2010) since “the idea of a single, clear goal is at odds with the reality” (Linehan and Kavanagh, 2006, 6) and there will be a lack of clarity on which issues are most relevant to the core task(s). This will typically manifest itself in the different and potentially conflicting interpretations of the same information among team members. A certain level of equivocality can be beneficial for enhancing creativity and preventing early closure, but most argue that this needs to be reduced if a viable (NPD) project is to proceed. For instance, building on IPT, the study by Aben et al. (2021) investigated the use of contractual and relational governance mechanisms to reduce information uncertainty and equivocality. However, both governance mechanisms are often only present in later innovation or project phases and cannot be relied on in the front-end. Youker (1999) concluded that lack of agreement on project objectives was one of the biggest problems facing international development projects. The same analysis was repeated on a sample of 17 large public investment projects in Norway (Andersen et al., 2014). Like Carlile’s (2002) model of knowledge boundary spanning, approaches to reducing equivocality should enable debate, clarification and enactment, rich communication for information processing rather than “just” data provision (Daft and Lengel, 1986). Rizova et  al. (2018) used social network analysis to understand how technical advice and friendship ties affect equivocality in project teams in the FEI. Their findings suggest that while high density in projects’ technicaladvice network is likely to reduce equivocality, high density in projects’ friendship network is likely to increase it. In earlier work, Frishammar et al. (2010) suggested that a reduction in effective uncertainty and equivocality was associated with successful PFE but that, more

112  Handbook on innovation and project management

interestingly, the negative consequences of equivocality may be more critical to PFE performance than the consequences of uncertainty. They also conclude that sequential uncertainty and equivocality reduction are more effective. In other words, if organizations can react to equivocality with the wrong kind of formalization, equivocality will persist in any meaningfully complex project and, consequently, more improvised adaptive behaviours (functional and dysfunctional) will co-exist. Consider the case of large-scale projects, often termed megaprojects (Babaei et al., 2021), with their messy combination of policy work and legislation, budgetary bargaining between elected officials and departments, negotiations with local government, agencies, pressure groups, etc., together with national and international firms looking for work (Flyvbjerg, 2014; Scott and Levitt, 2017). Interaction and interdependence among heterogenous actors come with diverging commitments to “collective” goals (Doz, 1996; Gulati et al., 2012). One obvious manifestation of this divergence can be found in the (sometimes) decades it takes before the various actors are ready (often following judicial and quasi-judicial intervention) to endorse a megaproject. It is well understood that divergent, self-interested (Gil and Baldwin, 2014) actors can hold up any project process (Morris, 1994; Miller and Lessard, 2000), making their support conditional on, for example, additional investment but, more specifically, this makes it very difficult to control initial project scope/budget. Moreover, the longevity of megaprojects can further exacerbate this “paradox of perverse incentives” (Samset and Volden, 2016; Welde and Odeck, 2017), ultimately creating the conditions for a version of the so-called “tragedy of the commons”.

Contingency Contingency plays a significant and under-discussed role in PFE and FEI. Classical theory (Burns and Stalker, 19618) suggests different external conditions require different organizational characteristics, and that effectiveness is therefore contingent upon the fit between structural and environmental variables (Lawrence and Lorsch, 1967; Drazin and Van de Ven, 1985; Pennings, 1992). For example, Koen et al. (2014a, 2014b) surveyed 197 large, US-based companies using their “new concept development” model and found organizational attributes accounted for 53 per cent of front-end performance, and team-related attributes accounted for 24 per cent. Evident from this is the need to differentiate between organization/project/ people-related archetypes (Lundin et al., 2015). In Table 5.2 we adapt Müller and Turner’s (2007) list of project attributes and suggest some areas where they may act as key PFE contingencies. Now, think about PFE and project-based firms (PBF). Whitley (2006) offers a typology around orthogonal dimensions: (i) the extent to which firms focus on singular outputs (i.e. “unusual, sometimes one-off, products and services for varied, and often uncertain, markets”); and (ii) the extent to which the organization (“of expertise, tasks, and roles”) is predictable and stable over projects. Such distinctions have significant implications for the PFE given that singular outputs mean organizations are less likely to draw on “economics of repetition”9 (Davies and Brady, 2000).

The front-end in project and innovation management  113

Table 5.2  Project categorization implications for PFE Attributes

Examples

Potential PFE implications

Application area

Public/private, engineering, construction, ICT, culture change, training, etc.

Range of stakeholders. Linking (in)tangibility of outcome and shared objectives Regulatory (e.g. safety) compliance.

Complexity

Dynamic/behavioural complexity typology: wicked problems, etc.

Defining agreed objectives, capabilities, stakeholders, etc. Emergent behaviour/complexity of interactions.

Strategic importance

Mandatory, repositioning, renewal.

Urgency and resourcing. Compliance versus creativity (objectives).

Contract type

Fixed price, cost+, PPP, etc.

Urgency and resourcing. Range of stakeholders.

Life-cycle stage

Feasibility, design, execution, close-out, commissioning.

Potentially reducing uncertainty over life-cycle. Risk of specification debt (cf. technical debt).

Culture

Project manager in single culture, host culture or expatriate.

Defining agreed objectives, capabilities, stakeholders, etc. Cultural attributes (power distance, etc.).

Source:   adapted from Müller and Turner, 2007.

CONCLUDING COMMENTS – ESTABLISHING FUTURE RESEARCH AVENUES In this chapter we explored two types of “front-end” research (and hence hopefully at least observed practice) that address related concerns but, to date, have been largely distinct. Some of the reasons for this isolation relate to structural contingency (see earlier section) and unit of analysis, but the discussion shows there was significant value in such a “side-by-side” comparison. It was not intended to be a structured review of either field and there was no empirical material to address specific research questions, but there is clearly scope for further research in both spaces. For example, is PFE the same for organizations which deliver projects (or indeed innovation) as their core business and organizations that use projects to structure their in-house and collaborative activities (Hobday, 2000)? Equally, given the emergence of the temporary organization literature (Lundin and Söderholm, 1995; Turner and Müller, 2003; Sydow and Braun, 2018), it could be argued that the very nature of the organization or structure undertaking the project becomes a key PFE decision. There is also the “exploratory project” literature. How different is the PFE of a project that is established to be a large PFE and to explore strategic opportunities, new technologies, business models or use cases (Brady and Davies, 2004) where neither the goal nor the means to achieve the goal can be clearly defined at the outset (Lenfle, 2008, 2016)? Research on exploratory projects has shown that it is difficult, if not impossible, to assume that standard project methodology can be efficiently transferred to exploratory projects. More generally, three themes are worth highlighting as a putative research “agenda”.

114  Handbook on innovation and project management

What Is the Front-End and Why Is It (Still) Fuzzy? First, there is a conceptual challenge. It is clear from the review that many definitional issues remain unresolved. The front-end of any process is clearly a multi-faceted notion. At one level is it simply a useful metaphor? Treated phenomenologically, it makes many assumptions about temporality, sequence and change, all determined to a large extent by the level of analysis and point of view and its manifold conceptual, experiential, psychological and political components. Is it correct to treat projects – even mega projects – as “lonely islands” (Engwall, 2003) divided from the rest of the world by (clock) time, task and people boundaries (Lundin and Söderholm, 1995; Sahlin-Andersson and Engwall, 2002)? It is interesting to reflect on Gersick’s (1989) pioneering time-pacing work (cf. Alioua and Simon, 2017) in this light. She found that project team members did not adapt their activities in a sequential and linear manner but rather went through phases of inertia and then more dramatic change – not time but tempo – a kind of fartlek. Interestingly she also noted that environmental events had consequences on how project members pace their activities with more beneficial consequences at the beginning of a project. Given this breadth and dynamism, is it possible to avoid being procrustean? Even if we are profoundly reductive, do we know much about the causality of the front–back transition? Post hoc, ergo propter hoc (“After this, therefore because of it”) can be true, but how often are we falling for a logical fallacy? There is abundant evidence that relatively lower-performing projects had relatively lower quality at entry (by some measures) than others, and not surprisingly plenty of research papers link the two. Samset and Volden’s (2016) work using the Norwegian data set is arguably amongst the strongest because of its longitudinal character. Yet most do so without really testing the causal link between quality at entry and ultimate project performance (at what point, etc.). Randomized controlled trials are missing – are they possible? – and many key questions of generalizability remain to be tackled. For example, Sharp and Salter (1997) found that although agency theory10 had strong explanatory power for project escalation behaviour in North America, it offered no explanatory power in their Asian sample. More recently, Driouchi et al. (2020) examined the role of national culture and ambiguity in valuing real options, an interesting proxy for the PFE/FEI, and found that cultural factors, along with age, gender and international life experience, influence subjective attitudes towards value and ambiguity. In sum, are we over- or under-sampled in different types of projects, and, if we are, will this not impact our conclusions about the character and consequences of the front-end? How Do We Resolve Temporal Conflict? Second, and most normatively, the PFE/FEI can be presented as a form of temporal conflict, whereby actions taken ex-ante to address a contemporary set of circumstances inadvertently harm another group ex-post. Resolving such a temporal conflict requires (especially when framed in agency terms) us to address an information asymmetry problem: how much information about a project (options, uncertainties, risks) should be disclosed (n.b., contingent on legislation, regulation and other factors) in these earliest, options-rich, creative stages? In a perfect world, there would be little difference between current and future stakeholders. Unfortunately, disclosure of a profusion of details can obfuscate and confuse stakeholders, and even the most sophisticated reviewers can suffer information overload, some may not have the time to review much less evaluate (Dahlmann and Roehrich, 2019; Aben et al., 2021).

The front-end in project and innovation management  115

Considering Bettis’ (2017) theory of “organizational intractability”, those circumstances when rational decision-making would take longer than a given decision remains invariant in its essentials seem very plausible in many PFE settings.11 Another reason takes us back to our discussion of a behavioural perspective on the front-end. People are not rational assessors of information (e.g. recency, optimism bounded rationality) and this can create another form of information asymmetry. This echoes calls for a move towards strategic marketing in the PFE (Cova et al., 1994) and the management of “sleeping relationships” (Hadjikhani, 1996). Earlier we argued that the longevity of many projects can exacerbate this “paradox of perverse incentives” (Samset and Volden, 2016; Welde and Odeck, 2017), ultimately creating the conditions for a version of the so-called “tragedy of the commons”. Here we argue that valuable and novel insights might be derived from considering aspects of initial (e.g. planning, budgeting) processes as a form of shared resource or “commons”. When Are We Really Looking At? Finally, there is an empirical challenge. Are we engaged with the “real” front-end? Do scholars need to venture even further off the PM/NPD map to a place where “here be dragons”12 (Elahi, 2011)? Andersen et al. (2014), in their study of 17 major public projects, found that in 11 cases the choice of concept had already been made when the so-called front-end process started, only in six cases, truly unique alternatives were identified. As Williams et al. (2019) stressed, “ideation” is at the heart of the process of project “emergence” (Kwak et al., 2014; Kock et al., 2015, 2016) and reaching a stable value proposition/business case can be time-consuming, especially in large/mega projects involving higher degrees of newness. The innovation literature offers some additive insights regarding how to work effectively with “formative” definitions during the learning process (Verworn et al., 2008), and stopping such activities from being crowded out by day-to-day project management (Kurkkio et al., 2011). Björk and Magnusson (2009) noted that there is extensive literature related to idea generation and identification, drawing on a broad range of disciplines and theories around creativity, learning, psychology and social networks.

NOTES 1. Legendary project scholar Peter Morris (1994) strongly argued that an overly narrow life cycle focus meant missing critical institutional elements – including the front-end – that more accurately typify project work in practice. 2. Sitting on a panel at a major projects conference in 2018, the author was confronted with this distinction (Morris, 2016). As I began to describe how the front-end was integral to any project, even if it is only a putative project at that point in time, a forceful comment came from the conference floor: “in my view Professor, projects only exist once the ‘front-end’ is completed!”. 3. A more recent and broader-based review by Park et al. (2021) identified and analysed 266 fuzzy FEI-linked studies. 4. Just as Cooper (1988) highlights idea generation, product definition and product evaluation, Smith and Reinertsen (1992) talk about idea screening, business plans and project and product specification. Khurana and Rosenthal (1997) identify a “pre-phase” zero where there is preliminary identification of opportunities and market and technological analysis, followed by phase zero where product concepts are defined and phase one for more detailed product and project planning. Similarly, Montoya-Weiss and O’Driscoll (2000) list idea qualification, concept development,

116  Handbook on innovation and project management

5.

6.

7. 8. 9. 10.

11.

12.

concept assignment and evaluation of concept. Langerak et al. (2004) identify four stages of predevelopment activity; Griffiths-Hemans and Grover (2006) offer three (idea creation, implementation and commitment). Khurana and Rosenthal (1997, 1998) split their sequential FEI process model into the three sections: pre-phase zero, phase zero and phase one. They stress the need for parallel but projectindependent activities, so-called foundation elements, such as idea generation via market and technology analysis, etc. Optimism bias is the generic label used for overestimating positive and/or underestimating negative outcomes. Stingl and Geraldi (2017) argue it is an umbrella term for various PFE-related cognitive biases like self-efficacy theory, illusion of control or outcome desirability. For example, research has shown increased levels of perceived control in endogenous (versus exogenous) project risks (Du et al., 2006; Jani, 2008, 2011). A key part of lean project logic is that “downstream” stakeholders are involved in front-end planning and design through cross-functional teams. Burns and Stalker (1961) also helped introduce the organic/mechanistic distinctions that feature heavily in the wider organization literature and are evident in most of the discussions (e.g. mechanistic = formal, centralized, etc.) in this chapter. Maniak and Midler (2014) proposed “lineage management” as an approach that emphasizes successive project learning and value creation processes from the initial breakthrough project. Agency theory assumes goal divergence between manager (agent) and the firm’s owners (principal). The argument goes something like this. Managers escalate a “losing” project if (a) there is an incentive for them to do so (personal gain, promotion, etc.), and (b) information asymmetry exists (i.e. principal has less information than agent). Moreover, escalation might mean later recovery of any “losses” already incurred, and if senior management has no awareness of the loss or the escalation, then the manager will have a further strong rational incentive to escalate. Interestingly, the broader psychological literature (e.g. Hammond, 2000; Ariely and Zakay, 2001) has also explored the ways in which individuals cope with a classic project concern, the stress of time pressure. Time pressure may lead to worse performance in learning tasks (DeDonno and Demaree, 2008) but Payne et al. (1988) suggest a hierarchy of responses. First, people try to respond by working faster but if the pressure is too high, they may begin to filter available information. If this is still insufficient, they may opt for a simpler decision-making strategy. Again, linking this concern to prospect theory, De Dreu (2003), for example, finds evidence that (perceived) time pressure, by weakening people’s motivation to process information, reduces negotiation efficiency. Since ancient times, the phrase “here be dragons” (HIC SVNT DRACONES) – engraved on the Lenox Globe circa 1500 – has been used to signify unexplored (dangerous) territories.

REFERENCES Aben, T., van der Valk, W., Roehrich, J., and Selviaridis, K. (2021). Managing information asymmetry in public-private relationships undergoing a digital transformation: The role of contractual and relational governance. International Journal of Operations and Production Management, 41(7), 1145–1191. Akbar, H. and Tzokas, N. (2012). An exploration of new product development’s front-end knowledge conceptualization process in discontinuous innovations. British Journal of Management, 24(2), 245–263. Alioua, H. and Simon, F. (2017). Managing time pacing in organizations transitioning to a projectbased mode – 3 case studies of two multinational companies. International Journal of Project Management, 35(8), 1427–1443. Amabile, T. (1983). The social psychology of creativity: A componential conceptualization. Journal of Personality and Social Psychology, 45(2), 357–376. Andersen, B., Samset, K., and Austeng, K. (2014). To which extent do projects explore the opportunity space? A study of conceptual appraisals and the choice of conceptual solutions. International Journal of Managing Projects in Business, 7(3), 473–492.

The front-end in project and innovation management  117

Ariely, D. and Zakay, D. (2001). A timely account of the role of duration in decision making. Acta Psychologica, 108(2), 187–207. Artto, K., Ahola, T., and Vartiainen, V. (2016). From the front end of projects to the back end of operations: Managing projects for value creation throughout the system lifecycle. International Journal of Project Management, 34(2), 258–270. Babaei, A., Locatelli, G., and Sainati, T. (2021). What is wrong with the front-end of infrastructure megaprojects and how to fix it: A systematic literature review. Project Leadership and Society, 2(1), 1–14. Backman, M., Börjesson, S., and Setterberg, S. (2007). Working with concepts in the fuzzy front end: Exploring the context for innovation for different types of concepts at Volvo cars. R&D Management, 37(1), 17–28. Bacon, G., Beckman, S., Mowery, D., and Wilson, E. (1994). Managing product definition in high‐technology industries: A pilot study. California Management Review, 36(3), 32–56. Barlow, J., Roehrich, J., and Wright, S. (2013). Europe sees mixed results from public-private partnerships for building and managing health care facilities and services. Heath Affairs, 32(1), 146–154. Beaume, R., Maniak, R., and Midler, C. (2009). Crossing innovation and product projects management: A comparative analysis in the automotive industry. International Journal of Project Management, 27(2), 166–174. Bettis, R. (2017). Organizationally intractable decision problems and the intellectual virtues of heuristics. Journal of Management, 43(8), 2620–2637. Björk, J. and Magnusson, M. (2009). Where do good innovation ideas come from? Exploring the influence of network connectivity on innovation idea quality. Journal of Product Innovation Management, 26(6), 662–670. Boulding, W., Guha, A., and Staelin, R. (2017). Do we really need to change the decision maker? Counterintuitive escalation of commitment results in real options contexts. Management Science, 63(10), 3459–3472. Brady, T. and Davies, A. (2004). Building project capabilities: From exploratory to exploitative learning. Organization Studies, 25(9), 1601–1621. Brady, T. and Davies, A. (2010). From hero to hubris – Reconsidering the project management of Heathrow’s terminal 5. International Journal of Project Management, 28(2), 151–157. Brown, S. and Eisenhardt, K. (1998). Competing on the edge: Strategy as structured chaos. Cambridge, MA: Harvard University Press. Burns, T. and Stalker, G. (1961). Mechanistic and organic systems. London: Tavistock Publications. Burström, T. and Wilson, T. (2018). The texture of tension: Complexity, uncertainty, and equivocality. International Journal of Managing Projects in Business, 11(2), 458–485. Calantone, R., Di Benedetto, C., and Schmidt, J. (1999). Using the analytic hierarchy process in new product screening. Journal of Product Innovation Management, 16(1), 65–76. Caputo, M. and Zirpoli, F. (2001). A new organisation for supplier involvement in vehicle design: The Italian automotive industry case. International Journal of Automotive Technology and Management, 1(2), 301–320. Carlile, P. (2002). A pragmatic view of knowledge and boundaries: Boundary objects in new product development. Organization Science, 13(4), 442–455. Chen, C., Lin, C., and Huang, S. (2006). A fuzzy approach for supplier evaluation and selection in supply chain management. International Journal of Production Economics, 102(2), 289–301. Christensen, C., Kaufman, S., and Shih, W. (2008). Innovation killers: How financial tools destroy your capacity to do new things. Harvard Business Review, 86(1), 98–105. Christiansen, J. and Varnes, C. (2008). From models to practice: Decision making at portfolio meetings. International Journal of Quality and Reliability Management, 25(1), 87–101. Cigolini, R., Cozzi, M., and Perona, M. (2004). A new framework for supply chain management: Conceptual model and empirical test. International Journal of Operations and Production Management, 24(1), 7–41. Clegg, S. and Courpasson, D. (2004). Political hybrids: Tocquevillean views on project organizations. Journal of Management Studies, 41(4), 525–547. Cohen, L., Kamienski, P., and Espino, R. (1998). Gate system focuses industrial basic research. Research-Technology Management, 41(4), 34–37.

118  Handbook on innovation and project management

Cooper, R. (1988). Predevelopment activities determine new product success. Industrial Marketing Management, 17(3), 237–247. Cooper, R. (1990). Stage-gate systems: A new tool for managing new products. Business Horizons, 33(3), 44–54. Cooper, R. (1994). Third-generation new product processes. Journal of Product Innovation Management, 11(1), 3–14. Cooper, R. (1996). Overhauling the new product process. Industrial Marketing Management, 25(6), 465–482. Cooper, R., Edgett, S., and Kleinschmidt, E. (2002). Portfolio management – fundamental to new product success. Research-Technology Management, 45(5), 21–27. Cooper, R. and Kleinschmidt, E. (1986). An investigation into the new product process: Steps, deficiencies, and impact. Journal of Product Innovation Management, 3(2), 71–85. Cooper, R. and Kleinschmidt, E. (1987). New products: What separates winners from losers? Journal of Product Innovation Management, 4(3), 169–184. Cooper, R. and Kleinschmidt, E. (2007). Winning businesses in product development: The critical success factors. Research-Technology Management, 50(3), 52–66. Cova, B., Mazet, F., and Salle, R. (1994). From competitive tendering to strategic marketing: An inductive approach for theory-building. Journal of Strategic Marketing, 2(1), 29–48. Daft, R. and Lengel, R. (1986). Organizational information requirements, media richness and structural design. Management Science, 32(5), 554–571. Daft, R. and Macintosh, N. (1981). A tentative exploration into the amount and equivocality of information processing in organizational work units. Administrative Science Quarterly, 26(2), 207–224. Dahlander, L. and Gann, D. (2010). How open is innovation? Research Policy, 39(6), 699–709. Dahlmann, F. and Roehrich, J. (2019). Sustainable supply chain management and partner engagement to manage climate change information. Business Strategy and the Environment, 28(8), 1632–1647. Davies, A. and Brady, T. (2000). Organisational capabilities and learning in complex product systems: Towards repeatable solutions. Research Policy, 29(7), 931–953. Davies, A., Manning, S., and Söderlund, J. (2018). When neighbouring disciplines fail to learn from each other: The case of innovation and project management research. Research Policy, 47(5), 965–979. DeDonno, M. and Demaree, H. (2008). Perceived time pressure and the Iowa gambling task. Judgement and Decision Making, 3(8), 636–640. De Dreu, C. (2003). Time pressure and closing of the mind in negotiation. Organizational Behavior and Human Decision Processes, 91(2), 280–295. Dietrich, P. (2006). Mechanisms for inter-project integration-empirical analysis in program context. Project Management Journal, 37(3), 49–61. Doz, Y. (1996). The evolution of cooperation in strategic alliances: Initial conditions or learning processes. Strategic Management Journal, 17(1), 55–83. Drazin, R. and Van de Ven, A. (1985). Alternative forms of fit in contingency theory. Administrative Science Quarterly, 30(4), 514–539. Driouchi, T., Trigeorgis, L., and So, R. (2020). Individual antecedents of real options appraisal: The role of national culture and ambiguity. European Journal of Operational Research, 286(3), 1018–1032. Du, S., Keil, M., Mathiassen, L., Shen, Y., and Tiwana, A. (2006). Attention-shaping tools, expertise, and perceived control in IT project risk assessment. Decision Support Systems, 43(1), 269–283. Dyer, J. (1996a). Does governance matter? Keiretsu alliances and asset specificity as sources of Japanese competitive advantage. Organization Science, 7(6), 649–666. Dyer, J. (1996b). Specialized supplier networks as a source of competitive advantage: Evidence from the auto industry. Strategic Management Journal, 17(4), 271–291. Edkins, A., Geraldi, J., Morris, P., and Smith, A. (2013). Exploring the front-end of project management. Engineering Project Organization Journal, 3(2), 71–85. Edkins, A. and Smith, A. (2012). Designing the project. In T. Williams and K. Samset (Eds.), Project governance: Getting investments right (pp. 135–174). London: Springer Publishing. Elahi, S. (2011). Here be dragons… exploring the ‘unknown unknowns’. Futures, 43(2), 196–201. Eling, K., Griffin, A., and Langerak, F. (2014). Using intuition in fuzzy front-end decision making: A conceptual framework. Journal of Product Innovation Management, 31(5), 956–972. Eling, K. and Herstatt, C. (2017). Managing the front end of innovation – Less fuzzy, yet still not fully understood. Journal of Product Innovation Management, 34(6), 864–874.

The front-end in project and innovation management  119

Englund, R. and Graham, R. (1999). From experience: Linking projects to strategy. Journal of Product Innovation Management, 16(1), 52–64. Engwall, M. (2003). No project is an island: Linking projects to history and context. Research Policy, 32(5), 789–808. Evanschitzky, H., Eisend, M., Calantone, R., and Jiang, Y. (2012). Success factors of product innovation: An updated meta-analysis. Journal of Product Innovation Management, 29(1), 21–37. Flyvbjerg, B. (2014). What you should know about megaprojects and why: An overview. Project Management Journal, 45(2), 6–19. Flyvbjerg, B., Garbuio, M., and Lovallo, D. (2009). Delusion and deception in large infrastructure projects: Two models for explaining and preventing executive disaster. California Management Review, 51(2), 170–194. Frishammar, J., Dahlskog, E., Krumlinde, C., and Yazgan, K. (2016). The front end of radical innovation: A case study of idea and concept development at prime group. Creativity and Innovation Management, 25(2), 179–198. Frishammar, J., Florén, H., and Wincent, J. (2010). Beyond managing uncertainty: Insights from studying equivocality in the fuzzy front end of product and process innovation projects. IEEE Transactions on Engineering Management, 58(3), 551–563. Galbraith, J. (1974). Organization design: An information processing view. Interfaces, 4(3), 28–36. Gassmann, O., Frankenberger, K., and Sauer, R. (2016). Exploring the field of business model innovation: New theoretical perspectives. Basingstoke: Springer Publishing. Gaubinger, K. and Rabl, M. (2014). Structuring the front end of innovation. In O. Gassmann and F. Schweitzer (Eds.), Management of the fuzzy front end of innovation (pp. 289–294). London: Springer Publishing. Geraldi, J. and Adlbrecht, G. (2007). On faith, fact, and interaction in projects. Project Management Journal, 38(1), 32–43. Gersick, C. (1989). Marking time: Predictable transitions in task groups. Academy of Management Journal, 32(2), 274–309. Gil, N. and Baldwin, C. (2014). Sharing design rights: A commons approach for developing infrastructure. Harvard Business School. Unpublished working paper. Goldratt, E. (1997). The Critical Chain. New York City: North River Press. Griffin, A., Vojak, B., and Price, R. (2012). Serial innovators: How individuals create and deliver breakthrough innovations in mature firms. Stanford, CA: Stanford University Press. Griffiths-Hemans, J. and Grover, R. (2006). Setting the stage for creative new products: Investigating the idea fruition process. Journal of the Academy of Marketing Science, 34(1), 27–39. Grimsey, D. and Lewis, M. (2005). Are public private partnerships value for money?: Evaluating alternative approaches and comparing academic and practitioner views. Accounting Forum, 29(4), 345–378. Gulati, R., Puranam, P., and Tushman, M. (2012). Meta-organization design: Rethinking design in interorganizational and community contexts. Strategic Management Journal, 33(6), 571–586. Gupta, S. and Maltz, E. (2015). Interdependency, dynamism, and variety (IDV) network modeling to explain knowledge diffusion at the fuzzy front-end of innovation. Journal of Business Research, 68(11), 2434–2442. Hadjikhani, A. (1996). Project marketing and the management of discontinuity. International Business Review, 5(3), 319–336. Hall, D. and Nauda, A. (1990). An interactive approach for selecting IR&D projects. IEEE Transactions on Engineering Management, 37(2), 126–133. Hällgren, M. (2010). Groupthink in temporary organisations. International Journal of Managing Projects in Business, 3(1), 94–110. Hammond, K. (2000). Judgements under stress. Oxford: Oxford University Press. Harvey, J., Cohendet, P., Simon, L., and Borzillo, S. (2015). Knowing communities in the front end of innovation. Research-Technology Management, 58(1), 46–54. Hellström, M., Ruuska, I., Wikström, K., and Jåfs, D. (2013). Project governance and path creation in the early stages of Finnish nuclear power projects. International Journal of Project Management, 31(5), 712–723. Henriksen, A. and Traynor, A. (1999). A practical R&D project-selection scoring tool. IEEE Transactions on Engineering Management, 46(2), 158–170.

120  Handbook on innovation and project management

Herstatt, C. and Verworn, B. (2007). Management of the early stages of innovation. Wiesbaden: Springer Fachmedien. Hobday, M. (2000). The project-based organisation: An ideal form for managing complex products and systems? Research Policy, 29(7), 871–893. Jani, A. (2008). An experimental investigation of factors influencing perceived control over a failing IT project. International Journal of Project Management, 26(7), 726–732. Jani, A. (2011). Escalation of commitment in troubled IT projects: Influence of project risk factors and self-efficacy on the perception of risk and the commitment to a failing project. International Journal of Project Management, 29(7), 934–945. Jensen, M. (2017). Opportunities of industry-based makerspaces: New ways of prototyping in the fuzzy front end. PhD thesis. Norwegian University of Science and Technology. Jordan, G., Lee, I., and Cawsey, G. (1988). Learning from experience: A report on the arrangements for managing major projects in the procurement executive. London: Her Majesty’s Stationery Office. Kagan, E., Leider, S., and Lovejoy, W. (2017). Ideation-execution transition in product development: An experimental analysis. Management Science, 64(5), 2238–2262. Keil, M., Tan, B., Wei, K., Saarinen, T., Tuunainen, V., and Wassenaar, A. (2000). A cross-cultural study on escalation of commitment behaviour in software projects. MIS Quarterly, 24(2), 299–325. Khurana, A. and Rosenthal, S. (1997). Integrating the fuzzy front end of new product development. MIT Sloan Management Review, 25(4), 35–49. Khurana, A. and Rosenthal, S. (1998). Towards holistic “front ends” in new product development. Journal of Product Innovation Management, 15(1), 57–74. Kim, J. and Wilemon, D. (2002). Focusing the fuzzy front-end in new product development. R&D Management, 32(4), 269–279. Kock, A; Heising, W., and Gemunden, H. (2015). How ideation portfolio management influences frontend success. Journal of Product Innovation Management, 32(4), 539–555. Kock, A., Heising, W., and Gemunden, H. (2016). A contingency approach on the impact of front-end success on project portfolio success. Project Management Journal, 47(2), 115–129. Koen, P., Ajamian, G., Burkart, R., Clamen, A., Davidson, J., D’Amore, R., Elkins, C., Herald, K., Incorvia, M., Johnson, A., Karol, R., Seibert, R., Slavejkov, A., and Wagner, K. (2001). Providing clarity and a common language to the “fuzzy front end”. Research-Technology Management, 44(2), 46–55. Koen, P., Bertels, H., and Kleinschmidt, E. (2014a). Managing the front end of innovation – Part I: Results from a three-year study. Research-Technology Management, 57(2), 34–43. Koen, P., Bertels, H., and Kleinschmidt, E. (2014b). Managing the front end of innovation – Part II: Results from a three-year study. Research-Technology Management, 57(3), 25–35. Kurkkio, M., Frishammar, J., and Lichtenthaler, U. (2011). Where process development begins: A multiple case study of front end activities in process firms. Technovation, 31(9), 490–504. Kutsch, E., Maylor, H., Weyer, B., and Lupson, J. (2011). Performers, trackers, lemmings and the lost: Sustained false optimism in forecasting project outcomes – evidence from a quasi-experiment. International Journal of Project Management, 29(8), 1070–1081. Kwak, Y., Walewski, J., Sleeper, D., and Sadatsafavi, H. (2014). What can we learn from the Hoover Dam project that influenced modern project management? International Journal of Project Management, 32(2), 256–264. Langerak, F., Hultink, E., and Robben, H. (2004). The impact of market orientation, product advantage, and launch proficiency on new product performance and organizational performance. Journal of Product Innovation Management, 21(2), 79–94. Lawrence, P. and Lorsch, J. (1967). Differentiation and integration in complex organizations. Administrative Science Quarterly, 12(1), 1–47. Lenfle, S. (2008). Exploration and project management. International Journal of Project Management, 26(5), 469–478. Lenfle, S. (2016). Floating in space? On the strangeness of exploratory projects. Project Management Journal, 47(2), 47–61. Linehan, C. and Kavanagh, D. (2006). From project ontologies to communities of virtue. In D. Hodgson and S. Cicmil (Eds.), Making projects critical (pp. 51–67). London: Palgrave Macmillan.

The front-end in project and innovation management  121

Little, T. (2005). Context-adaptive agility: Managing complexity and uncertainty. IEEE Software, 22(3), 28–35. Loch, C. (2000). Tailoring product development to strategy: Case of a European technology manufacturer. European Management Journal, 18(3), 246–258. Loch, C., Terwiesch, C., and Thomke, S. (2001). Parallel and sequential testing of design alternatives. Management Science, 47(5), 663–678. Long, X., Nasiry, J., and Wu, Y. (2020). A behavioural study on abandonment decisions in multistage projects. Management Science, 66(5), 1999–2016. Lubart, T. (2001). Models of the creative process: Past, present, and future. Creativity Research Journal, 13(3), 295–308. Lundin, R., Arvidsson, N., Brady, T., Ekstedt, E., Midler, C., and Sydow, J. (2015). Managing and working in project society. Cambridge: Cambridge University Press. Lundin, R. and Söderholm, A. (1995). A theory of the temporary organization. Scandinavian Journal of Management, 11(4), 437–455. Macdonald, S. and Williams, C. (1994). The survival of the gatekeeper. Research Policy, 23(2), 123–132. Maniak, R. and Midler, C. (2014). Multiproject lineage management: Bridging project management and design-based innovation strategy. International Journal of Project Management, 32(7), 1146–1156. Maniak, R., Midler, C., Beaume, R., and Von Pechmann, F. (2013). Featuring capability: How carmakers organize to deploy innovative features across products. Journal of Product Innovation Management, 31(1), 114–127. March, J. (2006). Rationality, foolishness, and adaptive intelligence. Strategic Management Journal, 27(3), 201–214. Markham, S. (2013). The impact of front-end innovation activities on product performance. Journal of Product Innovation Management, 30(1), 77–92. Markham, S., Ward, S., Aiman‐Smith, L., and Kingon, A. (2010). The valley of death as context for role theory in product innovation. Journal of Product Innovation Management, 27(3), 402–417. Marsh, S. and Stock, G. (2003). Building dynamic capabilities in new product development through intertemporal integration. Journal of Product Innovation Management, 20(2), 136–148. Martinsuo, M. and Poskela, J. (2011). Use of evaluation criteria and innovation performance in the frontend of innovation. Journal of Product Innovation Management, 28(6), 896–914. Martinsuo, M., Suomala, P., and Kanniainen, J. (2013). Evaluating the organizational impact of product development projects. International Journal of Managing Projects in Business, 31(6), 794–803. Maylor, H. (2001). Beyond the Gantt chart: Project management moving on. European Management Journal, 19(1), 92–100. Mesa, H., Molenaar, K., and Alarcón, L. (2019). Comparative analysis between integrated project delivery and lean project delivery. International Journal of Project Management, 37(3), 395–409. Meyer, W. (2014). The effect of optimism bias on the decision to terminate failing projects. Project Management Journal, 45(4), 7–20. Midler, C. (1995). “Projectification” of the firm: The Renault case. Scandinavian Journal of Management, 11(4), 363–375. Miller, R. and Hobbs, B. (2005). Governance regimes for large complex projects. Project Management Journal, 36(3), 42–50. Miller, R. and Lessard, D. (2000). The strategic management of large engineering projects: Shaping institutions, risks, and governance. Cambridge, MA: Massachusetts Institute of Technology Press. Moenaert, R., De Meyer, A., Souder, W., and Deschoolmeester, D. (1995). R&D/marketing communication during the fuzzy front-end. IEEE Transactions on Engineering Management, 42(3), 243–258. Montoya-Weiss, M. and O’Driscoll, T. (2000). From experience: Applying performance support technology in the fuzzy front end. Journal of Product Innovation Management, 17(2), 143–161. Moore, G. and McKenna, R. (1999). Crossing the chasm (2nd ed.). New York City: Harper Business Publishing. Morris, P. (1987). The anatomy of major projects: Study of the reality of project management. Oxford: John Wiley and Sons. Morris, P. (1994). The management of projects. London: T Telford Publishing.

122  Handbook on innovation and project management

Morris, P. (2013). Reconstructing project management reprised: A knowledge perspective. Project Management Journal, 44(5), 6–23. Morris, P. (2016). Reflections. International Journal of Project Management, 34(2), 365–370. Mosey, D. (2009). Early contractor involvement in building procurement: Contracts, partnering and project management. Oxford: Wiley-Blackwell. Müller, R. and Turner, R. (2007). The influence of project managers on project success criteria and project success by type of project. European Management Journal, 25(4), 298–309. O’Brien, K. (2020). Innovation types and the search for new ideas at the fuzzy front end: Where to look and how often? Journal of Business Research, 107(1), 13–24. Park, D., Han, J., and Childs, P. (2021). 266 Fuzzy front-end studies: Current state and future directions for new product development. Research in Engineering Design, 32(3), 377–409. Payne, J., Bettman, J., and Johnson, E. (1988). Adaptive strategy selection in decision making. Journal of Experimental Psychology: Learning, Memory, and Cognition, 14(3), 534–552. Pennings, J. (1992). Structural contingency theory: A re-appraisal. In B. Staw and L. Cummings (Eds.), Research in organization behaviour (pp. 267–309). Stamford, CT: JAI Press. Pereira, A., Ferreira, J., and Lopes, A. (2017). Front end of innovation: An integrative literature review. Journal of Innovation Management, 5(1), 22–39. Phelps, C., Heidl, R., and Wadhwa, A. (2012). Knowledge, networks, and knowledge networks: A review and research agenda. Journal of Management, 38(4), 1115–1166. Pinto, J. (2014). Project management, governance, and the normalization of deviance. International Journal of Project Management, 32(3), 376–387. Primo, M. and Amundson, S. (2002). An exploratory study of the effects of supplier relationships on new product development outcomes. Journal of Operations Management, 20(1), 33–52. Quinn, J. (1985). Innovation and corporate strategy: Managed chaos. Technology in Society, 7(2), 263–279. Reid, S. and De Brentani, U. (2004). The fuzzy front end of new product development for discontinuous innovations: A theoretical model. Journal of Product Innovation Management, 21(3), 170–184. Reinertsen, D. (1999). Taking the fuzziness out of the fuzzy front end. Research-Technology Management, 42(6), 25–31. Reinertsen, D. and Smith, P. (1991). The strategist’s role in shortening product development. Journal of Business Strategy, 12(4), 18–22. Rizova, P., Gupta, S., Maltz, E., and Walker, R. (2018). Overcoming equivocality on projects in the fuzzy front end: Bringing social networks back in. Technovation, 78(1), 40–55. Saff, D. and Ernst, M. (2003). Reducing wasted development time via continuous testing. In 14th international symposium on software reliability engineering. New York City: Institute of Electrical and Electronic Engineers. Sahlin-Andersson, K. and Engwall, L. (2002). The expansion of management knowledge: Carriers, flows, and sources. Stanford, CA: Stanford University Press. Salter, A., Ter Wal, A., Criscuolo, P., and Alexy, O. (2015). Open for ideation: Individual-level openness and idea generation in R&D. Journal of Product Innovation Management, 32(4), 488–504. Samset, K. (2010). Early project appraisal: Making the initial choices. Basingstoke: Springer Publishing. Samset, K. and Volden, G. (2016). Front-end definition of projects: Ten paradoxes and some reflections regarding project management and project governance. International Journal of Project Management, 34(2), 297–313. Schmidt, J. and Calantone, R. (2002). Escalation of commitment during new product development. Journal of the Academy of Marketing Science, 30(2), 103–118. Schmidt, J., Sarangee, K., and Montoya, M. (2009). Exploring new product development project review practices. Journal of Product Innovation Management, 26(5), 520–535. Scott, R. and Levitt, R. (2017). Institutional challenges and solutions for global megaprojects. In B. Flyvbjerg (Ed.), The Oxford handbook of megaproject management (pp. 96–117). Oxford: Oxford University Press. Seidel, V. and Fixson, S. (2013). Adopting design thinking in novice multidisciplinary teams: The application and limits of design methods and reflexive practices. Journal of Product Innovation Management, 30(1), 19–33.

The front-end in project and innovation management  123

Sharp, D. and Salter, S. (1997). Project escalation and sunk costs: A test of the international generalizability of agency and prospect theories. Journal of International Business Studies, 28(1), 101–121. Shenhar, A. and Dvir, D. (1996). Toward a typological theory of project management. Research Policy, 25(4), 607–632. Shmueli, O., Pliskin, N., and Fink, L. (2015). Explaining over-requirement in software development projects: An experimental investigation of behavioural effects. International Journal of Project Management, 33(2), 380–394. Smith, G., Herbein, W., and Morris, R. (1999). Front-end innovation at AlliedSignal and Alcoa. Research-Technology Management, 42(6), 15–24. Smith, P. and Reinertsen, D. (1992). Shortening the product development cycle. Research-Technology Management, 35(3), 44–49. Son, J. and Rojas, E. (2011). Evolution of collaboration in temporary project teams: An agent-based modelling and simulation approach. Journal of Construction Engineering and Management, 137(8), 619–628. Song, X. and Montoya-Weiss, M. (1998). Critical development activities for really new versus incremental products. Journal of Product Innovation Management, 15(2), 124–135. Song, Y., Lee, D., Lee, Y., and Chung, Y. (2007). Managing uncertainty and ambiguity in frontier R&D projects: A Korean case study. Journal of Engineering and Technology Management, 24(3), 231–250. Stingl, V. and Geraldi, J. (2017). Errors, lies and misunderstandings: Systematic review on behavioural decision making in projects. International Journal of Project Management, 35(2), 121–135. Stjerne, I. and Svejenova, S. (2016). Connecting temporary and permanent organizing: Tensions and boundary work in sequential film projects. Organization Studies, 37(12), 1771–1792. Sydow, J. and Braun, T. (2018). Projects as temporary organizations: An agenda for further theorizing the interorganizational dimension. International Journal of Project Management, 36(1), 4–11. Takahashi, M., Indulska, M., and Steen, J. (2018). Collaborative research project networks: Knowledge transfer at the fuzzy front end of innovation. Project Management Journal, 49(4), 36–52. Takey, S. and Carvalho, M. (2016). Fuzzy front end of systematic innovations: A conceptual framework based on a systematic literature review. Technological Forecasting and Social Change, 111(1), 97–109. Tatikonda, M. and Rosenthal, S. (2000). Technology novelty, project complexity, and product development project execution success: A deeper look at task uncertainty in product innovation. IEEE Transactions on Engineering Management, 47(1), 74–87. Thomke, S. and Fujimoto, T. (2000). The effect of “front-loading” problem-solving on product development performance. Journal of Product Innovation Management, 17(2), 128–142. Turner, J. and Cochrane, R. (1993). Goals-and-methods matrix: Coping with projects with ill-defined goals and/or methods of achieving them. International Journal of Project Management, 11(2), 93–102. Turner, J. and Müller, R. (2003). On the nature of the project as a temporary organization. International Journal of Project Management, 21(1), 1–8. Ulrich, K. and Eppinger, S. (2004). Product design and development (3rd ed.). New York City: McGraw Hill Publishing. Van den Ende, J., Frederiksen, L., and Prencipe, A. (2014). The front end of innovation: Organizing search for ideas. Journal of Product Innovation Management, 32(4), 482–487. Van der Duin, P., Ortt, J., and Aarts, W. (2014). Contextual innovation management using a stage-gate platform: The case of Philips shaving and beauty. Journal of Product Innovation Management, 31(3), 489–500. Verworn, B. (2006). How German measurement and control firms integrate market and technological knowledge into the front end of new product development. International Journal of Technology Management, 34(3), 379–389. Verworn, B. and Herstatt, C. (1999). Approaches to the “fuzzy front end” of innovation. Technische Universität Hamburg. Unpublished working paper. Verworn, B., Herstatt, C., and Nagahira, A. (2008). The fuzzy front end of Japanese new product development projects: Impact on success and differences between incremental and radical projects. R&D Management, 38(1), 1–19.

124  Handbook on innovation and project management

Wachs, M. (1989). When planners lie with numbers. Journal of the American Planning Association, 55(4), 476–479. Wallas, G. (1926). The art of thought. London: J Cape Publishing. Waterman, R. and Peters, T. (1982). In search of excellence: Lessons from America’s best-run companies. New York City: Harper and Row Publishing. Weick, K. (1979). The social psychology of organizing. Reading, MA: Addison-Wesley. Welde, M. and Odeck, J. (2017). Cost escalations in the front-end of projects-empirical evidence from Norwegian road projects. Transport Reviews, 37(5), 612–630. Whitley, R. (2006). Project-based firms: New organizational form or variations on a theme? Industrial and Corporate Change, 15(1), 77–99. Williams, T. and Samset, K. (2010). Issues in front-end decision making on projects. Project Management Journal, 41(2), 38–49. Williams, T., Vo, H., Bourne, M., Bourne, P., Cooke-Davies, T., Kirkham, R., Masterton, G., Quattrone, P., and Valette, J. (2020). A cross-national comparison of public project benefits management practices – The effectiveness of benefits management frameworks in application. Production Planning and Control, 31(8), 644–659. Williams, T., Vo, H., Samset, K., and Edkins, A. (2019). The front-end of projects: A systematic literature review and structuring. Production Planning and Control, 30(14), 1137–1169. Winch, G. (2013). Escalation in major projects: Lessons from the channel fixed link. International Journal of Project Management, 31(5), 724–734. Winch, G. (2014). Three domains of project organising. International Journal of Project Management, 32(5), 721–731. World Bank. (1996). Evaluation results 1994. West End, Washington: The International Bank of Reconstruction and Development. Youker, R. (1999). Managing international development projects – Lessons learned. Project Management Journal, 30(2), 6–7. Zhang, Q. and Doll, W. (2001). The fuzzy front end and success of new product development: A causal model. European Journal of Innovation Management, 4(2), 95–112.

6. “A disputed project identity”: ambiguity and hybridization of exploration and exploitation in complex projects Stéphanie Tillement, Frédéric Garcias and Florence Charue-Duboc

INTRODUCTION The literature on innovation management and project management makes extensive use of the concepts of exploitation and exploration, notably to understand the learning processes at play or the management of uncertainties. However, each literature makes a distinctive usage of these categories. On the one hand, scholars in the field of innovation management increasingly employ exploration and exploitation in a dynamic way. They insist on the coexistence of exploitation and exploration dynamics and highlight the associated tensions at the intra- or inter-firm levels. They are also increasingly interested in the way in which these tensions are dealt with by actors and organizations and in the capabilities that are developed to do so. In project management, on the other hand, the notions of exploitation and exploration are still used in a rather static way, to qualify a project as a whole, at the macro level. A project is therefore mostly described as either exploitative or exploratory. The way exploitation and exploration may entangle within a single project is not fully addressed by these literatures. In this chapter, we consider projects as essential instruments for innovation. Following this idea, we propose to mobilize the exploitation/exploration framework in a dynamic way to analyse the trajectory of a complex project and its management. In doing so, we aim to show (1) how exploration and exploitation dynamics may intertwine within a single large-scale project; (2) the tensions associated with this intertwining; and (3) how the distribution between exploration and exploitation can evolve in time throughout the course of the project, depending on internal and external factors that embed technical and political dimensions. To do so, we draw on a longitudinal and situated study of the ASTRID1 project, a largescale and complex project that was supposed to be the first French prototype of a “Generation IV” nuclear reactor. After outlining how literatures on innovation and project management address the question of exploration and exploitation and detailing the research approach and setting, the chapter analyses how and why exploitation and exploration dynamics get entangled within the project and discusses the consequences in terms of temporal and organizational framing of the project. To refer to the coexistence of exploitation and exploration dynamics within the project, it introduces the category of a “hybrid project”. The chapter then details the trajectory of the ASTRID project, between its launch and its interruption. It identifies important turning points or turnarounds when the balance between exploration and exploitation domains evolves and specifies the associated tensions. It highlights how it questions the very identity of the project, i.e. its goals and mission, and how this disputed identity relates to project stakeholders’ agenda 125

126  Handbook on innovation and project management

and to power relationships. The chapter finally discusses the notion of “project identity” and its interest in the field of project management and questions the exceptionalism or normality of nuclear projects.

EXPLORATION AND EXPLOITATION IN INNOVATION AND PROJECT MANAGEMENT LITERATURES Exploration and Exploitation in Innovation Management Literature The innovation management literature has introduced various kinds of innovation – incremental, radical, architectural, discontinuous, disruptive, etc. – initially to explain why established firms may be threatened by new entrants (Abernathy and Clark, 1985; Henderson and Clark 1990; Christensen, 1997). The processes of knowledge development and accumulation in companies and the path dependencies related to these processes appear central to explaining this phenomenon. Hence, Leonard-Barton (1992) emphasizes that core competencies may become core rigidities. Cohen and Levinthal (1990), with the notion of absorptive capacity, highlight the need for internal competencies to enable firms to identify and profit from external knowledge. Elaborating on the differentiation between exploitation and exploration learning introduced by March (1991) in his seminal paper, scholars have related exploitation processes to incremental innovation and considered that more discontinuous types of innovation, such as breakthrough innovation (Ahuja and Lampert, 2001) require exploration learning processes (Tushman and O’Reilly, 1997). Further, exploration learning is considered crucial in the ability of the firm to adapt to an ever-changing environment (Kogut and Zander, 1992; Stuart and Poldony, 1996). The literature in innovation management has defined exploitation as activities that search for familiar, mature, current or proximate knowledge and exploration as activities that search for unfamiliar and remote knowledge (Ahuja and Lampert, 2001; Rosenkopf and Nerkar, 2001; Katila and Ahuja, 2002; Nerkar, 2003). Particularly in technological innovation, exploitation involves “local search” that builds on a firm’s existing technological capabilities, while exploration entails a more “distant search” for new capabilities. This knowledge-based view of the exploitation/exploration learning which underscores the refinement of existing knowledge versus the merits of new knowledge development is, however, a narrow understanding of this framework (Lavie et  al., 2010). More importantly, it reconciles the fact that differentiating types of innovation refers to analyses undertaken once the innovation is introduced on the market whereas learning processes are best understood along the innovation development process. March (1991) acknowledged the fundamental distinction between two gestalts of organizational behaviour. Whereas exploration engages individuals and organizations in search, experimentation and variation, exploitation enhances productivity and efficiency through choice, execution and variance reduction. Both types of activities are essential for organizational learning and firm survival but entail inherent contradictions that need to be managed. Recent debates around the notions of exploration and exploitation have mainly focused on the way in which firms seek to articulate these two (conflicting) logics, by showing in particular the existence of several forms of “organizational ambidexterity” (O’Reilly and Tushman, 2013). In particular, it distinguishes a structural ambidexterity, which allocates exploration and exploitation activities to very distinct actors or entities, and a contextual ambidexterity, which requires individuals to combine these two logics. A great deal of research has been devoted

Exploration and exploitation in complex projects  127

to identifying the antecedents, or “micro-foundations” of organizational ambidexterity, which was seen as a condition for the long-term success of organizations in overcoming both the “productivity dilemma” (Abernathy, 1978) and the “innovator’s dilemma” (Christensen, 1997). Research on organizational ambidexterity has thus largely insisted on the fact that exploration and exploitation must not be opposed, but combined and articulated, by overcoming, in the daily practices of organizations, the tensions inherent in their juxtaposition. This new paradigm for innovation management is part of a renewed interest, within the management literature, in the tensions or paradoxes that organizations and individuals face (Raisch and Zimmermann, 2017). Exploration and Exploitation in Project Management Literature: Contributions and Limitations of a Contingent Approach The project management literature has long imported the concepts of exploration and exploitation from the innovation management literature (Brady and Davies, 2004; Lenfle, 2008). But for the most part, these concepts have been used to construct a typology of projects, in the wake of the revival of a contingent approach to projects since the 2000s. For a long time, the challenge for project management researchers has been to distinguish projects from one another, notably according to their level of uncertainty, in order to be able to manage them adequately and avoid the pitfalls of the “one best way” approach (Shenhar and Dvir, 1996) and to manage project portfolios. While this is a major advance, both theoretically and in practice, this concern has tended to obscure the question of the coexistence of different types of learning within projects. The need to build a contingent approach to projects resulted from a misunderstanding of how the field of projects relates to the issue of innovation. Indeed, projects have been identified for a long time in the innovation management literature as organizational structures that are particularly well suited to hosting the most innovative activities of the firm. Innovation scholars thus largely adopted a perspective inherited from the “contingency school” of organizational theory (Burns and Stalker, 2011). Innovation activities, and in particular the most radical ones, facing the “unknown” (Loch et al., 2011), require departing from the organizational “one best way” and looking for specific management and organizational modes. From this perspective, innovation management scholars have long considered projects as a suitable way to escape the bureaucratic constraints of large organizations and to create the conditions for achieving high levels of adaptability, flexibility and search. This postulate is at the heart of the highly influential work carried out by Clark, Fujimoto and Wheelwright at the turn of the 1980s and 1990s (Clark and Fujimoto, 1989; Clark and Wheelwright, 1992). But, as Lenfle (2008) and Davies et al. (2018) point out, this conflation of project and innovation overlooks that, simultaneously, the “mainstream” of project management literature has developed an approach that largely contradicts this association of ideas. In a way, this mainstream, which Söderlund (2011) calls the “optimization school” in project management, embodies almost perfectly the rationalistic, optimizing, instrumentalist and universalist “one best way” from which the contingency school and then innovation scholars have sought to escape. It follows that unlike innovation studies where projects were seen as a vehicle for change, projects in project management research were seen as complex, one-off endeavors that need to be managed with standardized tools, structures and techniques. Informed by a universal approach to management, every project, no matter what context, faced the ‘triple constraint’ of time, cost and quality specifications. (Davies et al., 2018, 970)

128  Handbook on innovation and project management

Faced with the risk of using management methods that would not fit the specificities of innovation, and in particular its most radical forms, several studies have emphasized the need to introduce distinctions between types of projects. For example, the distinction between “mainstream” and “newstream” projects, suggested by Kanter (1990), or between the “compression model” and the “experiential model” (Eisenhardt and Tabrizi, 1995), has enabled us to take a step in this direction. During the following years, a real “contingency school” emerged within project management studies, considered by Söderlund (2011) as one of the seven main schools of thought in the field. This school was initially embodied in the proposal of Shenhar and Dvir (1996) and Shenhar (2001) to make “technological uncertainty” and “system scope” the main contingency factors. Later, Sommer and Loch (2004) and Pich (2002) argued for a distinction between different types of uncertainty in order to establish a relevant typology of projects. In this wake, scholars have proposed to distinguish “routine projects” from “innovative projects” (Davies and Brady, 2016) or “creative projects” (Obstfeld, 2012). In a very similar way, Lenfle (2008) suggested importing into the field of project management the notion of exploration (as opposed to exploitation) borrowed from March (1991). He defined exploratory projects as “those in which neither the technology, nor the customer requirements are known at the beginning of the process”, which differentiates them from “development” projects where these parameters are known at the beginning. For such projects, models and tools from the mainstream of the discipline are not only inoperative but also counterproductive: as Lenfle indicates, the project management “body of knowledge is unsuitable for managing exploratory projects” (Lenfle, 2014, 930). While this clarification allows a significant advance, it seems difficult to fit the entire field of projects into these new categories. Indeed, certain types of projects, such as “megaprojects” (Flyvbjerg, 2014) or “complex projects” (Brady and Davies, 2014), resemble the so-called “exploration projects” without, however, embracing all their specificities. According to Brady and Davies (2014), “complex” projects entangle very “routine” and much more “innovative” activities or sub-projects. Megaprojects, similarly, combine relatively clear objectives at the outset with significant “pockets” of uncertainty and high levels of institutional complexity that make them difficult to manage with standard tools. “First-of-their-kind” or “vanguard projects” (Frederiksen and Davies, 2008; Brady and Davies, 2004; Laurila and Ahola, 2021), such as EPR nuclear reactor projects currently under construction in France or Finland, can easily be viewed as “megaprojects” (Lenfle and Loch, 2017), but also as “complex projects” since they mix high uncertainties with well-known objectives and established core technologies. To label them “exploration projects” would however not make sense. Such projects, with colossal stakes, resist fitting into the “ideal-types” forged by the contingent approach. Taking them into account therefore calls for a better understanding of the way in which exploration and exploitation are likely to entangle within the same project. The co-existence of exploitation and exploration and the tensions that might result from their juxtaposition meet the current interests of many researchers in the field of project studies (Geraldi and Söderlund, 2018). They call for a better understanding of the tensions and paradoxes that characterize projects’ lives, be they organizational (e.g. between permanent or enduring forms of organizing), temporal (e.g. between a short- or long-term temporal focus, between different temporal norms or rhythms, etc.) or goal-related (e.g. between time economy and performance quality) (Raisch and Zimmermann, 2017; Slawinski and Bansal, 2017; Braun and Lampel, 2020). These tensions are enacted by people’s actions (Geraldi et al., 2021) as well as affecting them and thereafter the project’s trajectory and final success or failure.

Exploration and exploitation in complex projects  129

Hence, gaining a deep understanding of how exploitation and exploration dynamics can entangle within a project means adopting a situated approach to projects, attentive to practices and their contexts (Geraldi and Söderlund, 2018). Such an approach, grounded in the tradition of interactionist sociology and in recent developments in the field of process studies, uncovers the tensions that fuel and arise from the simultaneous presence of exploitation and exploration activities in the same project. The Contribution of a Situated Approach of Projects to Analyse the Hybridization of Exploration and Exploitation This chapter is part of a renewal of the field of project studies (Geraldi and Söderlund, 2018). More precisely, “project studies”, beyond the traditional field of project management, proceed from a broadening of both the levels of analysis mobilized to study projects and the type of research practised. This broadening is reflected in the evolution of a journal located at the heart of the research field, IJPM: “Historically, the IJPM has had a firm grounding in engineering management, construction management and project planning […]. Over the years, the journal has become more rooted in social science and management/organization studies in a broader sense” (Geraldi and Söderlund, 2018, 57). This is also evidenced by how “Cicmil et al. (2006) plead for research on the ‘actuality’ of projects, arguing for a bottom-up, grounded approach to PM theory building” (Lenfle, 2014, 921). This more grounded approach could give a better account of the tensions or even paradoxes encountered in situ by the actors involved in the projects’ life, which the engineering and rationalist tradition of project management has for a long time kept out of its scope. Acknowledging and explaining these tensions would give more substance to the call for a “move from deterministic to explanatory and non-deterministic types of research” in project studies (Padalkar and Gopin’th’s, 2016, cited in Geraldi and Söderlund, 2018). In particular, considering the exploitative or exploratory nature of projects not as a fixed input that overdetermines the behaviour of actors, but as an emergent and negotiated quality that can be subject to conflicting views and hybridization, would constitute a further step towards non-deterministic research on projects. This would also be part of the movement to bring the field of project management and general management theory research closer together, as “project and general management research are increasingly being linked” (Geraldi and Söderlund, 2018). This convergence of research fields proceeds from the growing awareness that projects cannot be studied without taking into account the organizational and institutional context in which they are rooted. As put by Dille and Söderlund (2011, 481), “organizational processes and structures are, to a large extent, affected by the organization’s institutional environments and […] managerial actions are to a considerable extent directed towards the legitimization of the organization’s purpose and actions by actors in its surroundings”. The life of projects does not escape the injunctions of the environment, the power games or the institutional logics that cross the organizations (Engwall, 2003) and generate tensions and uncertainties for the individuals. There have been repeated calls within the field of project management “for more fine-grained treatments of projects in their institutional context” in the lineage of “earlier work by Engwall (2003), Kadefors (1995) and Grabher (2004)” (Dille and Söderlund, 2011, 481). These works converge towards a more nuanced vision of the projects, giving more room to the plurality and indeterminacy of the finalities, to the logics of action and to the interests, of which only a situated approach that would be attentive to multiplying the perspectives and

130  Handbook on innovation and project management

levels of analysis can give an accurate account. It also calls for a temporal lens, concerned with understanding events and bifurcations in relation to long-term temporal dynamics (past and future). This attention is all the more critical in “megaprojects”, “complex” or “vanguard projects”, which are often so-called inter-organizational or inter-institutional projects, defined as “a particular kind of project that needs to respond multiple institutional affiliations” (Dille and Söderlund, 2011). Nuclear projects are emblematic of the latter. To deepen our understanding of such mega or complex projects and to show how they can be at the same time exploitative and exploratory, we rely on an in-depth analysis of a flagship nuclear project of the last decade, the so-called ASTRID project. Designed to be the first French “Generation IV” reactor, the project has been halted in 2019 at the end of the basic design phase.2 The following section describes the research setting and the methodology.

A QUALITATIVE STUDY OF THE ASTRID PROJECT A Contextualized Approach to Projects In line with the contextualized approach of projects, aimed at understanding the nature and dynamics of “the social world of projects” (Geraldi and Söderlund, 2018, 60), we conducted a longitudinal study of the ASTRID project from 2015 to 2021. Our methodology was qualitative and interpretative (Gephart, 2004). We collected evidence from different sources (individual and collective interviews and documentation). Data collection started in 2015 (three and a half years after ASTRID’s launch) and continued through 2021 (about two years after ASTRID’s halt). We conducted 25 semistructured interviews, 23 of which took place during the course of the ASTRID’s project. Thanks to our research programme,3 we had privileged access to key actors of the project and were thus able – a rare thing for a nuclear reactor project – to follow the reactor’s design process “in the making”. Our panel included mainly actors from the former Areva, but also from EDF and IRSN (the French TSO). In 2021, we were also able to interview members of the CEA.4 We thus gained a deep understanding of the project’s nature and dynamics and of how it could differ depending on the role of the actors within the project or at its periphery. Acknowledging the fact that “the focus on the project as the primary level of analysis is relevant but no longer sufficient to understand the growing complexity of projects” (Geraldi and Söderlund, 2018, 62), we articulated the micro, meso and macro levels of analysis. At a micro level, we were attentive to the practices, assumptions, skills and careers of project members and to the nature of relationships between project teams. At a meso level, we questioned inter-organizational relationships, notably the collaboration, coordination and governance mechanisms, in light of the conflicts and power relations. Finally, at the macro level, we took into account the technopolitics (Hecht, 2014) in which ASTRID was embedded. This meant analysing how technological solutions and political decisions have intertwined not only at the time the project was taking place but also in a more distant past, in order to understand how the ASTRID project (as a social organization and a technical infrastructure) has been influenced by the long-term trajectory of nuclear infrastructures. From the outset, the issue of how restarting a design activity after a long interruption affected knowledge and learning processes was central to our study, hence our interest in the exploitation/exploration framework.

Exploration and exploitation in complex projects  131

Replacing the ASTRID Project in Its Technopolitical Context In many ways, France is an “extreme case” in the global energy landscape, since 69 per cent of the electricity mix was nuclear in 2021. In 2022, France (via the semi-public company EDF) operated 56 reactors, making it the most nuclearized country in the world in terms of electricity production. The French civil nuclear sector is structured around a few major organizations: EDF, Framatome/Orano (formerly Areva) and the CEA (the main R&D organization in the French nuclear sector). To these industrial and research organizations were added in 2007 the Nuclear Safety Authority (ASN), an independent authority that sets standards and monitors the entire chain of activity to ensure the highest level of safety, and its Technical Support Organisation (TSO) IRSN. EDF is the leading electricity producer in Europe. For the most part, EDF’s reactors were built in the 1970s, 1980s and early 1990s (Hecht, 2009). The replacement of this ageing installed base has been the subject of much debate for several years, with the construction of an EPR-type reactor in Flamanville (the first of its kind in France5) facing numerous setbacks since 2007. Existing reactors as well as this expected new reactor are all based on the same technology, originally developed by Westinghouse: pressurized water reactors (PWRs). This technology represents about two-thirds of the world’s commercial reactors and 100 per cent in France. However, France has long been a major player in the development of alternative technologies. In particular, it has been at the forefront of research and development in sodium-cooled fast reactors (SFRs). For several decades, this technology has held out the hope of drastically reducing uranium consumption and the production of nuclear waste (among the main criticisms of mainstream established technologies). In parallel with the deployment of PWRs by EDF, the CEA has actively engaged since the 1960s in research on a possible symbiosis between PWRs and SFRs able to close the nuclear fuel cycle by partly reprocessing spent fuel. Research and experimentation materialized in the development of Rapsodie (40 MWth), Phénix (250 MWe) – co-operated from 1973 to 2010 by CEA and EDF – and Superphénix (SPX, 1240 MWe). This quasi-industrial reactor built at Creys-Malville has had a rocky history. Commissioned in 1984, it focused the attention of a then-burgeoning antinuclear movement. Having encountered several highly publicized technical incidents, the government decided to shut it down in 1998 (independently of any recommendation from the safety authority). This decision put a brutal stop to the development of this technology. In 2000, the SFR technology was revived by the GIF6 as one of the six technologies qualified as Generation IV (the older PWRs being Generation II and the EPRs Generation III), whose industrial deployment horizon was expected for the second half of the 21st century. In 2009, at a time when the industry was nurturing great hopes for a “nuclear renaissance” after more than a decade of stagnation, the French government decided to revive sodium technology by entrusting the CEA with the responsibility of a consortium whose aim was to build an “industrial demonstrator” (Gauché, 2012) in 2020: ASTRID. A Brief Description of the ASTRID Trajectory The history of the ASTRID project is embedded in the French Act of 28 June 2006 on sustainable management of radioactive materials and wastes. The discourse of President Chirac who announced the building of a French Generation IV prototype in 2020 is a major milestone (Figure 6.1). The three key players of the French nuclear industry (CEA, EDF and Areva) then

132  Handbook on innovation and project management

Figure 6.1  Key dates and events of the ASTRID project

Exploration and exploitation in complex projects  133

came together to jointly perform R&D studies to investigate innovative solutions for a future SFR. In 2009, the ASTRID project was officially launched, with the French Government entrusting CEA as the programme and project director with the design studies for the reactor. In 2010, the project organization was set up. While CEA had a central position with the “overall responsibility over the general architecture, the core and the fuel” (Gauché, 2012), EDF and the former Areva were important partners from the beginning. EDF was in charge of “specialized support to the owner and operability and safety studies” (Gauché, 2012) and Areva was responsible for the design of the nuclear island. In 2011, 450 workers from five industrial partners contributed to the project. Four years later, 650 people and 13 partners were working on the project (Figure 6.2). The conceptual design phase lasted from 2010 to 2015 and ended with the delivery of a major report7 (CEA, 2015) to the public authorities. The Basic Design phase started in January 2016 and was to continue until 2020. But by the end of 2017, the project underwent a major turnaround after a project process review: the project objectives were revised to foster a “design to cost” approach. This resulted in the abandonment of the initial 600 MWe prototype in favour of a 150 MWe reactor project called NewASTRID. This downsizing aimed to strictly reduce the estimated investment cost. For two years (2018–2019), the managers and engineers worked hard to redesign this downscaled reactor. However, in August 2019, ten years after its launch and after several changes of direction but also many R&D efforts undertaken by the participants, the government finally decided to halt the project.

Source:   adapted from Varaine et al., 2017.

Figure 6.2  ASTRID industrial partners

134  Handbook on innovation and project management

With hindsight, the trajectory of the project is far from straightforward but eventful, marked by dramatic turnarounds (Engwall and Westling, 2004) due as much to external crises as to internal events. The next section describes the actors’ difficulties to define and share the project’s raison d’être throughout its progress. It introduces the category of “hybrid project” to capture this phenomenon and to label a project as being at the same time exploitative and exploratory, with a distribution between exploitation and exploration domains likely to change over time in unpredictable ways.

THE INTERTWINING OF EXPLOITATION AND EXPLORATION WITHIN ONE PROJECT: LESSONS FROM THE ASTRID CASE STUDY ASTRID as a Hybrid Project In the nuclear industry, the exploration/exploitation dichotomy is not so clear-cut. Between the low-power research reactor on the exploration side and the series of commercial/industrial reactors on the exploitation side, there are many intermediaries such as “prototype reactors” or “first-of-a-kind” (e.g. the French EPR). In 2015, our interviews highlighted the difficulty for project participants to link clearly the ASTRID project to an exploratory or an exploitative project and revealed its ambiguous nature. ASTRID fitted into this “grey area” between experimental and mass-produced commercial reactors. Those interviewed faced the same difficulty when it came to defining the mission or the roles of ASTRID. Interestingly, managers from both Framatome and CEA used the same expression (six years apart) to confirm our interpretation of ASTRID as being simultaneously an industrial prototype and an experimental reactor, saying that it was indeed trying to “satisfy dad, mum, grandma, grandpa!” This expression highlighted the many (and often conflicting) objectives of the ASTRID project. It also unveiled how much placing ASTRID in a linear trajectory of technological progress was far from obvious to most of the interviewees. From the very start, the actors were caught between two contradictory injunctions concerning Astrid’s heritage and future. On one hand, the very short deadlines set to complete the design (2020) and the initial vocation of the reactor as an “industrial demonstrator” argued for reusing previous knowledge and technical solutions about SFR, thus for an “exploitative” approach to the project. According to this approach, it made perfect sense to reuse previous SFRs’ legacy (notably SPX) to rationalize the project. Conversely, it was not consistent with the introduction of too many innovations and breakthrough solutions, which could jeopardize the respect of costs and delays. On the other hand, ASTRID’s predecessors (SPX particularly) were a cumbersome legacy, at the social and political levels. The shutdown of the reactor was a trauma for the engineers and researchers who designed, built or operated sodium reactors. To them, SPX was a “success” that was unjustly denied and a “treasure” (in terms of knowledge in research and experimentation) they feared would be lost. Recovering this valuable knowledge before it was lost forever was the tacit agenda of ASTRID’s promoters. At the same time, they knew that no politician would support a reactor that looked like a new SPX. This was forcing project designers to walk a tightrope from the beginning, as a CEA manager told us in 2021: We [had] to disavow the founding father Superphénix … while recovering all the knowledge to be able to do something new and with an industrial objective. So we can see to what extent the system [was] constrained.

Exploration and exploitation in complex projects  135

Its cumbersome and controversial technical heritage made the relationship between ASTRID and previous French SFRs very complicated. Hence the need to introduce major innovations very early on, which would clearly differentiate ASTRID from Superphénix in the eyes of public investors and public opinion. In this perspective, CEA’s rhetoric was very simple: “Why do we develop ASTRID? We do because there are new facts that are worth reopening the case.” We have a new reactor core (it has not been completely proven but it’s globally true). There is a technological breakthrough in terms of core operation between ASTRID and Superphénix. This is fundamental! We even give hope that maybe we won’t have any serious accidents. (Framatome, 2016)

Before the official launch of the project, the three main players (under the leadership of the CEA) agreed on the exploration of innovative solutions, notably the nuclear core. In doing so, the project came close to an exploratory project. From the beginning thus, the project was torn between exploitation and exploration and could not be labelled as either purely exploratory or exploitative. Hence our labelling as “hybrid”. This hybridity had very concrete consequences and was reflected in the very early organizational and technical framing of the project, notably the consortium and the reactor size. If the project organization involved the three main French nuclear institutions, CEA led the project while Framatome and EDF performed support functions. At first glance, entrusting the management of a large-scale “industrial” project to CEA rather than to Framatome or EDF (which were more used to this function) could seem paradoxical. This choice, which gave rise to internal controversies, could yet be explained by the emphasis on innovation, the CEA being historically the organization in the sector most oriented towards experimentation and research. The initial choice of reactor size (600 MWe) also sent a signal that could be interpreted in different ways. It was half the maximum power of Superphénix, which could rule out the idea that ASTRID was the continuation of the “old” technology at a more industrial stage. However, 600 MWe is already a large size in the nuclear industry landscape, which implies the need to produce a lot of electricity in order to amortize the investment cost, and kept ASTRID away from the category of “experimental” reactors. 600 MWe was, literally, a compromise between opposing injunctions, placing ASTRID halfway between well-identified categories of projects to which the actors could have referred. As the project members acknowledged, the initial design choices for ASTRID were made in an attempt to reconcile contradictory demands and expectations. The hybrid nature of the ASTRID project, combining continuity and discontinuity, routine and innovations, exploration and exploitation, is not really surprising for such a large project. It comes close to “complex projects” (Brady and Davies, 2016) that combine “routine” modules and exploratory subsets, calling for adapting management modes to the different “sub-projects”. This complexity was recurring in the discourse of the project stakeholders, including the managers. What is more surprising about the trajectory of ASTRID is that its exploratory dimension tended to reinforce over time. ASTRID’s Identity: A Permanent Construction? The PM literature generally predicts that the degree of freedom of the project, whether routine or exploratory, decreases over time as the actors have converged on options and as the project gets closer to its final deadlines (Midler, 1995). ASTRID has followed a

136  Handbook on innovation and project management

reverse trajectory, with a tendency towards more exploration as the project was unfolding, which reinforced the hybridity and blurred the ultimate purpose and mission of the ASTRID project. Retrospectively, two main episodes have interfered with its trajectory: (1) the decision of CEA to study a breakthrough system in parallel with the classical one in 2015; and (2) the move to a design-to-cost approach followed by the shift to NewASTRID in 2017–2018. Before the launch of the project, the actors agreed on specific project domains (notably the nuclear core), which were worth exploring innovative solutions that we labelled as “deliberate exploration” (Tillement et al., 2019). In spite of these exploratory knowledge domains within the project, the project members considered it as rather exploitative at the macro level: Let’s be clear, there are no breakthrough technological innovations, except perhaps the core […] or the power conversion system (where we hesitate between steam and gas), that’s really innovative, otherwise […] there are no breakthrough innovations […] in the sense that you create a complete new product etc. This is not the case. […] What is the main argument [for focusing our studies on sodium technology]? It’s to say: if we want to develop a new nuclear technology other than sodium, the costs would be exorbitant … we’re not going to revolutionise the design, whereas the interest of sodium technology is precisely that we benefit from experience and don’t have to reinvent everything. […] So no, there are no breakthrough innovations. (Framatome, 2015)

But as the project unfolded, project managers have pushed for breakthrough solutions to be studied, adding “emerging exploration”, i.e. the emergence of “a novel technological solution that was not envisioned at the beginning of the project and for which exploration learning in a specific knowledge domain is required” (Tillement et al., 2019, 547). Mid-2016, things seemed to be coming to a head. Tensions were emerging within the consortium around the CEA’s stated intention to explore the possibility of a gas power conversion system (PCS) instead of the classical steam PCS that had been used on previous SFRs and that had initially been chosen. CEA thus proposed to its partners to take two years to explore this solution and its consequences for the whole project, with a view to making a decision on whether or not to integrate this technology into the detailed design of ASTRID that was to start at the end of 2017. This idea was met with scepticism by the two main other nuclear actors (EDF in particular) due to its radical novelty and the inevitable impact of such an innovation on the budget: EDF doesn’t believe in it! It’s a machine that’s going to be much more expensive, with a lower yield, it’s not viable! (Framatome, 2015)

This decision had a major impact on the organizational and temporal framing of the project: important partners admitted that they were destabilized by this technical choice and the requirement to switch to a typically exploratory mode of operation: CEA […] asked to make a comparison at the end of 2017 between this gas version and the steam one, without explaining how this technical and economic comparison should be made … there are no criteria, no guideline defined today. (Framatome, 2016)

As the project steering practices were very different depending on the exploitative or exploratory nature of the project, the switch of the project to the exploratory side made the usual

Exploration and exploitation in complex projects  137

steering mechanisms suddenly superfluous. Actors thus faced the “floating” atmosphere and the “strangeness” that characterizes most exploratory projects according to Lenfle (2016), a strangeness even more accentuated since, officially, the project must follow its initial course. An engineer from Framatome explained in 2016: We have difficulty knowing how we should organize our studies in a very concrete way, what path we should give them. […] We do many prospective studies, very high-flying studies and at the same time we are still trapped in a work program that was initially called the “basic design” phase, 2016– 2019, it was anchored as a study phase where we start a detailed design in 2018–2019. Today, given the state we are in, the questions we still have, we can clearly not make a detailed design at the beginning of 2018 … in terms of technical maturity, especially on gas, but not only, we are still asking ourselves real questions about the economic viability of the project.

In the last two years of the project, the exploratory dimension was finally more clearly assumed by the programme management, with the passage to the so-called “NewASTRID” project, corresponding to a reduction of the planned power of the reactor to 150 MW. We were redoing a Safety Option File with a gas PCS! And then we finished the basic design, we had to move on to Detailed Design. So we hold a big symposium between all the Astrid project specialists over two days in 2016! And this is where we said: “we don’t fit into the costs that were given to us as the maximum investment cost and we will have to review the total design of the reactor with a ‘design to cost’ approach” … so we had a mix between … there was no discouragement, we bounced back! It’s really bouncing back on a new concept and we completely changed the way we worked when we have switched to “design to cost” … we started to put an Agile management in the Astrid project team … with the Scrum method. We said to all the partners: “we no longer pilot by the specifications as we do in a project, we only pilot by the cost and only the cost interests us”. We no longer had any taboos or constraints (of power, of innovation), we had to get out in time (at the end of 2018) a design to cost project that would allow us to show a reactor. And as this reactor was reduced to 150 MWe, it was not semi-industrial as the 600 MWe, it was a small reactor like our little Phenix, which we had lost. (CEA, 2021)

Again, this turnaround had important effects on the project organization. In terms of schedule first: the detailed design phase was abandoned, replaced by a new round of basic design, and the construction was no longer considered a serious option. On a project management level, this downsizing became a pretext for testing new methods and tools, such as Scrum. Finally, it had effects on the consortium. EDF in particular officially left the project. More importantly, in both cases, the turnarounds had major implications on the purpose, mission and temporal framing of ASTRID. Figure 6.3 shows the evolution of how project participants presented and conceptualized the ASTRID mission and how this coincides with an increasingly distant horizon of industrialization. Emerging exploration resulted in difficulty for most actors to understand the mission of the project, i.e. what ASTRID was really for: There is a question of substance, which is occasionally asked by people but remains unclear: what exactly is ASTRID for? Between the experimental vision that some people of CEA clearly have (for them, it would be a magnificent toy; it would be beautiful!) and the industrial demonstrator vision, the path is narrow. (Framatome, 2016)

The downsizing of ASTRID was an even sharper turnaround as it modified drastically the project’s raison d’être. Its purpose was no longer to be an “industrial demonstrator”, but

138

2012 (rapport CEA) 2013 (Le Coz et al., FR13)

Figure 6.3  Evolution of ASTRID’s goals and timeframes

"Industrial technology demonstrator" (2013)

No construction or industrial envisioned before the 2nd half of the 21st century

2015 (CEA official report; Devictor, ESNII+) 2016 (Vasile, IAEA) 2017, 2018 (Devictor, SFEN; Rodriguez, GIF) "industrial prototype« "technological integration prototype "Technological enabling the demonstration of safety demonstration reactor (a and operation on an industrial scale step before a First Of A ASTRID "is a technological 2018, 2019 of 4th generation RNR-Na" (2012) Kind)" demonstrator and is not a Construction and "Astrid must therefore demonstrate "technological First Of A Kind of a New ASTRID industrial deployment on an industrial scale the validity, by demonstrator« commercial reactor". timeframe: 2020, 2040 qualifying them, of the innovative Tool for experimentation and options in the areas of progress qualification identified, particularly safety and "little Phénix« operability." (2012) Construction and industrial deployment timeframe: 2030, Mid-21st century

"precursor of a first of a kind of the commercial reactor"

"prototype"

2009 (Rouault et al., FR09; Camarcat et al., FR09)

Exploration and exploitation in complex projects  139

rather to serve as a basis for the qualification of certain materials and for technological experiments: We kept a certain logic in our approach to move towards a power reactor while doing low power because we changed the functions of the low power reactor. It was going to be much more of an experimental reactor in support of the qualification of components. (CEA, 2021) ASTRID 150 […] was an experimental prototype. The aim […] was to validate the innovations for the future. So we changed the role a little. (CEA, 2021)

The “change of function” or “role” of the project itself was clearly assumed, confirming that what ASTRID was made for had never been really decided, shared or stabilized. This leads us to emphasize what we propose to call the “project identity”. Far from referring only to the goals and objectives of the project as defined ex-ante at its outset and stable during its course, this concept rather refers to the collective process of (re)defining the identity of the project as a whole. The case of ASTRID shows that it is all the more important since the distribution between exploration and exploitation activities evolved in time in an unpredictable way, as evidenced by the project actors’ surprise in the face of the turnarounds. This confronted the project participants with similar tensions to the ones that managers often experience at the firm level in front of unforeseeable uncertainties. Hybridization in the Face of Project Stakeholders’ Agenda and Power Relationships These tensions throughout the project’s course were mirrored in the ambiguity around the project identity at the stakeholders’ level. This is key to explaining ASTRID’s astonishing trajectory. Initially (2009), ASTRID was the result of a three-way marriage between the major players of the nuclear “French team” (Framatome). The engagement of these three actors was important as a guarantee of the robustness of the project. CEA was aware of the unusual character (in the eyes of the public and the other two “giants”) of their position as project leader. They knew that they had to devote significant efforts to build up their legitimacy in that function. This was reflected, in part, by the over-investment of the project team (at least from 2016) in the tools and techniques of classical rationalized project management (Reverdy, 2021) and the insistence of CEA managers on that point: Technically it was very well organised! Extremely well organised! There was a very strong dynamic, um … the project was rather … in good hands, it was progressing well, technically the people who were steering it were really at the right level. (CEA, 2021)

This contrasted with the statements of Areva’s engineers, who confessed to being puzzled by the way the project was managed and governed. From the outset, the relationships were tense, notably between EDF and CEA (a lot less with Areva). The innovative proposal on the core was really backed by the project, so it became the Astrid’s reference core very quickly. But still, we had to face enormous opposition; EDF was very opposed, it fought a trench war for two years in terms of R&D because it did not want the CEA to lead this innovation! For obscure reasons! (CEA, 2021)

140  Handbook on innovation and project management

CEA was constantly navigating on a ridge, torn between its internal teams, who were pushing for innovation, and Framatome and EDF, who defended “classic”, well-known technical solutions. From the start, the project’s trajectory was affected by the complexity of making compromises between irreconcilable imperatives. Lacking a clear and shared backbone allowing the actors to make sense of the whole project and coordinate their actions, the project was exposed to becoming a playground for tactical behaviours and choices on the part of the institutions involved. We were always on a crest line! Do we really stick to Real Engineering and say: “OK, I have Superphénix, so I’ll do the same thing again, that’s it” (which we could no longer do because safety was evolving and things we did twenty years ago were no longer acceptable now), or do I switch to: “look, we’re letting go of the bridles, we’re pushing innovations anyway, we’re going to explode the cost, we’re going to reduce the TRL and we’re going to do something that will be unfeasible”! And we were always on this ridge all the time, on the whole Astrid project, [oscillating between] “well, we’re keen to carry on because it’s a major innovation, let’s see where it takes us”, and sticking to something more … realistic. So we get yelled at from both sides! The CEA R&D people yelled at us, saying “every time I propose something innovative, you don’t take it, you just have to do Superphénix” and the engineering people said “stop dreaming with your stuff, we’ll never be able to manage it or we’ll be two years behind in the studies!” So we were always torn between these two poles, doing innovation or real engineering. (CEA, 2021)

Framatome and EDF followed a mostly exploitative logic, thus pleading for many existing solutions, which ASTRID would make it possible to qualify on an almost industrial scale. The tensions between the exploitative and exploratory logics point to inter-temporal tensions, the temporalities associated with ASTRID’s lifecycle being key in that story. CEA proposed quite a few innovations [but] we found ourselves – this is a bit of a standard for the ASTRID project – between a short-term vision and a more innovative vision! And if certain innovative choices had been made perhaps earlier on, we would have had time to develop them. (CEA, 2021)

ASTRID’s trajectory was punctuated by “self-legitimizing” decisions that were not dictated by consideration of the objective interest of the project, but rather by an implicit agenda of reinforcing the project participants’ position and legitimacy. The first decision was that of the government to set a very short deadline (start construction in 2020). Consequently, the use of sodium technology became almost compulsory. Given the date, the technology was already chosen: a sodium reactor! Given the maturity of other concepts, if something was to be done in 2020, it could only be a sodium reactor, nothing else! (CEA, 2021)

This aligned with the tacit agenda of CEA to preserve the skills developed on SFR by launching a new project almost concomitantly with the closure of Phénix: So it restarts all at once, trying to recover the definitive loss of competences that was going to happen very quickly because the Phénix reactor was going to stop definitively in 2009! It was scheduled to shut down! So […] we had to start again on something otherwise everything would collapse and we would lose our skills! (CEA, 2021)

Exploration and exploitation in complex projects  141

Such advocacy-driven choices (in this case, reusing and preserving an already acquired skill set) are reminiscent of the “garbage can” decision-making model (Cohen et al., 1972), in which solutions generally pre-exist the questions posed and frame the process of problem formulation. In some ways, the lack of a clear identity for ASTRID inevitably led to this type of situation. We can interpret in a similar way the decision to impose the exploration of the gas PCS. This choice, beyond its potential intrinsic interest in terms of R&D, can be understood as allowing the CEA to push the ASTRID project towards a more exploratory identity, by introducing, on a major component, a solution with a very high degree of unknown, which would definitively remove the “spectre” of Superphénix in the eyes of the politicians: CEA’s speech is very simple: “why do we make Astrid? Because this is definitely no more Superphénix! It is not the same core […] and we have no more water.” So you say that to politicians. (Framatome, 2015)

The very short deadlines, initially favourable to CEA’s choice of sodium, gave an obvious argument to Framatome and EDF to push for a more rationalized approach to project management. Then pushing the project towards more exploration was a way for the CEA to regain legitimacy as a project leader and an industrial architect. This is how Framatome partly explained the stance of the CEA, eager to bring the project back to familiar territory: Basically, the architect designer was rather an organization specialized in R&D. So obviously the technological object “gas cycle” is much more fun than the steam turbine that we buy at Alstom from the catalogue! (Framatome, 2016)

CEA’s partners perceived it as a research organization rather than an industrial actor. One CEA interviewee lamented this persistent (and in his view largely unfair) image: In the end, it’s always the same battle: Framatome always says: “CEA people are sweet dreamers; they only do R&D and don’t know how to manage a project!” (CEA, 2021)

The transition to NewASTRID, with a power of 150 MWe, confirmed the end of ASTRID as an “industrial demonstrator”. Although brutal for most engineers, it had the merit of clarifying the project’s identity by definitively siding with exploration. According to a member of the CEA interviewed: We were back in a comfort zone; […] we were back in a [normal] logic! We were no longer on the crest path, this tool [NewASTRID] was entirely dedicated to validation, to qualification to help with future power reactors, and it was much easier to work because we were no longer oscillating back and forth between two options. (CEA, 2021)

Even if it cannot alone explain the halt of ASTRID, this enduring ambiguity of the project’s identity, and the tensions that resulted from it, made the project vulnerable to internal tensions but also to external pressures. Officially, the halt of the ASTRID programme was justified by the lower-than-expected tensions in the uranium market, making a less fuel-intensive technology less needed. The lack of alignment of the project stakeholders around a common vision,

142  Handbook on innovation and project management

by never allowing a shared purpose and identity to emerge, deprived ASTRID of a capacity to resist a reversal of the external situation. Nevertheless, it would be wrong to consider ASTRID as a failure, insofar as the ten years of design work carried out have contributed to maintaining and developing knowledge and innovative design tools and practices that could be reused for future projects, whether in the field of sodium reactors or in another field.

DISCUSSION The observed trajectory of the ASTRID project did not follow the classic sequential course predicted in the traditional project management literature and prescribed by project managers (where the detailed design follows the basic design which follows the preconceptual design), nor did it evolve towards more exploitative objectives. Quite the opposite. It rather followed a whirlwind trajectory (Akrich et al., 2002), which cannot be attributed to a major external crisis (Fukushima does not solely explain ASTRID’s halt) nor to major conflicts between project partners. The turnarounds rather resulted from a series of gradual and quiet decisions at different levels (Engwall and Westling, 2004), from public authorities to programme and project management, which made it more and more difficult for project members to align on a shared interpretation of the ASTRID’s mission, and thus to agree on the best technical options and project organization. Even if the ASTRID project can be seen as an extreme and atypical case, hence the results as hardly generalizable, we believe it highlights factors that are largely invisible in more ordinary projects or circumstances. This is especially true given our situated and longitudinal research approach. The first important contribution is the notion of “project identity” itself, which stems from our observations of the dynamic entanglement of exploration and exploitation within a single project. The second contribution, both theoretical and practical, focuses on the significance of “being nuclear” (Hecht, 2014) for a project and questions how the “nuclearity” of a project may affect its trajectory and management. The Concept of “Project Identity” Over the years, the PM literature has proposed many projects’ typologies, such as “megaprojects” (Flyvbjerg, 2014), “routine” or “exploratory projects” (Lenfle, 2014) or more recently “complex” (Brady and Davies, 2014) or “vanguard projects” (Laurila and Ahola, 2021). Apart from identifying the main traits of such or such type of project, these categories help to explain why certain types of project encounter systematically the same pitfalls, to better define the relations between a given type of project and risks or uncertainties, or to propose adapted ways of managing and steering the project depending on its type. The study of ASTRID led to the construction of a new category: “hybrid projects”. This category was meant initially to capture how a single project could combine exploitation and exploration goals, the distribution and balance of which were evolving over time in unforeseen and unpredictable ways. But in the end, the main contribution of this case study is to draw our attention to the notion of “project identity”, since hybridity ultimately reflects the absence of a stable and shared identity. “Project identity” is a conceptual label, which is grounded in data reality (Corbin and Strauss, 1990) and consistent with a processual view of organizational identity (Schultz, 2016). When project management scholars take care to typify different categories of projects, they are (indirectly) talking about the identity of a project. Often, however (though

Exploration and exploitation in complex projects  143

this should be nuanced with the emergence of a more grounded and processual approach to projects), they implicitly assume that this identity is well known, well understood and shared among project managers and stakeholders, from the project launch to its completion. The ASTRID case forcefully reveals the extent to which a project identity is permanently constructed and shaped, through negotiations and struggles between the members of the project themselves but also external stakeholders (notably the political actors and the public authorities). It highlights the potentially disputed nature of a project’s identity. The goals, status and fundamental parameters of the project such as technical options, the project organization or the project schedule can give rise to contradictory interpretations, well after its early framing phase. Even more problematically, this can lead to attempts by some actors to redefine the mission of the project as a whole. This echoes the work of Engwall and Westling (2004) who underline and discuss the importance of enacting on a collective level “one conceptualisation of the project”, i.e. a shared and legitimate definition of the mission and content of the project, in order to be able to manage it. Adopting a methodology very close to ours (a longitudinal and in-depth qualitative case study), they describe a project in which the actors succeed (after a peripety) in agreeing on one conceptualization. It then became possible for project participants to devote their efforts to problem-solving (rather than problem-setting) and to change “the project’s mode from one dominated by ambiguity to one dominated by uncertainty” (Engwall and Westling, 2004, 1570). In our case, ambiguity was on the contrary reinforced over time, which project participants expressed well when explaining that they were not really able to understand the sense of some technical decisions and more globally what “ASTRID was really for”. Two important implications follow from this result. Firstly, this confirms the importance for project management to put in place the organizational processes and governance mechanisms that enable project stakeholders to collectively (re)enact a shared and legitimate project identity, which aligns with its dominantly exploitative, exploratory or hybrid nature. The identity of a project is the result of an alignment work, which is very complex since it must be carried out simultaneously at several levels: between the main project partners, between the different phases of the project and between the project and its environment (Tillement and Garcias, 2021). To our knowledge, this alignment is little addressed in the PM literature, as research on projects generally treats the identity of the project as an almost invisible input. Secondly, our research highlights the extent to which “project identity” is a temporal concept. Obviously, the project identity (as the professional identity) is never fixed once and for all. Following the famous words of Engwall (2003), “no project is an island”, no project is “off-the-ground” either. “Project practices relate to long-term institutions” (Engwall, 2003) and organizations, which embed histories and memories of humans and non-humans, of technical objects and social organizations. Our findings show well how much ASTRID’s distant and near past and future have affected the choices, including the most technical ones, and finally hindered the possibility of constructing a common narrative about the purpose of the project, its usefulness and the place it was called upon to occupy in the long term of nuclear history. In the absence of this shared narrative, the project could only whirl around, becoming more and more chimeric. This confirms that “not only is the context created for and around projects a key success factor, but it also largely determines how projects are done, and their impact and legacy” (Geraldi and Söderlund, 2018, 62). We believe this is all the more true in the case of nuclear projects.

144  Handbook on innovation and project management

What “Being Nuclear” Means for a Project “Megaprojects” are widely documented in the literature since Flyvbjerg’s seminal work, which constitutes a very popular framework to analyse the “pathologies” of large projects. In many respects, ASTRID has characteristics that place it in the category of megaprojects: its gigantic size, the multiplicity of stakeholders, its eminently political dimension, the imperative need to convince public investors and the very ambitious nature of the initial plans in terms of budget and schedule. By adopting this view, one could be led to conclude that the explanation for ASTRID’s trajectory (and its final stop) lies in the “disaster gene” inherent to most megaprojects according to Flyvbjerg (2014). However, recent research has pointed out the limitations of this approach in the case of nuclear megaprojects, which require, more than any other, “a vital contextualization” (Lehtonen, 2021). By this, Lehtonen refers to the necessity for nuclear projects to align “the various interests of the involved key stakeholders and in ensuring the compatibility of these projects with the material and institutional environment that characterizes the modern Western society” (Lehtonen, 2021, 1348). Unlike emblematic megaprojects such as the Sydney Opera House, or even the Channel Tunnel, nuclear megaprojects only makes sense if they are not isolated (or “one-shot”) projects. In order to be “successful”, nuclear megaprojects must be part of a trajectory, where a new project is simultaneously consistent with its technological heritage within a family of previous projects and the projection towards a desirable future. In this condition, it becomes possible to draw the lessons from previous projects so as not to be in a perpetual “blank page” regime (which would be economically unsustainable) while providing innovations compatible with the project’s mission and environment. In particular, any setbacks encountered (and classically so) on the first of a series can benefit, in a logic of learning and continuous improvement, the “nth-of-a-kind”. Their “success” thus depends on their ability to “amortize” the cost of the inevitable explorations and errors of the first project, thanks to economies of scale, learning and repetition. In addition (or in relation) to the difficulty in constructing a shared project identity, one of the explanations for the halting of ASTRID probably lies in the impossibility for its promoters and designers to align both these efforts of capitalization and projection. In spite of the many “lessons learned”, they did not succeed in aligning the stakes and interests of ASTRID with those of its broader environment (Geraldi and Söderlund, 2018). We believe that this difficulty goes far beyond the framework of ASTRID and concerns the majority of nuclear projects. The nuclear industry is full of hybrid projects, of the “first-ofa-kind” type, that capitalize on existing knowledge while introducing exploratory ambitions. These projects are particularly dependent (and this is probably not the case for all megaprojects) on the alignment of their own local infrastructure with the global nuclear infrastructure and on the associated technopolitical dynamics (Tillement and Garcias, 2021). They require constant and dynamic alignment work in order to adapt in the face of the internal and external contingencies that punctuate the projects’ life. This is all the more important because of another characteristic of nuclear projects, their very long timeframes, of the order of decades, which far exceed the time of political decisions. This long time span is combined with the very strong internal inertia of these projects, whose initial choices prove to be very structured, often irreversible or very difficult to reverse, of which the French EPR is a blatant example. Nuclear projects thus require being supported and positioned in a long-term vision and strategy, both by their managers and the government. The absence (or the slightest presence)

Exploration and exploitation in complex projects  145

of a state capable of playing the role of both arbitrator and strategy-maker (identified as one of the reasons for the success of the Generation II nuclear programme) for more than two decades has undoubtedly been detrimental to the French nuclear industry and its projects (ASTRID but also the EPR). This contributed to the growing ambiguity faced by the project participants and to the emergence of tensions between them, which, in the absence of a recognized and legitimate arbiter, persisted. Major issues regarding electricity production, following the Ukraine war, have marked 2022, forcing the French government to make decisions and finally offer a long-term vision to the nuclear sector. ASTRID may have arrived too soon, weakening or undermining the CEA’s great plan to safeguard, through practice, knowledge that was considered valuable and built up in the long-term, as one project member (CEA) sadly concluded: Generation IV reactors … the 4th generation is postponed to the end of the century … ASTRID arrived too soon! Like Concorde. That’s how it is with technical choices, it’s always complicated [to know] when to go ahead or not […] there is no strategy on GenIV [now]. We’re sitting on our treasure, waiting for it to be worthless, and then we’ll say [deep sigh].

In the coming years, it will be very interesting to observe if and how the nuclear industry can once again become a major and legitimate actor in the face of the major challenges ahead. Undoubtedly, its legitimacy and its future depend on its ability to carry out hybrid projects.

CONCLUSION This chapter analysed the ASTRID project not as a static object but rather as embedded in a temporal trajectory influenced both by internal processes and project members’ actions and by external forces related to its environment. We showed that a project can combine both exploratory and exploitative features and that the distribution and balance between exploratory and exploitative activities may change over time in an unpredictable way. As the project unfolds, new radically innovative knowledge domains or activities emerge, making the project increasingly exploratory. To make things even more complex, these emerging exploratory activities do not necessarily come to replace previous ones (either exploitative or exploratory) but can co-exist with them for some time. The resulting trajectory is far from linear but rather a whirlwind (Akrich et al., 2002). This opens major challenges for managing such “hybrid projects”. Among them is the possibility for these projects to face increased uncertainties and ambiguities associated with complexity and hybridity: if not perceived and monitored, the risk is blurring the goals, tasks and even the project’s raison d’être.

ACKNOWLEDGEMENTS We would like to thank the ANR (French National Research Agency) and the Investissement d’Avenir programme that funded the AGORAS research project in which this study has been carried out (Grant ANR-11-RSNR-0001). For their helpful comments and advice, we want to express our gratitude to the editors, and especially to our colleagues Sylvain Lenfle and Andrew Davies. Finally, a special and huge thank you goes to our informants from Framatome and CEA for their help, openness, reflexivity and patience.

146  Handbook on innovation and project management

NOTES 1. Advanced Sodium Technological Reactor for Industrial Demonstration. 2. This study has already resulted in two journal publications (Tillement et al., 2019; Tillement and Garcias, 2021). Readers who wish to know more about the methodology used (including the data collected) can refer to these papers. In addition, following these publications, three interviews were conducted with two technical directors of the project from the CEA (in June/July 2021), who wished to react to the previous articles. These interviews allowed us to obtain additional information that was particularly useful for a more exhaustive vision of the project’s trajectory. 3. This work was supported by the ANR and Investissement d’Avenir programme through the AGORAS project (Grant ANR-11-RSNR-0001). Ex-Areva and IRSN were partners in this project. 4. Commission for Atomic Energy and Alternative Energy. 5. The Olkiluoto EPR in Finland has started in March 2022 and two are operated in China. 6. Generation IV International Forum: launched in 2000 by the American DOE, it gathered 12 countries (including France) to renew and stimulate research on future nuclear technologies worldwide. 7. This dossier includes notably “the safety option report for the water / steam power conversion cycle, the design choices justification, the first systems and components technical specifications, ASTRID’s preliminary qualification plans for critical components, a preliminary ASTRID Cost estimation, preliminary Planning for implementation” (Varaine et al., 2017).

REFERENCES Abernathy, W.J. (1978). The productivity dilemma. Baltimore: Johns Hopkins University Press. Abernathy, W.J. and Clark, K.B. (1985). Innovation: Mapping the winds of creative destruction. Research Policy, 14(1), 3–22. Ahuja, G. and Morris Lampert, C. (2001). Entrepreneurship in the large corporation: A longitudinal study of how established firms create breakthrough inventions. Strategic Management Journal, 22(6–7), 521–543. Akrich, M., Callon, M., Latour, B., and Monaghan, A. (2002). The key to success in innovation part I: The art of interessement. International Journal of Innovation Management, 6(2), 187–206. Brady, T. and Davies, A. (2014). Managing structural and dynamic complexity: A tale of two projects. Project Management Journal, 45(4), 21–38. Brady, T. and Davies, A. (2004). Building project capabilities: From exploratory to exploitative learning. Organization Studies, 25(9), 1601–1621. Braun, T. and Lampel, J. (Eds.). (2020). Tensions and paradoxes in temporary organizing. Emerald Publishing. Burns, T. and Stalker, G.M. (1961). Mechanistic and organic systems of management. In T. Burns & G.M. Stalker (Eds.), The management of innovation (pp. 96–125). New York: Oxford University Press. CEA. (2015). “Avancées des recherches sur la séparation-transmutation et le multi-recyclage du plutonium dans les réacteurs à flux de neutrons rapides,” Décret n° 2013–1304 du 27 décembre 2013 pris pour application de l’article L. 542-1-2 du code de l’environnement et établissant les prescriptions du Plan national de gestion des matières et des déchets radioactifs. Official Report. Christensen, C.M. (1997). The innovators dilemma: When new technologies cause great firms to fail. Boston, MA: Harvard Business School Press. Cicmil, S., Williams, T., Thomas, J. and Hodgson, D. (2006). Rethinking project management: researching the actuality of projects. International journal of project management, 24(8), 675–686. Clark, K.B. and Fujimoto, T. (1989). Lead time in automobile product development explaining the Japanese advantage. Journal of Engineering and Technology Management, 6(1), 25–58. Clark, K.B. and Wheelwright, S.C. (1992). Organizing and leading “heavyweight” development teams. California Management Review, 34(3), 9–28.

Exploration and exploitation in complex projects  147

Cohen, M.D., March, J.G., and Olsen, J.P. (1972). A garbage can model of organizational choice. Administrative Science Quarterly, 17(1), 1–25. Cohen, W.M. and Levinthal, D.A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128–152. Corbin, J. M., & Strauss, A. (1990). Grounded theory research: Procedures, canons, and evaluative criteria. Qualitative Sociology, 13(1), 3-21. Davies, A. and Brady, T. (2016). Explicating the dynamics of project capabilities. International Journal of Project Management, 34(2), 314–327. Davies, A., Manning, S., and Söderlund, J. (2018). When neighboring disciplines fail to learn from each other: The case of innovation and project management research. Research Policy, 47(5), 965–979. Dille, T. and Söderlund, J. (2011). Managing inter-institutional projects: The significance of isochronism, timing norms and temporal misfits. International Journal of Project Management, 29(4), 480–490. Eisenhardt, K.M. and Tabrizi, B.N. (1995). Accelerating adaptive processes: Product innovation in the global computer industry. Administrative Science Quarterly, 40, 84–110. Engwall, M. (2003). No project is an Island: Linking projects to history and context. Research Policy, 32(5), 789–808. Engwall, M. and Westling, G. (2004). Peripety in an R&D drama: Capturing a turnaround in project dynamics. Organization Studies, 25(9), 1557–1578. Flyvbjerg, B. (2014). What you should know about megaprojects and why: An overview. Project Management Journal, 45(2), 6–19. Frederiksen, L. and Davies, A. (2008). Vanguards and ventures: Projects as vehicles for corporate entrepreneurship. International Journal of Project Management, 26(5), 487–496. Gauché, F. (2012). Generation IV reactors and the ASTRID prototype: Lessons from the Fukushima accident. Comptes Rendus Physique, 13(4), 365–371. Gephart Jr, R.P. (2004). Qualitative research and the Academy of Management Journal. Academy of Management Journal, 47(4), 454–462. Geraldi, J. and Söderlund, J. (2018). Project studies: What it is, where it is going. International Journal of Project Management, 36(1), 55–70. Geraldi, J., Söderlund, J., and van Marrewijk, A. (2021). Bright and dark spots in project studies: Continuing efforts to advance theory development and debate. Project Management Journal, April. doi:10.1177/87569728211004064 Grabher, G. (2004). Temporary architectures of learning: Knowledge governance in project ecologies. Organization Studies, 25(9), 1491–1514. Hecht, G. (2014). Being nuclear: Africans and the global uranium trade. MIT Press. Hecht, G. (2009). The radiance of France: Nuclear power and national identity after World War II. Boston: MIT Press. Henderson, R.M. and Clark, K.B. (1990). Architectural innovation: The reconfiguration of existing product technologies and the failure of established firms. Administrative Science Quarterly, 35(1), 9–30. Kadefors, A. (1995). Institutions in building projects: Implications for flexibility and change. Scandinavian Journal of Management 11(4), 395–408. Kanter, R.M. (1990). When giants learn to dance. Simon and Schuster. Katila, R. and Ahuja, G. (2002). Something old, something new: A longitudinal study of search behavior and new product introduction. Academy of Management Journal, 45(6), 1183–1194. Kogut, B. and Zander, U. (1992). Knowledge of the firm, combinative capabilities, and the replication of technology. Organization Science, 3(3), 383–397. Laurila, J. and Ahola, T. (2021). Vanguard projects as relay races: A historical case study on the building of Eurocan pulp and paper mill, 1965–1970. International Journal of Project Management, 39(5), 520535. Lavie, D., Stettner, U., and Tushman, M.L. (2010). Exploration and exploitation within and across organizations. Academy of Management Annals, 4(1), 109–155. Lehtonen, M. (2021). NEA framing nuclear megaproject “pathologies”: Vices of the modern western society? Nuclear Technology, 207(9), 1329–1350. Lenfle, S. (2008). Exploration and project management. International Journal of Project Management, 26(5), 469–478.

148  Handbook on innovation and project management

Lenfle, S. (2014). Toward a genealogy of project management: Sidewinder and the management of exploratory projects. International Journal of Project Management, 32(6), 921–931. Lenfle, S. (2016). Floating in space? On the strangeness of exploratory projects. Project Management Journal, 47(2), 47–61. Lenfle, S. and Loch, C. (2017). Has megaproject management lost its way? Lessons from history. In B. Flyvbjerg (Ed.), The Oxford handbook of megaproject management. Oxford, UK: Oxford Handbooks. Leonard‐Barton, D. (1992). Core capabilities and core rigidities: A paradox in managing new product development. Strategic Management Journal, 13(S1), 111–125. Loch, C.H., DeMeyer, A., and Pich, M. (2011). Managing the unknown: A new approach to managing high uncertainty and risk in projects. John Wiley & Sons. March, J.G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71–87. Midler, C. (1995). “Projectification” of the firm: The Renault case. Scandinavian Journal of Management, 11(4), 363–375. Nerkar, A. (2003). Old is gold? The value of temporal exploration in the creation of new knowledge. Management Science, 49(2), 211–229. Obstfeld, D. (2012). Creative projects: A less routine approach toward getting new things done. Organization Science, 23(6), 1571–1592. O’Reilly III, C.A. and Tushman, M.L. (2013). Organizational ambidexterity: Past, present, and future. Academy of Management Perspectives, 27(4), 324–338. Pich, M.T., Loch, C.H., and Meyer, A.D. (2002). On uncertainty, ambiguity, and complexity in project management. Management Science, 48(8), 1008–1023. Raisch, S. and Zimmermann, A. (2017). Pathways to ambidexterity: A process perspective on the exploration–exploitation paradox. In W.K. Smith, M.W. Lewis, P. Jarzabkowski, and A. Langley (Eds.), Handbook of organizational paradox (pp. 315–332). Oxford University Press. Reverdy, T. (2021). Antimanuel de management de projet: composer avec les incertitudes. Dunod. Rosenkopf, L. and Nerkar, A. (2001). Beyond local search: Boundary‐spanning, exploration, and impact in the optical disk industry. Strategic Management Journal, 22(4), 287–306. Schultz, M. (2016). Organizational identity, change and temporality. In M. Pratt, M. Schultz, B.E. Ashforth and D. Ravasi (Eds.), The Oxford handbook of organizational identity (pp. 93–105). Oxford University Press. Shenhar, A.J. (2001). One size does not fit all projects: Exploring classical contingency domains. Management Science, 47(3), 394–414. Shenhar, A.J. and Dvir, D. (1996). Toward a typological theory of project management. Research Policy, 25(4), 607–632. Slawinski, N. and Bansal, P. (2017). The paradoxes of time in organizations. In W.K. Smith, P. Jarzabkowski, M.W. Lewis, and A. Langley (Eds.), The Oxford handbook of organizational paradox (pp. 373–392). Oxford University Press. Söderlund, J. (2011). Pluralism in project management: Navigating the crossroads of specialization and fragmentation. International Journal of Management Reviews, 13(2), 153–176. Sommer, S.C. and Loch, C.H. (2004). Selectionism and learning in projects with complexity and unforeseeable uncertainty. Management Science, 50(10), 1334–1347. Stuart, T.E. and Podolny, J.M. (1996). Local search and the evolution of technological capabilities. Strategic Management Journal, 17(S1), 21–38. Tillement, S. and Garcias, F. (2021). ASTRID, back to the future: Bridging scales in the development of nuclear infrastructures. Nuclear Technology, 207(9), 1291–1311. Tillement, S., Garcias, F., Minguet, G., and Charue-Duboc, F.C. (2019). Disentangling exploitation and exploration in hybrid projects: The case of a new nuclear reactor development. Project Management Journal, 50(5), 538–553. Tushman, M.L. and O’Reilly, C.A. (1997). Winning through innovation: A practical guide to leading organizational change and renewal, III. Boston: Harvard Business School Press. Varaine, F., Rodriguez, G., Settimo, D., Hamy, J.M., Hayafune, H., Romdhane, S., ... Mazel, J. (2017). Status of the astrid sodium fast reactor project from conceptual design to basic design phase. In International Congress on Advances in Nuclear Power Plants (ICAPP 2017). International Congress on Advances in Nuclear Power Plants (ICAPP 2017), April.

7. Innovation projects in a global world: bridging global innovation management and project management Christophe Midler and Sihem BenMahmoud-Jouini

INTRODUCTION The globalization of projects is not a new topic in project management literature. It has been mainly addressed from the perspectives of resource diversity and geographical distribution. Indeed, definitions of global projects emphasize team members working in many locations across country borders dispersed geographically (Aaltonen et al., 2008), belonging to different national systems separated by geographical and potentially significant cultural and institutional distances (Ainamo et al., 2010; Aarseth et al., 2014) associated with language as well as time zone differences (Binder, 2007). Therefore, the research focus has been mainly on managing the project itself, i.e. its complexity (Aarseth et al., 2013; Yang et al., 2015), multicultural teams (Bredillet et  al., 2010; Henderson et  al., 2018; Chevrier, 2013), geographic distribution (Reed and Knight, 2010; Hosseini and Chileshe, 2013), procurement (Tracey and Neuhaus, 2013; Kardes et al., 2013), stakeholders (Aaltonen et al., 2008; Aaltonen and Sivonen, 2009), etc., rather than the relationships between the projects and the strategy or the organization of the parent firms. This chapter addresses these relationships and more specifically, according to the innovation focus of the book, the relationships between global innovation projects (GIPs) and the global innovation management (GIM) of multinational corporations (MNCs). We will focus on global projects with significant innovation content and investigate how they fit and generate the global innovation strategies of the firms involved. Indeed, these relationships between GIPs and GIM of MNCs deserve to be studied for theoretical as well as empirical motivations. On one hand, the increasing trend of projectification of the firms (Midler, 1995; Schoper et al., 2018) emphasizes the necessity to further study the link between temporary and permanent organizations (Bakker et al., 2016) which has been mainly studied through project portfolios (Cleland and Gareis, 2006; Binder, 2016; Chiesa, 2000) or resources allocation (Bredin and Söderlund, 2011). On the other hand, the internationalization of companies has been growing continuously through the expansion of markets as well as resources (globalization of R&D, etc.). However, the execution of global innovation projects as well as the management of global value chains by MNCs still raise critical issues. Regarding resource allocation, project-based organizations (PBOs), project-supported organizations (PSOs) or project-networked organizations (PNOs) (Lundin et al., 2015) share a common characteristic or issue with MNCs, i.e. sharing tangible or intangible assets across separate units. Indeed, an MNC is composed of a network of units or subsidiaries that generate new knowledge diffused through intra-firm cooperation and community-stimulating 149

150  Handbook on innovation and project management

innovation within the overall MNC (Birkinshaw and Lingblad, 2005, Kacpercyzk et al., 2015; Hu et al., 2017). Knott and Turner (2019) argue that the headquarters of an MNC can create value by favouring inter-subsidiaries dynamics as in the case of inter-project organizational learning (Brady and Davis, 2004; Midler, 2013). However, both streams of research, i.e. global innovation project management and global innovation management, have developed independently. We argue that bridging GIM which focuses on the company level (its strategy and organization) and GIPs which focus on the project level is potentially fruitful. Indeed, the innovation strategy of a firm is mainly implemented through projects (e.g. NPD projects, etc.) and reciprocally, innovation projects play an important role in the definition of the firm’s innovation strategy. In this chapter, we will start by highlighting the issues raised by the management of innovation by MNCs and the impact on global innovation projects. Indeed, the globalization of innovation management is a growing phenomenon (Ben Mahmoud-Jouini et al., 2015) that impacts the innovation strategies of firms (Meyer et al., 2011) and their organizational dynamics by inducing a more international R&D footprint (Von Zedwitch and Gassman, 2002) and resulting in new roles assigned to subsidiaries, as well as to headquarters and corporate functions. Literature has highlighted several models, i.e. transnational and meta-national models (Bartlett and Ghoshal, 1989; Doz et al., 2001) corresponding to specific innovation processes. One can assume that this phenomenon will have an important impact as well on global innovation projects. Then we will address global innovation projects, i.e. the empirical space in which MNCs’ global strategies and processes are executed. It is therefore through their analysis that one can enlighten the scope and obstacles of innovation processes within MNCs and understand and detail notions such as “reverse innovation”, for example. Furthermore, projects are a key component of organizational learning in firms. It is therefore through their analysis that we can understand the dynamics of knowledge within permanent organizations. Therefore, one can assume that managing global innovation projects enables the execution of the global innovation management of MNCs and its sustainability and evolution.

GLOBALIZATION OF INNOVATION MANAGEMENT The field of international management has generated a large amount of research and has led to several models of multinational companies (Vernon, 1966; Bartlett and Goshal, 1989; see Forsgren, 2013 for a review). Some work has more specifically focused on the globalization of innovation strategies and processes (Doz et al., 2001). The Globalization of Innovation Strategies In the past, innovation was primarily local happening in a specific place. The Philips brothers developed their innovation in their town of Eindhoven, in the southeast of the Netherlands, which was hardly predestined to become a hotbed of innovation. In most cases, the location was motivated by favourable local or national circumstances (Porter, 2000). For example, the textile industry in the Rhine Valley led to a need for dyes, which led to early innovations in the German and Swiss chemical and pharmaceutical industries, which are still world leaders today.

Innovation projects in a global world  151

Then starting from this location, as new markets are developed, companies exported their innovations internationally, a process conceptualized by Stephen Hymer (1960) and summarized by Raymond Vernon (1966) as the international product lifecycle. In short, innovations first developed for the domestic market would be “projected” internationally by firms wishing to retain control (in terms of intellectual property and economic rent) of the fruits of their innovations. This is a home-centric model of innovation. This model corresponds to the development of projects targeting global innovation (Ben Mahmoud-Jouini et al., 2020). Such projects are initiated at the corporate level and involve mainly corporate resources (R&D, marketing, etc.) with minimal involvement of local teams located within subsidiaries. They result in standardized offers generally commercialized in the home market with very few local adaptations for local subsidiaries. The offer is based on a set of specifications (technical and marketing) defined ex-ante by a corporate team. Global suppliers are selected, and global infrastructure is established in order to reach economies of scale. Local resources are marginally involved in the innovation project. Incentives are put in place to ensure that the subsidiary adopts and commercializes the innovation. Progressively, another model has developed. Rather than innovating in the home base through the development and the combination of technological and market knowledge at the corporate level, some multinational companies developed innovation in different locations where they are settled leading to a “multiple origin” model, i.e. the transnational model of MNCs (Bartlett and Ghoshal, 1989). This multi-home-base model is an extension of the home-centric model applied to several locations. Here as well, the origin may be incidental or linked to a local competitive advantage. In this model, some subsidiaries receive “global mandates” for specific products and activities. The principle is to leverage the competitive advantage provided by some locations. It is designated as glocalization considering that the processes of the MNC are designed to be global while leveraging local specificities of some subsidiaries (think global and act local). Besides these ones, the others maintain the same role as in the home-base model: commercializing the innovations with minimum adaptations. The multi-home model corresponds to the development of projects targeting regional or intermediate innovation (Ben Mahmoud-Jouini et  al., 2020). These projects result from a combination of corporate and local decisions. They share the same rationales of projects targeting global innovations but on a smaller scope, i.e. a group of subsidiaries nested in different countries but sharing the same needs and specificities such as customer behaviours, for example. The innovation is conceived in order to address these needs and is developed by a combination of corporate and local resources resulting in a core offer and specific modules. Corporate resources are involved in the design of the core as well as in the diffusion of innovations at the regional level. The complementary modules are developed by the subsidiary teams that leverage their local ecosystem. One specific case of the multi-home model is the case of subsidiaries of western MNCs located in emerging markets that develop specific innovations addressing local needs. Indeed, such growing markets represent growth opportunities for MNCs that face mature and stagnating markets in their traditional locations. Hence, they develop in and for emerging markets specific innovations targeting specific characteristics (Govindarajan and Ramamurti, 2011) and leading to “frugal” innovation strategy (Zeschky et  al., 2011). Such a local innovation strategy requires the understanding of the specific needs of local market segments such as the bottom of the pyramid (Prahalad, 2005) or the middle of the pyramid and addressing these needs in an innovative way. Beyond cost reduction and robustness, this type of innovation

152  Handbook on innovation and project management

leverages mainly local specificities, e.g. supplier networks, regulations, specific production processes, etc. This strategy requires the acquisition of local knowledge (usage, market, technology, etc.) that can as well be combined with corporate knowledge from other locations of the MNC such as R&D centres in the home market or other mature markets. For example, General Electric’s (GE) famous cost-reduction breakthroughs in medical monitoring devices in India drew on the knowledge of the specific needs of the local market and GE’s R&D efforts in India combined with specific skills and technologies developed in Israel (Govindarajan and Trimble, 2013). It happened that after their launch in emerging markets, these specific innovations are commercialized afterwards by the MNCs in their home market or in other subsidiaries (Von Zedwitch et  al., 2015) with potentially some adaptation of the offer or the business model (Hadingue et  al., 2019; Malodia et  al., 2019). This phenomenon has been designated as a “reverse innovation” strategy (Govindarajan and Trimble, 2012) because it reverses the traditional direction of diffusion of knowledge and innovation highlighted in the home-centric model and that used to go from the home market to the periphery. As a recap, the multi-home-base model combines corporate central needs with local needs, it is host-centric drawing on and combining the assets of several locations around the world. The process is inherently distributed and truly global. In other cases, subsidiaries can develop local innovations (Ben Mahmoud-Jouini et al., 2020) without the support of corporate resources based on a combination of their own resources with those of their ecosystem and targeting specific needs for their local markets. Such innovations may remain local or be diffused to other subsidiaries thanks to initiatives involving intersubsidiaries communities (Hu et al., 2017). A mix of a multi-home model with a host-centric one leads to a model where innovation (technological and market) can be generated anywhere in the MNC and diffused across the different locations while knowledge flows inter-subsidiaries. It involves offers that are potentially originated, developed and commercialized globally at any stage of the process. It is the integrated polycentric network allowing the deployment of competencies and innovations between the different poles. This model corresponds to the meta-national corporation model (Doz et al., 2001) where the objective is to leverage local assets globally (think local and act global). Organizing for Global Innovation Strategies Beyond the characterization of these global innovation strategies, literature on international management and more specifically on global innovation management has highlighted four organizational elements that play a crucial role to implement such strategies enabling specific innovation processes: the R&D footprint, the role of subsidiaries, the internal network of knowledge and the organizational player which coordinates the implementation of such strategy. R&D footprint The R&D footprint, i.e. where MNCs locate their innovation efforts, has evolved according to the evolution of the innovation strategies highlighted above. Indeed, historically, it has been centralized and generally located at the headquarter or the home market. The decrease in communication costs and the improvement in the quality of information systems led to

Innovation projects in a global world  153

the geographical distribution of innovation teams at the global level. This relocation of R&D activities has several motivations: access to local knowledge and resources that represent a critical asset and a competitive advantage, adaptation of the product or the operation process to local specificities, diversification of resources, cost reduction, exploitation of imbalances in resources supply and demand, etc. As a mirror of the different models presented here, the R&D footprint or internationalization of the R&D can adopt different forms. These forms differ as well according to the orientation of the innovation strategy, i.e., whether it is science and research-based or market-based. Indeed, in each case, the knowledge acquired will be different. Therefore, the R&D footprint can have different configurations: an ethnocentric centralized R&D, a polycentric decentralized R&D or an integrated R&D network. Such configurations have different performances in terms of absorption and efficient integration of local knowledge acquired and developed (Zedtwitz and Gassmann, 2000). This multi-localization leads innovation teams to collaborate but also to compete. More importantly, it requires knowledge management and integration skills so that valuable resources (market, technology, etc.) and corporate networks can be leveraged across structural and cultural boundaries (Doz and Wilson, 2012). Laurens et al. (2015) show that the R&D internationalization expansion reaches a plateau. Roles of subsidiaries The active role of subsidiaries in generating knowledge and stimulating innovation has been acknowledged. They are not only commercialization channels but also sources of innovation (Ferraris, 2014; Asakawa et  al., 2018; Lee et  al., 2020) involving knowledge creation and sharing (Ryan et al., 2018). Partly due to the globalization of R&D, MNC subsidiaries were increasingly involved in developing innovation (Ciabuschi et al., 2014; Asakawa et al., 2018). They enable local adaptation of the MNC’s global products and services as well as the acquisition of global technology for the whole MNC. Furthermore, considering that innovation does not involve only R&D, the global innovation strategies relied as well on different configurations of relationships between the subsidiaries and the headquarters and between the subsidiaries themselves. Indeed, innovation requires the integration of knowledge (technology, market needs, etc.) from different types of subsidiaries that can be sourced and developed in various locations. Bartlett and Ghoshal (1989) identified four types of subsidiaries depending on the strength of the local innovation capacity and the importance of the local market for the MNC: strategic leader, implementer (if both are weak), contributor if the innovation capacity is strong but the market small and black hole if the capacities are not strong enough to leverage the potential of the market. Therefore, subsidiaries have dual embeddedness (Figueiredo, 2011; Ciabuschi et al., 2014), internally within the global network of the MNC leveraging the assets and knowledge from HQ and their sister subsidiaries globally and externally within their local environment leveraging local assets. Tallman and Chacar (2011) have suggested that MNCs are networks of units (i.e. subsidiaries, research centres, etc.) that are simultaneously embedded locally and within the company as a whole. Therefore, each subsidiary will bring to the network specific resources and represent specific assets. They are boundary spanners (Monteiro et  al., 2008). Building on the differentiation of subsidiaries proposed by Bartlett and Goshal (1989), Guerineau et al. (2015) have proposed to differentiate four types of subsidiaries that contribute differently to the innovation strategy of the MNC based on their own local innovation

154  Handbook on innovation and project management

capabilities and on their local innovation ecosystem and its specificities: (i) historically major subsidiaries with innovation capabilities and significant market potential; (ii) implementation subsidiaries, which deploy at scale innovation validated elsewhere in the MNC; (iii) accelerators that, thanks to their expertise in specific fields, their flexibility and reactivity generally due to their modest size and their exposure to demanding markets, develop following an experimentation mode a specific innovation likely to be deployed elsewhere later on; and (iv) high potential subsidiaries located in emerging growing markets with a strong demand for innovation because of the necessity to explore new business models or distribution channels. Therefore, the subsidiaries can have their own innovation strategy that is combined with the global innovation strategy of the MNC as a whole. They play a crucial role in the global innovation process of the MNC. WHEN A REGION TAKES THE LEAD: THE CASE OF ORANGE MONEY Orange, a telecommunications operator, is present in 27 countries including 19 in the Africa and Middle East region (AME) where 11.6 per cent of its employees and 46 per cent of its customers realize 12 per cent of a highly growing turnover thanks to mobile services and data transmission. Therefore, Orange has adopted a growth strategy in that region. Indeed, one African in ten is a customer of Orange. Even if there are disparities in size, maturity and evolution of the various domestic markets in this region (mobile penetration rates vary from 130 per cent for Botswana and Jordan, reflecting the multidevice phenomenon, to less than 30 per cent for Niger), they present common characteristics, including a low penetration rate of bank accounts (less than 10 per cent in sub-Saharan Africa) compared to the penetration rate of mobile phones. Therefore, Orange Money, a mobile payment service, can interest a wide regional market. It comprises four services: money transfers, cash withdrawals and deposits, bill payments and refill of telephone call credit. The development and deployment of the offer required the creation of an ecosystem with local financial and commercial partners willing to accept this form of payment. It requires as well agreement with local bank authorities. The project began in 2006 at the corporate level, when a marketing team was created to discuss with subsidiaries in AME opportunities for a mobile payment service. A few months later, in 2007, Safaricom (a Vodafone subsidiary in Kenya) launched a mobile payment service (M-Pesa). It was a trigger to speed up the development. The corporate team carried out initial investigations that revealed a need for a specific platform, security controls in order to prevent fraud and money laundering and authorizations from the local financial regulator. Therefore, the team initiated a negotiation with the Central Bank of the West African States. The development of a new infrastructure required specification of the interface with existing information systems, both locally and globally. Some subsidiaries participated by sending their requirements to the corporate team. During its development, the project benefited from the support of several corporate sponsors that brought visibility and mobilized the resources necessary to make progress during critical stages. The first launch was in Ivory Coast in December 2008, then in Senegal in May 2010. A process was established for the following launches: once the decision to launch the service was made, a local project manager was appointed. He reported to the local

Innovation projects in a global world  155

subsidiary’s CEO and worked with the corporate centralized team. He established a local distribution network (bank partners, Orange retail stores, authorized Orange distributors, such as vendors and pharmacies, etc.) and executed the operational marketing campaign. A skill centre was created in Bamako to share and train local teams in negotiating with local partners, as well as controls and reporting to banks. The platform was installed by local teams with the support of the centralized team. In countries where local resources were limited such as in Niger, a shared infrastructure was installed in France where parameters and security tests were set up with little involvement of the local team in the technical running. After six launches, the project entered a second phase of improving the offer. The subsidiaries were consulted to identify new services that could potentially be launched. The final decisions were made at the corporate level favouring services that were likely to interest the widest range of countries such as the delivery of microfinance financial services (lending and saving) initiated in 2018 in Madagascar. In 2018, ten years after the launch of the first service, Orange Money counts 39.2 million customers (15.1 million monthly users) in 15 countries on the global 276 million customers of Orange. Two billion transactions with Orange Money have been registered. The customer growth is about 35 per cent (2017–2018). In 2015, the service has been launched in Poland and in 2018, Orange France launched an Orange Bank building on the capacities and the knowledge acquired during the decade of financial services development and operation in AME. This type of innovation is neither global nor local because it requires a lot of effort from the local team in the development phase (technical, marketing, ecosystem) beyond marketing adaptation but also relies on centralized corporate resources and on regional initiatives developed to mutualize the local efforts and share best practices.

Internal networks of knowledge The globalization of R&D and the network model of MNCs involve a wide variety of knowledge distributed within the MNC in different formats. In some cases, this knowledge is complex and tacit (Doz and Wilson, 2012) and therefore its diffusion and sharing within the firm becomes a big challenge. Literature on knowledge integration emphasizes the role of “communities of practice” (Wenger, 1998) as a way to overcome such a challenge. Communities of practice are organizational arrangements that foster formal and informal relationships through regular face-to-face meetings, rotating assignments and expatriations and thus represent an effective “internal network of practice” that enables the circulation sharing and integration of knowledge in geographically dispersed firms (Tallman and Chacar, 2011; Guerineau et al., 2016). Doz and Wilson (2012) showed that the geographic dispersion of innovation activities raises organizational integration challenges that limit the extent of dispersion. One specific case is when the knowledge sourced locally (either technology or market) is tacit and “sticky” (Von Hippel, 1994). Research has highlighted the role of colocation and embeddedness to capture such knowledge (Cantwell and Mudambi, 2005) such as in the case of scouting units located in innovation hubs (Silicon Valley, for example) (Monteiro, 2015) that will play a boundary-spanning role within the MNC. Globally distributed corporate

156  Handbook on innovation and project management

accelerators that host local startups also play such a role in acquiring knowledge and then distributing it within the MNC network (Ben Mahmoud-Jouini et al., 2018). Scholars (Ben Mahmoud-Jouini et al., 2015) interested in global innovation management from a knowledge transfer perspective have highlighted that the challenge for an effective GIM is to organize and exploit the knowledge distributed in order to leverage it in globalized innovation processes. It is therefore necessary to adopt an analytical perspective that takes a closer look at the processes at work. This is where the field of project management can make a significant contribution. A central coordination We have highlighted three organizational levers (R&D footprint, subsidiaries and internal knowledge networks) that would play an important role in GIM. However, without adopting a strict planning perspective, and while acknowledging the value of emergent strategies, in order to lead to effective global innovation strategies and to develop and support global innovation processes, these levers must be coordinated and managed. A central or corporate position and perspective are required to benefit from such levers. Researchers (Ben Mahmoud-Jouini et al., 2015) emphasized four central roles or functions that should be provided. First, there must be an animation of these internal networks or a trigger for the emergence of communities of practice to stimulate such initiatives and maintain the fluidity of communications within the MNC (Guerineau et al., 2017). Second, the set-up of a relevant incentive system for subsidiaries to innovate is needed in order to align their local innovation efforts with the global innovation strategy. Third, central architecture decisions to mitigate the tension between local adaptation and global deployment encountered during the deployment of local innovation at a global level are needed, for example, to clearly differentiate the stable core of the offering from its adaptable periphery (Ben Mahmoud-Jouini et al., 2020). Last, central human resource management is an important way to enable knowledge sharing and the global deployment of innovations thanks to innovation champions that would ensure or facilitate such a role (Ben Mahmoud-Jouini and Charue-Duboc, 2014; Munoz and Zarate, 2002). THE ROLE OF HQ IN THE EMERGENCE OF INNOVATIONS IN SUBSIDIARIES AND THEIR DEPLOYMENT IndusGaz is one of the world leaders in industrial gas with a vast network of subsidiaries in more than 80 countries. The gas is used in the industrial processes of various industrial customers leading to a matrix structure crossing major sectors served with geographical markets. Innovation can originate in one of the six R&D centres leading to “corporate” innovations and/or in the subsidiaries leading to local innovations. The company develops a wide diversity of innovations: specific gas, process and application, i.e. innovating in the industrial process of the customer who uses the gas. The subsidiaries are particularly involved in application innovations because of their proximity to customers. In IndusGas, the HQ plays a dual role in the development of local innovation and its deployment in the MNC across subsidiaries through two specific mechanisms: the Local Innovation Fund (LIF) that provides subsidiaries with resources in funds and technological expertise and the Industrial Process Engineering Expertise Network (IPEN) that supports the subsidiaries when developing application innovation with their industrial customers.

Innovation projects in a global world  157

The objectives of the LIF are twofold: to facilitate the emergence of local initiatives likely to be adopted by other subsidiaries and, once the first success has been achieved, to encourage their deployment throughout the MNC. It has its own team of two fulltime employees located at the corporate R&D department and ambassadors in four geographical areas and its own budget and process for selecting and allocating resources. Subsidiaries submit a funding request based on initial technical and commercial elements. A jury (the team, the R&D department, corporate marketing and internal experts chosen according to the subject) decides whether or not to allocate resources. The small team, together with the local ambassadors, then accelerate the development process by providing the resources and the expertise. They also ensure internal communication on the innovation in order to favour future deployment. Furthermore, the team and the ambassadors favour exchanges between subsidiaries (a request for expertise can sometimes be resolved through the help of a colleague from another subsidiary) and between subsidiaries and corporate managers. IPEN is a worldwide network of 130 full-time dedicated technical experts structured in seven areas of expertise corresponding to the types of industrial applications that use gas, such as combustion, atmospheric control or food cryogenics. The experts are distributed in 11 centres ensuring wide global coverage. IPEN involves two types of experts: locals who are based in the subsidiaries and interact very regularly with customers and vendors, and corporates located at the management level. Indeed, in addition to the seven global referents, IPEN is managed by eight members at the HQ. They ensure that the geographical experts’ resources are in line with the needs and expectations of the subsidiaries, provide them with technical support and visibility and animate the network through annual meetings and informal exchanges. They ensure the connection of the network with the rest of the organization. The knowledge developed by the experts is embedded in specific industrial processes difficult to model. It is developed through practice and interactions with customers close to the subsidiary. In the meantime, thanks to the relationships maintained between peers present throughout the world, the experts enrich their local tacit knowledge with a global vision. This configuration favours a certain level of standardization of innovations developed locally, which facilitates their subsequent deployment phase. Indeed, these experts are aware of the challenges of deployment in other contexts and therefore integrate them very early on. Therefore, the operating mode and the geographical distribution of the members enable the emergence of application innovation at the subsidiary level and their global deployment.

GLOBAL INNOVATION PROJECT MANAGEMENT, A KEY CAPABILITY OF THE INNOVATIVE MULTINATIONAL COMPANY Projects as Learning Opportunities in Globalized Innovation Processes One of the important issues in project management is the organizational learning and diffusion of the knowledge created within projects to other projects or more generally to the parent organization as a whole (Ben Mahmoud-Jouini, 1999). Lundin and Midler (1998) outlined

158  Handbook on innovation and project management

the transfer of knowledge from temporary to permanent organizations. In their articles of 2000 and 2004, Brady and Davis suggested a specific organizational learning mode that combines the project learning process with that of the permanent organization. This scheme is present as well in the specific case of vanguard projects (Frederiksen and Davies, 2008). Even though these articles have not explicitly referred to innovation in multinationals, we argue that the learning and innovation processes studied are relevant for understanding global innovation processes where knowledge produced within global projects flows across projects and within the permanent company. Indeed, as shown by Söderlund and Tell (2011), in project-based organizations (the P-form according to Lundin et al.’s 2017 classification), knowledge (technical, market, etc.) is created and integrated within innovation thanks to the projects. As such they represent opportunities to develop new knowledge. However, many studies, particularly in the field of construction, have shown that the P-form prevents this knowledge from flowing across projects unless the project’s members transfer their experiences from one project to another. In project-supported organizations (PSOs), Midler has shown how the knowledge produced in specific innovation projects supporting the firm’s growth strategy in Eastern European countries at the end of the 1990s (Jullien et al., 2013) and in India in the middle of 2010 (Midler et al., 2017, Midler et al. 2023) has diffused. Indeed, they outlined that a programme-based organization (Pellegrinelli, 2002) enables the diffusion of knowledge across projects (Artto Dietrich, 2007). Such a programme can be a group of projects developing a range of diversified products that share the same DNA of the initial innovation targeting markets geographically distributed. Midler (2013) suggested the concept of lineage to capture such a phenomenon where knowledge is shared across succeeding projects. On top of the concept of lineage (Maniak and Midler, 2014), managing the human resources across the projects and between projects and functions constitutes a vector of transfer from projects to the parent organization. It appears that the effectiveness of international projection strategies is closely dependent on the firm’s specific project organization. Globalized Innovation Processes: An Interplay between Projects, Subsidiaries and Corporate Functions If we consider innovation projects as a way to implement the innovation strategy of the firm as claimed earlier, the global innovation strategy of MNCs should introduce global innovation projects as an important player on top of the duo formed by headquarter and subsidiaries, i.e. centre and periphery. Indeed, the evolution of MNCs as presented in the previous section emphasizes the roles of subsidiaries in the development of innovation without specifying where and how the knowledge is produced. Indeed, wherever the sources of the innovation lie (from a subsidiary in order to address specific needs or to leverage specific assets or from a corporate service targeting the development of global innovation for standard needs or the exploitation of a promising technological innovation), it is generally developed through a global innovation project either supported by a subsidiary or by a corporate department. The current trend in project management triggers the integration of global projects in the interplay between headquarters and subsidiaries that is required to manage innovation in

Innovation projects in a global world  159

MNCs. Indeed, the competitive advantage of MNCs in terms of innovation lies in their ability to launch innovation projects quickly and efficiently on a global scale. Ben Mahmoud-Jouini and Charue-Duboc (2014) proposed the concept of innovation deployment, defined as the process leading to the successive commercialization of innovation in different subsidiaries and its adaptation to the corresponding markets once it has been developed and commercialized in the first targeted one. They insist on the necessary adaptation or even redesign of an innovative product to the local context in which it is marketed and on the conditions allowing the subsidiary that deploys the innovation to access the necessary knowledge, most often located in the subsidiary that originated the innovation (Ben Mahmoud-Jouini et al., 2020). Guerineau et al. (2015) differentiate between the types of innovation and the types of subsidiaries that are more likely to develop them, and they specify the role that each type of subsidiary can play in the deployment processes. Effectiveness in this area depends on the ability to mobilize the different components of the “three-player game” of project-subsidiary-hub according to the capacities they can bring for the rapid deployment of innovation on a global scale. The orchestration of these trajectories across subsidiaries is highly dependent on central decisions concerning technological choices, which will allow (or not) to adapt the innovation when it is diffused from one country to another, as well as on career management decisions, which will allow (or not) champions to ensure the mobilization of the actors involved in the different stages of the deployment trajectory. Is the Global Innovation Management of MNCs Shaped by Global Innovation Projects? In this “three-player game”, we see how projects are combined with the permanent components of the MNC in order to produce effective global development trajectories of innovations. However, projects are temporary. Therefore, to what extent can they influence the firm’s strategy? In the case of PBOs, it has been emphasized that learning takes place essentially from project to project, through the personal experience of professionals. In this context, the pole of stability remains the dual relationship between the centre and the country subsidiaries. This is not the case in the context of PSOs, such as the automotive or telecommunications firms studied, where permanent resources were dedicated to stringing together projects consistent with the DNA of the initial project. In this context, a trajectory of projects or a lineage played a huge role in the strategy beyond the centre versus periphery perspective. Indeed, the projects involve resources transversally to the centre and/or the subsidiaries. The examples of the global innovation strategy of Renault, studied by Jullien et al. (2013), and those of the Logan project in Romania, the Kwid project in India and the KZE project in China, studied by Midler et al. (2017, 2023), show that, beyond the launching projects, the MNCs developed three global platforms (or programmes) that combine global resources. This transformation of the MNC from a traditional “home-centric” model to a multi-polar model (see Figure 7.3) was enabled by the structuration of strong project management through heavyweight project managers responsible for vanguard projects and programmes combining different projects sharing common knowledge and components.

160  Handbook on innovation and project management

INTERNATIONALIZATION THROUGH PROJECT LINEAGE: THE RENAULT LOGAN CASE In 1999, when Renault started the Logan project, the €5,000 car, the Renault group was essentially a European company with a market share outside Europe of 11 per cent. Twenty years later, in 2019, more than 50 per cent of its sales are carried out outside Europe, mainly through the contribution of vehicles of the lineage resulting from Logan initially and then of Kwid. Between these two dates, a series of projects expanded and diversified the initial pilot project (the Logan, initially launched in 2004 in Romania) and then the Kwid (launched in 2015 at €3,500 in India) to attack new customer niches and adapt them to the specificities of various markets (see the following figures).​​​ This internationalization of the company is clearly the result of a multi-project learning process, beginning with the first breakthrough project of the frugal Logan, then developing successive projects to explore new product and market concepts while capitalizing on, sharing and adapting what had been learned from previous projects to fit the specificities of the intended customer targets. In such lineage management, which will be analysed in Chapter 8, programme management is at the heart of the design organization. The development of the Logan and Kwid lineages thus led to the evolution of a home-centric structure of innovation management centred on Renault’s central French engineering department to a tri-centric structure of the engineering departments that took charge of the pilot projects of the two lineages in Romania and India and then piloted the subsequent deployments.​

Source:   Midler et al., 2023.

Figure 7.1  Deployment of the product line from the Logan project

161

Figure 7.2  Geographic deployment of the Logan project line

Source:   Midler et al., 2023.

162

800,000 600,000

800,000

600,000

2006

2005

2004

2017

2016

2014

2013

2012

2011

2010

2009

2007

Figure 7.3  Logan lineage sales by market and vehicle type

Source:   Midler et al., 2017.

0

200,000 2015

Afrique Moyen-Orient Inde Asie Pacifique Ameriques

1,000,000

1,000,000

2008

Europe Eurasie

1,200,000

1,200,000

0

200,000

400,000

1,400,000

1,400,000

400,000

1,600,000

1,600,000

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

LOGAN SANDERO DUSTER / OROCH LODGY / DOKKER KAPTUR / CAPTUR GA

2016

KWID

2017

2015

2004

163

TC China

Technocenter

Central French

TC Brazil

TC India

TC Korea

Russia

TC

TC China

TC India

Kwid platform scope

TC Roumania

Central French Technocenter

TC Brazil

TC Spain

TC Korea

Russia

TC

TC Spain

TC Roumania

TC Brazil

TC India

European platforms scope

TC China

Central French Technocenter

TC Korea

TC India

Russia

TC

TC China

Figure 7.4  From the home-centric model in 2000 to the tri-centric global innovation process in 2018

Source:   Midler, 2019.

TC Russia

TC Spain

TC Roumania

TC Brazil

TC Spain

TC Korea

Logan platform scope

Roumania

TC

Central French Technocenter

164  Handbook on innovation and project management

CONCLUSIONS AND PERSPECTIVES Corporate globalization is a trend that is both old and has been developing rapidly for several decades, based on structural data such as differences in the pace of market growth or the asymmetry of resources and technological and financial capacities. The COVID crisis and the war in Ukraine have put the importance of the sovereignty of national identities back on the political and economic agenda, and have challenged the image of a “flat” world where the activities of large multinational groups could be deployed without constraints. In fact, this image of a “seamless” business world was largely idealized. For a long time, one of the key issues for MNCs has been to reconcile the local specificities of countries and regions with their global deployment strategies. This is particularly true for the internationalization of innovation management. The contemporary context makes the processes and organizations through which they attempt to achieve this more essential. International management and project management currents approach the problem of the internationalization of innovation management in a complementary way. On the one hand, the former focuses on the strategic and structural level of the firm, emphasizing the role of central governance and the role and capabilities of local units. It proposes typical models that respond to the imperative of local-global articulation, as well as trajectories of evolution from firms centred in their country of origin to polycentric networked organizational models, knowing how to take advantage of local resources and business opportunities and how to effectively circulate and combine knowledge useful for adapted agile innovation management. On the other hand, project management studies in a more precise way the processes by which these innovations are born and deployed (or not) within these structures and territories. It characterizes the difficulties associated with innovation projects in an international context. It analyses how the concepts developed by the discipline, in terms of organization and management style of projects, allow us to deal with these difficulties. It shows how these project identities are articulated with the classic variables of multinational firms, namely country and regional subsidiaries and the strategic centre. Finally, it analyses how multi-project approaches such as lineage management can constitute the vector of inter-project learning within the global firm that stimulates original and perennial innovation trajectories, preserving the DNA of disruptive innovations of the initial pilot project, while allowing us to capitalize and adapt it order to deploy it in different contexts. Returning to the current context, such lessons are important to deepen and deploy, both because of the tightening of specific political and regulatory constraints associated with the increasing power of public authorities in the business domain and also because of the huge expansion of innovation areas associated with the climate and environmental crisis, which are inherently global. Far from marking the end of research on the internationalization of innovation projects, these crises should, on the contrary, stimulate a strong development and renewal of the field in the future.

REFERENCES Artto, K.A. and Dietrich, P.H. (2007). Strategic business management through multiple projects. In P.W.G. Morris and J.K. Pinto (Eds.), The Wiley guide to project program & portfolio management (pp. 1–33). New Jersey: John Wiley & Sons Inc.

Innovation projects in a global world  165

Asakawa, K., Park, Y., Song, J., and Kim, S.J. (2018). Internal embeddedness, geographic distance, and global knowledge sourcing by overseas subsidiaries. Journal of International Business Studies, 49(6), 743–752. Bartlett, C. and Ghoshal, S. (1989). Managing across borders: The transnational solution. Boston, MA: Harvard Business School Press. Ben Mahmoud-Jouini, S. (1999). Innovation based competition and processes for the design of innovative market supply flow. The case of major general contractors in the French construction industry. In Proceedings of 6th international product development management conference (IPDMC). Cambridge (UK). Ben Mahmoud-Jouini, S., Burger-Helmchen, T., Charue-Duboc, F., and Doz, Y. (2015). Global organization of innovation processes. Management International, 19(4), 112–120. Ben Mahmoud-Jouini, S. and Charue-Duboc, F. (2014). Le déploiement d’innovations inter-filiales au sein d’une multinationale. Management International, 18, 42–58. Ben Mahmoud-Jouini, S., Charue-Duboc, F., and Hadingue, M. (2020). Intermediate, local and glocal innovation models for MNCs targeting emerging markets: The case of a European Telco operator in Africa and the Middle East. Management International, 24, 20–35. Ben Mahmoud-Jouini, S., Corentin, D., and Esquirol, M. (2018). Key factors in building a corporate accelerator capability. Research Technology Management, 61(4), 26–34. Birkinshaw, J. and Lingblad, M. (2005). Intrafirm competition and charter evolution in the multibusiness firm. Organization Science, 16(6), 674–686. Brady, T. and Davies, A. (2004). Building project capabilities: From exploratory to exploitative learning. Organization Studies, 25(9), 1601–1621. Chevrier, S. (2013). Managing multicultural teams. In J.F. Chanlat, E. Davel, and J.P. Dupuis (Eds.), Cross-cultural management (pp. 217–237). Routledge. Ciabuschi, F., Holm, U., and Martin, O.M. (2014). Dual embeddedness, influence and performance of innovating subsidiaries in the multinational corporation. International Business Review, 23(5), 897–909. Davies, A. and Brady, T. (2000). Organisational capabilities and learning in complex product systems: Towards repeatable solutions. Research Policy, 29(7–8), 931–953. Doz, Y. and Wilson, K. (2012). Managing global innovation: Frameworks for integrating capabilities around the world. Cambridge, MA: Harvard Business Review Press, 272p. Doz, Y.L., Santos, J., and Williamson, P. (2001). From global to metanational: How companies win in the knowledge economy (1st ed.). Boston, MA: Harvard Business Review Press. Ferraris, A. (2014). Rethinking the literature on “multiple embeddedness” and subsidiary-specific advantages. Multinational Business Review, 22(1), 15–33. Figueiredo, P.N. (2011). The role of dual embeddedness in the innovative performance of MNE subsidiaries: Evidence from Brazil. The Journal of Management Studies, 48(2), 417–440. Govindarajan, V. and Ramamurti, R. (2011). Reverse innovation, emerging markets, and global strategy. Global Strategy Journal, 1(3–4), 191–205. Govindarajan, V. and Trimble, C. (2013). Reverse innovation: Create far from home, win everywhere. Cambridge, MA: Harvard Business Press, 256p. Guerineau, M., Ben Mahmoud-Jouini, S., and Charue-Duboc, F. (2015). Différencier les contributions des filiales d’une multinationale en matière d’innovation. Management International, 19(4), 112–120. Guerineau, M., Ben Mahmoud-Jouini, S., and Charue-Duboc, F. (2017). Le rôle des communautés de pratiques et de leur coordination dans le développement et le déploiement des innovations dans une multinationale. Management International, 21(3), 16–32. Hadingue, M., Ben Mahmoud-Jouini, S., and Charue-Duboc, F. (2019). The deployment of reverse innovations: Adaptations from emerging to advanced markets. In R&D management conference proceedings, 19–21 June. Paris & Academy of Management. Isaac, V.R., Borini, F.M., Raziq, M.M., and Benito, G.R. (2019). From local to global innovation: the role of subsidiaries’ external relational embeddedness in an emerging market. International Business Review, 28(4), 638–646. Jullien, B., Lung, Y., and Midler, C. (2013). The logan epic; new trajectories for innovation. Paris: Dunod.

166  Handbook on innovation and project management

Lee, J.Y., Jimenez, A., and Bhandari, K.R. (2020). Subsidiary roles and dual knowledge flows between MNE subsidiaries and headquarters: the moderating effects of organizational governance types. Journal of Business Research, 108, 188–200. Lundin, R. and Midler, C. (1998). Projects as arenas for renewal and learning processes. Norwell, MA: Kluwer Academic Publishers, 259p. Malodia, S., Gupta, S., and Jaiswal, A.K. (2019). Reverse innovation: A conceptual framework. Journal of the Academy of Marketing Science, 48(5), 1009–1029. Maniak, R. and Midler, C. (2014). Multiproject lineage management: Bridging project management and design-based innovation strategy. International Journal of Project Management, 32, 1146–1156. Meyer, K.E., Mudambi, R., and Narula, R. (2011). Multinational enterprises and local contexts: The opportunities and challenges of multiple embeddedness. Journal of Management Studies, 48(2), 235–252. Midler, C. (2013). Implementing a low-end disruption strategy through multiproject lineage management: The logan case. Project Management Journal, 44(5), 24–35. Midler, C. (2019). Projectification: The forgotten variable in the internationalization of firms’ innovation processes? International Journal of Managing Project in Business, 12(3), 545–564. Midler, C., Alochet, M., and de Charentenay, C. (2023). The odyssey of innovation, lessons from an impossible project. Taylor and Francis. Midler, C., Jullien, B., and Lung, Y. (2017). Rethinking innovation and design for emerging markets, inside the Renault Kwid Project. Taylor & Francis. Prahalad, C.K. (2004). The fortune at the bottom of the pyramid: Eradicating poverty through profits (1st ed.). Upper Saddle River, NJ, Wharton School Publishing. Söderlund, J. and Tell, F. (2011). Strategy and capabilities in the P-form corporation: Linking strategic direction with organizational capabilities. In Project-based organizing and strategic management. Emerald Group Publishing Limited. Vernon, R. (1966). International investment and international trade in the product cycle. The Quarterly Journal of Economics, 80(2), 190–207. von Hippel, E. (1994). “Sticky information” and the locus of problem solving: implications for innovation. Management Science, 40(4), 429–439. von Zedtwitz, M., Corsi, S., Søberg, P.V., and Frega, R. (2015). A typology of reverse innovation. Journal of Product Innovation Management, 32(1), 12–28. von Zedtwitz, M. and Gassmann, O. (2002). Market versus technology drive in R&D internationalization: Four different patterns of managing research and development. Research Policy, 31(4), 569–588. Zeschky, M., Widenmayer, B., and Gassmann, O. (2011). Frugal innovation in emerging markets. Research Technology Management, 54(4), 38–45.

PART II BUILDING AND EXTENDING

8. Corporate innovation strategies and multi-project management on lineages and ambidextrous programmes Rémi Maniak and Christophe Midler

INTRODUCTION Over the last few decades, innovation has become a survival imperative for companies. The history and characteristics of the different multi-project management methodologies can be seen as a mirror of the challenges companies are facing. After problems centred on the management of a specific project, the issue of multi-project management developed in the 1990s to cope with an increasing number of projects in companies, according to an imperative to rationalize resource allocation. Project portfolio management was formalized at this time. At the same time, innovation strategies aiming to deploy more diversified offers while keeping common elements and thus reducing overall costs led to the grouping of projects according to programme and platform issues. The discipline then had to invent other models as corporate strategies evolved. The most recently formalized forms, project lineage management and ambidextrous programme management, are witness to the increasing intrusion of more radical and uncertain innovations in corporate strategies. The objective of this chapter is to characterize these last two models: •

•

Lineage management is based on the strategic management of a series of innovation projects over time. It aims to generate and deploy a range of disruptive offers for the company by progressively capitalizing on the assets generated by the trajectory of successive innovations (“reuse” and learning about the technology, the product, the services, the customer learning, etc.). It offers a flexibility of adaptation that pragmatically takes advantage of the learning accumulated along the way, as well as the specificities of the different contexts encountered in this trajectory. Ambidextrous programme management, for its part, is adapted to piloting sets of projects carried out in the context of ambidextrous strategies, i.e. strategies that seek the simultaneous performance of exploration and exploitation logics within large companies. These strategies have become widespread over the past decade with the development of competition through intensive innovation. The issue is to manage heterogeneous projects in terms of their content, level of maturity and time horizon, in order to accelerate the development of breakthrough innovations while preserving the capacity to valorize short-term developments and save committed resources. Consequently, the traditional framework of project portfolio management has reached its limits in terms of its ability to quickly bring to market the required breakthrough innovations. Ambidextrous programme management aims to overcome these limits. 168

Corporate innovation strategies and multi-project management  169

INNOVATION PROJECT MANAGEMENT IN THE AMBIDEXTROUS STRATEGY CONTEXT The Ambidextrous Strategy Context The empirical relevance of new concepts in the project management academic field lies in the dynamics of innovation strategies and the resulting transition in the management of innovation projects. The 1990s and 2000s saw an increase in competition through intensive innovation (Benghozi et al., 2000; Le Masson et al., 2010), with an increase in the variety and customization of products, the shortening of development cycles and the gradual increase in the radicalness of the innovations needed to create differentiation in the markets. This situation of tension between short-term operating performance and the relevance of long-term explorations in large companies is at the heart of the theoretical field of ambidexterity strategies (Duncan 1976; March, 1991). Raich et al. (2009) identify three different strategic models for resolving this tension. Temporal ambidexterity configures exploration and exploitation approaches in a sequential manner, alternating between exploitation and exploration when environmental disruptions require a renewal of the usual way of doing business. Structural ambidexterity (O’Reilly and Tushman, 2004) isolates exploration units from business units mobilized on exploitation activities. These units have limited resources, but have more freedom to explore products and services different from the company’s usual activity. Finally, contextual ambidexterity, where exploration efforts are driven by employees within the operating structures themselves, in the form of freed up work time to participate in the exploration of creative ideas (Gibson and Birkinshaw, 2004). Lavie and Rosenkopf (2006) have added a fourth form of ambidextrous strategy, “network ambidexterity”, where the firm mobilizes a network of outside firms to develop its disruptive innovation capabilities through open innovation (Chesbrough et al., 2006). The ambidexterity literature generally conducts high-level strategic and organizational analyses that focus on overall structural models and the importance of top management governance to integrate the two opposing approaches within these structures. From this perspective, Rosing et al. (2011) characterize different ambidextrous leadership styles. Turner et al. (2013), Junni et al. (2013) and O’Reilly and Tushman (2013) all call for research to understand the organizational mechanisms and processes within such organizational patterns. From this perspective, Ben Mahmoud-Jouini et al. (2007) identify, under the terminology of “multiplex ambidexterity”, the importance of the role of innovation units (or labs) and specific managers in combining different forms of ambidexterity. Projects, Programmes and Ambidexterity The organization of projects does not figure explicitly in the aforementioned studies. However, it is clear that the field of project management has interesting contributions to make, as projects are the primary organizational framework for orchestrating the sequence of activities from exploration to exploitation. Research in the early 1990s demonstrated how the introduction of new practices of project management into product development engineering improved the ability to develop innovative offerings within incumbent firms (Clark and Fujimoto, 1991; Midler, 1993, 1995; Wheelwright and Clark, 1992b).

170  Handbook on innovation and project management

Over the next decade, the scope of project management expanded from implementation projects to more exploratory situations (Gastaldi and Midler 2005; Lenfle, 2008). Lenfle (2008, 473–474) characterized five specific features that differentiate exploratory projects from implementation projects: They are strategically ambiguous (as opposed to an implementation project following a clear strategic formulation); they take a proactive approach (rather than a demand-pulling process); they are not driven by a clearly specified outcome or goal (as opposed to a target-driven project); they explore new knowledge (as opposed to integrating and leveraging existing knowledge); and their temporality is characterized by hidden urgency and multiple horizons (as opposed to the explicit deadlines and clear timelines of implementation projects). Such specificities call for management principles that differ from usual good project management practices. In a recent article, Lenfle (2016) showed how the institutional context could impose irrelevant project management models on such pathfinder projects, making them seem “strange” because their specificity was not explicitly recognized. Such exploration project management corresponds perfectly to the mission of exploration units as defined in the structural ambidexterity. Several studies also show that the boundary between exploratory projects and more traditional development projects is not clear-cut as soon as the complexity and the innovative dimension of the projects are high. This is the case for certain mega infrastructure projects with innovative components (Davies et  al., 2014) or complex technological projects, described as “hybrid” projects (Tillement et al., 2019). Moving from single-project management to multi-project management literature, project portfolio management can be seen as a way to implement sequential ambidexterity within organizations. The project management literature analyses two key issues in such a process: resources and learning. The issue of resource allocation is addressed by the step process stream (Cooper et  al., 1998; Teller et  al., 2012). Here, the goal is to organize competition between projects for scarce resources by prioritizing them along a sequence of phases from research to development to market launch. An important advantage of this sequential coordination is to conserve resources for risky, long-term projects that would inevitably lose out in a harsh financial comparison with short-term projects (Christensen and Raynor, 2013). Petro et al. 2020 confirm the positive aspect of projectportfolio management as an ambidexterity orchestration too. But their quantitative approach adopts a broad definition of portfolio management, whereas, in this chapter, we differentiate different types, from resource allocation optimization oriented to learning capability oriented. Yet, from this second perspective, an important limitation of the traditional stage-gate approach is that it introduces discontinuities in the innovation process that (i) make longitudinal transfer and knowledge sharing more difficult and (ii) increase the time to market for disruptive innovations (Sethi and Iqbal, 2008). Pellegrini et al. (2015) mobilize the concept of programme management (Artto et al. 2009) to analyse how a multi-project approach can contribute “as the framework or organizational structure for shaping and governing strategy implementation, simultaneously managing and synchronizing concurrent flows of change carried out by projects”. Citing the case of a large bank’s deep transformation strategy, they show how programme management appears to require a key level of coordination to bridge the long-term radical transition track with shorterterm operational change projects within the company. Such programme management is rather consistent with contextual and network ambidexterity, where local incremental projects (internal or external) will be coordinated to contribute to a more radical transition. Other project theories focus on the learning processes that take place within projects, between successive projects and between projects and permanent organizational structures.

Corporate innovation strategies and multi-project management  171

Brady and Davies (2004) envision a model of global learning, moving from existing knowledge to pioneering projects, then from project to project, and finally from project to permanent organization. Loch et  al. (2006) propose a typology to characterize four different types of multi-project processes that can be mobilized in exploring an uncertain and complex domain. Trial-and-error learning is the typical mode of exploration in start-ups, whereas a large pharmaceutical company relies on selectionism (i.e. exploring different solutions in parallel). Planning and risk management are appropriate for complex but less uncertain situations, while a combination of learning and selectionism is required when complexity is associated with high uncertainty (the type of uncertainty that Loch et al. call “unknown unknowns”). This chapter will focus on two different approaches that contribute to this stream of multiproject management where cross-project learning effectiveness is a key competency issue, due to the uncertainty of the innovation context explored. They both try to overcome the limitations of more traditional portfolio management systems when faced with a context of radical innovation. In the following section, we will focus on the lineage management approach, which fits well into the strategy of temporal ambidexterity, sequentially organizing the work of exploration and exploitation. Project lineage management proposes an approach focused on rationalizing learning between successive projects. In the third section, we will develop the ambidextrous programme concept, which addresses the challenge of coordinating (i) breakthrough, (ii) massive and (iii) urgent transitions, leading to managing simultaneously heterogeneous projects, in terms of horizon and content.

PROJECT LINEAGE MANAGEMENT Project Lineage: A Sequence of Projects with Increasing Value The success or performance of a project is traditionally seen as the achievement of objectives in terms of quality, costs, time and profits generated. The multi-project approach (portfolio, platform, programme) has made it possible to optimize these variables over a population of projects. However, even if the importance of learning mechanisms within a firm and within a population of projects has been widely discussed, very few works have explicitly focused on the dynamics integrating the progressive construction of assets and project management. This is what the concept of project lineage management attempts to explain. Indeed, many cases show that the success of a project is not only based on the performance of the management of a single project but on the management of a sequence of projects which, over time, will progressively build a path of profitability around a given concept. For instance, Nespresso was not an immediate success. On the contrary, after patents for capsule machines were filed in 1970, the project totally failed to deploy these capsule systems on machines intended for professionals (hotels, restaurants, etc.), but the development of an automated capsule insertion and ejection system in 2000 rebounded in 2004 with a first machine for individuals which sold more than a million units, opening the way to the development of a new market for espresso pods which was to experience tremendous growth. In 2015 the subsidiary’s turnover was estimated at €5 billion (Cimon and Poulin, 2017). Another well-known example is the Toyota Hybrid Prius case. The project can be considered a stroke of genius by Toyota. But it is precisely not a coup. According to our estimates,

172  Handbook on innovation and project management

the Prius 1 project cost the firm around €1 billion. But the firm used the assets built up from this “failure” to deploy its technologies in the hybrid market, which it had in fact created, with the success that we know today (Itazaki, 1999). The same story could be told of the iPod, whose first launch was an abject failure, but which opened the way to a connected music market and led to the success of multiple “cousin” products, or Renault’s Logan, an initiative that started successful but small, and which has evolved into a succession of successful major projects, each time developing the assets built by the previous projects, with this “Global Entry” programme accounting for nearly 20 per cent of Renault’s revenues in 2019 (Maniak et al., 2014b; Midler, 2013a; Midler et al., 2022). All these cases show that project profitability is not built solely on a single project but on a succession of cousin projects that build on each other. At the Crossroads of Different Theoretical Fields The difficulty in capturing this phenomenon theoretically stems largely from the fact that it is based on mechanisms that cross different fields of literature. In particular, this implies characterizing the links between strategy and project management. Historically, projects were first seen as a consequence of strategy. Projects were then defined as the application of existing strategy, knowledge and methods to achieve an objective defined by one or more stakeholders (Wheelwright and Clark, 1992; PMI, 2004). The fact that a key project portfolio notion to evaluate and control project progression is the project “alignment” (Cooper et al., 1998) to strategy mirrors this perspective of a clear ex-ante definition of strategy to project management. Since the 1990s, a new school of thought has been developing, affirming the link between strategy and project management, with projects being defined as a powerful lever for implementing strategy, whether at the level of a project (Morris and Jameson, 2005, 2013) or a portfolio of projects (Artto and Dietrich, 2007; Kaplan and Norton, 1996; Markides, 1999). At the same time, several studies have shown that projects can have behaviours and even outputs that were not foreseen at the time of their initial definition (Loch et al., 2011; Wideman, 1992). Such an evolution to the project strategizing perspective in the field of project management mirrors the growth of the emerging strategy concept in the field of corporate strategy (Mintzberg and Waters, 1985). This implies piloting projects with specific methods such as trial-and-error processes (Pich et al., 2002), milestones that are not oriented towards the detection of deviations from the forecast but towards the learning generated at each stage (Lenfle, 2008; McGrath and MacMillan, 1995; Iansiti and Clark, 1994) or a selection strategy between several parallel alternatives (Sommer and Loch, 2004). In the end, these works have shown that projects are not only execution processes but also processes that integrate a dose of uncertainty that will lead them to modify the initial specifications or even the purpose set by the strategic plans. From a strategic point of view, these considerations also refer to the notion of real options (Copeland and Antikarov, 2001; Kock and Gemünden, 2019a). Traditional investment approaches are based on forecasting scenarios with highly uncertain horizons, and therefore force initial choices that are risky between the credibility of such scenarios. The lineage approach commits the investment process to a first project of limited ambition and risk, and postpones the decision on subsequent investment development choices, when the returns on the first project will be able to shed light on the opportunity and direction of the development trajectory to be chosen, according to a non-risky opportunistic gain approach. We see here that the relevance of this strategic reasoning depends on the company’s ability to operate

Corporate innovation strategies and multi-project management  173

these successive developments in an agile and economical way. Kock and Gemünden (2021) demonstrate the performance of the “Triple A portfolio management” that defines portfolio practices that combine ambidextrous, adaptative and agile capabilities. As always in the field of innovation, the relevance of a strategy depends on the conditions of its implementation, in terms of process and organization. Secondly, it implies admitting that projects will not only obey a top-down orientation based on pre-existing knowledge but will also act in a more bottom-up way and feed the company’s assets (Burgelman and Sayles, 1988). The articles by Brady and Davies (2004) and Iansity and Clark (1994) are useful on the subject. They explain a sequence of interaction between projects and the firm’s assets, with a first project (vanguard) generating new capabilities for the firm, a phase of transferring this knowledge and these capabilities to other projects, and finally a phase of integrating these new capabilities into the host organization, particularly its routines. The notion of a skunkwork project is similar, focusing on how a project can disregard and rebuild new competencies and design routines (Bommer et al., 2002). This approach has been widely declined in many studies (Brady and Davies, 2004; Eriksson, 2013; Marsh and Stock, 2006). On this point, we must therefore consider that the project not only builds on pre-existing assets but also generates new ones, and that parallel or subsequent projects will be able to exploit these new assets. If these inter-project learning mechanisms are well known today, they remain relatively abstract, insofar as we do not really know what objects are the focus of this inter-project capitalization, and even less what the organizational forms or processes are that could allow such trajectories. Fewer studies analyse how projects build on each other, although the problem of transferring knowledge from one project to the follow-up project has been known for a long time (Clark and Wheelwright, 1992; Prencipe and Tell, 2001). On the first point, the theories developed by Hatchuel and his colleagues are instructive (Hatchuel et al., 2006; Le Masson et al., 2010). Based on concepts of design reasoning the authors explain the concept of “lineage”. A lineage can be defined as a sequence of “cousin” products, which are based on the same knowledge domain and the same product concept, and where each new product development generates learning that can be used on future “cousin” products. This approach makes it possible to specify and embody multi-project learning in “cousin” objects, and to move from the abstraction of capitalization to the concrete. However, these theories do not talk about the processes (project) or the underlying organizations. On the second point – the organizational forms favourable to inter-project capitalization – the literature remains strangely silent. We find several works on the first innovative project, i.e. how to introduce knowledge developed ex-ante into development projects, which point out in particular the importance of having a team responsible for making the transition from research to development (Iansiti and Clark, 1994). Regarding capitalization from one project to the next along a sequence of projects, there are several works indicating the importance of maintaining the same team along this trajectory (Bartsch et al., 2013; Midler, 2013b). But this vein of research needs further development. Project Lineage Management as a New Strategic Management Perspective These considerations invite to define the concept of “project lineage management” (Jullien et al., 2013; Maniak and Midler, 2014; Maniak et al., 2014b; Midler, 2013b) as a multi-project management perspective which encompasses the following aspects:

174  Handbook on innovation and project management

• • • •

The importance of considering the dynamics of a sequence of projects with the dynamic of assets empowering these projects. The importance of serendipity and reactivity to make a product’s conceptual identity expand along a sequence of coherent projects. The possibility that the flow of projects belonging to this sequence can influence and redefine the corporate strategy along the way. The organizational side of such sequences, especially the composition of the project teams which is involved in the lineage of projects.

Most of the multi-project management theories aim to reduce risks and costs. The portfolio approach optimizes the allocation of the company’s scarce resources between competing projects. The programme and platform approaches organize the coordination between complementary contemporary projects. But all typically neglect longitudinal interdependencies. Multi-project lineage management introduced a new unit of analysis and a new way to consider value creation along the path of several projects, encompassing the strategic, managerial and organizational aspects. The initial empirical basis that gave rise to this concept was the automotive industry. As mentioned earlier, Renault’s Entry line and Toyota’s Hybrid line showed that it could be rational to invest in a “vanguard project” (the Logan for the Entry line, the Prius for the Hybrid line) even if these projects were totally loss-making (Maniak and Midler, 2014; Maniak et al., 2014b; Midler, 2013b). The genius was to consider the value of these initial projects as an investment in assets, rather than as a “one-off” that had to reach a maximum level of profitability. From then on, and from one step to the next, this initial project was followed by related ones (Sandero, Duster and Kwid for the Entry line; Prius 2 and 3 and the entire Toyota and Lexus range). Those projects relied on the assets built by the previous ones to build up a formidable profitability which could not have been achieved and even considered if the first project had not existed. Project Lineage Management As mentioned, the concept is consistent with the notion of emergent strategy (Mintzberg, 1978; Mintzberg and Waters, 1985; Burgelman, 1983). The concrete implementation of these serendipity mechanisms in decision-making systems thus requires the implementation of a “planned emergence” regime (Grant, 2003). This requires companies to set up short-loop decision systems, a good dose of flexibility in the decision systems and a focus on achieving macro objectives rather than on monitoring the completion of a list of tasks. The muti-project level of analysis is particularly relevant for characterizing these deliberate and emergent steering modes (Burgelman and Sayles, 1988; Noda and Bower, 1996; Shenhar et al., 2001; Meskendahl, 2010). The concept of lineage addresses all phases of multi-project management. It involves allocating resources at the outset to projects that are clearly outside the traditional scope of the firm in terms of technology or market,1 but that point to future strategic trajectories. For example, if the company’s strategy is to expand internationally, a project targeting international markets will be prioritized even if it does not have a very attractive immediate payoff. The project can be formulated in a simple way as a breakthrough concept or a metaphor (Hatchuel et al., 2006), which in itself constitutes a call for emerging strategies insofar as management does not know a priori where the exploration of this concept will lead.

Corporate innovation strategies and multi-project management  175

The formation of the team is also a key point because it is a question of finding members of the project team who are not too procedural and who are open to both exploration and exploitation (in this case development). Project tracking within the portfolio is also specific. It is not simply a matter of making a resource allocation or a stage-gate sequence with go/no-go decisions, but to have, as mentioned earlier, richer and more flexible decisions than a compliance check. For example, this may involve a geographical reorientation of the target offer, a revision of the functional specifications, etc. In addition, and this is certainly one of the greatest specificities of the approach, it is also a question of identifying the assets that this project will potentially create, assets on which the company can build future projects. Thus knowledge management becomes central to this process. Of course, at an early stage, it is very difficult to identify these assets, but as the project progresses they can gradually be made explicit. Budget allocation decisions are therefore based on both the expectation of direct gain and the potential for the creation of strategic assets. We could compare this trade-off by saying that project portfolio control focuses on the cash result, whereas lineage control also integrates the result on the company’s assets. Once the first project has been completed and the first offers have been put on the market, it is important to pay attention to the first customer feedback and to the reality of the actual creation of assets associated with the project. Has the sales network really been modernized? What new technological knowledge has been acquired? Has the concept of the offer been understood by the customers? On the basis of this evaluation, the next phase can be initiated. This is followed by a deployment phase that will combine, to varying degrees, re-exploitation and re-exploration. The company can choose to base its next projects on these newly

Figure 8.1   The project lineage: a vehicle to project capitalization process

176  Handbook on innovation and project management

created assets without taking into account the recreation of new assets, or it can replay a new “lineage head” project (Chapel, 1997; Le Masson, 2001) that will focus on both the P&L and the contribution to the company’s balance sheet. The top management must also take advantage of the results of this vanguard project to modify, if necessary, the proclaimed strategy.​ Such a project-to-project capitalization needs specific project organization and resource management. The existence of a leadership capable of maintaining the “DNA” of the lineage through the successive metamorphoses of the projects is a necessary condition. This leadership can be embodied in the notion of a programme or platform director, which is understood as the coordination of the projects of the lineage over time, whereas this notion is generally considered as the responsibility of coordinating a group of projects simultaneously working towards a common objective. Beyond the leadership of the lineage director, the ability to deploy the lineage strategy is also highly dependent on the career management of the members of the successive project teams, which ensures the transmission of skills and management methods, even when the projects are carried out in different geographical areas (Midler, 2019; Midler et al. 2023). Ongoing research on this concept concerns four aspects. • • • •

The relationship between this dynamic project portfolio management and platform management, i.e. component commonality (Laine et al., 2016), and how this approach changes the way of approaching “new product development” (Laine et al., 2016). The performance of a project portfolio management balancing a portion of projects following a deliberate strategy and others an emergent strategy (Kock and Gemünden, 2019b). The relationship between lineage project portfolio management and the issue of organizational ambidexterity (Berggren, 2019). The relationship between lineage management and agile project management capability. As already mentioned, the efficiency of lineage learning relies on the capability to quickly derivate and adapt solutions to new business opportunities (Kock Gemünden, 2021; Rémondeau et al., 2021).

It is precisely on the basis of the latter questioning that the second concept explained in this chapter, namely ambidextrous programme management, is concerned.

AMBIDEXTROUS PROGRAMME MANAGEMENT Research on ambidexterity has shown the limitations of these different approaches, which are in line with the limitations of the associated multi-project management models. •

As has been pointed out (Midler et  al., 2019), sequential ambidexterity and portfolio management do not encourage learning between projects and increase the time to market for disruptive innovations. Lineage management, on the other hand, is focused on interproject capitalization but takes a long time to scale up the pilot concept.

Corporate innovation strategies and multi-project management  177

• •

Structural ambidexterity based on the management of exploration projects often comes up against the obstacle of the recovery of explored concepts by the operating business units, which alone can ensure their effective deployment. Finally, the decomposition of breakthrough innovation management into a programme of coordinated incremental projects is not always possible when the breakthrough in question involves major uncertainties.

These different limitations do not allow us to effectively deal with the context of disruptive innovations that are both radical and urgent, such as those encountered in the current challenge of responding to climate transition: decarbonization of automobile mobility involving the replacement of the dominant thermal engine design by electrification; or decarbonization of air transport, for example. These contexts combine the need for major technological breakthroughs with significant areas of uncertainty, and this is on a particularly short time constraint. In this section, we characterize a form of multi-project management that encompasses both exploratory projects and shorter-term development projects under the name of “ambidextrous programme management”. We will first characterize the strategic context in which these projects have emerged, that of the ambidextrous enterprise. We will then characterize, on the basis of an emblematic example, the specificity of this model and its differences from other forms of multi-project management such as portfolio management and programme management. We then study the rationality that it pursues and conclude with its advantages and limitations. This context is at the origin of the experimentation of new forms of multi-project management, formalized by Midler et  al. (2019) in the literature on the concept of “ambidextrous programmes”. Ambidextrous Programme Management: A Characterization Based on the analysis of an emblematic case of this type of context, that of an autonomous vehicle programme at a global car manufacturer, Midler and Maniak (2019) defined ambidextrous programme management by the following four characteristics: (1) It involves multiple projects. (2) The projects involved are complex. (3) The projects have strong interdependencies that require a specific coordination effort (which explains the name “programme”). (4) The projects have heterogeneous objectives, some of which are oriented towards implementation (or operation), and others towards exploration (this duality explains the qualification “ambidextrous”). Here we present the results of our case study, which illustrate how these principles are embodied in the organization and the R&D projects concerned by the autonomous mobility initiative within the car manufacturer studied. The following figure shows how the car manufacturer’s autonomous vehicle programme (i) brings together projects of different natures (exploratory projects, vehicle development, technological development, development of on-board equipment), (ii) is deployed within the different divisions of the company and (iii) associates companies or organizations outside the firm (Figure 8.1).

178  Handbook on innovation and project management

MAPPING THE VARIOUS PROJECTS INVOLVED IN THE AUTONOMOUS MOBILITY AMBIDEXTROUS PROGRAMME

Source:   Midler et al., 2019.

Figure 8.2  The various projects involved in the autonomous mobility initiative The arrows r​ epresent the projects and the rectangles represent the company divisions in the large rectangle, with the external units and partners involved outside. The projects mobilize internal or external resources within internal functional divisions and external units. The projects at the top of the figure are exploratory while those at the bottom are development projects leading to the market in the short term. Projects A and B are typical research projects on technological breakthroughs. Projects C, D, E, F, G and H prepared and matured technological solutions and components using an “on the shelf” featuring logic (Maniak et al., 2014a) to be included in AM vehicles. Project I is an autonomous driving equipment development programme. Projects J and K are vehicle development projects that had already been programmed in the group’s product planning. Projects L and O are complex integrated prototype projects. Projects M and N are technological development projects needed for AM deployment. Projects P, Q and R were field operational tests in different environments in various countries.

This mapping allows us to characterize the specificity of the scope of the ambidextrous programme, compared to the classic structures of multi-project management. On the one hand, it associates projects of different categories (exploration, complete vehicle development, equipment development, technologies and field experimentation). It combines

Corporate innovation strategies and multi-project management  179

different horizons (long-term exploration, shorter-term development). It involves internal bodies from different divisions. It brings together internal projects and cooperation with external partners. On the other hand, it allows for communication and learning between these different components, which would not be possible with traditional processes that are “siloed” by project category or by the scope of the bodies involved. Coordination between these multiple bodies takes place at two levels. At the level of project managers, in addition to the established processes mentioned earlier, a communication body for the extended perimeter makes it possible to put the managers of the various projects in contact, regardless of the unit to which they belong. At the strategic level, a senior vice-president’s committee ensures the overall governance of the AM domain. Ambidextrous Programme as an Orchestration Process of Ambidexterity The research cited concerns a transition in progress. It is therefore not possible to verify whether this original mode of multi-project organization will deliver the promises that are associated with ambidextrous programme management: shortening the time to market and scaling of disruptive innovations; reconciling the valorization of short-term learnings by development projects by coordinating them with longer-term trajectories; and articulating different but highly interdependent levels of projects (from technology to platforms and to complete products and equipment). Several examples (Midler et al., 2019) show, however, that these arrangements have already enabled learning, coordination and experience transfer that would not have been possible with other project coordination processes. It allows us to put forward the following three hypotheses on the development of these multi-project management models in the context of the response of companies to the “Great Challenges” that industries are currently facing, in order to respond to societal challenges concerning the preservation of the environment and global warming. H1: An extension of the concurrent engineering approach to learning about innovative breakthroughs. Exploration and implementation projects are traditionally coordinated by sequential stagegate processes. Ambidextrous programme management, as it is manifested in our case, sets up a different coordination process aimed at accelerating longitudinal knowledge transfers and mutualizations and shortening the time to market for breakthrough innovations as well as for the intermediate achievements of learning trajectories. This approach extends to disruptive innovation the transformation of concurrent engineering processes deployed in the 1990s in the area of product development. H2: A closer and more continuous articulation between the formalization of strategic choices and learning how to implement them. Ambidextrous programme management re-internalizes within multi-project management the tension between strategic choice in uncertainty and operational implementation of these choices, a tension that had been dissociated in traditional portfolio management. This has several important consequences both in the field of strategy and in that of project management and organization.

180  Handbook on innovation and project management

Ambidextrous programmes must support strategic ambiguity. Traditional phased portfolio management emphasizes the importance of strategic alignment as a key criterion for evaluating and selecting projects, with the strategy assumed to be clear ex-ante. Ambidextrous programmes, by making the variety of explorations visible, show the real dialectic between strategy formulation and exploration of possibilities, and thus force the actors of the organization to bear the uncertainty and the real strategic instability of the company. From this point of view, the concept of an ambidextrous programme seems relevant to the formulation of emergent strategies (Mintzberg and Waters, 1985; Burgelman, 1983). This characteristic has two consequences. First, it indicates the need to position the ambidextrous programme function at the strategic level of the firm. Second, it implies that the tension resulting from this strategic ambiguity is deliberately maintained within the programme, and thus understood and supported by actors accustomed to more structured and stable organizational contexts. In particular, ambidextrous programmes combine both competition and cooperation between projects, in accordance with a learning logic. In the selectionist approach (Loch et al., 2011), multi-project management usually integrates competition between projects. Such a competition context does not favour cooperation through cross-learning. Interaction between projects is more complex here. H3: What coordination is necessary for ambidextrous programmes? The literature on programme management emphasizes the importance of a programme manager who is empowered to coordinate the overall portfolio of projects. Such a proposal mirrors the emphasis on high-level sponsorship in the ambidextrous literature and clearly resembles the multiplex structure defined by Ben Mahmoud-Jouini et al. (2007). The leadership literature (Rosing et al., 2011) proposes that ambidextrous leadership emphasizes three elements: “(1) opening leader behaviors to foster exploration, (2) closing leader behaviors to foster exploitation, (3) and temporal flexibility to switch between them as the situation requires” (Rosing et al., 2011, 966). Clearly, this leadership style addresses the dilemma of competition/ cooperation between projects within the ambidextrous programme. In addition to this decision-oriented perspective on the role of the programme manager, research on lineage management (Midler, 2013; Maniak and Midler, 2014; Kock and Gemünden, 2023) has emphasized the role of managing multi-project sequences and longitudinal interdependencies of projects in order to implement cross-project learning. It emphasizes the importance of human resource management within the programme to leverage and transfer knowledge between sequential as well as parallel projects. The literature on knowledge integration and transfer within and between projects (Sydow et al., 2004; Enberg et al., 2006) emphasizes the multi-level dimension of inter-project learning processes. It is clear that the scope and dispersion characteristics of ambidextrous programmes are not compatible with the collocation approach that is often suggested as an effective way to transfer tacit knowledge. Ambidextrous programme coordination thus appears to be a loosely coupled system (Orton and Weick, 1990) that could enhance shared values and strategic decision-making among projects that differ in nature, horizons and goals. In addition to the specific leadership style of the programme manager, a hypothetical way to implement this loosely coupled system could be the design of an “ambidextrous programme hub” that could develop regular face-to-face communication among members of heterogeneous programme projects. Such a hub could not be equated with a programme team under the

Corporate innovation strategies and multi-project management  181

authority of the supervisor but rather would be an organizational process to stimulate regular and systematic learning between projects. A classic term to define such a knowledge-sharing process is the community of practice – a concept that has been widely developed in academic learning and knowledge management communities (Wenger, 1998). We prefer the hub metaphor because it emphasizes the importance of coordinating the connection points between different learning tracks, even if these tracks have different orientations and time perspectives (just as an airport hub connects different destinations and flights, from long distance to medium and short distance, bringing continuity to the customer experience). In our case study, we saw the beginnings of such a platform, but it could clearly be scaled up and streamlined. There is an opportunity here for the field of project organization to explore and define new organizational and methodological artefacts to better coordinate ambidextrous programmes. Managing Ambidextrous Programmes: Towards an Orchestration of Ambidexterity Our case shows how projects within ambidextrous programmes orchestrate different types of ambidexterity patterns, from contextual to structural, network and multiplex configurations. Not surprisingly, projects are the natural vehicle for developing “skunk” (Jenkins, 2001), “vanguard” (Brady and Davies, 2004) or exploration (Lenfle, 2008) projects in an organizational pattern of structural ambidexterity. But ambidextrous programmes are also the means to involve, stimulate and coordinate the actions of professionals in situations of contextual ambidexterity. Network ambidexterity is driven by a dual pattern: some partnerships are managed in a project orchestration, while others are more function- or knowledge-based cooperations. While the discussion of this case can help characterize ambidextrous programme situations and their challenges, it still does not allow us to derive robust principles for managing them. First, we still lack data on programme outcomes, as we adopted a real-time methodology to study the AM initiative at Global Car. Second, such a management situation is, as far as we know, emerging in the industry, and will be subject to a learning trajectory – our research being part of that collective effort. What we can do, however, is propose hypotheses from the existing literature on programmes and ambidexterity and evaluate them against the ongoing situation we observed at Global Car.

CONCLUDING REMARKS AND FURTHER RESEARCH The study of the management of innovation projects implies crossing the fields of corporate strategy, firm organization and project management. Indeed, innovation projects cannot be considered simple implementations of innovation strategies that have been clearly formulated beforehand. On the contrary, they are often the basis for the constitution of the ingredients that allow the formulation of these strategies. Innovation strategies and management of innovation projects are therefore two processes that need to be articulated in the time and space of the organization. Lineage management and management of ambidextrous programmes are two organizational forms for achieving this articulation. The first organizes in a longitudinal way the joint construction of the emerging strategy and the lineage of successive projects that constitute it. The second organizes, in the face of an imperative need for a major transition, the coordination of heterogeneous projects aimed at preparing for the future break while preserving the

182  Handbook on innovation and project management

profitability of short-term projects. Each in its own way, these two forms of multi-project management contrast with the approaches developed in the 1990s and 2000s: portfolio management and programme management, both of which organized the steering of projects by assuming the clear and stable ex-ante formulation of an overarching innovation strategy. The current period, which sees, with the imperatives of the ecological transition, the emergence of new innovation strategies based on renewed value criteria, seems to be a particularly favourable context for the deployment in various sectors of these forms of management of multiple innovation projects. This opens the way to rich perspectives for research in this field.

NOTE 1.

The strategy of deriving from existing products to differentiate and renew ranges is obviously not new. But this is done ex-post to enhance and extend already established rents. Here, the strategic aim is to explore ex-ante the possibility of creating new areas of value.

REFERENCES Artto, K., Martinsuo, M., Gemuënden, H.G., and Murtoaro, J. (2009). Foundations of program management: A bibliometric view. International Journal of Project Management, 27(1), 1–18. Artto, K.A. and Dietrich, P.H. (2007). Strategic business management through multiple projects. In P.W.G. Morris and J.K. Pinto (Eds.), The Wiley guide to project program & portfolio management (pp. 1–33). New Jersey: John Wiley & Sons Inc. Bartsch, V., Ebers, M., and Maurer, I. (2013). Learning in project-based organizations: The role of project teams’ social capital for overcoming barriers to learning. International Journal of Project Management, 31(2), 239–251. Benghozi, P.J., Charue, F., and Midler, C. (edts et co-auteur de 7 chapitres) (2004). Innovation based competition and design systems dynamics. Paris: L’Harmattan, 347p. Ben Mahmoud-Jouini, S.B., Charue-Duboc, F., and Fourcade, F. (2007). Multilevel integration of exploration units: Beyond the ambidextrous organization. In Academy of management proceedings, August (Vol. 2007, No. 1, pp. 1–6). Briarcliff Manor, NY: Academy of Management. Berggren, C. (2019). The cumulative power of incremental innovation and the role of project sequence management. International journal of project management, 37(3), 461–472. Brady, T. and Davies, A. (2004). Building project capabilities: From exploratory to exploitative learning. Organization Studies, 25, 1601–1621. Burgelman, R.A. (1983). Corporate entrepreneurship and strategic management: Insights from a process study. Management science, 29(12), 1349–1364. Burgelman, R.A. and Sayles, L.R. (1988). Inside corporate innovation. Simon and Schuster. Chapel, V. (1997). La croissance par l’innovation intensive: de la dynamique d’apprentissage à la révélation d’un modèle industriel le cas tefal. Doctoral dissertation, ENSMP. Chesbrough, H., Vanhaverbeke, W., and West, J. (Eds.). (2006). Open innovation: Researching a new paradigm. Oxford: Oxford University Press on Demand. Christensen, C. and Raynor, M. (2013). The innovator’s solution: Creating and sustaining successful growth. Harvard Business Review Press. Cimon, Y. and Poulin, D. (2017). Nespresso’s strategic and operational excellence: A review and logistical implications. In Supply chain forum: An international journal (Vol. 18, No. 1, pp. 30–35). Taylor & Francis, January. Clark, K.B. and Fujimoto, T. (1991). Heavyweight product managers. McKinsey Quarterly, 1, 42–60. Cooper, R.G., Edgett, S.J., and Kleinschmidt, E.J. (1998). Portfolio management for new products. Cambridge, MA: Perseus Books. Copeland, T. and Antikarov, V. (2001). Real options (No. Book). New York: Texere.

Corporate innovation strategies and multi-project management  183

Davies, A., MacAulay, S., DeBarro, T., and Thurston, M. (2014). Making innovation happen in a megaproject: London’s crossrail suburban railway system. Project Management Journal, 45(6), 25–37. Duncan, R.B. (1976). The ambidextrous organization: Designing dual structures for innovation. In R. Kilman and L. Pondy (Eds.), The management of organizational design (pp. 167–188). New York: North Holland. Enberg, C., Lindkvist, L., and Tell, F. (2006). Exploring the dynamics of knowledge integration: Acting and interacting in project teams. Management Learning, 37(2), 143–165. Eriksson, P. E. (2013). Exploration and exploitation in project-based organizations: Development and diffusion of knowledge at different organizational levels in construction companies. International Journal of Project Management, 31(3), 333–341. Gastaldi, L. and Midler, C. (2005). Exploration concourante et pilotage de la recherche. Une entreprise de specialites chimiques. Revue Française de Gestion, 31(155), 173–189. Gibson, C.B. and Birkinshaw, J. (2004). The antecedents, consequences, and mediating role of organizational ambidexterity. Academy of Management Journal, 47, 209–226. Grant, R.M. (2003). Strategic planning in a turbulent environment: Evidence from the oil majors. Strategic Management Journal, 24(6), 491–517. Hatchuel, A., Le Masson, P., and Weil, B. (2006). Building innovation capabilities. The development of design-oriented organizations. In Innovation, science and industrial change, the handbook of research (pp. 294–312). New York: Oxford University Press. Iansiti, M. and Clark, K. (1994). Integration and dynamic capabilities: Evidence from product development in automobiles and mainframe computers. Industrial and Corporate Change, 3(3), 507–605. Itazaki, H. (1999). The Prius that Shook the world. Tokyo: Nikkan Kogyo Shimbun. Jenkins, D.R. (2001). Lockheed secret projects: Inside the skunk works. Berlin: Zenith Imprint. Jullien, B., Lung, Y., and Midler, C. (2013). The logan epic: New trajectories for innovation. Paris: Dunod. Junni, P., Sarala, R.M., Taras, V., and Tarba, S.Y. (2013). Organizational ambidexterity: A meta-analysis. Academy of Management Perspectives, 27(4), 299–312. Kaplan, R.S. and Norton, D.P. (1996). Linking the balanced scorecard to strategy. California Management Review, 39(1), 53–79. Kock, A. and Gemünden, H.G. (2019a). Project lineage management and project portfolio success. Project Management Journal, 50(5), 587–601. Kock, A. and Gemünden, H.G. (2019b). Innovation portfolio management, ambidextrous, adaptative and agile. Kock, A., and Gemünden, H.G. (2023). Addressing the challenges of new product development by Triple-A project management. Research Handbook on Complex Project Organizing, 193. Laine, T., Korhonen, T., and Martinsuo, M. (2016). Managing program impacts in new product development: An exploratory case study on overcoming uncertainties. International Journal of Project Management, 34(4), 717–733. Lavie, D. and Rosenkopf, L. (2006). Balancing exploration and exploitation in alliance formation. Academy of Management Journal, 49(4), 797–818. Le Masson, P. (2001). De la R&D à la RI D: Modélisation des fonctions de conception et nouvelles organisations de la R&D. Doctoral dissertation, Paris, ENMP. Le Masson, P., Weil, B., and Hatchuel, A. (2010). Strategic management of innovation and design. Cambridge University Press. Lenfle, S. (2008). Exploration and project management. International Journal of Project Management, 26(5), 469–478. Lenfle, S. (2016). Floating in space? On the strangeness of exploratory projects. Project Management Journal, 47(2), 47–61. Loch, C.H., DeMeyer, A., and Pich, M. (2011). Managing the unknown: A new approach to managing high uncertainty and risk in projects. Hoboken, NJ: John Wiley & Sons. Maniak, R. and Midler, C. (2014). Multiproject lineage management: Bridging project management and design-based innovation strategy. International Journal of Project Management, 32, 1146–1156. Maniak, R., Midler, C., Beaume, R., and Von Pechmann, F. (2014a). Featuring capability: How carmakers organize to deploy innovative features across products. Journal of Product Innovation Management, 31(1), 114–127.

184  Handbook on innovation and project management

Maniak, R., Midler, C., Lenfle, S., and Le Pellec, M. (2014b). Value management for exploration projects. Project Management Journal, 45(4), 55–66. March, J.G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2, 71–87. Marsh, S.J. and Stock, G.N. (2006). Creating dynamic capability: The role of intertemporal integration, knowledge retention, and interpretation. Journal of Product Innovation Management, 23(5), 422–436. Markides, C.C. (1999). A dynamic view of strategy. Sloan Management Review, 40(3), 55–63. Meskendahl, S. (2010). The influence of business strategy on project portfolio management and its success—A conceptual framework. International Journal of Project Management, 28(8), 807–817. McGrath, R.G. and MacMillan, I.C. (1995). Discovery driven planning. Philadelphia, PA: Wharton School, Snider Entrepreneurial Center. Midler, C. (1993, 2012). L'auto qui n'existait pas: Management des projets et transformation de l'entreprise. Dunod. Midler, C. (1995). “Projectification” of the firm: the Renault case. Scandinavian Journal of Management, 11(4), 363–375. Midler, C. (2013). Implementing a low-end disruption strategy through multiproject lineage management: The logan case. Project Management Journal, 44(5), 24–35. Midler, C. (2019). Projectification: The forgotten variable in the internationalization of firms’ innovation processes? International Journal of Managing Project in Business, 12(3), 545–564. Midler, C. Alochet, M., and de Charentenay, C. (2023). The innovation Odyssey, Lessons from an impossible project. Taylor and Francis. Midler, C., Maniak, R., and de Campigneulles, T. (2019). Ambidextrous program management: The case of autonomous mobility. Project Management Journal, 50(5), 571–586. Mintzberg, H. (1978). Patterns in strategy formation. Management Science, 24(9), 934–948. Mintzberg, H. and Waters, J.A. (1985). Of strategies, deliberate and emergent. Strategic Management Journal, 6(3), 257–272. Morris, P. (2013). Reconstructing project management reprised: A knowledge perspective. Project Management Journal, 44(5), 6–23. Morris, P.W. and Jamieson, A. (2005). Moving from corporate strategy to project strategy. Project Management Journal, 36(4), 5–18. Noda, T. and Bower, J.L. (1996). Strategy making as iterated processes of resource allocation. Strategic Management Journal, 17(S1), 159–192. O’Reilly, C.A. and Tushman, M.L. (2004). The ambidextrous organization. Harvard Business Review, 82, 74–8. O’Reilly III, C.A., and Tushman, M.L. (2013). Organizational ambidexterity: Past, present, and future. Academy of Management Perspectives, 27(4), 324–338. Orton, J.D. and Weick, K.E. (1990). Loosely coupled systems: A reconceptualization. Academy of Management Review, 15(2), 203. Pellegrinelli, S., Murray-Webster, R., and Turner, N. (2015). Facilitating organizational ambidexterity through the complementary use of projects and programs. International Journal of Project Management, 33, 153–164. Petro, Y., Ojiako, U., Williams, T., and Marshall, A. (2020). Organizational ambidexterity: Using project portfolio management to support project-level ambidexterity. Production Planning & Control, 31(4), 287–307. Prencipe, A. and Tell, F. (2001). Inter-project learning: Processes and outcomes of knowledge codification in project-based firms. Research Policy, 30(9), 1373–1394. Raisch, S., Birkinshaw, J., Probst, G., and Tushman, M.L. (2009). Organizational ambidexterity: Balancing exploitation and exploration for sustained performance. Organization Science, 20(4), 685–695. Rémondeau, S.L., Le Glatin, M., Poyet, P., and Midler, C. (2021). Agile development: From software to complex industrial products? Euram Conference, June. Rosing, K., Frese, M., and Bausch, A. (2011). Explaining the heterogeneity of the leadership-innovation relationship: Ambidextrous leadership. The Leadership Quarterly, 22(5), 956–974.

Corporate innovation strategies and multi-project management  185

Sethi, R. and Iqbal, Z. (2008). Stage-gate controls, learning failure, and adverse effect on novel new products. Journal of Marketing, 72(1), 118–134. Shenhar, A.J., Dvir, D., Levy, O., and Maltz, A.C. (2001). Project success: A multidimensional strategic concept. Long Range Planning, 34(6), 699–725. Sommer, S.C. and Loch, C.H. (2004). Selectionism and learning in projects with complexity and unforeseeable uncertainty. Management Science, 50(10), 1334–1347. Sydow, J., Lindkvist, L., and DeFillippi, R. (2004). Project-based organizations, embeddedness and repositories of knowledge. Teller, J., Unger, B.N., Kock, A., and Gemünden, H.G. (2012). Formalization of project portfolio management: The moderating role of project portfolio complexity. International Journal of Project Management, 30(5), 596–607. Tillement, S., Garcias, F., Minguet, G., and Duboc, F.C. (2019). Disentangling exploitation and exploration in hybrid projects: The case of a new nuclear reactor development. Project Management Journal, 50(5), 538–553. Turner, N., Swart, J., and Maylor, H. (2013). Mechanisms for managing ambidexterity: A review and research agenda. International Journal of Management Review, 15(3), 317–332. Wenger, E. (1998). Communities of practice: Learning as a social system. Systems Thinker, 9(5), 2–3. Wheelwright, S.C. and Clark, K.B. (1992). Revolutionizing product development: Quantum leaps in speed, efficiency, and quality. Simon and Schuster. Wideman, R.M. (1992). Project and program risk management: A guide to managing project risks and opportunities. Doctoral dissertation, Univerza v Mariboru, Ekonomsko-poslovna fakulteta.

9. Exploratory projects: the state of the art and a research agenda Sylvain Lenfle

INTRODUCTION Today project management (PM) is a mature research field. As demonstrated by Soderlund (2004, 2011), project management research has grown and diversified in different research streams (see the seven schools identified in Söderlund, 2011). In this chapter, we will focus on the research on exploratory projects, which roughly emerged 15 years ago. In our view, this research results from two significant and interrelated changes in PM research. First is the move away from the universal approach behind the standard model of PM1 that did not distinguish between different types of projects. Indeed, as demonstrated by Shenhar and Dvir (2007), “one size does not fit all” and one has to adapt management models to the inner nature of the project. Their NTCP model exemplifies this contingency theory of project management. Second is the coming together of innovation and project management research. Until the early 2000s these two research fields had separate trajectories (Davies et al., 2018). However, things began to change with the growing role of innovation in the strategy of firms (e.g. Le Masson et  al., 2010). This leads a new generation of academics, most of them coming from production and/or innovation management, to study projects. The performance of new product development was the major topic of the 1990s (Clark and Fujimoto, 1991; Wheelwright and Clark, 1992; Midler, 1996). Then, with the strategic question of the firm’s ability to develop radically new products, processes and competencies, the management of projects confronted with unforeseeable uncertainties (which is not the case of NPD projects) emerged at the beginning of the 2000s (Pich et al., 2002; De Meyer et al., 2002) Research on exploratory projects emerges at this crossroads (Brady and Davies, 2004) and has become, during the last 15 years, an important research area (Lenfle et al., 2019). The goal of this chapter is to take a retrospective look at this research stream and to identify avenues for future research on exploratory projects. To do so we will first look at the emergence of the question of exploratory project management by adopting a historical perspective. The second section will focus on the synthesis of the main results of this research stream. Last, in the final part we will try to identify avenues for future research in this field.

THE EMERGENCE OF RESEARCH ON EXPLORATORY PROJECTS If the concept of exploratory projects first appears in the PM literature in Brady and Davis’ 2004 paper, the question of the management of “innovative” projects has an older history. As demonstrated by Davies et al. (2018), the fields of innovation and project management have a 186

Exploratory projects 

187

complex relationship with first a convergence and, quickly, separate trajectories. In this history, it is useful to distinguish four epochs. First epoch. The Second World War brought to the fore the question of the management of “radical innovation” projects. Endeavours such as the Manhattan Project (Rhodes, 1986) or the radar project (Buderi, 1996) raised new technical and managerial challenges for industry, science and the army. As summarized by L. Groves, Manhattan Project director, in his memoirs (1962), the many unknowns of the project forced them to “abandon all normal orderly procedures” almost at the beginning. What we see then is the deployment of very innovative managerial strategies (see Lenfle and Loch, 2010, 2017 for a summary): a. Creation of dedicated organizations mixing, in co-localized spaces like the MIT RadLab or Manhattan Los Alamos, science and engineering in order to foster innovation and speed (Lenfle and Söderlund, 2019). b. Parallel exploration of different technological solutions. c. Rapid experimentation at all levels of the projects. d. Constant reformulation of goals and means during the projects according to what has been learned. Second epoch. Lessons from the Second World War were learned, and these managerial strategies directly transferred to large Cold War projects such as inter-continental ballistic missiles (or ICBM) and nuclear submarines (Hewlett and Duncan, 1974; Hughes, 1998; Johnson, 2002). What is more interesting for us is the theorization of these practices in the 1950s. Indeed, researchers at the RAND Corporation like A. Alchian and R. Kessel (1954), K. Arrow (1955), R.R. Nelson (1959, 1961) or C. Hitch and R. McKean (1960) wrote vanguard papers on the management of highly innovative projects (called “exploratory development” by K. Arrow). The insights from these works are probably best summarized in Klein and Meckling’s 1958 landmark paper contrasting “Mr Optimizing” (standard PM) and “Mr Sceptic” approaches to project management. This paper demonstrated the superiority (in situations of radical innovation) of an approach by the project manager to try different solutions and to make a deliberate effort to keep his program flexible in the early stages of development so that he can take advantage of what he has learned. […] In order to maintain flexibility he commits resources to development only by stages, reviewing the state of his knowledge at each stage prior to commitments. (Klein & Meckling, 1958, 35; see also Brady et al., 2012)

Unfortunately this line of inquiry was not to have a rich posterity in the academic literature (Nelson, 1961). To the best of our knowledge, the last article dealing with this question (before the new millennium) was Abernathy and Rosenbloom’s Management Science paper of 1969 on “Parallel strategies in development projects”. Third epoch. The date of 1969 is emblematic since it corresponds both to the creation of the Project Management Institute and Armstrong’s landing on the Sea of Tranquility on 20 July.2 And, actually, the standardization of PM practices from the “optimizing” perspective was well in progress. It started in the early 1960s when the US Department of Defense and NASA published a PERT/Cost Guide that became a de facto standard in the PM community. This story has been told elsewhere (Johnson, 2000; Lenfle and Loch, 2010, 2017; Davies et  al., 2018) and is now well known, including the original misunderstanding on the supposed

188  Handbook on innovation and project management

efficiency of programme evaluation review technique (PERT) in the Polaris case (Sapolsky, 1972; Engwall, 2012). What is important for us is that the practices of the Second World War and the 1950s completely disappeared in the process. Project management became dominated by a rational and instrumental view of a project as the convergence towards a clearly defined goal. Mr Sceptic faded away and with him the notions of parallel strategy, rapid experimentation and emerging goals through learning.3 Fourth epoch. Then came the early 2000s and the rediscovery of the question of the management of very innovative projects. Whereas Shenhar and Dvir demonstrated the fallacy of the “one size fits all” approach, and Brady and Davies (2004) proposed the notion of “vanguard exploratory projects”, C. Loch and his colleagues developed a theory of project management under unforeseeable uncertainties (or unknown unknowns). What is interesting here is that they demonstrated the relevance of parallel (selectionist) or trial and error (iterate and learn) strategies to deal with unknown unknowns without any references to Cold War practices and theories4 (Pich et al., 2002; Loch et al., 2006; Sommer et al, 2009; Loch and Sommer, 2019). Following this line of inquiry, Lenfle (in particular 2008, 2014, 2016) examined exploratory projects5 in depth by characterizing their nature and proposing management principles (see the next section). He also built a bridge between the contemporary work of C. Loch and the work and cases of the Second World War and the Cold War (see Lenfle and Loch, 2010, 2017). Finally, these contributions led to the development of research on the management of exploratory projects with different lenses (see Lenfle et al., 2019, introduction to the Project Management Journal special issue on exploratory projects). The management of exploratory projects now constitutes a significant research stream at the crossroad of project and innovation management. As we’ve seen, its emergence follows, in a way, the process described in Davies et al. (2018): first a close connection, then complete separation and, finally, rediscovery and strengthening of the management of these exploratory projects (EPs). In the next section, we will summarize the main contributions of the field before turning to a research agenda in the final section. Since we have been part of this research stream, this chapter constitutes an opportunity to reflect upon this research trajectory.

THE MANAGEMENT OF EXPLORATORY PROJECTS: WHAT DO WE KNOW? Current research on exploratory projects has yielded several important results on their defining features and their management. Indeed in 15 years, the field has moved “from strangeness to theory” (Lenfle et al., 2019). We summarize the results in the following. Definition Several complementary definitions exist of exploratory projects (EPs). In fact, two definitions emerged independently at the beginning of the 2000s. C. Loch and colleagues (Pich et al., 2002; Sommer and Loch, 2004; Loch et al., 2006) explore the limitations of risk management methods for projects confronted with complexity and unforeseeable uncertainties, demonstrating the need for new management techniques. Quite at the same time, Brady and Davies (2004) define vanguard exploratory projects as first-of-a-kind projects that “explore strategic

Exploratory projects 

189

Table 9.1  Exploratory and exploitative projects Exploratory projects

Exploitative projects

Emerging and strategically ambiguous projects

Result of a clearly defined strategic decision process

Proactive process

The “client” is identified, needs are known

Difficulties defining the results ex-ante

Requirements are available

Exploration of new knowledge

Knowledge exists (mostly incremental innovation)

Hidden urgency and multiple timescales

Deadline is defined at the beginning

opportunities to move into new technology or market bases or to adapt to a changing market environment”, paving the way for future “exploitation” projects. Building on these first contributions, Lenfle (2008) proposed a definition of an EP as a “project for which neither the goals nor the means to reach them can be clearly defined at the outset”. More precisely he proposed five criteria to distinguish exploratory projects from exploitative projects, which were the main focus of the literature since Clark and Fujimoto’s landmark contributions on new product development projects6 (see Table 9.1). They underline the fundamental uncertainty of projects which, fundamentally, are “experimental learning processes” (Loch et  al., 2006). Therefore the founding principles of the rational approach (clear specifications and deadlines in particular) vanish and one needs to invent an alternative model of project management since the rational approach is insufficient (or even makes no sense) here. Instead, as formulated by Dugan and Gabriel (2013) based on their experience at DARPA, project managers here “are focused on managing constant flux—building, replanning, changing track, and moving talent in and out as needs shift”.7 The question then becomes how to manage these fluxes.

EXPLORATORY, BREAKTHROUGH, DISRUPTIVE, CREATIVE PROJECTS … WHAT ARE WE TALKING ABOUT? One important question is the positioning of exploratory projects compared to existing typologies of innovation and/or projects (e.g. Abernathy and Clark, 1985; Wheelwright and Clark, 1992; Christensen, 1997; Danneels, 2002; Obstfeld, 2012). Whereas these former typologies focus on the origins of innovation (e.g. technology/market competencies in Abernathy and Clark and Danneels; level of product/process change in Wheelwright and Clark; disruptive/sustaining innovation in Christensen; elements of recognizability/action repetitiveness in Obstfeld), our definition of exploratory projects emphasizes the impact of unknown unknowns, whatever they come from, on project management. Therefore the exploratory projects (1) exclude regular/incremental innovations (what Danneels refers to as pure exploitation) and (2) are compatible with different sources of uncertainties. For example, breakthrough projects in Wheelwright and Clark or Christensen’s disruptive innovation are exploratory in nature. We thank Andrew Davies for pushing us to clarify this point.

190  Handbook on innovation and project management

Managerial Principles The described work demonstrates that firms are confronted with a new type of project that requires a new kind of project management. The new model was summarized by Lenfle (2008) around five overarching (or meta-) principles that synthesize research on the question. These principles have evolved with research on the question. Since they have been presented elsewhere (in particular Lenfle 2008 and 2016), we summarize and reflect upon them next. P1: Differentiated managerial processes. Exploratory projects are confronted with the classic difficulties of innovation in large organizations. If they are evaluated through standard financial criteria, they will probably be killed before they start (e.g. Christensen et al., 2008). Furthermore if, once approved, they are managed with the standard stage-gate approach, there is a high probability that they will fail due to “project inflexibility”8 (Sehti and Iqbal, 2008). Thus the need arises to set up specific managerial processes for exploratory projects to evaluate and oversee them. Here the literature on exploratory projects joins research on ambidexterity in organizations, for example through skunkworks (Tushman and O’Reilly, 1996; Raisch et al., 2009; Zimerman et al., 2018) P2: The central role of experimentation. One of the central questions concerns the fundamental mechanisms of agency in exploratory projects. Indeed, given their distinctive features, in particular, the unknown unknowns, the fundamentals of standard project management vanish; goals are unclear, tasks largely unknown, knowledge is lacking, deadlines shift, etc. The cases and the literature on innovation show that EPs are probe-and-learn processes (Lynn et al., 1996). Therefore they progress through experimentation (Thomke, 2003) even if this can become quite complex when confronted with unknown unknowns (Gillier and Lenfle, 2019). The question is thus to manage this experimentation process. Here the contributions of C. Loch and colleagues are fundamental. They provide a framework to choose between different approaches, namely “iterate and learn” and “selectionism”9 (or a combination of both). Since this work is well known we will not present it here (see Loch and Sommer, 2019, for a recent overview and Chapter 10 in this volume). P3: Concurrent exploration of technology and “market”. One important point is that exploratory projects are projects; they have goals and deadlines (even fuzzy ones at the outset). As one of our interviewees explains, “we are not exploring for the sake of exploring. We try to do something that works” (in Lenfle, 2016). So exploratory projects are not research projects; they do the groundwork for other, more “development-oriented” follow-up projects. Therefore they have to explore simultaneously the technical and market dimensions of the innovation, what Gastaldi and Midler (2005) called concurrent exploration and Dugan and Gabriel (2013, following Stokes, 1997) called “use-inspired basic research”. The goal is to avoid the symmetrical traps of useless technology or inaccessible needs. P4: A project that leads to products, concepts and knowledge. The fourth principle tackles one of the difficulties raised by exploratory projects: the lack of clearly defined deliverables that constitute one of the fundamentals of standard project management. What happens when this premise disappears, when there is no obvious “result”, such as a product? Our argument here is that an EP does not necessarily lead to physical objects. Its goal is to map an “unfamiliar landscape” (McGrath, 2001) to build new competencies and explore original concepts through prototyping and experimentation. It is, as said before, doing the groundwork for future projects. Therefore reflecting on the innovation journey during its unfolding is fundamental, and projects should be evaluated from the “products” they deliver, which could be prototypes

Exploratory projects 

191

(see Jouini and Midler, 2020), as well as the knowledge, concepts, patents, competencies, etc., that they create (Iansiti and Clark, 1994; Elmquist and Le Masson, 2009; Keil et al., 2009; Lenfle, 2016). P5: Constant reformulation of goals. The last challenge identified in the literature follows from the previous point. The fifth principle tackles one of the major managerial challenges raised by EPs: the lack of “clear goals”.10 Indeed the existence of a contract book specifying the requirements to be fulfilled constitutes the foundation of standard PM processes. Because exploratory projects are “experimental learning processes”, it is important to develop managerial methods that will help the team to manage this learning process and assess the “progress” of the project. Reflection in action (Schön, 1983) is fundamental because the goals, and the means to reach them, will be defined (and probably modified) during the project. In particular, the challenge is to manage the expansive nature of these kinds of projects (Hatchuel, 2002; Lenfle, 2012; Gillier et al., 2014). No doubt this constitutes a major question for future research. These principles should be understood as overarching principles. They help to clarify the foundations of a management system for exploratory projects. But they do not settle the debate. They provide a framework to assess the relevance of different types of organization or management tools, proposed to manage exploratory projects. Recent Advances Indeed, research on exploratory projects is evolving. A recent special issue of the Project Management Journal that we coordinated with Christophe Midler and Markus Hällgren emphasizes several points that will be developed further in the next section. A. The distinction between exploration and exploitation is probably a bit too simple. This idea is already present in Loch et al. (2006). Indeed their framework suggests that some parts of the project can follow, for example, selectionism, while others are managed according to standard practices. Tillement et al. (2019 and Chapter 6 in this volume) go one step further by demonstrating that a single project can have elements of exploration and exploitation and that this may evolve during the project. They thus propose to distinguish between deliberate and emergent exploration. B. The analysis of uncertainty constitutes another interesting avenue. In their 2008 paper, Loch et al. propose a framework to diagnose unforeseeable uncertainty within a project. More recently, Gomes et  al. (2019) developed a multilevel approach that distinguishes four sources (ecosystem/network, organization, portfolio and project) and three levels (primitive, structural and elementary) of uncertainty. This, they argue, can help managers to avoid the trap of uncertainty blindness, a very promising concept, which occurs “when managers are not able to either define which uncertainties were mitigated (and the contributions to the firm) or why they should invest in reducing the additional ones” (2019, 566) and surely leads to project failure (see also Ramasesh and Browning, 2014). C. The governance of EPs emerges as a central question. Indeed, the fourth and fifth principles question the very foundation of project supervision. As we will develop in the next section, the entire project supervision toolbox (be it portfolio or stage-gate processes) is based on the premise that projects have clear goals and deliverables. What happens when projects are hard to understand because goals are complex and fuzzy, deliverables

192  Handbook on innovation and project management

are hard to define and deadlines are floating (Lenfle, 2016; Loch et al., 2017; Loch and Sommer, Chapter 10 in this volume)? Furthermore, how can we identify exploration and exploitation projects within portfolio management processes? How do we manage the transition from exploration to exploration? We know that there is frequently a valley of death (Midler, 2019) between exploration and development. How can we overcome it? From this perspective, the work of Kock and Gemünden (2019 and Chapter 11 in this volume) demonstrates the need to take into account intertemporal linkages in portfolio management. Indeed, as they argue, EPs create options that have to be developed through lineages of projects. In the same vein, Midler et al. (2019) propose the concept of ambidextrous programme management, i.e. a programme that combines exploration and exploitation projects to explore a new innovation field (autonomous mobility in their case). D. Finally, until now, exploratory projects have mainly been studied in isolation. Yet, as pointed out by Engwall (2003), projects are not islands. They unfold within a context. This is all the more true for EPs that have to manage their relations not only with their parent company (Burgelman, 1983) but also with their frequently as-yet-undefined ecosystem. Here, research on exploratory projects meets the expanding research on the role of ecosystems (Adner, 2012; Jacobides et al., 2018). Indeed one of the challenges of EPs is that they are confronted with emerging ecosystems. How they can manage (or at least influence) ecosystem creation and/or evolution thus constitutes an important question (Ben Mahmoud-Jouini and Duboc, 2017; Koch-Ørvad et al., 2019).

THE ROAD AHEAD: DEEPENING THE CASES, BROADENING THE SCOPE, STRENGTHENING THE THEORY This brief overview of the state of the art of management of exploratory projects helps to identify the questions/problems that lie before us and the promising research avenues. From our previous analysis, we can identify four areas for future work on exploratory projects. First, we need more cases. The empirical base of the research on exploratory projects is still limited and more cases are needed to understand their inner functioning, how coordination occurs when actors are confronted with unforeseeable uncertainties and novel problems (Lenfle and Soderlund, 2019), the problems they meet, the strategies they use during the experimentation process, the role of project leaders, etc. Research strategies here can be diverse: • • • •

Collaborative research with firms can allow researchers to dig deep into the processes of EPs through single or multiple case studies (Lenfle, 2016; Tillement et  al., 2019; Vasconcelos Gomes et al., 2019). The difficulty of accessing the field, due to the frequent secrecy of EPs, can also lead researchers to explore history. As we have seen, looking back at history leads to the excavation of the lost roots of project management (Lenfle and Loch, 2010, 2017). We can also hope that, with time, more quantitative approaches will develop (Koch et al., 2019) to complement case studies and provide comparisons between different projects, firms or sectors. Finally, there might be additional opportunities to create mathematical models of key decisions in exploratory projects, which include unforeseeable uncertainties as well as

Exploratory projects 

193

interest misalignments across multiple stakeholders. For example, Sommer and Loch (2009) showed that bonuses are not effective motivation mechanisms in exploratory projects (because bonuses assume that management knows what “success” looks like), as opposed to process rewards or upward rewards.11 An additional opportunity lies in the fact that some literature exists that deals with or can be useful to exploratory projects without using this concept, preferring more classical terms such as “radical innovation projects”. This work is of course relevant to our research and should be integrated into the corpus (e.g. Laamez and van Knippenberg, 2014 on the functioning of teams in pursuit of radical innovation; or Kelley et al., 2011 on the direct manager’s role). The richness of qualitative research is already visible in a recent paper by Wied et al. (2020) who, by relying on interviews of managers of EPs, identify a repertoire of 11 approaches12 used to increase the resilience of projects confronted with uncertainties. There is no doubt that this line of investigation should be continued. The second area of research concerns the management tools and methods adapted to these projects. This is an already fruitful area, particularly with the work of C. Loch and colleagues. We know that experimentation is the engine of exploratory projects and how to choose between “iterate and learn” and “selectionism” according to the project’s level of complexity and unknown unknowns. However, a lot remains to be done on the management tools that will help to make sense of this experimentation at the team level. Research is promising but quite fragmented in this dimension. Real option thinking (Kester, 1984; Schwartz and Trigeorgis, 2004) and its application through discovery-driven planning (McGrath and McMillan, 2009) is a dominant approach, but its application to exploratory projects remains to be studied. Moreover, we still miss real examples of its functioning in situations of radical innovations.13 In a stimulating paper, Gillier et al. (2014) demonstrate the limitations of value analysis for innovative projects given their “expansive nature”, i.e. when more goals, problems and solutions are discovered during the project (Lenfle, 2016). They thus propose new tools, based on advances in concept-knowledge design theory, to design new tools to manage innovative projects (Midler et al., 2012; Lenfle, 2012; Hooge and Stasia, 2016; Hooge, 2020; Hooge and Lenfle, Chapter 17 in this volume). Here again, research in collaboration with organizations is needed. The third research area relates to the governance of these projects. As pointed out by Loch and Sommer (2019), the lack of clearly defined goals in EPs runs counter to the logic of most control processes in organizations. Indeed, as they explain: It is at the very heart of management principles of accountability and control to have defined deliverables. Once you give up on an activity’s defined deliverables, you give up on this activity being manageable. […] [Therefore] allowing for not having clearly specified goals creates deep tension with the very definition of a project, and its associated accountability for, and (even imperfect) control of, a deliverable. This tension engenders significant resistance from practicing managers, who are assigned to provide project supervision – they simply cannot live with a complete (or so felt) abdication of control. This is important because it represents a barrier to the success of exploratory projects not from management methods, but from organizational oversight. (Loch & Sommer, 2019, 524)

The problem is all the more complex in that exploratory projects are often difficult to understand in their (novel or complex) details because of their very nature, thus rendering

194  Handbook on innovation and project management

supervision excessively difficult (Loch et al., 2017). The governance of exploratory projects should constitute a central research area. Here two different but complementary questions should be distinguished. The first relates to the definition of adequate management processes for exploratory projects. Indeed, it is clear that EPs face the challenge of uncertain content (be it technical, market, legal, etc., possibly also raising complexity challenges) that raises the question of managing their legitimacy in the organization, thus the importance of political processes.14 In this perspective, as discussed in Lenfle (2016) and Loch and Sommer (2019), the bootlegging strategy (Schön, 1963; Westrum, 1999) based on “organizational ingenuity” (KannanNarasimhan, 2014) is risky because it is fragile. There is a high risk that someone discovers the true nature of the project and kills it. However, it is clear, at least since Burgelman’s ICV work (Burgelman, 1983, 2003), that such projects have to be protected. They “have to be fought for by their originators. [And] hiding their effort until they could show positive results clearly had survival value for product champions” (Burgelman, 1983, 233). Indeed, they need time to build their legitimacy in the organization (Dougherty, 1994). How to build such sheltered places remains an important question, and the link with the literature on ambidexterity is obvious here. Should the organization design a separate process, such as IBM Emerging Business Opportunities (Tushman et al., 2009), set up skunkworks (Rich and Janos, 1994) or favour contextual ambidexterity (Gibson and Birkinshaw, 2004)? The question needs further research but it is now clear that the management of exploratory projects, as is common in innovation (Van de Ven, 1986), combines a double process of project content exploration and political legitimacy building. The second question relates to the management of the portfolio of projects. This classical dimension of project management has been, until now, insufficiently studied (for example, Lenfle and Loch remain mainly at the project level). However, Koch and Gemunden (2019) and Midler et al. (2019) demonstrate the fundamental role of portfolio management to articulate the firm’s exploration strategy through projects, manage their temporal linkages through lineages of projects and orchestrate the transition from exploration to exploitation. In this line of research the concept of ambidextrous programme management, proposed by Midler et al. (2019), i.e. a programme “that simultaneously coordinates both exploratory and implementation projects” in order to explore a new field (in their case autonomous mobility at Renault) seems very promising. Here again, it would be interesting to study the criteria used to manage a portfolio or programme of exploratory projects, the unfolding of the decision process and, of course, its impact on project “success” or “failure”.15 Last, but not least, we believe that the emergence of exploratory projects raises fundamental theoretical questions on the very nature of projects. Indeed, EPs are questioning the fundamental hypothesis of the standard model, namely that a project has a clearly defined goal. The problem is that the standard model is entirely structured around this hypothesis. Once you have a clearly defined goal, it is possible to define a deadline, break down the project into tasks, evaluate the costs, identify the risks, etc. So giving up on the idea that projects have defined goals leads to the collapse of the standard model and its instrumentation. What are the theoretical consequences of this situation? Indeed, removing the prerequisite that projects have “clear goals” leads to the questioning of the theoretical background of project management. Here again, the dialogue between project and innovation management could be fruitful since innovation is frequently described as a chaotic process (Van de Ven et al., 1999). For example, Dunne and Dougherty (2016) and Dougherty (2016) describe innovators’ reasoning

Exploratory projects 

195

as an abductive process that consists of gradually building/testing/refining hypotheses through and during projects. This pragmatic perspective16 may help us to theoretically strengthen our approach to a project as a probe and learn process (Lynn et al., 1996; Loch et al., 2006). No doubt more work is needed to build these new theoretical foundations of exploratory project management. In particular, we think that this could also lead us to intensify the connection with two other fields: • •

Research on sensemaking (Weick, 2001; Weick and Suttcliff, 2007) that, in our view, has an obvious link with the management of complex and uncertain projects (Loch et al., 2006; Ivory et al., 2006). Design theory, in particular the concept-knowledge design theory (Hatchuel and Weil, 2009), which could provide a theoretical framework precisely to make sense of the project’s trajectory during its unfolding (see earlier).

CONCLUSION As we have seen, exploratory projects offer a fruitful research field that, over the last 15 years, has yielded important results. EPs are now well identified, the need to develop specific processes is clear since the standard ones have been demonstrated to kill them, meta-principles exist for this research and avenues for future research have been identified. However, we are still only at the beginning of the process. One of the main challenges lies, in our view, in the possibility for researchers to access the field and collect relevant data. Indeed, if our experience demonstrates that organizations are eager to adapt their processes, working with researchers is unfortunately not always possible given the secrecy of these questions.

NOTES 1. When we refer to the standard model we have in mind the “rational school” exemplified by the Project Management Institute. 2. An analysis of the Apollo case would be very interesting since, as in Polaris, this is the management system implemented in 1964 by Sam Phillips, quite late in the project, that has been retained (Johnson, 2001; Seamans, 2005). Here again the goal was to regain control of the project in order to bring it back on track in terms of delay. Innovation was not the question. Innovation takes places before this, during the early stage of the project (see for example Hansen, 1995). 3. One important question that we decided to leave aside in this chapter is the discussion of the so-called agile methods and their relevance for exploration (a question frequently raised by practitioners at our conferences). Let’s just say that (1) agile approaches have their roots in software engineering at the end of the 1980s (see Boehm, 1988). Therefore their transferability of the realm of products remains questionable (Remondeau & Lenfle, 2022). (2) Agile methods do not necessarily lead to innovation. One can easily conceive designing a me-too product through agile. They generally suppose the existence of a customer and a product vision. This does not correspond to a situation of exploration. For a discussion see Remondeau et al. (2021). 4. Their oldest reference is Abernathy and Rosenbloom (1968) (a previous version of the 1969 Management Science paper). 5. Or exploration project; the two terms are interchangeable. 6. Clark and Fujimoto focus on the performance of NPD in terms of cost, quality, delay and product integrity. They are not studying innovative projects and uncertainty is very limited in this context.

196  Handbook on innovation and project management

7.

8. 9. 10.

11. 12. 13. 14.

15. 16.

Note that this idea of managing flux is also present in the description of the Manhattan Project’s Los Alamos laboratory during the war by Thorpe and Shapin (2000). They describe a lab being “in a continual state of flux and turbulence” due to the unknown unknowns confronting the project (see also Lenfle, 2011). It’s interesting to note that Dungan and Gabriel forcefully explain that in EPs “insisting that a team steadily hit milestones established in initial plans can cause it to adhere to a path that – based on something the team has learned – no longer makes sense”. I.e. the inability to learn and adapt the project goals during its unfolding. Try different solutions one after the other, or in parallel. It could be useful here to distinguish between goal and requirements. We think that there is always some kind of goal to start something. But it can be very broad, fuzzy, questionable, controversial, etc. (“go to Mars”, “build an electric mobility solution”). This leaves quite open how the goal evolves during the project and potentially leads to somewhere different than expected. At the opposite end, complete requirements written in a project’s contract book are the basis of the standard model. This approach is related to work in Economics and Entrepreneurial Finance (e.g. Maskin and Tirole, 1999; Levin, 2003). We are grateful to C. Loch for this suggestion. Modifiability, redundancy, sequentialism, reversibility, etc. The most complete example, the BioBarrier project in McGrath and McMillan (2009), really deals with incremental innovation and limited uncertainty. It is almost suitable for traditional risk management. The fact that exploratory projects raise technical and organizational problems is a recurring problem. It was already present in historical projects like Manhattan, Sage, Atlas/Titan and Polaris. For example, as explained by Sapolsky (2003), “as a new technology, ballistic missiles did not fit easily into the existing weapons acquisition structures”. Thus the need to create new organizations (the Special Projects Office for Polaris, the Western Development Division of the USAF for Atlas/ Titan, MITRE for SAGE, etc.). See Hughes (1998). We use quotation marks to underline the complex nature of the notion of success and failure in the case of exploratory projects. They rely on American pragmatism, in particular the work of C.S. Peirce.

REFERENCES Abernathy, W. and Clark, K. (1985). Innovation: Mapping the winds of creative destruction. Research Policy, 14(1), 3–22. Abernathy, W. and Rosenbloom, R. (1969). Parallel strategies in development projects. Management Science, 15(10), B486–B505. Adner, R. (2012). The wide lens. A new strategy for innovation. New York: Portfolio/Penguin. Alchian, A. and Kessel, R. (1954). A proper role of system analysis. D-2057. RAND Corporation. Arrow, K. (1955). Economic aspects of military research and development. D-3142. RAND Corporation. Ben Mahmoud-Jouini, S. and Charue-Duboc, F. (2017). Experimentations in emerging innovation ecosystems: Specificities and roles. The case of the hydrogen energy fuel cell. International Journal of Technology Management, 75(1–4), 28–54. Ben Mahmoud-Jouini, S. and Midler, C. (2020). Unpacking the notion of prototype archetypes in the early phase of an innovation process. Creativity and Innovation Management, 29, 49–71. Boehm, B. (1988). A spiral model of software development and enhancement. Computer, 21(5), 61–72. Brady, T. and Davies, A. (2004). Building project capabilities: From exploratory to exploitative learning. Organization Studies, 25(9), 1601–1621. Brady, T., Davies, A., and Nightingale, P. (2012). Dealing with complexity in complex projects: Revisiting Klein & Meckling. International Journal of Managing Projects in Business, 5(4), 718–736. Buderi, R. (1996). The invention that changed the world. How a small group of radar pioneers won the Second World War and launched a technical revolution. Sloan Technology Series. New York: Touchstone. Burgelman, R. (1983). A process model of internal corporate venturing in the diversified major firm. Administrative Science Quarterly, 28(2), 223–244.

Exploratory projects 

197

Burgelman, R. (2003). Strategy is destiny. How strategy making shapes a company’s future. New York: The Free Press. Christensen, C. (1997). The innovator’s dilemma. Boston, MA: Harvard Business School Press.. Christensen, C., Kaufman, S., and Shih, W. (2008). Innovation killers. How financial tools destroy your capacity to do new things. Harvard Business Review, January, 98–105. Clark, K. and Fujimoto, T. (1991). Product development performance. Strategy, organization and management in the world auto industry. Boston, MA: Harvard Business School Press. Danneels, E. (2002). The dynamics of product innovation and firm competences. Strategic Management Journal, 23(12), 1095–1121. Davies, A., Manning, S., and Soderlünd, J. (2018). When neighboring disciplines fail to learn from each other: The case of innovation and project management research. Research Policy, 47(5), 956–979. De Meyer, A., Loch, C., and Pich, M. (2002). Managing project uncertainty: From variation to Chaos. Sloan Management Review, 43(2), 60–67. Dougherty, D. (1994). The illegitimacy of product innovation in established firms. Organization Science, 5(2), 200–218. Dougherty, D. (2016). Taking advantage of emergence. Productively innovating in complex innovation systems. Oxford: Oxford University Press. Dugan, R. and Gabriel, K. (2013). “Special Forces” Innovation: How DARPA attacks problems. Harvard Business Review, October, 74–84. Dunne, D. and Dougherty, D. (2016). Abductive reasoning: How innovators navigate in the Labyrinth of complex product innovation. Organization Studies, 37(2), 131–159. Elmquist, M. and LeMasson, P. (2009). The value of “failed” R&D project: An emerging evaluation framework for building innovative capabilities. R&D Management, 39(2), 136–152. Engwall, M. (2003). No project is an Island: Linking projects to history and context. Research Policy, 32(5), 789–808. Engwall, M. (2012). PERT, Polaris and the realities of project execution. International Journal of Managing Projects in Business, 5(4), 595–616. Gastaldi, L. and Midler C. (2005). Exploration concourante et pilotage de la recherche. Une entreprise de spécialités chimiques. Revue Française de Gestion, 31(155), 173–189. Gibson, C. and Birkinshaw, J. (2004). The antecedents, consequences and mediating role of organizational ambidexterity. Academy of Management Journal, 47(2), 209–226. Gillier, T., Hooge, S., and Piat, G. (2014). Framing value management for creative projects: An expansive perspective. International Journal of Project Management, 33(4), 947–960. Gillier, T. and Lenfle, S. (2019). Experimenting in the unknown: Lessons from the Manhattan project. European Management Review, 16(2), 449–469. Groves, L. (1962). Now it can be told. The story of the Manhattan Project. New York: Da Capo Press. Hansen, J.R. (1995). Enchanted Rendezvous: J.C. Houbolt and the genesis of the lunar orbit Rendezvous concept. Monographs in Aerospace History Series #4. Washington, DC: NASA. Hatchuel, A. (2002). Toward design theory and expandable rationality: The unfinished program of Herbert Simon. Journal of Management and Governance, 5(3–4), 260–273. Hatchuel, A. and Weil, B. (2009). C-K design theory: An advanced formulation. Research in Engineering Design, 19(4), 181–192. Hewlett, R. and Duncan, F. (1974). Nuclear Navy, 1946–1962. Chicago: University of Chicago Press. Hitch, C. and McKean, R. (1960). The economics of defense in the nuclear age. Cambridge, MA: Harvard University Press. Hooge, S. (2020). La valeur de l’inconnu en entreprise. Modélisation des stratégies, outils et dynamiques collectives de la performance de l’innovation intensive. Mémoire pour l’habilitation à diriger des recherches, January 24. Hooge, S. and Stasia, R. (2016). Performance de la R&D et de l’innovation. Du contrôle de gestion à la gestion contrôlée. Paris: Presses des Mines. Hughes, T. (1998). Rescuing prometheus. New York: Vintage Books. Iansiti M. and Clark, K. (1994). Integration and dynamic capabilities: evidence from product development in automobiles and mainframe computers. Industrial and Corporate Change, 3(3), 507–605.

198  Handbook on innovation and project management

Ivory, C., Alderman, N., McLoughlin, I., and Vaughan, R. (2006). Sense-making as a process within complex projects. In D. Hodgson and S. Cicmil (Eds.), Making project criticals (pp. 316–334). New York: Palgrave. Jacobides, M., Cennama, C., and Gawer, A. (2018). Toward a theory of ecosystems. Strategic Management Journal, 39(8), 2255–2276. Johnson, S. (2000). From concurrency to phased planning: An episode in the history of systems management. In A. Hughes and T. Hughes (Eds.), Systems, experts and computers. The systems approach to management and engineering, World War II and after (pp. 93–112). Cambridge, MA: The MIT Press. Johnson, S. (2001). Samuel Phillips and the taming of Apollo. Technology and Culture, 42(4), 685–709. Johnson, S. (2002). The secret of Apollo. Systems management in American and European space programs. New Series in Nasa History. Baltimore: The John Hopkins University Press. Kannan-Narasimhan, R. (2014). Organizational ingenuity in Nascent innovations: Gaining resources and legitimacy through unconventional actions. Organization Studies, 35(4), 483–509. Keil, T., McGrath, R., and Tukiainen, T. (2009). Gems from the ashes: Capability creation and transformation in internal corporate venturing. Organization Science, 20(3), 601–620. Kelley, D., O’Connor, G., Neck, H., and Peters, L. (2011). Building an organizational capability for radical innovation: The direct managerial role. Journal of Engineering and Technology Management, 28, 249–267. Kester, C. (1984). Today’s options for tomorrow’s growth. Harvard Business Review, March-April, 153–160. Klein, B. and Meckling, W. (1958). Application of operations research to development decisions. Operations Research, 6(3), 352–363. Kock, A. and Gemünden, H. (2019). Project lineage management and project portfolio success. Project Management Journal, 50(5), 587–601. Koch-Ørvad, N., Thuesen, C., Koch, C., and Berker, T. (2019). Transforming ecosystems: Facilitating sustainable innovations through the lineage of exploratory projects. Project Management Journal, 50(5), 602–616. Laamez, A. and van Knippenberg, D. (2014). Teams in pursuit of radical innovation: A goal orientation perspective. Academy of Management Review, 39(4), 423–438. Lenfle, S. (2008). Exploration and project management. International Journal of Project Management, 26(5), 469–478. Lenfle, S. (2011). The strategy of parallel approaches in projects with unforeseeable uncertainty: The Manhattan case in retrospect. International Journal of Project Management, 29(4), 359–373. Lenfle, S. (2012). Exploration, project evaluation and design theory: A rereading of the Manhattan case. International Journal of Managing Projects in Business, 5(3), 486–507. Lenfle, S. (2014). Toward a genealogy of project management: Sidewinder and the management of exploratory projects. International Journal of Project Management, 32(6), 921–931. Lenfle, S. (2016). Floating in space ? On the strangeness of exploratory projects. Project Management Journal, 47(2), 47–61. Lenfle, S., LeMasson, P., and Weil, B. (2016). When project management meets design theory: Revisiting the Manhattan and Polaris projects to characterize “radical innovation” and its managerial implications. Creativity and Innovation Management, 25(3), 378–395. Lenfle, S. and Loch, C. (2010). Lost roots: How project management came to emphasize control over flexibility and novelty. California Management Review, 53(1), 32–55. Lenfle, S. and Loch, C. (2017). Has megaproject management lost its way ? Lessons from history. In B. Flyvbjerg (Ed.), Oxford handbook of megaproject management (pp. 21–38). Oxford: Oxford University Press Lenfle, S., Midler, C., and Hällgren, M. (2019). Exploratory projects: From strangeness to theory. Project Management Journal, 50(5), 519–523. Lenfle, S. and Soderlünd, J. (2019). Large-Scale Innovative Projects as Temporary Trading Zones: Toward an Interlanguage Theory. Organization Studies, 40(11), 1713–1739. Levin, J. (2003). Relational incentive contracts. American Economic Review, 93(3), 835–857. Loch, C. and Sommer, S. (2019). The Tension Between Flexible Goals and Managerial Control in Exploratory Projects. Project Management Journal, 50(5), 524–537.

Exploratory projects 

199

Loch, C., Mähring, M., and Sommer, S. (2017). Supervising projects you don’t (fully) understand: Lessons for effective project governance by steering committees. California Management Review, 59(2), 45–67. Lynn, L.S., Morone, J.G., and Paulson, A.S. (1996). Marketing and discontinuous innovation: The probe and learn process. California Management Review, 38(3), 8–37. Maskin, E. and Tirole, J. (1999). Unforeseen contingencies and incomplete contracts. Review of Economic Studies, 66(1), 83–114. McGrath, R. (2001). Exploratory Learning, innovative capacity and managerial oversight. Academy of Management Journal, 44(1), 118–131. Midler, C. (1996). L’auto qui n’existait pas (2nd ed.). Paris: Dunod. Midler, C. (2019). Crossing the valley of death: Managing the when, what, and how of innovative development projects. Project Management Journal, 50(4), 447–459. Midler, C., Maniak, R., and Beaume, R. (2012). Réenchanter l’industrie par l’innovation ; Stratégie et management de l’innovation dans les entreprises automobiles. (Re-enchant industry through innovation strategy and innovation management in automotive firms). Paris: Dunod. Midler, C., Maniak, R., and de Campigneulles, T. (2019). Ambidextrous program management: The Case of autonomous mobility. Project Management Journal, 50(5), 571–586. Nelson, R.R. (1959). The economics of parallel R and D efforts: A sequential-decision analysis. Rand Corporation Working Papers (RM-2482). Nelson, R. (1961). Uncertainty, learning, and the economics of parallel research and development efforts. The Review of Economics and Statistics, 43(4), 351–364. Obstfeld, D. (2012). Creative projects: A less routine approach toward getting new things done. Organization Science, 23(6), 1571–1592. Pich, M., Loch, C., and DeMeyer, A. (2002). On uncertainty, ambiguity and complexity in project management. Management Science, 48(8), 1008–1023. Raisch, S., Birkinshaw, J., Probst, G., and Tushman, M. (2009). Organizational ambidexterity: Balancing exploitation and exploration for sustained performance. Organization Science, 20(4), 685–695. Ramasesh, R. and Browning, T. (2014). A conceptual framework for tackling knowable unknown unknowns in project management. Journal of Operations Management, 32, 190–204. Remondeau, E. and Lenfle, S. (2022). How to guide the adaptation of agile approaches according to the project context, within a company, which designs complex systems? A typology of specific agile adaptation modes, R&D Management Conference, Trento, Italy, June 9–13. Best Ph.D Paper Award. Rhodes, R. (1986). The Making of the Atomic Bomb. New-York: Simon & Schuster. Rich, B. and Janos, L. (1994). Skunk works. A personal memoir of my years at lockheed. Boston: Little, Brown and Company. Sapolsky, H. (1972). The polaris system development. Cambridge, MA: Harvard University Press. Sapolsky, H. (2003). Inventing systems integration. In A. Prencipe, A. Davies, and M. Hobday (Eds.), The business of systems integration (pp. 15–34). Oxford: Oxford University Press. Schön, D. (1963). Champions for radical innovation. Harvard Business Review, March–April, 77–86. Schön, D. (1983). The reflective practitioner. How professionals think in action. New York: Basic Books. Schwartz, E. and Trigeorgis, L. (2004). Real options and investment under uncertainty. Classical readings and recent contributions. Cambridge, MA: The MIT Press. Seamans, R. (2005). Project Apollo. The though decisions. Monographs in Aerospace History – Number 37. Washington, DC: NASA History Division. Sehti, R. and Iqbal, Z. (2008). Stage-gate controls, learning failure, and adverse effects on novel new products. Journal of Marketing, 72(1), 118–134. Shenhar, A. and Dvir, D. (2007). Reinventing project management. Boston, MA: Harvard Business School Press. Söderlund, J. (2004). Building theories of project management: Past research, questions for the future. International Journal of Project Management, 22(3), 183–191. Soderlünd, J. (2011). Theoretical foundations of project management: Suggestions for a pluralistic understanding. In P. Morris, J. Soderlünd, and J. Pinto (Eds.), Oxford handbook of project management (pp. 37–64). Oxford: Oxford University Press.

200  Handbook on innovation and project management

Söderlund, J. (2011). Pluralism in project management: Navigating the crossroads of specialization and fragmentation. International Journal of Management Reviews, 13(2), 153–176. Sommer, S. and Loch, C. (2004). Selectionism and learning in projects with complexity and unforeseeable uncertainty. Management Science, 50(10), 1334–1347. Sommer, S. and Loch, C. (2009). Incomplete incentive contracts under ambiguity and complexity. Production and Operation Management, 18(2), 185–196. Sommer, S., Loch, C. and Dong, J. (2009). Managing complexity and unforseeables uncertainty in startup companies: An empirical study. Organization Science, 20(1), 118–133. Thomke, S. (2003). Experimentation matters. Boston, MA: Harvard Business School Press. Thorpe, C. and Shapin, S. (2000). Who Was J. Robert Oppenheimer? Charisma and Complex Organization. Social Studies of Science 30(4), 545–590. Tillement, S., Garcias, F., Minguet, G., and Charue-Duboc, F. (2019). Disentangling exploitation and exploration in hybrid projects: The case of a new nuclear reactor development. Project Management Journal, 50(5), 538–553. Tushman, M. and O’Reilly III, C. (1996). Ambidextrous Organizations: Managing Evolutionary and Revolutionary Change. California Management Review, 38(4), 8–30. Van de Ven, A., Polley, D., Garud, R., and Venkataraman, S. (1999). The innovation journey. New York: Oxford University Press. Vasconcelos Gomes, L.A., et  al. (2019). Proposing a multilevel approach for the management of uncertainties in exploratory projects. Project Management Journal, 50(5), 554–570. Weick, K. (2001). Making sense of the organization. Malden, MA: Blackwell. Weick, K. and Sutcliffe, K. (2007). Managing the unexpected. Resilient performance in an age of uncertainty (2nd ed.). San Francisco: Jossey-Bass. Westrum, R. (1999). Sidewinder. Creative missile development at China Lake. Annapolis, MD: Naval Institute Press. Wheelwright, S. and Clark, K. (1992). Revolutionizing product development. Quantum leaps in speed, efficiency and quality. New York: The Free Press. Wheelwright, S. and Clark, K. (1992). Creating project plan to focus product development. Harvard Business Review, March–April, 70–82. Wied, M., Koch-Ørvad, N., Welo, T., and Oehmen, J. (n.d.). Managing exploratory projects: A repertoire of approaches and their shared underpinnings. International Journal of Project Management, 38(2020), 75–84. Zimmerman, A., Raisch, S., and Cardinal, L. (2018). Managing persistent tensions on the frontline: A configurational perspective on ambidexterity. Journal of Management Studies, 55(5), 739–769.

10. Managing unforeseeable uncertainty through learning Christoph H. Loch, Svenja C. Sommer and Mengtong Jiang

INTRODUCTION It has long been known that novel projects pose the challenge of unknown unknowns or events and influences that cannot be anticipated. In “projects” drawn up around major technological innovations, unknown unknowns are rampant, stemming from the combination of developing a set of new and evolving technologies and applying them to new uses and markets (Pich et al., 2002; Loch et al., 2008). For such projects, firms (should) have a long-term vision, but it is impossible to define clear operational goals or even to determine the best action plan that could move the company forward towards the vision. As an example, consider the rapid manufacturing project initiated by a European car manufacturer at the turn of the millennium. In the summer of 2001, the car company European Motors initiated the “rapid manufacturing project”, an analysis of the emerging topic of rapid prototyping and rapid tooling. At that time, rapid manufacturing technologies generated a lot of enthusiasm in the industry, as they promised a solution to the long-time dream of offering customers competitively priced products in small series or even customized cars. The new technologies promised attractive speed and cost advantages both for tooling in small-volume production and for the production of unique parts, but they still had severe limitations in quality, cost and speed for larger volumes. In 2001, none of the existing technologies was even remotely close to meeting the automotive industry’s requirements. Nevertheless, a number of grassroots-driven small initiatives had emerged across the company to evaluate these technologies (Figure 10.1) and some of them had nothing to do with car manufacturing; the most exotic of them (not included in Figure 10.1) was a project to produce models of skulls from MRI data to help surgeons carry out brain operations. The Manufacturing Planning Department decided to start a more structured initiative to evaluate whether a unified “rapid manufacturing project” would have significant value for the company. However, it quickly found that planning and evaluating this project was very difficult, if not impossible. At this stage, the medium- to long-term performance of the various available technologies remained highly uncertain, and at the same time, new technologies and materials were under development. Even if performance measures were available for some of the technologies, the performance of these technologies was still rapidly evolving. Therefore, it was not clear which technologies would be relevant for which applications, or even which applications would be the most promising or the most exciting ones to pursue. It became quickly clear that the “rapid manufacturing project” could not be managed like prior product innovation projects. It was a “large vision”, which was only vaguely defined and for which no one knew how to get there. These are conditions that should (and do) frighten project managers because they are tied in with the extreme risk of failure, both for the project and for the careers of the people involved. 201

202  Handbook on innovation and project management

Vintage cars Technology Set 1

Spare parts

Individualized accessories Technology Set 2

Mass manufacturing

Processcentered approach

Vision: Apply rapid tooling to mainstream manufacturing

Niche cars

Concept car

Figure 10.1  Possible range of applications of “rapid manufacturing” technologies envisioned in 2001 This chapter will link the management of uncertainty to learning in projects and showcase how European Motors managed the unforeseeable uncertainty using a learning perspective. It will then argue for using a project learning process for novel projects, similar to the existing risk management process for risky projects. We will conclude with a second example of another highly uncertain project that was a technological success but can be considered an overall failure because (among other things) it did not follow some of these critical steps.

LEARNING IN PROJECTS Learning is key in any project. In fact, the project itself can be seen as a learning process using knowledge-based and intangible resources (Whitehill, 1997; Nonaka et al., 2000; Jugdev and Mathur, 2012). Learning in projects is a process of repeatedly building knowledge sets, such as “what do we already know”, “what might we know that we do not know right now” and “what do we need to know in the future” (Loch et al., 2006, 120). However, learning in projects is not easy: projects are by definition unique undertakings and constitute a non-permanent organization, with most teams being dissolved at the end of a project. Most often, learning will not happen naturally. “Learning schemes” should be “instituted over the long term and their continuity and development ensured” (Boudès et al., 1998, 65). The question is how to do so. Clearly, the type of learning is not the same across all projects. Ahern et al. (2014) distinguish the “emergent learning” about unforeseeable uncertainty, or ill-understood problems,

Managing unforeseeable uncertainty through learning  203

from the “planned” learning that is “programmed” up front in the stage-gate process (PMI, 2017), suggesting a similar contingency perspective for learning in projects as for project management overall. Routine Projects For routine projects, Nevison (1994) differentiates “learning from the past” (project planning), “learning from actions” taken in the project (project monitoring and progress measurement) and “learning in action” (corrective actions), and argues that “successful project managers have been, and remain, strongly committed to the idea of continuous learning” (Nevison, 1994, 6). The work breakdown structure and activity planning both build on knowledge from previous projects. But this knowledge must be explicitly adjusted for the unique aspects of the project at hand (for example, a different location of execution, a new feature or a new design). The adjustments introduce risks into the project because they may not go as planned; this requires risk management and learning (at least in the sense of continuous improvement). Existing organizational routines and solidified knowledge enable learning in such projects but also hinder project learning. Zollo and Winter (2002) considered that the dynamic capabilities of the organization arise to some extent from the accumulation of routines but also from knowledge articulation and codification. This happens in knowledge evolution through testing cycles (Zollo and Winter, 2002). Such well-codified testing cycles support continuous learning and are similar to continuous improvement initiatives in processes. These testing cycles can take place within projects, but the parallel can also be drawn at the level of the overall project. Kotnour (1999) shows the equivalence between the PDCA cycle of continuous improvement in processes and traditional steps of project management and hence routine projects overall: planning, doing = executing, checking = project control and finally acting = “the use of the lessons learned on the next project during the planning phases” (Kotnour, 1999, 33). Like in the PDCA cycle, detailed planning and clear hypothesis (outcome expectations) are seen as necessary for this continuous learning to take place, while the lessons learned ensure the learning is made explicit and subsequently disseminated across the organization (Kotnour, 1999). Similar to learning within existing processes, the testing and the associated learning in routine projects must overcome the resistance of the prevailing knowledge, such as pre-determined working procedures or experiential rules, and individual biased selection – “We already know how to do it, why are you rocking the boat?” (Ordanini et al., 2010; Ivory and Vaughan, 2008). Risky/Uncertain Projects As a project becomes less routine and more novel, the deviations from solutions used in the past grow, that is, the changes become less “obvious” (e.g. a new feature is no longer a straightforward change in the graphical user interface) and require additional substantial problem solving and creativity. In this case, testing cycles become more involved and turn into experimentation. A testing cycle consists of generative variation (diverse idea creation), internal selection of insights (choosing the most promising of hopefully many ideas for trials), replication (knowledge transfer) and retention (enactment and routinization) (Thomke, 2003). The shift from routine projects is gradual and may be subtle and hard to see at first glance. But it is embodied by a shift in managerial emphasis from a faithful replication of the past to

204  Handbook on innovation and project management

something new, from efficiency to effectiveness (and creativity) of a novel solution and from delivery of a planned solution to the possibly modified solution that requires changes in the plan (Thomke, 2020). Similarly, risk management shifts from the spirit of avoiding problems to spotting opportunities (Chapman and Ward, 2003). Learning becomes less continuous and less programmed and instead more emergent, still guided by an overall goal, but driven by the (possibly unexpected) experimentation cycles (Lindkvist and Söderlund, 2002). Novel and Exploratory Projects While traditional risk management is the “art and science” of wrestling with “known unknowns” (Wideman, 1992), it has long been known that novel projects pose the challenge of unknown unknowns or events and influences that cannot be anticipated. Unlike risk, which can be predicted, measured and tested for, unforeseeable uncertainty without a known “state space” or probabilities requires “the creation of novelty and (radically) new knowledge” (Peschl and Fundneider, 2017, 86; Gillier and Lenfle, 2019). Something hidden beyond the existing horizon leads to “the inability to recognize and articulate variables and their functional relationships” (Schrader et al., 1993, 73). Especially in the initial stage of such a project, multiple factors cannot be fully anticipated (in spite of the “homework” that one has, of course, to perform to become prepared; see Ramasesh and Browning, 2014), including unanticipated stakeholders, unexpected customer reactions (or even unexpected customers) and unforeseen technological problems or side effects. This creates major hurdles for testing, since “the problems to solve, the alternatives to test, and the evaluation criteria are unknown at the outset” and no prior theories exist to formulate clear hypotheses (Gillier and Lenfle, 2019, 450). Many have argued that learning is in fact more important in novel projects. The core intention of such a project should not only be the traditional efficiency-oriented achievement of a predetermined goal but also the innovation-oriented learning and exploration in its own right (Frederiksen and Davies, 2008). Thus, intermediate outcomes should include both the delivery of pivot products and the creation of intangible knowledge (Maniak and Midler, 2014). Iterations to pivot outcomes and iterations to learn are supportive of and complementary to each other, the former offering a basis for value creation and the latter providing the dynamic ability to respond quickly to urgent problems. In some cases, a project may not achieve its original goals, but it may still create important concepts, knowledge or capabilities for future projects (Loch et al., 2006; Keil et al., 2009; Maniak and Midler, 2014). Therefore, for novel projects, facing high unforeseeable uncertainty (Feduzi and Runde, 2014; Dattée et al., 2018; Loch et al., 2006), neither objectives and goals nor actions and means can be clearly defined at the outset. If the project lacks a clear goal for work structure decomposition, then the implementation method cannot be fixed either. Therefore, knowledge accumulation, a shifting vision and more flexible execution methods are essential to successfully deal with unforeseeable uncertainty (Lenfle, 2014, 2016; Loch and Sommer, 2019). Many scholars have proposed that the dual flexibility of goals and means can be achieved through two management approaches and their combination (Leonard-Barton, 1995; Pich et al., 2002), both of which represent forms of learning. The first approach is an iterative learning and adjusting process that focuses on repeated problem-solving cycles throughout the project, also referred to as trial-and-error learning or “probe and learn”. This approach has been applied in technology transfer, discontinuous innovation and new ventures (Van de Ven

Managing unforeseeable uncertainty through learning  205

et al., 1999; Lynn, et al., 1996), which are environments that “push the envelope” rather than implementing known techniques, and where the path to success and even the final outcome could not have been foreseen at the outset. It is important to emphasize that problem-solving cycles are not the same as experimentation cycles in risky projects. The latter test known hypotheses, resolving known risks and narrowing down the choice among known alternatives. In contrast, consecutive problem-solving cycles of exploratory projects cannot be defined at the outset, do not have plannable hypotheses and not all possible outcomes are known upfront. In extreme cases, even the evaluation tools and criteria might not be known (Gillier and Lenfle, 2019) and may have to be discovered over time. Thus, in novel projects, experimentation and testing are at least initially more of an exploratory nature; rather than running experiments to test hypotheses, the focus in novel projects might first need to develop the hypotheses themselves and to expand the search space rather than on narrowing it down and quickly converging on the best solution approach available. As new information becomes available, learning requires the flexibility of adjusting the project’s course and possibly even its goals (Loch and Sommer, 2019). Thus the goals cannot be narrow and specific at the outset. However, even emergent learning is not totally blind. When solutions finally do emerge through trial and error, firms need a vision specific enough to rule out directions that are not compatible with it (Loch et al., 2006, 103). Thus, the discovery process is not completely random; it is not like biological evolution, where changes are random and direction arises from selection only, but more like cultural evolution, in the sense that it is at least partially directed, here by the overarching vision (see Richerson et al., 2006). Consistent with this view, Lindkvist (2008) observed that project-based adaptation in organizations is based on goal-oriented but open-ended processes. The second approach is parallel trials (also referred to as “selectionism”, as the best of the trials is at some point selected, like in evolution). The approach is suitable if multiple alternatives exist and can be pursued simultaneously as part of the project (Abernathy and Rosenbloom, 1969; Lenfle, 2011). The premise of this approach is that no one can predict the best technology or the best application at the outset, and hence this choice is postponed until enough information is available (Pich et al., 2002; Lenfle, 2011). The parallel approach not only broadens the possibilities for learning, but also avoids the possibility of outright failure, reduces the need for pre-guessing and saves time. In the development of the atomic bomb, Los Alamos scientists pursued two solutions in parallel, and what they initially considered the backup solution led to success (Gillier and Lenfle, 2019). However, pursuing multiple solutions is very expensive, especially if the unforeseen uncertainty resolves only slowly, which deters many managers from making this choice (Wheelwright and Clark, 1992; Loch and Sommer, 2019).1 We summarize the differences between learning in novel projects and more traditional projects in Table 10.1.

THE “RAPID MANUFACTURING PROJECT” AT EUROPEAN MOTORS Our introductory example clearly falls into the category of an exploratory project. European Motors had a vision: a factory using rapid manufacturing technologies to build cars. But it had neither a concrete goal nor an idea of how to progress towards this vision. In fact, it faced

206  Handbook on innovation and project management

Table 10.1  Focus of learning across types of activity in projects Activity type

Focus of learning

Example

Routine project

Both outcomes and activities are known and planned upfront and fairly repetitive from one project to another. Learning focuses on learning from the past and on continuous improvements via systematic experiments.

Continuous improvement by changing activities for better speed or quality or lower cost. E.g. use of technologies to automate or otherwise improve activities.

Risky/uncertain project

Outcomes and activities are known and planned but might need substantial changes. Learning focuses on contingencies of the one-time execution, i.e. on possibly needed modifications to achieve the outcome. Experimentation cycles are an important institutional element of project activities to test hypotheses, with systematic idea generation, selection, replication and retention.

Post-mortems develop lessons of what went wrong, so the next time, the project team has a “better contingency list” and a more accurate contingency size.

Novel and exploratory projects

Outcomes and activities are only partially known, i.e. it is not known precisely what goal is achievable and what needs to be done to achieve it. Learning focuses on (a) what precisely can be achieved (within a broad vision) and (b) what needs to be done and how. Iteration and learning need to not only test hypotheses but establish targets and fundamental approaches in the first place.

A new technology is developed or implemented, and it is learned what it can achieve and whether, and in which form, it can be incorporated into the project. It is learned what stakeholder requirements really are only when they are confronted with the real (new) outcome for the first time, something that no one (including the stakeholders themselves) could foresee.

unforeseen uncertainty both on the market and on the technology side. Multiple technologies were still under development, and could, in principle, be applied to a number of different markets or user applications. Figure 10.1 (in the introduction) shows a simple overview created at the outset of the project. It shows possible applications in a qualitative way, not forcing “business case numbers”, because those were simply not available. The key realization of the preliminary discussions represented in Figure 10.1 was that an overarching vision was needed to guide decision-making and to integrate a stream of new information that would become available in a piecemeal fashion over the next years. The preliminary analysis also attempted to determine the market potential and the requirements of different user applications identified in Figure 10.1 (see Table 10.2). Comparing the requirements to the performance of the rapid prototyping technologies, it became quickly clear that a “business case” might be possible only for some niche applications, but not for the many technologies that were too early stage to do any reliable testing, and certainly not at all for the large opportunity on the horizon of “rapid manufacturing in batches of one”.

207

Requirements

Potential

Business

Possible to consider in vision, detailed planning not possible

~150 pieces per year

Low cost: < 2× series

Full quality and same material as in series

Same as vintage cars

Vintage cars Spare parts

Business case possible

Market test: 50 pieces; x000 if successful

Market test: 50 pieces for < $10K If success: cost like series

Full quality

Accessories

Low volumes

Low cost compared to today’s

High surface finishing; product lifetime can be lower

Concept car

Low volumes

Quality level dependent on application; lower than series

Speed

Prototyping

Table 10.2  Potential market opportunities as perceived in 2001

x0 to x000 pieces (?)

Low cost: < 2× series (?)

Full quality

Niche cars

Mass production

Volume influences level of postponement

Low cost; saving in tooling changes

No planning possible

Full quality; lifetime ? of tool can be possibly lower

Speed

Mfg. Ramp-up

208  Handbook on innovation and project management

In spite of this uncertainty, a project was put in place in order to drive this opportunity forward. A project manager was appointed with a small team. The team started to execute smaller intermediate projects with clearly defined, interim outcomes. Rapid prototyping had already been used in car development projects for ten years and soon became a standard part of testing in engineering. Next, parts were produced for concept cars at exhibitions – these parts had to look right but did not have to have the full functionality, durability or load-carrying capacity. In 2014, some worker-individualized ergonomic manufacturing tools were produced to reduce fatigue and injuries for manufacturing workers. The same year, water pump wheels were produced via additive manufacturing for “small series”, in particular for racing cars. Also, some parts were produced for the new all-electric models. In 2018, a service was offered to end customers of one model line to “print” parts that individualized elements of the passenger compartment. Finally, the company decided to take a large step forward, announcing a €15m investment in a dedicated Additive Manufacturing Centre with 80 employees. The Additive Manufacturing Centre opened in 2020, and the services of this centre are commercially used in multiple departments throughout the company. In summary, over 19 years, the company continually invested and “inched forward” toward a “large vision”, which was only vaguely defined at the outset and which no one knew how to attain. Looking at the “large vision”, the risk of failure was extreme, but failure did not happen here, at least not on a large scale. (Some of the intermediate projects did not work out, but they were not seen as failures but as sources of learning.) By structuring the overall project as a series of intermediate projects, progress happened in smaller steps, most of them producing some visible outcome and value. All the steps in the end complemented one another to enable the company to adopt a bundled approach to additive manufacturing in the new centre. The “dangerous sting” was taken out of this unforeseen project (along with the risk to the careers of employees involved in the project) by breaking the long journey into pieces and using the pieces to learn. The unforeseeable project was turned into a learning process, where learning about an unknown new strategic technology and its applications occurred. In the process of learning from the projects, the overall vision evolved and was modified and sharpened. It is important to note that this progress was not linear, not a simple narrowing down of risky technology choices to the one that best fits a set of pre-defined requirements. In fact, at the outset, the firm could neither specify the requirements for the long-term vision nor determine the complete choice set in terms of the finally available technologies or in terms of the possible applications. Therefore, these small projects did not always result in the narrowing down of choices; rather, some of them triggered the exploration of new opportunities (like the workerindividualized ergonomic manufacturing tools). This was possible because the company was willing to not set a tight schedule for achieving the vision – schedules were set for some of the intermediate projects, but reaching the vision emerged “when it did”; even the investment in the new facility had not been planned beforehand, but was undertaken when the technologies were ready and profitable applications could be envisioned. The uncertainty was overcome by articulating intermediate steps that were (a) reachable and achievable without excessive unknowns and (b) opportunity-driven, providing some value to the company in the form of some new application or service. At the same time, some of these services (such as the worker-individualized ergonomic manufacturing tools) had been completely unforeseen at the outset and emerged as the growing project team explored new opportunities. The third characteristic was that these projects (c) were not viewed or managed in isolation; rather, they were treated as a sequence of steps towards the (however vague) vision

Managing unforeseeable uncertainty through learning  209

of “large-scale rapid manufacturing”. The third characteristic is key because these intermediate projects were not only chosen to deliver a direct value – in fact, in many cases, the business case (ROI) would not even have resulted in the selection of these projects. Instead, they were chosen because they delivered progress (if they worked) and at least insights (even when they failed) that allowed the firm to learn and refine the vision. It was essential that the overall project did not have a fixed schedule or budget, but was open-ended. In fact, only the immediate next set of projects was to some extent planned, leaving the decision about any follow-up projects open and allowing for the discovery of new opportunities in the learning process. At the same time, the projects “accumulated” a sufficient stock of knowledge that finally allowed the company to announce the decision in 2018 (after 17 years) to invest in the “additive manufacturing” factory. Note that observing such long-time horizons in the development of radically new technologies is not new – it has been long known that such technologies can take more than a decade to reach commercial success (see, for example, Lynn et al., 1996). Thus, the two critical features are the pursuit of loweruncertainty intermediate projects to accumulate knowledge and explore opportunities at a lower risk for the firm and the flexibility to allow the “vision achievement” to be open-ended. We can summarize our observations from this example in Figure 10.2: firms can tackle a vague initial vision, which is itself unplannable, by using a staged series of learning projects. The use of such iterative cycles is a natural element of the management of unforeseeable uncertainty – a well-managed novel project that poses unforeseeable uncertainty offers an opportunity to accumulate emergent knowledge. Each learning project should, therefore, have two results: (a) a defined intermediate outcome that ideally creates an economic benefit in its own right (albeit possibly at a level below those required for stand-alone projects), and (b) an explicit learning goal that enables the Choose small set of learning projects

Initial Vision

Identify Major Hurdles and areas of knowledge gaps on the path towards Vision

– Stop/go decision – Redefinition of vision and general approach

Learning Project Learning Project Learning Project

Intermediate Project Outcomes – Collective evaluation – Track exogenous technological evolution

– Each project has -- a defined (intermediate) outcome -- ideally an economic value in itself -- contributes a defined competence to learning toward the vision -- is evaluated collectively vs the vision (rather than based solely on its own expected ROI)

Figure 10.2  A staged sequence of “learning projects”

Flexible Vision – Opportunity driven ITERATION: start a new set of learning projects

– Qualitative – Robust – Large – Evolving

210  Handbook on innovation and project management

firm to accumulate knowledge and dynamic capabilities in order to progress toward the (possibly modified) vision. Note that the intermediate outcomes in (novel) learning projects do not necessarily represent “progress” towards the overall vision (which may change anyway as new knowledge emerges), but include explicit learning objectives that allow the firm to explore what is now known that was not known before. Based on this learning, the vision will and is even expected to change and evolve. Each learning project has thus the explicit goal to produce two types of learning: learning towards the nature of the vision and learning towards how the vision can be attained. For this learning to be effective, it has to be carefully managed. After each wave of subprojects, the intermediate project outcomes have to be evaluated and the vision needs to be adapted to incorporate the learning. Since the learning is (at least in the initial rounds) of exploratory nature, this learning potentially includes learning about new opportunities and new alternatives. It is, therefore, only at this evaluation stage that the next wave of subprojects should be chosen, and the intermediate outcome and learning goals for the next wave of subprojects should be defined. The idea of managing a sequence (or overlapping portfolio) of projects and learning across them is not new. Midler (2013) coined the term “project lineage management” for a sequence of projects that build on each other. Such sequencing of projects allows for the development of several product generations that exploit options created via a first exploratory project (see also Maniak and Midler, 2014). Kock and Gemünden (2019) provide empirical evidence that managing the learning across lineage projects both in a forward-looking way in the sense of project roadmaps and in a backward-looking way by learning from past projects improves the overall success of a firm’s project portfolio. While the concepts and lessons in project lineage management are closely related to the learning projects described in our case example, there is a fundamental difference: the learning projects we describe are all part of the original exploratory project; they are all mere stepping stones to define (and then move towards) an emergent and changing overall project vision. These learning projects typically cannot be exploited directly in subsequent product generation but rather provide lessons that help clarify the project goal and how to progress towards it. Thus, what we describe is not a sequence of projects itself but a way to move a specific exploratory project forward, by cutting it down into smaller, lower-risk steps, which are more acceptable in an organization with budgetary and career concerns.

THE NEED FOR KNOWLEDGE GOVERNANCE IN NOVEL PROJECTS Let us summarize two important elements from the European Motors example that enable accumulated learning in exploratory projects: •

An “ambidextrous” approach to budget and schedules: the intermediate learning projects can be approached with some budget and schedule discipline (with flexibility and buffers due to the uncertainty that these projects also contain). However, the final vision is an unplanned “outcome” rather than a planned event at a planned point in time. The initial vision may be judged to be achieved at an emergent point in time, but it may also have an emergent form, with features that were not anticipated at the outset at all. For example, no one would have been able to describe at European Motors in 2001 what an additive manufacturing facility might look like.

Managing unforeseeable uncertainty through learning  211

•

The intermediate projects are managed as a mutually complementary group rather than as standalone projects. This will allow both for the investment into less profitable learning projects and for efficient learning to take place across projects. Indeed, even the failure of one project may create useful learning that makes several of the other projects more effective. Therefore, an important aspect of knowledge creation is the transfer of knowledge across the projects (see also Sydow et al., 2004; Söderlund, 2008), so that some projects may be changed, constrained or boosted by what happened in other projects. For intermediate projects to be managed as a mutually complementary group, it is necessary to put in place a shared overarching responsibility and accountability. In the European Motors example, this was embodied by a business manager responsible for the overall vision to whom the project managers of the individual projects reported.

In order for the staged sequence of learning projects to lead (or meander) to a successful final vision, it is essential that learning does not happen only at the level of the projects, but that this learning happens across the different learning projects at the organizational level. Prencipe and Tell (2001) acknowledge the importance of cross-project learning to develop new organizational capabilities and observe that firms emphasize different cross-project learning processes (people-embedded experience accumulation, knowledge articulation and knowledge codification) to varying degrees. Cross-project learning, however, requires the synchronization of many separate project activities in order to enable knowledge exchange. For learning to result in the transfer of insights across projects, the “clock speed” of learning insights must be coordinated across various parts of projects because otherwise insights cannot be absorbed (Söderlund, 2008, 2010 calls this “knowledge entrainment”). However, the learning process at multiple levels of projects increases the complexity of requirements for project management, especially the need to closely link knowledge activities at different levels (Grant, 1996; Hedlund, 1994). At the individual level, it requires knowledge transfer and integration across multiple fields, and at the project level, it poses a dilemma between control and autonomy in the learning process (Lindkvist et al., 1998). Additionally, there are inherent contradictions between cross-project learning (which consumes resources in the short run while offering the unpredictable possibility of future benefits) and overall efficiency at the organizational level (Sydow et al., 2004; Whitley, 2006). Since cross-project learning and learning at an organizational level is essential for novel projects to succeed, it is necessary to invest in proactive activities and a governance structure that allows for knowledge accumulation and knowledge integration to take place – not only at a project but at an overall organizational level (Pemsel et al., 2016). Söderlund (2008) recognizes the important role of top management in creating structures that allow for knowledge transfer and learning across projects and for knowledge integration at the firm level to build new capabilities. Similarly, Maniak and Midler (2014) acknowledge the need for top management to create linkages between the project and the overall organization and for it to decide which capabilities or new routines should be integrated into the overall organization. Pemsel et al. (2016) explicitly call for a knowledge governance strategy to shape organizational knowledge processes. They identify different knowledge governance strategies that differ among other things in the attitude of top and middle management towards (1) knowledge (considered a valuable resource or not), (2) knowledge control (via performance control, i.e. degree of knowledge codification, or socialization control, i.e. mentoring, training, etc.) and (3) humans (resilience and faith in others’ ability to learn). They recognize that these attitudes affect whether firms are able to engage in novel and exploratory projects and whether they are willing to allow for unstructured learning, which is essential for such projects.

212  Handbook on innovation and project management

A SKETCH OF A PROJECT LEARNING PROCESS Open-ended but vision-oriented problem-solving and learning across (parts of) projects is not an established project management method in most firms. In fact, anecdotal observations suggest that learning across projects is in most organizations not well managed. We, therefore, suggest that a project learning process should be established as an explicit set of activities in novel, exploratory projects, just like the risk management process was established explicitly for risky projects in the 1980s and 1990s (Wideman, 1992). Wideman (1992, II-3) defined project risk management as “the art and science of identifying and responding to project risk throughout the life of a project and in the best interests of its objectives”. This inspired us to propose the following definition for a project learning process: Proposition for a definition: a project learning process comprises institutionalized systematic steps of identifying, targeting and, if possible, codifying knowledge outcomes of project activities, which serve the evolution and development of a project vision and its pursuit as it evolves.

A project learning process should have institutionalized steps that can be incorporated into the management of novel projects. In other words, once learning from projects is institutionalized in such a process, it can contribute to the wider “dynamic capabilities of the organization” (Davies and Brady, 2016; Brady and Davies, 2004). In analogy, risk management has four steps: risk identification, risk prioritization, risk management (response) and documentation and learning (Wideman, 1992). More recently, a wider view of risk management has tried to also embrace elements of the management of uncertainty, including the management of unknown unknowns (Chapman and Ward, 2003). Chapman and Ward (2003) stress the importance of seeing risk management not only as the management of downside risks but also as the creation of opportunities, and they point out the value of integrating such uncertainty management into project management at an earlier stage, thereby possibly influencing even the objectives of a project. However, this still reflects risky (versus novel) projects, where outcomes are identifiable and plannable at an early stage (albeit with contingencies). The project learning process should therefore go one step further. It is not only about creating opportunities for the current project; rather, it is about the creation of novel knowledge that will allow the morphing and evolution of an overall project vision that is implemented via a portfolio of intermediate learning projects or activities. Analogous to the steps in a project risk management process, we suggest the steps shown in Figure 10.3 as a first sketch of a project learning process. The first step in this high-level process is the identification of learning domains. In which domains do you lack fundamental knowledge? What knowledge is missing or questionable to be able to define concrete goals and plan activities linked to the overall vision? What makes the project “novel”? Learning can occur in the domain of new technologies that the company needs to master, about the emerging needs of customer groups who cannot yet articulate their needs for new-to-the-world products or services, or with respect to regulatory regimes that evolve and are being put into place at the same time as the innovation project takes shape. In our example, the firm faced major gaps in knowledge about the performance potential of the different technology choices, of which many were still under development at research institutions at the outset, and about the market potential and even possible domains of application within the overall long-term vision of rapid manufacturing.

Managing unforeseeable uncertainty through learning  213

• Establish an overarching responsibility for the novel project overall to allow for knowledge integration at an organizational level • Establish responsibilities and decision right for managing each learning cycle, for documentation and sharing the results, for adjusting activities to emerging results • Recognize knowledge as the most valuable outcome and be willing to trust in the team’s learning abilities to allow for less structured and codified knowledge to be created.

Knowledge Governance System and Strategy Supportive of Novel Projects Identify Learning Domains • In which domain do you lack fundamental knowledge ?

• For example: market knowledge (customers, regulations), knowledge about the technology, or about design types • This identification helps to focus the learning activities

Prioritize Learning Domains

Establish Learning Activities

Evaluation and Sharing of Learning

• Evaluate outcomes of • Which knowledge gaps • Identify intermediate learning activities and are the most critical to learning projects that document / share be able to move will create knowledge knowledge obtained towards the vision? within the chosen learning domain, but if • Integrate knowledge / • In which domains is it possible creates capabilities at currently possible to economic value by itself organizational level. learn / create knowledge? • Only one wave of • Re-evaluate and adjust learning activities overall project vision should be planned; later based on knowledge waves will be planned acquired when results of the previous wave are available

Figure 10.3  A first sketch of a project learning process for novel projects Identifying learning domains assumes that the domains of “knowledge gaps” can be identified beforehand, as opposed to the unknown unknowns themselves (which have by their nature to remain unspecified until they emerge). Note that learning management thus means that learning is not generic; an organization cannot learn “any” unstructured knowledge explicitly. While individuals may learn things tacitly, this is not open to formal management and control. Specifying the important learning domains focuses the learning efforts, preventing them from becoming too diffuse and therefore unproductive. Similar to risk management, the second step in this process is the prioritization of the learning domains. It enables an effective design of the next learning cycle in step 3. The prioritization should take into account two factors: (1) what the most critical knowledge gap is that prevents the firm from moving towards the vision; and (2) which domain it is currently possible to learn/ create knowledge about. In our example, learning about the technologies was clearly more critical than identifying the most promising applications – also because identifying promising applications is intricately linked to the achievable performance of the chosen technology, and hence promising applications cannot be identified in isolation of technological learning. The decision about the learning domain allows a third step for the design of the next learning cycle or set of learning activities. This set of intermediate learning projects should produce

214  Handbook on innovation and project management

outcomes that enable the evolution of the vision – either progressing towards it (if it turns out to conform to assumptions) or adapting it (if it turns out that assumptions are not fulfilled or can be surpassed). Note that the actual knowledge acquired might not be anticipated. Especially in the first waves of learning projects, you might not be able to predict what you will learn. This still does not mean that learning is generic; it is still within a specific learning domain. However, what you learn might be only discovered in the learning project, including possibly the identification of previously unanticipated knowledge gaps (see Gillier and Lenfle, 2019 for such an example). Given the uncertainty about the knowledge acquisition itself, these learning activities might be asked to also create (if possible) an economic value in the traditional sense of a project outcome, thereby limiting financial risks and risks for the careers of the people involved. The fourth step is the evaluation and sharing of knowledge acquired across the set of learning projects in step 3. This relates to Söderlund’s (2010) knowledge entrainment (clock speed coordination). It is at this point that the knowledge needs to be integrated at the organizational level. The overall project vision should then be re-evaluated and possibly adjusted or morphed into a new project vision, which then serves as input into the next cycle through those four steps. Some of the knowledge gaps might have been closed by the previous set of learning activities, others might have just been narrowed down (but not fully removed), or the evaluation of the learning outcomes might even show that new, previously unanticipated knowledge gaps emerged in the last wave of learning projects. Therefore, the firm should re-evaluate the learning domains before choosing which knowledge domain(s) to prioritize for the next wave of learning projects. Last but not least, the intermediate projects and learning cycles have to be chosen and managed as a group rather than as individual projects, in order to enable effective knowledge transfer across the different learning projects and different learning cycles. This requires the establishment of a knowledge governance structure supportive of organizational knowledge creation and integration processes (Pemsel et al., 2016). These learning cycles need managers who (a) recognize that knowledge is a valuable outcome in its own right in exploratory projects and who are hence willing to launch learning projects that might not meet the cut-off criteria as standalone projects, and who (b) are willing to replace outcome-oriented performance measures by qualitative demonstrations of learning taking place. This requires a larger amount of delegation and trust in a team’s ability to learn in order to enable creativity and flexibility toward unanticipated outcomes (Sting et al., 2021). Equally important, it requires that clear decision rights and responsibilities are formally assigned, not only at the level of the intermediary learning projects but more importantly as a shared overarching responsibility for the novel project overall. This responsibility needs to include that the created knowledge is shared in a timely manner with the right parties, and hence it requires top management involvement (Maniak and Midler, 2014). In the European Motors example, this was the responsibility of the business manager, but it could be the role of a separate project coordinator, analogous to a risk manager.

CONCLUSION As we have started with an example, we will conclude also with an example. The opening example of European Motors consists of a long-term vision with multiple intermediate projects. The closing example is a novel project of a “flying car” (Loch and Sommer, 2005).

Managing unforeseeable uncertainty through learning  215

An external inventor brought the idea and drawings of a flying car to the technology scouting manager of the automotive company Lemond Automobiles. The idea of the flying car has fascinated car users for a century, so the manager explored the idea with the help of enthusiastic colleagues and suppliers who saw an opportunity in collaborating with Lemond Automobiles. The decision was taken to develop a proof of concept of a flying vehicle (with wider lessons). But since this idea was so far outside any beaten track, it was unpredictable which technological approach might be suitable, or which concept might have any chance of getting market traction. Therefore, three concepts were developed in parallel (Figure 10.4, from left to right): a “flying scooter” based on a scooter with a wing assembly that would fly at slow speeds; a “flybike” based on a heavy motorcycle that would keep its propeller and wing assembly at the nearest airport and fly like a small propeller plane; and the three-wheel “Duosport” that would be a sports vehicle on the road and also fly like a small plane. The flying scooter and flybike were built as mock-ups but were abandoned when it became clear that the Duosport was the most appealing concept. The Duosport was developed into a functional prototype that won flight approval from the air traffic authority and successfully flew with a pilot. Technically, the project was a success, producing a functional concept in less than three years for a total budget (for all three mock-ups and the flying prototype) of €2 million. The Duosport was admired by the people who were allowed to see it. It also offered learning benefits with respect to its new steering interface (which worked for driving on the road and in the air), the testing of new lightweight materials, as well as testing market reactions to an alternative concept. However, no overarching project learning architecture was in place. The project was run as an informal “submarine” (indeed, some of the budget was bootlegged from leftovers in other projects), the company did not buy into the experiment and the learnings were rejected. The project was cancelled, and the prototype was not even used as an attractive PR story to showcase the innovativeness of the company. This example demonstrates that technical learning within one project alone accomplishes nothing if the overarching vision (of alternative uses) is not identified, agreed to and authorized to be explored by top management. This project fulfilled the requirements of a learning project: clear learning goals were identified at the outset (learn about new steering interface, new light-weight materials, etc.), and the project had an identified economic value of the concept development itself (PR value). But neither the learnings nor the economic value was realized, since it was not embedded in a larger vision and no knowledge governance structure was

Figure 10.4  Three parallel mock-ups/ prototypes for a flying car

216  Handbook on innovation and project management

in place. The Duosport example shows that if an overarching learning process is not in place, learning simply will not be disseminated and get accepted. Novel project learning rarely happens if it has not been identified at the outset as an important activity with valuable results in its own right. Only when activities are defined can organizations reliably execute them (Nelson and Winter, 1982), and the same holds true for learning activities. With a project learning process, learning management can be integrated into project activities in a similar way as how risk management was integrated into project management 30 years ago. While the project example in this section shows the importance of a project learning process at the firm level, we did not demonstrate how to implement such a learning process. The process proposed here is merely a conjecture based on our observations of two case studies (the rapid manufacturing project and the flying vehicle project), which needs to be further tested, modified and developed in empirical work.

NOTE 1.

The two approaches of iteration and parallel trials often occur together and can often not be neatly separated in projects. Few projects have the resources to apply both approaches throughout the entire project, therefore iteration and parallelism should be tightly focused on the project elements where knowledge has the largest gaps and uncertainty is highest. The choice of the best combination of the two approaches is influenced by the complexity and the extent of unforeseeable uncertainty (knowledge gaps) of the project (Sommer et al., 2009).

REFERENCES Abernathy, W.J. and Rosenbloom, R.S. (1969). Parallel strategies in development projects. Management Science, 15(10), B486–B505. Ahern, T., Leavy, B., and Byrne, P.J. (2014). Knowledge formation and learning in the management of projects: A problem solving perspective. International Journal of Project Management, 32(8), 1423–1431. Boudès, T., Charue-Duboc, F., and Midler, C. (1998). Project management learning: A contingent approach. In R.A. Lundin and C. Midler (Eds.), Projects as arenas for renewal and learning processes (pp. 61–70). Boston, MA: Springer. Brady, T. and Davies, A. (2004). Building project capabilities: From exploratory to exploitative learning. Organizational Studies, 25(9), 1601–1621. Chapman, C. and Ward, S.C. (2003). Project risk management: Processes, techniques and insights (2nd ed.). Chichester: Wiley. Dattée, B., Alexy, O., and Autio, E. (2018). Manoeuvring in poor visibility: How firms play the ecosystem game when uncertainty is High. Academy of Management Journal, 61(2), 466–498. Davies, A. and Brady, T. (2016). Explicating the dynamics of project capabilities. International Journal of Project Management, 34(2), 314–327. Feduzi, A. and Runde, J. (2014). Uncovering unknown unknowns: Towards a Baconian approach to management decision-making. Organizational Behavior and Human Decision Processes, 124(2), 268–283. Frederiksen, L. and Davies, A. (2008). Vanguards and ventures: Projects as vehicles for corporate entrepreneurship. International Journal of Project Management, 26(5), 487–496. Gillier, T. and Lenfle, S. (2019). Experimenting in the unknown: Lessons from the Manhattan project. European Management Review, 16(2), 449–469. Grant, R.M. (1996). Toward a knowledge-based theory of the firm. Strategic Management Journal, 17(Winter special issue), 109–122.

Managing unforeseeable uncertainty through learning  217

Hedlund, G. (1994). A model of knowledge management and the N-form corporation. Strategic Management Journal, 15(S2), 73–90. Ivory, C.J. and Vaughan, R. (2008). The role of framing in complex transitional projects. Long Range Planning, 41(1), 93–106. Jugdev, K. and Mathur, G. (2012). Classifying project management resources by complexity and leverage. International Journal of Managing Projects in Business, 5(1), 105–124. Keil, T., McGrath, R.G., and Tukiainen, T. (2009). Gems from ashes: capability creation and transformation in internal corporate venturing. Organization Science, 20(3), 601–620. Kock, A.H. and Gemünden, G. (2019). Project lineage management and project portfolio success. Project Management Journal, 50(5), 587–601. Kotnour, T. (1999). A learning framework for project management. Project Management Journal, 30(2), 32–38. Lenfle, S. (2011). The strategy of parallel approaches in projects with unforeseeable uncertainty: The Manhattan case in retrospect. International Journal of Project Management, 29(4), 359–373. Lenfle, S. (2014). Toward a genealogy of project management: Sidewinder and the management of exploratory projects. International Journal of Project Management, 32(6), 921–931. Lenfle, S. (2016). Floating in space? On the strangeness of exploratory projects. Project Management Journal, 47(2), 47–61. Leonard Barton, D. (1995). Wellsprings of knowledge. Cambridge, MA: Harvard Business School Press. Lindkvist, L. (2008). Project organization: Exploring its adaptation properties. International Journal of Project Management, 26(1), 13–20. Lindkvist, L. and Söderlund, J. (2002). What goes on in projects? On goal-directed learning processes. In K. Sahlin-Andersson and A. Söderholm, A. (Eds.), Beyond project management (pp. 278–348). Malmö: Liber. Lindkvist, L. et al. (1998). Tell managing product development projects: On the significance of fountains and deadlines. Organization Studies, 19(6), 931–951. Loch, C.H., De Meyer, A., and Pich, M.T. (2006). Managing the unknown: A new way of managing high uncertainty and risk in projects. New York: John Wiley. Loch, C.H., Solt, M.E., and Bailey, E. (2008). Diagnosing unforeseeable uncertainty in a new venture. Journal of Product Innovation Management, 25(1), 28–46. Loch, C.H. and Sommer, S. (2005). Vol de Nuit: The dream of the flying car at Lemond Automobiles SA. INSEAD Case Study, 2005-5086. Loch, C.H. and Sommer, S. (2019). The tension between flexible goals and managerial control in exploratory projects. Project Management Journal, 50(5), 1–14. Lynn, G.S., Morone, J.G., and Paulson, A.S. (1996). Marketing and discontinuous innovation: The probe and learn process. California Management Review, 38(3), 8–37. Maniak, R. and Midler, C. (2014). Multiproject lineage management: Bridging project management and design-based innovation strategy. International Journal of Project Management, 32(7), 1146–1156. Midler, C. (2013). Implementing a low-end disruption strategy through multiproject lineage management: The Logan case. Project Management Journal, 44(5), 24–35. Nelson, R.R. and Winter, S.G. (1982). An evolutionary theory of economic change. Cambridge, MA: Harvard University Press. Nevison, J.M. (1994). What can we learn about learning on projects? PM Network, 8(6), 6–8. Nonaka, I., Toyama, R., and Konno, N. (2000). SECI, Ba and leadership: A unified model of dynamic knowledge creation. Long Range Planning, 33(1), 5–34. Ordanini, A., Rubera, G., and Defillippi, R. (2010). The many moods of inter-organizational imitation: A critical review. International Journal of Management Reviews, 10(4), 375–398. Pemsel, S., Mueller, R., and Söderlund, J. (2016). Knowledge governance strategies in project-based organizations. Long Range Planning, 49(6), 648–660. Peschl, M.F. and Fundneider, T. (2017). Uncertainty and opportunity as drivers for re-thinking management: Future-oriented organizations by going beyond a mechanistic culture in organizations. In W. Küpers, S. Sonnenburg, and M. Zierold (Eds.), ReThinking management. Management – culture – interpretation (pp. 79–96). Springer Fachmedien Wiesbaden. Pich, M.T., Loch, C.H., and De Meyer, A. (2002). On uncertainty, ambiguity and complexity in project management. Management Science, 48(8), 1008–1023.

218  Handbook on innovation and project management

Prencipe, A. and Tell, F. (2001). Inter-project learning: Processes and outcomes of knowledge codification in project-based firms. Research Policy, 30(9), 1373–1394. Project Management Institute (PMI). (2017). A guide to the project management body of knowledge (PMBOK Guide) (6th ed.). Newton Square, PA: Project Management Institute. Ramasesh, R.V. and Browning, T.R. (2014). A conceptual framework for tackling knowable unknown unknowns in project management. Journal of Operations Management, 32, 190–204. Richerson, P., Collins, D., and Genet, R.M. (2006). Why managers need an evolutionary theory of organizations. Strategic Organization, 4(2), 201–211. Schrader, S., Riggs, W.M., and Smith, R.P. (1993). Choice over uncertainty and ambiguity in technical problem solving. Journal of Engineering & Technology Management, 10(1–2), 73–99. Söderlund, J. (2008). Competence dynamics and learning processes in project-based firms: Shifting, adapting, and leveraging. International Journal of Innovation Management, 12(1), 41–67. Söderlund, J. (2010). Knowledge entrainment and project management: The case of large-scale transformation projects. International Journal of Project Management, 28(2), 130–141. Sommer, S., Loch, C.H., and Dong, J. (2009). Managing complexity and unforeseeable uncertainty in startup companies: An empirical study. Organization Science, 20(1), 118–133. Sting, F., Mihm, J., and Loch, C. (2021). Collaborative search: The role of joint problem solving. Universität Köln/INSEAD/Cambridge Judge Business School Working Paper. Sydow, J., Lindkvist, L., and Defillippi, R. (2004). Project-based organizations, embeddedness and repositories of knowledge: Editorial. Organization Studies, 25(9), 1475–1489. Thomke, S. (2003). Experimentation matters. Cambridge, MA: HBS Press. Thomke, S. (2020). Building a culture of experimentation. Harvard Business Review, 98(2), 39–48. Van de Ven, A.H., Polley, D.E., Garud, R., and Venkataraman, S. (1999). The innovation journey. Oxford: Oxford University Press. Wheelwright, S.C. and Clark, K.B. (1992). Creating project plans to focus product development. Harvard Business Review, 70(2), 70–82. Whitehill, M. (1997). Knowledge-based strategy to deliver sustained competitive advantage. Long Range Planning, 30(4), 621–627. Whitley, R. (2006). Understanding differences: Searching for the social processes that construct and reproduce variety in science and economic organization. Organization Studies, 27(8), 1153–1177. Wideman, R.M. (1992). Project and program risk management. Newton Square, PA: Project Management Institute. Zollo, M. and Winter, S. (2002). Deliberate learning and the evolution of dynamic capabilities. Organization Science, 13(3), 339–351.

11. Success factors of project portfolio management and their influence on innovation success Alexander Kock and Hans Georg Gemünden

INTRODUCTION Any company that wants to be enduringly successful needs innovation capabilities to continuously renew itself by creating new products or services or reinventing how it creates value. The task of an innovating organization is to attract, create and select innovative ideas and concepts for new products, processes, services, systems and business models that are then developed, produced and used (Gemünden et al., 2018). Companies use projects as temporary organizations to manage such tasks. Therefore, companies typically run many innovative projects concurrently, and the share of project work generally increases (Nieto-Rodriguez, 2021; Schoper et al., 2018). Project portfolio management (PPM) helps exploit the potential of a portfolio of projects and mitigate risk accumulation. The task of PPM is to lead the organization properly so that it carries out the right projects, staffs these projects with competent project managers and teams, uses the project results sustainably and achieves all stakeholders’ value-creating objectives.

PROJECT PORTFOLIO MANAGEMENT Objectives of PPM Typically, portfolio management for innovation projects pursues several goals (Cooper et al., 2001; Kester et al., 2014): First, firms do not necessarily need to make every innovation project successful but should strive to maximize the overall value of the portfolio: one big breakthrough can make up for many failures, which are bound to happen due to innovation projects’ high uncertainty and complexity (Kock et al., 2011). Managers should strive to maximize the overall value across the portfolio’s projects by ensuring that projects achieve their objectives and deliver benefits for the organization (Cooper et al., 2001). Second, like in a financial portfolio, firms do not want to put all eggs in one basket but instead aim for a balanced portfolio. Portfolio balance refers to a harmonious portfolio composition concerning, for example, project innovativeness, time horizon or risk level (Cooper et  al., 2001; Kester et  al., 2014). Balance is supposed to assure organizational ambidexterity (O’Reilly and Tushman, 2004). Ambidexterity means simultaneously performing projects that improve innovations and hone existing competencies (i.e. exploitation) and projects that develop new competencies and create new options (i.e. exploration). Without exploitation,

219

220  Handbook on innovation and project management

companies may not survive today; without exploration, they may not survive tomorrow. Therefore, ambidexterity is crucial for long-term survival (O’Reilly and Tushman, 2004). Third, an organization must ensure that all innovation activities support the overall strategy and bring it closer to where it wants to be. Strategic implementation success describes the extent to which a portfolio’s projects align with the overall business strategy (Cooper et al., 2001; Kester et al., 2014; Kock et al., 2015; Kopmann et al., 2017). Fourth, a project portfolio high in future preparedness is one that, in the present, builds new skills, competencies, products and technologies that open up long-term future opportunities towards shaping the organization’s market and gaining a competitive edge (Kaufmann et al., 2020, 2021; Kock et al., 2015). Since there may be some trade-offs between these objectives, we need to assess the success of innovation portfolios multi-dimensionally. Firms achieving success in these dimensions have higher customer satisfaction, market effectiveness and profit (Kester et al., 2014). Challenges of Project Portfolio Management Portfolio management faces several challenges that are well-documented in the literature. A significant challenge lies in the elements of the portfolio, innovation projects, which are uncertain, difficult to predict and complex because they apply new and uncertain technologies and address uncertain markets (Kock et al., 2011; Schultz et al., 2013b). Managing the overall collection of portfolio elements that are individually difficult to predict makes portfolio decisions highly difficult. The innovation literature intensively debates balancing projects with different degrees of innovativeness or innovation horizons. Already Wheelwright and Clark (1992) emphasized the right mix of derivative, platform and breakthrough development projects. Christensen stressed that disruptive empowering innovations creating new markets and jobs should receive more investments and management attention, contrary to the current practice favouring investments in sustaining and efficiency innovations (Christensen and van Bever, 2014; Mezue et al., 2015). Kim and Mauborgne (2004) made an appealing plea for highly innovative strategic moves in product offerings that help firms avoid competitive battles in “red oceans” and exploit yet uncontested highly profitable “blue oceans”. However, this does not mean that every radical innovation is successful. On the contrary: the more innovative a project becomes (i.e. the more it addresses previously unaddressed needs and uses new technologies), the higher the likelihood of failure (Kock et al., 2011). In addition, the more successful innovations are, the higher the likelihood they get imitated and contested so that the initially blue ocean can also become red. Similarly, Nagji and Tuff (2012) argue that radical innovations are rare but contribute so much to growth and profitability that firms should strive for higher innovativeness in their portfolios. However, the authors acknowledge that the right balance varies between industries and firms and that no objective ratios can be derived. This proposal is in line with the findings from Schultz et al. (2013b) that the relationship between a portfolio’s innovativeness and success is inverted u-shaped. Finally, the frameworks by Kim and Mauborgne (2004) and Nagji and Tuff (2012) ignore that many innovations require new technologies using new knowledge bases, new technological principles, new materials or components or new systems designs. It usually takes a lot of time and effort until this pays back – and it is not one simple strategic move but consecutive projects building on each other.

Success factors of project portfolio management  221

Nevertheless, firms must make decisions about the degree of innovativeness of their project portfolios. The balance between projects from different innovation horizons is challenging because with increasing proficiency in one type of project, the ability in the other type wanes. Decision-makers are often unaware of this path dependence and may slip away from the right balance. A permanent challenge portfolio decision-makers must monitor is establishing the right balance and sticking to the ambidexterity rule to perform sufficient explorative and exploitive projects simultaneously. In portfolio decisions, exploitation projects often look more favourable (Christensen and van Bever, 2014). They need resources more “urgently”, promise quicker gains, face lower uncertainties and are backed by influential stakeholders who depend on their funding. A further challenge is that projects are highly interdependent. Portfolio complexity increases with the number of projects, the degree of interdependency and the magnitude of changes in projects and interdependencies (Teller et al., 2012). Projects are interdependent when the success of one project depends upon other projects (Killen and Kjaer, 2012). Interdependencies can relate to benefits, resources, risks or knowledge. For example, the benefits of one project might increase when other projects are also done, or projects may need to share the same specialized human resources. Making holistic portfolio decisions – instead of isolated project decisions – is therefore essential. However, decision-makers struggle with understanding interdependencies (Killen and Kjaer, 2012), which can overload their mental capacity to analyse the high number of combinations and the variety of information (Killen et al., 2020). Sommer and Loch (2004) show that for unforeseeable uncertainties (“unknown unknowns”), a trial-and-error approach is superior to selectionism (i.e. parallel testing of alternatives and retaining the best option) if the costs for both strategies are high and in a comparable range. Parallel testing is only superior if the tests are precise and reliable and the complexity caused by the interaction of variables is very high. Finally, portfolio decision processes can be very political and biased. The stakes are high when deciding on the initiation and termination of innovation projects because they involve the company’s future and viability. In addition, many different and influential stakeholders must participate in the decision process. This constellation invariably leads to negotiation and bargaining (Martinsuo, 2013). For example, Kester et al. (2011) show how political behaviour in the form of influence, persuasion and negotiation leads to power-based decision-making so that an unequal distribution of power allows more powerful groups or individuals to make decisions that reflect their personal interests. Furthermore, portfolio decisions about project initiation, continuation or termination are often subject to cognitive biases (Killen et al., 2020; Kruft et al., 2019). For example, portfolio decision-makers tend to prefer less novel project proposals, especially when they have a high workload (Criscuolo et al., 2017), and even the order of proposals in portfolio meetings affects their decisions (Criscuolo et al., 2021).

PORTFOLIO MANAGEMENT SUCCESS FACTORS Empirical research has identified several success factors to overcome these challenges and successfully innovate through project portfolio management. We categorize these success factors in a framework of five groups that follows a decision-making perspective. The framework starts with one stakeholder group and a few decision-making parameters and then integrates more stakeholders and malleable parameters that influence project portfolio success (see Figure 11.1).

222  Handbook on innovation and project management

Figure 11.1  The five groups of success factors in portfolio management The first group contains the traditional success factors, which were investigated early on by Cooper et al. (2001). This research focuses on the stakeholder group senior management, and the decision situation assumes the resources, projects and strategic goals as given and fully controlled by the focal organization. The decision situation becomes more complex in the second group, which integrates upstream and downstream factors and external stakeholders who co-create or co-exploit innovations or act as their buyers. The project proposals are no more considered as given. Instead, searching and creating project candidates – often with external partners – becomes an integral part of project portfolio management. Similarly, using and commercializing the project results becomes an essential part of PPM. In the third group, the human resource factors, the people who work in projects and PPM environments are integrated as a major stakeholder group that needs to be attracted, selected, developed and motivated. These three types of success factors are driven and leveraged by the fourth group of success factors that we call strategic frame factors. We emphasize strategic orientations that indirectly affect portfolio success and moderate other factors’ success influence. The last group, long-term factors, are those factors that help overcome the somewhat static perspective of PPM. The previous groups did not yet include how a system of success factors evolves, which path dependencies may explain why some factors have developed well and others have not, and what kind of decision-making behaviour may help find the best development paths to create enduring success. In the following, we will discuss the five groups in more detail. Traditional Success Factors The first group concerns traditional success factors that assume a project portfolio’s resources, projects, strategies and stakeholders as given. Although the corresponding practices are not sufficient for innovation success, they pose necessary conditions. First, strategic clarity means that the organization should clearly formulate and communicate its innovation strategy and closely link corporate and portfolio strategic planning to operationalize the strategy to the single project level (Kopmann et al., 2017; Meskendahl, 2010; Salomo et al., 2008). For example, deliberately specifying innovation focus areas and providing organizational framing

Success factors of project portfolio management  223

for related innovation projects increases the overall innovativeness and the success of new product development portfolios (Salomo et al., 2008). Second, portfolio stakeholders, such as senior managers, line managers and portfolio and project managers, need to communicate openly, share common goals and support and trust each other (Jonas et al., 2013). Particularly, senior manager involvement is beneficial, but only if they follow their own rules and do not regulate every detail (Unger et al., 2012b). Third, a mature PPM organization is a necessary condition for success. This means portfolio decision processes are clearly defined with accepted and transparent criteria (Teller et al., 2012). Furthermore, single project management needs a certain degree of maturity and formalization to enable effective portfolio processes (Schultz et al., 2013a; Teller et al., 2012). Project portfolio management offices also support success through their coordinating, controlling and caretaking roles (Unger et al., 2012a). Fourth, informed planning and controlling are essential. Top-performing companies review their project portfolios more often, adjust faster, communicate decisions well and pursue actions more intensively (Kock and Gemünden, 2016). Formal risk management also positively influences portfolio success (Teller and Kock, 2013), but risk management is more than managing the sum of individual project risks (Teller et al., 2014). Finally, project portfolio management information systems improve transparency, collaboration quality, resource allocation and decision-making, but only if the portfolio, project and risk management processes have sufficient maturity (Kock et al., 2020). Enlarging the Scope: Up- and Downstream Factors The traditional factors concentrate on internal stakeholders and project execution. The second group abandons this limited view and also considers the ideation and exploitation stage and external stakeholders’ inclusion and co-creation processes. First, top-performing companies actively manage the idea pipeline of their portfolio. Good front-end management is a critical success factor not only in single projects (Eling and Herstatt, 2017; Park et al., 2021; Williams et al., 2019) but also in project portfolios. For example, Kock et al. (2015) showed that ideation management positively influences portfolios’ front end by simultaneously supporting the variety and selection of ideas, thus improving the project candidates’ value and feasibility. Ideation management supports variety, creativity and openness through creative encouragement to give employees autonomy, resources and support for ideas’ further development. For example, ideators can increase their ideas’ quality by receiving constructive feedback from a heterogeneous group of commentators (Zhu et al., 2019). Furthermore, the novelty of selected ideas is higher if the portfolio board is more diverse in expertise (Criscuolo et  al., 2017). But ideation management should also provide alignment and integration, which can be achieved by a supportive ideation strategy – providing a vision and guarding rails aligned with corporate goals – and a formalized ideation process to improve idea selection (Kock et al., 2015). The front end’s positive effect on portfolio success is significantly stronger when companies are willing to take risks and their innovation portfolios are larger and more complex (Kock et al., 2016). Thus, ideation pays back for large and complex innovation portfolios if the will to take risks is reasonably high. Second, top performers consider benefit exploitation over and above the immediate project results. For example, Kopmann et al. (2015) define the term business case control as a portfolio control activity that includes (1) the use and analysis of business cases for evaluating project

224  Handbook on innovation and project management

proposals, (2) the continuous monitoring of the business case validity of ongoing projects and (3) the tracking of the business case in terms of benefits realized after project completion. While most companies apply the first element, only a few use the second and third elements. But companies that monitor and question business case validity during project execution and track business case realization long after a project’s completion have, on average, more successful portfolios. Business case control has an even more substantial positive effect in more complex portfolios, under higher environmental turbulence, and when business case owners are incentivized for overall portfolio goals and made accountable. Third, integrating external stakeholders becomes critical because the external context is highly relevant for project portfolios (Martinsuo and Geraldi, 2020). For example, Vedel and Geraldi (2020) show how external partners can profoundly shape a portfolio’s strategic direction over time. Voss and Kock (2013) analysed customers’ influence in portfolio boards on portfolio success and found that “value for the customer” and “value from the customer” increased portfolio success. And Biedenbach and Müller (2012) find a strong correlation between an organization’s ability to integrate external knowledge (i.e. absorptive capability) and project portfolio performance. Human Resource Factors The third group addresses people-related capability factors. Project portfolio management usually considers the assigned human resources as given. Developing and motivating employees to do a good job and collaborate well with others is typically outside the scope of project portfolio management, but it is an important part of multi-project management. In addition to developing individual competencies, a learning project-oriented organization must institutionalize knowledge management practices for systematic collective learning. We, therefore, mainly address how companies recognize and support project managers and experts working on innovation projects and portfolios. The first issue is knowledge management: lessons-learned practices for capturing and disseminating the knowledge gained during projects effectively retain project management competence and eventually increase business success (Ekrot et al., 2016a). For example, communities of practice help to share and co-create knowledge. Second, project manager career systems should fit the needs of project managers the company wants to develop and retain. Firms should communicate and manage such systems well so that their offers are credible and reliable. Offers include remuneration and career advancement comparable to line managers, training and coaching matched to their career stage, and participation in assignments that match their development (Gemünden et  al., 2018). Ekrot et al. (2016a) show that combining career systems and lessons-learned practices improves project management competence, fostering the success of project portfolios. But since this support is often unavailable, project professionals initiate informal practices, including mentoring or buddy systems (Huemann et al., 2019). Third, project managers’ voice behaviour, the discretionary communication of ideas, suggestions or concerns with the intent to improve organizational functioning (Ekrot et al., 2016b), increases portfolio success (Kaufmann et al., 2020). Senior managers should listen to their project managers’ suggestions, which can also trigger new emerging strategies. Ekrot et al. (2016b) found that career systems, qualification opportunities, idea encouragement and peer collaboration improve voice behaviour. Investing in people-related capability factors positively influences not only project portfolio success but also project managers’ development

Success factors of project portfolio management  225

and work satisfaction. Work satisfaction and perceived organizational support are higher, and turnover intention is lower when career systems and qualification opportunities offer developmental perspectives (Ekrot et  al., 2018). Combined with better knowledge management activities, this leads to higher competence retention because more successful project managers remain, and their knowledge is improved and better exploited (Ekrot et al., 2016a). So far, the studies seem to indicate a positive relationship between fulfilling the goals of project managers and project portfolio success, particularly if the investments in project management career systems and upward communication are enduring and create an excellent vertical collaboration culture. Strategic Frame Factors The fourth group includes decision-makers’ fundamental strategic orientations that guide their attitude and behaviour and are essential antecedents for managerial practice. These orientations have also been called core values (Gemünden et al., 2018), and they affect innovation success directly and indirectly because they can leverage the effect of other success factors. Stakeholder orientation: a central idea of project management is that problem-oriented cross-functional, inter-disciplinary and inter-organizational collaboration in teams may help find better solutions in a shorter time and save money by avoiding mistakes. This idea does not only apply to single projects but also to the management of project portfolios that contain interdependent projects. The more the notion of mutual understanding, respect, trust and support becomes a central value for joint problem-solving, the higher the performance will be. This kind of stakeholder orientation applies to internal and external stakeholders who cocreate or co-commercialize projects and their results. Stakeholder orientation refers not only to partners who exchange essential inputs and outputs but also to people negatively affected by projects that have a risk at stake. It is essential to understand their concerns, often legally protected, and act accordingly. Stakeholder orientation is particularly supportive of sustainable and social innovations. Future orientation means that decision-makers prioritize future success above current success, meaning they aim at long-term, sustainable development at the expense of shortterm gains and profits. This orientation implies a company’s willingness to invest in projects that make existing products, investments and capabilities obsolete, favouring investment in empowering innovation projects (Christensen Bever, 2014; Christensen, 2015). For example, Rank et  al. (2015) showed that this willingness to cannibalize is significantly related to a company’s future preparedness. Entrepreneurial orientation describes the characteristics of firms and their decision-makers who actively pursue innovation, accept risks and deliberately enter new markets. Covin and Slevin (1991) suggested that entrepreneurial orientation comprises innovativeness (constantly striving for novelty through experimentation), proactiveness (actively pursuing opportunities) and risk-taking (accepting high-risk ventures). Firms with high entrepreneurial orientation have more innovative portfolios (Kaufmann et al., 2021), are more successful (Kaufmann et al., 2020) and further increase the positive effects of PPM practices (Kock and Gemünden, 2021). Long-Term Factors The last group of factors complement the previously introduced elements in various ways. First, we consider path dependence to emphasize that both the PPM success factors and the

226  Handbook on innovation and project management

innovative results they create develop over time: the current and future states depend on previous states. By introducing the path development perspective, we want to overcome the static view of PPM and integrate the intertemporal dependencies. Second, so far, we have assumed the organizational strategy as given and that portfolio management does the strategy’s bidding by aligning the projects with it. However, this is an unrealistic assumption. Strategies need to adapt in the face of new threats or opportunities and proactively create new fields of action. Therefore, we look at the role of emerging strategies, how they come into being and how they drive changes in the success factors or moderate their impact. Third, we are interested in what kind of decision-making principles are supportive in a dynamic world. Real options reasoning is a principle that can serve as a good heuristic. Path dependence: “Rome was not built in a day”. This proverb also applies to innovations. Successful new products often build on previous successful products and improve their functionality, usability, reliability or safety. Therefore, firms develop products like the iPhone or the Star Wars movies in project sequences that describe successful innovation paths. In contrast to single projects, which are temporary organizations with a predetermined time horizon, a project sequence building a long-term innovation path is not a temporary organization because it is uncertain how many elements the sequence will have. Wheelwright and Clark (1992) already acknowledged the importance of project sequencing for building development capabilities. Midler (2013) studied Renault’s successful Logan, designed as a low-cost car. Accompanied by aggressive marketing in price-sensitive markets, it established a new brand and product family. Davies and Brady (2000) proposed an organizational learning cycle for innovation of complex product systems, modelling capability building via lessons learned from initial projects and leading to improved project management procedures and higher performance of follow-up projects. Successful firms consciously manage project sequences rather than isolated projects and use established planning and knowledge management practices for their sequence management. The contribution from Midler and Maniak in this book deals with the challenge of managing such project sequences and proposes a model of project lineage management. Portfolio managers should know that their choices affect a portfolio of innovation paths and that business success depends strongly on developing innovation paths. It is essential to recognize when an innovation path ends and should not be supported anymore. And it is also vital to build and seize options for new paths that extend the existing portfolio and lay the ground for future success. Emerging strategies: while the influence of clearly defined and well-communicated deliberate strategies is well documented (Meskendahl, 2010), the performance effect of deliberate strategies might vanish in turbulent environments and emergent strategic initiatives (i.e. initiatives that arise unintentionally, usually bottom-up) increase in importance. Such emerging strategies may react more quickly to opportunities and risks observed by mid-level line managers and project managers. For example, Kopmann et al. (2017) show that PPM not only fosters the implementation of intended strategies but can also disclose strategic opportunities by unveiling emerging patterns. Deliberate strategy implementation and emerging strategy recognition even show complementary effects on success (i.e. one increases the benefits of the other). However, the deliberate strategy’s impact becomes weaker with increasing environmental turbulence. Both strategy implementation processes are supported by strategic control, which comprises premise control (continuous verification of strategic planning assumptions also during implementation), implementation control (scrutinizing the currently pursued strategic direction) and strategic surveillance (scanning the environment to identify unforeseeable

Success factors of project portfolio management  227

or previously undetected critical events) (Kopmann et  al., 2017). Another study shows that also agile capabilities (i.e. the competence in and the application of agile practices) drive strategy emergence in multi-project environments (Kaufmann et  al., 2020). Agile projects have a higher autonomy, and team members interact more frequently with project users and consistently exchange information with the portfolio’s other projects (Sweetman and Conboy, 2018). Such a portfolio resembles a complex adaptive system that can adapt to a challenging environment (Sweetman and Conboy, 2018). Through the dynamic relationships between individuals and projects, valuable strategic initiatives can arise that benefit portfolio success. Real options reasoning: the core principles of longitudinal intertemporal interdependencies can also be investigated from a real options perspective. According to Klingebiel and Adner (2015), real options reasoning means that (1) instead of deciding whether or not to fully finance an option at a certain point in time, the decision-makers distribute the investment sequentially over a period of time; (2) only low initial investments are made in selected options, increasing the autonomy of future decisions; and (3) all available options compete against each other for further investment, allowing shifts from low-potential options to better ones. The empirical results from Kaufmann et al. (2021) confirm a positive relationship between real options reasoning and portfolio innovativeness, and between portfolio innovativeness and portfolio success. This finding is in line with the argument that ROR encourages project portfolio decision-makers to venture into more innovative and, therefore, uncertain options. The influence also depends on the strategic and cultural context because a sufficiently high level of entrepreneurial orientation is required for ROR to affect portfolio success. A strong entrepreneurial orientation seems conducive for managers to rely more on high-option values and be willing to take considerable risks to use these options if there is sufficient evidence of eventual success. We encourage managers to apply ROR to cope with innovative projects’ higher uncertainty. However, we also recommend managers assess a firm’s strategic and cultural contexts before introducing ROR.

DISCUSSION Our framework offers a grouping of project portfolio management success factors that positively influence innovation success. There is positive evidence for all reported success factors, but we are not yet aware of a meta-analysis of these factors. Kock et al. (2021) also showed that six selected success factors covering several of our success factor groups influence project portfolio success when controlling for each other’s influence. The explained variance amounts to 50 per cent, suggesting that the simultaneous use of several success factors can make a big difference. It might be helpful to extend such tests using the proposed new model. We emphasize that external and internal contingency factors moderate the influence of the success factors because project portfolios are highly context-dependent (Martinsuo, 2013; Martinsuo and Geraldi, 2020). Context dependence means, for example, that in more static environments, the influence weights of the success factors may have other values than in more dynamic environments, or the effects may even change direction (i.e. we see a disordinal interaction effect). Internal contingency factors may also play a role, for example, a project portfolio’s innovativeness, its composition concerning the projects’ content, or the degree of interdependencies between projects. Thus, simple linear models may be helpful for orientation but misleading if strong contingencies exist.

228  Handbook on innovation and project management

One specific contingency deserves more profound attention. We hypothesized and found positive evidence that the entrepreneurial orientation positively moderated several other success factors but did not directly influence portfolio success when controlling for the other success factors. There is no free lunch. Establishing and maintaining a success factor comes at a cost. If the success factor’s dose is too small, it will not show the desired effect; if the dose is too high, adverse side effects may occur. Success factors may also deliver diminishing returns. Therefore, the dose of a success factor might be within a limited range, and the success factor may also have a limited effect. If a leveraging factor such as entrepreneurial orientation moderates this success factor positively, its impact can further increase (Kock and Gemünden, 2021). Future research should develop theories and tests for such leveraging success factors. We want to stress another issue. The success of innovative project portfolios is usually measured from the perspective of the firm that is this portfolio’s business owner. The success measures thus reflect the perspective of upper managers who make decisions about project portfolios and investors who own a firm’s equity. However, project portfolio management only indirectly influences the success of the projects in a portfolio. A more direct and strong influence comes from the project managers and the experts working on the projects. What are these stakeholders’ success criteria and expectations regarding good project portfolio management? Surprisingly, we found that project managers who had a more successful previous project were more motivated to leave the project manager position, favouring a line manager position (Ekrot et al., 2018). In addition, successful project managers are more likely to get promotional offers. Therefore, firms need to be concerned about retaining good project managers in project management positions. What do project managers want, and how can firms manage their project portfolio to fulfil these wishes? Firms that prefer more innovative and challenging projects need to attract, select, develop and retain good project managers; firms also need to give them more power and a higher status. Project selection and staffing choices influence not only customer and supplier benefits and growth and profitability goals but also project team members’ competence development and motivation. Thus, portfolio decisions should also consider the benefits and risks of these decisions for the project managers and team members. The previously referenced studies show that people-related success factors increase perceived organizational support, work satisfaction and the willingness to stay in a project management role. However, does this also mean that career success measures like salary, promotion quality and speed, social status, disposable power and perceived achievement are sufficiently fulfilled? We know that there are deeply rooted conflicts between project and line managers, and if more empowered project managers want a higher share of the created value, this may cause conflicts with those that get a lower share. Therefore, we suggest extending the performance measurement of project portfolio management. The success factors are not given; they must be developed and maintained over time. Like innovations, innovation systems also show a path dependence. Applying the promotor theory from Witte and Hauschildt, Lehner et al. (2020) found positive evidence that key innovators – expert, power and process promotors – cooperatively established the success factors of a project-oriented organization. However, it took about ten years to develop the success factors of such an organization, and they came mainly from the first and third groups of our framework. We should learn more about how innovation systems develop over time, which success factors are easy and more quickly to create, which need more time and effort, which barriers hinder their development and how we can overcome these barriers.

Success factors of project portfolio management  229

REFERENCES Biedenbach, T. and Müller, R. (2012). Absorptive, innovative and adaptive capabilities and their impact on project and project portfolio performance. International Journal of Project Management, 30(5), 621–635. Christensen, C.M. and van Bever, D. (2014). The capitalist’s dilemma. Harvard Business Review, 92(6), 60. Cooper, R.G., Edgett, S.J., and Kleinschmidt, E.J. (2001). Portfolio management for new products (Vol. 2). Cambridge, MA: Perseus Pub. Covin, J.G. and Slevin, D.P. (1991). A conceptual model of entrepreneurship as firm behavior. Entrepreneurship: Theory & Practice, 16(1), 7–25. Criscuolo, P., Dahlander, L., Grohsjean, T., and Salter, A. (2017). Evaluating novelty: The role of panels in the selection of R&D Projects. Academy of Management Journal, 60(2), 433–460. Criscuolo, P., Dahlander, L., Grohsjean, T., and Salter, A. (2021). The sequence effect in panel decisions: Evidence from the evaluation of research and development projects. Organization Science, 32(4), 987–1008. Davies, A. and Brady, T. (2000). Organisational capabilities and learning in complex product systems: Towards repeatable solutions. Research Policy, 29(7–8), 931–953. Ekrot, B., Kock, A., and Gemünden, H.G. (2016a). Retaining project management competence— antecedents and consequences. International Journal of Project Management, 34(2), 145–157. Ekrot, B., Rank, J., and Gemünden, H.G. (2016b). Antecedents of project managers’ voice behavior: The moderating effect of organization-based self-esteem and affective organizational commitment. International Journal of Project Management, 34(6), 1028–1042. Ekrot, B., Rank, J., Kock, A., and Gemünden, H.G. (2018). Retaining and satisfying project managers - antecedents and outcomes of project managers’ perceived organizational support. International Journal of Human Resource Management, 29(12), 1950–1971. Eling, K. and Herstatt, C. (2017). Managing the front end of innovation—less fuzzy, yet still not fully understood. Journal of Product Innovation Management, 34(6), 864–874. Gemünden, H.G., Lehner, P., and Kock, A. (2018). The project-oriented organization and its contribution to innovation. International Journal of Project Management, 36(1), 147–160. Huemann, M., Ringhofer, C., and Keegan, A. (2019). Who supports project careers? Leveraging the compensatory roles of line managers. Project Management Journal, 50(4), 476–486. Jonas, D., Kock, A., and Gemünden, H.G. (2013). Predicting project portfolio success by measuring management quality-A longitudinal study. IEEE Transactions on Engineering Management, 60(2), 215–226. Kaufmann, C., Kock, A., and Gemünden, H.G. (2020). Emerging strategy recognition in agile portfolios. International Journal of Project Management, 38(7), 429–440. Kaufmann, C., Kock, A., and Gemünden, H.G. (2021). Strategic and cultural contexts of real options reasoning in innovation portfolios. Journal of Product Innovation Management, 38(3), 334–354. Kester, L., Griffin, A., Hultink, E.J., and Lauche, K. (2011). Exploring portfolio decision‑making processes. Journal of Product Innovation Management, 28(5), 641–661. Kester, L., Hultink, E.J., and Griffin, A. (2014). An empirical investigation of the antecedents and outcomes of NPD portfolio success. Journal of Product Innovation Management, 31(6), 1199–1213. Killen, C.P., Geraldi, J., and Kock, A. (2020). The role of decision makers’ use of visualizations in project portfolio decision making. International Journal of Project Management, 38(5), 267–277. Killen, C.P. and Kjaer, C. (2012). Understanding project interdependencies: The role of visual representation, culture and process. International Journal of Project Management, 30(5), 554–566. Kim, W.C. and Mauborgne, R. (2004). Blue ocean strategy. Harvard Business Review, 82(10), 76–84. Klingebiel, R. and Adner, R. (2015). Real options logic revisited: The performance effects of alternative resource allocation regimes. Academy of Management Journal, 58(1), 221–241. Kock, A. and Gemünden, H.G. (2016). Antecedents to decision-making quality and agility in innovation portfolio management. Journal of Product Innovation Management, 33(6), 670–686. Kock, A. and Gemünden, H.G. (2021). How entrepreneurial orientation can leverage innovation project portfolio management. R&D Management, 51(1), 40–56. Kock, A., Gemünden, H.G., Salomo, S., and Schultz, C. (2011). The mixed blessings of technological innovativeness for the commercial success of new products. Journal of Product Innovation Management, 28(S1), 28–43.

230  Handbook on innovation and project management

Kock, A., Heising, W., and Gemünden, H.G. (2015). How ideation portfolio management influences front-end success: Ideation portfolio management. Journal of Product Innovation Management, 32(4), 539–555. Kock, A., Heising, W., and Gemünden, H.G. (2016). A contingency approach on the impact of front-end success on project portfolio success. Project Management Journal, 47(2), 115–129. Kock, A., Lehner, P., and Gemünden, H.G. (2021). The project-oriented organisation: An empirical investigation of its impact on performance through driving promotors. Paper presented at the European Academy of Management, Montreal. Kock, A., Schulz, B., Kopmann, J., and Gemünden, H.G. (2020). Project portfolio management information systems’ positive influence on performance - the importance of process maturity. International Journal of Project Management, 38(4), 229–241. Kopmann, J., Kock, A., Killen, C.P., and Gemünden, H.G. (2015). Business case control in project portfolios - an empirical investigation of performance consequences and moderating effects. IEEE Transactions on Engineering Management, 62(4), 529–543. Kopmann, J., Kock, A., Killen, C.P., and Gemünden, H.G. (2017). The role of project portfolio management in fostering both deliberate and emergent strategy. International Journal of Project Management, 35(4), 557–570. Kruft, T., Tilsner, C., Schindler, A., and Kock, A. (2019). Persuasion in corporate idea contests: The moderating role of content scarcity on decision-making. Journal of Product Innovation Management, 36(5), 560–585. Lehner, P., Martignoni, J., and Gemünden, H.G. (2020). Promotors – necessary drivers of viable, project-oriented organizations. Paper presented at the European Academy of Management, Dublin. Martinsuo, M. (2013). Project portfolio management in practice and in context. International Journal of Project Management, 31(6), 794–803. Martinsuo, M. and Geraldi, J. (2020). Management of project portfolios: Relationships of project portfolios with their contexts. International Journal of Project Management, 38(7), 441–453. Meskendahl, S. (2010). The influence of business strategy on project portfolio management and its success - A conceptual framework. International Journal of Project Management, 28(8), 807–817. Mezue, B.C., Christensen, C.M., and van Bever, D. (2015). The power of market creation how innovation can spur development. Foreign Affairs, 94(1), 69–76. Midler, C. (2013). Implementing a low-end disruption strategy through multiproject lineage management: The Logan case. Project Management Journal, 44(5), 24–35. Nagji, B. and Tuff, G. (2012). Managing your innovation portfolio. Harvard Business Review, 90(5), 66–74. Nieto-Rodriguez, A. (2021). The project economy has arrived: Use these skills and tools to make the most of it. Harvard Business Review, 99(6), 38–45. O’Reilly, C.A. and Tushman, M.L. (2004). The ambidextrous organisation. Harvard Business Review, 82(4), 74–81. Park, D., Han, J., and Childs, P.R.N. (2021). 266 Fuzzy front‑end studies: Current state and future directions for new product development. Research in Engineering Design, 32(3), 77–409. Rank, J., Unger, B.N., and Gemünden, H.G. (2015). Preparedness for the future in project portfolio management: The roles of proactiveness, riskiness and willingness to cannibalize. International Journal of Project Management, 33(8), 1730–1743. Salomo, S., Talke, K., and Strecker, N. (2008). Innovation field orientation and its effect on innovativeness and firm performance. Journal of Product Innovation Management, 25(6), 560–576. Schoper, Y.-G., Wald, A., Ingason, H.T., and Fridgeirsson, T.V. (2018). Projectification in western economies: A comparative study of Germany, Norway and Iceland. International Journal of Project Management, 36(1), 71–82. Schultz, C., Salomo, S., de Brentani, U., and Kleinschmidt, E.J. (2013a). How formal control influences decision-making clarity and innovation performance. Journal of Product Innovation Management, 30(3), 430–447. Schultz, C., Salomo, S., and Talke, K. (2013b). Measuring new product portfolio innovativeness: How differences in scale width and evaluator perspectives affect its relationship with performance: Measuring product portfolio innovativeness. Journal of Product Innovation Management, 30, 93–109.

Success factors of project portfolio management  231

Sommer, S.C. and Loch, C.H. (2004). Selectionism and learning in projects with complexity and unforeseeable uncertainty. Management Science, 50(10), 1334–1347. Sweetman, R. and Conboy, K. (2018). Portfolios of agile projects. Project Management Journal, 49(6), 18–38. Teller, J. and Kock, A. (2013). An empirical investigation on how portfolio risk management influences project portfolio success. International Journal of Project Management, 31(6), 817–829. Teller, J., Kock, A., and Gemünden, H.G. (2014). Risk management in project portfolios is more than managing project risks: A contingency perspective on risk management. Project Management Journal, 45(4), 67–80. Teller, J., Unger, B.N., Kock, A., and Gemünden, H.G. (2012). Formalization of project portfolio management: The moderating role of project portfolio complexity. International Journal of Project Management, 30(5), 596–607. Unger, B.N., Gemünden, H.G., and Aubry, M. (2012a). The three roles of a project portfolio management office: Their impact on portfolio management execution and success. International Journal of Project Management, 30(5), 608–620. Unger, B.N., Kock, A., Gemünden, H.G., and Jonas, D. (2012b). Enforcing strategic fit of project portfolios by project termination: An empirical study on senior management involvement. International Journal of Project Management, 30(6), 675–685. Vedel, J.B. and Geraldi, J. (2020). A “stranger” in the making of strategy: A process perspective of project portfolio management in a pharmaceutical firm. International Journal of Project Management, 38(7), 454–463. Voss, M. and Kock, A. (2013). Impact of relationship value on project portfolio success — Investigating the moderating effects of portfolio characteristics and external turbulence. International Journal of Project Management, 31(6), 847–861. Wheelwright, S.C. and Clark, K.B. (1992). Creating project plans to focus product development. Harvard Business Review, 70(2), 70–82. Williams, T., Vo, H., Samset, K., and Edkins, A. (2019). The front-end of projects: A systematic literature review and structuring. Production Planning and Control, 30(14), 1137–1169. Zhu, H.Z., Kock, A., Wentker, M., and Leker, J. (2019). How does online interaction affect idea quality? The effect of feedback in firm-internal idea competitions. Journal of Product Innovation Management, 36(1), 24–40.

12. Innovation in project-based organizations1 Jan van den Ende and Floor Blindenbach-Driessen

INTRODUCTION: WHAT IS A PROJECT-BASED ORGANIZATION? In this chapter, we address innovation and new business development in project-based organizations. Project-based organizations perform their activities in the form of projects for customers (Davies et al., 2011; Hobday, 2000). Examples are construction companies, consultancy firms, IT solution providers and law firms. Project-based organizations are distributed organizations, in the sense that knowledge and innovation-related activities are more spread across the organization compared with most product or mass-service firms (Moore, 2005). In addition, projectbased organizations have a different organizational structure than product or mass-service firms. Even if such organizations operate in a single country, their sales and operations are spread over different units and projects that often each have their own profit and loss responsibilities. Because of their characteristics, project-based organizations have certain advantages over mass-product or -service firms when it comes to innovating. Most of the innovation literature addresses the friction between operations and innovation activities in mass-product and -service firms (Raisch and Birkinshaw, 2008). In those firms, operations usually focus on short-term efficiencies and on preserving the status quo. In such an operational environment it is difficult to make innovation thrive (Tushman and O’Reilly, 1996). In project-based organizations these tensions are not the same, because operations in these organizations are less focused on efficiency, are more customer-oriented and are much more adaptable (Blindenbach-Driessen and Van den Ende, 2010). That means that ambidexterity – the ability of an organization to simultaneously exploit today’s capabilities and explore those needed in the future – has a different polarity. In project-based organizations, all infrastructure and decision-making processes, including quality control, are client-centric. When the client asks, the organization is quick to deliver (Gann and Salter, 2000; Hobday, 2000). As a result, the ambidextrous polarity is not so much between operations and innovation activities, but instead, the tension arises from the conflicts between the demands of the short-term customer-focused innovation and more future-oriented, firm-initiated innovation. We label this latter type of innovation as proactive innovation. The proactive innovation projects lack the same urgency, funding source and immediate application as the operational projects that are executed on behalf of clients. That is the challenge that project-based firms must overcome if they want to become ambidextrous. We discuss the solutions to these tensions in this chapter and illustrate the challenges and solutions with practical examples from the legal and healthcare sectors.

HOW DO PROJECT-BASED ORGANIZATIONS INNOVATE? Innovation plays a paradoxical role in project-based organizations. On the one hand, innovation is their core competence, but on the other, they really struggle to renew their own 232

Innovation in project-based organizations  233

offerings, business models and processes. For example, a typical product of an IT solutions provider is building a new IT system for a bank. Such projects result in an innovative solution for the client. As such, project-based organizations have the development of innovative solutions for clients as a core competence. But as the saying goes, “The shoemaker’s children go barefoot”; project-based organizations are usually not good at innovating for themselves. As we will explain, this has much to do with the distributed character of the knowledge base in project-based organizations and with how they operate (Van den Ende, 2021). There are in general two ways of innovating for project-based organizations. The first is reactive innovation, which involves innovating on a customer’s project. In this case, the project-based organization performs a project for a customer in which it includes some kind of innovative part, which it can apply in the future for other customers. Gann and Salter label this activity as “practitioner-research” (2000, 965) and Brady and Davies (2004, 1607) speak of project-based learning, which occurs in a bottom-up process through the activities of customer-facing units. So, for instance, a contractor builds an office block with an innovative air-conditioning installation which is new to the contractor and the customer. The customer is of course aware of the innovation, and if it is more expensive, they will pay an extra price. The customer may (also) pay for the cost of the provider learning about the innovation, or these costs may be shared between the project-based organization and the customer. This way of innovating is an attractive option for the project-based organization because it is nearly riskfree since the customer is paying for the development and implementation. Another advantage is that the decisions regarding these types of reactive customer-oriented innovations are conveniently aligned with these organizations’ core operations and decision-making processes. Because the client is paying, reactive innovation projects typically don’t require approval from anyone else in the organization, except the business unit that is signing off on the job. However, this approach also has two disadvantages. The most important one is that the project-based organization is required to adapt the innovation to the specific needs of the first customer – since they are paying. These requirements do not necessarily coincide with the needs of the larger market. In many cases, the first customer will be an innovative company, which is not necessarily representative of the average customer. The project-based organization may therefore have to adapt the innovation again for other customers, or a permanent misfit may remain between the innovation and other customers’ needs. Second, this innovation approach is suitable for more incremental innovations that are aligned with the organization’s core competencies (Moore, 2007). Clients won’t be asking an organization to do something new in an area they do not yet have a reputation for and are unlikely willing to foot the bill and take all the risk to help the organization build completely new competencies. Therefore, the scope of innovations that can be developed through the reactive innovation process is limited. The second way of innovating for project-based organizations – proactive innovation – is by initiating innovation or new business development projects themselves. In such a project, the project-based organization describes, invests, develops and tests the innovation before selling it. Brady and Davies (2004, 1607) speak of business-led learning that emphasizes top-down strategic changes. In fact, this is the way in which most other companies innovate. In such an innovation project, the project-based organization develops a new product or service that it can sell to existing or new customers or apply internally if it concerns a process innovation. The main advantage of this approach is that it is a more proactive way of innovating because the project-based organization can take the initiative itself independently of its current client base and reputation. The solution can be aimed at the best target market and is not limited to

234  Handbook on innovation and project management

the needs of a single customer as in the reactive approach. Since the project-based organization has total control over these projects, it can give direction to the outcomes. As such, a proactive innovation project allows a project-based organization to address completely new customer groups and yet unmet needs of existing customers. It is the means to address disruptive innovations. The main disadvantages for the project-based organization are that proactive innovation activities are much riskier. What does not help, either, is that most project-based organizations lack the capabilities and infrastructure to make organization-wide investments. Such investments are never needed for the core business, in which no activities take place unless a client has agreed to pay for them. And while the project can target all clients in a particular market, the scale and scope will often still be relatively limited by the nature of the work involved. Even when services get automated, nearly always a human service component remains, as their human capital in the end is a core capability of these organizations. For these reasons, many project-based organizations stick with having a reactive innovation process only. In times of overcapacity, they tend to spend time and effort on more futureoriented, proactive innovation. In other cases, digital transformation and the need to have an innovative image to attract clients and talent have forced project-based organizations to venture into proactive innovation activities. But even then, many project-based organizations invest little in proactive innovation, and they don’t do it consistently. To optimize the outcomes of their innovation activities, project-based organizations need to operate a reactive process in response to explicit customer demands and foster a proactive process of defining and creating innovations. It is a challenge to bring these two processes in line with each other. The business units will often perform reactive innovation activities, whereas proactive innovation activities require a more centralized approach. Because of the strong decentralized nature of these organizations, conflicts can easily occur when it comes to priorities, budgets, allocation of resources and decision-making power, with inefficiencies and duplications in the innovation activities as a result. Coordinating the processes is even more challenging if the organization operates in different countries, which many project organizations do, since the innovation activities can take place in different countries too. As we will argue in the following, a central innovation manager can be a solution to these problems.

HOW TO MANAGE PROACTIVE INNOVATION PROJECTS How should project-based organizations manage and execute proactive innovation projects? How do they develop the new capabilities needed for proactive innovation (Brady and Davies, 2004)? Project-based organizations are usually organized around certain competencies, for instance, “tunnelling” and “road construction” in a project-based construction firm, and at the same time they are organized around certain customer segments, such as “government”, “offshore”, etc. Matrix structures are quite common in these kinds of organizations. In addition, these organizations may have supporting departments for marketing, purchasing, etc. This means that the traditional functional structure does not exist. In addition, employees in project-based organizations often work more autonomously than in other types of firms. Many employees have direct customer contacts, and they are used to organize projects, including collecting resources, themselves. All in all, activities are more distributed in project-based

Innovation in project-based organizations  235

organizations than in more functional or divisional companies. This distributed way of decision-making works because on all the operational projects, the client has the role of the budget owner, key decision-maker, quality controller and arbiter. It is worth noting here that the absence of the role of the client on proactive innovation projects creates numerous challenges for the management and execution of innovation projects. Blindenbach-Driessen and Van den Ende (2010) studied the success factors for innovation projects in project-based organizations. The question was whether the normal success factors, such as having cross-functional teams or a structured process, would also apply to proactive innovation projects in project-based organizations. We had to adapt our vocabulary; for instance, in the absence of functional departments we had to replace “cross-functional team” with “multidisciplinary team”. We compared functional firms (product and mass-service firms) with project-based organizations in the same industries and found that: 1. While cross-functional teams contribute to the performance of innovation projects in functional firms, multidisciplinary teams do not contribute to the success of proactive innovation projects in project-based organizations. Our explanation was that cross-functional teams serve to integrate knowledge from different functions, but that project-based organizations have little need for dedicated mechanisms to integrate knowledge because they are already used to doing so in their customer projects. So, it’s relatively easy to integrate knowledge in innovation projects, even if there is no multidisciplinary team. 2. A structured innovation process didn’t increase success in project-based organizations. Our explanation was that project-based organizations are used to a fairly strict way of organizing customer projects, and innovation projects need more flexible processes. So, the innovation processes they apply are too rigid, which does not contribute to success. For innovation, a structured innovation process is needed, but with some degree of flexibility (Lenfle, 2016; Markham and Lee, 2013, 419). 3. A heavyweight project manager, on the other hand, did have a positive influence on innovation projects in project-based organizations, and much more than in functional firms. This is because the project manager must bridge the default decision-making structures, cross organizational silos and have enough cloud to keep their project on the forefront against all the other pressing demands of external clients. In addition, the diffusion of innovation is a particularly difficult process in project-based organizations. You can’t just send the product to the factory, as in a product firm, or start the operations, such as in mass-service firms. In a project-based company, you always need other people to sell your innovation concept to the customer, or to apply the innovation to the processes. And a heavyweight project manager is better able to get other people committed. With respect to the second point, the innovation process, we can note that project-based organizations that today use agile, lean-start-up, and design thinking methodologies while serving their clients are at a distinct advantage when it comes to managing and executing innovation projects, as these are processes, tools and capabilities that they can also use for the execution of their proactive innovation projects. However, project-based organizations – like most construction firms – that use traditional project-management methodologies are at a clear disadvantage because the capabilities needed and used for operational projects that are characterized by relatively low levels of uncertainty are very different from those needed for often less complex but far more uncertain innovation projects. Using the traditional project

236  Handbook on innovation and project management

management process will lead to a lot of unnecessary planning and creates a false sense of certainty when used for highly uncertain innovation projects. The general lesson is that the application of management practices in innovation projects, such as cross-functional teams or heavyweight project managers, depends on the organizational context. As mentioned earlier, a project-based organization is a highly distributed organization, where people work autonomously in a matrix organization. In such a context, innovation projects must be managed differently than in a functional context. For instance, a highly mono-disciplinary project team may work fine in a project-based organization, since it is easy to acquire knowledge from other disciplines in the project context. The bottleneck comes later when the result of the project has to be commercialized. CASE: COORDINATION OF INNOVATION IN AN ENGINEERING COMPANY Engineering company WaterCo develops and manages hydraulic projects, infrastructure projects, chemical installation projects, etc., and operates in several countries, with different disciplinary units in each country. The company performs future-oriented research projects for customers, often government agencies, financed by those customers. Although the company develops new technologies in those projects, implementation on markets is often not guaranteed. To improve this process and facilitate implementation, a central new business development unit defines proactive innovation projects. As a result of those projects, the firm can make offerings to customers. However, employees have to perform these projects on top of their customer-oriented projects and with limited budgets. That means that these proactive innovation projects often get delayed. To improve these projects, the new business development unit appoints experienced project managers for each innovation project.

THE ROLE OF THE INNOVATION MANAGER Most product and mass-service firms have dedicated research, innovation and development teams. We single out the role of the innovation manager here because they can have an important role in project-based organizations. The innovation manager in a project-based organization has a challenging role when it comes to orchestrating the innovation activities that happen throughout the organization because of the distributed and knowledge-intensive nature of these organizations (Van den Ende, 2021, Chapter 7). An innovation manager does not operate on his or her own (Figure 12.1). An innovation manager coordinates the innovation and new business development activities in the organization, while business units perform the activities themselves. Depending on the size of the organization, the business units may have a department or team within the business unit for this purpose, or employees dispersed in the business unit may perform the innovation activities. The innovation manager may come up with ideas, select projects and organize portfolio management at the organization level. Most likely the business units will provide the resources for the innovation projects, but the innovation manager may have a budget for pilots. The innovation manager does not necessarily operate alone but may have a supporting team or unit. The innovation manager will usually report to top management.

Innovation in project-based organizations  237

Source:   Van den Ende, 2021, Chapter 7.

Figure 12.1  The role of the innovation manager The innovation manager in a project-based firm faces four challenges. First, the scalability of successful innovation projects is limited. The distributed nature of the organization makes that novel solutions and processes have a limited reach, and thus often a limited return on investment, at least initially. The reliance on human capital to differentiate from the competition further limits scalability. This means that it is challenging to create profit from the portfolio of innovation activities in a project-based organization. Second, the level of centralized control for any function is limited in project-based organizations. As a result, the coherence and speed of the innovation programme are also limited. Business units have annual revenue and profitability targets. They are focused on the short term and their priorities are not always in line with the strategic priorities of the organization at large. For instance, people in the business units do not always see the advantage of largescale operations, while management is likely to dictate to the innovation manager that the scale of activities is a priority to increase the return on their innovation investments. Third, since internal rates are lower than what external clients are paying, it is unattractive for the business unit to lend their most talented employees to an innovation effort. And when business units are not inclined to dedicate resources to innovation, it leads to a downward selffulfilling prophecy of failures, due to inadequate staffing and low speed in execution. Fourth, the profitability of the innovation function is highly dependent on the adoption by the business units over which it has no control. When a business unit has implemented the innovation only once or a few times, they may lose interest in it and return to their earlier activities, leaving the innovation in a loss-making condition. Because of the distributed nature

238  Handbook on innovation and project management

of these organizations, there is limited if any incentive for one business unit to assist other business units with the adoption of novel ways of working. An Alternative Option: A Separate Innovation Unit An alternative to the aforementioned innovation manager option is to create a separate unit. The literature calls this “structural” ambidexterity, while the option of the innovation manager can be labelled as “contextual ambidexterity” (Lavie et al., 2010; Raisch and Birkinshaw, 2008). Structural ambidexterity means that the organization sets radical explorative innovation activities apart in a separate unit to shield them from the demands of the operational units. The traditional R&D department in companies is an example of structural ambidexterity. Contextual ambidexterity means that the organization integrates explorative innovation activities in the operational units. As we mentioned earlier, most project-based organizations follow the contextual ambidexterity model, with the innovation manager facilitating the innovation activities that take place within the operational business units. The separate unit in a project-based organization would be tasked with developing proactively innovative solutions. The unit may either bring the innovative solution to the market itself or transfer it to a business unit for commercialization. One advantage of creating a separate innovation unit is that it can avoid the pressure of the business units’ focus on customer projects and today’s urgent issues. Another advantage is that in this separate function, the project management practices can be optimized to deal with innovation projects that are uncertain, full of ambiguity, prone to failure and require a new skill set (Benner and Tushman, 2003; Tushman and O’Reilly, 1996). The separate innovation unit can be used to ensure that innovation activities have the same urgency and a dedicated funding source and obtain the same status as the operational projects. That is, a separate innovation unit provides the advantage of an innovative culture and a test environment that is independent of the operational context. However, a separate unit in a project-based firm has considerable disadvantages. An important one is that the adoption of the resulting innovations by the parent organization is not a given. Also, the separate unit may lack sufficient access to the knowledge base of the organization, which is dispersed in the organization. Because of these disadvantages, few projectbased organizations have a separate innovation unit, and there are many examples in the literature of project-based organizations that create a separate unit at some point in time, to dissolve it after a few years again (Brady and Davies, 2004; Eccles et al., 2013).

INNOVATION IN LEGAL FIRMS – MAKING IT WORTHWHILE TO INNOVATE Just like other project-based organizations, law firms are distributed organizations that are good at executing reactive types of innovation. But most of them struggle with all forms of proactive innovations, whether it concerns the introduction of new offerings, the automation of business operations, the introduction of new revenue models, the implementation of legal tech, etc. Until recently, change in those areas was never necessary, since the market for these services was rather stable. But the coronavirus epidemic has accelerated the need for digital transformation and with that the need to be able to innovate more proactively.

Innovation in project-based organizations  239

Digitization requires more than making a form available online. It impacts the business model of a law firm and requires a significant time and cost investment to set up and implement these projects. Let’s take an innovation project that involves a customer portal: a website behind a login that makes it possible for clients to receive online services from a lawyer, paid or unpaid. It is often one of the most visible parts of a digital transformation strategy in legal firms, something that any innovation manager could suggest the firm invest in. Since it is not too difficult to imagine what such a portal should look like – a slightly more extensive version of the website, with valuable information for the customers, behind a login – the project gets the green light from management. Building such a portal is also not too difficult for the IT department. However, getting a consensus about the content is difficult. Lawyers are not used to having to collaborate. And in a decentralized organization like a law firm, it is unclear who decides what service will be put behind the paid wall. There is no clear hierarchical structure among the practice groups to make such decisions, the innovation manager does not have the authority to impose decisions and reward structures to compensate for such unbillable time are absent. And even in the case that the portal gets filled with valuable information from each practice group and is unveiled to existing customers with great fanfare, who will ensure the portal will become a business success? So, in most cases, such innovation projects in this type of company result in endless meetings where a lot gets discussed, but no progress or decisions are being made. As a result, most innovation projects don’t get anywhere and are a waste of time. To get better results, a different approach is needed (Blindenbach-Driessen, 2018), one that recognizes that proactive innovation projects need to be executed with the same rigour and expediency as projects for clients. The innovation process for proactive innovation projects needs to start with the future service. What problem should this client portal solve and for whom? What can the client currently not do and how big of an issue is that? And does that make it worth it to invest in this opportunity? Questions like this are typically answered in a business case that describes what the project entails and in which the costs and benefits are compared. However, for an innovation manager or dedicated innovation team, these are all near-impossible questions to answer without the support of the leaders of the practice groups. In the end, the practice groups and business units guard access to the firm’s clients. Who Should Do the Work? Who, then, should invest their time to create the business case? Senior associates and junior partners are ideally suited to drive proactive innovation projects. They have seen enough to know what good service entails and to know what is not going well in terms of knowledge and processes. Interviewing and speaking with clients and other departments within the firm will help them grow as leaders. Because their time is not cheap and they have revenue and profitability targets as part of the regular operations, each proactive innovation project must be worthwhile for the client, the office and the involved talent before anyone starts investing time. For the execution of these projects, these senior associates and junior partners are likely not heavyweight enough. In some cases, that gap can be filled by the innovation manager. Nevertheless, nearly always, a more senior partner will need to get involved to secure the successful execution of the project beyond the business case.

240  Handbook on innovation and project management

INNOVATION IN HEALTHCARE – THE ROLE OF THE PROFESSIONAL We can see the challenges of innovating in project-based firms in healthcare organizations. While healthcare organizations are generally labelled as professional service firms, the organization of their innovation activities is very much like project-based firms. We use this sector to showcase the role of the professional in the innovation process. Traditionally in most countries, healthcare is part of the public sector and not very innovative. The main topics of innovation are medical treatments, in which medical specialists aim to adapt their treatments to the most recent medical knowledge. Clayton Christensen would label such innovations as “sustaining” (Christensen, 1997) since they improve the services for customers on the traditional performance metric, which is the quality of treatments. Innovating communication with patients or creating new business models is disruptive because they break with the dominant trend in the sector. Because digital communication with patients has a lower quality than face-to-face communication, it can even mean a slight decrease in service quality. At the same time, such innovations can have advantages on other performance characteristics, such as ease for the patient, frequency of contact with the patient and cost for the hospital. Such disruptive innovations were unusual in healthcare organizations. Healthcare organizations did not perceive demand for such innovations either, as medical professionals had the monopoly over the knowledge and data needed for the latter types of innovations. Digital transformation and the pressure to reduce the costs of the excessively expensive medical sector have opened the door for alternative ways to deliver healthcare. In addition, patients are requiring higher service levels: for instance, in consultation hours and means of communication with the doctors. As a result, doctors and entrepreneurs have started specialist medical clinics, which focus on executing a limited set of treatments in a high-quality and cost-effective manner. Hospitals have started to invest in customer service, for instance by improving their customer scheduling systems. And, to reduce operating costs, non-specialized tasks are transferred from specialists to administrative or lower-educated medical personnel. However, these kinds of innovation processes in hospitals meet specific barriers. Hospitals are highly complex organizations, and risks for patients should be avoided at all costs. So, innovation and new business development activities will always have to go through rigorous tests or risk assessments before being implemented. Since physicians have a monopoly on the right to treat patients, it means that the professional identity of medical specialists can be a barrier, particularly for innovations that may affect their professional image. For instance, it appears to be hard to get specialists to communicate with patients by email or electronic device. Although such communication may be handy for patients and may give the option of providing more real-time monitoring of patients’ conditions, doctors often resist such changes since they consider them to decrease the quality of their communication and treatment. The COVID-19 crisis has changed their attitude with respect to online communication, but then it was for medical reasons, not because of the service level for customers. Reorganizing hospitals to create more specialist clinics for a limited set of treatments can meet substantive resistance since specialists consider that it diminishes their professionalism. And last, but not least, it can be difficult for tech start-ups, as non-medical providers, to bring their disruptive solutions to the market, as they need the assistance of a medical provider to get approval to test their solutions in practice. Project-based firms, such as IT solution providers, experience the same type of problem: professionals in those firms are more interested in developing high-tech

Innovation in project-based organizations  241

and high-quality solutions for existing customers than in disruptive business model innovations that may open new lower-quality but larger-volume markets. A stand-alone innovation unit could be the solution to these types of problems. However, as we mentioned earlier, this solution has disadvantages, among which is the lack of access to knowledge of employees in the business units. Therefore, members of such a separate unit will have to create strong networks with professionals in the rest of the organization to get support for their projects. An alternative is creating financial incentive systems for professionals to participate in proactive innovation projects.

CONCLUSION In this chapter, we discussed project-based organizations that need a more dispersed innovation and new business development process and organization. We saw that these organizations must be capable of executing both reactive client-driven innovation and proactive organization-driven innovation projects. Reactive client-driven innovation is the bread and butter of these organizations. Proactive innovation requires special processes, infrastructure and reward structures to make these projects happen successfully. In the current era of digital transformation, it is a must for project-based firms to also be able to successfully execute proactive innovation projects. We discussed success factors for proactive innovation projects in project-based organizations. Furthermore, we argued that an innovation manager will add much to the effectiveness of the innovation activities in project-based organizations. Finally, we discussed innovation in legal firms and healthcare organizations. We illustrated what needs to happen to make proactive innovation projects successful, using the example of legal firms. Lastly, we showed that the identity of medical specialists is an important driver for, but sometimes also a barrier to, innovation in healthcare institutions.

NOTE 1.

Part of this text is derived from Jan van den Ende, Innovation Management, Red Globe Press, an imprint of Bloomsbury Publishing Plc.

REFERENCES Benner, M.J. and Tushman, M.L. (2003). Exploitation, exploration and process management: The productivity dilemma revisited. Academy of Management Review, 28(2), 238–256. Blindenbach-Driessen, F. (2018). New service development for the professional services. In S. Gurtner, J. Spanjol, and A. Griffin (Eds.), Time commitment as the scarcest resource, Leveraging Constraints for Innovation – New Product Development Essentials from the PDMA (pp. 75–94). Hoboken, NJ: Wiley Publishing. Blindenbach-Driessen, F. and Van den Ende, J. (2010). Innovation management practices compared: The example of project-based firms. Journal of Product Innovation Management, 27(5), 705–724. Brady, T. and Davies, A. (2004). Building project capabilities: From exploratory to exploitative learning. Organization Studies, 25(9), 1601–1621. Christensen, C.M. (1997). The innovator’s dilemma. Harvard Business School Press.

242  Handbook on innovation and project management

Davies, A., Brady, T., Prencipe, A., and Hobday, M. (2011). Innovation in complex products and systems: Implications for project-based organizing. In G. Cattani, S. Ferriani, L. Frederiksen, and F. Taube (Eds.), Project-based organizing and strategic management (Advances in Strategic Management, Vol. 28, pp. 3–26). Bingley: Emerald Group Publishing Limited. Eccles, R.G., Naraandas, D., and Rossano, P. (2013). Innovation at the Boston Consulting Group. Harvard Business School, Teaching Case 9-313-137. Gann, D.M. and Salter, A.J. (2000). Innovation in project-based, service-enhanced firms: The construction of complex products and systems. Research Policy, 29(7–8), 955–972. Hobday, M. (2000). The project-based organisation: an ideal form for managing complex products and systems? Research Policy, 29, 871–893. Lavie, D., Stettner, U., and Tushman, M.L. (2010). Exploration and exploitation within and across organizations. Academy of Management Annals, 4, 109–155. Lenfle, S. (2016). Floating in space? On the strangeness of exploratory projects. Project Management Journal, 47(2), 47–61. Markham, S.K. and Lee, H. (2013). Product development and management association’s 2012 comparative performance assessment study. Journal of Product Innovation Management, 30(3), 408–429. Moore, G.A. (2005). Strategy and your stronger hand. Harvard Business Review, December, 62–69. Moore, G.A. (2007). To succeed in the long term, focus on the middle term. Harvard Business Review, July–August, 84–90. Raisch, S. and Birkinshaw, J. (2008). Organizational ambidexterity: Antecedents, outcomes and moderators. Journal of Management, 34, 375–409. Tushman, M.L. and O’Reilly, C.A. (1996). Ambidextrous organizations: Managing evolutionary and revolutionary change. California Management Review, 38, 8–30. Van den Ende, J. (2021). Innovation management. Red Globe Press, Macmillan/Bloomsbury.

PART III IMPORTING AND CROSS-FERTILIZING

13. Collaboration and trust in innovative projects Niels Noorderhaven

INTRODUCTION: THE PROBLEM OF COLLABORATION IN PROJECTS Innovative activities are very often organized in temporary organizational forms, such as research and development projects or new product development projects. This makes sense, as such activities are different from organizational activities that are governed by more permanent routines and procedures (Obstfeld, 2012). For the sake of brevity, I will in the remainder of this chapter refer to all forms of temporary organizations as “projects”. Self-evidently, projects are distinguished from permanent forms of organization most of all by their temporariness. Even though some projects may have a lifetime of decades, their essential defining characteristic is that they will terminate at a predetermined point in time, when a particular task has been performed or when project principals decide that the planned outcome will not be realized or is not desirable anymore (Bakker et al., 2016). A second important characteristic of projects, which is strongly connected to temporariness, is their uniqueness, compared to the repetitiveness of activities of permanent organizations (Whitley, 2006). One important corollary of this condition is that the configuration of project participants often is also unique, in that these have not earlier worked together in the same composition. Although projects can also be vehicles for sets of activities that are relatively routine (Bygballe et al., 2021), I will focus in this chapter on “innovative projects”, i.e. projects for the execution of new and/or unique activities. Innovative projects bring together actors (individuals and/or organizations) in particular configurations for a limited period of time and for a unique set of tasks. In such situations, contributions cannot be specified in advance in any detail, and much emphasis is on creativity and idea generation (Malhotra et al., 2001). This has important ramifications for the organization of collaboration. The mostly strictly limited amount of time available for project execution and the uniqueness of the task create significant uncertainty, and the professional field of project management has developed procedures to ascertain predictability and control in spite of this uncertainty. This ongoing endeavour is embodied in the Project Management Body of Knowledge (PMBOK), a repository of knowledge continuously updated by the Project Management Institute.1 The PMBOK brings together procedures and techniques for managing in particular the scope, time and cost dimensions of a project, and in this way offers a framework for the organization of collaboration. For instance, in scope management, the work breakdown structure has a central position. The work breakdown structure divides the totality of activities to be performed into smaller, coherent tasks that can be assigned to a particular individual or organizational unit. Connected to each task is also a step-by-step time planning and an overview of necessary resources and their cost. Taken together, these inputs form a strong basis for collaboration in the project, for if every party involved performs the tasks assigned to them, successful project completion in principle should be assured. 244

Collaboration and trust in innovative projects  245

However, in innovative projects, it is impossible to completely plan activities in advance and to stick to that planning, as too many factors are unknown, uncertain or unforeseeable. Hence, improvisation will be necessary. Improvisation in the context of project management involves spontaneous efforts to find a solution for an unexpected circumstance or problem, taking a distance from the structured project management process (Malucelli et  al., 2019). This requires trust and collaboration between project participants (McGinn and Keros, 2002). Moving outside of the formal project management structures implies a leap of faith, and trust gives project participants the confidence to make this leap. The problem, however, is that the defining characteristics of projects are likely to impede the development of trust between project partners. As I will discuss in more detail in the following, the limited duration of projects hampers the accumulation of direct experience in collaborating with the project partners, while the uniqueness of the task and the project participant configuration makes it also less likely that participants know each other from previous collaborations. In this chapter, I will explore how trust can nevertheless arise in the context of a project, and how such trust can stimulate the achievement of positive project outcomes by enabling collaboration between project participants. Trust as discussed in this chapter can pertain both to the relationships within the project team, and those between the project team and the project principals. The latter can be higher managers, but also organizations, in the case of an inter-organizational project. Hence for the discussion in this chapter, both interpersonal and inter-organizational trust is relevant. Below I will first discuss the concept of trust, the different types of trust that can be distinguished, the different sources of trust, and how trust can be formed in and around ephemeral organizational forms like projects. Subsequently, I will consider the consequences of trust in the context of projects. How does trust influence collaborative behaviours and processes within projects, and how do these in turn influence project outcomes? Finally, I will discuss structural and processual measures for stimulating the build-up of trust in projects. In the concluding section, I will briefly summarize the main conclusions of the chapter.

THE MANY FACETS OF TRUST Definitions of trust abound, and I will conform to the most frequently used one, by Mayer, Davis and Schoorman (1995, 712): the willingness of a party to be vulnerable to the action of another party based on the expectation that the other will perform a particular action important to the trustor, irrespective of the ability to monitor or control that other party.

Trust is meaningful only in the context of risk or uncertainty (Nooteboom, 1996). If the actions of the other party can be perfectly predicted, or if there is no chance of negative consequences, trust becomes irrelevant. Essential in the definition of trust is that the trustor, with a view on a desired outcome, takes a risk by betting on the positive behaviours of the other party, the trustee, on the basis of the expectation that the trustee will not exploit the vulnerability of the trustor if the opportunity to do so would arise. Some advantages of trust are that it facilitates knowledge exchange (Uzzi, 1997), reduces transaction costs (Dyer and Chu, 2003), decreases conflict (Zaheer et al., 1998), facilitates mutual understanding (Nooteboom et al., 1997) and

246  Handbook on innovation and project management

more generally increases efficiency, productivity and financial performance (Krishnan et al., 2006; Zaheer et al., 1998). Generally, we can distinguish between three types of trust in terms of what is trusted: competence trust, integrity trust and benevolence trust (Mayer et al., 1995). All three types can be important for the outcomes of innovative projects. Competence trust refers to the trustor’s expectation that the trustee has the ability to fulfil an agreed task (Das and Teng, 2001). Integrity trust concerns the trustor’s expectation that the trustee has the intention to fulfil the task (Nooteboom, 2002). Integrity trust is based on the perception that the trustee accepts moral obligations and has concern for the trustor’s interests (Das and Teng, 2001). Benevolence trust, finally, refers to the extent to which the trustor believes that the trustee wants to do good to the trustor, aside from egocentric motives (Mayer et al., 1995). In business situations this third type of trust is less likely to play a central role (Connelly et al., 2018), hence we will not further discuss this type of trust here. Apart from these three types of trust, we can also distinguish between sources of trust (why does the trustor trust the trustee?). The first important distinction to make is between reflective and presumptive bases for trust (Marková et al., 2008). As the labels suggest, in the case of reflective trust the trustor decides to trust on the basis of some degree of deliberation, e.g. I have worked with the other party before, and I have good experiences, so I trust him or her. With presumptive trust, in contrast, the trustworthiness of the other is taken for granted, and the trustor puts himself in a vulnerable position without deliberation. Presumptive trust also has a dispositional element, as some individuals are more inclined to trust than others (Kramer, 1999). Reflective trust and presumptive trust can be based on different sources. Starting with reflective trust, i.e. the kind of trust that is relatively deliberate, this could be based on specific characteristics of the other party (this is a person or an organization that can be trusted), characteristics of the relationship (the other party may not necessarily be trustworthy in general, but is in this relationship, for instance, because it is not in his or her interest to act in an untrustworthy way) or characteristics of the environment (for instance, there are adequate legal safeguards). Calculative trust is based on the assumption that it would not be in the interest of the other party to violate trust expectations (Lewicki and Bunker, 1996). Reputation can play a role in this: if the other party has built a strong reputation, it will not want to put that at risk by betrayal in a single relationship. Reflective trust can also be based on direct experiences in interactions with the other party. Such knowledge-based trust distinguishes between partners who are more trustworthy (because we know them and have good experiences) and all others, of whose trustworthiness we have no knowledge (Lewicki and Bunker, 1996). Presumptive trust can be based on the trustor’s innate disposition to trust individuals and/or organizations, a characteristic that also varies between cultures (Ferrin and Gillespie, 2010). It can also be based on the membership of the trusted party of a particular category (Kramer, 1999), for instance, a particular professional group (Bechky, 2006). This is often called category-based trust (Ertug et al., 2013). Presumptive trust can also be institutionalized if, in a particular sector or profession, the trustworthiness of actors is taken for granted (Baier, 1986). This is strongly related to the existence of expectations regarding the behaviours and skills connected to a particular institutionalized role. For the issue of trust in projects it is important to note that while some sources of trust, like experience-based or knowledge-based trust, take time to be built, other sources can lead to more or less instantaneous trust between participants in a project (McKnight et al., 1998). A

Collaboration and trust in innovative projects  247

phenomenon that has been described in this context is that of “swift trust” (Meyerson et al., 1996), i.e. trust that instantaneously arises in a project, even if the project participants are strangers to each other. Such swift trust cannot be based on any direct experience regarding the trustworthiness of the project participants, but can instead be rooted in mutual expectations connected to institutionalized roles or a well-functioning reputation system (Meyerson et al., 1996). Work on swift trust has identified clear and institutionalized roles as an important source of trust in projects. This has for instance been found in the construction sector, where project participants place trust not so much because of previous experiences with each other, but on the basis of the expectation that the institutional environment (e.g. educational system, system of job qualifications, etc.) will ensure that other project participants will be able to competently fulfil their roles (Kadefors, 1995). While this may be true in a sector like construction, where the level of innovation is not very high, reliance on prescribed role fulfilment is likely to be insufficient for projects of a more open-ended nature and requiring more creativity (Blomqvist and Cook, 2018). Moreover, institutionalized roles may offer sufficient ground for competence trust, but this still leaves open the question of how project participants can have integrity trust. One possibility is reputation, especially in relatively close-knit contexts where news regarding someone’s lack of reliability travels fast (Meyerson et al., 1996). The relatively strong emphasis on competence trust in projects may also be due to the by-definition restricted time available in a project, which leads to a strong focus on the task at hand (Meyerson et al., 1996). Nevertheless, Blomqvist and Cook (2018) on the basis of a review of the literature conclude that the establishment of interpersonal relationships still is important in projects. Finally, trust in the context of projects can be interpersonal trust (between individuals participating in the project) and inter-organizational trust (in the case of a project between organizations, as in a consortium for the construction of a large infrastructure project). There is much more research into interpersonal trust than into inter-organizational trust. As a result, there is much that we do not know, although there are indications that in relations between organizations, interpersonal and inter-organizational trust are related but distinct constructs that impact differentially on processes like negotiation and conflict (Zaheer et al., 1998). On the other hand, there are also indications that practitioners do not actually make much difference and treat trust in an organization and in its representatives as equivalents (Laan et al., 2011). In the following discussions, we will therefore not differentiate between trust between organizations and between individuals involved in a project. In practice, trust in innovative projects will be characterized by combinations of types and sources of trust, with the mix differing between situations and conditions (Lewis and Weigert, 1985). At this point, it is also useful to mention that trust cannot be assumed to be universally beneficial for project outcomes. Trust can make a party vulnerable to exploitation, or lackadaisical where a more proactive and vigilant attitude would be better. Overreliance on trusted partners can also hinder innovation if opportunities to cooperate with others who could deliver new insights are neglected (Krishnan et al., 2006). This makes attention to the sources of trust in project contexts, and the soundness of these sources, an issue of considerable practical importance. Before going into the question of how the level and basis of trust at the start of an innovative project can be influenced, I will in the next section discuss how trust can lead to positive project outcomes through its influence on the collaborative behaviours of project participants.

248  Handbook on innovation and project management

TRUST AND COLLABORATION IN INNOVATIVE PROJECTS The aim of this chapter is to explore the interrelations between trust, collaborative behaviours in innovative projects and the outcomes of these projects. I have already briefly summarized some key aspects of trust. In this section, I will articulate collaborative behaviours. Collaboration can be seen as an umbrella concept, distinguishing a broad class of behaviours from other behaviours (non-collaborative and competitive behaviours). Digging a bit deeper, collaboration can be seen as encompassing two distinctive behavioural categories: coordination and cooperation (Gulati et al., 2012). Coordination in turn can be defined as “the deliberate and orderly alignment or adjustment of partners’ actions to achieve jointly determined goals” and cooperation as the “joint pursuit of agreed-on goal(s) in a manner corresponding to a shared understanding about contributions and pay offs” (Gulati et al., 2012, 537 and 533, respectively). These definitions are not very informative about the behaviours constituting coordination and cooperation, however. I will first unpack these two categories, before making the link with trust. Coordination is a key topic in organizational theorizing and focuses on how task interdependencies can be managed. At a high level of abstraction, a distinction can be made between formal and informal coordination mechanisms. The structural approach as prescribed by the PMBOK is clearly an example of the first and an improvisation of the latter. Other elements of coordination are task decomposition, allocation of jobs, pooling of resources and communication (Castañer and Oliveira, 2020). Mintzberg’s (1980) influential framework makes a more refined distinction between mutual adjustment, direct supervision and three types of standardization: that of work processes, of outputs and of skills. Of these, mutual adjustment and standardization of skills can be seen as belonging to the informal category. Mutual adjustment consists of the informal coordination of work between project participants. Standardization of skills allows for informal coordination because it makes formal coordination superfluous. The other three types are on the formal side, with standardization of work processes and outputs being strongly reminiscent of the prescriptions of the PMBOK. Although cooperation is doubtlessly a key factor in organizing, this concept has been less articulated in the literature. In a review article, Castañer and Oliveira (2020) sum up a number of behaviours mentioned in the literature, including joint activities, the pursuit of mutual gain or interests and common benefits. Based on the sociological literature on cooperation, Tjosvold (1984) distinguishes four types of cooperative behaviour: assistance behaviours, communication behaviours, task accomplishment behaviours and friendliness and support behaviours. This is conceptually close to the project citizenship behaviours described by Braun, Ferreira and Sydow (2013): helping behaviour, loyalty to the project goals, compliance with projectbased rules, individual initiative and relationship maintenance. Cooperation outcomes are typically described in terms of task performance and of satisfaction of the participants (Smith et al., 1995), and similarly, it seems natural to divide the cooperative behaviours into two types: task-oriented (assistance, task accomplishment and communication) and relationship-oriented (friendliness and support behaviours and, again, communication). Communication fits both categories as it can be geared to task performance (e.g. providing necessary information for the other participant to do his or her task) or to the relationship (e.g. small talk to strengthen the emotional bond between participants). Both task-oriented and relationship-oriented cooperation behaviours are likely to be necessary to make innovative projects successful.

Collaboration and trust in innovative projects  249

How is trust related to project coordination and cooperation behaviours? Three preliminary remarks are in order. First, relationships between types of trust and project collaboration behaviours are complex and likely to be bidirectional. For instance, whereas a high level of trust can accommodate cooperative behaviours, cooperative behaviours can in turn also increase the level of trust in a relationship (McAllister, 1995). Second, the literature on the relations between types of trust and forms of collaboration is fragmented and incomplete, hence the following discussion will partly be based on plausible speculation rather than empirical evidence. Third, the distinctions between collaboration, cooperation and coordination elaborated earlier are not made in any precise way in most of the literature. Having said this, there seems to be little doubt that trust is strongly related to collaboration (Smith et al., 1995). Various studies have established relations between trust and collaboration, in general (Chiocchio et al., 2011), or regarding specific types of trust (Zhang et al., 2018) and/ or elements of collaboration (Paul et al., 2016). Likewise, the relationship between trust and collaboration on the one hand and project outcomes on the other has also been documented extensively. This is true for project performance in general (Cheng et al., 2021; Strahorn et al., 2017), as well as for outcomes specifically related to innovation, like knowledge sharing and exploration (Arranz and de Arroyabe, 2012; Bond-Barnard et al., 2018; Buvik and Tvedt, 2017; Nygaard and Russo, 2008). At the level of the project team trust is also important because it promotes psychological safety, i.e. a group climate in which “people feel free to express relevant thoughts and feelings” (Edmondson, 2012, 118). Psychological safety is especially important in innovative projects because it provides room for unconventional ideas and innovative proposals. A study of project teams in the ICT and pharmaceutical industries found that psychological safety was positively associated with both exploitative and exploratory learning by the team (Kostopoulos and Bozionelos, 2011). These findings and observations make sense and are not very surprising. Whereas a more fine-grained understanding of the relationships between types of trust and elements of collaboration would be helpful, the literature as yet does not offer much guidance in this respect. Consequently, the following discussion will be speculative. Distinguishing between competence-based trust and integrity-based trust, it is clear that while both may be conducive for coordination within projects, this is not equally the case for all forms of coordination. Starting with competence trust, this type of trust is particularly important for the coordination mechanism of standardization of skills, whereas standardization of processes and of outputs can be seen as a substitute for competence trust. This is also reflected in criticism of the PMBOK, which can be seen as striving for the latter two types of standardization (Hodgson and Cicmil, 2007). For mutual adjustment and direct supervision to be effective, competence trust should also be above a certain threshold. Integrity trust is particularly relevant for mutual adjustment, as a voluntary adaptation generally implies ceding some advantage for oneself, often in the expectation that the other party will do the same if necessary (see Ligthart et al., 2016). Integrity trust can also be expected to be important for direct supervision, for if a project leader is not believed to act in an ethical way, the effectiveness of this coordination mechanism is undermined (Bhatti et  al., 2021). Finally, integrity trust is also important for coordination on the basis of standardization of skills, as parties should be confident that the freedom that this type of coordination gives to skilled professionals will not be abused. Integrity trust is not important for the standardization of processes or of outputs, in contrast.

250  Handbook on innovation and project management

Turning now to the elements of cooperation, two of these, offering assistance in general and, more specifically, helping others in their task accomplishment, can be expected to require a significant level of both competence and integrity trust to be effective. The other two elements of cooperation, communication and friendliness and support, are relationship-oriented, and these will require some level of integrity trust, while competence trust seems less relevant. The upshot of this brief discussion is that both competence trust and integrity trust are important for collaboration, but not each type of trust equally so for all elements of collaboration. The foregoing discussion has implicitly assumed project participants who are co-located and can engage in direct interactions. However, projects increasingly become virtual, with participants located in different geographical regions and time zones. The dynamics of virtual project teams merit an in-depth discussion that goes beyond the confines of this chapter, but a few remarks are in place. First of all, studies suggest that in virtual projects intensive communication is even more important than in face-to-face projects (Zakaria and Yusof, 2020). This constitutes a challenge because of the more restricted communication modalities available to virtual project teams, as well as the restrictions to synchronous communication because of members being in different time zones. Maybe for this reason, sources of trust like reputation, institutions and calculation tend to be relatively important in such projects (Cheng et al., 2021). Secondly, there are some indications that behavioural controls are just as or even more important in virtual projects in order to establish clear expectations and avoid misunderstandings (Lukić and Vracar, 2018). At the same time, these control mechanisms may undermine trust, as they heighten vigilance and make it more likely that shortfalls, even if small, are detected (Piccoli and Ives, 2003). This is of course also the case in face-to-face projects, but in these circumstances, it is easier to smoothen small task-related conflicts through intensive informal communication. Thus the balance between maintaining good relationships and maintaining sufficient control could be disturbed more easily in virtual projects. I will now turn to a question of great practical importance: how can both forms of trust be promoted in projects, especially in non-routine, innovation-oriented projects?

HOW CAN TRUST FORMATION BE PROMOTED IN INNOVATIVE PROJECTS? Given the importance of trust for collaboration in projects, and ultimately also for the outcomes of these projects, it is important to know how the level of trust in a project can be increased. In the following, I will discuss two categories of measures that project managers can engage in: structural measures and process measures. Although I will discuss them separately, it is important to note that in practical situations the two categories are overlapping. Starting with structural measures, a number of these have already been mentioned when discussing sources of trust in projects. First of all, having standardized roles and skill sets is a powerful factor in promoting swift trust in projects. However, this is often not something that can be arranged at the project level but depends on formal and informal arrangements at the sectoral level, or even across sectors, for multiple domains of project organizing. The work of the Project Management Institute and the promulgation of the PMBOK can be seen as an example of this. In spite of such work, standardization in project-based industries like construction and engineering remains a challenge (Choi et al., 2021). This is not only true at the level of the industry but also within project-based organizations. Bresnen et  al. (2004)

Collaboration and trust in innovative projects  251

describe the efforts of a UK construction firm to introduce a standardized project management system, which largely failed because of resistance from project managers. Nevertheless, role clarity has been shown to play an important role in the emergence of swift trust in project teams (Curnin et al., 2015). If all participants know their own roles and those of the others, and each knows how to enact these roles, trust can arise in a project team quasi-immediately. However, this does not mean that it is impossible to implement structural measures to stimulate trust in projects at the organizational level. Valentine and Edmondson (2015), while not studying trust, provide some important clues. These authors describe how three types of “team scaffolds”, boundaries between team members and others, clear role sets and collective responsibility, enabled employees who worked together for just a single shift to start working as a team immediately. The boundaries between teams functioned in spite of the lack of continuity of team membership and led to the formation of a clear in-group for the duration of the work shift. The standardized role sets (also defining the skills necessary for a given role) enabled the team members to cooperate on a “plug-and-play” basis. Obviously, this is related to the standardization strategy discussed earlier. The fact that this was not met with resistance is probably because Valentine and Edmondson’s case focused on the emergency department of a hospital, an environment in which skill and role standards are already very strong. Finally, giving a team collective responsibility for the outcomes is a powerful trigger for collaboration. Specifically, these “team scaffolds” enabled teams to prioritize mutual efforts, continuously communicate, help each other and hold each other accountable for outcomes. Such a kind of setup could also be expected to function for project work and to induce both collaboration and trust. In the preceding example, one of the major impediments to collaboration, overcome through “team scaffolds”, was the discontinuity of group membership. While in some situations this may be unavoidable, very often it is a variable that managers can manipulate. In the project literature the metaphors of “shadow of the past” and “shadow of the future” are employed to indicate that although a project may be temporary, actors in the project may have worked with one another in the past, and/or may expect to do so again in the future (Ligthart et al., 2016). In such cases, we can say that project participants (whether individuals or organizations) are embedded in a network of latent ties, which can be activated at any moment in the future in the form of participation in a new project (like in the production of television programmes; Starkey et al., 2000). Having worked together on previous projects may expedite trust formation in a new project in various ways. On the basis of a case study in the construction industry, Buvik and Rolfsen (2015) identify four mechanisms. Previous experience helps project participants to develop integrative work practices early in the project, helps them to form a common project philosophy, promotes open communication and contributes to clear role expectations. In other words, the initial experience-based trust can be augmented further in the new project. If the parties in a project have worked together in previous projects, experience-based trust may already be present at the start of the focal project, enabling smooth collaboration. However, in the context of an innovative project, characterized by little routine and repetition and a relatively unique task, it is less likely that experience-based trust is present a priori, and it will be difficult to establish such trust in the project given its limited duration. In this situation, the expectation of working again together on future projects can still induce a calculative form of trust. This “shadow of the future” discourages untrustworthy behaviour in the present project by increasing participants’ willingness to make short-term sacrifices in order to realize long-term benefits (Klein Woolthuis et al., 2005). This is a form of calculus-based trust, where

252  Handbook on innovation and project management

project participants make efforts to conform to expectations to increase the chance of being selected for future projects. Thus managers should take into account that projects are not purely stand-alone phenomena (Engwall, 2003), and make most of the effects of the shadows of the past and the future, e.g. by selecting project participants (individuals or organizations) that have worked together successfully in the past or by promising new project participation in the future if the present project is successful (see e.g. Maurer, 2010). Apart from the structural measures discussed earlier, there are also more processual measures. First of all, research emphasizes the importance of intensive interaction and communication for trust and collaboration in projects. Frequent interaction and communication are key, especially early in a project (Blomqvist and Cook, 2018; Bstieler, 2006). The communication can be about the content of the project and the tasks involved, but sharing personal information at the beginning of a project is also related to the formation of trust (Jarvenpaa and Leidner, 1998). Apart from interaction and communication, project participants may also make small gestures that signal goodwill, like relinquishing compensation for additional hours of work, which, when reciprocated, may lead to spiralling levels of trust within a project (Swärd, 2016). A case study of a construction project alliance by Laan et al. (2011) further illustrates how trust can be built through social interactions in a project. Two interrelated elements are particularly salient in this case study: the importance of physical proximity of project participants and the importance of transparency. The first element accommodates the second, as illustrated by the following quote from a representative of the client organization: “You need to see how your opponent, your opponent of the past, operates. That is what makes trust grow, seeing what position people take’’ (2011, 105). The importance of physical proximity for building trust underlines that virtual project teams face particular challenges, as discussed in the third section. Particular behaviours, especially leadership behaviours, are also associated with the emergence of trust and psychological safety in project teams. Edmondson (2012, 135–145) discusses a number of leadership behaviours that promote psychological safety, including the accessibility of the leader and treating failures as learning opportunities, while at the same time holding participants accountable for transgressions of agreed norms regarding task accomplishment. This is also very relevant in the context of project management, where the emphasis may often be on accountability without offering the necessary countervailing psychological safety. Finally, the literature also demonstrates that rituals and symbols can play a role in forming trust between project participants. An example of a ritual is the project kick-off meeting. Such a kick-off meeting, which in the case of infrastructure projects is often open to stakeholders in the environment, like local residents, and serves multiple purposes. Externally, it engages various groups of stakeholders and legitimizes the project plan. Internally, it marks a “point of no return”, which can help to strengthen the bond between project participants, who now have become collectively responsible for bringing the project to a good ending (Van de Ende and Van Marrewijk, 2018). Intensive communication and interaction as well as rituals are likely to strengthen the identification of the participants with the project, and with this mutual trust and collaboration. Hence, these are things that project managers need to plan for and take seriously. An example of a symbol that can play a role in creating trust in a project is provided by Livne-Tarandach and Jazaieri (2020). Although the context of this study is somewhat atypical (a temporary organization for the management of a summer camp), the mechanism that these authors describe has more general relevance. Livne-Tarandach and Jazaieri (2020, 5) describe how in the summer camp a “swift sense of community” arose, defined as “a state

Collaboration and trust in innovative projects  253

of felt inclusion, joint responsibility for members’ well-being and needs experienced within a group of people through the seeding and rapid amplification of experiences of momentary positive regard and widespread sense of influence”. Described in this way, it is clear that a swift sense of community is strongly related to the concept of “swift trust”, discussed earlier. In the process of forming a sense of community, the use of a mundane artefact (a bread tag) as a symbol of bonding between participants plays a role in starting a process of spiralling sense of community. It is not so hard to imagine that all kinds of artefacts, like coffee mugs or mousepads, could play such a community-enhancing role within a project. Whereas we have seen that standardized roles and skill sets are structural characteristics that help trust to arise quickly (or even instantaneously) within a project, research by Bechky (2006) shows that this structural mechanism may need to be complemented by processual means. In the film projects studied by Bechky, these took the form of frequent and enthusiastic expressions of praise for a role well executed, as well as polite admonishing when this was not completely the case. A third type of process identified by Becky was role-oriented joking: [H]umor allowed for expectations and understanding of roles to be displayed in a less direct, and possibly less threatening, way. It also furnished crew members with a means for role distancing; humor was a safety valve that enabled them to complain about their role constraints while still enacting roles appropriately and accomplishing their work. (Bechky, 2006, 12)

While Bechky does not study trust, it is clear that thanking, admonishing and joking all reinforced the functioning of role expectations, and hence indirectly also the trust between project participants based on these. This demonstrates the importance of frequent friendly feedback on role fulfilment between project participants for stimulating trust.

CONCLUSIONS In this chapter, I have discussed the relationships between trust and collaboration in the context of projects. Projects, especially those that are of an innovative nature, are inherently uncertain. The normative theory of project management, as embodied in the PMBOK, aims to reduce this uncertainty by means of a variety of control mechanisms, but this can never be fully effective, hence some degree of improvised collaboration will be necessary. In this context, trust is important because it fosters collaboration, just like it is promoted by collaboration in a positive cycle. Looking at the concept of trust, a number of useful distinctions can be made. One of these is the distinction between trust in the other party’s competence versus his or her integrity. Another dimension in which trust can be articulated is the basis on which it is grounded, like direct experience, reputation, the membership of the other in a particular category of actors or institutional arrangements in the environment. Some of these can also be assumed to be effective in the context of projects, but others much less so, in particular those that need time to develop (like direct experience). Trust and collaboration are strongly interconnected, so it is difficult to say which of the two comes first. Rather, they are mutually reinforcing and together can form a positive spiralling effect on processes and outcomes of projects. Although both competence-based and integritybased trust is important in projects, the extent to which these two are connected to various aspects of coordination and cooperation (the two components of collaboration) differs.

254  Handbook on innovation and project management

Finally, how can managers in or around projects stimulate trust? A number of structural and processual measures are available, each of which targets one or more of the sources of trust discussed in the chapter. Structural measures can for instance aim at establishing clear standardized roles and skill sets. The disadvantage is that this often needs to be done at the level of the sector or industry, something on which an individual project or organization has little influence. Other structural measures aim at increasing the temporal embeddedness of the project. This can be done by strengthening the “shadow of the past”, by selecting project participants with whom one has worked successfully in the past. The other option is to create a “shadow of the future” by creating the perspective of working again with the same project participants in the future. This will promote both trust and collaborative behaviours in the present project. Processual measures are for instance the deliberate promotion of intensive communication and interaction, especially early in the project. These interactions can include reciprocation of small positive gestures, helping to set off a spiral of trust. Furthermore, rituals and symbols can be used to create a sense of community within a project, which will also promote trust and collaboration. While this chapter offers an overview of what the literatures on trust and projects teach us, it is also clear that there is much that we still do not know. Gaps in academic knowledge are serious and need to be filled by conducting more studies. But even the limited insights that research has generated seem to have had little influence on practitioners. A phenomenological study among construction project practitioners concluded that “little understanding was evident regarding methods for building and maintaining trust, nor for repairing trust when problems arose” (Strahorn et al., 2017, 1). If this observation is representative, it is clear that much work is needed also in terms of knowledge dissemination. For Further Reading •

Kenis, P., Janowicz, M., and Cambré, B. (Eds.). (2009). Temporary organizations: Prevalence, logic and effectiveness. Edward Elgar Publishing.

This book is a good introduction to many aspects of project organization. • •

Chiocchio, F., Kelloway, E.K., and Hobbs, B. (Eds.). (2015). The psychology and management of project teams. Oxford University Press. Mann, L. (2005). Leadership, management, and innovation in R&D project teams. Westport, CT: Praeger Publishers.

These two books focus on behavioural aspects of project management. • •

Marková, I. and Gillespie, A. (Eds.). (2008). Trust and distrust: Sociocultural perspectives. Charlotte, NC: Information Age Publishing. Nooteboom, B. (2002). Trust: Forms, foundations, functions, failures and figures. Cheltenham and Northhampton, MA: Edward Elgar Publishing.

These two books are good introductions to the concept of trust and also cover many applications. No specific attention to trust in projects.

Collaboration and trust in innovative projects  255

NOTE 1.

www​.pmi​.org​/pmbok​-guide​-standards (retrieved on 5 April 2021).

REFERENCES Arranz, N. and De Arroyabe, J.F. (2012). Effect of formal contracts, relational norms and trust on performance of joint research and development projects. British Journal of Management, 23(4), 575–588. Baier, A. (1986). Trust and antitrust. Ethics, 96(2), 231–260. Bakker, R.M., DeFillippi, R.J., Schwab, A., and Sydow, J. (2016). Temporary organizing: Promises, processes, problems. Organization Studies, 37(12), 1703–1719. Bechky, B.A. (2006). Gaffers, gofers, and grips: Role-based coordination in temporary organizations. Organization Science, 17(1), 3–21. Bhatti, S.H., Kiyani, S.K., Dust, S.B., and Zakariya, R. (2021). The impact of ethical leadership on project success: The mediating role of trust and knowledge sharing. International Journal of Managing Projects in Business, 14(4), 982–998. Blomqvist, K. and Cook, K.S. (2018). Swift trust - State-of-the-art and future research directions. In Searle, R.H.A. Nienaber, and S. Sitkin (Eds.), The Routledge companion to trust (pp. 29–49). Abingdon and New York: Routledge. Bond-Barnard, T.J., Fletcher, L., and Steyn, H. (2018). Linking trust and collaboration in project teams to project management success. International Journal of Managing Projects in Business, 11(2), 432–457. Braun, T., Ferreira, A.I., and Sydow, J. (2013). Citizenship behavior and effectiveness in temporary organizations. International Journal of Project Management, 31(6), 862–876. Bresnen, M., Goussevskaia, A., and Swan, J. (2004). Embedding new management knowledge in project-based organizations. Organization Studies, 25(9), 1535–1555. Bstieler, L. (2006). Trust formation in collaborative new product development. Journal of Product Innovation Management, 23(1), 56–72. Buvik, M.P. and Rolfsen, M. (2015). Prior ties and trust development in project teams–A case study from the construction industry. International Journal of Project Management, 33(7), 1484–1494. Buvik, M.P. and Tvedt, S.D. (2017). The influence of project commitment and team commitment on the relationship between trust and knowledge sharing in project teams. Project Management Journal, 48(2), 5–21. Bygballe, L.E., Swärd, A., and Vaagaasar, A.L. (2021). A Routine Dynamics Lens on the StabilityChange Dilemma in Project-Based Organizations. Project Management Journal, 52(3), 278–286. Castañer, X. and Oliveira, N. (2020). Collaboration, coordination, and cooperation among organizations: Establishing the distinctive meanings of these terms through a systematic literature review. Journal of Management, 46(6), 965–1001. Cheng, X., Fu, S., and de Vreede, G.J. (2021). Determinants of trust in computer-mediated offshore software-outsourcing collaboration. International Journal of Information Management, 57, https:// doi​.org​/10​.1016​/j​.ijinfomgt​.2020​.102301. Chiocchio, F., Forgues, D., Paradis, D., and Iordanova, I. (2011). Teamwork in integrated design projects: Understanding the effects of trust, conflict, and collaboration on performance. Project Management Journal, 42(6), 78–91. Choi, J.O., Shrestha, B.K., Kwak, Y.H., and Shane, J. (2021). Exploring the benefits and trade-offs of design standardization in capital projects. Engineering, Construction and Architectural Management. doi:10.1108/ECAM-08-2020-0661 Connelly, B.L., Crook, T.R., Combs, J.G., Ketchen Jr, D.J., and Aguinis, H. (2018). Competenceand integrity-based trust in interorganizational relationships: Which matters more? Journal of Management, 44(3), 919–945. Curnin, S., Owen, C., Paton, D., Trist, C., and Parsons, D. (2015). Role clarity, swift trust and multi‐agency coordination. Journal of Contingencies and Crisis Management, 23(1), 29–35.

256  Handbook on innovation and project management

Das, T.K. and Teng, B.S. (2001). Trust, control, and risk in strategic alliances: An integrated framework. Organization Studies, 22(2), 251–283. Dyer, J.H. and Chu, W. (2003). The role of trustworthiness in reducing transaction costs and improving performance: Empirical evidence from the United States, Japan, and Korea. Organization Science, 14(1), 57–68. Edmondson, A.C. (2012). Teaming: How organizations learn, innovate, and compete in the knowledge economy. San Francisco: John Wiley and Sons. Engwall, M. (2003). No project is an Island: Linking projects to history and context. Research Policy, 32(5), 789–808. Ertug, G., Cuypers, I.R., Noorderhaven, N.G., and Bensaou, B.M. (2013). Trust between international joint venture partners: Effects of home countries. Journal of International Business Studies, 44(3), 263–282. Ferrin, D.I. and Gillespie, N. (2010). Trust differences across national–societal cultures: Much to do, or much ado about nothing? In M.K. Saunders, D. Skinner, G. Dietz, N. Gillespie, and R.J. Lewicki (Eds.), Organizational trust: A cultural perspective (pp. 42–86). Cambridge: Cambridge University Press. Gulati, R., Wohlgezogen, F., and Zhelyazkov, P. (2012). The two facets of collaboration: Cooperation and coordination in strategic alliances. Academy of Management Annals, 6(1), 531–583. Hodgson, D. and Cicmil, S. (2007). The politics of standards in modern management: Making ‘the project’ a reality. Journal of Management Studies, 44(3), 431–450. Jarvenpaa, S.L. and Leidner, D.E. (1998). Communication and trust in global virtual teams. Journal of Computer-Mediated Communication, 3(4), JCMC346. Kadefors, A. (1995). Institutions in building projects: Implications for flexibility and change. Scandinavian Journal of Management, 11(4), 395–408. Klein Woolthuis, R.K., Hillebrand, B., and Nooteboom, B. (2005). Trust, contract and relationship development. Organization Studies, 26(6), 813–840. Kostopoulos, K.C. and Bozionelos, N. (2011). Team exploratory and exploitative learning: Psychological safety, task conflict, and team performance. Group & Organization Management, 36(3), 385–415. Kramer, R.M. (1999). Trust and distrust in organizations: Emerging perspectives, enduring questions. Annual Review of Psychology, 50, 569–598. Krishnan, R., Martin, X., and Noorderhaven, N.G. (2006). When does trust matter to alliance performance? Academy of Management Journal, 49(5), 894–917. Laan, A., Noorderhaven, N., Voordijk, H., and Dewulf, G. (2011). Building trust in construction partnering projects: An exploratory case-study. Journal of Purchasing and Supply Management, 17(2), 98–108. Lewicki, R.J. and Bunker, B.B. (1996). Developing and maintaining trust in work relationships. In R.M. Kramer and T.R. Tyler (Eds.),Trust in organizations: Frontiers of theory and research (pp. 114–139). Thousand Oaks, CA: Sage. Lewis, J.D. and Weigert, A. (1985). Trust as a social reality. Social Forces, 63(4), 967–985. Ligthart, R., Oerlemans, L., and Noorderhaven, N. (2016). In the shadows of time: A case study of flexibility behaviors in an interorganizational project. Organization Studies, 37(12), 1721–1743. Livne-Tarandach, R. and Jazaieri, H. (2020). Swift sense of community: Resourcing artifacts for rapid community emergence in a temporary organization. Academy of Management Journal, online first 28 September. https://doi​.org​/10​.5465​/amj​.2019​.0410 Lukić, J.M. and Vračar, M.M. (2018). Building and nurturing trust among members in virtual project teams. Strategic Management, 23(3), 10–16. Malhotra, A., Majchrzak, A., Carman, R., and Lott, V. (2001). Radical innovation without collocation: A case study at Boeing-Rocketdyne. MIS Quarterly, 25(2), 229–249. Malucelli, G., Barbosa, M.T., and de Carvalho, M.M. (2019). Facing the challenge of improvisation in project management: A critical review. International Journal of Managing Projects in Business, 14(20), 369–389. Marková, I., Linell, P., and Gillespie, A. (2008). Trust and distrust in society. In I. Marková and A. Gillespie (Eds.), Trust and distrust: Sociocultural perspectives (pp. 3–27). Charlotte, NC: Information Age Publishing.

Collaboration and trust in innovative projects  257

Maurer, I. (2010). How to build trust in inter-organizational projects: The impact of project staffing and project rewards on the formation of trust, knowledge acquisition and product innovation. International Journal of Project Management, 28(7), 629–637. Mayer, R.C., Davis, J.H., and Schoorman, F.D. (1995). An integrative model of organizational trust. Academy of Management Review, 20(3), 709–734. McAllister, D.J. (1995). Affect-and cognition-based trust as foundations for interpersonal cooperation in organizations. Academy of Management Journal, 38(1), 24–59. McGinn, K.L. and Keros, A.T. (2002). Improvisation and the logic of exchange in socially embedded transactions. Administrative Science Quarterly, 47(3), 442–473. McKnight, D.H., Cummings, L.L., and Chervany, N.L. (1998). Initial trust formation in new organizational relationships. Academy of Management Review, 23(3), 473–490. Meyerson, D., Weick, K.E., and Kramer, R.M. (1996). Swift trust and temporary groups. In R.M. Kramer and T.R. Tyler (Eds.), Trust in organizations: Frontiers of theory and research (pp. 166– 195). Thousand Oaks, CA: Sage. Mintzberg, H. (1980). Structure in 5’s: A synthesis of the research on organization design. Management Science, 26(3), 322–341. Nooteboom, B. (2002). Trust: Forms, foundations, functions, failures and figures. Cheltenham and Northampton, MA: Edward Elgar Publishing. Nooteboom, B. (1996). Trust, opportunism and governance: A process and control model. Organization Studies, 17(6), 985–1010. Nooteboom, B., Berger, H., and Noorderhaven, N.G. (1997). Effects of trust and governance on relational risk. Academy of Management Journal, 40(2), 308–338. Nygaard, S. and Russo, A. (2008). Trust, coordination and knowledge flows in R&D projects: The case of fuel cell technologies. Business Ethics: A European Review, 17(1), 23–34. Obstfeld, D. (2012). Creative projects: A less routine approach toward getting new things done. Organization Science, 23(6), 1571–1592. Paul, R., Drake, J.R., and Liang, H. (2016). Global virtual team performance: The effect of coordination effectiveness, trust, and team cohesion. IEEE Transactions on Professional Communication, 59(3), 186–202. Piccoli, G. and Ives, B. (2003). Trust and the unintended effects of behavior control in virtual teams. MIS Quarterly, 27(3), 365–395. Smith, K.G., Carroll, S.J., and Ashford, S.J. (1995). Intra-and interorganizational cooperation: Toward a research agenda. Academy of Management Journal, 38(1), 7–23. Starkey, K., Barnatt, C., and Tempest, S. (2000). Beyond networks and hierarchies: Latent organizations in the UK television industry. Organization Science, 11(3), 299–305. Strahorn, S., Brewer, G., and Gajendran, T. (2017). The influence of trust on project management practice within the construction industry. Construction Economics and Building, 17(1), 1–19. Swärd, A. (2016). Trust, reciprocity, and actions: The development of trust in temporary interorganizational relations. Organization Studies, 37(12), 1841–1860. Tjosvold, D. (1984). Cooperation theory and organizations. Human Relations, 37(9), 743–767. Uzzi, B. (1997). Social structure and competition in interfirm networks: The paradox of embeddedness. Administrative Science Quarterly, 42(1), 35–67. Valentine, M.A. and Edmondson, A.C. (2015). Team scaffolds: How mesolevel structures enable rolebased coordination in temporary groups. Organization Science, 26(2), 405–422. Van den Ende, L. and van Marrewijk, A. (2018). The point of no return: Ritual performance and strategy making in project organizations. Long Range Planning, 51(3), 451–462. Whitley, R. (2006). Project-based firms: New organizational form or variations on a theme? Industrial and Corporate Change, 15(1), 77–99. Zaheer, A., McEvily, B., and Perrone, V. (1998). Does trust matter? Exploring the effects of interorganizational and interpersonal trust on performance. Organization Science, 9(2), 141–159. Zakaria, N. and Yusof, S.A.M. (2020). Crossing cultural boundaries using the internet: Toward building a model of swift trust formation in global virtual teams. Journal of International Management, 26(1), https://doi​.org​/10​.1016​/j​.intman​.2018​.10​.004. Zhang, L., Huang, S., and Peng, Y. (2018). Collaboration in integrated project delivery: The effects of trust and formal contracts. Engineering Management Journal, 30(4), 262–273.

14. A cultural evolution theory of balancing innovative and routine projects Christoph H. Loch, Stylianos Kavadias and Svenja C. Sommer

INTRODUCTION In anthropology, culture is defined as “the transmission from one generation to the next, via teaching and imitation, of knowledge, values and other factors” (Boyd and Richerson, 1985, 2). This definition emphasizes the nature of culture as socially transmitted knowledge, which is evaluated and selected via “fitness pressures” on the group. The discussion of culture in organizational theory is often focused on norms and values (Cameron and Quinn, 2011), although Schein’s (2016) classic definition is closer to anthropology, where culture also includes knowledge and beliefs as well as technologies and artefacts. Cultural evolution theory uses the mathematical and empirical toolkit from evolutionary biology to examine the evolution of culture (Brahm and Poblete, 2022). Projects are ideally suited to test proposals from cultural evolution theory because they are embodiments of organizational change: projects are temporary organizational endeavours that use problem-solving to find solutions to novel problems (for those organizations) where existing standardized processes, with defined solution procedures, prove insufficient. Projects are therefore key tools for organizations to create and implement change and to learn. The novel nature of most projects makes it hard for learning to come from pre-planned and standardized procedures; rather, it is influenced by informal activities and beliefs as well as tacit knowledge that resides with the people in the organization. Therefore, projects can be prime examples and drivers of cultural evolution. Therefore, our research goal is to theoretically demonstrate, in a simple model, how projects can influence the evolution of culture (especially linked to innovation), specifically, how the balance between innovative and routine projects (ambidexterity as introduced by Tushman and O’Reilly, 1996) may evolve in the tension of top-down direction and bottom-up dynamic learning and imitation behaviours. We note that this research goal is consistent with an accepted view that an organization’s strategy does not evolve top-down or bottom-up but through a dynamic interaction between the two directions (Burgelman, 1983; Loch and Kavadias, 2011; Kim et al., 2014; HutchisonKrupat and Kavadias, 2015; Sting and Loch, 2016; Hutchison-Krupat, 2018). Cohen et al.’s (1972) “garbage can model” illustrated that organizations may drift, and Lovas and Ghoshal (2000) indicated through a case study that a company’s strategy might be the outcome of Darwinian evolution. These studies complemented numerous anecdotes where managers conceded that they did not understand how the behaviour of their project teams evolved. Still, these studies offered little detail, beyond the general description of evolution, about the mechanisms that govern the occurrence of drift. A multi-level system view is required to understand these dynamic interactions. 258

A cultural evolution theory  259

In anthropology, it is accepted wisdom that cultures develop in bottom-up and undirected ways that follow evolutionary pressures, but without a strong “strategic” direction – a direction is “selected in” at the group level (rather than planned). Cultural evolution models are designed to incorporate a multi-level analysis but have not entered mainstream management studies, especially not in project management. This chapter aims to demonstrate the modelling machinery developed in cultural anthropology on the example of the balance between innovative and routine projects. We review a few fundamental models of cultural evolution, and we adapt one of those classical models to explore how top-down direction may shape project execution culture and the project balance, which in turn may constrain and influence the overall strategic direction. Our model shows how “bottom-up” cultural dynamics among project teams may influence the competitive position of an organization, but also how these dynamics are at the same time shaped by the “top-down’” (competitively driven) performance (or “fitness”) criteria set out by the organization’s senior management. Thus, we demonstrate how models of cultural evolution can offer a multi-level system analysis of the interaction between culture at the project level and strategy.

CULTURAL EVOLUTION THEORIES AND PROJECT MANAGEMENT A key characteristic of projects is that they deal with “novel” or “unique” problems as opposed to standard outputs delivered by processes. Therefore, projects require a higher degree of learning compared to other organizational activities. Such learning happens not only through pre-planned and conscious actions (see the chapter on managing unforeseeable uncertainty through learning) but is both emergent (creative and unpredictable) and influenced by culture. A sociological definition of culture is a pattern of shared basic assumptions learned by a group as it solved its problems of external adaptation and internal integration […] it is a product of joint learning. […] culture expresses itself in visible artifacts, in expressed beliefs, and in basic underlying assumptions (unconscious, “taken for granted” values). (Schein, 2016, 6)

A narrower definition of culture from economics stresses that the routinization of activities in an organization constitutes the most important form of storage of the organization’s specific operational knowledge. […] There is no need for anyone to know anyone else’s job, neither is there any need for anyone to be able to articulate or conceptualize the procedures employed by the organization as a whole. (Nelson and Winter, 1982, 99, 105)

This is also echoed by Hodgson (1996, 255): “Culture is more than shared information: through shared practices and habits of thought, it provides the method, context, values, and language of learning, and the evolution of group and individual competences”. While these representations of culture are narrower than both the sociological and anthropological views of culture, they agree with Schein on the subconscious nature of cultural norms. The fact that structured knowledge and values may evolve in ways that are, at best, partially understood by anyone at the top of an organization has been widely observed. Within firms, processes and structures arise partially randomly, e.g., because new employees are hired, or

260  Handbook on innovation and project management

because individual employees invent new rules to improve their daily reality. These processes and structures “compete” for resources, attention and support from the various stakeholders, and they are selected based on efficiency and success, where “success” may be subjectively rather than objectively defined. For example, during R&D portfolio decision-making within organizations, innovations compete for resources and are selected based on their “success potential”; this is rarely objective, but it is significantly influenced by the individual guesses and personal as well as group biases of those participating in this process; project workers also inherit competencies and know-how from previous project efforts (Basalla, 1988; Mokyr, 1992; Fleming, 2001). Despite its wide acknowledgement, this viewpoint has not found the “right” machinery within the management discipline to study it (Brahm and Poblete, 2022; Feylessoufi et al., 2022). Such machinery exists in the field of cultural evolution in anthropology. The aim of these cultural evolution models is to take the micro-scale properties of individual behaviour, aggregate them up to a population and deduce the collective long-run evolutionary consequences of the assumed micro-level behaviours (Richerson et al., 2006). This makes these models an appropriate “tool” to understand dynamics at the population level as well as at the underlying individual level. Moreover, cultural evolution is different from biological (Darwinian) evolution because traits are not only “vertically inherited” from parents but can be “horizontally” transmitted among peers within the population (and thus “what is transmitted” changes from genes to packageable ideas). Horizontal transmission happens in two ways – by people with certain behaviours moving around and by people acquiring information (ideas, practices) from others by learning and teaching. Thus, cultural evolution emphasizes social learning – the imitation of “phenotypes” of behaviour from others.1 Social scientists have built reasonable mathematical representations of the micro-level processes of cultural evolution (e.g., Richerson et al., 2006). These models have enabled social scientists to understand important behavioural dynamics across different levels of decision-making and effort within organizations. For example, if people meet “randomly”, the spread of knowledge through imitation cannot explain the adoption of collaborative behaviours as long as such behaviours carry the slightest disadvantage to individuals. Collaboration can spread effectively only when people stably organize in groups, and selection takes place at the aggregate group level (Hamilton, 1975). This is the case in organizations: members stay with the organization for a while, and if they move, they adopt the culture of their new organization. Thus, the same behaviours “assort” themselves (through people adapting to them) in stable ways. As a result, one organization’s members are sustainably subject to different social pressures than members of other organizations with which the first organization may compete. Specifically, projects function as vehicles that drive cultural evolution: each project tackles a new problem, even if the problem is only “slightly” new, such as assembling known resources at a new location. Therefore it exhibits new experimental behaviours, which may disappear, or be selected (explicitly or implicitly) to be used again. Thus, projects manifest the individual or team level of cultural evolution (the inner circle in Figure 14.1). Multi-level analysis is relevant as the surrounding organization is shaped by the ideas and procedures that are created in the projects and retained (the outer circle in Figure 14.1); yet, at the same time, the organization, with its selection criteria and action procedures, influences the way the projects are carried out. Finally, at the third level in Figure 14.1, the organization,

A cultural evolution theory  261

Source:   adapted from Loch and Kavadias, 2011.

Figure 14.1  Nested organizational evolution as a whole, competes with other organizations. This competitive pressure drives group selection – organizations with effective ideas and procedures (this may mean fast, efficient, flexible or robust) are more successful and grow. Notably, at all levels of aggregation, all three characteristics of evolution are present: (partially random) generation of a variety of behaviours, selection according to some (often noisy) criteria that are stable for a while, and elaboration and inheritance (Dawkins, 1996). Overall, models of evolutionary theory offer a set of causal explanations across levels of aggregate decision-making. They allow us to explicitly consider not only the dynamics that emerge within the different levels of decision-making, but also the dynamics across those levels. They can describe how behaviours evolve “spontaneously” according to dynamic laws of social learning that happen at the level of individuals/teams and are not controlled, maybe not even understood, by senior management (the group level of decision-making). Yet, they can also identify how management can influence (enable or constrain) this evolutionary dynamic by setting performance rules, which function as “fitness” measures at the lower level, while at the same time, the high-level decisions are constrained by the lower-level dynamics. The possibility to simultaneously address multi-level decisions and their interactions allows us to make Peter Drucker’s classic quip that “culture eats strategy for breakfast” more precise, while also identifying its limitations. We build on an influential basic model of cultural evolution (Rogers, 1989), which considers whether, and how, cultural imitation increases the fitness of a population. In this model, an agent population lives in an environment that may switch (with constant probability) between

262  Handbook on innovation and project management

two states that require different behaviour for survival. The probability of switching is a measure of the predictability of the environment – from stable to volatile. Agents survive in this environment depending on whether they correctly diagnose the state of the environment and apply the right behaviour (e.g., if is it rainy and wet, seek shelter, but if it is sunny and hot, store water and hydrate effectively). Some agents (individual learners) cope with this situation by obtaining, at some cost, information about the environment and then adapting their behaviour to fit the environment (they correspond to “innovators” in our following model). Others (imitators, or social learners) simply pick a random individual from the population and copy it. Imitation is less costly than individual learning but does not add any value if one copies from an individual that has chosen the “wrong” (for the current environment) behaviour (these agents correspond to the “executors” in our upcoming model). The outcome of this simple model is surprising. In the long run, there is always a mixture of individual learners and social learners, and both types have the same fitness as individual learners alone. In other words, cultural imitation provides no benefit to the population. The organisms are no better off than they were without any imitation, a result that has been termed “Rogers’ paradox”. The reason is that each type can “invade” when rare: when there exist few social learners, it becomes very likely they imitate an individual learner, and thus they get all the benefits from the individual learners’ efforts without the cost. In this scenario, social learners have an advantage and can spread. When individual learners are rare, they track the environment perfectly, whereas most social learners get it wrong as they tend to imitate role models from the more numerous other social learners who cannot correctly track the changing environment. In this scenario, the individual learner has an advantage and spreads. In equilibrium, both types are present and have equal fitness. The result is important on two counts: first, individual learning is not a stable behaviour (it is not defensible in an environment with evolutionary competition), as “free rider” imitators might invade the overall population and benefit. Second, social learning as a strategy does not add fitness at the population level by itself, i.e. in equilibrium, the average population fitness is equal to the fitness of individual learners. Several studies have examined which elements of the Rogers model would have to be modified for social learning to add value at the population level. Boyd and Richerson (1995) show, first, that Rogers’ result is robust to spatial variation across groups and to social learners imitating multiple role models. Second, they show that social learning can add fitness to the population if individuals can choose to learn only when the possible result of learning looks sufficiently superior. Third, social learning also improves the population’s fitness if it is cumulative over time, in the sense that even social learners can “experiment around” their behaviour adopted from imitation and improve it a little bit. This allows the population to improve even when many social learners copy from one another. More recently, Brahm and Poblete (2021) argue that the rise of the corporation in history represents the emergence of groups within which social learners exhibit lower costs of learning by taking advantage of ideas that are produced on the outside. In the next section, we propose a different variation of Rogers’ model. Similar to Boyd and Richerson (1995), we assume some type of cumulative effect on the level of the individual’s fitness (where both social and individual learners can benefit from “continuous improvements”), but most importantly, we embed the evolutionary dynamics of individuals within a firm (group) level competition model. We examine multi-level evolutionary dynamics by endogenizing the level of fitness that the individuals are evaluated on. Prior models of cultural

A cultural evolution theory  263

evolution have taken the group environment as given, since they sought to address the typical situation in nature where, indeed, the environmental conditions are exogenous. However, intra-organizational dynamics directly affect their organizational environment and its fitness demands.

A CULTURE EVOLUTION MODEL OF INNOVATION AND ROUTINE PROJECTS The evolutionary model, inspired by Rogers (1989), comprises two levels: first, the intrafirm cultural dynamics capture how project-level learning from problem-solving and imitation is guided by organizational performance measurement. Second, the interfirm competitive dynamics capture competing organizations choosing their strategic positions (market segments and technologies) in an effort to maximize their returns. The strategic position of each firm determines the objectives of each firm’s projects. Intrafirm Cultural Dynamics Project teams contribute to the company’s strategic position by executing projects, one per period. If successful, a project produces value according to the requirements of the market segment within which the firm operates. For now, generically denote the project value by V. However, the market requirements may discontinuously change each period with a (stationary) probability P. (P may depend on the market segment, which will be discussed in the next subsection.) In the spirit of ambidexterity (Tushman and O’Reilly, 1996), there are two project types: innovative projects that require original new problem solving, and routine projects that repeat previous solutions obtained from peers with only small changes. Accordingly, there are two types of employees in the organization (who are fixed in their skills within the duration of a project but can learn over multiple projects/periods): first, teams of innovators or problem solvers (who are individual learners in the cultural evolution terminology). These individuals always experiment around the established project blueprints to see whether they can find better responses or solutions. On the one hand, this enables them to respond to changing market requirements and hence to capture the value potential of the market segment even when the task requirements change (whereas “normal project processes” are designed for planned responses rather than innovation). Note that this behaviour is not only enabling new outcomes but could equally effectively enable innovation within the project, e.g., experimenting with new analysis methods or project team communication technologies that better respond to market requirements. On the other hand, such unrelenting innovation comes at a sizeable cost C (of invested time as well as “aggravation” to others who do routine work), since these individuals spend effort each period regardless of whether a discontinuity occurs or not. Second, routine projects are carried out by teams of project executors (Pedersen and Ritter, 2017) (who are social learners in the cultural evolution terminology). These individuals use previous solutions, gleaned from colleagues, with small modifications that may achieve slightly better outcomes or small improvements upon previous practices. These workers do not spend time exploring new methods or solutions but copy previously used approaches and practices from other workers in the organization. This is less costly than innovation or original

264  Handbook on innovation and project management

problem solving (c < C) but creates no value when the environment changes while the team copies these approaches or practices from other executors rather than innovators. Similar to the cumulative learning in Boyd and Richerson (1995), we consider that the project executors add value to the organization by introducing (small) continuous improvements and modifications of the approaches they copy, adding a value of δ when the environment is stable or the executor team gets its information from an innovation project team. The timeline works as follows: at the beginning of each period, project innovators (representing a fraction rI of the population) start problem-solving to analyse the requirements and to produce a new customized solution, possibly with new methods (at cost C). While they analyse and adapt their approach regardless of whether the external requirements have changed or not, we assume that innovators who realize that they find themselves in a stable environment can, in addition, incorporate continuous improvements resulting from their interactions with process workers. Such interactions happen with a probability rS = (1 − rI ) (S for social learners), which is the fraction of project executors in their organization. Executors start each period by (randomly) choosing a source of information: if an executor team happens to choose an innovator team, they are able to use the solution that the innovator develops, at a lower imitation cost c. In addition, the interaction between the two teams results in a small improvement of δ (in the spirit of “continuous improvement”) that benefits both. If, on the other hand, the executor team chooses to get its information from another executor team, it benefits from the improvement initiatives only if the market requirements remain stable; in case of a disruption, the chosen approach will result in a project failure and value 0. The economics of these social dynamics are summarized in Figure 14.2. This model expresses a conceptual characterization of cultural learning dynamics within and across projects. Critical assumptions in the model are for now that V > C > c.2 We derive the average project performance (equivalent to the fitness in cultural evolution models) for the two types of teams, f I and f S, evaluated over the probabilities of being in a

Figure 14.2  Employee fitness depending on behaviour and environment

A cultural evolution theory  265

stable or disruptive environment and, in the case of executors, the type of team chosen as an information source. f I = V − C + δ(1 − rI )(1 − P ) f S = (V − c + δ)rI + [−cP + (V − c + δ)(1 − P )](1 − rI ) = (V + δ )[1 − P + rI P ] – c. These project performances are subject to evolutionary dynamics as in the original Rogers model: if executors are rare, they choose (randomly) mostly innovators as information sources and benefit from their problem-solving, incurring a lower learning cost c. If, in contrast, innovators are rare, they benefit from the fact that the executors mostly fail by choosing wrong information sources. Thus, the two types of teams will evolve their relative frequencies by leaving and getting replaced or by changing their modes of problem-solving, prompted by performance (fitness) feedback. This particular type of evolutionary dynamics is known as a quasi-birth and death process, and it has been shown to converge to equilibria of evolutionary stable strategies (ESS) (Boyd and Richerson, 1985). Formally, given the standard assumption of weak selection, a population of project teams with shares (rI, 1 – rI ) plays an ESS if a team population using any different relative share of these strategies achieves a strictly lower average project performance. Consistent with previous literature (Boyd and Richerson, 1995), we find that there exists a unique equilibrium (characterized by the two fitness levels being the same) in which the share of innovators is given by:

rI 

VP   C  c  (14.1) V 

V 1  P     C  c . Moreover, V  the performance (fitness) of both types of teams ends up being equal at: Note that this implies the fraction of executors to be 1  rI  



f  V  C   1  P  1  rI  (14.2)

As an aside observation, this model overcomes Rogers’ (1989) “paradox” that the presence of imitation or social learning does not affect the population’s average performance outcome (similar to other modifications discussed earlier): executors do contribute small continuous improvements – the average organizational performance in Equation (14.2) is higher than when there are only innovators present. The extant literature on cultural evolution theory has naturally taken the contextual parameters V, P, C and c as fixed and exogenous (environmental) factors. However, a business context, in particular a project context, usually has these parameters (at least partly) shaped by firm-level decisions. Comparative static analysis allows us to explore the impact of these firm-level decisions (anticipating the examination of organizational-level decisions in the next section): for example, the frequency of change P and the potential project value V can be affected by the higher

266  Handbook on innovation and project management

level strategic position and goals of the firm. A higher P may reflect a more volatile market segment. How do these parameters, which result from higher-level choices, influence the cultural dynamics? We calculate the partial derivatives of rI as

rI P  C  c   0 (14.3) 2 V V   



rI V   0. (14.4) P V  

These results show that if a firm’s senior management seeks a higher project value V, most often accompanied by higher requirements instability P (the infamous “high risk, high return” opportunities), it will observe an increasing fraction of innovators in the firm. In other words, as the project value and the requirements discontinuity increase, project teams will over time rearrange themselves into a higher fraction of innovative behaviours and practices rather than executing projects through routine approaches based on past successful efforts. Note that this happens “culturally” bottom-up rather than by management orders. This is important for the discussion of what happens when the organization faces its competitive environment, which we turn to in the next subsection. Similar analyses can be performed with respect to the type of organizational practices put into place in firms. An organization that chooses to compete by reducing the organizational “cost” of problem-solving (C), for example by investing in analysis and problem-solving tools,  rI   0  . Similarly, organizawould naturally see an increase in the fraction of innovators   C  tions which invest in benchmarking and best practice sharing (lowering c) or put in place continuous improvement initiatives (increasing δ ) would end up with a larger fraction of r   rI  0 and I  0 . executors     c These comparative statics remind us that project management processes, rules, norms and approaches do not merely achieve a short-term objective, but carry larger implications by shaping the future behaviours of project teams, and therefore set limits or offer opportunities for the organization’s competitive strategy. To some degree, the firm’s senior management can anticipate this when making their competitive choices; we turn to this next. Interfirm Competitive Dynamics Suppose we have two firms (the simplest case with which we can demonstrate competitive dynamics, or “group selection”), and each firm chooses a market segment to compete in. Let’s suppose there are two segments, a “high end” segment H and a “low end” segment L. Segment H is characterized by a higher project value VH > VL but also by more frequently changing market requirements, thus PH > PL; the high-end market segment experiences more frequent changes in the customer requirements and thus a more volatile business environment. Depending on which segment each firm decides to operate in, the project teams will shift their behaviour in response to the performance signals they receive from their organizational environments; the resulting equilibrium compositions and their performance levels are

A cultural evolution theory  267

provided by Equations (14.1) and (14.2), which reflect the segment’s project value and volatility. Formally, we index them as rIH and f H (and the analogue for segment L). For simplicity of exposition, suppose that a company’s return from operating within a segment for a period is  i  f H or fL i  1, 2 – the overall company performance is the average value output from a project per period (or equivalently, the sum of the team performances). The company performances determine the division of revenues by the following competition mechanism, a simple constant-sum structure: a company operating alone in a segment captures the full return, while the market value will be split if the two competitors operate in the same segment. We summarize the firm payoffs in Figure 14.3. This analysis makes a well-established assumption about the timescale of the evolution process: any cultural adjustment of the fraction of executors and innovators in the organization takes place over a much shorter time window compared to the organization’s strategic implementation of operating in a certain segment. In other words, attacking a new segment is a multi-year endeavour, while the adjustment of the fraction of executors and innovators happens in less time. Therefore, we can use the equilibrium derivations of workforce composition and performance (14.1) and (14.2) as “instantaneous” reactions to the choice of segment. Our assumption is consistent with group selection models in evolutionary theory, e.g. Hamilton (1975). We now examine the resulting competitive equilibria: when firms choose to compete in the same market segment (H, H) and when they, instead, prefer to differentiate and serve different market segments. The most interesting case for our analysis is the setting where an asymmetric equilibrium exists. It is interesting because the differentiation causes two different cultures to evolve in a priori identical firms with the same choice sets. For such an asymmetric equi1 1 librium to exist the following two conditions have to hold:3 f H > fL and fL > f H . 2 2 We showed in Equations (14.3) and (14.4) that the fraction of innovators in the organization increases with higher task value V and with higher volatility P. This implies that a company operating in segment H will have a higher fraction of innovators (it will pursue a





Figure 14.3  Firm payoffs depending on market segment choice

268  Handbook on innovation and project management

higher fraction of expensive but innovative projects) than a company operating in segment L. However, the comparison is less straightforward for the per-team performances:

f r  1   1  P  I  0 V V



r f   1  rI    1  P  I  0. P V

The performance per project and period increases in the project value but decreases in the volatility of the market segment. It is therefore possible within the conditions stated so far that the high-end segment H could be less profitable than the low-end segment, specifically when the volatility is so much higher that it outweighs the higher project value. The foregoing general competitive equilibrium conditions, which hold even when f H might be lower than fL , are complicated implicit equations. Since we are developing this model to demonstrate how cultural evolution theory might be able to inform us about project management outputs, we focus on two simpler sufficient conditions for an asymmetric equilibrium to exist in our duopoly game. (We derive these two conditions in the Appendix.) Sufficient equilibrium conditions Two conditions are together sufficient for a separating competitive equilibrium to exist among two identical firms: •

•



The high-end segment is more valuable than the low-end segment, f H > fL . This is the case if the task value difference outweighs the volatility difference (weighted by the fractions of executors):

VH 

VL  /   1  PL  (1  rIL )  1  PH  (1  rIH ).

The value margin generated by problem-solving in the low-end segment environment is at least 50 per cent of the value margin generated by problem solvers in the high-end segment: VL  C 

1 VH  C  . 2

Our equilibrium characterization demonstrates that our simple model offers valid insights (it “makes sense” – the conditions derived above carry intuitive interpretations). The high-end segment should be sufficiently valuable (corrected for volatility), and the low-end segment should guarantee sufficient margins so that both firms have an incentive to differentiate their strategic positioning and not try to invade the segment of the other firm. Yet, the more important message from our model and analysis is the following: first, we show explicitly how top-down management and bottom-up cultural dynamics interact. Management “dictates”, based on competitive considerations, the target segment and thus the project values (which become measures of team performance) as well as the requirement volatility P. But cultural dynamics, which are not controlled and may not even be understood by

A cultural evolution theory  269

top management, produce the executor versus innovator composition (fraction of innovators rI ) and resulting performance f . The chosen strategic position “directs” culture, but simultaneously, cultural dynamics deliver the mixture of innovation versus execution behaviour and the resulting performance outcomes that constrain or enable the chosen strategy. Top-down strategy and bottom-up cultural dynamics form a complex interactive system. Second, we show how projects can represent the drivers of the culture. Of course, culture in our simple model means something simple, namely the fraction of innovators versus executors (and thus, how ambidextrous or innovative the organization “feels” as a whole). But although the selection pressure comes from the environment (and is set at the top), the resulting behavioural adaptations happen at the project level. Thus, the model illustrates how projects, by their fast turnover, can be the “units of cultural change”. In doing so, the model also illustrates how simple stylized analyses can direct attention to projects as fundamental evolutionary drivers of innovation dynamics in organizations.

DISCUSSION AND POSSIBLE DIRECTIONS FOR FUTURE RESEARCH We have developed a modification of a classic model from cultural evolution theory by Rogers (1989) to study the cultural dynamics driven by projects and their performance implications. We depart from Rogers’ model in two ways: first, we add firm-level selection, which represents the fact that the cultural dynamics that emerge at the individual project level do not happen in a fixed exogenous environment, but instead, they interact with organizational-level dynamics arising from competitiveness considerations. Second, we acknowledge a continuous improvement benefit from routine projects that widens the view of social learning. The model demonstrates that cultural evolution theory gives us a tool to model multi-level organizational dynamics, which are required to understand the interaction of top-down and bottom-up strategy processes as a system. In other words, management chooses dimensions of competitive success, and the individual adaptation at the project level can end up supporting this positioning (“group-level selection”) without management ever making the decisions on the “right” composition of projects: the mixture of innovation versus routine projects (and thus ambidexterity in the sense of Tushman and O’Reilly, 1996) is not planned top-down but emerges. This shows how cultural evolution models can contribute to studying the interplay between strategic direction and project-level behaviours in a multi-level analysis. Our model can be used as a language to interpret well-known innovation instances, for example, the famous invention of Post-it Notes at 3M (Nayak and Ketteringham, 1986). After the unexpected success of the product (the “too weak” glue that created a new product category because the weak adhesiveness enabled removability), co-inventor Art Fry was flown first class around the world to proselytize the creativity of the product idea and to motivate other company employees to search for the same kind of innovation. This was a clear instance of trying to “intensify” social imitation. But how successful was this – how many colleagues did pick this up? Our model suggests that first, this may depend on which idea actually travelled across minds – the usage of weak glues, or the idea generation from “improbable” connections, such as between technical characteristics and social application contexts (bookmarks falling out of the church songbook). Second, the effectiveness of imitation will depend on how people imitate – do they copy random people they meet (in which case flying one person around may be an unproductive endeavour), or do they copy mainly high-salience and

270  Handbook on innovation and project management

high-status role models, in which case Art Fry’s presentations to crowds may have proven very effective indeed? This observation points to a specific extension of our model: like most of the models of cultural evolution, we assume that executors (social learners) copy from randomly chosen others. Empirically, it is known that social imitation is not purely random. It does not always choose the most representative, best or even average role models to imitate what they know, but it is biased: as it is not always clear and easily interpretable what are good role models, imitation may follow social cues. Three well-known social cue biases have been identified and could be further explored through cultural evolution models. First, imitation may be conformist: do what the majority does, no matter whether it creates value for your project. Once a majority of behaviour is established (and deviation penalized), this may entrench itself even when it is unproductive or even damaging (as long as the selective pressure of the group, or the organization, is noisy enough that the group does not get punished or selected out) – this can explain dominant but persistent cultural habits that look wasteful or unproductive (Boyd and Richerson, 1992). In the context of project management, examples are the adoption of certain heavy-handed documentation or the adoption of a method (such as Discounted Cash Flow analysis, DCF, or Economic Value Add, EVA) simply because a majority of organizations have done so. Second, imitation may follow the highest status individuals that a given subject is able to get in contact with (or observe) (Boyd and Richerson, 1985, Chapter 7): social status is taken as a proxy of expertise. This was what 3M tried to exploit by flying Art Fry first class around the world, and this is also what causes teenagers to wear a “hood” (because certain sports stars do so), young employees to start smoking cigars (because the CEO does) or project workers to want to conduct a kickoff meeting in a prestigious site (because a highly successful project manager “role model” has done so in the past). Thus, imitating high-status individuals can be helpful in spreading desired behaviours. But it can also have dangerous effects, as sometimes the imitation itself may cause the highstatus “standard”, or expectation, of this behaviour to shift in the population, which then again changes the level of this behaviour seen in high-status individuals. This may cause feedback or “runaway” cycles (Boyd and Richerson, 1985, Chapter 8).4 Runaway cycles are well documented in nature: e.g. the exaggerated antlers of extinct stoneage elk (which perished partially because the antlers became so heavy over many generations that the males starved too frequently) or exaggerated teeth of (extinct) sabretooth tigers. But such runaway cycles can also be observed in human behaviour, for example, in bodybuilding world championships that at some point around 1980 became so extreme that many top athletes damaged their health and some died. In project management, an example is escalating return expectation followed by imitated cost reduction behaviour, which causes increased return expectations and may cause a runaway cycle that ends with a hollowing-out of project management standards and at some point failure. Project failures from escalating return demands and tightening budgets are not uncommon. The conditions (i.e. strength of the feedback from imitator adoption to the measurement standard of the high-status role models, and selective pressure on the group) can be modelled. This opens up the capability to characterize situations where runaway cycles are in danger of occurring. The conceptual understanding of the connection between high-level managerial performance pressures and the (partially autonomous) dynamics of culturally driven behaviour by many employees at the operational level is powerful and necessary, but it has not been

A cultural evolution theory  271

explicitly pursued by studies so far, certainly not in the context of project management. The simple model presented in this chapter introduces (in a basic form) a method to pursue this connection: strategy and operational-level cultural reactions form a dynamic system, which results in an emergent combination of innovation and routine projects. We have also assumed, for clarity of focus on the effects of evolutionary dynamics, that the two firms are identical. With more work, more complex models of differing firms can be built. Mentioning only the few parameters present in our simple model, one firm may have more effective employee habits in continuous improvement and thus a higher δ than a second firm. Or in one firm the innovators may be able to share more widely their problem-solving (which 3M tried to achieve, and which would change the payoff probabilities in Figure 14.2), or innovators may be taught to apply process improvements themselves (for example, by collaborating with more people), which would increase their effectiveness in Figure 14.2. The result of such cultural differences may be that one strategy works in one firm but not in another, or that the competitive equilibrium may be more lopsided for the benefit of one firm than expected by those not aware of the cultural differences. In short, this type of modelling approach offers the potential of adding to our understanding of the dynamics of managing innovative projects in organizations for the future. Multi-level models of the type demonstrated here (in its simplest form for illustration) are useful in order to truly understand the resulting interplay between strategy and cultural dynamics, in project management and more widely.

NOTES 1.

There is evidence that the ability to imitate differentiates humans from animals at least as much as or more than sheer intelligence (Herrmann et al., 2007). Moreover, human intelligence is likely a result of social imitation and competition (Dunbar, 1992). Just like biological inheritance, cultural transmission is imperfect, so the transmission is not always exact. People invent new cultural variants, making culture a system for the inheritance of acquired variation of behaviours. People also pick and choose the cultural variants they adopt and use, processes that are not generally possible in the genetic system. 2. Additional assumptions will be required in order for equilibria to exist in the competitive setting. 3. Note that for firms with different organizational practices, these conditions have to hold for both firms for a stable equilibrium to exist. The symmetry of considering a priori identical firms allows us to focus on the effects of the evolutionary dynamics rather than mixing in additional effects of other (exogenous) differences between the firms. 4. Note that this runaway cycle is fundamentally different from escalation of commitment (Staw, 1981), which refers to a reluctance to give up a failing project because of social pressure and the perceived need to defend one’s own past actions. Escalation of commitment does not include a feedback loop, which causes the behaviour to be imitated by others and to be amplified.

REFERENCES Basalla, G. (1988). Continuity and discontinuity, Ch. 2. In G. Basalla (Ed.), The evolution of technology (pp. 26–63). Cambridge University Press. Boyd, R. and Richerson, P.J. (1985). Culture and the evolutionary process. University of Chicago Press. Boyd, R. and Richerson, P.J. (1992). Punishment allows the evolution of cooperation (or anything else) in sizable groups. Ethology and Sociobiology, 13, 171–195.

272  Handbook on innovation and project management

Boyd, R. and Richerson, P.J. (1995). Why does culture increase human adaptability? Ethology and Sociobiology, 16, 125–143. Brahm, F. and Poblete, J. (2021). The evolution of productive organizations. Nature Human Behavior, 5(1), 39–48. Brahm, F. and Poblete, J. (2022). Cultural evolution theory and organizations. Organization Theory, 3, 1–30. Burgelman, R.A. (1983). Corporate entrepreneurship and strategic management: Insights from a process study. Management Science, 29(12), 1349–1364. Cameron, K.S. and Quinn, R.E. (2011). Diagnosing and changing organizational culture: Based on the competing values framework. New York: John Wiley and Sons. Cohen, M.D., March, J.G., and Olsen, J.P. (1972). A garbage can model of organizational choice. Administrative Science Quarterly, 17(1), 1–25. Dawkins, R. (1996). Climbing mount improbable. Norton. Dunbar, R.I.M. (1992). Neocortex size as a constraint on group size in primates. Journal of Human Evolution, 20, 469–493. Feylessoufi, A., Kavadias, S., and Ralph, D. (2022). The role of behavioral micro-foundations on the optimal organizational adoption of new practices. SSRN Working Paper. Fleming, L. (2001). Recombinant uncertainty in technological search. Management Science, 47(1), 117–132. Hamilton, W.D. (1975). Innate social aptitudes of man: An approach from evolutionary genetics. In R. Fox (Ed.), ASA studies 4: Biosocial anthropology (pp. 133–153). London: Malaby Press. Herrmann, E., Call, J., Hernandez-Lloreda, M.V., Hare, B., and Tomasello, M. (2007). Humans have evolved specialized skills of social cognition: The cultural intelligence hypothesis. Science, 317, 1360–1366. Hodgson, G.M. (1996). Corporate culture and the nature of the firm. In J. Groenewegen (Ed.), Transaction cost economics and beyond (pp. 249–269). Boston: Kluwer Academic Press. Hutchison-Krupat, J. (2018). Communication, uncertainty and the execution of a strategic initiative. Management Science, 64(7), 3380–3399. Hutchison-Krupat, J. and Kavadias, S. (2015). Strategic resource allocation; top-down, bottom-up and the value of strategic buckets. Management Science, 61(2), 391–412. Kim, Y.-H., Sting, F., and Loch, C.H. (2014). Top-down, bottom-up or both? Towards an integrative perspective on operations strategy formation. Journal of Operations Management, 32(7–8), 462–474. Loch, C.H. and Kavadias, S. (2011). Implementing strategy through projects, Ch. 8. In P.W. Morris, J. Pinto, and J. Soderlund (Eds.), Oxford handbook of project management (pp. 224–251). Oxford. Lovas, B. and Ghoshal, S. (2000). Strategy as guided evolution. Strategic Management Journal, 21, 875–896. Mokyr, J. (1992). The lever of riches: Technological creativity and economic progress. Oxford University Press. Nayak, P.R. and Ketteringham, J.M. (1986). Breakthroughs! New York: Rawson Associates. Nelson, R.E. and Winter, S.G. (1982). An evolutionary theory of economic change. Cambridge, MA: Belknap. Pedersen, C.L. and Ritter, T. (2017). The 4 types of project manager. Harvard Business Review Blog, 27 July, downloaded from https://hbr​.org​/2017​/07​/the​- 4​-types​-of​-project​-manager Richerson, P.J., Collins, D.E., and Genet, R.M. (2006). Why managers need an evolutionary theory of organizations. Strategic Organization, 4(2), 201–211. Rogers, A.R. (1989). Does biology constrain culture? American Anthropologist, 90, 819–831. Schein, E.H. (2016). Organizational culture and leadership (5th ed.). Jossey Bass. Staw, B.M. (1981). The escalation of commitment to a course of action. Academy of Management Review, 6(4), 577–587. Sting, F.J. and Loch, C.H. (2016). Implementing operations strategy: How vertical and horizontal coordination interact. Production and Operations Management, 25(7), 1177–1193. Tushman, M. and O’Reilly, C. (1996). Ambidextrous organizations: Managing evolutionary and revolutionary change. California Management Review, 38(4), 8–30.

A cultural evolution theory  273

APPENDIX Here, we derive sufficient conditions for a separating competitive equilibrium. We can write the full conditions as follows: 1 VL  C   1  PL  1  rIL   2



VH  C   1  PH  1  rIH  



VH  C   1  PH  1  rIH   2 VL  C   1  PL  1  rIL  

The first condition is subsumed by the stricter condition that the high-end segment is more attractive (f H > f L), which becomes the condition stated in the text earlier. The second condition can be rewritten as:

 1  PH  1  rIH   2 1  PL  1  rIL    2VL  VH  C.

By assumption, (1−PH ) < (1−PL), and we have derived that 1  rIH   1  rIL , and therefore the left-hand side of this inequality is negative. A stricter condition is thus to require that 2VL  VH  C  0 . This is the second condition mentioned earlier in the text.

15. Organizing projects for social innovation Stephan Manning and Stanislav Vavilov

INTRODUCTION The concept of social innovation (SI) has become one of the most discussed in recent years both in innovation research (Cajaiba-Santana, 2014; Dionisio and de Vargas, 2020; Pel et al., 2020) and innovation practice (The Young Foundation, 2007; Chesbrough and Di Minin, 2014; Howaldt et al., 2018). SI refers to new ideas, methods and practices that address social problems in new ways (Mulgan, 2006; Pel et al., 2020). SI is a new innovation paradigm (van der Have and Rubalcaba, 2016; Nicholls and Murdock, 2012) that acknowledges that innovation is not only about developing new technologies and business models but also about ways to directly address social problems and grand societal challenges (Heiscala, 2007; Pol and Ville, 2009; Ghazinoory et al., 2020). In doing so, social innovators seek to change social relations (Pel et al., 2020) to achieve transformative change in institutional contexts and social practices (Van Wijk et al., 2019; Cajaiba-Santana, 2014), and “to improve either the quality or the quantity of life” especially for people on the margins of society (Pol and Ville, 2009, 881). In addressing systemic change, SI shows important similarities with institutional entrepreneurship (DiMaggio, 1988; Garud et al., 2002, 2007). Historical examples of important SIs include the introduction of building societies, cooperatives, new childcare and education models, antidiscrimination laws and other legislation, as well as more recently, microcredit and sustainability standards to address market failures (Mulgan, 2006; Phills et al., 2008; Pel et al., 2020). A SI perspective urges us to rethink the drivers and purposes of innovation (see also Zott and Amit, 2016). Fundamentally, SI combines a customer needs focus with an emphasis on social values and benefits for society (Gaparin et al., 2021). It thus extends the current understanding of the composition and purpose of systems of innovation. For example, taking the case of innovation that reduces air pollution in the US, Ghazinoory et al. (2020) reframe such innovations from the more conventional notion of technology or industry-driven innovations to the notion of innovations that utilize technology to address a fundamental social problem. Similarly, Audretsch and colleagues (2021) argue that the concept of the entrepreneurial ecosystem, including interrelated policies, norms, institutions and cultures, needs to be extended to account for SI (see also Mair and Gegenhuber, 2021; Manning and Vavilov, 2023). Also, SI extends our understanding of the factors enabling successful organizing to address large-scale societal challenges (George et al., 2012; Eisenhardt et al., 2016). One mechanism, for example, is “open social innovation”, in which networks of developers and contributors are mobilized to take part in SI contests (Chandra et al., 2021). In sum, the focus on SI helps develop a novel perspective connecting innovation studies with research on social problems and grand societal challenges. This chapter contributes to these efforts by bringing in another important perspective – the role of project-based organizing in SI. In the process of SI, projects may play a vital role in mobilizing support and changing social practice (Chandra et al., 2021). Examples include local community projects, civil rights 274

Organizing projects for social innovation  275

campaigns, crowdfunding projects, fundraising events, international development projects and institution-building projects, such as the development of new regulations and standards (see e.g. Mulgan, 2006; Manning and Von Hagen, 2010; Ika et al., 2020). Projects have the capacity to mobilize resources from critical stakeholders towards joint objectives (Søderlund, 2008), and they can take place at multiple levels – local, national and international (Ainamo et al., 2010; Manning and Von Hagen, 2010). Yet, our understanding of the opportunities and challenges of project-based organizing for SI is surprisingly limited. This chapter attempts to fill this gap by focusing on three important aspects of project-based organizing – project entrepreneurship, project capabilities and project network organizations – and their implications for SI. First, we characterize SI in more detail, followed by a description of three central challenges: (1) the embeddedness of social innovators in established structures; (2) the management of multiple stakeholders; and (3) the embedding of new solutions to achieve social change. We then discuss how project-based organizing addresses these challenges.

WHAT CHARACTERIZES SOCIAL INNOVATION? The growing interest in SI is motivated by the observation that innovation matters not only for the development of new technologies and products but for the transformation of social structures and practices as well (Mulgan, 2006; Pol and Ville, 2009). Accordingly, SI is often defined as a multi-level process to develop, implement and scale novel solutions to address social problems in specific institutional contexts (Van Wijk et  al., 2019; Cajaiba-Santana, 2014; Lawrence et al., 2014). By comparison, business innovations are often understood as technological and process innovations that aim to improve firm performance and result in profitability and commercial success (Pol and Ville, 2009; Nicholls et  al., 2015; Lawrence et  al., 2014; Oeij et  al., 2019). Before further examining SI (and the role of projects) it is important to determine in more detail how exactly SI is similar to and different from business innovation. Many scholars argue – and we agree – that SIs show some distinct characteristics that make them worth studying in their own right. We refer to this as the “narrow perspective” on SI. In this perspective, SIs are “motivated by the goal of meeting a social need” (Mulgan, 2006, 146). Specifically, they are oriented towards creating new or changing established social practices along with changes in cultural, normative or regulative structures (Heiscala, 2007; Neumeier, 2012). As highlighted by Cajaiba-Santana (2014, 45) “the outcomes of social innovation might be manifold, taking the form of new institutions, new social movements, new social practices, or different structures of collaborative work”. The locus of SI is not a particular organization, but typically the social system that the innovators inhabit (Phillips et al., 2015). That said, to promote SI, certain organizations may play a vital role in mobilizing and coordinating key stakeholders. Such intermediaries may include government agencies (Audretsch et al., 2021), non-profits (Maclean et al., 2013), social enterprises (Chalmers and Balan-Vnuk, 2013; Phillips et al., 2019), universities (Bellandi et al., 2021; Arocena and Sutz, 2021) and corporations (Mirvis and Googins, 2018; Dionisio and de Vargas, 2020). They are motivated to engage in SI due to government mandates (e.g. development agencies), their social mission and duties towards supporters (e.g. NGOs) or stakeholder expectations (e.g. firms). However, since SIs typically focus on social value creation for various disadvantaged

276  Handbook on innovation and project management

beneficiaries, they are typically not designed to primarily benefit the innovators but groups of people in line with the innovators’ social mission (Phillips et al., 2019). By comparison, what we call the “extended perspective” on SI includes “unintended” SIs in terms of side products or spillovers of business and technological innovations. In this view, some business innovations can be understood as “social innovations” insofar as they generate value well beyond an innovating firm or industry (Pol and Ville, 2009; Van der Have and Rubalcaba, 2016). For example, commercial innovations such as solar lanterns, water purification systems or low-cost laptops have not only changed the landscape of commercial products but created transformative change in the context of poverty. The main difference to SI in the more “narrow perspective” is that transformative effects in the “extended perspective” are not intended by any organization. Rather, social effects are spillovers that are – at least initially – not deliberately managed. Conceptualizing this type of innovating activity as “bifocal SIs”, Van der Have and Rubalcaba (2016) suggest that business innovation can turn into SI as innovators start to account for and manage positive and negative spillovers of innovative activity more deliberately. However, no matter whether SIs are intended or not, one key constituting factor is the social impact they generate. After all, SIs are about transformative change (Pel et al., 2020) and thus it is important to understand whether they actually address any social problem in substantial ways. Such impact can focus on different geographical levels – local, national/regional or global (see for examples Table 15.1). Measuring impact is important, for example, in the international development field, where innovation-based approaches are essential instruments to address social and environmental issues in the context of poverty (Dyck and Silvestre, 2019), and where innovators, such as NGOs and international development organizations, heavily rely on donor support (Watkins et al., 2012). Various approaches to detecting and measuring social impact exist. First, changes in law and legislation, or in the adoption of standards and codes of conduct, as a result of SI initiatives are often considered an important tangible outcome (see for examples Table 15.1; Mulgan, 2006; Pel et al., 2020). Second, many innovators adopt certain “theory of change” frameworks or “logic models of social impact” (see e.g. Ebrahim and Rangan, 2014) that help them measure not only “the immediate and measurable results of an organization” (Wry and Haugh, 2018, 4), e.g. the amount of green energy produced, but also the “the medium Table 15.1  Examples of social innovations Types of social innovation

Social impact at local level

Social impact at national/ regional level

Social innovation by design (narrow definition)

Local school Changes in law, e.g. programs, day care antidiscrimination laws, as facilities, cooperatives a result of campaigns

Social innovation as spillover of commercial / technological innovation (extended definition)

More inclusive employment through new platform-based work models in rural areas

More inclusive access to financial capital through mobile banking e.g. in subSaharan Africa

Social impact at global level Sustainable development goals; global labor standards; Fairtrade practices Increasing global access to information thanks to the Internet and the World Wide Web

Organizing projects for social innovation  277

and long-term effects of an organization’s outputs on the constituencies that it aspires to create value for” (5), e.g. effects on employment and poverty. Third, NGOs and development organizations increasingly adopt randomized controlled trials (RCT) as a very reliable way to measure the effectiveness of interventions. RCTs are applied increasingly also in education and public policy (Banerjee and Duflo, 2011).

THREE CHALLENGES OF SOCIAL INNOVATION Next, we discuss three major challenges of SI to focus our following discussion of projectbased organizing in the context of SI: (1) the challenge of embedded agency of a social innovator, (2) the challenge of managing critical stakeholders of a social system and (3) the challenge of embedding solutions to accomplish social change. The Challenge of Embedded Agency of a Social Innovator The first central challenge for any individual or organization driving SI – in short: “social innovators” – comes from the fact that social innovators are (and need to be) embedded to some extent in the very system they try to change. This is because, while social innovators seek to create social change, their ideas, plans and access to resources are embedded in existing social and institutional structures (Cajaiba-Santana, 2014). Engaging in SI thus requires social innovators to partly utilize existing structures but also to some degree “disembed” themselves from them, e.g. by distancing themselves from established templates, routines and practices that may relate to the very social problem they seek to address (Mair et al., 2012). Otherwise, rather than transforming social and institutional orders, the efforts of social innovators may run the risk of replicating existing structures and institutions (Van Wijk et al., 2019). In institutional theory, this problem is also known as the “paradox of embedded agency” of institutional entrepreneurs (Garud et al., 2007). Like social innovators, institutional entrepreneurs are actors who take an interest in leveraging resources to bring about new or changed institutions. However, in order to leverage resources they partially rely on established rules, frameworks and practices that legitimize and give meaning to their endeavours (see also Giddens, 1984). Thus, institutional entrepreneurs – and social innovators – must be socially skilled actors who are able to “narrate and theorize change in ways that give other social groups reasons to cooperate” (Garud et  al., 2007, 962). Framing, translation and reflective capacities are therefore important tools for social innovators to address entrenched social problems (Van Wijk et al., 2020). The Challenge of Managing Critical Stakeholders of a Social System The second challenge is associated with involving critical stakeholders in the process of SI and managing them to develop a shared understanding of social change. Because of their interactive nature and system-level focus, SIs are only possible through collective action (Cajaiba-Santana, 2014). While social innovators are highly important drivers of SI, SI does not emerge from the heroic actions of a single individual or organization but rather from the collective efforts of multiple stakeholders (Cajaiba-Santana, 2014). Thus, SI often requires the

278  Handbook on innovation and project management

inclusion of diverse stakeholders, including socially deprived groups, governments, communities, market actors, etc. (Oeij et al., 2019). More than commercial innovation, SI thereby often faces the challenge of powerful opposition from dominant groups, e.g. market actors opposing new environmental laws because they benefit from environmentally harmful business practices. SIs also often span geographic boundaries – interconnecting local communities and their specific needs with transnational networks of funders and supporters (Pel et al., 2020). In turn, the failure to involve and connect critical stakeholders can impede the success of SI (Lettice and Parekh, 2010). The need to engage critical stakeholders often requires the design of interactive spaces (van Wijk et al., 2019; Furnari, 2014) that allow these stakeholders to discuss and negotiate solutions for shared social problems. To create these spaces, social innovators engage in boundary work (Zietsma and Lawrence, 2010; Cartel et  al., 2019) to involve beneficiary individuals and groups. In these spaces, social innovators seek to establish a shared perspective among participants, elicit engagement and cooperation (Cajaiba-Santana, 2014), and manage political dynamics, tensions, resistance and conflict (Phills et al., 2008; Pol and Ville, 2009). The latter becomes important not least because social problems and innovations may look very different from different viewpoints (Nicholls et al., 2015). Social innovators therefore also engage in various forms of facilitation to “disembed” participants from established ways of thinking (Cartel et al., 2019; Mair et al., 2012). The Challenge of Embedding Solutions to Accomplish Social Change The third challenge is to embed a solution to a social problem into a wider set of norms, behaviours and practices (see also Garud et  al., 2007). Only when new ways of satisfying social needs can be embedded in the larger institutional context can a SI get acceptance and diffuse (Mair et al., 2012). Thus, the process of creating and implementing new solutions to social problems involves renegotiating established institutions or creating new system-level conditions that embed and reproduce the solution (Van Wijk et al., 2019). This challenge resembles the more general challenge of institutional change (e.g. Furnari, 2016; Hoffman, 1999). Prior studies have shown for example the importance of changing discourse in order to establish and legitimize new practices (Munir and Phillips, 2005). In the context of technological change, studies show that those innovations that combine familiar with novel design elements have a higher chance of being accepted, even if their introduction ultimately changes the social and institutional systems within which they are applied (Hargadon and Douglas, 2001). In the context of SI, this means that innovators face the challenge of developing and communicating new norms and practices that embody familiar elements in order for key stakeholders to accept them. Other studies also show the importance of setting up locally bounded proto-institutions to “test” the likelihood of effective institutional change (Lawrence et al., 2002). However, changes are effective only when they get embedded within interconnected configurations of practices, discourses, business models and regulatory structures (Levy et al., 2016; Van Wijk et al., 2013). At the same time, SIs are often dynamic and subject to continuous adjustments (Mulgan, 2006). One example is sustainability standards, i.e. sets of rules and practices that businesses commit to in order to regulate their social and environmental performance (see e.g. Reinecke et  al., 2012). The study by Manning and Reinecke (2016) shows that sustainability standards are “modular governance architectures” which may expand, thereby adding or adjusting

Organizing projects for social innovation  279

modular components over time, in line with changing expectations of critical stakeholders. This requires continuous SI and re-embedding of new solutions into emerging and changing frameworks.

SOCIAL INNOVATION AND PROJECT-BASED ORGANIZING In the process of SI, projects may play a vital role in mobilizing support and changing social practice (Chandra et al., 2021; Perkmann and Spicer, 2007). Projects can be defined as temporary systems that are constituted by multiple individual or organizational actors to accomplish rather complex and partially unique tasks within a limited timeframe (Lundin and Søderholm, 1995; Obstfeld, 2012). Projects have become an increasingly important form of organizing (Bakker et  al., 2011, 2016; Cattani et  al., 2011) not least because of their unique capacity to flexibly mobilize resources from multiple organizations to implement shared objectives (Søderlund, 2008). Projects are thus well-suited to promote both commercial innovation (e.g. Al-Laham and Amburgey, 2011; Du et al., 2014) and SI (Mulgan, 2006; Ika et al., 2020). In the context of the latter, examples of projects include local community projects, civil rights campaigns, crowdfunding projects, fundraising events, international development projects and institution-building projects, such as the development of new regulations and standards (see e.g. Hirschman, 1967; Perkmann and Spicer, 2007; Manning and Von Hagen, 2010; Ika et al., 2020). Next, we look more carefully at how and to what extent project-based organizing can help stimulate SI but also mitigate some of the challenges SI is associated with. Using examples from international development, film impact campaigns and other domains, we thereby focus on three important dimensions of project-based organizing at the individual, organizational and inter-organizational levels: project entrepreneurship (individual), project capabilities (organizational) and project network organizations (inter-organizational). Table 15.2 gives an overview of how all three aspects of project-based organizing address the major challenges of SI. Project Entrepreneurship One critical driver of both project-based organizing and SI is entrepreneurial action (DeFillippi and Arthur, 1998; Garud et  al., 2007). In general, entrepreneurial action is about forming and exploiting opportunities (Shane and Venkataraman, 2000; Alvarez and Barney, 2007). Opportunities may relate to “competitive imperfections” in markets and industries, social needs and demands, funding opportunities, etc. However, opportunities for action, innovation and change often remain dormant or invisible, unless individual entrepreneurs spot and exploit them (Shane, 2003). SI research therefore emphasizes that entrepreneurial individuals play a critical role in driving SI (Mulgan, 2006; Nicholls and Murdock, 2012). Likewise, the concept of “institutional entrepreneur” was initially reserved for particular individuals who take an interest in institutional change and who mobilize support towards that end (DiMaggio, 1988). To better understand and assess the role of entrepreneurial action in specific relation to projects driving SI, the concept of project entrepreneurship is critical. Project entrepreneurs have been typically defined as individuals who repeatedly develop and pursue project ideas and who assemble teams to implement these ideas (DeFillippi and Arthur, 1998;

280  Handbook on innovation and project management

Table 15.2  Addressing social innovation challenges through project-based organizing Addressing Challenges in Social Innovation Processes challenges of social Managing embedded Managing multiple innovation… agency of social innovators stakeholders

Embedding of solutions in practice

… through project Promotes combinations entrepreneurship of individual and organizational resources to mobilize and extend existing support structures Facilitates the discovery and creation of opportunities for social change Introduces reflexivity and continuous adaptation to social innovation processes

Promotes the creation and maintenance of individual networks with potential project stakeholders for related social innovation efforts Helps catalyze and link resources from multiple stakeholders while promoting project-based trust through repeated collaboration

Connects singular projects with each other by re-engaging project partners and by building on previously developed solutions. Helps in continuously revising social innovations by initiating new projects with old and new partners over time

… through project Helps establish capabilities mechanisms of “disembedding” projects from established structures, e.g. by setting rules to allow for creative experimentation outside established norms Promotes reflexivity and learning across projects to balance the needs for embedding / disembedding

Makes identification and selection of critical stakeholders a core element of project planning. Helps establish rules of stakeholder interaction that may deviate from established power structures to facilitate experimentation for systemic change

Helps establish sophisticated practices of measuring project success, including immediate outputs and long-term impacts May require alliances between organizations with different evaluation capacity

… through project network organizations

Allows multiple stakeholders to continuously work together on a projectby-project basis, but privileges those stakeholders who have the resources to do so

Provides platform for continuing projectbased adaptation of solutions, but is limited in enforcing mechanisms for change due to lean governance structures and limited resource commitments

Provides permanent social space for initiating projects around a shared agenda; Entails risk of re-introducing power structures that may hinder radical social change

Manning, 2010). Examples include film producers, research entrepreneurs and project leaders in NGOs, firms and development organizations (e.g. Manning, 2010; Manning and von Hagen, 2010). Project entrepreneurs are typically motivated by a combination of personal interests in particular projects and project-based careers, and their institutional role in the field or organization they operate in (Jones, 2001). For example, Manning (2010) studied an entrepreneurial

Organizing projects for social innovation  281

European researcher who developed a successful academic career by using his position as a university professor and his network to repeatedly apply for European funding in support of related projects. In the context of SI, Manning and Von Hagen (2010) show how entrepreneurial project managers at a German government-led development agency were able to repeatedly initiate public–private partnership projects with colleagues at major coffee roasters to experiment with more sustainable coffee growing practices in different local settings. These projects would drive the development of what became the Common Code for the Coffee Community – one of today’s major global coffee sustainability standards (Manning and Reinecke, 2016). Another example of project entrepreneurs in support of SI are so-called impact producers in film, i.e. campaign managers who use films as vehicles to change people’s minds and behaviours, and to stimulate changes in legislation (DocSociety, 2021). For example, campaign managers at the US-based production firm Participant Media were instrumental in supporting the Academy Award–winning film Roma and in launching impact campaigns in both Mexico and the US to strengthen the legal rights of domestic workers – one central theme of the film (Gilchrist, 2019). Next, we explore how project entrepreneurship can help mitigate the three major challenges of SI we discussed earlier: first, project entrepreneurship can help social innovators manage their embeddedness in both enabling and constraining systemic structures. In practice, project entrepreneurs often use their affiliations with employers – universities, NGOs, governments and development agencies – to mobilize teams and financial support for projects (Manning, 2010). To do so, however, they need to navigate the system in effective ways – by acting in the interest of powerful internal resource-holders, while stretching established frameworks of action in order to drive social and institutional change (see also Garud et al., 2007). For example, in order to develop and test new sustainable coffee growing practices (which later led to a global standard), the aforementioned project entrepreneur at the German development agency collaborated informally with expert partners at global coffee firms on a project-by-project basis even before any official cooperation with private partners was allowed by the overseeing government programme. These early experiments allowed this entrepreneur to pilot highly successful public–private partnership (PPP) projects at a time when his employer – the development agency – was eager to demonstrate their ability to carry out PPP projects after the PPP programme was officially launched by the government (Manning and Von Hagen, 2010). Project entrepreneurs can thus manage the dilemma of embedded agency in established structures by mobilizing their individual networks along with their individual reputations to drive new project ideas. Second, project entrepreneurship assists with the mobilization of critical stakeholders for systemic change. One central feature of project entrepreneurs is their ability to develop, maintain and mobilize individual networks of potential partners for particular types of projects (DeFillippi and Arthur, 1998; Manning, 2010). Projects may provide a shared context within which project entrepreneurs can develop a common language and common ground among critical stakeholders (Lenfle and Søderlund, 2019), e.g. by organizing and managing interactive spaces on a temporary basis to address and discuss social problems. Thereby, project entrepreneurs can develop and nurture relationships with critical stakeholders in a specific context of change on a project-by-project basis (see e.g. Manning and Von Hagen, 2010). For example, the Common Code for the Coffee Community (4C) is a global sustainability standard that was developed by multiple critical stakeholders in the coffee community – major global coffee roasters, coffee growing associations and NGOs. In mobilizing all these

282  Handbook on innovation and project management

stakeholders, project entrepreneurs played a vital role by repeatedly initiating interrelated projects in different countries with partially the same, partially new partners. Each project collaboration served to develop trust between different stakeholders in their ability to work together towards higher-level change (Manning and Von Hagen, 2010). Another example is film producer Amy Ziering and director Kirby Dick who jointly developed multiple documentaries on sexual assault – The Invisible War (2012) and The Hunting Ground (2015) – which in combination were instrumental in mobilizing leaders in media and society to support what would become the #MeToo movement (DocSociety, 2021). Project entrepreneurs can thus play a vital role in mobilizing critical stakeholders towards social change efforts on a project-byproject basis. Third, project entrepreneurs can mitigate the challenge of embedding new solutions into a broader institutional context. As temporary organizational forms, projects, on the one hand, have the benefit of providing a “protected space” within which new practices or solutions to collective problems can be developed and tested, based on limited investments of key stakeholders (see also Raven et al., 2010; Smith and Raven, 2012; Lawrence et al., 2014). On the other hand, projects typically have the limitation of “institutionalized termination” (Lundin and Søderholm, 1995). When projects end, project teams often dissolve and it is highly uncertain whether project objectives will be followed up on beyond particular projects. This has always been a major concern in the context of foreign aid and development (Hirschman, 1967). Yet, project entrepreneurs can exploit the experimental flexibility of projects while also – to some extent – promoting the embeddedness of SI into a broader systemic context. The key to this is the capacity of project entrepreneurs to repeatedly initiate interrelated projects (Manning, 2010). This role of project entrepreneurs is well-understood in the film industry, where new project ideas are often legitimized in reference to previous successful projects in related domains (Manning and Sydow, 2011). This principle is now used by impact producers who often engage in multiple interrelated projects over time to drive a common agenda of social change. In other contexts, such as research and foreign aid, projects also build onto each other, accumulate knowledge and incrementally drive systemic change (Manning, 2017). For example, in the context of sustainability standards, project entrepreneurs often initiate pilot projects to develop and test new sustainable practices and then use follow-up projects with the same or new partners to further refine and adapt these practices (Manning and Von Hagen, 2010). This allows SIs, such as sustainable coffee growing practices, to become more robust and sophisticated over time, while also becoming more adaptable in different contexts of application (Manning and Reinecke, 2016). However, more research is needed to more fully understand the benefits and limitations of project entrepreneurship in the pursuit of SI. For example, if indeed the involvement of project entrepreneurs is critical in driving SI, how might the individual interests and career aspirations of these entrepreneurs affect the success of SI processes? Also, how do project entrepreneurs in the context of SI actually spot “entrepreneurial opportunities” and what is guiding the idea development process, especially if it is outside any organizational agenda? Project Capabilities Another important driver of both project-based organizing and SI is organizational capabilities. In general, capabilities refer to reliable, more or less organizationally specific patterns of resource allocation, management and problem-solving (see e.g. Schreyoegg and

Organizing projects for social innovation  283

Kliesch-Eberl, 2007). More specifically, in the context of innovation, such capabilities may refer to practices of generating and transforming ideas into new products, services and processes (e.g. Lawson and Samson, 2001). One important element of such capabilities, for any innovation, is the ability to organize projects in pursuit of innovations. However, since, by definition, each project is to some extent unique and unpredictable (Lundin and Søderholm, 1995; Obstfeld, 2012), being able to develop reliable, yet flexible organizational capabilities for innovation projects is a challenging task – even more so when projects aim for structural or systemic changes like in the case of SI. To better examine this challenge, we focus, in the following, specifically on so-called project capabilities which can be defined as sets of managerial knowledge, skills and experience that are located and accumulated within organizations (e.g. project-based firms) to establish, coordinate and execute projects (Brady and Davies, 2004; Davies and Brady, 2016). Established project capabilities within a particular organization could be conceived as a type of operational capability (Helfat and Peteraf, 2003) whose recurrent application allows us to manage similar projects over time. This is why project-based organizations are as important as individual project entrepreneurs in getting projects done. While the latter drive project ideas and the mobilization of teams, the former provide knowledge, routines and resources that entrepreneurs employ in the process. When project-based organizations seek to engage in projects that differ from “routine projects” in terms of their goals, resources, markets and technology – so-called innovative projects (Brady and Davies, 2004) – they may develop new project capabilities, especially if those innovative projects are followed up on by similar projects over time. In the context of SI, for example, campaign management agencies that specialize in running campaigns, events and rallies for social causes may develop campaign management capabilities that allow them to draw on familiar practices – marketing, team-building etc. – in order to professionalize campaigns. Likewise, development agencies develop certain project capabilities regarding project planning, stakeholder involvement, project evaluation, etc. that allow them to increase the effectiveness of development projects (Hirschman, 1967). Impact production firms in film develop special capabilities related to identifying film projects with impact potential, pitching projects to funding partners, running impact campaigns alongside film distribution and measuring impact for various stakeholders (DocSociety, 2021). Project capabilities often emerge from vanguard projects (Frederiksen and Davies, 2008), which allow for exploring new project practices through trial-and-error learning and experimenting with innovative combinations of resources and capabilities (Brown and Duguid, 2000; Davies and Brady, 2016). To design and conduct vanguard projects, project-based organizations utilize their existing project capabilities to provide a vanguard project team with resources, expertise and experimentation space (Frederiksen and Davies, 2008). The knowledge gained from a vanguard project is captured and transferred to subsequent projects through project-to-project learning. One important challenge in developing project capabilities is the tension between providing some predictability in how projects are organized while at the same time being adaptable to changing demands and environmental opportunities. Brady and Davies (2016) suggest analytically distinguishing between operational (and often rather routine-based) project capabilities and higher-level “dynamic capabilities” that allow organizations to spot new opportunities, revise existing organizational templates and expand the portfolio of project capabilities. Similarly, in strategic management, dynamic capabilities were introduced to capture the idea

284  Handbook on innovation and project management

of continuous “renewal” and “adaptation” (Teece et al., 1997). At the same time, critics like Schreyoegg and Kliesch-Eberl (2007) have pointed out that in order for capabilities to provide some level of stability and predictability they should not be inherently “dynamic”. Instead, similar to the conception of Brady and Davies (2016), they suggest a “dual-process model of capability dynamization” by distinguishing established capabilities at the operational level (e.g. project capabilities) from capabilities at the “observational level” that allow for continuous monitoring of environmental changes and revisions in capability development. Next, we discuss in more detail how project capabilities (along with the capacity to revise and extend them) can help mitigate the three major challenges of SI we introduced earlier. First, project capabilities can help social innovators deal with their dilemma of being embedded in both enabling and constraining social structures. Prior studies suggest that, for example, the effectiveness of international development projects that aim for social and economic change depends on their ability to elicit trial-and-error experimentation with new social and economic practices (Ika and Donnelly, 2017; Ika et  al., 2020; McKaque et  al., 2015). For example, the value of local sustainability projects in various countries leading up to the formation of the Common Code for the Coffee Community lay in lessons learnt from locally embedded experimentation with new farming practices, quality control systems, etc. (Manning and von Hagen, 2010). In order to allow for such experimentation on a regular basis, project-based organizations, such as development agencies, need to develop project capabilities that include the creation of spaces for experimentation and the inclusion of multiple stakeholders (see also Furnari, 2014). Especially, such spaces need to be protected against the pressures and norms of established structures – a requirement that is well known in the context of sustainability transitions (Smith and Raven, 2012; Coenen et al., 2012). This may also involve allowing project partners to interact in ways that may deviate from established norms and practices in order to “test” the implications of structural or systemic changes. One good example of such a purposeful deviation is the “law of two feet” in Open Space large group meetings (see e.g. Owen, 1993) that authorizes all participants – no matter what social status they have outside the meeting – to stand up and leave any sub-meetings during the Open Space if they feel that they can neither contribute to nor benefit from a given discussion or debate. This norm helps unfreeze established power structures to facilitate knowledge exchange towards collective solutions everybody can agree on. Second, project capabilities in support of SI can be designed in a way to facilitate the involvement of critical stakeholders without whom actual change at the system level would not be possible. In the context of development, for example, it is critical to identify multiple stakeholders for every project who will be involved in supporting and implementing project goals, including donors, local partners, consultants, policymakers, local authorities and target beneficiaries or communities (Lannon and Walsh, 2020). Similarly, in the context of organizing large group intervention meetings, such as Open Space or Future Search, identifying the right stakeholders is key in order for these meetings to be productive (Weisbord and Janoff, 2005). One way in which social innovators can develop their stakeholder management capacity is by forming long-term partnerships with support organizations that can be mobilized for multiple projects. For example, the film impact funding organization DocSociety works with several funding partners they can mobilize across projects based on prior collaborative experience (DocSociety, 2021).

Organizing projects for social innovation  285

However, multi-stakeholder projects are often embedded in multiple institutional contexts at the same time (Cartel et al., 2019). This may lead to misalignments, for example between the interests and needs of local communities and the vision of international donors. Based on the study of a Dutch development organization that was engaged in making the dairy value chain in Ethiopia more inclusive, Van Wijk et al. (2020) find that various misalignments between the vision of the donor and the contextual conditions on the ground were responsible for project failures. More specifically, the lack of local knowledge and overreliance on experience constrained the ability of the organization to identify and engage with relevant local parties. It is thus important for project capabilities, such as stakeholder identification, to be subject to continuous monitoring and adjustment across contexts. This is why higher-level “observational” capabilities are key. Also, more than in the case of commercial innovation, effective SI projects require a commitment of lead organizations to address multiple stakeholders simultaneously rather than treating certain stakeholders as more important than others (Ika and Donnelly, 2017). This implies that multiple stakeholders also need to get involved in project planning from early on rather than being invited later (Mikovic et al., 2020). This multi-stakeholder orientation also facilitates communication about project progress and project value as well as continuous multi-stakeholder engagement (Yalegama et al., 2016). Third, project capabilities in support of SI need to also prepare for the challenge of embedding solutions in larger structures to promote effective change. In this regard, assessing project performance becomes critical. In particular, these types of project performance are distinguished: (1) project outputs, i.e. the immediate and measurable results of an organization’s SI pursuits; (2) project outcomes, i.e. lasting changes in the lives of individuals; and (3) project impact, i.e. lasting results achieved at a community or societal level (see Ebrahim and Rangan, 2014; Wry and Haugh, 2018). Focusing on outputs, outcomes and impact of projects, project-based organizations need to engage in various monitoring and evaluation activities that often start before a project is launched to create a baseline to compare against, and that might continue several years after the project is implemented. These evaluation practices need to be embedded in project capabilities as well as higher-level capabilities across different project types. While it can be relatively straightforward to assess immediate and measurable outputs of a project, such as the number of solar lanterns provided or the number of wells dug, the longerterm outcomes of the project on individuals and its systemic impact on a large-scale problem can only be understood over time. Since many organizations that specialize in SI projects are relatively small and resource constrained, such as NGOs and campaign agencies, assessing longer-term project impacts can be a challenge. Ebrahim and Ragnar (2014) therefore suggest that social mission-driven organizations should focus on measuring short-term project outputs and outcomes, whereas resource-rich organizations, such as foundations and impact investors, can take on the challenge of measuring and evaluating long-term systemic impacts. For example, organizations like Innovation for Poverty Action and J-PAL specialize in bringing together development organizations and development economists who use sophisticated techniques, such as randomized controlled trials, to measure the impact of particular interventions on social problems. Another strategy is to build long-term partnerships beyond specific projects with various impact assessment providers. This is what the impact funding organization DocSociety has done by working with specialized partners to measure to what extent

286  Handbook on innovation and project management

films and campaigns have changed people’s minds and behaviours or changed regulations and institutional structures (DocSociety, 2021). To summarize, project capabilities can be a useful means to tackle some of the major challenges of SI. However, we need more research to better understand the potential and limitations of project capabilities in this context. For example, if indeed one major challenge relates to the effective involvement of multiple stakeholders on a project-by-project basis, this raises the question of how or to what extent these stakeholders also need to get involved in developing suitable project capabilities. Also, to what extent can project capabilities really prepare for the complexity and uncertainty involved in systemic change? Finally, which organizational forms or structures are best suited to support the development and adaptation of project capabilities in support of SI? Next, we elaborate on one such structure – project network organizations. Project Network Organizations In project-based organizing and SI, inter-organizational networks play an important role. In most project businesses, so-called “project ecologies” emerge in which projects and project teams emerge from longer-lasting, yet dynamic network relationships (Grabher, 2004; Ferriani et al., 2009). Prior network ties may both enable and constrain the initiation of projects, team formation and project success (Sorensen and Waguespack, 2006; Schwab and Miner, 2008). Similarly, SI processes are often embedded in, and thereby enabled and constrained by, local and global networks of critical stakeholders (Oeij et al., 2019; Pel et al., 2020). While network ties can affect projects and SI in various ways, we focus here on the role of so-called “project networks”, and more specifically, “project network organizations” (PNOs). PNOs consist of “legally independent, yet operationally interdependent individuals and organizations who maintain longer-term collaborative relationships beyond the time limitations of particular projects” (Manning, 2017, 1399). Unlike project-based organizations, PNOs reach beyond the boundaries of any particular organization, incorporating multiple partners for related projects. At the same time, unlike more fluid and “boundaryless” networks, PNOs are typically strategically led and have a collective coordination capacity that enables partners to repeatedly team up for projects. PNOs form around core teams that repeatedly collaborate, but they also include flexible partner pools which are mobilized to recruit ad-hoc partners who can complement core teams for specific projects (Manning, 2010, 2017; Starkey et al., 2000). In the strategic development and coordination of PNOs, both project-based lead firms and individual project entrepreneurs can play a key role. PNOs have been studied mainly in creative industries (Grabher, 2002; Starkey et al., 2000), construction (Eccles, 1981), collaborative research (Manning, 2010) and international development (Manning and von Hagen, 2010). Even though PNOs have not been discussed much in the context of SI, their potential importance can be derived from anecdotal evidence. Earlier we mentioned the role of project entrepreneurs in initiating projects in support of SI. As part of such efforts, project entrepreneurs often build PNOs together with core project partners as a more permanent governance structure to assist the launch of new projects. PNOs may be incorporated in so-called “metaorganizations” (Berkowitz and Dumez, 2016) whose organizational members repeatedly team up for SI projects. One example is the Roundtable for Sustainable Palmoil (RSPO) which regulates the RSPO standard but also serves as a platform for particular project initiatives (Carmagnac and Carbone, 2019). In other cases, PNOs may be more informal by connecting core project partners beyond the time limitations of single projects. Examples include PNOs

Organizing projects for social innovation  287

in the context of film production in general (see e.g. Manning and Sydow, 2011) and impact campaigns around film in particular. In this context, certain directors, impact producers and funding organizations may form core project teams that come together repeatedly to run filmbased social change campaigns. Such longer-term ties help develop and maintain trust and collaborative routines in support of joint projects and larger social change agendas. The creative team behind the two documentaries The Invisible War and The Hunting Ground (see earlier) is a good example. Next, we discuss how PNOs may mitigate the three main SI challenges introduced earlier. First, PNOs can help manage the social innovator’s challenge of being embedded in both enabling and constraining social structures by establishing an organizational context – the PNO – which serves as a social space within which particular SI objectives can be pursued beyond just one particular project. Instead, PNOs are typically set up around a particular issue and thus help concentrate resources and commitments of participating organizations and individuals around that issue on a project-by-project basis (see also Chaudhury et al., 2016). However, like metaorganizations in general, PNOs typically have very lean governance structures and little overhead, thus depending a lot on resources from their member organizations (Berkowitz and Bor, 2018). This re-introduces the problem of embedded agency. For example, the development of multi-stakeholder standards, such as RSPO or 4C, has been strongly influenced by the interests of powerful corporate members of the meta-organizations that develop the standards. This has arguably limited the extent to which sustainability standards can radically deviate from established practices of commodity food production (see also Levy et al., 2016). Second, and relatedly, PNOs have the potential to mobilize and retain critical stakeholders for SI (Berkowitz and Dumez, 2016; Chaudhury et al., 2016), yet they need to find a balance between being open and flexible enough to incorporate various diverse stakeholder interests and being specific enough in their agenda to effectively initiate projects in support of SI objectives (Berkowitz et al., 2020). One way to manage this balance is through effective governance structures that facilitate the collective decision-making of core partners (Carmagnac and Carbone, 2019; Scherer and Palazzo, 2007). For example, in film production, certain routines of project idea development can emerge among core project partners over time (Manning and Sydow, 2011). However, PNOs may also (re-) produce power disparities between different project partners. For example, the PNO that was set up to support the launch of pilot projects for what would become the Common Code for the Coffee Community displayed a global–local divide (Manning and Von Hagen, 2010): whereas the agenda for most pilot projects was mainly determined by globally operating partners – coffee roasters and a development agency – who repeatedly worked together across the world, local partners, e.g. coffee growers, only had a say in setting up local projects, but had very limited influence on the global agenda of the PNO. Third, evidence for the ability of PNOs to help embed new solutions into a broader institutional context is equally mixed. One main strength of PNOs is their governance flexibility and their capacity to serve as platforms for the continuous launch of innovative projects (Manning and Von Hagen, 2010; Carmagnac and Carbone, 2019). Accordingly, Manning and Reinecke (2016) link such meta-organizations to what they call a “modular governance architecture” that helps continuously adapt and expand SIs, such as sustainability standards. However, one major weakness of PNOs – like meta-organizations in general – is their limited enforcement capacity as a collective body (Ahrne et al., 2016; Carmagnac and Carbone, 2019). As mentioned earlier, the resource base of PNOs is typically thin and the resource commitments of participating partners are often limited to the objectives of particular projects.

288  Handbook on innovation and project management

Based on this brief review, we encourage future studies to further look into variations of PNOs in support of SIs. For example, while there is substantial research on meta-organizations and PNOs in support of sustainability standards, we need to better understand how they are similar to or different from PNOs in the context of human rights campaigns and other SI processes. Also, addressing the problem of embedding solutions and committing stakeholders to longer-term change, it seems critical to study how PNOs may be linked to more stable and institutionalized organizational structures and legal systems in support of new practices and regulations.

CONCLUSION AND OUTLOOK This chapter has reviewed important features of SI along with three key challenges – (1) the embeddedness of social innovators in established structures; (2) the management of multiple stakeholders; and (3) the embedding of new solutions in social practice to achieve social change. We then discussed the extent to which project entrepreneurs, project capabilities and project network organizations can help address these challenges. Going forward, we invite future research to build on these insights, while also considering other promising avenues of research interlinking SI with project organizing. For example, one could study the role of projects in translating commercial innovations into SIs and vice versa. As argued here, the boundaries between these two types are often fluid, yet we know little about the mechanisms promoting “spillovers” across these domains. Also, one could examine further the role of technology-enabled platforms in assisting SI projects, including crowdfunding. For example, to what extent does the increasing demand for crowdfunding generate a new market for intermediaries specializing in running campaigns for SI? Finally, we need to better understand the interlinkage of project-based organizing with other forms of organizing in support of SI.

REFERENCES Ahrne, G., Brunsson, N., and Seidl, D. (2016). Resurrecting organization by going beyond organizations. European Management Journal, 34(2), 93–101. Ainamo, A., Artto, K., Levitt, R.E., Orr, R.J., Scott, W.R., and Tainio, R. (2010). Global projects: Strategic perspectives. Scandinavian Journal of Management, 26(4), 343–351. Al-Laham, A. and Amburgey, T.L. (2011). Staying local or reaching globally? Analyzing structural characteristics of project-based networks in German biotech. Advances in Strategic Management, 28, 323–356. Alvarez, S.A. and Barney, J.B. (2007). Discovery and creation: Alternative theories of entrepreneurial action. Strategic Entrepreneurship Journal, 1(1–2), 11–26. Amit, R. and Zott, C. (2016). Business model design: A dynamic capability perspective. In D. J. Teece and S. Leih (Eds.). The Oxford handbook of dynamic capabilities. Oxford University Press. Arocena, R. and Sutz, J. (2021). Universities and social innovation for global sustainable development as seen from the south. Technological Forecasting and Social Change, 162, 120399. Audretsch, D.B., Eichler, G.M., and Schwarz, E.J. (2021). Emerging needs of social innovators and social innovation ecosystems. International Entrepreneurship and Management Journal, 18, 217–254. Bakker, R.M., Cambré, B., Korlaar, L., and Raab, J. (2011). Managing the project learning paradox: A set-theoretic approach toward project knowledge transfer. International Journal of Project Management, 29(5), 494–503.

Organizing projects for social innovation  289

Bakker, R.M., DeFillippi, R.J., Schwab, A., and Sydow, J. (2016). Temporary organizing: Promises, processes, problems. Organization Studies, 37(12), 1703–1719. Banerjee, A. and Duflo, E. (2011). Poor economics, New York: Public Affairs. Bellandi, M., Donati, L., and Cataneo, A. (2021). Social innovation governance and the role of universities: Cases of quadruple helix partnerships in Italy. Technological Forecasting and Social Change, 164, 120518. Berkowitz, H. and Bor, S. (2018). Why meta-organizations matter: A response to Lawton et  al. and Spillman. Journal of Management Inquiry, 27(2), 204–211. Berkowitz, H. Crowder, L.B., and Brooks, C.M. (2020). Organizational perspectives on sustainable ocean governance: A multi-stakeholder, meta-organization model of collective action. Marine Policy, 118, 104026. Berkowitz, H. and Dumez, H. (2016). The concept of meta‐organization: Issues for management studies. European Management Review, 13(2), 149–156. Brady, T. and Davies, A. (2004). Building project capabilities: From exploratory to exploitative learning. Organization Studies, 25(9), 1601–1621. Brown, J.S. and Duguid, P. (2000). Balancing act: How to capture knowledge without killing it. Harvard Business Review, 78(3), 73–80. Cajaiba-Santana, G. (2014). Social innovation: Moving the field forward. A conceptual framework. Technological Forecasting and Social Change, 82, 42–51. Carmagnac, L. and Carbone, V. (2019). Making supply networks more sustainable “together”: The role of meta-organisations. Supply Chain Forum: An International Journal, 20(1), 56–67. Cartel, M., Boxenbaum, E., and Aggeri, F. (2019). Just for fun! How experimental spaces stimulate innovation in institutionalized fields. Organization Studies, 40(1), 65–92. Cattani, G., Ferriani, S., Frederiksen, L., and Täube, F. (2011). Project-based organizing and strategic management: A long-term research agenda on temporary organizational forms. Emerald Group Publishing Limited. Chalmers, D.M. and Balan-Vnuk, E. (2013). Innovating not-for-profit social ventures: Exploring the microfoundations of internal and external absorptive capacity routines. International Small Business Journal, 31(7), 785–810. Chandra, Y., Shang, L., and Mair, J. (2021). Drivers of success in social innovation: Insights into competition in open social innovation contest. Journal of Business Venturing Insights, 16, e00257. Chaudhury, A.S., Ventresca, M.J., Thornton, T.F., Helfgott, A., Sova, C., Baral, P., Rasheed, T., and Ligthart, J. (2016). Emerging meta-organisations and adaptation to global climate change: Evidence from implementing adaptation in Nepal, Pakistan and Ghana. Global Environmental Change, 38, 243–257. Chesbrough, H. and Di Minin, A. (2014). Open social innovation. New Frontiers in Open Innovation, 16, 301–315. Coenen, L., Benneworth, P., and Truffer, B. (2012). Toward a spatial perspective on sustainability transitions. Research Policy, 41(6), 968–979. Davies, A. and Brady, T. (2016). Explicating the dynamics of project capabilities. International Journal of Project Management, 34(2), 314–327. DeFillippi, R.J. and Arthur, M.B. (1998). Paradox in project-based enterprise: The case of film making. California Management Review, 40(2), 125–139. DiMaggio, P.J. (1988). Interest and agency in institutional theory. In L.G. Zucker (Eds.), Institutional patterns and organizations: Culture and environment (pp. 3–21). Cambridge, MA: Ballinger. Dionisio, M. and de Vargas, E.R. (2020). Corporate social innovation: A systematic literature review. International Business Review, 29(2), 101641. DocSociety (2021). The impact field guide & toolkit. From art to impact. Impactguide​.org​. Accessed 1 October 2021. Du, J., Leten, B., and Vanhaverbeke, W. (2014). Managing open innovation projects with science-based and market-based partners. Research Policy, 43, 828–840. Dyck, B. and Silvestre, B.S. (2019). A novel NGO approach to facilitate the adoption of sustainable innovations in low-income countries: Lessons from small-scale farms in Nicaragua. Organization Studies, 40(3), 443–461. Ebrahim, A. and Rangan, V.K. (2014). What impact? A framework for measuring the scale and scope of social performance. California Management Review, 56(3), 118–141.

290  Handbook on innovation and project management

Eccles, R.G. (1981). Bureaucratic versus craft administration: The relationship of market structure to the construction firm. Administrative Science Quarterly, 26 (3), 449–469. Eisenhardt, K.M., Graebner, M.E., and Sonenshein, S. (2016). Grand challenges and inductive methods: Rigor without rigor mortis. Academy of Management Journal, 59(4), 1113–1123. Ferriani, S., Cattani, G., and Baden-Fuller, C. (2009). The relational antecedents of projectentrepreneurship: Network centrality, team composition and project performance. Research Policy, 38(10), 1545–1558. Frederiksen, L. and Davies, A. (2008). Vanguards and ventures: Projects as vehicles for corporate entrepreneurship. International Journal of Project Management, 26(5), 487–496. Furnari, S. (2014). Interstitial spaces: Microinteraction settings and the genesis of new practices between institutional fields. Academy of Management Review, 39(4), 439–462. Furnari, S. (2016). Institutional fields as linked arenas: Inter-field resource dependence, institutional work and institutional change. Human Relations, 69(3), 551–580. Garud, R., Hardy, C., and Maguire, S. (2007). Institutional entrepreneurship as embedded agency: An introduction to the special issue. Organization Studies, 28(7), 957–969. Garud, R., Jain, S., and Kumaraswamy, A. (2002). Institutional entrepreneurship in the sponsorship of common technological standards: The case of Sun Microsystems and Java. Academy of Management Journal, 45(1), 196–214. George, G., McGahan, A.M., and Prabhu, J. (2012). Innovation for inclusive growth: Towards a theoretical framework and a research agenda. Journal of Management Studies, 49(4), 661–683. Ghazinoory, S., Nasri, S., Ameri, F., Montazer, G.A., and Shayan, A. (2020). Why do we need “Problemoriented Innovation System (PIS)” for solving macro-level societal problems? Technological Forecasting and Social Change, 150, 119749. Giddens, A. (1984). The constitution of society: Outline of the theory of structuration. University of California Press. Gilchrist, T.E. (2019). Participant media creates entertainment for social change. Stanford Social Innovation Review, 28 October, https://phi​lant​h rop​ynew​sdigest​.org​/columns​/ssir​-pnd​/participant​ -media​-creates​-entertainment​-for​-social​-change Grabher, G. (2002). The project ecology of advertising: Tasks, talents and teams. Regional Studies, 36(3), 245–262. Grabher, G. (2004). Temporary architectures of learning: Knowledge governance in project ecologies. Organization Studies, 25(9), 1491–1514. Hargadon, A.B. and Douglas, Y. (2001). When innovations meet institutions: Edison and the design of the electric light. Administrative Science Quarterly, 46(3), 476–501. Heiskala, R. (2007). Social innovations: Structural and power perspectives. Social Innovations, Institutional Change and Economic Performance, 1, 52–79. Helfat, C.E. and Peteraf, M.A. (2003). The dynamic resource‐based view: Capability lifecycles. Strategic Management Journal, 24(10), 997–1010. Hirschman, A.O. (1967). Development projects observed, Washington, DC: Brookings Institution. Hoffman, A.J. (1999). Institutional evolution and change: Environmentalism and the US chemical industry. Academy of Management Journal, 42(4), 351–371. Howaldt, J., Kaletka, C., Schröder, A., and Zimgiebl, M. (2018). Atlas of social innovation: New practices for a better future. Dortmund: Technische Universität Dortmund, ZWE Sozialforschungsstelle. Ika, L.A. and Donnelly, J. (2017). Success conditions for international development capacity building projects. International Journal of Project Management, 35(1), 44–63. Ika, L.A., Søderlund, J., Munro, L.T., and Landoni, P. (2020). When project management meets international development, what can we learn? International Journal of Project Management, 38(8), 469–473. Jones, C. (2001). Co-evolution of entrepreneurial careers, institutional rules and competitive dynamics in American Film, 1895–1920. Organization Studies, 22(6), 911–944. Lannon, J. and Walsh, J.N. (2020). Project facilitation as an active response to tensions in international development programmes. International Journal of Project Management, 38(8), 486–499. Lawrence, T.B., Dover, G., and Gallagher, B. (2014). Managing social innovation. In M. Dodgson, D. Gann, and N. Phillips (Eds.), Oxford handbook of innovation management (pp. 316–334). Oxford, UK: Oxford University Press.

Organizing projects for social innovation  291

Lawrence, T.B., Hardy, C., and Phillips, N. (2002). Institutional effects of interorganizational collaboration: The emergence of proto-institutions. Academy of Management Journal, 45(1), 281–290. Lawson, B. and Samson, D. (2001). Developing innovation capability in organisations: A dynamic capabilities approach. International Journal of Innovation Management, 5(3), 377–400. Lenfle, S. and Søderlund, J. (2019). Large-scale innovative projects as temporary trading zones: Toward an interlanguage theory. Organization Studies, 40(11), 1713–1739. Lettice, F. and Parekh, M. (2010). The social innovation process: Themes, challenges and implications for practice. International Journal of Technology Management, 51(1), 139–158. Levy, D., Reinecke, J., and Manning, S. (2016). The political dynamics of sustainable coffee: Contested value regimes and the transformation of sustainability. Journal of Management Studies, 53(3), 364–401. Lundin, R.A. and Søderholm, A. (1995). A theory of the temporary organization. Scandinavian Journal of Management, 11(4), 437–455. Maclean, M., Harvey, C., and Gordon, J. (2013). Social innovation, social entrepreneurship and the practice of contemporary entrepreneurial philanthropy. International Small Business Journal, 31(7), 747–763. Mair, J. and Gegenhuber, T. (2021). Open social innovation. Stanford Social Innovation Review, 19, 26–33.. Mair, J., Marti, I., and Ventresca, M.J. (2012). Building inclusive markets in rural Bangladesh: How intermediaries work institutional voids. Academy of Management Journal, 55(4), 819–850. Manning, S. (2010). The strategic formation of project networks: A relational practice perspective. Human Relations, 63(4), 551–573. Manning, S. (2017). The rise of project network organizations: Building core teams and flexible partner pools for interorganizational projects. Research Policy, 46(8), 1399–1415. Manning, S. and Reinecke, J. (2016). A modular governance architecture in-the-making: How transnational standard-setters govern sustainability transitions. Research Policy, 45(3), 618–633. Manning, S. and Sydow, J. (2011). Projects, paths, and practices: Sustaining and leveraging projectbased relationships. Industrial and Corporate Change, 20(5), 1369–1402. Manning, S. and Vavilov, S. (2023). Global development agenda meets local opportunities: The rise of development-focused entrepreneurship support. Research Policy, forthcoming. Manning, S. and Von Hagen, O. (2010). Linking local experiments to global standards: How project networks promote global institution-building. Scandinavian Journal of Management, 26(4), 398–416. McKague, K., Zietsma, C., and Oliver, C. (2015). Building the social structure of a market. Organization Studies, 36(8), 1063–1093. Miković, R., Petrović, D., Mihić, M., Obradović, V., and Todorović, M. (2020). The integration of social capital and knowledge management–The key challenge for international development and cooperation projects of nonprofit organizations. International Journal of Project Management, 38(8), 515–533. Mirvis, P. and Googins, B. (2018). Engaging employees as social innovators. California Management Review, 60(4), 25–50. Mulgan, G. (2006). The process of social innovation. Innovations: Technology, Governance, Globalization, 1(2), 145–162. Munir, K.A. and Phillips, N. (2005). The birth of the “Kodak Moment”: Institutional entrepreneurship and the adoption of new technologies. Organization Studies, 26(11), 1665–1687. Neumeier, S. (2012). Why do social innovations in rural development matter and should they be considered more seriously in rural development research?–Proposal for a stronger focus on social innovations in rural development research. Sociologia Ruralis, 52(1), 48–69. Nicholls, A. and Murdock, A. (2012). The nature of social innovation. In A. Nicholls and A. Murdock (Eds.), Social innovation (pp. 1–30). London: Palgrave Macmillan. Nicholls, A., Simon, J., and Gabriel, M. (2015). Introduction: Dimensions of social innovation. In A. Nicholls, J. Simon, and M. Gabriel (Eds.), New frontiers in social innovation research (pp. 1–26). London: Palgrave Macmillan. Obstfeld, D. (2012). Creative projects: A less routine approach toward getting new things done. Organization Science, 23(6), 1571–1592.

292  Handbook on innovation and project management

Oeij, P.R., Van Der Torre, W., Vaas, F., and Dhondt, S. (2019). Understanding social innovation as an innovation process: Applying the innovation journey model. Journal of Business Research, 101, 243–254. Owen, H. (1993). Open space technology: A user’s guide. Oakland, CA: Berrett-Koehler Publishers.. Pel, B., Haxeltine, A., Avelino, F., Dumitru, A., Kemp, R., Bauler, T., Kunze, I., Dorland, J., Wittmayer, J., and Jørgensen, M.S. (2020). Towards a theory of transformative social innovation: A relational framework and 12 propositions. Research Policy, 49(8), 104080. Perkmann, M. and Spicer, A. (2007). Healing the scars of history: Projects, skills and field strategies in institutional entrepreneurship. Organization Studies, 28(7), 1101–1122. Phillips, W., Alexander, E.A., and Lee, H. (2019). Going it alone won’t work! The relational imperative for social innovation in social enterprises. Journal of Business Ethics, 156(2), 315–331. Phillips, W., Lee, H., Ghobadian, A., O’Regan, N., and James, P. (2015). Social innovation and social entrepreneurship: A systematic review. Group and Organization Management, 40(3), 428–461. Phills, J.A., Deiglmeier, K., and Miller, D.T. (2008). Rediscovering social innovation. Stanford Social Innovation Review, 6(4), 34–43. Pol, E. and Ville, S. (2009). Social innovation: Buzz word or enduring term? The Journal of SocioEconomics, 38(6), 878–885. Raven, R., Van den Bosch, S., and Weterings, R. (2010). Transitions and strategic niche management: Towards a competence kit for practitioners. International Journal of Technology Management, 51(1), 57–74. Reinecke, J., Manning, S., and Von Hagen, O. (2012). The emergence of a standards market: Multiplicity of sustainability standards in the global coffee industry. Organization Studies, 33(5–6), 791–814. Scherer, A.G. and Palazzo, G. (2007). Toward a political conception of corporate responsibility: Business and society seen from a Habermasian perspective. Academy of Management Review, 32(4), 1096–1120. Schreyögg, G. and Kliesch‐Eberl, M. (2007). How dynamic can organizational capabilities be? Towards a dual‐process model of capability dynamization. Strategic Management Journal, 28(9), 913–933. Schwab, A. and Miner, A.S. (2008). Learning in hybrid-project systems: The effects of project performance on repeated collaboration. Academy of Management Journal, 51(6), 1117–1149. Shane, S. (2003). A general theory of entrepreneurship: The individual-opportunity nexus. Edward Elgar Publishing. Shane, S. and Venkataraman, S. (2000). The promise of entrepreneurship as a field of research. Academy of Management Review, 25(1), 217–226. Smith, A. and Raven, R. (2012). What is protective space? Reconsidering niches in transitions to sustainability. Research Policy, 41(6), 1025–1036. Søderlund, J. (2008). Competence dynamics and learning processes in project-based firms: Shifting, adapting and leveraging. International Journal of Innovation Management, 12(1), 41–67. Sorenson, O. and Waguespack, D.M. (2006). Social structure and exchange: Self-confirming dynamics in Hollywood. Administrative Science Quarterly, 51(4), 560–589. Starkey, K., Barnatt, C., and Tempest, S. (2000). Beyond networks and hierarchies: Latent organizations in the UK television industry. Organization Science, 11(3), 299–305. Teece, D.J., Pisano, G., and Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509–533. The Young Foundation (2007). Social innovation: What it is, why it matters, how it can be accelerated. Accessed 6 January 2022. https://www​.youngfoundation​.org​/publications​/social​-innovation​-what​-it​ -is​-why​-it​-matters​-how​-it​-can​-be​-accelerated/ Van der Have, R.P. and Rubalcaba, L. (2016). Social innovation research: An emerging area of innovation studies?. Research Policy, 45(9), 1923–1935. Van Wijk, J., Stam, W., Elfring, T., Zietsma, C., and Den Hond, F. (2013). Activists and incumbents structuring change: The interplay of agency, culture, and networks in field evolution. Academy of Management Journal, 56(2), 358–386. Van Wijk, J., van Wijk, J., Drost, S., and Stam, W. (2020). Challenges in building robust interventions in contexts of poverty: Insights from an NGO-driven multi-stakeholder network in Ethiopia. Organization Studies, 41(10), 1391–1415.

Organizing projects for social innovation  293

Van Wijk, J., Zietsma, C., Dorado, S., De Bakker, F.G., and Marti, I. (2019). Social innovation: Integrating micro, meso, and macro level insights from institutional theory. Business and Society, 58(5), 887–918. Watkins, S.C., Swidler, A., and Hannan, T. (2012). Outsourcing social transformation: Development NGOs as organizations. Annual Review of Sociology, 38, 285–315. Weisbord, M. and Janoff, S. (2005). Faster, shorter, cheaper may be simple; it’s never easy. The Journal of Applied Behavioral Science, 41(1), 70–82. Wry, T. and Haugh, H. (2018). Brace for impact: Uniting our diverse voices through a social impact frame. Journal of Business Venturing, 33, 566–574. Yalegama, S., Chileshe, N., and Ma, T. (2016). Critical success factors for community-driven development projects: A Sri Lankan community perspective. International Journal of Project Management, 34(4), 643–659. Zietsma, C. and Lawrence, T.B. (2010). Institutional work in the transformation of an organizational field: The interplay of boundary work and practice work. Administrative Science Quarterly, 55(2), 189–221.

16. From “lonely projects” to orchestrating project innovation ecosystems Samuel C. MacAulay, Andrew Davies and Mark Dodgson

INTRODUCTION Research at the intersection of organizations and projects has long grappled with how best to organize innovation. The present chapter contributes the concept of a “project innovation ecosystem” to this literature and draws on a case study to help explain its origins and outline what we see as its value to project scholars. The intellectual origins of this enterprise stretch back at least to Burns and Stalker’s (1961) classic work distinguishing between mechanistic organizations, suitable for stable and predictable circumstances, and organic organizational forms, appropriate for changeable and unpredictable conditions. A mechanistic organization is typified by high levels of centralization, often siloed, functional and rigid structures. An organic organization is typified by low levels of centralization and cross-functional and fluid structures. These distinctions also resonate with Morgan’s (1986) use of metaphors in describing organizations; specifically, the idea of the organization as a machine and an organism. Research on project management also has a long history, and much of its extensive literature is predicated on conditions of stability, predictability and isolation from the environment, with the assumption that mechanistic forms of organization, with centralized and rigid controls, are the most appropriate means of delivering planned outcomes (Engwall, 2003). Stability, predictability and isolation, however, are so elusive in today’s business environment, in the face of rapidly changing competitive conditions and technologies, that mechanistic approaches throughout the whole lifecycle of projects can be disadvantageous. Systems thinking is another well-established influence on the literature on project and innovation management, encouraging holistic thinking about complex problems by breaking them down into component elements and determining the means by which they are connected (Morris, 2013; Davies, 2017; Whyte and Davies, 2021). The notion of such systems echoes the machine metaphor for organizations. Just as a machine is designed, assembled and operated, in this view so too can a project or an innovation; it is a case of determining their constituent components and interdependencies and ensuring their integration. Better reflecting the uncertainties and unpredictabilities of projects and innovations in the modern world, the organizational metaphor of an organism rather than a machine has become more valuable. In the innovation literature, discussion of innovation systems, with their assumptions that their structures and relationships can be mapped and are relatively static, has been advanced by notions of ecosystems (e.g. Jacobides et al., 2018; Thomas and Autio, 2020). This advance recognizes that evolution and adaptation are continuing features of changing organisms and environments. It is a feature of the innovation literature that is attuned to endemic uncertainties, the continual emergence of unforeseen challenges and opportunities, and the need for organizational flexibility and responsiveness (Dougherty, 2016). And it is a view that shares similarities to a growing stream of literature studying the management and 294

From “lonely projects” to project innovation ecosystems  295

organization of projects (e.g. Grabher, 2002; Engwall, 2003; DeFillippi and Sydow, 2016; Davies et al., 2017; Gil and Fu, 2021). There is much to be gained, in our view, by using the organic/organism metaphor as the starting point to build bridges between the two neighbouring disciplines of innovation management and project management, thus improving our understanding of how to manage innovation in projects (Davies et al., 2018). While much of the conduct of projects is of course mechanistic – without which they simply could not progress – because of the environment in which they occur, and the uncertainties they face, their delivery relies on features of organizations that are dynamic, emergent and adaptable. We offer the concept of a project innovation ecosystem to capture these features of projects, defining it as a formally designed temporary form of “meta-organization” that is tightly coordinated by a focal project organization with the aim of using innovation to create new value to be captured by members (Gulati et al., 2012; Kretschmer et al., 2022). We see this concept as complementary to but distinct from the established concept of a “project ecology” which better describes a permanent geographic cluster of project-based organizations that emerge informally over time without the tight coordination of a focal organization and work in a loosely coordinated way to create and capture value through different streams of project-based activities (Grabher, 2004; Davies, 2017). Using an illustrative case study, we discuss the challenges that motivated one focal project organization – Crossrail – to begin designing a meta-organization to manage its project’s innovation ecosystem and reveal how understanding project innovation ecosystems can inform the study of project management.

FROM “LONELY PROJECTS” TO ORCHESTRATING PROJECT INNOVATION ECOSYSTEMS The last 20 years have seen an important shift away from studying projects and their management in isolation from their broader organizational and institutional context. Projects are no longer viewed as lonely “islands” (Engwall, 2003), but temporary organizations embedded in environments that shape their identities, values, reputations and performances (DeFillippi and Sydow, 2016; Grabher, 2004; Manning and Sydow, 2011; Manning, 2017; Sergeeva and Roehrich, 2018). Time, place and history are recognized as having a profound influence on the management and organization of projects (Engwall, 2003; Söderlund and Tell, 2009). We also know that, far from being isolated from the environment, the effective management and organization of projects requires the negotiation of a plethora of important strategic interdependencies beyond the boundaries of a focal project (Gil and Fu, 2021; Killen and Kjaer, 2012; Lobo and Whyte, 2017; Newell et al., 2008). Identifying and exploiting such interdependencies can be crucial to learning and innovation at the level of both project and organization (Brady and Davies, 2004; Davies et  al., 2009; Gann et  al., 2012; Lenfle, 2011; Lenfle and Loch, 2010; Roehrich et al., 2019). Far from lonely islands, projects are increasingly viewed as being embedded in vibrant ecologies (Brunet and Cohendet, 2022). The literature studying these “project ecologies” has grown notably since Grabher’s (2001) foundational paper on the topic. The concept itself has been used to describe the “relational space which affords the personal, organizational, and institutional resources for performing projects” (Grabher and Ibert, 2011) and has proven to be a useful way for project scholars to capture the “interdependencies and informal relationships

296  Handbook on innovation and project management

built up over time, beyond what can be described through portfolio or programme management” (Hedborg and Karrbom Gustavsson, 2020). For example, Hedborg et al. (2020) trace the emergence of interdependencies between three neighbouring construction projects in Sweden and how the development of social capital facilitated effective coordination. In addition to serving as an analytical construct, project ecologies have also proven useful as a unit of analysis for studying intersecting organizational processes, such as field configuring events (Grabher and Thiel, 2015). The broad literature on project ecologies provides useful insight into how managers might cultivate learning within such an ecology (e.g. Ibert, 2004) and offers a starting point for considering innovation. Existing studies of project ecologies tell us that the complexity of their interdependencies poses serious knowledge integration challenges to innovators (Newell et al., 2008) and that the management of complementarities between different types of resources and capabilities within an ecology will be important to success (Manning and Sydow, 2011). However, this literature is yet to systematically focus on how organizations strategically design, develop and orchestrate complementarities in search of innovation. Lobo and Whyte (2017) arguably come closest in their study of how a global engineering firm’s key projects shaped the way knowledge about digital delivery was transferred between them and, more broadly, how this ecology influenced the use of project capabilities to create and capture value. In contrast to project studies, research on the innovation process in strategy and management has increasingly centred these forms of agency within studies of “innovation ecosystems” (e.g. Adner, 2017; Davis, 2016; Jacobides et al., 2018). These different points of focus suggest the potential for cross-fertilization, but, to date, we have lacked fine-grained empirical data on the management of innovation in project (rather than firm) ecosystems and thus do not have a detailed understanding of the forms such interdependencies might take, nor how their complementarities might impact a project’s ability to manage innovation. Without this data, our knowledge about the management of innovation in projects risks remaining trapped within the assumptions of the “lonely project” rather than reaching out to embrace the complexity that comes from orchestrating a project’s innovation ecosystem. Our chapter seeks to advance this literature through an in-depth case study embedded in London’s “megaproject ecology” (Davies, 2017; Lobo and Whyte, 2017). We focus on the case of Crossrail (now called the Elizabeth Line) – at the time, one of the largest and most complex infrastructure projects in the world – and its attempt to build a proactive strategy for pursuing innovation opportunities. The data drawn on in this chapter primarily comes from research we and other colleagues have published on the topic (Davies et al., 2014; DeBarro et al., 2015; Dodgson et al., 2015; Pelton et al., 2017; Worsnip et al., 2016), but is at times complemented by additional interviews conducted to both clarify and update information relating to Crossrail’s efforts to orchestrate an innovation ecosystem around the project.

CROSSRAIL AND THE SEARCH FOR INNOVATION Crossrail’s CEO, Andrew Wolstenholme, came to the project in late 2011 with an agenda he wanted to pursue on innovation.1 He had previously worked on major infrastructure projects – including Heathrow Terminal 5, the Western Harbour Tunnel Crossing (Hong Kong) and Hong Kong Airport – and observed that, while there was often substantial innovation on these projects, it was rarely organized in a strategic way; “We didn’t formalise it”, he

From “lonely projects” to project innovation ecosystems  297

lamented. We discussed this view in detail during our initial interview with Wolstenholme in 2012 to get a better idea of what he meant by formalization; what he meant was that they lacked a clear strategy for where the client organization would invest in innovation and an organizational process for identifying, evaluating, selecting, resourcing and operationalizing innovation opportunities. This view was broadly shared by members of the executive team. For example, the Chief Engineer, in reflecting on his experience at a leading engineering and design firm, explained that his previous firm “used to have a really good system for seeding innovation” which encouraged employees to put together innovation proposals, which would then be reviewed by an R&D panel and, if favourably evaluated, funding would be provided for development and the employees would gain recognition through the process (for a similar approach see Criscuolo et al., 2017). He strongly believed that projects like Crossrail should have a similar process because their size and complexity meant that opportunities for innovation often struggled to break through from their local site, gain recognition and funding, and then diffuse across the programme. Crossrail was an opportunity to fix this, he believed, by providing a “clear [organizational] path for people” to get “their ideas out there” and gain input, resources and recognition. Work thus began in 2012 to design and build the organizational architecture and a broader strategy for managing innovation within the project.2 Over time, this approach would shift from managing innovation within the project to orchestrating innovation within the project’s innovation ecosystem. There was no ready organizational template for what this innovation process should look like within an infrastructure project. The innovation process that ultimately emerged from this work is documented in DeBarro et al. (2014). To the best of our knowledge, this was the first time a major project developed and implemented such an organizational process for innovation. Those within the industry considered it a radical innovation.

INNOVATION AT CROSSRAIL The organizational process for managing innovation was viewed as a success and other major projects in the London ecology, such as Thames Tideway Tunnel and HighSpeed2 (HS2), became interested in imitating and building on it. Table 16.1 provides illustrative examples of what was considered innovation on the Crossrail project. These examples range in novelty from incremental to more radical ideas for innovation. Crossrail’s conception of innovation was developed through discussions with the research team and is thus aligned with academic definitions of innovation as the creation of new combinations of ideas, knowledge and resources and taken to include “scientific, technological, organizational, financial, and business activities leading to the commercial introduction of a new (or significantly improved) product or service” (Dodgson et al., 2008, 2).

THE CHALLENGE OF ORCHESTRATING INNOVATING AT CROSSRAIL There were two key challenges that consistently emerged when Crossrail attempted to orchestrate innovation. The first came when the timing was critical to value creation and capture.

298  Handbook on innovation and project management

Table 16.1  Innovation on Crossrail Degree of Novelty

Examples

Incremental

1. High definition drone-mounted camera for site inspections: Produce a video stream that can be used to carry out site inspections. The stream would make expensive aerial photographs redundant, reduce the need for field engineers to travel across sites to carry out inspections, and make it easier to access restricted areas (e.g. hazardous works; mass movement of plant). Transport for London has successfully trialled drones for carrying out inspections and monitoring site security. 2. Hydrophobic coating for concrete hopper: The application of a hydrophobic coating to the surface of concrete hoppers. This coating prevents concrete adhering to the hopper and speeds up concrete flow. Cleaning and maintenance costs are significantly reduced, and the risk profile of concreting is substantially reduced (e.g. lower risk of clogging).

Intermediate 1. Liftpro App: Lifting operations are a central part of the construction process (e.g. using an overhead crane to lift steel). These are high-risk activities and detailed planning is required to ensure they are conducted efficiently and effectively. Creating a lift plan is currently a time intensive task and requires a lot of traditional paper and pencil work. The Liftpro App is designed to bring this operation into the digital age. It stores information on common lifting machines used in the UK and then applies the standard calculations required to produce a lift plan. The App is designed to enable a plan to be produced in minutes instead of hours. 2. Tactical Messages on Safety Gloves: Print tactical safety messages on the back of gloves. For instance, if a site is having problems with finger trapping injuries, a targeted safety message related to hand safety was developed to reinforce the site’s safety message (‘‘Don’t give your finger to safety’’). Radical

1. Heat extraction from grout shafts: Tens of thousands of metres of grout shafts were developed to help stabilize the ground and prevent subsidence during the excavation process (following the ‘‘Tube a Machenette’’ method). They were originally going to be backfilled with concrete. However, it is possible that these grout shafts could be paired with a ground-sourced heat pump to produce geothermal energy. This energy could then be used to heat and cool Crossrail Stations and the over site developments that are being constructed above them. 2. Real time micro-positioning system: This innovation uses Bluetooth beacons to generate high precision location data for mobile devices on construction sites. Existing technologies, such as GPS and WiFi triangulation, are not accurate enough nor work underground. The three main areas of application are: (a) use location data to lock/unlock device functionality according to the safe operating conditions in a given area. This would make mobile devices safer to use and reduce resistance to having them on site. (b) Use location data to actively push relevant data (e.g. engineering drawings) to users rather than having them search through thousands of documents. (c) Make augmented reality applications easier to use (e.g. use a tablet to visualise construction sequences associated with a given space). The difficulty of getting accurate location data is currently constraining the use of augmented reality.

Source:   adapted from Dodgson, Gann, MacAulay and Davies (2015)

From “lonely projects” to project innovation ecosystems  299

Many innovation opportunities were viewed as being highly attractive in principle, but unfeasible in practice due to their emergence at an inappropriate “stage” of the project’s life. Colloquially, these innovation opportunities were said to have “missed the boat”, and examples included an improved stakeholder management system and the experimental application of fibre optics to measure tunnel deformation. The timing of their emergence meant that the window of opportunity associated with that part of the production process would be closed (or soon to be closed) by the time innovations such as these were available for implementation. As a result, the innovation either could not be deployed in time (e.g. tunnels would be completed by the time the fibre optic system could be usefully deployed) or it could not be deployed at the scale (e.g. there were only a small number of stakeholders left to manage to justify a new stakeholder management system) required to enable sufficient value to be created and captured so that an investment could be justified. These sequential, time-based interdependencies between different phases of the production process were constantly evolving and, depending on what was happening within the project, they could also be in flux. Understanding these interdependencies was crucial to effectively identify, evaluate, select, resource and operationalize innovation opportunities within the constraints of the project’s ecosystem. The second challenge came when the multiplex of organizational boundaries spanning the project ecosystem had to be navigated to create and capture value from innovation. The innovation team’s identification of an opportunity to introduce an energy demand management system provides a typical illustration of the complexity of navigating these boundaries and how the process shaped innovation. The team was approached by a Tier 1 contractor who could see an opportunity to reduce the operational energy consumption at the stations Crossrail was constructing. The energy management system would allow the asset operator to earn revenue by agreeing to temporarily increase or decrease their energy use (e.g. air conditioning, heating) depending on demand/supply fluctuations within the market.3 There were now multiple case studies showing that these systems could prove profitable for asset owners and operators, but the systems did not exist when Crossrail’s design was specified and so lay outside its current scope. To explore this opportunity for Crossrail, the innovation team had to mobilize a complex mix of actors from across the project’s innovation ecosystem, including: • • • •

Transport for London (TfL): the future owner of the assets where this system was proposed to be installed. Crossrail’s Chief Engineer’s Office: who had responsibility for systems specification. Two separate suppliers: these firms provided energy demand management solutions and could provide advice on the value proposition and requirements. Representatives from the ATC joint venture: this organization was responsible for the system-wide fit-out and commissioning of the central section of the railway and thus knew which assets could be targeted for management.

As one member described the experience: “Trying to find the right people to talk to, to get engaged, to even get to the stage where you could understand that this was a good idea, is very, very challenging”. At the beginning of the process, it was not clear which of the actors in the ecosystem stood to capture the most value from the opportunity’s exploitation nor who was best positioned to create this value in the first place. It ultimately took six months of

300  Handbook on innovation and project management

work for the innovation team to identify the right stakeholders, convince them to explore this innovation opportunity, and then mobilize the right 25 people across these organizations into a workshop to explore its desirability, feasibility and viability. Their study of this specific innovation opportunity suggested it was promising but that it should be considered in light of a much broader insight the group generated: the design of Crossrail’s energy management systems was likely over-specified. The recommendation therefore was to launch a much broader review of the energy management strategy and place the demand management solution within that. This example illustrates how the capabilities, resources and authority required to effectively identify, evaluate, select, resource and operationalize innovation opportunities could be distributed across actors in the project’s ecosystem, rather than within Crossrail itself. These two forms of interdependencies could also co-occur. Crossrail’s “Tunnel Energy Segments” project illustrates how the timing and multiplexity of organizational boundaries associated with an innovation created substantial managerial challenges. The project was spurred by the identification of an opportunity to use new heat exchange technology instead of fan-driven cooling of tunnels. This technology did not exist during the early days of Crossrail’s design and so the opportunity only emerged once the project was underway (for a detailed technical description of the innovation, see Nicholson et al., 2014). The original motivation for pursuing this innovation was that it might be able to substitute or substantially reduce the railway’s dependence on large fans to meet its cooling needs. Heat exchange was seen as a desirable alternative to fans because it was less energy intensive, thus improving the railway’s sustainability. However, since the system had not previously been deployed beyond a small number of experimental operations in Austria and Germany, significant research was required to better understand the desirability, feasibility and viability of this innovation opportunity within the context of Crossrail. To do this, Crossrail had to assemble a multidisciplinary team from across the project ecosystem, including experts in building services, costing, energy, fire, hydrogeology, geotechnics, material, mechanic and electrical engineering, structures, risk management, tunnelling and ventilation engineering. These experts came from a wide array of organizations, ranging from external suppliers (e.g. Rehau A G+Co), project sponsors (e.g. TfL) and design and engineering firms working with Crossrail (e.g. Arup). Together, the team discovered new ways that this innovation might create value beyond the original hypothesis of reducing energy intensity and began investigating them. In each instance, a promising value proposition eventually ran into challenges when it came to figuring out how value might be captured from the innovation. First, it was realized that the system’s ability to transmit energy from below ground to above, thus cooling the tunnels, could generate enough heat to service the needs of 30,000 people in central London. Selling this heating to offices, apartments, hospitals, etc. could thus provide a new source of operational revenue. However, it was difficult to determine the right business model for operating the system and which organization in the ecosystem would be best placed to deliver it. Was it the asset owner? The operator? Or did the project’s proponents need to bring a new organization – such as an energy generator and retailer – into the ecosystem? Second, the capital costs of building the underground section of the railway could be cut by reducing or eliminating the need for the infrastructure required to deliver cooling via fan-based ventilation. For example, when the tunnel’s diameter is sized to enable ventilation, this could be reduced, along with the need for ventilation shafts. However, it was eventually realized “that ship had sailed” on Crossrail and the design was now at the point where these gains could not be realized.

From “lonely projects” to project innovation ecosystems  301

Third, using tunnel heat to cool buildings in central London would substantially reduce carbon emissions. For example, it was estimated that switching a 500-bed luxury hotel over to Crossrail’s heat could reduce carbon emissions by 42 per cent. However, in a similar spirit to selling heat mentioned earlier, it was not clear ex-ante what the most appropriate business model would be for capturing value from this resource. For example, would the railway operator sell carbon credits? Or would consumers (e.g. hotels, offices) be willing to pay for both the heat and carbon offsets? Fourth, having tested this idea in practice, subsequent new railway projects with significant urban tunnelling programmes, such as the UK’s HighSpeed2, would be able to make an adoption decision and formulate a production plan with greatly reduced technical and market uncertainty. Fifth, if this project was successful, then the companies that had delivered the world’s first full-scale tunnel energy system would stand to gain a first-mover advantage in what would be a new product category. Consequently, there was discussion about the extent to which these actors (e.g. the joint ventures running the tunnelling contracts, technology suppliers) should be expected to contribute their own resources to the development and deployment of the innovation. After all, the argument went, were they not the ones who stood to capture the most value from this innovation’s success in the future? For Crossrail, value might be created within the capital programme’s delivery, but with the Crossrail organization ceasing to exist once the railway was handed back to the owner, their ability to capture any future value was limited by time. However, exploration of this hypothesis was curtailed when the above constraints saw the project limited to the feasibility studies documented in Nicholson et al. (2014). In summary, as research into desirability, feasibility and viability progressed, it became clear that the design options could not be developed fast enough to be included in the final design and delivery strategy. For example, by the time the benefits of the system were understood, it was too late to re-design the air ventilation and under-platform exhaust systems. Crossrail could therefore not capture value by reducing capital costs or generate value for the end operator by reducing energy consumption. Time-based interdependencies foreclosed these options. Therefore, the team re-orientated their plans in the hope of conducting a smaller in-field pilot study centred on Tottenham Court Road station (Nicholson et  al., 2014) that would help further reduce uncertainty, but this justification could not ultimately gain the required approvals. At this small scale, it was clear that the project would simply serve as a demonstrator, which for Crossrail would mean that sufficient value could not be extracted to justify an investment. The resourcing would have to come from another stakeholder within the ecosystem or even beyond it. Research into this possibility failed to reveal another actor in the ecosystem (or beyond) that could capture enough value to justify the requisite investment. The value would be spread too broadly across a diffuse set of actors for private firms to be confident of successfully capturing value, and public actors who could capture value from the reduction in future uncertainty (e.g. TfL; HS2; Crossrail2), did not have the financial resources at this time to invest. As one lead proponent put it: if we can prove [the innovation] on Crossrail through this pilot, when we come to building Crossrail 2, you know, from day one we’ll be saying, well actually this is the way we’re going to design it. The primary method of cooling for this is going to be tunnel energy segments.

This reality put Crossrail in a unique position to fund the creation of value by reducing the uncertainty future projects might face in tackling this challenge, but not in a position to

302  Handbook on innovation and project management

capture it. Instead, the value created by the reduction in uncertainty would be captured by other stakeholders.

LESSONS LEARNT ABOUT MANAGING INNOVATION IN A PROJECT’S INNOVATION ECOSYSTEM Reflecting on such cases, the innovation team began to realize that it was crucial to understand who stood to appropriate the most value from a given innovation and the time horizon over which this could happen. In each of these cases, the main beneficiaries were outside the core organization set up to produce the infrastructure (Crossrail Ltd) including either the eventual asset owner, a concession holder, a contractor or some combination of these actors. The team learnt a valuable lesson from these cases and changed their approach to resourcing innovation as a result. When confronted with similar opportunities in the future, they first sat down and attempted to determine which actors were best placed to capture value from the innovation and the time horizon in which this would be possible. If these actors were within the project’s innovation ecosystem, the team could then approach this actor with a proposal for investment, rather than attempt to make the case for the innovation to be funded internally through the existing capital budget. This growing realization triggered a much broader reconceptualization of the way innovation should be managed at Crossrail. There was a shift from managing innovation within the bounds of the project, and towards managing innovation within the bounds of the project’s ecosystem. The team realized that if they wanted to be effective at managing innovation, they needed to work across interdependencies within that ecosystem to orchestrate the capabilities, resources and authority required to create and capture value from innovation. This shift in cognition can be seen in the way Crossrail’s abstract vision of innovation changed from 2012 (Figure 16.1) to 2016 (Figure 16.2). It goes from an image of

Figure 16.1  Crossrail’s innovation vision 2012

From “lonely projects” to project innovation ecosystems  303

Figure 16.2  Crossrail’s innovation vision 2016 input-output with Crossrail at the centre, to a vision that foregrounds innovation over time and the different actors involved in the ecosystem and beyond into the UK’s broader infrastructure project ecology. The key obstacle identified to this task was the lack of institutional mechanisms or intermediaries available to coordinate collaboration and co-investment in innovation across the UK’s broader infrastructure project ecology. It was recognized that major infrastructure projects, such as the Thames Tideway Tunnel and HighSpeed2, did at times face similar opportunities to create value through innovation. For example, the projects mentioned here all have sizeable tunnelling programmes. However, there were not strong enough institutional mechanisms or actors able to effectively coordinate investments in areas of common interest and facilitate the diffusion of this innovation across relevant stakeholders in each distinct project’s innovation ecosystem. Sensing an important opportunity to bridge this institutional void, Crossrail’s CEO Andrew Wolstenholme began working with others in the project, such as John Pelton, to build the institutional scaffolding required to bridge this divide (Pelton et al., 2017). The result was a new intermediary organization called i3P (www​.i3p​.org​.uk/) whose membership was composed of major infrastructure client and supply chain organizations whose mission was to improve the coordination of innovation across the infrastructure project ecology within the UK.

304  Handbook on innovation and project management

DISCUSSION AND CONCLUSION The concept of a project innovation ecosystem helps scholars and practitioners move further beyond the “lonely island” view that for so long characterized project management. It does this by focusing attention beyond the core project organization itself and on the careful design of interventions aimed at orchestrating complementarities in search of innovation across multiple interdependent, but legally distinct, organizations. A project innovation ecosystem can be distinguished from the established stream of research on project ecologies. Focusing on a cluster of project-based activities in a geographical area, the project ecology concept draws attention to the ongoing and enduring network of ties and relationships, such as the people, teams, firms and institutions, and epistemic communities involved in the stream of megaprojects established to design, build and transform London’s infrastructure over the past two decades (Davies, 2017). The personal layers of London’s megaproject ecology provide a pool of resources, capabilities and relationships that can be mobilized to support current and future infrastructure projects. While Crossrail benefited from its participation in London’s megaproject ecology, it established and orchestrated its own innovation ecosystem to create and capture value with organizations participating in the project as well as other collaborating organizations (e.g. professional institutions and universities). Prior research has tended to assume that an innovation ecosystem is orchestrated by a focal firm with no defined or obvious end date for when the task has been completed (Poblete et al., 2022), whereas a project innovation ecosystem identifies how a focal organization (in our case the client body) designs a structure and process to create and capture value for participating members of a temporary organization that dissolves on completion of its task. An innovation ecosystem established for a project assembles, leverages and eventually dismantles innovation resources and capabilities distributed amongst parties and exploits interdependencies between organizations on a temporary basis. This analytical shift from firm to project ecosystems will be particularly useful in an era that has seen major projects become increasingly focused on the challenges of innovation to improve performance and outcomes. Our case study of Crossrail highlights the innovation challenges that inspired this shift towards the management of the project innovation ecosystem and discusses its use in practice. However, there is much more to be learnt about this approach to managing innovation in projects. An important first step will be drawing on theory to carefully define and understand the complementarities being managed. For example, are they supermodular complementarities where more of “A” makes “B” more valuable (Jacobides et al., 2018), such as when two distinct projects might increase the value created by coordinating innovation investments in tunnelling? Or another form? A second crucial step will be better understanding the mechanisms through which project ecosystems resource innovation and how these choices impact performance and outcomes. The resources required for innovation are conceptualized as “organizational slack” within the literature (Cyert and March, 1963; Nohria and Gulati, 1996) and scholars have traditionally considered temporary organizations, such as the projects we study here, as being characterized by very little of it (Grabher, 2004). However, in our case, it was not the case that there was a lack of organizational slack per se. Slack existed within the project (e.g. in different project contingency budgets) and the broader supply chain, but to be of use to the innovation programme, this slack had to be actively searched for, discovered and mobilized. Future research should study the dynamic capabilities (e.g. Davies et al., 2016)

From “lonely projects” to project innovation ecosystems  305

required to effectively execute this search-discovery-mobilization process as well as the way the structure of the associated budget shapes the types of innovation generated (Argyres and Silverman, 2004; Argyres et al., 2020). This chapter began by recognizing the importance of viewing projects not as isolated endeavours, but as embedded in a wider set of interrelated activities in a changing environment. Far from being isolated from its environment, the case of Crossrail helps show how projects are not only embedded in the environment but can intervene to change the environment (cf. Whyte et  al., 2022). Crossrail’s innovation programme did just this. Many other infrastructure projects in the UK followed suit by establishing their own innovation programmes (e.g. the Thames Tideway sewer, Hinkley Point C nuclear power station and HS2 railway). To prevent innovation from occurring in isolation on each project, most of the UK’s large infrastructure projects began shifting to a more open form of innovation process institutionalized through the i3P community. Together, they share a pool of resources and collaborate on programmes of innovation aimed at improving the performance and outcomes of many projects. These shifts in practice make it increasingly important to bridge innovation and project management. We believe that doing so is the most promising way forward for improving our understanding of how and why organizations establish innovation ecosystems for projects and how those innovation activities form part of a wider project ecology.

NOTES 1.

An early articulation of these views can be found in a key construction industry report chaired by Wolstenholme (“Never Waste a Good Crisis”, 2009). The report argued that the industry focused excessively on passing risk “down the supply chain” rather than on drawing up “opportunities to create value” (22). This, the review argues, had led to a situation in which the “tap of innovation” had been effectively turned off in major projects like Crossrail (20). There was a wide range of initiatives seen as helpful for tackling this problem, ranging from a shift towards life cycle evaluations of cost through to business models structured around new types of vertical integration. By the time Wolstenholme joined Crossrail, efforts to improve performance had turned from “delivery model innovation” (Davies et al., 2019) to innovation efforts within the existing delivery model. 2. See Debarro et al. (2014) for an in-depth description of this process and our involvement. 3. Flexitricity is an example of one such offering in the UK: www​.flexitricity​.com​/more​/ how​-does​-it​work/

REFERENCES Adner, R. (2017). Ecosystem as structure: An actionable construct for strategy. Journal of Management, 43(1), 39–58. Argyres, N., Rios, L.A., and Silverman, B.S. (2020). Organizational change and the dynamics of innovation: Formal R&D structure and intrafirm inventor networks. Strategic Management Journal, 41(11), 2015–2049. Argyres, N.S. and Silverman, B.S. (2004). R&D, organization structure, and the development of corporate technological knowledge. Strategic Management Journal, 25(8–9), 929–958. Autio, E. and Thomas, L.D. (2020). Value co-creation in ecosystems: Insights and research promise from three disciplinary perspectives. In Handbook of digital innovation (pp. 107–132). Edward Elgar Publishing. Brady, T. and Davies, A. (2004). Building project capabilities: From exploratory to exploitative learning. Organization Studies, 25(9), 1601–1621.

306  Handbook on innovation and project management

Brunet, M. and Cohendet, P. (2022). Transforming construction: Heterarchical megaproject ecologies and the management of innovation. Construction Management and Economics, 40(11–12), 973–986. Burns, T. and Stalker, G.M. (1961). The management of innovation. London: Tavistock. Criscuolo, P., Dahlander, L., Grohsjean, T., and Salter, A. (2017). Evaluating novelty: The role of panels in the selection of R&D projects. Academy of Management Journal, 60(2), 433–460. Davies, A. (2017). Projects: A very short introduction. Oxford: Oxford University Press. Translated into Chinese in 2022. Davies, A., Dodgson, M., and Gann, D. (2016). Dynamic capabilities in complex projects: The case of London Heathrow Terminal 5. Project Management Journal, 47(2), 26–46. Davies, A., Dodgson, M., Gann., D., and MacAulay, S. (2017). Five rules for managing large, complex projects. MIT Sloan Management Review, 59(1), 73–78. Davies, A., Gann, D., and Douglas, T. (2009). Innovation in megaprojects: Systems integration at Heathrow Terminal 5. California Management Review, 51(2), 101–125. Davies, A., MacAulay, S., and Brady, T. (2019), ‘Delivery model innovation: Insights from infrastructure projects’, Special Issue: Innovation in infrastructure delivery models. Project Management Journal, 50(2), 1–9. Davies, A., MacAulay, S., DeBarro, T., and Thurston, M. (2014). Making innovation happen in a megaproject: London’s crossrail suburban railway system. Project Management Journal, 45(6), 25–37. Davies, A., Manning, S., and Söderlund, J. (2018). When neighboring disciplines fail to learn from each other: The case of innovation and project management research. Research Policy, 47(5), 965–979. Davis, J.P. (2016). The group dynamics of interorganizational relationships: Collaborating with multiple partners in innovation ecosystems. Administrative Science Quarterly, 61(4), 621–661. DeBarro, T., MacAulay, S., Davies, A., Wolstenholme, A., Gann, D., and Pelton, J. (2015). Mantra to method: Lessons from managing innovation on Crossrail, UK. In Proceedings of the institution of civil engineers-civil engineering (Vol. 168, No. 4, pp. 171–178). Thomas Telford Ltd. November. DeFillippi, R. and Sydow, J. (2016). Project networks: Governance choices and paradoxical tensions. Project Management Journal, 47(5), 6–17. Dodgson, M., Gann, D., MacAulay, S., and Davies, A. (2015). Innovation strategy in new transportation systems: The case of Crossrail. Transportation Research Part A: Policy and Practice, 77, 261–275. Dodgson, M., Gann, D., and Salter, A. (2008). The management of technological innovation: Strategy and practice. Oxford: Oxford University Press. Dougherty, D. (2016). Taking advantage of emergence: Productively innovating in complex innovation systems. Oxford: Oxford University Press. Engwall, M. (2003). No project is an island: Linking projects to history and context. Research Policy, 32(5), 789–808. Gann, D., Salter, A., Dodgson, M., and Phillips, N. (2012). Inside the world of the project baron. MIT Sloan Management Review, 53(3), 63. Gil, N.A. and Fu, Y. (2021). Megaproject performance, value creation and value distribution: An organizational governance perspective. Academy of Management Discoveries. Grabher, G. (2001). Ecologies of creativity: The Village, the Group, and the heterarchic organization of the British advertising industry. Environment and Planning A, 33(2), 351–374. Grabher, G. (2002). Cool projects, boring institutions: Temporary collaboration in social context. Regional Studies, 36, 245–262. Grabher, G. (2004). Temporary architectures of learning: Knowledge governance in project ecologies. Organization Studies, 25(9), 1491–1514. Grabher, G. and Ibert, O. (2011). Project ecologies: A contextual view on temporary organizations. In P. Morris, J. Pinto, and J. Söderlund (Eds.), The Oxford handbook of project management (pp. 175–199). https://doi.org/10.1093/oxfordhb/9780199563142.001.0001 Grabher, G. and Thiel, J. (2015). Projects, people, professions: Trajectories of learning through a megaevent (the London 2012 case). Geoforum, 65, 328–337. Gulati, R., Puranam, P., and Tushman, M. (2012). Meta‐organization design: Rethinking design in interorganizational and community contexts. Strategic Management Journal, 33(6), 571–586. Hedborg, S., Eriksson, P.E., and Karrbom Gustavsson, T. (2020). Organisational routines in multiproject contexts: Coordinating in an urban development project ecology. International Journal of Project Management, 38(7), 394–404.

From “lonely projects” to project innovation ecosystems  307

Hedborg, S. and Karrbom Gustavsson, T. (2020). Developing a neighbourhood: Exploring construction projects from a project ecology perspective. Construction Management and Economics, 38(10), 964–976. Ibert, O. (2004). Projects and firms as discordant complements: Organisational learning in the Munich software ecology. Research Policy, 33(10), 1529–1546. Jacobides, M., Cennamo, C., and Gawer, A., (2018). Towards a theory of ecosystems. Strategic Management Journal, 39, 2255–2276. Killen, C.P. and Kjaer, C. (2012). Understanding project interdependencies: The role of visual representation, culture and process. International Journal of Project Management, 30(5), 554–566. Kretschmer, T., Leiponen, A., Schilling, M., and Vasudeva, G. (2022). Platform ecosystems as meta‐organizations: Implications for platform strategies. Strategic Management Journal, 43(3), 405–424. Lenfle, S. (2011). The strategy of parallel approaches in projects with unforeseeable uncertainty: The Manhattan case in retrospect. International Journal of Project Management, 29(4), 359–373. Lenfle, S. and Loch, C. (2010). Lost roots: How project management came to emphasize control over flexibility and novelty. California Management Review, 53(1), 32–55. Lobo, S. and Whyte, J. (2017). Aligning and reconciling: Building project capabilities for digital delivery. Research Policy, 46(1), 93–107. Manning, S. (2017). The rise of project network organizations: Building core teams and flexible partner pools for interorganizational projects. Research Policy, 46(8), 1399–1415. Manning, S. and Sydow, J. (2011). Projects, paths, and practices: Sustaining and leveraging projectbased relationships. Industrial and Corporate Change, 20(5), 1369–1402. Morgan, G. (1986). Images of organization. Thousand Oaks, CA: Sage. Morris, P.W.G. (2013). Reconstructing project management. Chichester: John Wiley & Sons. Newell, S., Goussevskaia, A., Swan, J., Bresnen, M., and Obembe, A. (2008). Interdependencies in complex project ecologies: The case of biomedical innovation. Long Range Planning, 41(1), 33–54. Nicholson, D.P., Chen, Q., de Silva, M., Winter, A., and Winterling, R. (2014, June). The design of thermal tunnel energy segments for Crossrail, UK. In Proceedings of the institution of civil engineersengineering sustainability (Vol. 167, No. 3, pp. 118–134). Thomas Telford Ltd. Nohria, N. and Gulati, R. (1996). Is slack good or bad for innovation? Academy of Management Journal, 39(5), 1245–1264. Pelton, J., Brown, M., Reddaway, W., Gilmour, M., Phoon, S., Wolstenholme, A., and Gann, D. (2017). Crossrail project: The evolution of an innovation ecosystem. In Proceedings of the institution of civil engineers-civil engineering (Vol. 170, No. 4, pp. 181–190). Thomas Telford Ltd. April. Poblete, L., Kadefors, A., Rådberg, K.K., and Gluch, P. (2022). Temporality, temporariness and keystone actor capabilities in innovation ecosystems. Industrial Marketing Management, 102, 301–310. Roehrich, J.K., Davies, A., Frederiksen, L., and Sergeeeva, N. (2019). Management innovation in complex products and systems: The case of integrated project teams. Industrial Marketing Management, 79, 84–93. Sergeeva, N. and Roehrich, J.K. (2018). Temporary multi-organizations: Constructing identities to realize performance improvements. Industrial Marketing Management, 75, 184–192. Söderlund, J. and Tell, F. (2009). The P-form organization and the dynamics of project competence: Project epochs in Asea/ABB, 1950–2000. International Journal of Project Management, 27(2), 101–112. Whyte, J. and Davies, A. (2021). Reframing systems integration: A process perspective on projects. Project Management Journal, 52(3), 237–249. Whyte, J., Naderpajouh, N., Clegg, S., Matous, P., Pollack, J., and Crawford, L. (2022). Project leadership: A research agenda for a changing world. Project Leadership and Society, 3, 100044. Wolstenholme, A. (2009). Never waste a good crisis. Accessed 2 June 2022. https://con​stru​ctin​gexc​ ellence​.org​.uk ​/wolstenholme​_ report​_oct​_2009/. Worsnip, T., Mirgalia, S., and Davies, A. (2016). Balancing open and closed innovation in megaprojects: Insights from Crossrail. Project Management Journal, 47(4), 79–94.

17. Value management of innovation projects: contemporary challenges and perspectives Sophie Hooge and Sylvain Lenfle

INTRODUCTION The steering of each project’s contribution to the firm’s performance is a core objective of managers’ tasks from daily routines to the most prospective activity. Project leaders face a widespread use of the discounted cash flow approach, which assimilates project performance to monetary dimension and short-term profit, to increase the comparativeness of projects, and thus, optimize the strategic resources allocation. It’s an unsatisfactory issue known for decades, in particular for innovative projects: even if the resources planning system allowed managers to efficiently evaluate the business proposals, these tools are also known to hide project benefits related to organizational capabilities and longer-term business profitability (Baldwin and Clark, 1994) and, therefore, to hinder innovation (Christensen et al., 2008). Nevertheless, some tools dedicated to the exhaustive modelling of innovation benefits for customers have been developed since the 1940s, at the same time as strategic planning. In new product development (NPD) projects, the gradual process of constructing the value of the future object – as known as “value management” or “VM” – has referred since the 1960s to analyses, proposals and choices made in projects to bring about the appropriate value for the targeted customer of the innovation while minimizing the associated costs (Miles, 1961). Nowadays, the definition of the value earned from innovative design has enriched and a wide range of tools are available for project leaders – from ecosystem modelling of beneficiaries beyond customers and optimized rules for economic assessment to stage-gate process for internal project stakeholders coordination – to help them to efficiently support project progress. In this chapter, we investigate how intensive innovation contexts of the 20 last years have renewed the tools dedicated to performance management of NPD projects for both project leaders and decision-makers involved in steering committees. Indeed, as demonstrated by Baldwin and Clark (1994), to understand the process of project evaluation it is necessary to distinguish between the project team on one side and the strategic level of the project evaluation committee on the other. The engineering of project performance is a field fed by international research and practices for decades: it’s crucial to apprehend the diversity of tools that are available to project leaders to understand their contemporary challenges and to choose the best data to gather for efficient innovation project management. A large number of tools have been developed, tested and optimized to meet the needs of project leaders to describe the potential of a new product and to warranty its design at the right time for clients: quality language covers a large range of expectations from functionality to safety or affordability, processes for technical feasibility and test are well-known, and best time-to-market could be studied with competitive data analysis. In parallel, resource allocations in complex organizations have led to a specific engineering of the value analysis created by investments: development and production costs 308

Value management of innovation projects  309

can be described and tracked in detail in enterprise resource planning (ERP) software that both supports the strategic decisions to allocate resources in the development of new products. Therefore we face a dual engineering of the performance of industrial innovation with project leaders and designers on one hand, and on the other hand, decision-makers and strategists. In this chapter, we will explain how these two sets of stakeholders have designed and structured processes and tools of value management by capturing theories and developing management tools. We will see why value management tools are widely used in companies equipped with R&D departments and how these stakeholders coordinate. Moreover, we propose to describe the value management of innovation projects and how actors developed new areas of value management to face intensive innovation since the turn of the 2000s. Nowadays, value management in innovation projects systematically requires describing, enriching, disseminating and analysing a large range of data on the value the not-yet-existing products (or services) could procure to the firm well beyond its intrinsic profitability. From a stage-gate point of view, we will examine how value management tools evolved from simple decision tools to complex information systems shared between project leaders and decision-makers. Thus, we propose to describe firstly the origin of value management tools in engineering departments, then to study the contemporary approaches of designing the innovation business model and contribution of innovation projects to firm performance, and then to underline the main challenges of today’s value management and open perspectives for better value management of innovation projects.

THE ORIGIN OF VALUE MANAGEMENT IN NPD: THE ENGINEERING DEPARTMENT’S EFFORTS TO MASTER FUNCTIONAL DESIGN OF INNOVATION AND RESOURCES ALLOCATION This part of the chapter proposes a synthetic literature review of value management history, which has been an abundant research field in engineering design since the 1960s. It used to be seen by general management as an instrumental area where specialized researchers propose and debate complex tools and models to describe expected functionalities of the object to propose the best technical solution to achieve it. Indeed, functional design, and its main tool functional analysis (SAVE, 1998), are complex instruments daily used in engineering departments. Here, to highlight their contemporary contribution to innovation stakes in project management and the challenges still open for project performance, we propose a description of the theoretical foundations of value management in NPD. To do so, we provide an analysis of the literature looking specifically at how performance is engineered, trying to clarify which theoretical models it is based on. Beyond tools, the research issue faced by researchers specialized in the field was (and still is) the management of the novelty of a project’s goals to assure innovation success: what is enough novelty to be a valuable innovation? How to reduce risk exposure due to novelty? On which NPD project should the resource allocation be concentrated? These questions require common definitions of the value of innovation. It supposes a balance between (1) mastering the value of a brief that one wishes to be singular and creative and (2) being able to impose some reuse of knowledge and proven performing rules from past experiences to assure the feasibility of the innovation. This refers to the well-known issue in the engineering science of organizing design

310  Handbook on innovation and project management

generativity and robustness (Hatchuel et al., 2011). We will characterize its effectiveness with the robustness of the knowledge manipulated by project stakeholders in a situation of intensive innovation: diversity of risks and opportunities, multiple uncertainties, questioning generated by the arrival of unexpected knowledge, and the nature of this previously unknown information. The Tools of the New Product Performance: Engineering of Hard and Soft Value Management First of all, there is a wide variety of tools for engineers gathered initially under the name of value engineering. Since the creation of the Value Analysis Functional Approach in the 1940s by Lawrence Miles and colleagues at General Electric (Miles, 1961; Dell’Isola, 1966), the concept has brought together the tools that allow us to systematically compare the function provided by the new object and its costs (product value = function/costs). Building on this approach, when tools are focused on designers’ activities for R&D specifications, the contemporary academic community referred to it as “hard value management”. They are the most diffused tools and they support the coordination of thousands of designers in engineering departments around the world. Thus, for most practitioners, value engineering is a very precise stage of new product development – the functional analysis stage in the systematic design of a product, manufacturing process or industrial process (Pahl and Beitz, 1977) – and, thus, refers to a measurement toolbox named “value analysis”. In the 1950s, it even became a profession with the recruitment of “value engineers” in the US Navy (SAVE, 1998). Through a more and more normalized process of functional satisfaction inquiry, value analysis techniques help the design teams first to identify the hierarchy of the client’s functional needs and then to analyse the benefits provided by proposed solutions, compared to their costs of implementation. This approach supports the optimization of the quality/price ratio of a product. It has spread throughout the worldwide industry (e.g. Bowen et al., 2010) and it is now supervised by several international standards (AS/NZS 4183, 1994; SAVE, 1998; in France, NF X50-153, 1985). Value analysis is probably the most popular value engineering tool in both engineering and manufacturing communities. Many methodologies have been proposed for decades, forming an extensive toolbox, to correctly identify what the customer wants (functional analysis system techniques, quality functions deployment), eliminate all unnecessary costs (cost analysis methodologies) or compare several alternatives with multi-criteria analysis methodologies. Nevertheless, at the end of the 1980s, these tools became more and more difficult to deploy in NPD of products that compete on the same dominant design, such as the automotive industry, textiles or consumer goods. Developments in the field have then enlarged the scope of value engineering, taking into account the value created by project stakeholders outside the boundaries of R&D departments, and for actors beyond the beneficiaries identified in the functional analysis (users of the object). These approaches are generally grouped under the name of “soft value management” (Green, 1994, 1997). Indeed, the value management toolbox prompts designers to focus on their most representative customers and reduce the diversity of functions to master the associated quality and costs, whereas increased competition is required, on the contrary, to enlarge this modelling of customers and product functionality. This leads to the emergence of a new generation of

Value management of innovation projects  311

tools, aiming to overcome this challenge and support value engineering in the industry; it is a transformation of hard value engineering, focused on two main changes: • •

Documenting the heterogeneity and dynamics of customers’ functional expectations. Reporting on the social process of designing the value of proposals that involve many internal and external stakeholders of the NPD project beyond R&D engineers.

Its founder, Stuart D. Green, offered then a new definition of VM that enlarged its scope: A structured process of dialogue and debate among a team of designers and decision makers during an intense short-term conference. The primary objective of value management is to develop a common understanding of the design problem, identify explicitly the design objectives, and synthesize a group consensus about the comparative merits of alternative courses of action. Value management makes no pretense about finding optimal answers; it is solely concerned with establishing a common decision framework around which participants can think and communicate. (Green, 1994, 51)

From this perspective, VM is no longer exclusive to engineering teams in R&D and end customers but takes into account the needs and expectations of many other people such as internal stakeholders (marketing, strategy, industrial design, manufacturing), external partners (distributors, suppliers) and even employees. Thus, beyond the development of engineering products, the VM literature has evolved towards a more holistic and upstream approach similar to strategic project management, the initial information phase of project or construction programme management (Ellis et al., 2005; Thiry, 2002; Yu et al., 2005). These authors have in particular underlined the importance of engineering the collective construction of value by stakeholders: relying on explicit processes and dedicated tools, they can make sense of their common problems, discuss indices of performance potential perceived individually and build a common vision of the situation and the different alternatives to seek (Thiry, 2001). Beyond the debates within the value management research community on the strengths and weaknesses of existing tools, we have shown that even the broader, “soft” view of value engineering is limited to supporting design teams in a situation of disruptive innovation and breakthrough R&D projects (Gillier et al., 2015). Indeed, these tools are only effective under two conditions: available knowledge of the nature of the object to design and clear identification of its beneficiaries. These approaches are less diffused in practice and still under research. Performance Control: Tools for Strategic Decision-Making in NPD Engineering Simultaneously, another engineering effort was also conducted in the 1950s on the optimization of industrial portfolio management, mainly focused on firm investment and profitability (Baker and Freeland, 1975; Kengpol, 2002). While designers developed an ability to control the costs of each product’s functionality, decision-makers acquired the ability and the tools to optimize the allocation of resources on a portfolio of NPD projects. Likewise, the RAND Corporation and numerous research teams have proposed management tools since the Second World War to coordinate the players in the resource allocation decision that has been detailed previously (e.g. Kengpol, 2002; Kavadias and Chao, 2007). Two avenues were investigated during the past decades: economic optimization based on expected profitability and selection by experts’ peer review.

312  Handbook on innovation and project management

•

•

First, mathematical programming approaches were created to optimize quantitative objective functions, mostly economic, for a set of specified and constrained resources. They are the oldest models developed in the literature. On this basis, return on investment measurement methods were developed, among which are discounted cash flow calculations that are, by far, the most developed and used in the industry. Second, scoring, classification and checklist assessment approaches are the oldest multiattribute methods designed to support critical peer review of portfolios. Multi-attribute models with strategic goals often provide an interactive process aimed at capturing information about projects and then assigning scores for decision-support logic. The bestknown approaches in this category are the multi-criteria hierarchical method by Saaty named the Analytical Hierarchy Process (Saaty, 1980; Liberatore and Stylianou, 1995), the Q-Sort approach (Souder and Mandakovic, 1986) and the Delphi method developed in the 1950s by the RAND Corporation (Kengpol, 2002). If the names have been lost, they are well known and regularly used in the industry by expert committees mandated to evaluate and score innovation ideas in scoping/exploration phase of NPD.

Even if the literature presents a wide range of proposals based on value exploration for the selection of innovative ideas, the next gates of the NPD process (feasibility/business case building, testing and industrial validation) are dominated by economic tools (Figure 17.1 illustrates a classic stage-gate process). The problem for our topic is that the majority of them have been criticized for their poor adaptability to risky R&D and innovation projects, in particular, the most widely used: the net present value (NPV) and the rate of return on investment (RRI). Empirical studies regularly confirm that few instrumental alternatives are used even in contexts of major innovative projects or in rapidly changing environments (Bititci et al., 2012; Adams et al., 2006; Henriksen and Traynor, 1999), despite strong demand that is resulting in an abundant commercial offer of software to help with multi-criteria portfolio analysis (Morton et al., 2016). The experimentations of new tools that we led in partnership with the Renault automotive firm (Hooge and Dalmasso, 2015, Hooge and Hatchuel, 2008) constitute a good example of this phenomenon:

Figure 17.1  Stage-gate process with main objectives of stages and gates in the NPD process

Value management of innovation projects  313

only the adaptations of the NPV to highlight uncertainties have been integrated into the long run to the stage-gate process. The other management tools we’ve proposed (quality process for the innovation design system, review of strategic valuation criteria, stakeholders involvement tracking, etc.) have been regularly reviewed by managers for ten years but have never been established in the long term. Even though these tools are more accurate for an innovation project, they are always more challenging to use in project portfolio reviews. Therefore, economic tools are still the main method used to evaluate all projects in most firms, even the most innovative ones (Cooper, 2014; Cooper and Sommer, 2018). Economic tools support a very simple comparison of projects, even if there are few common points between topics, industrial challenges or time to market. Indeed, the need for tools more suitable than the NPV is identified by project stakeholders but no satisfactory solution emerges despite the presence of numerous engineering proposals. This is critical since the management innovative activities desperately need decision-support instruments which fall precisely into the three deficiencies of traditional management systems, conventionally denounced for decades by researchers in accounting management (Savall and Zardet, 2008): • • •

Lack of or very imperfect measurement of indicators of potential value creation, in particular for intangible investment potential (for example, the performance of a new label of quality or industrial standard is really hard to model). Lack of measurement and management of the intangible investment generated and selffinanced by the company as a source of sustainability (for example, the performance of new expertise is a blind spot). Failure to take into account the cost of malfunctions that destroy real added value (unnecessary overloads) or potential (unrecognized opportunity costs).

Throughout the project lifecycle, the loss of management capability that the economical tools generate should not be underestimated. Operationally, stakeholders no longer know how to coordinate on extra-financial dimensions and it creates dissatisfaction (exogenous or endogenous) since all activities are reduced to their monetary expression in the value space with devastating effects: the euros being identical, why for an equal amount prioritize one activity, especially an innovative one, rather than another? Why make a greener product if it is less economical for the customer? If only the price matters to the consumer, why would it be useful to invest to improve the product in another dimension of the total cost of ownership (TCO)? Furthermore, there is a loss of value management skills for both decisional and design stakeholders. Due to the variety of contemporary expectations about innovation, practitioners are no longer confident in the choice and scheduling of the design activities for new offers. Financial optimization neglects, or even eliminates from the accounts, the time and the actors associated with these activities of elicitation, transmission, delegation of responsibilities and distribution of activities that allow for innovative objects to exist and be brought to a customer (Baldwin and Clark, 1994). When optimizing the economic equation of profitability of a new product, the more the project is piloted by monetary data, the more innovation only appears as a risk. Generativity in design (i.e. the ability to produce design proposals that are different from existing solutions and design standards and contribute to the expansion of the identity of objects’ class1 [Hatchuel et al., 2011; Thomas and Tee, 2021]) induces many forms of uncertainties in the economic equation: uncertainties on price, attainable volumes, difficulties in

314  Handbook on innovation and project management

estimating R&D study times, production costs, sourcing of new materials/parts, etc. These uncertainties are exactly the space where design activities take place, even though they may be contrary to the search for reliability and mastery of economic data. Another important skill in innovation projects is the ability to propose a design robust to a range of uncertainty or changes in its application context (Zaman et al., 2011). Yet, the conditions of a system’s robustness, i.e. the independence of design sub-elements and minimum information allowing the realization of the function (Suh, 1990), are no longer observed when one focuses on local economic optimizations. The resulting couplings of design parameters that have been linked for economical optimization, by increasing in number, induce a progressive stabilization of all elements of the system that forms the technical dominant design. This leads to an impoverishment of the capacity to generate new designs based on only one part of conservation. Likewise, the ability to describe in detail who will receive, use and adopt the innovation proposal is crucial in innovation projects. But user and consumer models are no longer shared between the different actors who build and manipulate them independently of each other in departments of marketing, industrial design, purchasing, R&D or external prescribers because profitability calculations make them invisible. In addition, this remoteness undermines the vigilance of the changing expectations of consumers-users. In the absence of an active quest for coherence between consumer and user models, advertising, marketing systems, sourcing systems, ergonomics and uses of the object are no longer necessarily aligned and the adoption of the innovation could be badly impacted. These failures are still at the heart of contemporary research (Sethi and Iqbal, 2008; Lenfle, 2016). Yet, in previous work on piloting innovation in R&D (Hooge et al., 2016; Borjesson et al., 2014), we were able to verify the hypothesis that existing instruments were abandoned or challenged precisely for these reasons. However, these specifications are particularly suitable for describing the challenges of innovation evaluation: characterizing the creation of potential, understanding and tracing the impact of investments allowing activities other than the studied project, identifying destructive disturbances or creating value during design. If accounting management has helped us to build tools that make it possible to trace the dynamics of inter-project resource consumption in R&D (Hooge and Dalmasso, 2015), tools for

Figure 17.2  Value engineering and performance control tools in the NPD process

Value management of innovation projects  315

value management of innovation beyond R&D activities remain to be designed. Thus we must return to the literature to clarify the conceptual models that researchers and contemporary practitioners share in management to describe the potential of an activity or an investment, a cost of dysfunction or an opportunity. Indeed, we need a better understanding of the interacting motivations of the innovation stakeholders who manipulate data about project potential and go into detail about the motivations of innovation investment decisions, to resolve this conflict of values ​​at the level of instruments. This is the topic of the next section.​

CONTEMPORARY APPROACH OF VALUE MANAGEMENT: A TOOLBOX TO STEER PROJECTS’ BENEFITS FOR FIRMS In this section, we propose to highlight what we call a “value space” to manage between designers and decision-makers. As we have seen, these populations have different perceptions of innovation value in, respectively, a design space and a decision space. Here we propose to describe the components of the value space as an independent management space (i.e. with specific tools and professionals) whose aims will be to create coordination between the actors of the two other spaces that contain their tools and stakeholders (Figure 17.3). Indeed, the decision to invest in innovation projects results from prior interactions between several individuals from different departments of the firm, henceforth known as the project stakeholders (e.g. Lettice and Thomond, 2008; Jepsen and Eskerod, 2009). Building on a review of the contemporary literature in management science, we propose an analysis of how this network of internal stakeholders considers innovation assessment through the prism of business model performance in design space, whereas decision-makers and strategic committees focus on firm performance in the decision space. This modelling leads us to propose a characterization of the value space through two dimensions of coordination: innovation assessment and strategic planning. Therefore we define value management as the coordination of all the stakeholders of these three spaces in the long run.

Figure 17.3  The value space, a coordination space between decision-makers and designers

316  Handbook on innovation and project management

Operational Tools for Business Model Performance Stakeholders of the design space In the NPD process, very diverse actors are involved in methods for estimating the performance of the new product business model. The occurrence of events that may impact the implementation of a future object is often known but heterogeneous: events could vary in nature from technology to marketing, law, purchase, etc. Thus, these data are built by a large range of actors involved in the project according to their areas of expertise. Each profession produces a set of experiments and tests (prototypes, customer interviews, benchmarking, etc.). Thus, within the design space, many stakeholders interact with project leaders to describe the whole benefits and improvements that could be managed through a search for business model performance (Demil et  al., 2018). To coordinate, these stakeholders rely on the traditional separation of languages in systematic design – functions, conceptual models, embodiments, detailed parameters – as it is the basis of design department organization (Pahl and Beitz, 1977). However their perspective of what is the object differs. So, we propose to gather them according to their perspective on the identity of the “object-to-design” (Le Masson et  al., 2010). We could describe their tools of value management through their professional responsibility and involvement roles in the design process (Figure 17.4): •

•

•

Providers of the design are mainly engineering designers that focus on the technical proposal. They are the heirs of the hard value management toolbox and not surprisingly, contemporary models rely heavily on the distinction between functional requirements and design parameters put forward in work on design theory as the key to the design robustness of a technical system (Suh, 1990). Receivers of the design are those who will be in direct contact with the innovation or its users (industrial designers, commercial marketers, sellers, etc.), because either they have to describe how potential customers will use the innovation, they are going to sell it to a customer or it will be integrated into the industrial system that they manage. Prescribers of the design (purchasers, product marketers, regulators, etc.) impose some attributes to the innovation both for differentiation and competition and adequation to industrial rules and regulations.

Figure 17.4  Design space stakeholders of value management in the NPD process

Value management of innovation projects  317

When they give feedback to project leaders on the benefits knowable to the future object, actors from the design space could argue on a large diversity of potentials for the customer, the user, and also the environment of the innovation lifecycle, from sales to recycling. From a stakeholder perspective (Mitchell et al., 1997), these actors share logics of coordination and cohesion linked by their legitimacy in the organization, but also to urgency as they also manage costs and delays of the firm’s delivery (see Hooge and Dalmasso, 2015 for an extended classification of innovation project stakeholders). This salient diversity introduces biases in the quality of data given to the project leader as motivations of “urgent” stakeholders to the project completion could introduce disturbances in the expected rationality of the value analysis. Value in the design space Knowing the breadth of vision of these actors on the benefits or constraints brought by the object being designed, the contemporary literature on business models is very interesting to analyse in detail. Building on an exhaustive literature review we made previously,2 Table 17.1 presents the diversity of value paradigms mobilized by researchers to discuss the main issues of business model design in innovation projects. Three points are worth noting: •

•

•

First, the literature on business model performance distinguished four processes of value design for the firm: external value design and three types of value creation (collaborative, internal and competitive). In each process, researchers identified a diversity of innovation elements, which could explain what supports or destroys the value for the firm, or the stakeholders of its ecosystem (column 2). To discuss the impacts of these “value objects”, they mobilized an amazing diversity of theoretical frameworks of performance (column 3). This reflects both the richness and the dynamics of the study of identified objects, but also the fact that academics are interested in these objects from the point of view of both designers, prescribers and/or receivers. Thus, performance models vary from engineering approaches of quality-costs-delay to more strategic deployments of the organizational capability to provide a sustainable quality to customers (knowledge-based view and resources-based view). According to this high diversity, the value paradigms (column 4), i.e. what it means to “do value” at the end in these academic papers, appear richer than practices focused on economic evaluation might suggest in all fields. Second, the economic approaches to the benefits/costs ratio remain dominant. However we observe a diversity of paradigms within them: some papers will be based on approaches that reduce the value of income that is distant in time (discounted cash flows, net present value), while others will consider these flows as equal in value over time, or only focus on the gains after reimbursements of the initial investments (ROI), or even look only at the cumulative revenues or the growth of revenues. Third, the performance approaches are richer than a purely economic approach. The contemporary debate induces a large mobilization of qualitative or multi-criteria paradigms (e.g. balance of resources according to their competitive specificities in the lineage of Barney [1991] that assess resources’ rareness, imitability and non-substitutability in addition to their intrinsic value). Conceptually, it also supports an open discussion of relevant elements to consider in a benefit/cost approach for the customer (including customer fidelity, the total cost of ownership, affordability and durability), for all beneficiaries of goods at the firm level (market share, top-management teams efficiency) and at the ecosystem level (international competitiveness, threshold effect, patents coverage).

318

Internal value creation

Core competencies, human resources architecture (management systems, skills, training); NPD and creativity Ambidexterity, R&D intensity, managerial cognition Operations performance, corporate value, firm strategies, corporate board and TMT and organization recovery MNE, operational efficiency, BRICs, base of pyramid, logistics, accounting for productive investment

Knowledge-based view

Resource-based view

Corporate governance and performance of firms

Global value chain

Value proposition validation, learning, user innovation communities

Co-creation with customers

Competition, R&D and intellectual property, environmental dynamism and technological diversity

Shared value, organizational capabilities

Knowledge and business ecosystems

Innovation value

Open innovation, co-ownership of IP, investment in technology, economic levers, risks sharing

Knowledge and business ecosystems

Partnership for NPD

Dynamic capabilities, absorptive capacity

Value chain – industry architectures

Public–private collaboration, resource networks, network value (expertise and skills), RBV joint value

BtoB, operational efficiency, subcontracting, outsourcing

IT value for business

Partnership for R&D

Fluency, quality, reporting

Crowdsourcing and value capture

Collaborative value creation

Crowd intelligence, outsourcing

Acquisition – management

External value capture

Main theoretical frameworks of performance Integration, human resource management, motivations, stakeholders, corporate venturing

Studied value objects

Performance source

Table 17.1  Diversity of value approach in contemporary literature on business model performance

Value = max sales. quality. min(costs​.del​ay)

Value = CF​.grow​th € // ζ TMT

Value α benefits/costs // ζ VRIN

Value = multicriteria VRIN

Value = NPV €

Value = DCF €

Value α benefits/costs // ζ VRIN

Value = DCF €

Value = threshold effect

Value α benefits/costs // ζ VRIN

Value = DCF €

Value = ROI €

Value = benefits €

Value α benefits/costs

Value paradigm

319

CSR, stakeholder theory Expectations, environmental dynamism and technological diversity, established value networks, competition, R&D and intellectual property Marketing performance: brand value, reputation, customer value, purchase intention, business intelligence, market sensing capability, perceived value CRM, reputation, early adopters IP, defence, barriers Ambidexterity, R&D intensity, NPD acceleration Blue Ocean Strategy

CSR – environmental responsibility of business

Innovation value

Offer performance

Value of customer

Patent value

Firm resources in dynamic environment

Value innovation

Value analysis, soft and hard value

Value management Foresight, BM innovation, value-added, BM dynamics, globalization, creation and capture system

Competitive advantage, added value, CSR, entrepreneurial actions and environmental jolts, positive psychological capital

Value chain – innovation

Competition by business model

Cultural adaptation of new products, diversity and standardization

Value chain –global and innovation capabilities

Value = margin of new product

Value α benefits/costs

Value = ROI

Value = customer fidelity, TCO

value = market share. customer value

value = market share​.​nb of new products

Value = multicriteria context

value = market share​. bolu​me

Value α benefits/costs

Value = market share​. volu​me

Value = market share​. volu​me

Value = ROI €

Notes:   DCF, discounted cash flow; NPV, net present value; ROI, return on investment; TCO, total cost of ownership; TMT, top management team; VRIN, valuable rare inimitable non-substitutable.

Competitive value creation

Worldwide balance of workload, skills diversity

Value chain – global and human resources

320  Handbook on innovation and project management

Thanks to this diversity, it’s easier to tackle the challenge of proposing formal performance models more adapted to contemporary industrial dynamics of competition (open innovation, high velocity, ultra-competitiveness, sustainability, etc.) than the paradigm of short-term economic profitability. These works propose changes in the foundations of the definition of value that are more profound than the usual criticism of ROI short-termism to focus on what constitutes value, beyond profitability. Doing so, this field gives powerful insights to challenge the engineering approach of value management in innovation projects as these dimensions are not deployed in value management tools for the moment. Strategic Tools for Firm Valuing The stakeholders of the decision space On the other side of project value management, decision-makers and strategic committees focus on firm performance. Their power and ability to improve the firm performance are often associated with the decision to allocate resources to innovation activities because it’s one of the most visible actions taken by the executive management. There are a lot of other impacts they manage: they explain and diffuse within the firm a strategy that presents the expected utility objective to be reached collectively (vision, common purpose), they develop decisionmaking preferences (rule of profit control) and establish a meta distribution of resources (strategic plan). All these actions embody rules for value management and highlight an expected strategic playground for innovation projects. Moreover, through the delegation of restricted areas of responsibility, the representatives of executive management in the organization – individual “decision-makers” or decision-making committees – are responsible for deploying the vision and applying the preferences. Thus, theoretically, all the decisions taken to allocate resources are consistent across the organization. To do so, “local” decision-makers rely on in-house strategic material but also on accounting and purchase teams to optimize resource allocation and on industrial forecast tools (foresight, technological watch, economic intelligence) to deploy the vision at the level of their delegation. These actors form the decision space of the organization: they are stakeholders with specific logics of coordination and cohesion linked by their power in the organization, according to (Mitchell et al., 1997). The value in the decision space Building on the same literature, Table 17.2 synthesizes the main sources of firm performance for decision makers, providing an overview of studied objects and the theoretical framework of performance mobilized per authors (columns 1 to 3). We added information on the performance models of the firm as they are more formalized in firm value research than in business model ones (column 4) and completed the analysis with the value paradigm of researchers (column 5). Four main sources of performance are identified by academics to increase the value of the firm: (i) corporate governance, (ii) resources management and coalition management, (iii) value chain and (iv) marketing. As detailed in Table 17.2, value objects range from very classical objects of governance and strategy (venture capital, funding, added value, commercial success) to more recent ones (CSR, board management, reputation, etc.). As we expect, due to the focus on firm profits, the theoretical frameworks and performance models are deeply rooted in a financial approach to performance (profit growth, operating margin, share value,

321

V(firm) = share value = f(market capitalization, dividends)

Governance – Corporate boards performance, corporate boards and shareholder impact performance

Shareholder value

Resources and coalition management

V(firm) = multicriteria {TMT valuation, trust}

Hedge funds, contrarian funds

Funding (funds)

Joint value, partnerships, RBV and valuation of shared tangible and intangible assets, KBV and organizational performance Economic leverage, entry barriers IP valuation

Networks and ecosystems (RBV and KBV)

Investment in technology

Patent value

Maximization, CSR impact, reputation

V(firm) = share value = f(capitalization, Financial Volatility Index)

Acquisition, competition advantage, venture cap

Corporate venture capital

Value = share value growth.dividend €

Value = CF​.grow​th € // multicriteria TMT

Value = DCF €

Value = cost reduction €

Value = benefits €

Value paradigm

V(firm) = IP weight = f(portfolio size, annual rates of deposit, patent licensing, scientific publications)

V(firm) = investment size = {threshold effects, ROI, IP, NPV, R&D annual investment, publication rates)

(Continued)

Value = patents number /y

Value = DCF €

V(firm) = VRIN model of resources Value α benefits/costs // (valuable, rare, inimitable, non-substitutable) multicriteria VRIN V(firm) = multicriteria on knowledge {R&D invest, patent deposits, publications, firm size, PPP investment, CIR}

V(firm) = fund size (€/nbSU) = f(expected capitalization of start-up, equity stake, expected market share, SVA, portfolio ROI)

V(firm) = profits​.grow​th = {EVA, SVA, market share}

Financial performance

Corporate value

Performance models

Corporate governance

Main theoretical frameworks of performance

Studied value objects

Performance source

Table 17.2  Diversity of value approach in contemporary literature on firm value

322

Marketing

Value chain

Performance source

Worldwide markets (sells, manufacturing) BtoB, integration, subcontracting, buyer/seller Competition, pioneers, market exit risks Firm identity, organizational identity

Globalization

Industry architectures

Innovation and new technology

Reputation Offer coherence and diversity, brand value, customer value, perceived value, CRM, product diversification, customer satisfaction

Efficiency of operations and stock in value chain

Added value

Commercial success

Incentives and knowledge maximization

KBV – NPD and creativity

Value = max SQ min(CD)

Value = share value. dividend €

Value = DCF €

value = market share​.volu​ me €

v(firm) = f(value proposition, perceived value, value = market share. Bowman Scale, product range, time to market customer value € performance, market share)

V(firm) = share value dynamics (growth and volatility)

V(firm) = investments risks valuation (ROI, NPV, IP), market share on new products

V(firm) = operations performance and efficiency

ROI, international ranking on market, growth Value = ROI €

V(firm) = efficiency (QCD).safety

Value α benefits/costs

Value = operating margin (ranking per sector)

V(firm) = firm ranking (market share, stock market)

International balances of good manufacturing, operations performance, contingency, idiosyncratism V(firm) = rate of converted project, invest R&D, market share new product and CA

Value = costs € // multicriteria VRIN

V(firm) = size.multicriteria {HR skills, core competencies structures)

RBV – human RBV, slack, breakdown resource architecture structure, organizational performance, HR model of tangible and intangible assets

RBV – multinational enterprise management

Value paradigm

Main theoretical frameworks of performance

Performance models

Studied value objects

Table 17.2  (Continued)

Value management of innovation projects  323

etc.). Therefore they almost systematically mobilize the economic tools for optimizing the short-term valuation of investments based on profitability calculation models: the return on investment (net profit divided by total investment, expressed in percentage or rate); and net present value (with a few debates on the closeness of it standardized rate to the weighted average cost of the capital). As performance models are more and more sophisticated, greater details (translating into better data reliability) are available for decision-makers. For example, work on the calculation of share value, although based on discounted cash flows, mobilizes volatility calculation tools allowing a richer vision of the arrival of newness on the market than the modelling of the gains from a new product. Some research works in the R&D management and engineering research field focused on the crossroads of the performance of firms and business models’ profitability. In particular, research on value management tools for NPD project committees focuses mostly on three dimensions dedicated to decision space stakeholders: • • •

Simulation tools for the value engineering of economic performance (such as NPV simulation for various scenarios). Valuation tools for the industrial property beyond the object (mainly to study the impact of patents on competition and partnerships). Portfolio visualization tools (such as strategic road-mapping) (Phaal and Muller, 2009).

These modelling efforts highlight a key point of value management: the economic value paradigm – and specially discounted cash flow approach – constitutes a bridge between the decision space and the design space. The attention and frustrations developed by all stakeholders on this tool result from this particular status of economic assessments. Indeed, tools for decision-making include data that all stakeholders are looking at: economic optimization models focused on the benefits from the marketing of innovative offers where value is a function of customer value and the costs that generate it. Nevertheless, the decisional models study the impact of time on the financial gain in risk (mainly by discounting) but could also study the profit in progressive capitalization (earn value), looking at the interdependencies of investments (real options) (Trigeorgis and Tsekrekos, 2018) or the impact of the unknown on profitability (Le Masson et al., 2019). However, these instrumental works have traditionally been of concern within the research community which remains more focused on the management of R&D and engineering activities, without the ambition to improve value management at the company level. Symmetrically, scholars publishing in the strategic field or general management have mostly focused on epistemic models for business model performance and firm value, opening value meaning at the firm level but without attention to the specific need of coordination carried by management tools at the project level. Once again, this dichotomy highlights the division between strategic and operational management in the research field. Moreover, it results in a damageable lack of attention from management researchers on the issue of value management as a process to master between a large diversity of internal stakeholders from both professional areas (Hooge and Dalmasso, 2015). In an innovation project, the resulting tension peaks. Indeed, most management scholars focus their research on strategic management. Since the 2000s, a huge effort has been led in the study of the mechanisms of firm internal value creation, through cooperation or competition and the associated concepts of capture and absorption of external value. Simultaneously, a lot of research has emerged on the other hand of firm value

324  Handbook on innovation and project management

(works on shareholder value, CSR impact, and the performance of investment in technology). All these works are of interest to decision-makers but they are disconnected from the project management toolbox they are used to handling in their daily work. Thus, it increases their feeling of complexity and uncontrolled consequences when they need to decide on innovation investments on the economic assessment of the innovation project. Characterization of Value Space To conclude this literature analysis, it appears that a variety of research has led to the development of numerous and stimulating foundations of the notion of value in management, especially to integrate and handle contemporary societal debates. However, on the ground, practitioners have been suffering daily from the unsuitability of NPV to highlight the potential of innovation projects they are carrying, and they remain helpless: rather than being inspired by this stimulating diversity from academia, they feel overwhelmed by an impractical proliferation of concepts. This gap between practices and research is still ongoing and particularly problematic in the case of innovation projects. This leads to a feeling of fragmentation for value management engineering, although its unification is one of the main objectives of practitioners. Indeed, the instrumental elaborations of the new concepts seem poorly effective. This can be seen with the discrepancies in the valuation of intangible assets in accounting, the creation of value which refers to different hypotheses in finance and strategy, and the same for the concepts of the value of the brand or the customer value in marketing or even business valuation and market value in finance and governance. However, our analysis of the recent literature shows that the underlying formal models are not that varied: the vast majority of tools for managing the performance of innovation activities remain strongly financialized (focusing on “outputs” and its beneficiaries). This induces several structuring hypotheses that emergent contemporary approaches try to overcome to introduce cognitive and social flexibility that is more representative of the fast-changing environments of contemporary innovation. Several focal points are therefore possible to design alternative concepts of value in innovation activities and are mobilized by management researchers. They first try to deconstruct the impact of financial assumptions on the firm, the market and the customer when they are applied in situations of radical innovation. Then, they focus on the robustness of the models mobilized by practitioners. On the one hand, some propose to restrict the field of investigation by temporarily isolating certain actors in the organization and specifically equipping certain professions so that they can introduce uncertainty and the unknown into their contributions to the construction of the value of innovation. Thus, we observe the development of instrumentation dedicated to innovation by functions (R&D, production, marketing, HRM, strategy, accounting/control, finance, administration, governance and shareholders). These approaches support an increasing ability of experts from these departments to subjectively describe the probability they associate with an innovation scenario they are discussing with the project leader in the design space (Figure 17.5). Another approach is to study the established forms of involvement of innovation stakeholders (contracts, partnerships, subsidies, regulations, competition) to renew their instruments to integrate the radical uncertainty and the unknown. Finally, a third approach consists of analysing the incentive systems at work in innovation ecosystems which seeks to introduce exogenous valuations encouraging collective action.

Value management of innovation projects  325

Figure 17.5  Feeding design and decision spaces with data about innovation value Even if these three approaches encounter the same difficulties with information – identification of missing knowledge and treatment of new knowledge – they refer today to radically different models of social process to design the value without a common understanding of the concept of value. This inevitably leads to an explosion of concepts manipulated by stakeholders, to document the value of the innovation. Thus, associated evaluation tools are as difficult to understand for researchers and practitioners in innovation management. However, in the context of intensive innovation, the competitiveness of companies depends on the efficiency of their management of innovation projects. Therefore, there is a managerial and instrumental gap between, on the one hand, the massive use of traditional economic and strategic indicators allowing the evaluation of innovation activities and, on the other hand, the understanding of the strong uncertainties on techniques and markets, and the social complexity of the motivations allowing the commitment of actors and resources to innovative activities. This discrepancy felt by the actors is widening quickly in the face of the application of a single performance regime in most organizations, necessary for coordination, but almost systematically based on a financialized value approach. This discrepancy leads decision-makers and project managers to interact through two processes of data reduction in the value space that we are now able to describe (Figure 17.6). The main aim of these processes is to support an efficient resource allocation on NPD projects at the project and portfolio levels. On the one hand, there is an interactive process of innovation assessment on why the project should go on (upper arrow in Figure 17.6). In a portfolio management process, decisionmakers prioritize their resource allocation choices to maximize the benefits from each of these investments. Decision-makers build on the expected utility they consider the project could reach. To do so they rely on the data they have about competition and corporate strategy from a diversity of channels: scenarios about the firm’s environment dynamics (mainly from the firm strategic department) and scenarios about the firm’s internal resources availability (mainly from accounting stakeholders) and possibilities to externalize or share the workload (mainly from internal stakeholders of strategic purchase and partnerships). From these hypotheses, decision-makers give goals to the project leader about the expected performance of the project. Building on his/her experience and knowledge of project management within the firm and in the industrial sector, the leader then converts these goals into performance measurement criteria he/she could manage to actively steer the project completion

326  Handbook on innovation and project management

Figure 17.6  The two processes of data reduction in the value space and distribute the work among the stakeholders of the design space. This presupposes the existence and clarification of a performance target, shared between the players, to support the coordination between design space stakeholders. Facing the complexity of data and people networks, the project leader pre-orders these performance criteria according to his/her perception of strategic importance in the rationales presented to decision-makers during project committees. On the other hand, there is a process of strategic planning on how the project should be conducted (lower arrow in Figure 17.6). Project managers gather subjective probabilities from the experts involved in the project about the reliability of simulated earnings or losses the project could generate (from a business model point of view). They also have information from intermediate objects designed during the projects (technical prototypes as commercial experimentations). Moreover, they massively expose decision-making committees to modelling of the so-called “expert” probability distributions, the reliability of which the decisionmakers assess, then gradually clarify with the progress of the design. As the latter is only possible in the last steps of NPD processes, the nature and legitimacy of “experts” chosen by project leaders to highlight the robustness of their work become a key point at the heart of value management. All data allow them to present to decision-makers an estimation of the performance the project could reach, and what they consider the best organization and technical solutions to adopt to increase the probability of achieving this performance. Confronting these data to their knowledge of internal resources availability and corporate ambition, decision-makers estimate the reliability of commercial and industrial options exposed by the project leader. Then, they deduce from their experience and their knowledge of the other ongoing projects what they consider a realistic probability of earnings from the future completion of the project. This situation is an attempt to model uncertainties embedded in the project as recommended in decision theory, but knowledge is asymmetrical between actors and of a heterogeneous nature, both on action effects and states of the world (Pich et al., 2002). Moreover, it has been demonstrated that stakeholders not only managed uncertainty and complexity but were also unknown in innovation projects (Le Masson et al., 2019; Loch et al., 2011; Stoelsnes, 2007). Beyond calculus, this particular context induces relational discrepancies between stakeholders that disagree on information reliability. Thus, Loch et al. (2017) show that the knowledge gap between project managers and the steering committee constitutes an important problem to steer a project that managers “don’t fully understand”.

Value management of innovation projects  327

The engineering of the value space aims to establish an efficient place of interaction between the stakeholders in decision-making and project leaders: innovation assessment on the one hand and strategic planning on the other hand are not independent and fully sequential processes, it’s more a redundancy loop to allow the coupling between the value within the two worlds.

PERSPECTIVES FOR THE VALUE MANAGEMENT OF INNOVATION PROJECTS The modelling of contemporary value management in the NPD process allows us to understand the growing difficulty of managing the performance of innovation projects and opens new perspectives for project management. Firstly, the management discipline has entered for over ten years into an epistemological emulation of innovation purpose within a firm, discussing both the performance of the business model and the firm as a process of value meaning to be managed (Levillain and Segrestin, 2019). Indeed, since the global economic crisis, innovation has become a questionable way of progress for both industrial and societal sustainability. To this has been added in recent years the increasing recognition by practitioners of the impacts of industrial and economic activities on climate change and biodiversity decline and the emergency to reduce energy consumption and transform consumption behaviours (IPCC, 2022). Likewise, profit and technological abundance are more and more dubious logics of performance to target in innovation projects: these goals are not rejected but they are insufficient to attract people and fund such risky activities. All create a strong feeling of discomfort during project reviews that remain mainly structured on economic simulations of profitability. We try in this chapter to underline how internal stakeholders of innovation projects, from both design and decision spaces, are involved in supporting this paradigm shift through a new data collection process. Thus, we observe the emergence of various conceptual models of firm value design and business model design (for example, in the renewal of consumer models, in the logic of competition leading to the sustainability of firms as creative organizations, or in the beneficial dynamics of internal and external collaborations, etc.). The instrumental maturity of new approaches of value in NPD processes is unclear for practitioners and largely perceived as less robust when facing engineering tools of economic performance simulation. Moreover, the “best” level of value analysis is now largely debated in the literature and practices – is it the firm, the business units, projects or portfolios, the value chain or the ecosystem? Whereas projects remain on the operational grid in the vast majority of firms and tools used to evaluate projects are still embodying the assumption of their independence, mainly due to an accounting process that isolates them in the cost accounting engineering. This gap between, on one hand, an open and active epistemic search to redefine the meaning of innovation value, with a diversity of new paradigm proposals between stakeholders communities, and, on the other hand, a stable engineering of economic tools at the project level (that is shared by all stakeholders) results in increasing difficulty of mutual understanding between people. Indeed, if strategic and operational communities largely share the same language on performance management tools – cash flows and growth analysis, return on investments, market share, etc. – they do not share an extended language of value to describe benefits from innovation projects. This gap creates daily tensions in the NPD process and

328  Handbook on innovation and project management

more widely in the decision and design networks (Loch et al., 2017). Consequently, the first main challenge for value management becomes how to build a general theoretical model of innovation value that supports stakeholders’ generative collaboration beyond the monetary paradigm. Fruitful perspectives are still under exploration and the concept of firm value has been strongly challenged in strategy or governance research for the last 20 years. This leads researchers and practitioners to work on renewing models to meet contemporary challenges more than on adapting old ones. Thus, international efforts on the theoretical modelling and practical implementation of profit-with-purpose corporations are a good example of a large epistemological debate on what the firm value is (e.g. Levillain and Segrestin, 2019; Segrestin et al., 2021). On the other hand, we saw that the engineering design literature regularly discusses the concept of innovation performance through the benefit/cost paradigm. The contemporary engineering community builds on it to propose new models and approaches of business models generation through a rich language of value creation (“benefits”) and complex technical systems (“costs”) for a large range of stakeholders of the innovation ecosystem far beyond the actors of the value chain. Beyond previously cited works of design theorists (Hatchuel et  al., 2011; Thomas and Tee, 2021), generativity appears as the new relevant paradigm to describe innovation benefits and to manage the value space that bridges decision-makers and project leaders. But as for “firm value”, there is no common model of what is generativity in an innovation project (see Thomas and Tee, 2021 for an overview of the concept). Consequently how to manage generativity emergence in NPD processes is a rich perspective to investigate. If the first challenge of the value management of innovation projects is epistemic, the second challenge opened up by contemporary changes is one of the evaluation techniques. There is a specificity to the evaluation exercise of an innovation activity: it is a design project. Therefore it combines the technical challenges of risk simulation with scenarios that contain elements of the unknown since learning is at the heart of innovative design. Whereas the definitions that designers use to describe the potential of the benefits and costs continue to evolve and enrich themselves (see earlier section), evaluation techniques should be able to take into account simultaneously: i) A heterogeneity of risks and uncertainties about benefits and costs within the same project. ii) The sudden emergence of unknown elements during the exploration process, which changes the expected benefits of the project. Numerous studies on data exchanged in the decision-making process of innovation projects make it possible to highlight and describe the reliability of the assessment of expected profitability in the value space (Lenfle and Loch, 2010; Lenfle, 2011; Loch et al., 2017; Le Masson et al., 2019). These authors help to establish a lexicon of data reliability for projects that is much more elaborate than the classic Knightian division (known and reliable data, risk, and uncertain, unknown and chaotic data), whose main impact on practitioners is probably the distinction between different kinds of unknowns in the design process. Thus, they propose to distinguish “known unknown” from “unknown unknown” to underline that a part of the unknown is conceivable and identified by design stakeholders (Loch et al., 2011; Stoelsnes, 2007). Le Masson et al. (2019) instruct the technical impact of some “desirable unknowns”3 on the economic evaluation, highlighting the fact that designers voluntarily target proposals

Value management of innovation projects  329

that do not exist. Gilain et al. (2019) for example show how the generation of unknowns in the NPD portfolio allows profitable management of the accumulation of heterogeneous uncertainties in the design process of complex technological objects such as aeronautics. To overcome the technical difficulty, many firms try to reduce the main sources of unknowns (lack of knowledge and complexity) through the thematic organization of NPD steering committees. However, recent work by Christoph Loch and colleagues shows that a classic segmentation by nature of the activity – R&D projects, engineering services, organizational changes and IT projects – exposes decision-makers to similar difficulties of management: • • •

Diverging interests between stakeholders, which lead to practical issues on the committee composition and agreement on its goal. Quality of interaction between design teams and top managers, which impacts motivation and control of each stakeholder. The novelty and complexity of the project, which induce misunderstanding of project key drivers and barriers.

This imposes on decision-makers continuous intelligence-gathering and personal involvement in managing surprises and changes (Loch et al., 2017). We also demonstrate that stakeholders’ interactions in the design space generate massive impacts in terms of involvement or rejection of innovation projects (Hooge and Dalmasso, 2015). Consequently, the second main challenge for value management becomes how to build a general theoretical model combining uncertainty and unknown evaluation that supports stakeholders’ desirable and attractive collaboration beyond the monetary paradigm. The avenues we have just mentioned are all interesting perspectives to explore to develop tools adapted to the value space, both to efficiently instruct the innovation assessment process and the strategic planning process. We believe that the most ambitious challenge for value management is to combine both previous perspectives to tackle the issue of developing a theoretical model of the value of the unknown within the firm that supports the coherence between this triple dimension of an innovation project: generativity, desirability and attractiveness.

NOTES 1.

The notion of the identity of the object is developed in the section “Operational Tools for Business Model Performance”, p. 316. 2. In 2016, we carried out a systematic analysis exercise of the management literature mobilizing centrally the notion of value. For this, we selected 20 international journals highly ranked by CNRS, the French research institution (respectively the five best in four fields of management research – strategy, general management, innovation and R&D), then we systematically isolated the articles published since the creation of journals until 2015 in which the authors made a direct reference to the concept of value in management in the title. In the period 2006–2015, this corresponds to 419 publications, well distributed in each of the four research fields (Hooge, 2020). 3. “Desirable unknown” is a key concept in design as it is the resource that supports the creative effort at both individual and collective levels. Le Masson et al. (2019, 477) defines it as a concept in the sense of C-K theory: “an incomplete proposals that guide us towards the emergence of new values, uses, and identities of objects (e.g., products, services, processes, and business models) and new knowledge”. From the innovation project perspective, a “desirable unknown” for both the firm and involved individuals gathers three dimensions: cognitive generative power, collaborative attractiveness for new organizations experimentation and strategic positioning renewal of the firm in quickly evolving environments (Hooge et al., 2019).

330  Handbook on innovation and project management

REFERENCES Adams, R., Bessant, J., and Phelps, R. (2006). Innovation management measurement: A review. International Journal of Management Reviews, 8(1), 21–47. AS/NZS 4183 (1994). Value management. Joint Technical Committee OB6. Standards Australia and Standards New Zealand, Sydney, Australia. Baker, N. and Freeland, J. (1975). Recent advances in R&D benefit measurement and project selection methods. Management Science, 21(10), 1164–1175. Baldwin, C.Y. and Clark, K.B. (1994). Capital-budgeting systems and capabilities investments in US companies after the Second World War. Business History Review, 68(1), 73–109. Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. Bititci, U., Garengo, P., Dörfler, V., and Nudurupati, S. (2012). Performance measurement: Challenges for tomorrow. International Journal of Management Reviews, 14(3), 305–327. Börjesson, S., Elmquist, M., and Hooge, S. (2014). The challenges of innovation capability building: Learning from longitudinal studies of innovation efforts at Renault and Volvo Cars. Journal of Engineering and Technology Management, 31, 120–140. Bowen, P., Edwards, P., Cattell, K., and Jay, I. (2010). The awareness and practice of value management by South African consulting engineers: Preliminary research survey findings. International Journal of Project Management, 28, 285–295. Christensen, C., Kaufman, S., and Shih W. (2008). Innovation killers. How financial tools destroy your capacity to do new things. Harvard Business Review, January, 98–105. Cooper, R.G. (2014). What’s next?: After stage-gate. Research-Technology Management, 57(1), 20–31. Cooper, R.G. and Sommer, A.F. (2018). Agile–Stage-Gate for manufacturers: Changing the way new products are developed integrating agile project management methods into a stage-gate system offers both opportunities and challenges. Research-Technology Management, 61(2), 17–26. Dell’Isola, A. (1966). Value engineering in the construction industry. Civil Engineering, 36(9), 58–61. Demil, B., Lecocq, X., and Warnier, V. (2018). “Business model thinking”, business ecosystems and platforms: The new perspective on the environment of the organization. M@n@gement, 21(4), 1213–1228. Ellis, R.C., Wood, G.D., and Keel, D.A. (2005). Value management practices of leading UK cost consultants. Construction Management and Economics, 23, 483–493. Gilain, A., Le Masson, P., Levillain, K., Marin, Y., and Weil, B. (2019). How to enhance the profitability of your project portfolio – by reducing uncertainty or exploring the unknown? IPDMC, June, Leicester, United Kingdom. Gillier, T., Hooge, S., and Piat, G. (2015). Framing value management for creative projects: An expansive perspective. International Journal of Project Management, 33(4), 947–960. Green, S.D. (1994). Beyond value engineering: SMART value management for building projects. International Journal of Project Management, 12(1), 49–56. Green, S.D. (1997). A Kuhnian crisis in value management. Value World, 20, 19–24. Hatchuel, A., Le Masson, P., Reich, Y., and Weil, B. (2011). A systematic approach of design theories using generativeness and robustness. In DS 68-2: Proceedings of the 18th International Conference on Engineering Design (ICED 11), Impacting society through engineering design, vol. 2: Design theory and research methodology, Lyngby/Copenhagen, Denmark, 15.-19.08. 2011 (pp. 87–97). Henriksen, A.D. and Traynor, A.J. (1999). A practical R&D project-selection scoring tool. IEEE Transactions on Engineering Management, 46(2), 158–170. Hooge, S. (2020). The value of the unknown in the firm: Modeling strategies, tools and collective dynamics of intensive innovation performance. Research summary, Dauphine - PSL University, 139p. Hooge, S. and Dalmasso, C. (2015). Breakthrough R&D stakeholders: The challenges of legitimacy in highly uncertain projects. Project Management Journal, 46(6), 54–73. Hooge, S. and Hatchuel, A. (2008). Value indicators and monitoring in innovative PDM: A grounded approach. Proceedings of XVe IPDMC, Hamburg, Germany. Hooge, S., Klasing Chen, M., and Laousse, D. (2019). Managing the emergence of concepts in fuzzy front end: A framework of strategic performance and emerging process of innovation briefs. Proceedings of EURAM Conference. Lisbon, Portugal.

Value management of innovation projects  331

Hooge, S., Kokshagina, O., Le Masson, P., Levillain, K., Weil, B., Fabreguettes, V., and Popiolek, N. (2016). Gambling versus designing: Organizing for the design of the probability space in the energy sector. Creativity and Innovation Management, 25(4), 464–483. IPCC (2022). Climate change 2022-impacts, adaptation and vulnerability, summary for policymakers. In Working Group II contribution to the sixth assessment report of the intergovernmental panel on climate change. Switzerland, 40p. Jepsen, A.L. and Eskerod, P. (2009). Stakeholder analysis in projects: Challenges in using current guidelines in the real world. International Journal of Project Management, 27(4), 335–343. Kavadias, S. and Chao, R.O. (2007). Resource allocation and new product development portfolio management. In Christoph Loch and Stylianos Kavadias (Eds.), Handbook of new product development management (pp. 151–180). London: Routledge. Kengpol, A. (2002). The technology selection approach for group decision-making in the evaluation of information technology. The Journal of KMUTNB, 12(4). Le Masson, P., Hatchuel, A., Le Glatin, M., and Weil, B. (2019). Designing decisions in the unknown: A generative model. European Management Review, 16(2), 471–490. Le Masson, P., Weil, B., and Hatchuel, A. (2010). Strategic management of innovation and design. Cambridge University Press. Lenfle, S. (2011). The strategy of parallel approaches in projects with unforeseeable uncertainty: The Manhattan case in retrospect. International Journal of Project Management, 29(4), 359–373. Lenfle, S. (2016). Floating in space? On the strangeness of exploratory projects. Project Management Journal, 47(2), 47–61. Lenfle, S. and Loch, C. (2010). Lost roots: How project management came to emphasize control over flexibility and novelty. California Management Review, 53(1), 32–55. Lettice, F. and Thomond, P. (2008). Allocating resources to disruptive innovation projects: Challenging mental models and overcoming management resistance. International Journal of Technology Management, 44(1), 140. Levillain, K. and Segrestin, B. (2019). From primacy to purpose commitment: How emerging profitwith-purpose corporations open new corporate governance avenues. European Management Journal, 37(5), 637–647. Liberatore, M.J. and Stylianou, A.C. (1995). Expert support systems for new product development decision making: A modeling framework and applications. Management Science, 41(8), 1296–1316. Loch, C.H., DeMeyer, A., and Pich, M. (2011). Managing the unknown: A new approach to managing high uncertainty and risk in projects. John Wiley & Sons. Loch, C.H., Mähring, M., and Sommer, S. (2017). Supervising projects you don’t (fully) understand: lessons for effective project governance by steering committees. California Management Review, 59(2), 45–67. Miles, L.D. (1961). Techniques of value analysis and engineering. New York: McGraw-Hill. Mitchell, R.K., Agle, B.R., and Wood, D.J. (1997). Toward a theory of stakeholder identification and salience: Defining the principle of who and what really counts. Academy of Management Review, 22(4), 853–886. Morton, A., Keisler, J.M., and Salo, A. (2016). Multicriteria portfolio decision analysis for project selection. In S. Greco, M. Ehrgott, and J. Figueira (Eds.), Multiple criteria decision analysis, Vol. 233, pp. 1269–1298. New York, NY: Springer. NF X50-153 (1985). Recommandations pour la mise en œuvre de l’analyse de la valeur (revue en septembre 2009). Association française de normalisation (AFNOR). Pahl, G. and Beitz, W. (1977). Konstruktionslehre (English title: engineering design) (English ed.). Springer Verlag, Heidelberg: The Design Council, London. Phaal, R. and Muller, G. (2009). An architectural framework for road mapping: Towards visual strategy. Technological Forecasting and Social Change, 76(1), 39–49. Pich, M.T., Loch, C.H., and Meyer, A.D. (2002). On uncertainty, ambiguity, and complexity in project management. Management Science, 48(8), 1008–1023. Saaty, T.L. (1980). The analytical hierarchy process. New York: McGraw-Hill. Savall, H. and Zardet, V. (2008). Mastering hidden costs and socio-economic performance. Charlotte: Information Age Publishing, 376p. SAVE (1998). Value methodology standard. Society of American Value Engineers International.

332  Handbook on innovation and project management

Segrestin, B., Hatchuel, A., and Levillain, K. (2021). When the law distinguishes between the enterprise and the corporation: The case of the new French law on corporate purpose. Journal of Business Ethics, 171(1), 1–13. Sethi, R. and Iqbal, Z. (2008). Stage-gate controls, learning failure, and adverse effect on novel new products. Journal of Marketing, 72(1), 118–134. Souder, W.E. and Mandakovic, T. (1986). R&D project selection models. Research Management, 29(4), 36–42. Stoelsnes, R.R. (2007). Managing unknowns in projects. Risk Management, 9(4), 271–280. Suh, N.P. (1990). The principles of design. Oxford University Press on Demand. Thiry, M. (2001). Sensemaking in value management practice. International Journal of Project Management, 19, 71–77. Thiry, M. (2002). Combining value and project management into an effective program management model. International Journal of Project Management, 20, 221–227. Thomas, L.D. and Tee, R. (2021). Generativity: A systematic review and conceptual framework. International Journal of Management Reviews, 24(2), 255–278. Trigeorgis, L. and Tsekrekos, A.E. (2018). Real options in operations research: A review. European Journal of Operational Research, 270(1), 1–24. Yu, A.T.W., Shen, Q., Kelly, J., and Hunter, K. (2005). Application of value management in project briefing. Facilities, 23, 330–342. Zaman, K., McDonald, M., Mahadevan, S., and Green, L. (2011). Robustness-based design optimization under data uncertainty. Structural and Multidisciplinary Optimization, 44(2), 183–197.

18. Blending novelty and tradition in creative projects: how robust project design and conventionality shape the appeal of operatic productions Giulia Cancellieri, Gino Cattani and Simone Ferriani

INTRODUCTION Projects are presented in the organizational literature as purposeful mechanisms to facilitate the combination of different resources and competencies and to manage tasks that are timelimited and typically performed by a semi-temporary collection of individuals with heterogeneous expertise who collectively enable the host organization to transition from one state of performance to a new state (Lundin and Söderholm, 1995; Cattani et  al., 2011). Firms have become increasingly reliant on projects to support the development of new and complex products precisely because firms generally find it difficult to combine the range of resources needed to fuel new product development processes (Gann and Salter, 2000; Brady and Davies, 2004; Manning, 2008). Indeed, a vibrant stream of research focuses on how “temporary organizations, generally projects, are articulated within the continuous, so called permanent organizations” (Lenfle et al., 2019, 519). The creative industries provide many opportunities for the observation and analysis of such project-based forms of organizing (Castaner and Campos, 2002; DeFillippi, 2015). The production of theatrical plays (Goodman and Goodman, 1976), movies (Ferriani et al., 2009), videogames (Ayoama and Izushi, 2003), music (Lorenzen and Fredriksen, 2005; Ordanini et  al., 2008; Sedita, 2008), TV productions (Manning and Sydow, 2011) and advertising (Grabher, 2004) are all typical examples of contexts where project-based organizing is the privileged organizing approach to address some of the key challenges associated to the development of new products. Paramount among such challenges is how to establish legitimacy while simultaneously demonstrating novelty (Navis and Glynn, 2011). This challenge reflects two competing approaches on how to signal the value of a new product to the market. On the one hand, in their search for market success, firms must organize innovative projects that pique audience curiosity and generate excitement. On the other, they need to be ready to satisfy the expectations of audiences that “demand familiarity to understand what they are offered” (Lampel et al., 2000, 264). Even if novelty surprises, provokes and entertains audiences, it is understood and appreciated only with respect to the “familiar” against which it is gauged and interpreted (Cattani et al., 2020; Keuschnigg, 2015; Slavich and Castellucci, 2016; Lampel et al., 2000). This tension is particularly acute in the creative industries where a few hits dominate the market and consumers often treat variation as deviant (Phillips and Kim, 2009; Younkin and Kashkooli, 2020). Strategy and organizational scholars have suggested that firms can best address this 333

334  Handbook on innovation and project management

tension by pursuing optimal distinctiveness – i.e. choosing a position that is optimally poised between being the same and being distinctive – to ensure that firms are “as different as legitimately possible” (Deephouse, 1999, 147; see also Durand and Kremp, 2016; Zhao et al., 2017; Zhao et al., 2013). Yet questions remain on how firms can configure their product development projects to pursue an optimally distinct market position. We address these questions in the Italian opera industry, which we examine in light of recent work that has focused on the strategic choices that can be made to increase the reception of new products (Cattani et  al., 2017; Kim and Jensen, 2011; Younkin and Kashkooli, 2020). Italian opera houses are non-profit companies that experience strong pressures to simultaneously preserve and deviate from an established tradition as they are expected to both introduce novelty into their programming strategies and capitalize on the audience’s familiarity with revered operatic material. As opera houses are project-based organizations where “projects are represented by shows” (Mariani, 2007, 105) and each staged opera is a new project that (re)interprets an existing opera, focusing on shows’ (project) characteristics and distinctive features allows us to examine how tradition and innovation combine in opera houses’ project design choices and how these choices affect market appeal. To this end, we analysed industry archives and conducted interviews with opera managers to gain a deeper understanding of the factors that shape operatic performance. We then used this understanding as a basis for developing and testing our theoretical arguments. In line with research on optimal distinctiveness, opera houses can achieve an equilibrium between preserving and renewing a revered tradition by pursuing what we term a robust project design strategy. A robust design involves framing novelty in familiar terms through the design of “the particular arrangement of concrete details that embodies an innovation” (Hargadon and Douglas, 2001, 478). To bring this to the context under study, in our prior work we have suggested that opera houses can revive past cultural projects through robust design strategies, that is, through reinterpretations that preserve what the target audience perceives as the most familiar aspects of a particular operatic tradition while departing from that tradition on other more peripheral attributes (Cancellieri et al., 2022). Unlike exploratory projects that “are frequently first-of-a-kind projects, exploring new technology, uses, business models, or strategic opportunities” (Lenfle et al., 2019, 519; see also Brady and Davies, 2004; Lenfle, 2008), this project design strategy allows firms to reconcile novelty and familiarity by pursuing innovation projects that remain within the boundaries of tradition. In this study, we examine how the effectiveness of a robust project design strategy varies with the strength of the tradition associated with a particular opera, which we measure in terms of opera conventionality. By conventionality, we mean material that is the expression of a well-known operatic tradition (e.g. La Traviata, Madama Butterfly, etc.) and is performed very frequently because it appeals to a broad audience. As a result, even minor deviations from that tradition may elicit poor evaluation if not outright rejection. If instead the material is less conventional and the target audience is less familiar with the original work (and therefore, has no clear expectations), project design strategies that cross the boundaries of tradition are more likely to be well received. Accordingly, we suggest that the degree of opera conventionality moderates the effectiveness of a robust project design strategy; as the level of conventionality of the operatic material increases, the appeal of a robust design will decline because the target audience perceives the departure from tradition as being more salient. We contribute to research on optimal distinctiveness (Deephouse, 1999; Lounsbury and Glynn, 2001; Slavich and Castellucci, 2016; Zhao et al., 2017) and novelty acceptance (Cattani

Blending novelty and tradition in creative projects  335

et al., 2017; Hargadon and Douglas, 2001; Sgourev, 2013) by examining the design choices through which firms seek to be optimally distinctive and improve the appeal of their product offering. After illustrating some important features of the tension between novelty and familiarity in the opera industry and drawing from interviews with key informants that echo and give nuance to the notion of robust project design, we present our arguments on how conventionality moderates the effectiveness of a robust project design strategy. Next, we describe our research design, sample, variables and econometric models. After reporting the results, we conclude with a discussion of the contributions, implications and limitations of our study.

EMPIRICAL SETTING AND HYPOTHESES Optimal Distinctiveness and Robust Project Design in the Italian Opera Industry Our empirical setting is the Italian opera industry during the period 1989–2011. Since Italy is the birthplace of opera, Italian opera houses have been the guardians of tradition and have devoted themselves to preserving a traditional form of art. In deciding which operas to include in their repertoires, they often prioritize traditional, pre-20th-century operas that have come to define operas for many audiences (Gossett, 2008). Examples of traditional operas are La Traviata by Giuseppe Verdi and La Tosca by Giacomo Puccini. As nonprofit arts institutions that exist partly to develop opera, however, opera houses also aspire to innovation and artistic originality which are commonly pursued by including modern and contemporary works in their repertoires. While this is a key indicator of artistic achievement for opera experts, most opera attendees prefer traditional to modern and contemporary operas as they perceive the latter as aesthetically avant-garde and challenging (Jensen and Kim, 2013; Martorella, 1977). Hence, opera houses that aspire to innovate their artistic programmes run the risk of not meeting the expectations of their customers. This, in turn, could undermine their success and survival as government funding cuts and periods of economic contraction have made Italian theatres more reliant on ticket sales: when they stage modern and contemporary works, they pursue artistic originality but often fail to attract the attention and support of the majority of opera attendees; when they stage traditional pre-20th-century works they are more likely to achieve market success but also forgo opportunities to promote novelty and artistic originality. This poses challenges for creative project managers: how should opera houses reconcile artistic exploration with the conservative preferences of current and potential patrons? Recent findings suggest that opera houses can introduce novelty in their artistic programmes and ensure its recognition through a project design strategy that frames novelty in familiar and comprehensible terms (Cattani et  al., 2020; Bielby and Bielby, 1994). Borrowing from innovation management literature (Hargadon and Douglas, 2001) in our prior work we have termed this strategy “robust” to denote a product design that has sufficient inherent versatility to help locate novel product features within the familiar world by invoking valued schemas and scripts, yet preserve the flexibility necessary to allow for the potential evolution of understanding and action that follows use (Cancellieri et al., 2022). In the opera industry, a robust project design strategy can be effectively deployed through the modern staging production of traditional operas. The modern staging of traditional operas is robust to the extent that it blends traditional (and, therefore, familiar) music and dramatic contents with new forms and

336  Handbook on innovation and project management

visual dimensions such as modern scenes, set designs and costumes (Castaner and Campos, 2002; Heilbrun and Grey, 2001).1 Innovative visual elements that take the form of modern staging allow for the creation of new interpretations of traditional operas by shifting their temporal and spatial coordinates into the present or near past, thus unveiling their contemporary relevance. For instance, staging the nineteenth-century operas La Traviata or Rigoletto by Giuseppe Verdi in the present and so making the protagonists feel contemporary, or presenting Mozart’s Così Fan Tutte as a modern-day talk show, are all examples of modern staging. In the course of our fieldwork, several of our informants pointed out that modern staging productions depart from established visual interpretations of traditional operas. Through modern staging, opera houses also update their forms to modern sociocultural trends to find new ways to engage the audience (Gossett, 2008; Heilbrun and Gray, 2001). As four of our key informants pointed out: Opera has a traditional identity and modes of representation. In the collective imaginary opera is Aida, Traviata, Tosca, Madama Butterfly, Rigoletto, Trovatore and so on […] but there is also the possibility of renewing some established ways of representing traditional operas […] The challenge is to communicate a traditional identity in a new way through modern reinterpretations. (Artistic Director # 8) Opera should be a show of extreme vitality, in constant dialogue with the public and our contemporaneity. You cannot try to reproduce what a show was in the past because the audience for that show no longer exists. Therefore, any show that I put on, from my personal experience, is in any case a show aimed at our contemporaneity and certainly not at the past. Because opera lives on shared codes. (Stage Director #1) Opera can survive only through a process of renewal based on stage directions that take the values​​ of our contemporaneity into account. (Artistic Director # 1) We cannot offer only traditional staging […] we want to offer new and vital cultural stimuli to our local cultural community, engage with different audiences in new ways and convince them not to have prejudicial attitudes towards our artistic offer. (Artistic Director # 5)

Preserving traditional music and dramatic content, however, facilitates opera-goers’ understanding and appreciation of visually innovative productions. Those attributes are the most important to establish the membership of an opera production in a traditional category – i.e., pre-20th-century artistic works that reflect opera-goers’ expectations and preferences. Operagoers can indeed more easily interpret the visually innovative aspects of a production as minor changes that aim to refresh rather than radically transform a traditional style. Thanks to the modern staging of traditional operas, opera houses can introduce distinctive product forms and facilitate their acceptance by associating them with the key features of an established genre or category of the past (Bielby and Bielby, 1994; Shamsie et al., 2009). This strategy enables firms to preserve certain established features (be the same) but also introduce novelties (be different), thus trying to be optimally distinctive (Deephouse, 1999). For these reasons and consistently with previous studies emphasizing the benefits of being optimally distinctive (Zhao et al., 2017), a robust design strategy based on innovative visual dimensions and familiar content (i.e. traditional operas’ modern staging) allows opera houses to pursue artistic originality and appeal to opera-goers (Cancellieri et  al., 2022). Yet the

Blending novelty and tradition in creative projects  337

appeal of traditional operas’ modern staging may also depend on other types of productlevel cues that may affect their perceived degree of novelty, as well as the relative balance between novelty and familiarity in this robust design. One such cue that is likely to affect the perception of novelty is the degree of conventionality of the operas that are offered in modern staging. Previous studies have described conventionality as the “selective adoption of highly salient and expected attributes” (Durand and Kremp, 2016, 66; Di Maggio and Stenberg, 1985; Kim and Jensen, 2011; Jensen and Kim, 2013). Conventional cultural products are “performed or offered frequently because they appeal to broad audiences or are particularly good examples of a specific genre” (Kim and Jensen, 2011, 240). According to Durand and Kremp, conventionality reflects “a systematic bias toward common programming choices that are already widely shared and accepted” (2016, 74). Unconventionality, instead, refers to underperformed, forgotten cultural products of the past that have fallen into disuse (Kim and Jensen, 2011; Di Maggio and Stenberg, 1985; Pierce, 2000). In the Italian opera sector, opera houses’ traditional operas have become increasingly crystallized around a canon of classics, whose music and dramas have become well-known and representative of the Italian opera tradition (e.g. Verdi’s La Traviata, Puccini’s La Bohème, Mozart’s Don Giovanni) ( Savage, 1994). Conventional operas are defined precisely as those prominent and salient opera titles associated with well-established music and dramas that are regularly performed (Kim and Jensen, 2011; Di Maggio and Stenberg, 1985). For example, the opera La Bohème by Puccini is more conventional than La Wally by Catalani, just as the opera La Traviata has a higher degree of conventionality relative to the opera La Finta Giardiniera by Mozart. Less conventional operas are performed much less frequently even if they are not necessarily innovative (Castaner and Campos, 2002). Conventional operas are imbued with higher status which, in turn, generates greater expectations from external observers, thus becoming a liability for opera houses contemplating changes in their repertoires (Durand et al., 2007; Slavich and Castellucci, 2016). These observations have two important implications. First, programming conventional repertoires implies directing opera-goers’ attention towards operas subject to social comparison. Because they have been exposed repeatedly to highly conventional operas, opera-goers can more easily compare and contrast traditional and modern staging productions of these operatic projects. Second, conventional operas can hardly be modified without triggering external observers’ scepticism (Dion and Mazzalovo, 2016) because they have acquired the status of iconic cultural products of the past (Martorella, 1977; Gossett, 2008; DiMaggio and Stenberg, 1985) and, therefore, any attempt to innovate them risks falling into the spotlight of public attention. As the artistic director of a famous theatre in central Italy explained, modern staging productions of very famous traditional operas are perceived as major attacks on tradition that are more likely to upset the audience: It is very difficult to make Verdi’s La Traviata different from the one that is in the collective imaginary, so risking on famous titles is a challenge. You risk less when the title is less famous and, consequently, the comparison with other interpretations is also less prominent. (Artistic Director # 4)

According to our informants, when modern staging involves consecrated operas, their strong connection with highly regarded and venerated music and drama raises the risk that such operas might be devalued. One, in particular, was very clear about this point:

338  Handbook on innovation and project management

The great repertoire is a series of totems and, therefore, the perception that you are challenging and destroying a masterpiece is stronger. (Artistic Director #5)

By contrast, modern staging productions of traditional operas with a lower degree of conventionality are perceived as “sleeping beauties”, that is, lesser-known works of the past with the potential to be recast in original ways: It is easier for unknown works to be accepted in modern staging because there are fewer terms of comparison […] the audience has a great willingness, even unconsciously, to accept new interpretations of less conventional titles. (Artistic Director #5) Modern directions of titles that are performed less have fewer points of reference […] a modern staging of an obsolete opera such as Rinaldo is more likely to succeed because the title is unknown. (Artistic Director #2)

Our interviews suggest that opera-goers are more accustomed to non-interventionist, traditionalist staging of highly conventional traditional operas: they not only know their music and lyrics very well but also have some bias towards modern interpretations of the same repertoires. Indeed, they are still drawn to interpretations of traditional operas littered with enduring cliché that are as close as possible to the original operatic works and retain their historical context (Savage, 1994). In contrast, modernist interpretations of less conventional operas involve less bias as their music and lyrics are unknown to most opera-goers. This has been clearly expressed by two stage and artistic directors widely renowned for their experimental interpretations of traditional operas: Less famous titles have a greater chance of success when presented with a modern staging production because no-one really knows them and, therefore, does not have prejudices. (Artistic Director # 9) Think for example of the underperformed baroque operas. In my opinion they can more easily be reinterpreted through modern staging productions […] because they are not part of the “untouchable” repertoire. (Artistic Director # 3)

For an innovation to be successful, the novel and the familiar must combine in ways that neither hide the novelty nor shed the familiar (Cattani et al., 2020; Hargadon and Douglas, 2001). The perception of newness that stems from modernizing iconic operas of the past obscures their familiarity, making traditional operas’ modern staging relatively less appealing to operagoers. By contrast, the modern staging of less conventional operas appeals more to operagoers as they perceive those productions to depart less from a revered tradition. For these reasons, we argue that the degree of conventionality of revived cultural products (operas) moderates the effectiveness of a robust design strategy (traditional operas’ modern staging). We thus hypothesize the following. Hypothesis: The appeal of traditional operas’ modern staging to opera-goers decreases when the conventionality of the operas increases.

Blending novelty and tradition in creative projects  339

EMPIRICAL ANALYSIS Sample and Data We collected data on the opera projects staged by the major Italian non-profit opera houses from the artistic season 1989–1990 to the artistic season 2010–2011.2 Italian opera houses adopt a stagione (season) model, i.e. the production of a number of operas that run independently for a few days every year. We focused on 42 non-profit organizations staging operas classified according to the official classification of the Italian Ministry of Cultural Heritage. The first group of these organizations includes the Lyric-Symphonic Foundations (Fondazioni Lirico-Sinfonica, LSFs). Known for their prestigious opera seasons, LSFs are private foundations located in the largest Italian towns. The second and third types are the Traditional Theatres (Teatri di Tradizione, TTs) and Opera Festivals, whose artistic programmes are smaller in size and realized in a more concentrated timeframe. LSFs, TTs and Festivals are all funded by public bodies at the national and local levels. Because of their prestige and long-term tradition, however, LSFs are more heavily funded by the state compared to TTs and Festivals (Cori, 2004). Over the study period, not all theatres and festivals were active on an ongoing basis. Also, the artistic seasons of some theatres are not comparable with those of other theatres in the sample because of their focus on the promotion of certain composers (e.g. Pergolesi by the Jesi Fondazione, Puccini by the Torre del Lago Festival and Rossini by the Pesaro Festival) or their need to fill out their seating capacity with extremely popular repertoires (e.g. Arena di Verona). Thus, we excluded those theatres from the final analysis, which is based on a sample of 35 organizations for which comprehensive data on their productions were available. Our statistical analysis includes 2,627 useful observations. We collected most of our data manually from the specialist magazine Annuario EDT/ CIDIM of the Italian Lyric Opera, which is widely regarded as the top Italian industry reference for opera. In developing our hypotheses, we also consulted archival materials and conducted interviews with a sample of opera house artistic and stage directors to gain a deeper contextual understanding of the main characteristics of traditional operas’ modern staging and how conventionality influences their appeal. Our interviewees include the artistic and general directors, as well as the invited stage directors of 12 Italian opera houses. Overall, we conducted 13 interviews that lasted between 30 minutes and one hour. Table 18.1 reports some of the most representative quotes. Dependent Variable We measured the dependent variable – attendance – as the natural logarithm of the total number of people present at the opera’s opening and any subsequent re-runs (Cancellieri et al., 2022). In a series of supplementary analyses (see robustness checks to follow), we also expressed the dependent variable in terms of occupancy rate to control for an opera house’s seating capacity. Specifically, we divided the total number of tickets sold by the number of available tickets. Independent Variables Traditional operas’ modern staging (robust project design). Following previous research (Savage, 1994; Gossett, 2008), we codified operatic projects that reinterpret traditional operas

340  Handbook on innovation and project management

Table 18.1  Modern staging of traditional operas and conventionality: representative quotes Modern staging

“Opera has a traditional identity and modes of representation. In the collective imaginary opera is Aida, Traviata, Tosca, Madama Butterfly, Rigoletto, Trovatore and so on […] but there is also the possibility of renewing some established ways of representing traditional operas […] The challenge is to communicate a traditional identity in a new way through modern reinterpretations” (Artistic Director # 8). “Opera should be a show of extreme vitality, in constant dialogue with the public and our contemporaneity. You cannot try to reproduce what a show was in the past because the audience for that show no longer exists. Therefore, any show that I put on, from my personal experience, is in any case a show aimed at our contemporaneity and certainly not at the past. Because opera lives on shared codes” (Stage Director #1). “Opera can survive only through a process of renewal based on stage directions that take the values ​​of our contemporaneity into account” (Artistic Director # 1). “We cannot offer only traditional staging […] we want to offer new and vital cultural stimuli to our local cultural community, engage with different audiences in new ways and convince them not to have prejudicial attitudes towards our artistic offer” (Artistic Director # 5).

Opera conventionality

“It is very difficult to make La Traviata different from the one that is in the collective imaginary, so risking on famous titles is a challenge. You risk less when the title is less famous and, consequently, the comparison with other interpretations is also less prominent” (Artistic Director # 4) “Less famous titles have a greater chance of success when presented with a modern staging production because no one really knows them and, therefore, does not have prejudices” (Artistic Director # 9). “Modern directions of titles that are performed less have fewer points of reference […] a modern staging of an obsolete opera such as Rinaldo is more likely to succeed because the title is unknown” (Artistic Director # 2). “It is easier for unknown works to be accepted in modern staging because there are fewer terms of comparison and also because the great repertoire is a series of totems and, therefore, the perception that you are challenging and destroying a masterpiece is stronger” (Artistic Director # 5). “Think for example of the underperformed baroque operas. In my opinion they can more easily be reinterpreted through modern staging productions […] because they are not part of the ‘untouchable’ repertoire” (Artistic Director # 6).

through innovative staging dimensions and alter taken-for-granted visual attributes as traditional operas’ modern staging (robust design). We use the term traditional operas for all operas characterized by pre-20th-century music styles and dramatic contents. All operas whose composers were born before 1881 were classified as traditional operas as they display a tonal music system and traditional narrative standards.3 By contrast, all operas composed after 1881 were classified as modern operas as they display chromaticism, atonality, disturbing systems of

Blending novelty and tradition in creative projects  341

musical expression and the use of plots that by traditional narrative standards go nowhere (Heilbrun, 2001; Kim and Jensen, 2011; Jensen and Kim, 2013; Lindenberger, 2007; Griffiths, 1994). Examples of traditional operas’ modern staging include performances of Macbeth taking place in an airport terminal, La Bohème at a ski resort and Rigoletto in a timeless and bare modern setting. We created a dummy variable that is equal to 1 if the opera is a traditional opera’s modern staging, and 0 otherwise. We identified traditional operas’ modern staging following a two-step procedure. First, we read the plots of each opera in the original formulation of the temporal and spatial characteristics of the text. We relied on the Opera Book by Kobbé (2007), a very authoritative source that details the plot of more than 500 operas. Next, we analysed and coded the visuals of all operas that the sampled theatres produced over the period 1993–2010 (from the artistic season 1993–1994 to the artistic season 2010–2011) based on the Annuario EDT/CIDIM. Visuals include pictures of each opera production. This visual analysis allowed us to classify operas as “traditional staging” or “modern staging” – with the latter displaying a 20th- or 21st-century or an abstract and timeless setting. We double-checked our coding by visually inspecting online pictures and examining the reviews of each opera published in the Annuario as well as specialized websites. Table 18.2 shows examples of some of the reviews we collected to classify operas as “modern staging”. Opera conventionality. Conventional operas are well-known and popular operas performed frequently because they appeal to a broad audience, while unconventional operas are new or underperformed operas of the past that have fallen into oblivion. We operationalized this variable using DiMaggio and Stenberg’s (1985) measure of theatres’ repertoire conventionality. Conventionality measures the number of times each opera in a theatre’s repertoire was produced by all opera companies in the population in a given period (see also Pierce, 2000; Jensen and Kim, 2011, 2013). Following the same approach, we counted the number of times opera companies stage a particular opera during the four artistic seasons prior to the current one. The first year in our statistical analyses is 1993 (artistic season 1993–1994) and the corresponding conventionality measure refers to the years 1989–1992. The higher (lower) the index, the higher (lower) the opera’s conventionality. Control Variables We included several control variables – at the opera house and opera production levels – to rule out alternative explanations for our results. Opera house status. The status of a theatre acts as a signal of quality that is likely to affect attendance. We determined the (high) status of a theatre by looking at whether it is a Lyric and Symphonic Foundation (LSF): LSFs are indeed known for their prestigious opera seasons. We thus created a dummy variable that is equal to 1 if an opera house is a LSF, and 0 otherwise. Opera music style. Some music styles are more popular than others (Martorella, 1977). We considered the following styles: Baroque (1600–1750); classic (1750–1820); early and midlate Romantic (1820–1920); modern and contemporary (1920–nowadays). Styles are mutually exclusive as operas embrace only one style (Parker, 2001; Heilbrun, 2001; Fisher, 2005). For each style, we then created a binary variable that is equal to 1 if an opera belongs to that style, and 0 otherwise. Popularity of the composer. The operas of some composers are more frequently staged. The variable composer popularity then measures the number of times all opera houses staged

342  Handbook on innovation and project management

Table 18.2  Traditional operas’ modern staging: reviews Title and composer Stage director

Review

Source

Gianni Schicchi by Giacomo Puccini

Lorenzo Mariani 1996–1997

“Mariani relied on television imagery to transform the relatives of the protagonist into the characters of the Addams family. An exhilarating update”.

La Nuova Sardegna; L’Unione Sarda

La Traviata by Giuseppe Verdi

Irina Brook 2005–2006

“Irina Brook changed the usual places of the opera, to transfer the countryside around Paris to an unidentified beach. She selected an old swimming pool inside an industrial archeology pavilion as the most suitable environment for Alfredo’s meeting with Violetta and Flora’s grotesque and disturbing party”.

Opera Click

La Bohème by Giacomo Puccini

Aldo Tarabella 2006–2007

“Aldo Tarabella set La Bohème in a post-war Paris. He deliberately emphasized the spirit of precariousness of the young people who live in a sort of aerial village metaphorically located in the clouds. The director chose to contextualize the work in a different period from the original one”.

Opera Click

La Cenerentola by Gioachino Rossini

Daniele Abbado 2009–2010

“This production of La Cenerentola will be remembered as ‘the kitchen Cinderella’: a small yellow laminate kitchen at the center of the scene, in perfect 60s style, is in fact the element that gives a spatial and temporal connotation to the fairy tale of this modern Angelina, while underlining her servile condition”.

GBOpera

La Traviata by Giuseppe Verdi

Graham Vick 2003–2004

“Graham Vick proposed a radical updating of Verdi’s opera, between the kitsch and the pop art, in a present that could be set in the 60s onwards, but also in the near future”.

Il Giornale della Musica

the operas of a composer during the four artistic seasons before the current one. The higher (lower) the index, the higher (lower) the composer’s popularity. The first in our analyses is 1993 (artistic season 1993–1994), so the variable refers to the years 1989–1992. Coproduction. Since the costs of producing an opera are very high, co-productions represent a cost-saving strategy that allows theatres to reduce their expenses by sharing them with other opera houses. We created a binary variable that is equal to 1 if the opera was coproduced with other theatres, and 0 otherwise. New staging. A new staging is characterized by visual attributes (e.g. set design, costumes and stage directions) that no other opera house has ever presented before. For example, a theatre can stage the famous opera Aida by Giuseppe Verdi ex novo with new set designs, costumes and stage direction; alternatively, the same theatre can buy a production of Aida, whose visual elements have already been presented elsewhere, and integrate them into its offer. Only

Blending novelty and tradition in creative projects  343

the first case is an example of new staging. We controlled for the effect of new staging by creating a binary variable that is equal to 1 if the opera is a new staging, and 0 otherwise. Eclecticism and popularity of the stage director. The stage director is one of the artistic leaders of an opera production. We control for the eclecticism and popularity of the stage director because they can influence ticket sales by determining opera attendees’ perception of the status and popularity of opera productions. Some opera productions are directed by eclectic stage directors who are also active in low-brow cultural fields (e.g. cinema or television). An eclectic identity can challenge the status of a high-brow cultural form like the opera and influence its appeal by determining whether it is perceived as a “pop” reinterpretation of a high-status genre. We considered eclectic those directors who are simultaneously field insiders and active in at least one popular cultural genre. We accounted for the effect of stage directors’ eclecticism by creating a binary variable that is equal to 1 if the stage director is eclectic, and 0 otherwise. The popularity of the stage director was measured as the number of productions each individual artist directed in the past (during the previous three artistic seasons). Reputation of the conductor. We accounted for the reputation of the conductor, the figure responsible for the musical aspects of the production, by looking at whether s/he won the Abbiati Prize in the category “Best Conductor”. Repertoire size. Theatres with larger repertoire sizes tend to have more financial resources to increase the quality of their productions, experiment, promote their artistic seasons and schedule more operas of different styles, which may in itself affect attendance. We measured this variable as the number of opera productions each theatre staged in a given season. Time dummies (artistic season). We included dummies for each artistic season in the model to control for macroeconomic trends and other time-invariant effects. Model We tested our hypotheses by estimating three-level mixed-effect linear regression models, which include both fixed and random effects. Because opera productions are nested within individual operas (La Traviata versus La Wally) and individual operas are nested within opera companies, we considered the opera production as level 1, the individual opera (or title) as level 2, and the opera company as level 3. We obtained our estimates using STATA version 13. We report significance levels based on Huber–White robust standard errors to control for any residual heteroscedasticity across panels.

RESULTS The descriptive statistics and correlations for our measures are presented in Tables 18.3 and 18.4, respectively. To evaluate whether multicollinearity is affecting our estimates, we computed the variance inflation factor (VIF) for each model and found that the highest VIF statistics were below the recommended value of 10 (Hair et al., 1995), suggesting that multicollinearity is not an issue.​ Table 18.5 presents the results of the multilevel mixed-effect linear regression model in which the natural logarithm of the total number of tickets sold is the dependent variable. Although the coefficients are not displayed, all models include year dummies. In Model 1 and Model 2, we included the variables of theoretical interests measuring, respectively, traditional

344  Handbook on innovation and project management

Table 18.3   Descriptive statistics Variable

Mean

Std. dev.

Min

Max

  1. Attendance

5,359.997

4,799.269

44

28,788

  2. Modern staging

0.345

0.475

0

1

  3. Conventionality

8.560

8.599

0

38

  4. Theatre status

0.440

0.496

0

1

  5. New staging

0.411

0.492

0

1

  6. Coproduction

0.371

0.483

0

1

  7. Director eclecticism

0.242

0.428

0

1

  8. Director popularity

5.427

6.477

0

42

  9. Conductor rep

0.093

0.290

0

1

10. Baroque

0.046

0.210

0

1

11. Classic

0.138

0.345

0

1

12. Mid and late Romantic

0.567

0.495

0

1

13. Modern and contemporary

0.025

0.156

0

1

14. Repertoire size

5.770

2.462

1

14

15. Summer opera

0.030

0.172

0

1

operas’ modern staging and opera conventionality separately. To guard against multicollinearity and facilitate the interpretation of the regression coefficients, we used the standardized values of opera conventionality (similar results are obtained by using unstandardized values and are available upon request). In Model 3, we introduced the two-way interaction effect between traditional operas’ modern staging and opera conventionality. Model 4 is a baseline model that includes only the control variables. The model estimates suggest that an opera production is more likely to appeal to opera-goers when the staging theatre has (high) status and when it is directed by eclectic artists. Operas directed by highly popular stage directors are more likely to be positively recognized by opera-goers and increase attendance. An opera production characterized by a Baroque or contemporary music style is less appealing to opera-goers than a production with a Romantic music style, and coproduced operas are also less attractive. Model 5 (our full model) includes the variables of theoretical interests – traditional operas’ modern staging and opera conventionality separately – the interaction effect between them and the control variables. The relationship between traditional operas’ modern staging and attendance (our dependent variable) is positive and significant (β = 0.085; p < 0.001). In line with our theory, opera productions are more likely to appeal to opera-goers when they merge modern visual dimensions with traditional music and dramatic contents (i.e. traditional operas’ modern staging). Similarly, the conventionality of the opera that is being staged has a positive and statistically significant effect on attendance. The interaction effect between traditional operas’ modern staging and opera conventionality is negative and significant (β = –0.040; p < 0.05). The result suggests that the appeal of traditional operas’ modern staging to opera-goers is lower when the conventionality of the opera increases, thereby lending support to our hypothesis. The overall fit of the full model improves substantially relative to the

345

0.534***

–0.135**

13. Modern and contemporary

14. Repertoire size

15. Summer opera

Note:  ** p