TRANSDISCIPLINARY RESEARCH, SUSTAINABILITY, AND SOCIAL TRANSFORMATION This book addresses the gap in the existing literature on the governance of transdisciplinary research partnerships in transformational sustainability research by exploring the governance of knowledge co production in coupled socio ecological system dynamics. Multiple social and ecological crises raise new cross sectoral research questions that call for an evolution in contemporary science in the direction of society wide knowledge co production on sustainability transformations of interdependent social and ecological systems. This book proposes a new approach to this based on enabling capacities for collaboration among scientifc researchers and societal actors with diverse values, perspectives, and research interests. By drawing upon the thriving literature on the conditions for community and multistakeholder driven collective action, the analysis sheds new light on the governance arrangements for organizing so called transdisciplinary research partnerships for sustainability. This book identifes robust conditions that lead to efective collaborative research with societal actors and digs deeper into capacity building for partnership research through fostering social learning on sustainability values among research partners and organizing training and knowledge exchange at institutions of higher education. The book proposes solutions for addressing collective action challenges in transdisciplinary partnerships in an accessible and broadly interdisciplinary manner to a large audience of sustainability scholars and practitioners. It will be of interest to students and researchers in the felds of sustainable development, social ecological transitions, and science policy, while also being a useful resource for engineers, QSE managers, and policymakers. Tom Dedeurwaerdere is Professor of the Theory of Governance and Philosophy of Science at the Université catholique de Louvain (UCLouvain), Louvain la Neuve, Belgium. He has extensively published in scholarly journals on the organization of scientifc research commons and collective action for sustainability transformations. His previous books include Social Innovation in the Service of Social and Ecological Transformation: The Rise of the Enabling State (with Olivier de Schutter, 2022), Governing Digitally Integrated Genetic Resources, Data, and Literature: Global Intellectual Property Strategies for a Redesigned Microbial Research Commons (with Jerome H. Reichman and Paul F. Uhlir, 2016) and Sustainability Science for Strong Sustainability (2014). Routledge Studies in Sustainability Rural Governance in the UK Towards a Sustainable and Equitable Society Edited by Adrienne Attorp, Sean Heron and Ruth McAreavey The Environmental Impact of Cities Death by Democracy and Capitalism Fabricio Chicca, Brenda Vale and Robert Vale Reimagining Labour for a Sustainable Future Alison E. Vogelaar and Poulomi Dasgupta Waste and Discards in the Asia Pacific Region Social and Cultural Perspectives Edited by Viktor Pál and Iris Borowy Digital Innovations for a Circular Plastic Economy in Africa Edited by Muyiwa Oyinlola and Oluwaseun Kolade Critical Sustainability Sciences Intercultural and Emancipatory Perspectives Edited by Stephan Rist, Patrick Bottazzi and Johanna Jacobi Transdisciplinary Research, Sustainability, and Social Transformation Governance and Knowledge Co Production Tom Dedeurwaerdere For more information on this series, please visit: www.routledge.com/Routledge Studies in Sustainability/book series/RSSTY TRANSDISCIPLINARY RESEARCH, SUSTAINABILITY, AND SOCIAL TRANSFORMATION Governance and Knowledge Co-Production Tom Dedeurwaerdere Designed cover image: © Getty Images First published 2024 by Routledge 4 Park Square, Milton Park, Abingdon, Oxon OX14 4RN and by Routledge 605 Third Avenue, New York, NY 10158 Routledge is an imprint of the Taylor & Francis Group, an informa business © 2024 Tom Dedeurwaerdere The right of Tom Dedeurwaerdere to be identifed as author of this work has been asserted in accordance with sections 77 and 78 of the Copyright, Designs and Patents Act 1988. The Open Access version of this book, available at www.taylorfrancis.com, has been made available under a Creative Commons Attribution NonCommercial NoDerivatives (CC BY NC ND) 4.0 International license. Funded by Université Catholique de Louvain. Trademark notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identifcation and explanation without intent to infringe. British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data Names: Dedeurwaerdere, Tom, author. Title: Transdisciplinary research, sustainability, and social transformation : governance and knowledge co production / Tom Dedeurwaerdere. Description: Abingdon, Oxon ; New York, NY : Routledge, 2024. | Includes bibliographical references and index. Identifers: LCCN 2023036189 (print) | LCCN 2023036190 (ebook) | ISBN 9781032624273 (hardback) | ISBN 9781032624242 (paperback) | ISBN 9781032624297 (ebook) Subjects: LCSH: Social change. | Social action. | Community development. | Political participation. Classifcation: LCC HM831 .D43 2023 (print) | LCC HM831 (ebook) | DDC 303.44—dc23/eng/20230901 LC record available at https://lccn.loc.gov/2023036189 LC ebook record available at https://lccn.loc.gov/2023036190 ISBN: 978 1 032 62427 3 (hbk) ISBN: 978 1 032 62424 2 (pbk) ISBN: 978 1 032 62429 7 (ebk) DOI: 10.4324/9781032624297 To Brice, Mathilde and Samuel, for their love and inspiration, may they see the timely advance of pathways to just and sustainable futures CONTENTS List of Figures List of Tables Acknowledgments 1 x xi xii Introduction 1 Transdisciplinary research partnerships for environmental justice and citizenship within planetary boundaries 5 1.1 Organizing research on integrated social and ecological systems 8 1.2 The promises of transdisciplinary sustainability research 10 1.3 Addressing governance challenges in partnerships between scientifc researchers and societal actors 16 2 Overcoming collective action failures in knowledge co production practices 2.1 Governance failures in transdisciplinary research 27 2.2 Theoretical building blocks from the multilevel approach to governing scientifc research commons 33 2.3 Promoting synergies among various styles of transdisciplinary research practice 40 24 viii Contents 3 Generating actionable knowledge outputs through collaborative research co design 49 3.1 Usable knowledge production on sustainability transformations 50 3.2 Collaborative research co-design across technological, socioeconomic, and cultural levers of sustainability transformations 61 3.3 A pragmatist constructivist approach to knowledge co-production 88 4 Social learning among actors with incommensurable value perspectives on sustainability transformations 100 4.1 Building common perspectives for research collaboration in highly diverse societal value settings 102 4.2 Amartya Sen’s deliberative approach to social choice with incommensurable societal values 104 4.3 Illustrating the various types of social learning in transdisciplinary research practices 108 4.4 Fostering critical engagement across diferences 117 5 Developing integrated boundary crossing organizational networks 123 5.1 From disciplinary divisions and departments to fexible network organizations 124 5.2 Embedding knowledge co-production and social learning in the institutional enabling of transdisciplinary research 129 5.3 Implementing integrated boundary-crossing networks for teaching, knowledge exchange, and team formation 131 5.4 New management functions for boundary-crossing network integration 138 6 Implementing knowledge co production on sustainability transformations in academia and beyond 144 Conclusion 153 Contents ix Annex 1: Glossary of key conceptual terms Annex 2: Case study list Annex 3: Coding scales Index 160 167 176 179 FIGURES 1.1 2.1 2.2 3.1 3.2 3.3 3.4 3.5 3.6 4.1 5.1 5.2 Comparison of key features of interdisciplinary and transdisciplinary research Research styles within transdisciplinary research contributing to sustainability transformations Key conditions for governing collective action in each of the three styles of transdisciplinary research practice Research co design among researchers in multi method disciplinary research Research co design among researchers in interdisciplinary research Research co design between researchers and societal actors in transdisciplinary research Core variables of the comparative case study design of transdisciplinary research projects Aggregate results of the coding of the case studies of transdisciplinary sustainability research Examples of types of transdisciplinary research in the case study sample, with varying degrees of strength of co design, co management and social learning Process standards for authentic deliberation in heterogeneous actor networks Ideal types of organizational forms for dealing with diferent types of task environments Co produced transdisciplinary research enabling functions 13 41 43 52 52 54 55 59 61 119 125 130 TABLES 1.1 1.2 Illustration of sustainability research topics addressing situations with diferent degrees of socio ecological interdependency and heterogeneity of societal value perspectives Categories of sustainability problems typically addressed through disciplinary, multi disciplinary, and transdisciplinary research 15 17 ACKNOWLEDGMENTS The project for this book began as a side activity of a starting grant of the European Research Council (ERC) in 2013. With a group of research fel lows, we started to refect on the integration of knowledge from academic research with knowledge from societal actors involved in real world sustain ability transformations. The journal publication from this side activity, with Florin Popa and Mathieu Guillermin, sparked the interest of many societal actors and colleagues at the university and led us into a much deeper investi gation into the broad feld of transdisciplinary sustainability research, which is the topic of this book. Since then, I have had the pleasure of discussing these issues with the large community of scholars and societal actors who have made seminal contribu tions over the last three decades in trying to understand the many challenges to overcome in the building of research partnerships for transformational sustainability research. The debts incurred in writing this book therefore started to accumulate well before the actual writing. A major impetus for the work is the personal experience of facing knowledge co production challenges in large scale fun damental research programs based on partnerships between researchers and societal actors. This personal experience—and the possibility for trial and error learning in this relatively young feld—would not have been possible without being part of the research environment at the Centre for Philosophy of Law, Université catholique de Louvain. I take this opportunity to thank the co directors of the Centre, Jacques Lenoble—now emeritus—and Marc Maesschalck, for their confdence and pathbreaking work in under standing the conditions of critical and transformational partnership based research. Two prominent scholars of the digital knowledge commons, Jerome Acknowledgments xiii Reichman and Paul Uhlir, directly participated in several of these collabora tive research projects. Their insights and their important role in connect ing high profle research on global knowledge commons to the international negotiations around the implementation of the Access and Beneft Sharing provisions of the Convention on Biological Diversity was enormously helpful in the present endeavor. I also had the incredible chance to co direct many of the research projects on social innovation for social and ecological transition with my colleague at the Centre for Philosophy of Law, Olivier De Schutter. I would like to thank him for this long standing collaboration and the fruitful exchanges that contributed to many of the ideas on knowledge co produc tion with societal actors developed in this book. Further, being hosted, in 2018 and 2019, by many colleagues during my “video interviews” trip on transdisciplinary research throughout Europe was a life changing experience, which provided many of the examples dis cussed and analyzed in the book (videos available at www.lptransition.be/td). A warm thanks for the many stimulating discussions, during these project visits, on innovative approaches to implementing transdisciplinarity part nership research in practice: Michael Staufacher and Chistian Pohl at the ETH Zürich, Switzerland; Adrian Ely at the University of Sussex, United Kingdom; Ariane König at the University of Luxembourg, Luxembourg; Derk Loorbach at the University of Rotterdam, the Netherlands; Anna Kramers at the KTH, Sweden; Uwe Schneidewind at the Wuppertal Institute for Climate, Environment and Energy, Germany; Simon De Muynck at the Centre d’écologie urbaine, Belgium; Sandra Lavorel at the University of Grenoble, France; Mathieu Berger at the UCLouvain, Belgium; Pierre Stassart at the Université de Liège, Belgium; Fabienne Barataud at INRAE Mirecourt, France; and all the other colleagues I met during these research visits. The various versions of the manuscript benefted greatly from many dis cussions and comments, which made for an improved manuscript. In particu lar, I gratefully acknowledge the feedback on earlier drafts and the assistance with cross checking the case studies on transdisciplinary research described in the book by many fellow researchers: Agathe Osinski, Selim Louaf, Michael Madison, Laurent Hazard, Gill Ainsworth, Brendan Coolsaet, Bianca Vienni Baptista, Stéphane Ginestet, Merritt Polk, Flurina Schneider, Audrey Podann, Suzanne Smit Luyt, and Joseph Maxwell. My gratitude is also due to Caroline Van Schendel for her help with editing the manuscript. I certainly forgot some of the colleagues and fellow travelers on the jour ney who contributed to the book; let me thank them here. Finally, many gaps and mistakes might remain, in spite of all this support, and I take full respon sibility for these. And, of course, I want to thank my family, Brice, Mathilde, Samuel, and Anne Sophie, who made it all so much more meaningful and enjoyable. INTRODUCTION The current crisis of the resource intensive development model has had a major impact on how human societies envision sustainable and global futures. In particular, the convergence of multiple social and ecological cri ses in the frst decades of the new millennium raises new challenges that necessitate an evolution in our modes of living, a deepening of democratic decision making processes, and society wide knowledge mobilization to fos ter long term social and ecological sustainability. In this context, citizens, entrepreneurs, and public officials place great hope in collaborative research and innovation to improve our comprehension of scientifcally credible and socially desirable sustainability transformations. Much transformative research has addressed specifc sustainability issues and proposed solutions for specifc actors. However, many of the problems we face today defy settlement because they are characterized by very hetero geneous and boundless problem features (Polk, 2014). For this reason, they are often referred to as “wicked” (Rittel and Webber, 1973). They involve multiple and often strongly contested societal values, are causally complex, and engage actors from multiple sectors and societal spheres of activity (Harris et al., 2010; Polk, 2015). These diferent features of wicked problems suggest that the traditional division of labor between scientifc and societal actors’ expertise in societal responses to the crisis is insufficient to address complex sustainability prob lems (Haasnoot et al., 2013). In particular, wicked problem situations have led to a set of research questions on sustainability challenges that cannot be addressed through conventional multidisciplinary and academic expert led only approaches. DOI: 10.4324/9781032624297 1 This chapter has been made available under a CC BY NC ND 4.0 international license. 2 Introduction A study directed by the Organization for Economic Cooperation and Development (OECD) on “Addressing Societal Challenges” (OECD, 2020) stated that engaging societal actors across the boundaries of science and practice will be crucial to addressing urgent social and ecological challenges. As highlighted in the report, the impacts of global warming, biodiversity loss, natural disasters, economic migration, and health pandemics are manifested at multiple scales and require both technological and social innovations” (ibid, p. 9). To achieve such innovations, “diferent scientifc disciplines, including natural and social sciences and humanities need to work together and fully engage other public and private sector actors, including policy makers” (ibid). In response to these new societal demands for collaborative research and social innovation, scientifc researchers and societal actors have initiated diferent forms of knowledge co production and partnerships for interdisci plinary socio ecological research in all felds of sustainability, in both basic and applied research. However, less efort has been made to understand the institutional conditions for moving beyond the myriad of these incipient and piecemeal eforts toward a more systematic reform of social practices and institutional rules within the modern science fabric. Nevertheless, to address the scale and urgency of contemporary socio ecological challenges, research ers, societal actors, and science officials underline the need for such system atic reform. Therefore, the discussion in this book proposes taking a fresh look at the collective action challenges involved in building large scale boundary crossing interdisciplinary research collaborations among researchers and societal actors—including citizens, members of associations, teachers, entrepreneurs, public officials, and policymakers. These collaborative research practices are described in scholarly literature under the umbrella of “transdisciplinary research.” Indeed, transdisciplinary research has been promoted as a novel approach to produce societally relevant, value laden, and scientifcally robust knowledge on sustainability transformations that transcends established boundaries among scientifc disciplines and between science and society. The objective of the investigation of transdisciplinary research in this book is to identify the appropriate mix of governance mechanisms for organiz ing knowledge co production processes that contribute to the generation of actionable knowledge outputs in real world sustainability transformations. Two core lessons emerged from our inquiry into the governance challenges. First, to generate actionable knowledge outputs, researchers and societal actors must look beyond knowledge integration and actively co design research questions, frameworks, and approaches. Second, to build capaci ties for research co design in transdisciplinary research, funders and research managers must build a fexible, polycentric institutional organizational environment for boundary crossing knowledge exchange, the acquisition of Introduction 3 competencies for knowledge co production beyond academia, and transdis ciplinary team formation. By addressing the issue of governance of knowledge co production in transformational sustainability research through the lens of the theory of col lective action, our analysis intends to add value to the existing literature both theoretically and practically. First, at the level of tools for theoretical analy sis, this book presents an innovative framework for successfully navigating collective action challenges in boundary crossing collaborations, based on insights from the literature on the governance of knowledge commons. This framework is introduced by discussing various types of collective action fail ures encountered in building partnerships between scientifc researchers and societal actors involved in value laden and multifaceted sustainability trans formations. To highlight the signifcance of institutional rules for knowledge co production in overcoming these collective action failures, the framework is applied to various institutional rules for organizing research co design, social learning on sustainability values, and the institutional enabling of boundary crossing collaboration. Second, to examine the practical implementation challenges of these collec tive action arrangements, this study adopts a bottom up empirical approach. Through a comparative assessment of the process design of transdisciplinary research in a sample of 44 projects, we analyze the conditions for the success ful co production of usable knowledge on value laden socio ecological trans formations. This sample is constructed through a “most diferent” case study selection, with the view to encompassing a broad diversity of research tradi tions ranging from technological and biophysical research to socioeconomic and sociocultural research approaches. This comparative assessment aims to identify robust combinations of conditions that lead to efective collaborative research with societal actors. Subsequently, the analysis delves deeper into capacity building for partnership research through fostering social learning about sustainability values among research partners and organizing transdis ciplinary training and knowledge exchanges at higher education institutions. To present the fndings of the analysis, various governance mechanisms are illustrated with a wealth of in depth case studies from various thematic areas of sustainability transformations. The overall aim is to present col lective action challenges in transdisciplinary research in an accessible and broadly interdisciplinary manner to a large audience of sustainability schol ars and practitioners. Indeed, writing this book would not have been possible without the intensive experimentation and collective learning on transdis ciplinary research by a growing community of societal actors and scholars from all scientifc disciplines and professional backgrounds over the last three decades. The upscaling of transdisciplinary research on society wide sustainability transformations is therefore likely to beneft from the mutual learning that occurs between researchers and societal actors across all these 4 Introduction disciplinary backgrounds and across diferent types of science and society interfaces. This book also aims to invite its readers to embark on that mutual learning journey with transdisciplinary scholars and practitioners. References Haasnoot, M., Kwakkel, J. H., Walker, W. E. and ter Maat, J. (2013). Dynamic adap tive policy pathways: A method for crafting robust decisions for a deeply uncertain world. Global Environmental Change, 23(2), 485–498. Harris, J., Brown, V. A. and Russell, J. (Eds.). (2010). Tackling wicked problems: Through the transdisciplinary imagination. Thames: Taylor and Francis. OECD. (2020). Addressing societal challenges using transdisciplinary research. OECD Science, Technology and Industry Policy Papers 88, OECD Publishing, Paris. Polk, M. (2014). Achieving the promise of transdisciplinarity: A critical exploration of the relationship between transdisciplinary research and societal problem solv ing. Sustainability Science, 9, 439–451. Polk, M. (2015). Transdisciplinary co production: Designing and testing a transdis ciplinary research framework for societal problem solving. Futures, 65, 110–122. Rittel, H. W. and Webber, M. M. (1973). Dilemmas in a general theory of planning. Policy Sciences, 4(2), 155–169. 1 TRANSDISCIPLINARY RESEARCH PARTNERSHIPS FOR ENVIRONMENTAL JUSTICE AND CITIZENSHIP WITHIN PLANETARY BOUNDARIES The increase in human knowledge and advances in technological innova tion, along with the expansion of globally integrated economic activities, have allowed advanced industrial societies to evolve into mass consumption societies during the second half of the 20th century (Matsuyama, 2002). This transformation, especially strong during the so called golden 1960s, yielded considerable growth in material well being and was accompanied by improved social welfare provisions in many countries worldwide. In the fol lowing decades, emerging and developing economies adopted many features of this development model (Stearns, 2006). This model is now in crisis. As extensively documented by researchers and international organizations, the current path of resource intensive growth is rapidly exhausting non renewable resources and already disrupting global life supporting processes on the planet, such as the global carbon cycle or the ecosystems serving as habitats for many endangered species (Rockström et al., 2009). Further, the current development model raises important global and local social equity issues as the average per capita resource use of the people living in the advanced economies cannot be generalized to the entire world population without further aggravating the ecological crisis (Chancel and Piketty, 2015). Moreover, multi scale and multi sectoral sustainability problems raise new governance challenges that call for new forms of multi stakeholder collective action at local, regional, and global scales (Jordan et al., 2015; Dorsch and Flachsland, 2017). Some interdependencies in socio-ecological systems*1 are not new fea tures of human societies. Historical agro pastoral land use practices directly impacted many of the ecosystems we know today. Further, natural resources have been exploited on a large scale by all major empires (Costanza et al., DOI: 10.4324/9781032624297 2 This chapter has been made available under a CC BY NC ND 4.0 international license. 6 Transdisciplinary research partnerships 2007). However, the current planetary challenges seem to dwarf these histori cal examples of socio ecological interdependencies by the scale of the impacts, the speed of the process, the scope of the potential risks, and the diversity of stakeholders involved and impacted from various sectors of human activity (Aarts and Drenthen, 2020). Moreover, the current interaction path between the natural dynamics of planetary ecosystems and the dynamics of social systems has produced irreversible exhaustion of natural resources and living organisms and a lock in of socio ecological systems in development paths that further promote the overexploitation of the stock of exhaustible nature resources (Norgaard, 1984). Although necessary in the short term, piecemeal adaptations to address the undesirable consequences of the development model are likely to be insuf fcient to address the large scale and society wide interdependencies between social and ecological systems. As shown in many models of resource use, if human beings wish to live within safe planetary boundaries now and for future generations, human societies must transform society wide systems of production and consumption, including the felds of energy, housing, mobil ity, and agrifood production, among others (Falk et al., 2020). In response to this challenge of society wide sustainability transforma tions, researchers, social movements, social entrepreneurs, and policymakers have developed a broad array of new approaches to human progress and well being around an alternative narrative of living within planetary bound aries, ecological justice, and environmental citizenship (Petit et al., 2022). These three societal value frameworks aim to address social and ecological sustainability* challenges in a just and socially legitimate manner. First, the mobilization around planetary boundaries acknowledges the need for urgent action to maintain the functioning of basic life supporting systems and processes on Earth (Gunderson and Holling, 2002; Folke et al., 2002; Rockström et al., 2009; du Plessis, 2012). This call for action is moti vated by the awareness of potential risks generated by major system insta bilities and the wish to preserve the diversity of human and non human life forms and social practices that co evolved with and depended on the plan etary processes (Larrère, 1997, pp. 83–84). Second, the overall objective of environmental justice regards the need to address the specifc social justice issues that arise in interdependent socio ecological systems (Larrère and Larrère, 2014, p. 320). Indeed, the growth in intensity and scale of socio ecological interactions has important conse quences for social justice and equity. The emergence of new ecological and technological risks induces distributional issues between those who endure the consequences of these risks and those who are not impacted or who can pay for adaptation measures. Such distributional issues also involve the ques tion of who benefts from the new opportunities created by sustainability transformations. In short, societies face an array of choices to make between Transdisciplinary research partnerships 7 various sustainability transformation pathways to overcome the current cri ses, with diferent costs and benefts for diferent social groups (UN, 2019). More generally, environmental justice scholars highlight three important justice related concerns for sustainability transformations (Fraser, 2009; Schlosberg, 2013; Schlosberg et al., 2019; Coolsaet, 2016, 2020). They are often labeled in shorthand as the three concerns of “distribution, process, and recognition.” They relate to individual distributive concerns based on the cri teria of socioeconomic justice (distribution), concerns over the fairness of the process of collective decision making (process), and recognition of the contri bution of all concerned sociocultural groups to the process of change (recogni tion). Further, environmental justice scholars also highlight power issues as an important cross cutting category (Schlosberg, 2013). As will be seen in the case studies on sustainability research, addressing power asymmetries in knowledge co production processes is crucial to promoting just sustainability solutions and the efective involvement of disenfranchised social groups in knowledge production on desirable and feasible sustainability transformations. Third, promoting environmental citizenship addresses innovations toward forms of collaborative governance and collective decision making that are needed to advance the objectives of sustainable development within Earth’s planetary boundaries and in accordance with environmental justice (Dobson, 2007). Indeed, the current crisis involves a broad area of collective goods, such as human life supporting climate, air quality, biodiversity, or sustain able management of plant and crop diseases, that require collective action beyond the conventional nation state, involving societal actors at various scales and from highly diverse sectors of activity. This third core value framework partially overlaps with the second, as it underlines the importance of building capacities for meaningful participation of all parties beyond merely formal process guarantees for inclusive govern ance of all parties in societal transformations (Arnstein, 1969). However, the framework of environmental citizenship emphasizes the role of participation beyond situations of environmental injustice and stresses the importance of new forms of participation by citizens and stakeholders in all forms of public and private collective action that are required to address the current sustaina bility crises in an efective manner (De Schutter and Dedeurwaerdere, 2022). As this short overview shows, the current crisis of the resource intensive growth model has major impacts on the relationship between the evolution of human societies and the various ecological and natural resource systems on Earth. The unprecedented scope of social and ecological interdependen cies, if left on an unsustainable trajectory, can have disastrous consequences for the future survival of humankind on Earth. In response, societal actors and policymakers actively elaborate new value frameworks to envision a sus tainable and socially just future within planetary boundaries, which, how ever, remain under intense social debate. 8 Transdisciplinary research partnerships In this context, there is an urgent need to provide scientifcally credible and socially legitimate perspectives on the feasible and desirable sustain ability transformations required to address the crisis (UN, 2019). As will be argued in this introductory chapter, conventional specialized disciplinary science and expert led advice are largely insufficient in providing the body of usable knowledge—applied and basic—needed to accelerate the incipient societal transformations toward a sustainable evolution of natural and social systems. Indeed, the achievement of sustainable human development objec tives in interdependent social and ecological systems requires new modes of knowledge generation. These new modes must cross the boundaries of vari ous disciplines to produce an improved understanding of the complex social and ecological interdependencies. Moreover, they must involve the concerned societal actors and researchers in mutual learning on the overall sustainabil ity values that can guide human action in various specifc societal transfor mation pathways. 1.1 Organizing research on integrated social and ecological systems Over the last three decades, science policy officials and sustainability researchers have developed major new modalities for organizing scientifc research (Kates, 2011). These new modes of knowledge mobilization aim to overcome the failures of conventional disciplinary research for addressing cross sectoral and value laden sustainability issues. Two major features char acterize this emerging landscape of scientifc research in support of sustain ability research: (1) an integrated* interdisciplinary approach encompassing social and ecological system dimensions and (2) a partnership approach based on knowledge co-production* and social learning* among scientifc researchers and societal actors. The end goal of this combination of inter disciplinary and partnership approaches is the production of knowledge on specifc sustainability transformations that is scientifcally credible, socially legitimate, and socially relevant. First, as per many scholars, the mere aggregation of specialized disciplinary expertise is insufficient to provide usable knowledge on sustainability trans formations (Fernandes and Philippi, 2017). However, such interdisciplinary approaches do not constitute a new kind of “interdisciplinary discipline.” Rather, integrated interdisciplinary approaches to interdependent social and ecological systems require combining perspectives that mobilize radi cally heterogeneous epistemological, conceptual, and empirical perspectives (Norgaard, 1989; Goddard et al., 2019). Therefore, for each specifc transfor mation pathway, researchers must actively collaborate to integrate heteroge neous perspectives into common research frameworks (Ostrom, 2007). Transdisciplinary research partnerships 9 Second, the analysis of the integrated socio ecological systems cannot be separated from the value related discussions on the core sustainability values regarding environmental sustainability, justice, and citizenship (Brandt et al., 2013; Dedeurwaerdere, 2014). Indeed, in interdependent social and ecologi cal system dynamics, the analysis of the biophysical, socioeconomic, and sociocultural levers of societal transformations cannot be conducted inde pendently of a discussion on value related considerations, which co defne the basic orientations of the sustainability transformations of these systems. One set of examples that will be further illustrated in this book relates to the research on the thresholds for sustainable resource use. Defning such thresholds involves biophysical analysis, socioeconomic considerations, and value related positions in environmental or social ethics. For instance, how much territory do we reserve for pristine nature, which plays an important role in rare species protection? How much territory do we dedicate to carbon capture in forests or wetlands relative to other possible land use purposes? Further, how do we consider the diverse societal actors’ perspectives on social justice when analyzing various sustainable practices of natural resource use with diferent distributional impacts? In practice, the discussions on the overall orientation of sustainability transformations involve a set of heterogeneous societal values or societal val ues that remain under intense debate. Therefore, reliable scientifc knowledge production on the transformation pathways depends on involving societal actors in clarifying the various values at stake in framing a specifc feld of sustainability transformations. The transgression of the conventional boundaries of academic disciplinary and interdisciplinary science—by integrating knowledge from societal actors in the research process—has three important purposes in the context of sustain ability research (see Pohl et al., 2021). First, this collaboration with societal actors aims to construct a more integrative and complete approach to sustain ability transformations by integrating empirical and analytic knowledge from scientifc research with experiential knowledge on specifc feasible and desirable pathways from societal actors. Second, the partnership with societal actors has a transformational purpose by producing usable knowledge directly related to the social possibilities of change in specifc interdependent social and ecological systems. Third, the partnership also has a critical dimension. Indeed, whenever societal or scientifc debates over sustainability value are fraught with distorted communication processes, given rent seeking or power imbalances, a critical approach is needed to deconstruct dominant structures of knowledge that per petuate unsustainable development paths. This critical aspect of the knowledge integration from societal actors calls for appropriate governance mechanisms for the collaborative practice within the research partnerships, which is at the heart of the analysis of sustainability research in this book. 10 Transdisciplinary research partnerships As will be illustrated through the various case studies, to improve our understanding of feasible and desirable possibilities of change, societal actors and scientists embarked on innovative boundary crossing research endeav ors that combined interdisciplinary knowledge integration and collaborative research partnerships. Over the last three decades at least, these approaches have been designated more generally under the umbrella of transdisciplinary sustainability research* (Hirsch Hadorn et al., 2008). The latter designates basic and applied sustainability research practices based on knowledge co production among researchers from various scientifc disciplines (for the interdisciplinary analysis of interdependent socio ecological systems) and knowledge co production among scientifc researchers and societal actors (the partnership research aspect). In this context, some transdisciplinary research approaches may give the impression that the mobilization of societal actors for improved contextual information gathering is sufficient to induce the efective production of usable knowledge on sustainability transformations. However, as discussed at length in this book, such a focus on knowledge integration, although an impor tant aspect, is insufficient to successfully organize transdisciplinary research. The organization of knowledge co production in transdisciplinary research requires dedicated governance mechanisms to overcome a set of hurdles that can hamper collaboration among research partners. Major potential hurdles to be discussed include the lack of involvement in co constructing common frameworks and the failures in mutual learning on socially legitimate and relevant sustainability values. To introduce these issues, this chapter further presents the sustainability problems that motivate transdisciplinary sustain ability research, introduces the key components of the transdisciplinary research process, and gives a short overview of the various book chapters. 1.2 The promises of transdisciplinary sustainability research Throughout human history, science has played a key role in fostering pro gress in human well being. One paradigmatic case is the contribution of the oretical knowledge in mathematics, physics, and biology to improvements in many areas of human activity, to cite just one well known feld of research with large scale impacts. For instance, ancient knowledge of mathematics and physics played a key role in developing public infrastructure to channel drinking water into cities and organize complex irrigation systems in ancient civilizations from China and India to the Middle East and Europe (Swetz, 1979; Koutsoyiannis and Angelakis, 2003). In the 19th century, the control of many infectious diseases became possible with the pioneering work of Robert Koch and Louis Pasteur on the microbial theory of disease (Satcher, 1995). In the 1970s, the Consultative Group on International Agricultural Research set up a scientifc crop breeding program in collaboration with Transdisciplinary research partnerships 11 research centers throughout the world, which majorly contributed to reduc ing global hunger through the huge increase in crop yields of cereals such as rice, wheat, and maize (Byerlee and Dubin, 2009). Scholars document similar broad impacts of science on progress in human well being throughout history, ranging from the biophysical sciences to the social sciences and humanities (Mokyr, 2011). In the process, the feld of sci ence evolved from operating within small networks of well connected indi viduals to large scale collective endeavors (Ravetz, 2006). Especially after the Second World War, public sector science underwent a rapid transformation, evolving toward so called big science, organized around large scale research consortia that address various societal missions through publicly funded research (Nelson, 1993; Stokes, 1997; Mazzucato, 2018). The reform of the science fabric by setting up large scale expert driven research consortia by national and international governments, however, falls short of addressing the knowledge needs for cross sectoral and multistake holder sustainability issues. Indeed, except for specifc research niches, post war innovations in multi disciplinary and interdisciplinary research consortia remain characterized by functional autonomy from society, are led by inde pendent scientists, and are largely self governing in their scientifc priorities, their procedures for information gathering, and the quality assurance of the produced knowledge (Kitcher, 2011). Even though science policy increas ingly requires democratic accountability and proof of the societal relevance of functionally autonomous, so called ivory tower science, overall, the strict division of labor between scientifc expertise and societal actors’ knowledge remains strong. In particular, the design of the scientifc methods, the fram ing of the research approaches, and the organization of research processes remain outside of the remit of collaboration with societal actors (ibid). Among the noted large scale science eforts is the Intergovernmental Panel on Climate Change (IPCC). This Panel organizes the writing of a report in intervals of approximately six years with a community of over 700 scien tists (for the 2021–2023 sixth assessment report) to deliver state of the art knowledge on climate change to policymakers. Despite being an authori tative and essential resource for decision making on climate change, IPCC reports remain largely insufficient to guide specifc societal transformations to address climate change. The latter is mainly because of the strong focus on the biophysical basis and impacts of climate change in the report (Bjurström and Polk, 2011). Indeed, rather than investigating in depth the various inter dependencies between biophysical, socioeconomic, and sociocultural drives for reaching efective climate change adaptation and mitigation, the main purpose of the report is to map the biophysical trends and discuss the policy targets for mitigation and adaptation action. Nevertheless, without inte grated knowledge on specifc feasible, socially relevant, and legitimate sus tainability transformation pathways, such multi disciplinary expert reports 12 Transdisciplinary research partnerships are unlikely to provide the necessary guidance to address the current social and ecological crises. As noted, the emergence of new cross sectoral research questions on sus tainability transformations of interdependent social and ecological systems calls for the next stage in the contemporary science evolution in the direc tion of transdisciplinary knowledge co production. Relative to functionally autonomous “ivory tower” science, transdisciplinary research involves soci etal actors in research partnerships with scientifc researchers in a much more encompassing way. Scholars have provided a more specifc defnition of the key components of transdisciplinary research projects. While multi disciplinarity has been described as the mere juxtaposition of disciplinary perspectives, transdisci plinarity goes a step further (Hirsch Hadorn et al., 2008), in particular by 1 integrating information from diferent disciplines and types of knowledge (from scientifc researchers and societal actors) to address a common spe cifc problem and research question through a jointly constructed frame work and 2 organizing a partnership between researchers and societal actors for co managing the knowledge integration process and organizing social learn ing on the diversity of societal values In short, transdisciplinary research is based on interdisciplinary knowledge integration and organizing knowledge co production partnerships between researchers and societal actors, as illustrated in Figure 1.1. Over the last decades, to navigate this emerging landscape of multi disci plinary, interdisciplinary, and transdisciplinary research approaches, national and international research agencies have organized various international meetings with science and stakeholder communities. First, as per a state of the art report based on a workshop organized by the United States National Academies of Sciences, interdisciplinarity is a research, education, and prob lem solving mode that integrates methods, tools, concepts, and theories from one or more disciplines to address common problems (National Academy of Sciences, 2005, p. 306). According to the report, the concept of interdisci plinary research emerged in the early 20th century in response to the need to address complex problems or develop comprehensive general views of a problem area. As underlined by Klein (2010), the scope varies from narrow interdisciplinarity, involving disciplines with compatible methods and epis temologies (e.g., physics and molecular biology), to broad interdisciplinarity that bridges disparate approaches (e.g., combining sociocultural history of land use practices and biophysical analysis of ecosystem functions). This form of broad interdisciplinarity is most relevant (Pohl et al., 2021) to understanding society wide sustainability transformations. Indeed, Transdisciplinary research partnerships 13 Interdisciplinarity • Crosses disciplinary boundaries • Common goal setting • Integration of disciplines • Development of integrated knowledge and theory Disciplinary research participants Goal of research project Transdisicplinarity • Crosses disciplinary and academic/non-academic boundaries • Common goal setting • Integration of disciplines and non-academic participants • Development of integrated knowledge and theory among science and society Disciplinary research participants Non-academic research participants Goal of research project FIGURE 1.1 Comparison of key features of interdisciplinary and transdisciplinary research Figure by the author, based on an adaptation of the ideas developed in Tress et al. (2005). sustainability transformations require bridging disparate sources of knowl edge on social and ecological system dynamics to cross boundaries between various sectoral and often disconnected decision making processes in public and private organizations, which often address distinct aspects of social and biophysical systems. This requirement to develop broad interdisciplinarity research practices is strongly underlined in the frst generation of transdisci plinary research in the 1970s by scholars such as Jean Piaget, Leo Apostel, and Erich Jantsch, who focused on the elaboration of overarching syntheses in specifc domains of reality (Hirsch Hadorn et al., 2008; Klein, 2010). The second generation of transdisciplinary research moved the analysis of socio ecological systems beyond the walls of conventional academic and expert led interdisciplinary science by involving societal actors and citizens in knowledge mobilization and social learning on society wide sustainabil ity transformations (Hirsch Hadorn et al., 2008). A major historical land mark event showcasing, for the frst time, the broad international uptake of this move toward partnership based research approaches to sustainability issues was the International Transdisciplinary Conference in 2000, organ ized in Zürich by the Priority Program Environment of the Swiss Academy of Sciences. This conference gathered over 700 participants from 57 nations to discuss their success and challenges in conducting transdisciplinary research. Although this research feld is broad and shaped by various lines of thinking 14 Transdisciplinary research partnerships and heterogeneous approaches to research, participants widely shared the concern for transcending disciplinary paradigms and various types of knowl edge to address real world sustainability problems (ibid, p. 29). In general, this second generation of transdisciplinary research practices additionally focused on building partnerships with societal actors to consider the diversity of legitimate value perspectives on sustainability transforma tions in the design of the research process. Indeed, the goal of reaching a socially robust understanding of sustainability transformations requires that sustainability researchers move from a general interdisciplinary analysis of all theoretically possible socio ecological dynamics to an analysis of specifc socio ecological transformation pathways that are socially desirable and sci entifcally valid. The latter implies the identifcation of the problems that are considered most relevant by concerned societal actors and the matching of the research framework to real world social possibilities of change. Hence, research partners must co construct the research design in a way all partners consider relevant and socially legitimate. Accordingly, per the study directed by the Organisation for Economic Cooperation and Development (OECD) on “Addressing Societal Challenges” (OECD, 2020)—referred to in the introduction—transdisciplinarity is defned as “the integration of academic researchers from unrelated disci plines and non academic participants in creating new knowledge and the ory to achieve a common goal, involving the creation of new knowledge and theory.” According to the study, drawing upon the breadth of scientifc and non scientifc knowledge domains, such as local and traditional knowl edge, practitioners’ know how, and cultural norms and values, knowledge co production aims to supplement and transform scientifc insights. Thus, it ofers a way to address issues involving diverse societal values being debated. Further, expanding on existing scientifc evidence and organizing social learn ing processes can generate more innovative solutions and holistic understand ing (ibid, p. 9). Given the importance of the disciplinary organization of research in many research institutions and universities, science policy officials and research evaluators may face considerable challenges in situating transdisciplinary research in the current institutional landscape. In this context, it is impor tant to highlight some possible misunderstandings. First, some scholars might tend to equate transdisciplinary research with more applied research. Nevertheless, the diference between transdisciplinary research and discipli nary research is not situated in the production of more direct, applicable research results relative to more theoretical and basic approaches to reality. On the contrary, transdisciplinary and disciplinary research share basic and applied research strands (Mittelstrass, 2018, p. 72). Regarding transdiscipli nary research for sustainability, practices may range from applied knowl edge co production within an action research setting to more basic strands of Transdisciplinary research partnerships 15 strategic research, foresight studies, or general theoretical syntheses of com plex socio ecological interdependencies that cannot be apprehended through disciplinary or multi disciplinary approaches. Furthermore, not all situations justify investment in transdisciplinary research. The choice of multi disciplinary, interdisciplinary, or transdis ciplinary research hinges on the type and representation of the research problem the research partners aim to address (Hirsch Hadorn et al., 2006, pp. 123–124). The latter can be illustrated schematically through the case of sustainability problems regarding water management in a river basin, as in Table 1.1. Water management might concern local and isolated problem features or more encompassing, interdependent socio ecological problem features. For instance, the inhabitants and users of a river basin may focus on a set of well defned problems, such as building a bridge over the river or solving a pollution problem caused by a local actor. Alternatively, they may be concerned with water management problems in so called river basin con tracts for addressing various interrelated social demands around biodiversity protection, recreation, and industrial use of water (Huitema and Meijerink, 2014). Such diferent problem situations have implications for organizing multi disciplinary, interdisciplinary, or transdisciplinary research. Indeed, it may be that the involved partners prioritize solving some technical problems related to a well identifed local problem. In such a case, they likely opt for conducting disciplinary or multi disciplinary research. Conversely, the focus may be on the problems generated by the dynamics of interdependencies and value laden controversies in the river basin contract, which are more adequately addressed through modes of transdisciplinary research. TABLE 1.1 Illustration of sustainability research topics addressing situations with dif ferent degrees of socio ecological interdependency and heterogeneity of societal value perspectives Research questions related Rather homogeneous to river basin management societal value perspective Heterogeneous societal value perspectives Various rather independent Research question on social and ecological the architecture of a dynamics pedestrian bridge to cross the river Strongly interdependent Research on the social and ecological adaptation of legal dynamics frameworks to new threats to valuable biodiversity in the river basin Solving a contentious local river pollution issue afecting diverse actors Research on balancing objectives of recreational use, industry development, and biodiversity in the river basin 16 Transdisciplinary research partnerships In this context, Spangenberg (2011) suggests the distinction between sci ence for incremental sustainability change (technical and disciplinary) and science of system wide sustainability transformations (interdisciplinary and transdisciplinary). Regarding “science for incremental sustainability change,” scientifc research aims to bridge technical knowledge gaps that must be addressed to solve problems within a given sustainability transfor mation pathway. For such purposes, disciplinary knowledge and methods are well adapted to provide in depth knowledge of a system component from a highly specialized perspective on sub system features. In contrast, regard ing the “science of system wide sustainability transformations,” the research process is designed to understand the overall dynamics of interaction between the social and ecological system features in given sustainability transforma tions. The latter is the specifc object of analysis of transdisciplinary sus tainability science, as illustrated in the lower right box of Table 1.2. Both interdisciplinary analyses of coupled socio ecological systems and partner ships for knowledge co production between societal actors and researchers are involved in this undertaking. In general, transdisciplinary sustainability research aims to produce bet ter knowledge and a better general understanding of sustainability problems characterized by strong system interdependencies and diverse societal values that play a role at multiple scales of socio ecological interactions. As is the case with all scientifc research, such knowledge will be provisional and sub ject to further refnement. Nevertheless, as the many case studies in this book show, integrating processes of transdisciplinary knowledge co production in sustainability research is a key requirement to advance the undertaking of scientifcally credible and socially robust knowledge production on multi scale and multistakeholder sustainability challenges. 1.3 Addressing governance challenges in partnerships between scientific researchers and societal actors Scholarly discussions on transdisciplinary research have produced a wealth of research on approaches to knowledge integration among researchers from various disciplines and societal actors (Hirsch Hadorn et al., 2008; Bergmann et al., 2012). Subsequently, with the proliferation of researcher and social actor partnerships in transdisciplinary sustainability research, scholars furnished insights into various aspects of knowledge co production and social learning. However, except for some notable exceptions (e.g., Pohl et al., 2021), few systematic studies probe the overall institutional design of knowledge co production in transdisciplinary research. What is often implicit in this scant regard for governance issues of knowl edge co production is the assumption that the conventional disciplinary mech anisms of journal based peer review, community building through scientifc Transdisciplinary research partnerships 17 TABLE 1.2 Categories of sustainability problems typically addressed through discipli nary, multi disciplinary, and transdisciplinary research Application domains of sustainability science Rather homogeneous societal value perspective Heterogeneous societal value perspectives Various rather independent social and ecological dynamics • Analyze components of social and ecological systems and their interactions • Well-identified research problems and purposes Typically addressed through disciplinary (one main system component) or multi disciplinary research (parallel or sequential analysis of components) • Analyze emergent system patterns resulting from the reciprocal relationships between social and ecological system components • Well-identified research problems and purposes Typically addressed through interdisciplinary approaches • Analyze components of social and ecological systems and their interactions • Multiple diverging perspectives on the research problems and purposes Typically addressed through multi disciplinary research, to take into account the diversity of diverging perspectives Strongly interdependent social and ecological dynamics • Analyze emergent system patterns resulting from the reciprocal between social and ecological system components • Multiple diverging perspectives on the research problems and purposes Typically transdisciplinary research when values have a strong impact on the research design of the socio ecological system; sometimes interdisciplinary if the research design can be settled outside the discussions on the value framing conferences, and dedicated training will also provide the key mechanisms for consolidating transdisciplinary research into larger communities and organi zational frameworks (Benkler, 2008). However, through such imitation of existing organizational mechanisms, although useful to partially address issues of quality management of research outputs and training of young scholars, among others, major organizational issues remain unaddressed. Transdisciplinary research raises major questions regarding designing appropriate institutional rules* for governing research partnerships at vari ous levels. First, the organization of the knowledge co production process 18 Transdisciplinary research partnerships between societal actors and scientifc researchers requires rules for collabo ration among research partners mobilizing heterogeneous knowledge types (Pohl et al., 2021). Second, transdisciplinary research requires appropriate rules for organizing social learning on sustainability values among actors from diferent sectors of activity involved in society wide transformations (Herrero et al., 2019). Finally, to consolidate transdisciplinary research eforts beyond small niche projects, transdisciplinary research requires organizational support for competency and capacity building for research ers, students, and societal actors to allow them to successfully participate in boundary crossing knowledge co production eforts (Pearce et al., 2018). The frst two governance challenges for building transdisciplinary research partnerships are situated at the project level and can be illustrated through a set of questions that must be addressed by the project partners. Given het erogeneous knowledge interests in transdisciplinary research partnerships, how can one avoid each of the partners pursuing their own research agenda once a project proposal has been approved and funded? In particular, how can one create mechanisms such that research partners invest time and resources in research methods and data gathering priorities that best suit the joint boundary crossing research issues? What tools can be used to foster a mutual understanding of how knowledge is constructed in each of the dis ciplines or practitioners’ communities? Moreover, how can one create the appropriate balance between acknowledging the diversity of societal values developed in diferent communities and organizing a dialogue on the possible convergence or accommodation between these values as a basis for successful collaboration? Thus, to tackle these questions, beyond methodological innovations in transdisciplinary knowledge integration, transdisciplinary research will require new forms of collaboration and partnership building, along with pro cesses of social learning among the partners to foster mutual understanding of diverse societal values and methodological perspectives. Indeed, transdis ciplinary research projects generate new governance challenges as they gather scientifc researchers or societal actors with diferent research agendas and interests who are often involved in diferent project contexts. For instance, a project on biodiversity in inhabited agricultural landscapes may assemble historians, sociologists, and biologists to understand the social legitimacy of various landscape management options. Hence, to successfully integrate such diverse knowledge, participating disciplinary scientists or non academic experts must look beyond the methodologies that, at best, satisfy their inter est (quantitative for some, interpretative or qualitative for others) and agree upon a set of research tasks that, at best, serve the common purpose. Further, at a second level, transdisciplinary research faces governance challenges regarding consolidating transdisciplinary research projects in larger organizational units and capacity building eforts. Indeed, how can Transdisciplinary research partnerships 19 one involve interdisciplinary or transdisciplinary researchers beyond small niche networks of jointly defned but specifc research issues? What kind of networking activities can contribute to creating new interactions beyond such small niche networks? How can one decrease search costs to fnd new partners beyond the already well known partners from prior collaborations? Finally, what kind of research resources can be shared across a heterogene ous network of boundary crossing projects to build capacities for training and joint quality management on issues of common concern? Indeed, to consolidate transdisciplinary research in more diverse and com prehensive research networks, researchers and science policy officials require a set of institutional mechanisms to build transdisciplinary research compe tences and research networks in larger communities. As will be discussed in depth in Chapter 5, such larger organizational units can be organized around cross cutting thematic areas of sustainability transformations, be it in the felds of mobility, energy, or agrifood systems, or directly integrate research ers of various thematic communities in more generic research enabling platforms. To develop the various features of the enabling knowledge ecosystem for transdisciplinary research, this book is organized as follows. As highlighted throughout this chapter, research partnerships are prone to a set of govern ance failures. Chapter 2 reviews some of these failures and discusses the key concepts proposed to overcome them by building upon the core insights from the literature on collective action challenges in building scientifc knowledge commons. Chapter 3 presents a comparative analysis of a broad set of cases of transdisciplinary research partnerships, with the view to identify core features of the knowledge co production process that contribute to efec tive usable knowledge production on specifc sustainability transformations. Chapter 4 probes the question of the various strategies for social learning on sustainability values among the project partners, by extending the typology of social learning situations proposed by Amartya Sen in his work on social choice. Chapter 5 uses the results of the comparative analysis at the project level in Chapters 3 and 4 to tackle the question of the institutional design of the consolidation of transdisciplinary research in larger organizational architectures. Chapter 6 briefy discusses some limits and extensions of the analysis by highlighting the importance of building synergies between vari ous modes and types of knowledge production within and beyond academia. As announced in the introduction, through analyzing these various aspects of the enabling knowledge ecosystem, this book aims to provide added value to both the theoretical perspectives for analyzing the governance of knowledge co production and the comparative analysis of collective action challenges encountered in transdisciplinary sustainability research. First, in relation to the theoretical approaches, this book develops a multi level approach to the insti tutional design of transdisciplinary research partnerships, building upon and 20 Transdisciplinary research partnerships extending the literature on the governance of scientifc research commons*. Second, for deepening the analysis of institutional design principles, the book provides a comparative assessment of the conditions for the successful produc tion of usable knowledge based on a large sample of transdisciplinary research projects that encompass a broad diversity of research traditions in academia, ranging from biophysical research to socioeconomic and cultural sciences. Finally, the book uses these insights to provide an analysis of the most appro priate organizational architectures, drawing upon governance mechanisms from the literature on fexible network organizations. Overall, these diferent strands aim to analyze the building blocks for constructing a consistent account of the new transdisciplinary modes for organizing scientifc research, where the integration of societal actors’ knowledge and social learning on societal values is an indispensable part of the knowledge generation process. 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Independent Group of Scientists appointed by the Secretary General of the United Nations, New York. 2 OVERCOMING COLLECTIVE ACTION FAILURES IN KNOWLEDGE CO-PRODUCTION PRACTICES At the heart of transdisciplinary sustainability research projects lies the organization of collective action in research groups or consortia to gener ate common knowledge that is scientifcally credible and socially relevant for addressing specifc sustainability challenges. In particular, understand ing real world interdependent social and ecological system dynamics requires organizing research collaborations among specialized expert communities and societal actors involved in various felds of sustainability transforma tions. This chapter introduces the main collective action challenges encoun tered in organizing collaborative research with heterogeneous groups of knowledge holders and the proposed design principles to address gaps within the literature on the governance of knowledge commons. Collective action problems in community provided public goods have been studied in depth in the context of the theory of the commons. Famously, Elinor Ostrom, in her work on the governance of the commons, for which she was awarded the 2009 Nobel Prize in Economic Sciences, showed that groups of actors can efectively self organize to produce rules to overcome collective action failures in public good provision without centralized rule making by a state. The approach developed in the theory of the commons shows the soundness of pursuing an alternative road to the centralized management of collective action problems and decentralized market governance based on case by case transactions over proprietary goods. A well known promoter of the central ized management option is Mancur Olson (1965), who predicted the col lapse of community provided public goods without state based supervision. Prominent examples of the alternative road of community or network based collection action are common pool resources, such as community forests or DOI: 10.4324/9781032624297 3 This chapter has been made available under a CC BY NC ND 4.0 international license. Overcoming collective action failures 25 community irrigation systems. However, Elinor Ostrom and her co workers also broadened the study of the commons beyond the natural resource com mons to so called new commons, which include scientifc research commons as an important sub category (Hess and Ostrom, 2007). The study of the knowledge commons boomed in the mid 1990s with the rapid spread of digital tools for conducting and disseminating research. As documented in the landmark book Understanding Knowledge as a Commons (ibid), scholars from various disciplines became concerned with the new collective action problems arising from large scale collaboration in digital networks. Especially in legal scholarship, “commons” became a buzzword for the new possibilities of collaboration opened up by globally distributed information, despite the countervailing trends of the global expansion of intellectual property rights over digital network tools and the spread of pass word protected fences on the Internet (Reichman et al., 2016). More generally, within this feld of the knowledge commons, scholars noticed many similarities between collective action problems encountered in governing research commons and community managed natural resources (Hess and Ostrom, 2007). In both cases, non state actors not only provide collective goods in the general interests that are publicly accessible on a non exclusive basis but also exhibit so called partial rivalry among the user communities. Such rivalry, which characterizes “impure” public goods in the standard economic approach of public goods, means that making the good available for consumption by one person might decrease its future availability for other persons (Sandler, 2004). The latter can be because the public good is depleted through use or because there is a cost for making it available in a way that corresponds to the needs or demands of given user communities. Regarding community managed natural resources, this rivalry can lead to the well known “tragedy of the commons,” where the absence of appropri ate rules for the use of the common resource depletes the resource through overconsumption. Regarding the knowledge commons, rivalry may similarly induce a diverse set of collective action failures. As there is a cost to deliver ing knowledge in an appropriate format for targeted users, the lack of rules for collective action may lead to poor quality knowledge, a delay in dissemi nating new fndings, withholding research data, or a lack of investment in new lines of research. Scholars have extensively noted the collective action mechanisms for addressing these challenges in the case of disciplinary knowledge com mons. Disciplinary communities gather researchers around a relatively similar set of core concepts and methodological approaches (Jacobs, 2017). As widely noted by scholars in science studies, such a division of labor in communities organized around common disciplinary purposes and its fur ther specialization in sub disciplines are highly successful in reaching a 26 Overcoming collective action failures critical mass for quality assessment and review, an efficient organization of education and training, and consolidating general results in specifc felds of inquiry (ibid). The main collective action mechanism for organizing collaboration in sub disciplinary and disciplinary communities are the disciplinary journals and disciplinary conferences that channel the contributions around a set of key approaches, concepts, and methods of inquiry (Benkler, 2008). Further, the various social networks built around the disciplinary conferences, the jour nals, and the informal networking of researchers from disciplinary depart ments of diferent universities contribute to building strong social norms around the so called epistemic values or thought styles of the community (Fleck, 1979). Additionally, the institutionalization of the various disciplines and sub disciplines into larger organizational structures is achieved through the conventional organization of research universities and research organiza tions in disciplinary departments. This organization is supported through available funding streams by national research foundations and other research bodies along disciplinary lines (König and Gorman, 2017). As this short overview of the approach to collective action in disciplinary knowledge commons shows, research partners in consortia and research net works can address collective action failures in a decentralized manner via var ious governance mechanisms. As shown by Benkler and Nissenbaum (2006), disciplinary communities can overcome collective action failures through a combination of rules for quality assurance managed by the research commu nities (for peer review and research evaluation, among others) and the devel opment of social norms. Such social norms support the sharing of research results and teaching materials among scientists based on the intrinsic motiva tions of individual researchers to contribute to public science (Macfarlane and Cheng, 2008; Stromberg et al., 2013). However, even if the specifc set of design rules reviewed by Benkler is also important in the transdisciplinary knowledge commons, they fail to address some of the new collective action problems that emerge in the organ ization of knowledge co production. Few of the recommendations indeed specifcally address challenges for governing the hybrid interdisciplinary and co produced knowledge commons typical for transdisciplinary research. Unlike disciplinary and multi disciplinary research consortia and communi ties, transdisciplinary research includes collective action arrangements with non academic societal actors that directly afect the design of the scientifc research framework and processes of social learning over societal values that are specifc to each research partnership. The next sections address some of these specifc governance challenges for organizing transdisciplinary knowl edge co production, which will be analyzed in the subsequent chapters. Overcoming collective action failures 27 2.1 Governance failures in transdisciplinary research This section discusses some of the main hurdles researchers and societal actors may encounter in building efective boundary crossing research part nerships for sustainability research. According to some scholars, part of the difficulty in further expanding the transdisciplinary research practice regards inertia, misunderstandings, and, in some cases, resistance from the existing disciplinary practices. These barriers are certainly pivotal, given the recent growth of transdisciplinary research practices relative to the long time his tory of modern science. However, an important part is also related to a set of new challenges regarding the innovative nature of the collective action and decision making arrangements required to conduct transdisciplinary research. As documented in the general scholarly literature on knowledge commons (Benkler, 2008; Frischmann et al., 2014), efective collective action to build the scientifc knowledge commons results from action at two main levels, which are also present in other forms of collective action for the decentral ized provision of collective goods: 1 The frst level of action is situated at the community, project, or network level (comprising research groups, research consortia, and larger research networks). At this level, scholars underline two important mechanisms that contribute to fostering decentralized collective action: a. The collective action agreements to guarantee the contribution of all participants to common research purposes b. The development of common societal value perspectives that allows for building trust, strengthening intrinsic motivations to take part in the commons, and facilitating coordinated action. 2 The second level is the consolidation of the decentralized knowledge com mons in larger organizational architectures through a supportive insti tutional environment. As the collective action for collaborative research mainly results from action on a decentralized basis (the frst level), the institutional environment does not have a “steering” or “controlling” role but mainly assumes an enabling role of decentralized dynamics. The lat ter can be fostered through capacity building and knowledge exchange networks. The two levels of decentralized collective action and an enabling institutional environment are also present in the case of the transdisciplinary knowl edge commons. Based on the action strategies at these two levels, one can 28 Overcoming collective action failures distinguish three categories of hurdles that have to be overcome in the spe cifc case of transdisciplinary research: 1 The lack of contribution to common boundary-crossing research purposes The organization of collective action to work around common purposes is hampered by the presence of individuals with heterogeneous knowledge interests who might use the transdisciplinary process instrumentally to foster their own knowledge interests. Indeed, disciplinary research ers might use the transdisciplinary research environment merely to facilitate access to new feld research within their disciplinary research agenda, or societal actors might be mainly interested in advocacy for pre given advocacy positions. 2 The fragmentation in an unstructured diversity of values perspectives The lack of relatively homogeneous societal values requires additional mechanisms to reach mutual understanding and forms of collaboration among research partners. These mechanisms are not meant to reach a consensus but to use diversity in a structured way as an asset for an improved understanding of the social possibilities of change in interde pendent social and ecological systems. 3 The isolation of many context-specifc and situated research partnerships Innovative institutional mechanisms must be developed to bridge the many niche networks of tailor made partnerships and foster an enabling envi ronment of common teaching, training, and research resources for transdisciplinary research. Overcoming small niche approaches is key if researchers and societal actors aim to reach a more general understand ing of system interdependencies and desirable system orientations in specifc domains of sustainability transformations and types of collabo rative governance arrangements. The next sections will briefy review each of these challenges and present some ways to overcome them, as per the literature. 2.1.1 The curse of instrumentalization of the research partnership A frst set of collective action failures is related to the proneness of research partners to pursue only their own knowledge interests or habitual ways of working instead of embedding their work within a common research endeavor. This failure was, for instance, clearly identifed in early experi ences with transdisciplinary research on environmental risk assessment, Overcoming collective action failures 29 where societal actors were mobilized in a purely instrumental way to provide increased legitimacy to expert led knowledge generation. According to the seminal analysis by Daniel Fiorino, such an instrumental role of stakeholder involvement in risk assessment mainly served to make the decisions based on research results more legitimate to the general public (Fiorino, 1990). Indeed, as per Fiorino (ibid), in the early 1990s, research institutions working on environmental risks were confronted with a crisis of confdence, as the lay public was increasingly unwilling to delegate decisions to experts and administrative authorities. In response, societal actors were included in risk assessment procedures to restore confdence by acknowledging societal actors’ value perspectives in the expert led assessments and reducing the probability of error through additional inputs of data and information. More generally, in a situation of instrumental mobilization of societal actors’ knowledge, the latter provides additional information or advice to a research team, but the researchers judge if these contributions are relevant or useful within their pre defned research protocol (Mobjörk, 2010). From the point of view of disciplinary and expert led science, the instrumental use of contextual information from societal actors is not necessarily a problem if such use is intended by and based on clear agreements among the parties. Indeed, in situations where the aim is to provide technical knowledge on system components, and the knowledge is relatively independent of specifc path dependent features and societal value choices, science can operate in a relatively autonomous sphere from the input of societal actors. In these cases, several instrumental roles may contribute to the quality of the research process, such as providing extra technical information and know how from practice or contributing to research dissemination by translating the research results to the specifc needs of certain social groups. Importantly, even the case of instrumental participation requires transpar ent prior agreements with societal actors and should be distinguished from window dressing forms of participation, where societal actors are manipu lated such that researchers can more easily obtain data and information or legitimize their funding demands. A positive case in point for such transpar ency requirements is the international agreement on prior informed consent of indigenous and local communities in research projects on the discovery of new drugs or plant varieties for agriculture (Dedeurwaerdere et al., 2016). In other commendatory cases, such as in collaborative research projects funded by national or international research bodies, societal actors are involved in formal consultative bodies or even in the consortia agreements such that their contribution is explicitly acknowledged in the overall research process (Ahrweiler et al., 2019). Obviously, these kinds of agreements may also be important in transdisciplinary research—especially if certain societal actors are mobilized in some project components for instrumental purposes, for 30 Overcoming collective action failures example, when gathering contextual information to improve the overall quality of the research outputs. However, the involvement of societal actors in transdisciplinary partner ship research is substantially diferent from the instrumental mobilization of contextual knowledge. The main diference with the instrumental role is that, for those parts of the research that are co produced, societal actors contrib ute as substantively to the design of the research framework and the interpre tation of the results as scientifc researchers. The reasons for such substantive co production are multiple. For instance, as discussed in one of the case stud ies in Chapter 3 regarding a living lab for the renovation of the historical city center of Cahors in Southern France, the knowledge of old building tech niques by local craftsmen was essential to co develop a research protocol for designing locally adapted bio based materials (see the Cahors living lab project, Section 3.2.1.2). In another case to be discussed, the implementation of a vaccination campaign in Chad, researchers and nomadic pastoralists co designed a joint human and animal vaccination campaign. This collaboration mobilized the knowledge gained from anthropological feld research on the traditional communities’ integrated approach to human and animal health and livestock holders’ knowledge about the efficacy of the livestock vacci nation campaigns (see the Chad healthcare delivery project, Section 4.3.4). In both these examples, the combination of laboratory research and joint experimentation in real world situations allowed for integrating scientifc knowledge with detailed practitioners’ knowledge of technical know how within a co designed research framework. 2.1.2 The pitfalls of unstructured pluralism of societal values The frst governance failure shows the consequences of unequal contributions of research partners to the commonly agreed research purpose. However, successful and efective knowledge co production also depends on mutual understanding among societal actors and scientifc researchers on the specifc value laden perspectives on sustainability transformation pathways. Indeed, research partners might agree on the division of labor to address the common research questions but fail to organize a discussion on how to resolve the dif ference in opinion on the sustainability values used to assess the social desir ability of the envisioned transformation pathways or the contextual validity of the research outcomes (Russel, 2010). In practice, sustainability values can be highly diverse. Indeed, societal actors and researchers might each envision diferent ways to create syner gies and co benefts among the interrelated sustainability goals, inducing a plurality of distinct transformation pathways considered socially legitimate and relevant by the project partners (Fam and O’Rourke, 2020). Thus, to allow for efective coordination among the project partners in this situation, Overcoming collective action failures 31 a minimum level of mutual understanding is required that acknowledges the diversity and employs this diversity to explore areas where converging value perspectives or common action strategies can be formulated. Beyond the minimum level, research partners might strive for stronger forms of partial convergence around core sustainability values, depending on the history of collaboration and the perceived need for enhanced coordina tion to tackle the given problem situation. To designate the failure of reach ing a situation of minimum mutual understanding, or of reaching the desired level of partial convergence on core sustainability values, some scholars refer to this second governance failure as “unstructured pluralism.” As such, unstructured pluralism refers to a situation where a more advanced stage of social learning on sustainability values is required to address coordina tion needs among partners with highly diverse heterogeneous values (Spash, 2012; Popa et al., 2015). An example of the lack of social learning in each of the core sustainability value perspectives around planetary boundaries, environmental justice, and environmental citizenship can give an initial insight into the possible conse quences of the failure to structure these societal values. For instance, regarding the planetary boundaries, in a vast fve year multi stakeholder research project, researchers and societal actors collaborated on understanding waste management transitions in Flanders, Belgium, without concluding the research project given value disagreements (Paredis, 2011). In this case, the partners discovered quite late in the project (the last year out of fve) that one group understood waste management transition as the creation of a market for reused and recycled materials, while the other aimed for reducing waste intensive consumption practices and, thus, waste produc tion. In this case, despite the successful knowledge integration among difer ent societal actors, the project partners used this knowledge to understand and promote two disjointed pathways. Given these disagreements, one of the societal actor partners decided to leave the project consortium before pen ning the conclusion. A second example regarding the Chad healthcare delivery project to be discussed in Chapter 4 (see Section 4.3.4) shows the challenge of a large scale project consortium to address environmental justice issues. In this long term research project on healthcare delivery to nomadic pastoralists in Chad, the project researchers initially failed to recognize the livelihood concerns of the pastoralist community (Bergmann et al., 2012, ch. 3; Hirsch Hadorn et al., 2008, ch. 17). This project was set up after observing that the nomadic pas toralists did not visit the state organized local health centers. In this case, healthcare services were organized in a form that the nomads did not use, given a diferent cultural understanding of the organization of healthcare; hence, in practice, most of them were excluded from primary social services. As analyzed in depth in Chapter 4, it is only through partial convergence 32 Overcoming collective action failures around a set of values addressing both animal and human health that the research team could set up a coordinated research approach with the pasto ralists. On this basis, the program adopted a so called one health approach to the delivery of health services, which organizes healthcare delivery for humans and livestock in an integrated manner. Further, the lack of clarifcation of environmental justice concerns of local communities in research partnerships might also be related to issues of pro cess fairness. A telling illustration of such a situation is the transdisciplinary research on the improvement of education and access to basic social services among an immigrant population in Albuquerque, United States (Goodkind et al., 2011). In that research project, researchers evaluated the contribution of a godfathering program to the improvement of the situation of the immigrant population. However, when selecting individuals to participate in this action research project, some individuals declined to participate, as they estimated that other members of the community should frst be involved and beneft from the godfathering, even if they were not originally part of the group targeted through the research protocol. Overall, the community members highlighted the lack of dialogue in the selection process of possible participants in the action research program. In response, the research team adapted the sampling procedure to these requirements of process fairness by better integrating com munity members in organizing the data gathering process. 2.1.3 Beyond small niche networks for boundary-crossing research The frst two governance failures of instrumentalization of the knowledge generation process and the failure of unstructured pluralism are situated at the project level. Nonetheless, to successfully build transdisciplinary knowledge commons on sustainability challenges, there is also a need to look beyond the project level. Indeed, without additional institutional eforts, project partners may remain in small niche networks around practical or theoretical problem solving on highly specifc research issues. The small niche networks for transdisciplinary research, although already useful for addressing selected research puzzles that cannot appropriately dealt with through disciplinary methods, may fail to contribute to reliable and comprehensive transdisciplinary research commons on sustainability transformations. Indeed, if limited to small niche networks, these research projects do not address some important objectives that are part of the more general purposes of scientifc research (Singleton and Straits, 2005; Willis, 2007). First, small niche projects lack a more general perspective on thematic areas of sustainability transformations and fail to contribute to a more generic understanding of human and natural interdependencies. Second, they lack the means to verify the validity of research results and Overcoming collective action failures 33 research approaches in other similar contexts of sustainability challenges. Further, they do not contribute to building more generic approaches to knowledge co production and social learning that can be used in a broader set of problem situations. Therefore, to strengthen the overall scientifc knowledge base and meth odological approach that are relevant for addressing a broad diversity of sustainability issues in society wide transformations, the small niche projects must be embedded in a larger institutional ecosystem of boundary crossing research projects. In the context of transdisciplinary research, characterized by a heterogeneous set of highly diverse boundary crossing projects, mov ing beyond small niche projects might be quite challenging. Various mecha nisms to address this challenge to be discussed in more detail throughout this book include the organization of knowledge exchange in hybrid knowl edge networks, social networking for identifying potential opportunities for knowledge co production with societal actors, and training for the building of transdisciplinary research competences. 2.2 Theoretical building blocks from the multi-level approach to governing scientific research commons This section further develops the multi level approach for overcoming the identifed collective action failures. Indeed, as underlined more generally by scholars of knowledge commons, to address the possible collective failures, appropriate strategies at, at least, two main levels (the level of decentralized collective action and the enabling institutional environment) are necessary (Ostrom, 2005, pp. 99–133). Based on this basic model, this book will analyze three core sets of strat egies for the organizational and institutional design of transdisciplinary knowledge co production. These three strategies and the related research questions will be addressed. First, two core strategies at the level of decentralized collective action 1 Decentralized collaborative governance strategies at the research commu nity level (research groups, consortia, and larger research networks) • Analysis of the collaboration mechanisms for knowledge co-production (knowledge integration, co management of the knowledge co produc tion, and co construction of the research design) 2 Decentralized social learning mechanisms at the research community level • Analysis of the mechanisms of social learning over sustainability values in knowledge co production 34 Overcoming collective action failures Second, a third strategy at the level of the enabling institutional environment 3 Enabling and consolidating the decentralized dynamics through a support ive institutional environment • Analysis of the integration of the boundary-crossing project networks into broader enabling networks for transdisciplinary research Given the historical importance of the scholarship on collective action based on the rational actor perspective, this chapter will introduce these various strategies from the perspective of the so called second generation theory of collective action (Ostrom, 1998). This perspective helps to introduce a simplifed model of the two level approach, which will then be gradually enriched and broadened in the specifc chapters dedicated to each of the col lective action strategies and mechanisms. The proposed model does not address the higher level of the overarch ing institutions of research policy that impact the choices that can be made in universities and research organizations for building the enabling environ ments and organizing transdisciplinary project work. This does not mean that this overarching higher level is not important, as clearly shown in the systematic review of multi level institutional analysis by Hollingsworth (2000). However, to address the issues of reform of research policy, a deeper understanding of the design requirements at the level of the organization of boundary crossing research projects and the level of the enabling environ ment in research organizations is frst required. Except for some short indica tions in Chapter 5, the analysis of governance and institutional design in this book will therefore mainly focus on the levels of the project organization and the enabling institutional environment at institutions of higher education. 2.2.1 Organizing collaboration mechanisms for knowledge co-production Based on the similarities of the collective action challenges between natural resource and knowledge commons, scholars have adopted a broad approach to community produced collective goods. From a theoretical perspective, commons can be defned as resources that are jointly used and managed by groups of varying sizes and interests (Hess and Ostrom, 2007, p. 5). This approach also applies to the case of transdisciplinary knowledge co pro duction, where the research partners collaborate in the production, use, and dissemination of usable knowledge on specifc sustainability transformation pathways. The previous section highlighted an important collective action fail ure in the case of transdisciplinary knowledge commons, which is the Overcoming collective action failures 35 instrumentalization of the partnership for one’s research purposes. This fail ure is related to the challenge of overcoming the tendency of research part ners to follow their own disciplinary or practical knowledge interests instead of contributing their eforts and resources to solving common boundary crossing research questions. This collective action failure of common knowledge production, which may induce under provision of the common good, is a feature that is also somewhat present in interdisciplinary research consortia. In the case of inter disciplinary consortia, neglecting to invest time and resources in the common interdisciplinary research questions is in part related to the lack of incentives to produce knowledge beyond disciplinary interests. Two main hurdles can be mentioned. First, the expected contributions to the common interdisci plinary research framework do not necessarily contribute to the state of the art in the disciplinary specialization, and, second, they do not always ft the specialized disciplinary standards for data gathering. This so called under provision is an important collective action challenge recognized in the broader scholarship on the building of knowledge com mons in large scale collaborative research. Michael Madison highlights the latter in the case studies of the companion volume on Governing Knowledge Commons (Frischmann et al., 2014). As stated by Madison, without proper governance mechanisms, producers of knowledge resources “will fail to invest in creating new goods or in preserving them, either on their own or in combination with others, because of uncertain[ty] [in] their ability (either individually or collectively) to earn returns that justify the investment” (Madison, 2014, p. 219). Hence, to address these problems in interdisciplinary research collabora tions, researchers have set up various governance mechanisms to foster col lective action around standards of open science, research accreditation, and joint eforts in common quality management. For instance, Yochai Benkler shows in his landmark work on “the power of networks” how scientists in interdisciplinary felds of research follow common standards of open science and joint quality standards by participating in various social networks at scholarly conferences and expert groups (Benkler, 2008). Another leading political economy scholar of the historical emergence of the science com mons, Joel Mokyr, highlights the crucial role of formal and informal peer review practices as a tool for collective quality management ever since the emergence of the modern scientifc societies in the 17th and 18th centuries (Mokyr, 2011). Nevertheless, regarding the transdisciplinary research commons, these governance mechanisms are not sufficient to build an efective knowledge commons. Indeed, regarding transdisciplinary research projects, a single sci entist does not operate within a larger community, as in the case of disci plines or interdisciplinary felds of research. Rather, they are involved in a set 36 Overcoming collective action failures of diferent research projects, each of which comprises members of distinct disciplinary communities and societal actor groups. For instance, a researcher on the transition toward sustainable food sys tems may collaborate in one project with health professionals and researchers in bio medical and nutrition sciences; in another project, they may collabo rate with agronomists and economists, and in yet another project, with a representative of the local municipality and a political scientist. Each pro ject mobilizes diferent combinations of disciplinary and practical knowledge that require building agreements on the contribution of partners with difer ent knowledge interests to the common knowledge co production process. A centralized, top down solution to this challenge is unlikely to provide sufficient guarantees to ensure the collaboration of all partners to contribute to common research endeavors. For instance, research funding bodies may require evidence for efective collaboration with societal actors in knowledge production as a condition for the allocation of funding. However, as shown in comparative analyses of climate change research projects by de Jong et al. (2016), such contractual obligations may attract projects that involve soci etal actors as window dressing, assigning them a role while not necessarily giving them infuence. It forms part of the general issues with participation, as highlighted by Sherry Arnstein in her classic work on citizen involvement in planning processes in the United States: “There is a critical diference between going through the empty ritual of participation and having the real power needed to afect the outcome of the process” (Arnstein, 1969, p. 216). As per de Jong et al. (2016), true participation in joint knowledge genera tion requires more direct co management by the participating scientists and societal actors of the various aspects of the research process, similar to the co management arrangements to overcome collective action problems in the natural resource commons. For instance, scientifc researchers and societal actors as project partners can collaborate on the joint defnition of research goals and core research questions. Regarding research design, both partners can make valuable contributions to the selection of cases and data sources. During the research, they may contribute data that would otherwise be chal lenging to obtain and provide access to facilities and study sites. In com municating research results, their involvement may help to consider local contexts and communicate research results clearly. Ideally, all research part ners should play a role in each phase of the process, as the impact on the production of usable knowledge has been shown to increase with the number of phases in which they have a role (Pohl and Hirsch Hadorn, 2007; Peer and Stoeglehner, 2013). Notably, scholars of transdisciplinary research distinguish diferent degrees of involvement in the co management of the knowledge co production pro cess. This involvement can be quite strong, as in the case of co decision making in a common governing board or joint supervision by scientifc Overcoming collective action failures 37 researchers and societal actors of the Ph.D. research fellows of the project. It can also rely on weaker forms, such as through specifc collaborations on agreed upon real world test cases or agreements for joint involvement in data gathering. Per the perception of the danger of a lack of dedication of time and resources to the common endeavor, the partners might decide to invest in stronger (thus, more demanding) or weaker and less demanding forms of co management. In some cases, when the initial motivations of all partners to address a common research question are strong, they may consider that the risk of instrumentalization is not high. For instance, in a well documented suc cessful large scale transdisciplinary research project on community health approaches in the province of North Karelia, Finland, there was a clear intrinsic motivation of all partners to contribute knowledge to understand ing the interdependencies between environmental factors, change in social practices, and individual behavior and health outcomes (Puska et al., 2009). In such cases, the co management processes may be lightweight. In this case, the co management process was mainly organized around specifc tasks for joint data gathering on the common research issues and joint analysis of the research results. When the risk of instrumentalization is high, as in the case of the partici pation of disenfranchised social groups, research partners are likely to make stronger investments in co managing various components of the research pro cess. One prominent example of such a situation of strong power diferentials will be discussed in Chapter 4, regarding the project co led by ATD Quart Monde on food assistance in Brussels, Belgium. In this case, the research partners adopted a strong co decision making approach called “merging of knowledge,” developed by the non proft association ATD Quart Monde. It is used for building transdisciplinary research partnerships to overcome situ ations of extreme poverty. In this methodology, given the important power diferentials, persons living in poverty are involved at all stages through co decision on the question to be addressed, joint data gathering, permanent discussion and adjustment on the research methods to be chosen, and com mon writing of the research outputs. By involving persons living in poverty as “situational experts,” this project contributed to a more multi dimensional approach to food assistance, in particular by underlining the importance of respect for the dignity of each recipient of food assistance as a key “soft” value that is often not at the heart of poverty research. Overall, the main lesson of the literature on collective action for invest ment in common knowledge production in transdisciplinary research is the importance of the collaboration of scientifc researchers and societal actors in the governance of the research process. As analyzed in depth in Chapter 3, this collaboration process goes beyond the conventional stage of knowledge integration between science and practice. The collaboration also includes the 38 Overcoming collective action failures co management of various steps of the co production process and the active involvement in research co design (Lang et al., 2012; Norström et al., 2020). Per the perceived danger of instrumentalization, the research partners may decide to invest more time and resources in the deliberation on one or several of these aspects of the collaboration process. 2.2.2 Social learning on the sustainability values The organizational perspective on the partnership among scientifc researchers and societal actors is only one lens through which one can approach the chal lenges of collaborative governance of the research process. A second impor tant aspect that contributes to the efective governance of the commons is the mutual learning on partially convergent or at least mutually compatible soci etal values perspectives. As shown in several review papers on knowledge inte gration by leading scholars in sustainability research, social learning that seeks to reach mutual understanding on a diversity of societal values plays a key role in successful transdisciplinary knowledge co production (Pohl et al., 2021). In her later work during the mid 1990s, Ostrom (1998) developed the role of convergence around societal values in contributing to in depth collective action. For instance, in the review paper on the “Second generation theory of collection action,” Ostrom (ibid) shows how communities that develop mutual learning around societal values successfully decrease the costs (regard ing time, organizational means, and material resources) invested in organ izing coordination among the community members. Indeed, these societal values create patterns of behavior that, if recognized by the other members, allow for anticipating behavior and common action strategies around the agreed upon rules more efectively. In the case of the community manage ment of natural resource commons analyzed by Ostrom (1990), societal val ues evolve through two types of mechanisms. First, communities gradually adopted societal values through a process of trial and error experimentation throughout the history. Second, when societal values became more diverse, they further evolved through processes of public deliberation to impartially assess their respective validity through rational argumentation. This second type of evolution of societal values through deliberation is most relevant to the case of transdisciplinary research partnerships. Indeed, regarding transdisciplinary research commons, the role of deliberation among the research partners is likely to be crucial, as the actor networks are highly heterogeneous and changing. As will be discussed in depth in Chapter 4, this deliberation on societal values among the project partners can strive to reach stronger or weaker forms of partial convergence over key sustainability val ues. The latter hinges on the perceived need for convergence—which depends on the complexity of the coordination needs among the project partners— and on the history of trust building through previous collaborations. Overcoming collective action failures 39 For instance, convergence among societal values can be absent at the begin ning of a project amid strong conficting interests. In such cases, partners may decide to focus frst on creating the conditions for mutual understanding of the legitimate and relevant perspectives of the various project partners. In other situations, the partnership may start with high levels of mutual under standing, but the addressed sustainability transformations may nevertheless require identifying the areas of convergence on societal values for organizing coordinated action. In the latter case, the social learning process may strive to identify such areas of convergence and clarify the remaining areas of diver gence. These diferent mechanisms will be analyzed in depth in Chapter 4. 2.2.3 Collaborative platforms for enabling the integration of polycentric knowledge networks The second level of collective action strategies reaches beyond the decentral ized strategies at the project level to the building of larger organizational archi tectures for enabling transdisciplinary research. As argued, to build a more encompassing knowledge base on sustainable interdependent social and eco logical system dynamics, an appropriate institutional environment is required to enable the building of generic capacities for transdisciplinary research. The challenge of fostering interactions among a broad diversity of knowl edge co production activities, beyond the individual boundary crossing project networks, shows many similarities to the general idea of building a polycentric network of commons in Elinor Ostrom’s analysis. According to Ostrom (2010), beyond the level of specifc commons based initiatives, a major governance feature of successful and enduring commons is their embedding in larger polycentric networks. These networks provide a higher level of integration among the local commons that contributes to their long term successful operation through various collaborative arrangements. As shown in the broader research on network governance (Sørensen and Torfng, 2007), such institutional arrangements can be limited to only parts of the overall network, such as the creation of network clusters for the shar ing of knowledge, or be more generic, such as through the building of generic competences for collaboration and co management. Regarding transdisciplinary research, the challenge is to build capacities for researchers and societal actors to conduct transdisciplinary research in highly diverse problem contexts involving diferent combinations of con ceptual approaches and partners with diferent knowledge backgrounds. Therefore, the enabling institutional environment must create incentives for research partners to look beyond their specialized project networks and to build bridges with other feld specifc knowledge co production processes. For instance, the review papers by Veronica Boix Mansilla et al. (2016) on interdisciplinary collaborations and the review paper by Christian Pohl 40 Overcoming collective action failures et al. (2021) on transdisciplinary research underline the importance of such boundary crossing institutional enabling mechanisms. First, they underline the importance of decentralized learning by research partners across hybrid boundary crossing initiatives through the creation of so called trading zones or boundary objects (Boix Mansilla et al., 2016, p. 573; Pohl et al., 2021, p. 23). These spaces for decentralized learning cluster participants around overlapping research activities in a way that is “plastic enough to be inter preted diferently by relevant actors yet robust enough to maintain . . . unity across contexts” (Boix Mansilla et al., 2016, p. 580). Further, participation in these bridging networks promotes the acquisition of transdisciplinary research competences via mastering a diversity of socio ecological research methods and frameworks that can be used to analyze a broad set of context specifc transformation pathways. Despite the similarities between the various enabling mechanisms for polycentric networking in the cases of natural resource commons and trans disciplinary knowledge commons, it is important to highlight an important diference between these two cases. Natural resource commons addresses communities that manage well identifed natural resource systems with rather homogeneous shared societal values that evolved gradually to adapt resource management strategies to local contexts. Regarding transdiscipli nary research projects, the defnition of the socio ecological system is not identifed in advance, as it strongly depends on the problem framing, and societal values tend to be highly heterogeneous among the project partners. Further, to apply the polycentric network concept developed by Ostrom and other scholars of network based governance to the case of transdiscipli nary research commons, the collaboration agreements must involve a strong degree of active deliberation on the network boundaries, the co construction of the topics to be addressed, and the value perspectives to be included. Therefore, the various proposed network bridging and competence building activities must also be actively co constructed with both societal actors and scientifc researchers. As will be discussed in depth in Chapter 5, the lat ter can be implemented via practicing interdisciplinary and transdisciplinary research co design in the teaching of transdisciplinary methods, the involve ment of societal actors in identifying potential research topics or creating thematic clusters for the sharing of knowledge. 2.3 Promoting synergies among various styles of transdisciplinary research practice The multi level analysis of collective action for contributing to knowledge commons shows that the building of transdisciplinary research commons relies on a distinct set of design principles. These design principles are dif ferent from the case of specialized disciplinary research commons, as they Overcoming collective action failures 41 introduce new standards of evidence, such as the integration of societal actor knowledge in the co construction of research design and social learning on societal values at the project level. Likewise, at the level of the supporting institutional environment, the accent is more on the development of capaci ties for boundary crossing work and network bridging instead of the consoli dation of research results around relatively consistent common disciplinary concepts and methodological approaches. As shown in the discussion of three main strategies to overcome collective action failures, transdisciplinary scholars mobilize a variety of mechanisms to ensure the efective contribution of all research partners to knowledge co production. In theory, research projects that combine each of these strategies show the highest chance of efective co production of usable knowledge on sustainability transformations. In practice, however, given limits of resources or diferent initial experiences among the project partners, projects often focus on one of the strategies or a combination of strategies deemed most relevant for improving upon the problem situation. The choice of these strategies and mechanisms is infuenced in large part by a broader understanding of the relationship between knowledge gen eration in transdisciplinary research projects and the contribution to solv ing sustainability issues in interdependent socio ecological systems. In this context, based on a literature review and an analysis of a representative set of 31 transdisciplinary research projects at their research institute, Flurina Schneider and her colleagues identifed three main pathways of impact gen eration (Schneider et al., 2019) (see Figure 2.1). The most well known pathway is rooted in the assumption that transdis ciplinary co production of knowledge is a cognitive process leading to new knowledge, understanding, and propositions that can subsequently be used Research projects oriented towards knowledge co-production on socio-ecological system dynamics Transdisciplinary co-production of knowledge Research projects oriented towards social learning on sustainability values within societal transformation processes Sustainability transformations Workshops and training involving the building of transdisciplinary competences within coproduced socio-ecological analysis FIGURE 2.1 Research styles within transdisciplinary research contributing to sus tainability transformations Figure by the author, based on an adaptation of theoretical concepts developed in Schneider et al. (2019). 42 Overcoming collective action failures to inform societal actors for decision making. As stated by Schneider et al. (2019), in this pathway, the generated knowledge is seen as “a substance to be transferred from the project to other people,” where it can trigger action (ibid, p. 29). The project review by Schneider et al. (2019) identifed two other impor tant understandings of impact pathways that play a role in transdisciplinary research practices. The second pathway is the generation of societal impact by promoting capacities for collaborative governance among research part ners with heterogeneous societal values. In this understanding, transdisci plinary knowledge is “conceived as the emergent property of interactions and is situated in coordinated actions rather than as a substance that can be removed from the social context where it was created” (ibid, p. 30). The third pathway focuses on the building of individual competences for boundary crossing analysis via transformative educational practices or shared learn ing in communities of practice (ibid, p. 31). The research partners can use the acquired competences in various research projects or decision making in societal practices. Given these diferent understandings of the impact pathways, the spread of transdisciplinary research practices does not induce a well identifable and unifed new research practice. Rather, researchers developed diferent approaches and research traditions within the enterprise of transdisciplinary research. As in the case of disciplinary research commons, these diferent approaches and research traditions can be understood as diferent research styles.* Following the historical epistemology approach of Ian Hacking (2012), research styles are characterized by common problem interests and approaches to tackle research problems. That is, via the diferentiation in diferent research styles, the key organizing concepts of transdisciplinary sustainability science (interdisciplinary analysis of interdependent social and ecological dynamics and partnership research with societal actors) yield various research traditions with interrelated but distinct research interests (Sciortino, 2017). Obviously, the various collective action challenges play a role in each of the three research styles identifed by Schneider et al. (2019). However, some challenges are more critical in certain research styles than others. Therefore, in the subsequent chapters, we will analyze each of the collective action chal lenges in the context of one research style (see Figure 2.2). First, as noted, the most well known research style is related to the pro duction of usable knowledge outputs that can subsequently be transferred to support societal actors in decision making. Moreover, this research style is formulated in one of the most cited papers in the feld (Lang et al., 2012), which defnes transdisciplinary research as a “refexive, integrative, method driven scientifc principle aiming at the solution or the transition of societal problems and concurrently of related scientifc problems by diferentiating Overcoming collective action failures 43 Conditions for governing collective action in transdisciplinary knowledge commons • Research co-design • Co-management of the partnership Research styles contributing to research impact Knowledge co-production on socio-ecological system dynamics • Impartial dialogue on societal values Transdisciplinary co-production of knowledge • Non-coercive dialogue • Broad inclusive Social learning on sustainability values within societal transformation processes Sustainability transformations perspective o Enabling of formation of flexible, adaptive boundary crossing teams Competences and capacity building for co-produced socio-ecological analaysis o Enabling of decentralized research goal setting + generic conditions common to disciplinary / interdisicplinary / transdisciplinary research: peer review of research results and community building through workshops and conferences. FIGURE 2.2 Key conditions for governing collective action in each of the three styles of transdisciplinary research practice. The detailed analysis of each condition is the subject of Chapters 3, 4 and 5. and integrating knowledge from various scientifc and societal bodies of knowledge” (ibid, p. 27). In particular, as highlighted by many scholars, understanding issues and solving problems in the practical life world of soci etal actors through transdisciplinary research requires matching the knowl edge co knowledge process with legitimate actors’ purposes in the problem feld and the available real world options for change. Therefore, transdisci plinary research in this perspective must integrate three main types of knowl edge: (1) systems knowledge, (2) target knowledge (regarding the purposes of social practices), and (3) transformation knowledge (regarding the real world options for change) (Hirsch Hadorn et al., 2008, p. 28; Lang et al., 2012, p. 26; Schneider et al., 2019, p. 29; Karrasch et al., 2022). Although researchers can encounter a diverse set of governance challenges, a core collective action challenge to tackle in this frst research style is the tendency toward the instrumentalization of the usable knowledge focus. As noted in the analysis in this chapter, research partners can instrumentalize the common endeavor for their scientifc or advocacy purposes without dedicat ing time and resources to co producing a common problem understanding, research approach, and methodological framework. Disciplinary research ers may be confronted with diferent methodological requirements for feld research, laboratory work, or modeling. Societal actors may also have dif ferent priorities when mobilizing resources for promoting action strategies that address diferent aspects of desirable sustainability transformations. In this context, organizing deliberation throughout the research process to align 44 Overcoming collective action failures the partners around a common research design is crucial to provide usable knowledge on feasible and scientifcally reliable options for society wide transformations. The overall objective of the frst style of transdisciplinary research prac tice is to produce scientifcally reliable and usable knowledge that matches, at best, the legitimate and most relevant sustainability value perspectives in the specifc problem area. Although social learning on sustainability values occurs during such research projects, the main focus in the analysis of this frst research style is on collective action for matching the usable knowledge to the given set of sustainability values in the problem area. An important presupposition of the analysis of this frst style of research is the existence of a sufficient level of mutual understanding of the given value perspectives among the research partners. When the mutual understanding is insufficient, the collaboration between the actors may be seriously hampered and research partners may decide to focus the research partnership in the frst instance on improving this mutual understanding as a condition of fruitful collaboration before embarking upon usable knowledge production. The second style of research practice identi fed by Schneider et al. (2019) addresses this second challenge by organizing a “social learning process that enhances the participants’ collective agency and potential for joint action toward sustainability” (ibid p. 30). In this under standing of transdisciplinary research practice, one major collective action challenge is organizing deliberation to foster mutual understanding among the project partners on sustainability values. An important goal of this second style therefore is to overcome the collective action problems regarding the unstruc tured diversity of societal value perspectives. As noted, such unstructured diversity may lead to fragmentation or the unrefective uptake of certain nor mative orientations based on path dependent habits (potentially perpetuating existing rent seeking behavior). The main issue is the establishment of mutual understanding through a process of impartial and inclusive dialogue, where the societal value positions are submitted to public argumentation and critical deconstruction of ideology and dominant knowledge structures. Finally, the research styles directed toward usable knowledge production and social learning within societal transformation processes can beneft from a supportive institutional environment. Such an environment is especially important to further disseminate transdisciplinary practices beyond small niche projects. Important features of this institutional capacity building for transdisciplinary research can also be the specifc target of research projects, for instance, via organizing competence building or knowledge exchange on research in diferent situations of sustainability transformations. This third concern is addressed in part through the third research style identifed by Schneider et al. (ibid), directed toward building transdisciplinary research competences. Overcoming collective action failures 45 As stated by Schneider et al. (ibid, p. 31), the underlying assumption in this third style of research practices is that when research partners “engage in transdisciplinary work, including joint experimentation, learning, and self refection, they develop competences (knowledge, skills, values, and atti tudes) that enable them to better tackle sustainability challenges and oppor tunities in their life and work.” Obviously, the example of transdisciplinary teaching, where students must design and implement a partnership research project (e.g., as a part of their master thesis) is a good case in point of such competence building research practices. In the analysis in Chapter 5, this third research style will be considered more broadly as designating transdisciplinary research practices that con tribute to various kinds of capacity building in the institutional environment. Competence building is one of the mechanisms; other enabling mechanisms to be considered include research practices to consolidate knowledge, such as meta research for a better understanding of certain transdisciplinary process features and exploratory research projects or workshops to connect interested actors and initiate new co production or social learning processes. Regarding the collective action problems discussed, these practices specifcally presup pose the formation of integrated polycentric networks that can support research activities in a larger ecosystem of boundary crossing research and knowledge exchanges. As noted from this short outline, each of the subsequent chapters will address the collective action challenges in the context of one style of trans disciplinary research practice, respectively organized around one aspect of the impact pathways of transdisciplinary research. As mentioned, in practice however, research partners often combine various aspects of the research styles to organize successful transdisciplinary research. The lat ter can be the case within a given project or through a sequence of difer ent projects that build upon the outcomes of the previous project work. Therefore, the analysis of the diferent research styles must be considered in the context of a broader research ecosystem, where, through the crea tion of synergies and interactions among research teams involved in various transdisciplinary research practices, the diferent knowledge co production, social learning, and institutional capacity building challenges can be suc cessfully addressed. References Ahrweiler, P., Gilbert, N., Schrempf, B., Grimpe, B. and Jirotka, M. (2019). The role of civil society organisations in European responsible research and innovation. Journal of Responsible Innovation, 6(1), 25–49. Arnstein, S. R. (1969). A ladder of citizen participation. 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Governing digitally integrated genetic resources, data, and literature: Global intellectual property 48 Overcoming collective action failures strategies for a redesigned microbial research commons. Cambridge: Cambridge University Press. Russell, J. Y. (2010). A philosophical framework for an open and critical transdisci plinary inquiry. In V. A. Brown, J. A. Harris and J. Russell (Eds.), Tackling wicked problems (pp. 31–60). Abingdon: Routledge. Sandler, T. (2004). Global collective action. Cambridge: Cambridge University Press. Schneider, F., Giger, M., Harari, N., Moser, S., Oberlack, C., Providoli, I., . . . and Zimmermann, A. (2019). Transdisciplinary co production of knowledge and sus tainability transformations: Three generic mechanisms of impact generation. Environmental Science and Policy, 102, 26–35. Sciortino, L. (2017). On Ian Hacking’s notion of style of reasoning. Erkenntnis, 82(2), 243–264. Singleton, R. A. and Straits, B. C. (2005). Approaches to social research. 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This efort is refected in the vast amount of scientifc journal papers produced on knowledge integration in sustainability research. However, such research eforts do not always induce the production of usable knowledge on real world sustainability transformation pathways. The hypothesis in this chapter is that to produce usable knowledge outputs for sustainability transformations, sustainability researchers must strengthen the collective action arrangements to co construct a common research frame work for socio ecological analysis. This investment in research co design is needed to provide additional guarantees for the alignment of heterogeneous knowledge interests and value laden perspectives around a common research purpose. These guarantees extend beyond the well researched conditions of the integration of societal actors’ knowledge and perspectives in knowledge generation processes. Thus, to test the hypothesis on the importance of co constructing the research design, this chapter considers a broad sample of cases that covers diferent levers of transformation in socio ecological systems, ranging from technological and socioeconomic levers to policy and sociocultural change. Covering the various levers of societal transformation aims to provide evi dence of the organization of research co construction with societal actors that are, potentially, of concern to a broad set of transdisciplinary research traditions on interdependent social and ecological system dynamics. The analysis in this chapter will proceed in three steps. The frst sec tion presents a sample of in depth case studies of transdisciplinary research DOI: 10.4324/9781032624297 4 This chapter has been made available under a CC BY NC ND 4.0 international license. 50 Actionable knowledge outputs through collaborative research co-design and applies a basic model of research co design to the comparative analysis of success or failures in usable knowledge production. The second section deep ens this preliminary analysis via an overview of knowledge co production in fve research clusters dealing with distinct levers of sustainability transforma tions. The third section concludes by showing how this analysis of knowl edge co production fts with the more general epistemological framework of pragmatist constructivism. 3.1 Usable knowledge production on sustainability transformations 3.1.1 A model of research co-design for delivering usable knowledge outputs To conduct a preliminary analysis of the production of usable knowledge, this section discusses the key features of research co design and a basic model of various types of usable knowledge outputs developed from the existing scholarly literature on the societal impacts of transdisciplinary research. 3.1.1.1 Collaboration for knowledge integration, process co-management, and research co-design As acknowledged by scholars of transdisciplinary research, efective produc tion of usable knowledge outputs requires intensive collaboration among sci entifc researchers and societal actors for knowledge integration from various sources in combination with a form of co management of the knowledge generation and dissemination processes. These two types of collaboration mechanisms are also highlighted in a review paper by 36 co authors work ing on sustainability research published in Nature Sustainability (Norström et al., 2020). Norström et al. (ibid) frst highlight various mechanisms of knowledge integration between scientifc researchers and societal actors. This frst type respectively aims at producing knowledge situated in a particular context or issue (context based), integrating multiple ways of knowing and doing (pluralistic) and articulating shared goals related to the challenge at hand (goal oriented). The second type of mechanism relates to the iterative and collaborative character of the co management process. As stated by the authors, the “act of engagement across domains and disciplines can be as important for the pursuit of sustainability as the production of knowledge.” This mechanism of “process co management” emphasizes that co production produces more than just knowledge. It develops capacity, builds networks, fosters social capital, and implements actions that contribute to sustainability (ibid, p. 2). Actionable knowledge outputs through collaborative research co-design 51 The need to combine mechanisms for knowledge integration with the co management by the scientifc researchers and societal actors is a com mon thread in the literature on transdisciplinary co production (see also sec tion 2.2.1). However, this perspective on knowledge co production does not specify the conditions under which the collaboration leads to elaborating a common framework for analyzing interdependent socio ecological transfor mation dynamics. The contextual and pluralist knowledge integration mech anisms identifed by Norström et al. (ibid) may be successfully implemented without co designing the interdisciplinary framework for the analysis of the socio ecological system dynamics. Thus, such a process might produce usable knowledge outputs that are co produced among the scientifc researchers and societal actors in a pluralist and context specifc way but that only address separate components of the overall sustainability issues. To address the challenge of common knowledge production on specifc interdependent dynamics between social and ecological system dynamics, this chapter considers an additional type of mechanism to be considered in the knowledge co production process: the co construction of the interdisci plinary research design among the scientifc researchers and societal actors. Indeed, to understand the specifc coupled dynamics between the social and ecological dimensions of sustainability transformations, scientifc researchers and societal actors must match the research design to the real world pos sibilities of interdependent socio ecological transformations. Therefore, the design of interdisciplinary frameworks cannot be separated from the under standing of the given value related perspectives on real world transformation pathways. The key additional challenge, therefore, is to understand how heterogene ous knowledge sources and research styles can ft into a common research design that refects specifc feasible and desirable sustainability transforma tion pathways. In this context, researchers can beneft from the systematic analysis of research design practices in the broad feld of mixed methods research. Mixed methods are used in many specifc areas of interdisciplinary research, such as geography or landscape ecology. However, in transdiscipli nary research on socio ecological systems, they are omnipresent. In a review paper on mixed methods research, Joseph Maxwell and Diane Loomis summarize fve key ingredients of successful mixed methods research that can be adapted to the purposes of transdisciplinary co design (Maxwell and Loomis, 2003). Figures 3.1 and 3.2 schematically represent them, respec tively, for the cases of disciplinary and interdisciplinary research. The central component of the research design with mixed methods is the design of interrelated and compatible research question among the research partners: What specifcally do the researchers want to understand by con ducting the research? What questions will the researcher attempt to answer? However, as illustrated in Figure 3.1, to fruitfully combine various methods 52 Actionable knowledge outputs through collaborative research co-design Conceptual framework Purposes Interrelated/compatible research questions Validity Methods FIGURE 3.1 Research co design among researchers in multi method disciplinary research Figure by the author, based on an adaptation of the concepts developed in Maxwell and Loomis (2003). Conceptual framework Purposes Research questions Methods Conceptual framework Purposes Validity Research questions Research questions Methods FIGURE 3.2 Conceptual framework Purposes Validity Methods Validity Research co design among researchers in interdisciplinary research in a common research design, the researchers must agree upon a set of other design elements. Four additional design elements are underlined in the review by Maxwell and Loomis (ibid): (1) the conceptual framework that gathers the contributions of the various disciplines in a common model, (2) the crite ria of validity and the limits of each of the knowledge types, (3) the available Actionable knowledge outputs through collaborative research co-design 53 approaches and techniques to collect and analyze the data, and (4) the com monly agreed upon goals of the study. Regarding interdisciplinary research on sustainability problems, the co construction of the diferent design elements must be coordinated among the diferent disciplines. Indeed, to be relevant, interdisciplinary framework research must look beyond the analysis of the single components, which are often better addressed through purely disciplinary research, and look at the interactions between the natural, social, and human science features of the problem at hand. In this context, to make the heterogeneous knowledge perspectives among the various disciplines mutually consistent, the research partners must organ ize a form of reciprocal learning between the various disciplines, sometimes qualifed as reciprocal reference (Jaeger and Scheringer, 1998) or reciprocal critique (Becker and Jahn, 2003). This reciprocal learning can take the form of adjustments at the level of selection of methods that allow for knowledge transfer from one discipline or knowledge type to another or adjustments at the level of conceptual background assumptions, data collection methods, and sampling strategies. Without such reciprocal adjustment of knowledge perspectives, there is no guarantee for an efective contribution to a common research endeavor. Indeed, scholars approaching the same socio ecological reality through dif ferent disciplinary approaches use diferent conceptual frameworks to build their research objects, even when addressing the same real world phenom ena (Sciortino, 2017). In such a context there is a danger that the various disciplines focus on one aspect of reality per the disciplinary state of the art and the skills of the disciplinary researchers involved, instead of selecting the disciplinary variables and the various research questions in the function of the common transdisciplinary framework (Ostrom, 2007; Wuelser and Pohl, 2016). Therefore, the diferent conceptual choices by the project partners in constructing their research objects must be adjusted to bring them in line with a common object of inquiry. In the context of transdisciplinary research, the research co design must satisfy an additional requirement, as the co design must consider the research participation of societal actors. Indeed, the various aspects of the research co design must accord with the societal actor and scientifc researcher perspec tives on the identifcation of the socio ecological problem situation and their perspectives on sustainability values. Figure 3.3 illustrates the additional requirements. In summary, the key question scientifc researchers and societal actors must address for successful co design is to clarify and collectively decide how the various approaches to methodology, validity, research purpose, concep tual framing, and the identifcation of the most relevant research questions can be integrated into a common transdisciplinary framework. Failure to do 54 Actionable knowledge outputs through collaborative research co-design Conceptual framework Purposes Research co-design amongst social actors and researchers in transdisciplinary research Research questions Methods Grey: interdisciplinary framework Black : societal actors partnership Validity RESEARCHERS and SOCIETAL ACTOR perspectives on the sustainability value orientations of the socio-ecological transformations pathways Conceptual framework Purposes Research questions Methods FIGURE 3.3 Conceptual framework Purposes Research questions Validity Methods Validity Research co design between researchers and societal actors in trans disciplinary research so may still yield interesting knowledge on disjointed aspects of the over all socio ecological system dynamics, which might be of interest to individ ual disciplinary researchers or societal actors. However, such a disjointed approach is likely to be of poor use to understanding the dynamics of change in interdependent social and ecological systems in a socially relevant and legitimate manner. 3.1.1.2 Factoring in a broad variety of societal efects of transdisciplinary research The short review on collaboration mechanisms for usable knowledge pro duction on specifc socio ecological transformation pathways shows the importance of combining collaboration for knowledge integration, process co management, and research co design. To analyze their contribution to efective transdisciplinary research, the basic model used in this chapter con siders three main categories of knowledge outputs to analyze the contribu tion of the various mechanisms of collaboration. The frst category covers scientifc research outputs on socio ecological relationships, and the second, the dissemination through peer reviewed scientifc publications. The third category covers diferent usable knowledge outputs that can support deci sion making by societal actors, as illustrated in Figure 3.4. First, as in the case of interdisciplinary research on sustainability issues, the goal is to produce knowledge to better understand the world in a scientifcally Actionable knowledge outputs through collaborative research co-design 55 Explanatory variables Outcome variables 1. One of the following usable knowledge outputs Knowledge integration through information gathering and interactive communication Research co-management Research co-design Social learning on background values/representations Control variables • Types of societal actors involved • Types of disciplines • Thematic field of sustainability FIGURE 3.4 New solutions implemented Societal actors’ action plan at implementation stage Govt action plan at implementation stage New organisational mechanisms established (hierarchies/networks) 2. Published in peer reviewed journals 3. New knowledge on socio-ecological relations resulting from knowledge integration in the project Core variables of the comparative case study design of transdiscipli nary research projects. For details on the scales used for coding the variables, see Annex 3. reliable manner. Such usable knowledge can be produced through applied and basic research. As highlighted in the introduction, both applied and basic research practices are present in transdisciplinary research. Applied transdisciplinary research provides knowledge that contributes directly to improving the understanding of specifc problem situations. On the other hand, basic transdisciplinary research contributes by building more general knowledge on socio ecological dynamics, which may yield new approaches and problem solving in the long term (Rosenberg, 2010). In the case studies below, the contribution to such improved understanding from applied and basic research will be assessed through evidence of peer reviewed publications from the projects that address social and ecological system interdependencies. Second, to assess the contribution of the improved understanding to usa ble knowledge for decision making by societal actors, this chapter considers a broad variety of usable knowledge outputs. The analysis will evaluate the possible contribution to three distinct categories of usable knowledge out puts highlighted in a series of review papers on usable knowledge production in transdisciplinary research (Walter et al., 2007; Wiek et al., 2014; Mitchell et al., 2015; Schneider et al., 2019). These categories include contributions to (1) new knowledge for the implementation of solutions and improvement of the situation; (2) promoting knowledge integration among the actors by translating the research results in integrated strategy and planning docu ments, for both societal actors and policy makers; and (3) building new actor networks, leading to new organizational initiatives. An important feature of this basic model of usable knowledge outputs must be mentioned before proceeding. Following other authors, for the 56 Actionable knowledge outputs through collaborative research co-design consistency of the comparison among the projects, the analysis considers essentially so called frst order efects. Such frst order efects can be directly linked to the project activities, occur within the spatial scope of the project, and produce the efect within the immediate temporal context—that is, dur ing or shortly after the end of the project (Lux et al., 2019, p. 184). However, the projects also produce more difuse, so called second or third order social efects, which extend beyond the temporal and spatial scope of a given pro ject (ibid). However, the analysis of these latter efects falls outside the scope of the comparative project assessment. Nevertheless, one can reasonably pre sume that projects that show strong frst order efects on the direct produc tion of usable knowledge outputs also contribute to enhancing the likelihood of the production of second and third order efects. 3.1.2 A sample of in-depth case studies on transdisciplinary research processes To grasp the contribution of the various mechanisms of knowledge co production, this chapter presents a comparative assessment of a sample of well documented transdisciplinary research projects via a unique “most dif ferent” case study sampling process covering a broad variety of thematic areas of sustainability research. The initial cases in the sample were identifed through a keyword search on “transdisciplinarity and sustainability” and “participatory research and sustainability” in four scholarly journals. The purpose of the keyword search was to identify publications on case studies of research projects that were based on interdisciplinary sustainability analysis and involved research col laborations among scientifc researchers and societal actors. Based on an ini tial reading of the journal publications and the available project documents, a further selection was made to keep only projects that (1) were interdisci plinary across the natural and social or the natural and human sciences and (2) efectively integrated knowledge from societal actors on the sustainability transformations into the analysis. Only journal publications that provide an in depth analysis of the organizational features of the full research process in the journal publication (in addition to the presentation of the results) or in the supplementary material were selected. For the selected projects, all avail able project materials (other journal publications and web documents) were consulted to complete the analysis. In a second step, to cover a variety of diferent thematic approaches to sus tainability transformations, the sample considered cases that address fve dif ferent levers of change, ranging from technological and socioeconomic levers to policy and sociocultural change, as detailed below. Whenever the initial selection process did not yield a sufficient number of papers dealing with one of these levers (with a minimum of fve in each lever), the sample was completed Actionable knowledge outputs through collaborative research co-design 57 based on a general keyword search in a broader set of journals on that spe cifc lever of change combined with the keyword “transdisciplinary” in Google Scholar. Annex 2 lists the cases that resulted from the sampling process. As can be seen, the sampling process used a minimalistic characterization of transdisciplinary sustainability research based on the two core features of (1) interdisciplinary modeling of interdependent socio ecological systems and (2) integration of scientifc and practitioner knowledge in the research process. The sample from this process contained a sufficiently broad variety of failed and successful cases, with diferent degrees of success, in usable knowledge production to allow for a qualitative comparative analysis of the institutional design features for overcoming collective action failures (see, e.g., Rihoux and Ragin (2008) for an analysis of sample size for Medium N qualitative comparative analysis). Further, the sampling of a set of highly diverse cases from within the fve levers of change decreases the potential bias from an overly strong represen tation in the sample of a specifc methodological approach or thematic feld of society wide transformation. In particular, the sample covers a diversity of methodological approaches for integrated boundary crossing research that are mobilized to analyze the various levers of change, including technology living labs, multi criteria analysis, community based survey methods, and participatory qualitative research. The projects in the sample also covered a broad variety of thematic felds of sustainability transformations, including sustainable food and agriculture, sustainable mobility, energy, and housing. As noted, to analyze successful knowledge co production, the sample addresses cases from within fve clusters that focus on a specifc lever of sus tainability transformations in socio ecological systems. These clusters are based on the knowledge based sustainability transformations framework elaborated in the 2019 Global Sustainability Report (UN, 2019). According to this report, societal transformations can be accelerated through actions based on diferent levers, respectively: Biophysical levers 1 Fostering technological innovation from a socio technical systems perspective 2 Planning sustainable resource use in society wide sectors of activity (e.g., energy, mobility, and housing) Socioeconomic and policy levers 3 Designing socioeconomic regimes for sustainability transformations 4 Developing policy and governance for implementing new socioeconomic regimes 58 Actionable knowledge outputs through collaborative research co-design Sociocultural levers 5 Including the diversity of sociocultural perspectives in the sustainability transformation pathways The consideration of these diferent levers allows covering a broad diversity of knowledge integration challenges in the case study sample. For instance, the analysis of the frst lever requires combining technical knowledge with socioeconomic and sociocultural variables. Other cases, dealing with the ffth cluster, require combining knowledge of sociocultural practices with knowl edge of the broader socio ecological system wide changes and challenges that impact the transformation of these practices. The challenges encountered in organizing research co design can difer per lever of change. For instance, in transdisciplinary research on socio technical transitions, researchers may fnd it relatively easy to integrate general ethical perspectives as a constraint on the choices of future technological innovation pathways. Indeed, such considerations do not necessarily directly impact the technical component of the research design, as long as the envisioned innova tions stay within the set of socially acceptable ethical perspectives. However, addressing the change in habits and impacts on social meanings of each of the technological pathways is likely to require a more in depth reciprocal learn ing process between disciplines. In the latter case, the question of patterns of the use of technology in specifc sociocultural contexts and technical choices must be analyzed in close relation to each other. In other cases, the co design of the sociocultural dimensions of the socio ecological pathway may be the frst entry point for the research partners, while the integration of the techni cal or economic system dimensions requires stepping outside of the research partners’ comfort zone. Although most scholars recognize the importance of these fve levers of change in addressing major sustainability challenges, they often fail to organ ize efective co design processes with the various disciplines and societal actors involved. Therefore, the remainder of this chapter discusses the chal lenges of organizing a broad interdisciplinary approach to the analysis of levers, the benefts from research co design in the building of partnerships among researchers and societal actors, and organizing appropriate forms of co management for conducting such transdisciplinary partnership research. 3.1.3 Aggregate results from the in-depth case study analysis An elementary coding of the key explanatory and usable knowledge outcome variables (see Figure 3.4) of the case studies of the sample confrms, at an aggregative level, the overall importance of knowledge co production pro cesses. In particular, the analysis strongly supports the role of the two mech anisms of research co design and co management with the societal actors reviewed above. Actionable knowledge outputs through collaborative research co-design 59 Even though the authors of the publications on these case studies labeled the projects explicitly as transdisciplinary sustainability research or participa tory sustainability research, some projects in the sample are, in reality, at the level of a pure aggregation of diferent types of knowledge for academic sci entifc research purposes without signifcant knowledge co production with societal actors. Indeed, all the projects in the sample used contextual infor mation from societal actors and resulted in peer reviewed publications, but not all led to one or several co produced usable knowledge outputs related to common research questions among the partners on socio ecological trans formation dynamics. The analysis shows that, of the 44 transdisciplinary research projects, only 29 co produced at least one of the types of usable knowledge outputs on spe cifc socio ecological transformation pathways that resulted from the integra tion of knowledge from the scientifc researchers and societal actors. In this sub sample of 29 projects, all projects explicitly organized co construction activities of the research design with societal actors and a form of co man agement among researchers and societal actors in the knowledge produc tion process. Specifcally, the amount and strength of usable knowledge outputs increase with the strength of the knowledge co production features, as illustrated in Figure 3.5 (for an overview of the average results on the Strong collaborative and transformative • Very strong and comprehensive co-design • Very strong and multi-pronged co-management • Both Informal and explicitly organized social learning Strong collaborative • Strong co-design • Strong co-management • Informal and regular social learning Moderate collaborative • Moderate co-design • Moderate co-management • Moderate and sporadic social learning Consultative • Information from social actors • No co-design, no co-management • Informal and sporadic social learning • comprehensive usable knowledge outcomes • with clear context specific (local or global) implementation strategies at the end of the project and • evidence of broad acceptance by a large part of the intended user group/beneficiaries Science and societal actors co-production of credible and legitimate usable knowledge outcomes (short term/long term) • No or very few usable knowledge outcomes • reaching very few of the intended user group/beneficiaries FIGURE 3.5 Aggregate results of the coding of the case studies of transdiscipli nary sustainability research. Co produced knowledge outputs (right side of the fgure) resulting from increasing comprehensiveness of the science and societal actors partnership (left side of the fgure). The ladder schematically represents the increasing strength of the part nership, according to comparative case study analysis (for a detailed overview, see Annex 2). 60 Actionable knowledge outputs through collaborative research co-design importance of these features and the detailed coding scale used for the analy sis, see Annex 2). In practice of course, not all individual projects have the means to organize comprehensive research co design and/or social learning. Nevertheless, the analysis clearly indicates the beneft of doing so and the need to imagine diferent means to strengthen the knowledge co production features, including through the networking of diferent projects (sequen tially or in clusters) or through the integration of knowledge co production in training activities at institutions of higher education. Therefore, even if the analysis in this chapter is based on the comparison of individual pro ject outcomes, the fndings also show the need to explore the embedding of these projects in broader polycentric networks for transdisciplinary knowl edge co production. The latter will be further developed in the discussion on the building of integrated boundary crossing organizational networks in Chapter 5. The other 15 transdisciplinary research projects did not produce any of the usable knowledge outputs within the time frame of the project in direct relation to specifc socio ecological transformations in a signifcant manner. Some mention this explicitly as a failure or a challenge that remains to be addressed. All these projects produced peer reviewed scientifc publications from the partnership processes and mentioned the contextual information gathering with societal actors as an appropriate defnition of transdiscipli nary research. None of the projects in this sub sample of 15 mentions co construction of research design or co management as a governance feature of the partnership. A note of caution for the correct interpretation of these results needs to be mentioned, however. As we only selected projects in our case study sample that explicitly provide an in depth analysis of the knowledge co production process, and as we consulted a broad set of supplementary material for each of the cases, we assume that the omission of co management or research co design with societal actors is an indication that these features were absent or in any case considered not sufficiently signifcant in the overall process. In case of doubt on the completeness of the available information on these process features in the project publication and supplementary material, pro jects were excluded from our sample for the outset (cf. the explanation of the sampling process above). Nevertheless, in spite of the careful analysis of the provided documents on the process design and its evaluation, the results pre sented in this section should be considered as an average trend over the entire sample of 44 cases. This trend is clearly strongly signifcant but needs to be further substantiated through additional comparative analyses and in depth qualitative research on isolated cases. The presentation of in depth research on illustrative cases presented in the subsequent section aims to contribute to this deepening of the results. Actionable knowledge outputs through collaborative research co-design 61 Levels of comprehensiveness of science and social actors participation in transd. sust. research Strong collaborative and transformative • Very strong and comprehensive co-design • Very strong and multi-pronged co-management • Both Informal and explicitly organized social learning Strong collaborative • Strong co-design • Strong co-management • Informal and regular social learning Moderate collaborative • Moderate co-design • Moderate co-management • Moderate and sporadic social learning Multi-stakeholder user/beneficiary driven science, with active co-design, co-interventions and coresearch (ex. Community health case §3.2.4) Multi-stakeholder user/beneficary driven science, with active co-design and cointerventions (ex. Enkanini §3.2.5) Multi-stakeholder research alliance with active research co-design (ex. Street design §3.2.2; Climpol §3.2.3) Participatory action research: co-interventions with active research co-design (ex. Cahors § 3.2.1) Consultative • Information from social actors • No co-design, no co-management • Informal and sporadic social learning FIGURE 3.6 Examples of types of transdisciplinary research in the case study sam ple, with varying degrees of strength of co design, co management and social learning; case study names refer to the detailed case study sections in Annex 2. The next section will therefore further build on this elementary compar ative analysis to better understand the benefts of various components of knowledge co production in transdisciplinary research through a series of selected cases out of the sample of 29 transdisciplinary projects that pro duced efective, usable knowledge outputs. Obviously, the various trans disciplinary research projects are extremely diverse, as they cover diferent areas of sustainability transformations and involve highly diverse societal actors. Thus, as one can expect, there is no optimal design of the process for organizing knowledge co production with societal actors but rather a set of diverse types of approaches, as illustrated in the right column of Figure 3.6. Nevertheless, all successful projects in the sample show strong evidence of the explicit organization of research co management and research co design with the view to developing integrated interdisciplinary frameworks of socio ecological system dynamics that match legitimate and relevant societal value perspectives in the specifc feld of sustainability transformations. 3.2 Collaborative research co-design across technological, socioeconomic, and cultural levers of sustainability transformations The next sections illustrate cases of research co design across various levers of change to foster sustainability transformations, ranging from the analy sis of technological and biophysical levers of change to socioeconomic and 62 Actionable knowledge outputs through collaborative research co-design sociocultural levers. For each lever, scholars widely documented the failures of the mere aggregation of disciplinary approaches for understanding inter dependent social and ecological dynamics and proposed specifc methodolo gies for interdisciplinary analysis of sustainability transformation pathways. Therefore, each section frst presents a specifc methodology of interdiscipli nary analysis before discussing the various attempts in the selected cases for integrating knowledge co production processes with societal actors in this interdisciplinary approach. Moreover, to illustrate the role of co design in transdisciplinary research, each section addresses a diferent aspect of the co design framework devel oped based on the analysis of Maxwell and Loomis (2003) (see Figure 3.2). Specifcally, the selected case studies respectively show the role of co con struction of the following aspects of the research design: Co-designing “Validity of data collection and analysis” • Historic City Centre Living Lab case study: Co-design of data collection from various methodological perspectives to match available data sources on social possibilities to use bio based materials (in Section 3.2.1). Co-designing “Research purposes” • Future Streets case study: Co-design of the research purposes of dynamic systems modeling to match the research framework to diverse sociocul tural perspectives (in Section 3.2.2). Co-designing “Methods” • Sustainable Mobility case study: Co-design of a research method to match this method to the analysis of the feasible transformation options of the sustainable mobility strategy of a municipality (in Section 3.2.3). Co-designing “Research questions” • Environmental Health case study: Iterative co-design of research questions through diferent rounds of community surveying that reveal the case spe cifc social and ecological interdependencies (in Section 3.2.4). Co-designing “Conceptual frameworks” • Energy Poverty in Informal Urban Settlements: Co-design of a new con ceptual framework that better matches the key societal actors’ perspec tives on sustainable energy transformations (in Section 3.2.5). Actionable knowledge outputs through collaborative research co-design 63 Each of the case study sections is structured as follows. The section frst reca pitulates some of the key arguments for moving toward an interdisciplinary and social actor partnership based approach to the sustainability problems in the analysis of a given lever of change. In the second step, a case study illustrating a specifc aspect of research co design in that lever of change is presented. In the third step, other cases from the case study sample are pre sented to further illustrate the contribution of co design processes around the diferent sustainability value orientations of planetary resilience, environ mental justice, and environmental citizenship. 3.2.1 3.2.1.1 User and citizen co-design of technological levers of change From the laboratory to interdisciplinary socio-technical transformation research The frst lever of society wide sustainability transformations, also promi nently present in the popular media and policy debates on sustainability, is technological innovation and product development (UN, 2019). However, technological innovation on its own is neutral toward achieving sustaina bility objectives. On the one hand, well designed technologies can increase resource efficiency and contribute to transformation pathways for living within the boundaries of the planet. On the other hand, technological innova tion is a major driver of the development of ever new products for individual consumption, which might further add to the already existing dependency on the use of natural resource inputs, such as energy or non renewable materials in contemporary mass consumption societies. For instance, innovations in consumer products, such as digital platforms for car sharing, LED lighting systems, or less energy consuming water boil ers, have brought important cost benefts to consumers but without a proven shift in behavior toward overall less resource intensive consumption patterns (Ceschin and Gaziulusoy, 2016). In particular, researchers estimate that 78% of discarded products still function properly when replaced (Van Nes, 2003). The reasons include new trends in fashion, the desire for societal status, or changing user needs (Van Nes, 2003; Cooper, 2004, 2016). Moreover, for products that consume energy, user behavior mainly determines the level of energy consumption (Tang and Bhamra, 2009). Further, regarding industry led innovations, emission and waste reduction technologies in industrial pro duction processes, even when they ofer cost efective alternatives to current practice, often fail to engage the company shareholders or to mobilize the technical staf in developing new competences to implement the envisioned changes on a wider scale (Stindt et al., 2016). Therefore, the frst challenge for sustainability research focused on techno logical innovation and product development is to move from a disciplinary 64 Actionable knowledge outputs through collaborative research co-design product centered research approach to an interdisciplinary analysis of inter dependent technological and social dynamics. How can sustainable product or service innovations be developed that address environmental challenges and promote sustainable behavior by producing co benefts with social and economic sustainability dimensions? How can new technologies be developed for the factory foor while generating efective participation of all the relevant actors in the re organization of production and supply chains? Further, how can the broad range of concerned societal stakeholders be associated with the dissemination of technologies that promote environmental, social, and economic sustainability in an integrated manner? In response to these challenges, researchers in engineering and biophysical sciences and societal actors have developed a broad set of interdisciplinary methods for user centered research and technological innovation processes. Indeed, given the initial impetus in the 1990s by early initiatives, such as the living lab initiated at the Massachusetts Institute for Technology in the United States (ENoLL, 2019), researchers have developed user centered technologi cal innovation methods to orient these toward advancing social, environmen tal, and economic sustainability in an integrated socio technological systems approach. Labeled in the literature with diferent terms such as “sustainable living labs,” “design for sustainability,” or “product service system” innova tions, these approaches share a focus on involving users and other relevant actors along value chains in technological design and innovation processes (Ceschin and Gaziulusoy, 2016) The interdisciplinary challenge of the socio technological systems approach to address sustainability issues is to integrate product related improvements with other sustainability dimensions, such as through an analysis of behav ioral changes, psychological factors, business models, governance of innova tion, and inclusive economic development goals. Nevertheless, to produce usable knowledge in specifc transformation pathways, societal actors must be involved in this integrated and multi dimensional approach. Indeed, each research project must zoom in on a subset of these sustainability dimensions when building the research partnership. Per the most urgent challenges iden tifed, to promote desirable and feasible real world sustainability transfor mations, researchers and societal actors must prioritize certain scientifc and societal outcomes and organize the various phases of the knowledge co pro duction process accordingly. 3.2.1.2 A living lab for sustainable renovation in the historic city center of Cahors, France The research on energy refurbishment technologies in the historic city of Cahors in France aptly illustrates the contribution of co constructing research design in user centered research on technological innovation Actionable knowledge outputs through collaborative research co-design 65 (Cruchon, 2019). As in many other cities, the development in recent decades of suburban areas has led to the depopulation of the city center and a lack of investment in the refurbishment of historic dwellings (Claude et al., 2017). In response, to revitalize the city center, the municipality launched in 2015 a renovation program while promoting sustainable building techniques based on the sourcing of locally available bio based materials and the conservation of valuable historical heritage. Even though the project partners agreed on the general sustainability values that guided the project (around the use of bio based materials and preservation of historical heritage), they still faced the challenge of match ing the activities in the research project to real world social possibilities for transformation in the local building sector that refects these values. Indeed, in the broader context of the building sector, many refurbishment solutions are based on conventional solutions with mass produced non renewable materials proposed by the industrialized building sector (ibid). In this con text, a more systematic integration of artisan knowledge with expertise in the refurbishment of a historical building remains a considerable challenge to be addressed. Moreover, government programs for fnancial support of energy refurbishment are based on a theoretical diagnosis of energy performance, which is not well adapted to the situation of old buildings (ibid, p. 122). The standard governmental energy performance requirements can encourage renovators to favor solutions that contradict the preservation of the histori cal heritage, for instance, by changing windows and doors. Finally, despite being one of the green energies with high economic potential and the broad availability of these materials, the industry and market for bio based materi als remain poorly coordinated and lack overall recognition. Thus, to address these issues, the municipality and the researchers from the University of Toulouse established a living lab on new refurbishment technologies that are better adapted to the thermal renovation of old historic buildings while enhancing the skills of local craftsmen. This living lab imple mented a knowledge co production process by involving local artisans, end users, local authorities, and material producers in the design of an interactive process of data gathering combining refurbishment of buildings in real world test sites in Cahors, laboratory measurement, and socio historical analysis. In contrast with classical interdisciplinary and expert based approaches, par ticipants in the living lab could develop sustainable technologies in a real life context, where political, ecological, socioeconomic, and technological dimensions must be integrated. The overall research process included a frst phase of more conventional interdisciplinary framework building and a second transdisciplinary phase of knowledge co production and research co design. First, to involve the stake holders in the defnition of the research frame and the choice of the materials to be tested, the Cahors living lab organized a set of co creation workshops 66 Actionable knowledge outputs through collaborative research co-design during the 2017–2018 period in the context of the overall ENERPAT project (2018). They yielded an interdisciplinary framework that considered vari ous theoretical aspects to implement the bio based sustainable building path way. This specifc socio ecological pathway required considering multiple dimensions in the choice of the materials and energy, such as the moisture regulation efficiency of the bio based materials, the shape and orientation of the building on the test sites, the climate and geographical conditions of the region, and socioeconomic and cultural factors of historical building prac tices (Claude et al., 2017). Second, to match these choices to the real world possibilities for imple mentation in the specifc context of the Cahors living lab, the partners designed a process of data collection that integrated the various constraints of the test sites. Given the collaboration with local artisans and their empirical knowledge of vernacular techniques, the partners designed an iterative process of on site prototyping of bio based materials, laboratory measurements, and feld testing of using the materials in building renova tion. The archaeologist from the city council brought expert knowledge on the architectural and socioeconomic features of the historical building practices. Based on these combined inputs, various on site experiments were performed (e.g., moisture measurements and testing the sealing of the doors) by researchers and students to improve the proposed refurbishment solutions. The project resulted in some direct exploitable research results, such as the development of mixes of Earth and natural fber with the desired proper ties for use in historical buildings. These results were communicated through public events in 2018 and 2019 with various researchers and actors in the sustainable building sector. Beyond these events and the scientifc publica tions on the properties of bio based building materials, the project team also notes more indirect results that impact the social practices in the building sector. First, the project produced guidelines on various aspects of improv ing the energy efficiency of buildings in historic city centers. Second, for the federation of artisans and the local small building frms, the project allowed for upgrading the status and the recognition of their work. In particular, the project has shown that the artisans can contribute to solutions with many co benefts for the environment, the creation of new social bonds in old city centers, and the conservation of historic patrimony. 3.2.1.3 Co-designing socio-technical research for understanding real-world sustainability transformations The living lab approach in Cahors is part of the cases in the sub sample on the technological lever of change. Within this sub sample, other successful Actionable knowledge outputs through collaborative research co-design 67 cases also consider the need for co construction of various aspects of the research design with societal actors. A frst group of cases in this sub sample focuses—in line with the Cahors case—on sustainability values regarding planetary boundaries and responsi bility for living beings and ecosystems. These cases clearly show the limits of purely technical eco design to foster sustainability transformations (Tofolini et al., 2021). For instance, the twin research projects, Capfor (2011–2020) and SALSA (2013–2015) (Goutiers et al., 2016; Lacombe et al., 2017), by the French National Agricultural Research Institute clearly show the need for partnership research to consider societal actors’ perspectives on understand ing diferent pathways that integrate planetary boundaries in agro ecological innovations. The Capfor project started when a group of farmers aimed to limit the external inputs of feed for their livestock by promoting “on farm” fodder production on the surrounding grasslands while decreasing the use of fer tilizers on these grasslands. In this context, the farmers sought a seed mix that would be more productive, biodiverse (for pollination services), and include legumes, such as clover and alfalfa (for nitrogen fxation). Given the absence of a tradition of using complex mixed grasslands in France, they resorted to buying complex seed mixes from Switzerland, where research ers and farmers at Agroscope developed seed mixes through a user driven research platform with farm test felds. However, this initial attempt failed, as the seeds were not adapted to the specifcities of the local farming prac tices and the understanding of desirable sustainability transformations by the local farmers. A more integrated understanding that is more sensitive to the local con text of feasible and desirable socio technical innovations was needed to transition toward diverse grassland management. Hence, the twin projects Capfor and SALSA organized a set of workshops among researchers, farm ers, and local organizations to identify the key agronomic, environmen tal, economic, and social decision making criteria that should be used in designing and evaluating a transition to a diversifed grassland system. The project organized feld experiments with the farmers, which led to develop ing seed mixes adapted to the local context that better matched the desir able transformation pathways. For instance, the research team was able to broaden the set of sustainabil ity targets for sustainable grassland management. The resulting pathways did not only consider diversifed grassland systems with high biodiversity outcomes but also consider other pathways of grassland diversifcation with lower biodiversity outcomes, which provided an equally high level of fodder autonomy but higher perceived work satisfaction by the involved farmers. Another tangible output of this knowledge co production process 68 Actionable knowledge outputs through collaborative research co-design is the efective uptake of more sustainable grassland management by the farmers in the area, relative to a much lower uptake in other areas where no partnership research has been conducted (Ribeiro et al., 2017, p. 34; Apaba, 2014). Other cases in this sub sample on the technical lever of change focus on research co design between the researchers and societal actors to frame the environmental justice issues. Indeed, many socio technical innovations do not apply to all income groups or low income markets (Crul and Diehl, 2008, p. 129). In the latter contexts, researchers highlight the need to focus on specifc issues that are diferent from the high income markets, such as the desirability of the technical innovations by low income groups, capac ity building for efective use, and afordability (Gomez Castillo et al., 2012, p. 129; Ehrenfeld, 2008, p. 135). For instance, in Tanzania, a research project on the installation of local of grid photovoltaic solar cell systems induced a re framing of the problem issue to investigate from a purely technical one to a socioeconomic evalua tion of the adaptation of the photovoltaic system to the local energy needs. Through this project, the of grid solar system was combined with build ing a locally managed and owned biomass generator operating during peak electricity demand, using vegetable oil from local jatropha nuts (Chionidou, 2008). Similar initiatives of of grid or micro grid electricity provision have been promoted worldwide. However, as illustrated by many failures, to be successful, they should be designed around local needs and capacities instead of promoting specifc products or technologies (Wilson and Zarsky, 2009). Overall, as shown by various reviews of sustainable living labs (Ceschin and Gaziulusoy, 2016; McCrory et al., 2020), the researchers involved in co construction processes for socio technical research have gradually expanded their sustainability focus. The earlier approaches mainly dealt with environ mental aspects. Subsequently, social and economic sustainability aspects, such as labor conditions, integration of marginalized people, or inclusive governance of socio technical change, were increasingly integrated (Ceschin and Gaziulusoy, 2016, p. 145). What these evolutions show is that the development of transdisciplinary partnership research on the technical levers of change is not just based on a rejection of conventional scientifc methods. Rather, the evolution shows an integration of existing tools and methods in a new way of organizing the research process. Therefore, the failures of “ivory tower” science to ana lyze the role of technical levers of sustainability transformations should not induce a call for less science and less knowledge but more and better science by enhancing existing methods with new principles of knowledge co production. As illustrated by the cases, such co production involves knowledge integration among researchers and societal actors and research co design to consider the socially relevant and legitimate perspectives on sustainability values. Actionable knowledge outputs through collaborative research co-design 69 3.2.2 3.2.2.1 Participatory modeling of sustainable resource use in societywide sustainability transformations From optimization modeling to participatory modeling of socio-ecological system dynamics The second biophysical lever highlighted in the 2019 Report (UN, 2019) regards actions for improving the sustainable use of natural resources in society wide sustainability transformations (e.g., transformations in the mobility, energy, or housing sector). In this context, to produce biophysical analyses of resource use that also provide a match to knowledge on specifc socially desirable and feasible transformation pathways, researchers devel oped a broad range of participatory modeling approaches. This section dis cusses how knowledge co production can be successfully integrated into this brand of sustainability research. Since the publication in 1972 of the infuential computational models in the book The Limits to Growth by Dennis Meadows and her co authors at MIT, computational modeling of system dynamics has been improved and has become a key research tool for understanding the evolution of resource use in complex socio ecological systems (Meadows, 2009). Grounded in systems theory, system dynamics models typically analyze networks of cause–efect relations among the elements of a system and feedback loops that stabilize or amplify changes in the system through time. This simulation of system wide efects of networks of causal relations and feedback processes makes system dynamics modeling well suited to exploring emergent system level behavior of integrated socio ecological systems and assessing the implications of man agement or policy interventions in these systems (Schlüter et al., 2019). In practice however, the use of these models may yield fancy simulations and sophisticated results of resource use at the expense of a proper under standing of the value related perspectives of researchers and societal actors on the overall orientation of the system dynamics (Vennix, 1999). Indeed, researchers who produce computational models may have trouble organiz ing the active involvement of societal actors in the co design of the research framework, analysis, or interpretation of the results. In such circumstances, even though the models may formally consider technically feasible pathways for sustainable resource use in society wide transformations, they are likely to fail to match the socially legitimate and relevant perspectives of societal actors on real world transformation processes. Hence, to answer these concerns, participatory modeling aims to address a double challenge. First, it aims to combine the respective strengths of quantitative and qualitative dynamic modeling tools, as these approaches complement each other (Smetschka and Gaube, 2020). On the one hand, quantitative computational models used in socio ecological analyses provide 70 Actionable knowledge outputs through collaborative research co-design accurate measurable results on the general system level results that can be compared across cases. On the other hand, many of the core social sustaina bility concerns, such as strengthening social bonds or work life balance, can not be captured in quantitative measures and are better approached through qualitative research. Second, participatory modeling also actively involves societal actors in the research design. As will be shown through the below case studies in our sample, by co designing the quantitative and the qualita tive variables of the system models, participatory modeling allows for reach ing a better understanding of the real world outcomes of the action strategies envisioned by societal actors to tackle specifc sustainability issues. 3.2.2.2 Self-explaining people-friendly street design in Auckland, New Zealand The Future Streets project in Auckland, New Zealand, is a good illustration of the outcome of a series of transdisciplinary research projects based on par ticipatory systems dynamic modeling and community surveying. The project was headed by a multistakeholder consortium from the regional transporta tion planning authority (Auckland Transport), the New Zealand Transport Agency, local community leaders, various local transportation consultancies, and university researchers (Mackie et al., 2018). The Future Streets project was inspired by a previous pilot project on traffic calming in Point England, Auckland. The pilot project modifed local streets by making them more environmentally friendly, removing line marking, placing plants and artwork to slow motorists, and reinforcing a sense of place. Five years after this pilot project, the likelihood of accidents had more than halved, with more pedes trians and cyclists using local streets (ibid, 2018). The idea of broadening this pilot project to a set of social interventions for redesigning the streets in the Mãngere neighborhood in Auckland stems from several years of collaborative research. The Mãngere area has a large indigenous population. The area was selected because of the high number of fatal and serious car crashes in the neighborhood. The choice of the various priority interventions in the area was based on intensive community consul tation and insights from a series of projects that were conducted from 2014 to 2016. The main result from the research co design processes in the project was a broadening of the initial research purpose of the pilot project (initially mainly related to road safety) toward addressing biodiversity related and sociocul tural objectives in the street design proposals that were subsequently ana lyzed in the participatory modeling exercise. In particular, based on a vast number of community engagement meetings, the project identifed the main social well being factors highly valued by the community: environmental health, neighborhood connections, a sense of neighborhood safety, and ease Actionable knowledge outputs through collaborative research co-design 71 of access to employment, goods, and services (Macmillan and Mackie, 2016). Through this process, the researchers also engaged with cultural values that are important to the indigenous communities of the neighborhood. The lat ter led to road improvements that refect the identity of the Mãngere people. Some of these improvements are colored pathways that refer to shark oil traditionally used by Mãori (Kōkowhai—yellow), the use of endemic plant species to slow traffic, and signposts for wayfnding and culturally relevant landmarks (Mackie et al., 2018). For the initial participatory systems dynamics study in 2014, the research team created a stakeholder group of 16 people from public authorities, citi zens from various social groups, researchers, and representatives of indig enous communities from the Mãori and Pacifc people (Macmillan et al., 2014). The constitution of a representative, comprehensive stakeholder group, with connections to the local and regional policy was considered a key condition of a successful participatory modeling process. Among others, the creation of a comprehensive stakeholder group allowed for a continuous process of confdence building with societal actors. On this basis, the project team organized two rounds of dynamic system modeling. First, in 2014, the team developed a detailed quantitative model of the impacts of three diferent active mobility infrastructures on bicycle use, cyclist injuries, and air pollution (Macmillan et al., 2014). Second, in 2016, the team integrated this analysis into a broader dynamic system model that also considers the economic, environmental, and sociocultural drivers of sustainable mobility solutions. This model helped to build a common under standing of a multi dimensional approach to the proposed transformations (Macmillan et al., 2016, 2020). From a societal perspective, self explaining road design in the Mãngere area of Auckland is the most visible project outcome. This street design aims to calm traffic on local roads via self explanatory features that refect the sociocultural concerns of the research partners, particularly the local indig enous communities. Overall, through careful selection and ongoing collabo ration with the non academic project partners in a socially inclusive way, the project team could generate a high level of uptake of the research results by the local actors. 3.2.2.3 Co-designing participatory modeling frameworks for matching feasible and socially desirable transformation pathways Some additional cases for this second sub sample on biophysical levers of change in socio ecological systems allow for illustrating the importance of research co construction among scientifc researchers and societal actors. One project that ranked high in matching the research design with the diversity of the sustainability values of the key societal actors was the 72 Actionable knowledge outputs through collaborative research co-design NATCAP project in Belize, Central America. The NATCAP project provided data intensive modeling of ecosystem health and fsheries revenue in Belize, a coastal state in Central America (Verutes et al., 2017; Arkema et al., 2019). A six year collaboration (2010–2016) between the research consortium of NATCAP and the Coastal Zone Management Body allowed for building relationships, making scientifc advances, and strengthening local planning capacity. The latter was especially challenging, as it involved addressing the competition among societal actors for limited space, mainly for oil explora tion, aquaculture, fsheries, coastal real estate development, and conservation of unique mangrove ecosystems. Through joint data gathering among scientists and various Coastal Advisory Committees, the project could explore alternative strategies to over intensive coastal real estate development. These strategies focused on two sustainability transformation pathways considered desirable and feasi ble by the main societal actors. The frst pathway was protecting sensitive habitats in the unique mangrove ecosystem. The second pathway aimed at safeguarding the operations of the small scale coastal lobster fsheries, which is the economic activity in the area that is most compatible with the various sustainability values. In other projects in this sub sample, the research co design resulted in the revision of the overall strategies to be prioritized through the modeling exer cise. For instance, the TERIM project provided an agent based model that simulated the interactions of various stakeholders in the energy system in the Weiz Gleisdorf region in Austria (Binder et al., 2014). The discussion on the project design induced a strong shift in the understanding of action priorities by the multistakeholder steering board of the energy region Weiz Gleisdorf. Initially focused on reaching regional energy sufficiency through local bio mass, the research team gradually shifted the focus toward reducing energy demand through renovation as the main action priority. Moreover, within this new research purpose, the project gathered new evidence on the impor tance of social networking among house owners for motivating sustainable energy choices and fostering behavioral change, which was not foreseen in the initial research design. The sub sample of participatory biophysical modeling cases also highlights the role of research co design in considering environmental justice values. A potential beneft of research co design among societal actors and researchers on sustainability values is promoting equity in participation and empowering more marginal actors to bring their knowledge to the modeling process. For instance, the participatory design of a computational model for the sustain able management of a community forest in Larzac, Southern France, revealed the contribution of practices of woodcutting by small scale farmers, as it contributes to their economic subsistence and provides tangible biodiversity benefts. In the frst round of simulations, such practices were not included, Actionable knowledge outputs through collaborative research co-design 73 as they were considered contrary to science based rational forest manage ment by the regional forest administration (Simon and Etienne, 2010). In general, the various cases in this sub sample show that participatory systems dynamics modeling can create a better match of the modeling frame works with socially desirable and feasible transformation pathways. In prac tice, as the understanding of the appropriate action strategies may evolve with the intermediary results of the participatory modeling process, researchers must update and adjust the computational models in various rounds of model design. The frst phase, building the model, requires input from a broad range of people and an initial understanding of the main causal interactions in the socio ecological system. In the next phases, the computation of the model in a series of test runs allows for tackling the limitations and faws of the initial intuitive mental models of societal actors and researchers to capture the dynamics of complex systems (Videira et al., 2010). Therefore, research co design in the feld of participatory modeling shows the importance of the ongoing commitment of the researchers and societal actors throughout the process in a series of iterations between computational modeling and partici patory workshop discussions. 3.2.3 3.2.3.1 Multi-criteria assessment of socioeconomic levers of change From quantitative cost-beneft analysis to participatory multi-criteria assessment As can already be seen in the discussion of the biophysical levers of change, socioeconomic policies are key to the dissemination or upscaling of tech nical solutions for accelerating sustainability transformations. Therefore, developing an appropriate framework of socioeconomic policy planning and decision making is a key to achieving the social transformations necessary for implementing sustainable development goals. It is the third major lever of change in the 2019 Global Sustainability Report (UN, 2019). As shown by economics and sustainability science scholars, conventional quantitative cost beneft analysis fails to provide an adequate framework for analyzing multi dimensional economic policy and decision making (Scrieciu, 2007; Salas Molina, 2019). In the context of economic theorizing, the limits of quantitative approaches have been extensively documented in the literature on social cost beneft analysis (Nussbaum, 2000; Masur and Posner, 2011). Indeed, conventional cost beneft analysis adopts a quantitative approach to the economic and social dimensions, for example by calculating a monetary equivalent to assess societal values. At best, this approach can provide infor mation on the efficiency of a policy measure at a certain moment of time in a given context of consensual societal values (Masur and Posner, 2011). Nevertheless, the approach is less well equipped to account for the broad 74 Actionable knowledge outputs through collaborative research co-design scope of intangible social benefts that drive sustainability transformations, such as the building of more inclusive and just societies (ibid). In response to these well known failures of conventional cost beneft anal ysis to address broader social dimensions of sustainability transformations, scholars have developed a set of multi criteria decision support tools (Abaza and Baranzini, 2002). These tools consider quantitative and qualitative crite ria, and, through an interactive and structured knowledge gathering process on the criteria, organize a dialogue among researchers and societal actors on the value laden choices among the many social welfare and social well being outcome targets. This section draws upon the sub sample cases within the thriving research tradition of multi criteria assessment to illustrate the role of research co design processes in usable knowledge production on socioeco nomic levers of change in sustainability transformations. 3.2.3.2 Sustainable mobility in Potsdam, Germany The ClimPol research group at the Institute for Advanced Sustainability Studies in Potsdam, Germany, provides a good illustration of a highly suc cessful research partnership on socioeconomic mobility planning from an integrated sustainability perspective. The group developed a study in cooper ation with international research partners, the federal government, the state of Brandenburg, and local business and society partners. The team worked from 2015 to 2016 on a multi criteria assessment of policies to address wide spread air pollution in the Potsdam area, while recognizing the importance of the social dimension of mobility transitions beyond the more conventional technological and economic perspectives. Much research on transport and pollution is still conducted through expert led multi disciplinary science. As shown in a review of scholarly work by the ClimPol project team, most mobility decision support tools are based on researches that analyze the various aspects of mobility planning through sepa rate research frameworks, whether through models for analyzing traffic plan ning, air quality, or carbon emissions mitigation (von Schneidemesser et al., 2017, p. 3). For instance, time efficiency surveys in traffic planning focus on individual route planning, which places a heavy focus on time gains that can be made by various mobility choices, without considering measures to stop the circle of increasing travel speed, travel distances, and energy consumption (BFS and ARE, 2017; Hoppe and Michl, 2017). Other studies use cost beneft anal ysis to compare the costs of mobility choices with various benefts regarding the satisfaction of individual mobility needs and pollution impacts but without considering the broader benefts on urban welfare or quality of life, which can not be captured entirely in quantitative measures (Delhaye et al., 2017). Given this separate analysis of the various dimensions, the results fail to provide an integrated understanding of society wide mobility transformations. Actionable knowledge outputs through collaborative research co-design 75 Thus, to support multi dimensional decision making on mobility transi tions, the research group on mobility and climate developed a multi criteria assessment jointly with scientists, practitioners, and decision makers, between 2015 and 2017 (Schmale et al., 2015, 2016). This assessment included envi ronmental considerations and considerations for road safety, eco mobility, and quality of life. As stated by the project team, to successfully address complex urban trans portation challenges, it is necessary to adapt the multi criteria assessment methods to include available sources of knowledge on local and regional fea sible sustainability transformation options. Practical knowledge can be used to judge, for example, the feasibility of local travel options, while discus sions with societal actors can play a role in clarifying value choices regarding social equity in urban planning. On the other hand, scientifc knowledge can contribute to the various quantitative and qualitative assessments of environ mental, economic, and social impacts. In the frst phase, the project team gathered roughly 10 representatives from various departments of the municipality’s administration, one person from the state province, one from the ministry of environment, and two natu ral scientists. This working group framed collaboratively the main research questions and developed the multi criteria assessment process. The project worked with a list of socioeconomic policy measures in the municipalities’ planning stage. The measures were assessed by a set of criteria that considered impacts on six categories: air quality, climate change, noise emissions, road safety, eco mobility, and quality of life. The integrated par ticipatory assessment was applied in a one day workshop. Before the work shop, the team studied the indicators for assessing the various criteria and gathered the best available scientifc data on these indicators. At the work shop, breakout groups ranked the various measures. The resulting scores were statistically analyzed by the scientists and presented to the participants in the various working groups. Further discussions, adjustments, plausibil ity checks, and decisions on weighting the various criteria were conducted within the plenary workshop meetings. Initially, the city’s “urban and climate friendly mobility” initiative identi fed over 75 specifc measures in the planning or pre implementation stage in 2013. With so many measures, it was challenging to maintain an overview of the synergies, overlaps, or counter productivity of the measures and assess the priorities within the limited city’s budget. At the end of the project, the research team listed the measures of the ini tiative that were ranked as very high and high priority. The very high priority group included extensions of park and ride facilities (connecting to public transport and cycling walking paths), the overall enhancement of infrastruc ture for public transport and cycling, limiting parking spaces in the city to discourage driving, and creating a mobility agency. Most measures were 76 Actionable knowledge outputs through collaborative research co-design assessed based on the reference data and previous experience. Through the participatory process, expert input was combined with other considerations, such as the public acceptance of the new policies and contextual features related to the real world options for urban re design. Based on the project results, the municipality adjusted its planning to implement all the high and very high priority measures from the fnal project ranking. 3.2.3.3 Co-designing sustainability evaluation frameworks for participatory multi-criteria assessments In the ClimPol research project, the key focus is on the design of sustain able mobility that integrates social and environmental value concerns. In this case, most of the criteria related to desirable city development were assessed through qualitative scales, while the air pollution data was gathered through quantifed pollution measurements. The quantitative part of the multi criteria assessment is more prominent in its other applications. For instance, one case in the Transport Innovation Deployment for Europe (TIDE) Handbook on Impact Assessment addresses a multi criteria assessment of congestion charging measures, introduced in cities such as London, Stockholm, or Milan (TIDE, 2015, p. 35). In this multi criteria assessment, even many behavioral impacts, such as changes in travel time or the share of walking and cycling, could be quantifed, based on structured surveys on the impact of congestion charging measures introduced in various pilot cities. However, other research aspects, such as the equity of the scheme regarding the various population groups could not be quantifed, as they involved value related choices. Thus, even though the project was focused on the quantitative criteria, this key societal value required involving the societal actor partners in the design of the empirical methodology of the project, dealing with data collection on the social equity implications of the congestion charging measures. As shown in the various case studies presented in the TIDE handbook, by involving societal actors in co designing quantitative and qualitative data col lection methods, multi criteria assessment has evolved into a powerful tool for integrated sustainability assessment of the socioeconomic lever of change. Scholars developed improvements to make the weighting of the various crite ria more reliable. The direct weighting of the importance of the criteria, as in the ClimPol case, has the advantage of very low resource requirements and high transparency of the process. More resource intensive techniques intro duce pairwise comparisons of the criteria in the weighting procedure and sev eral techniques to check the consistency among the assessment scales, often using a software (for an overview, see, for instance, Németh et al., 2019). For complex assessment processes, some of the technical improvements will be useful. However, regardless of the choice among these techniques, Actionable knowledge outputs through collaborative research co-design 77 the participatory nature of the process remains an essential attribute and the improvements must be evaluated accordingly. Therefore, when co designing the research protocol, the research partners must carefully consider the bal ance between the increasing complexity of the computational algorithms that can be used with the transparency and the quality of the research co construction. 3.2.4 3.2.4.1 Multistakeholder policy implementation research From idealized sampling standards to real-world feld research on policy impacts Sustainability scholars highlight innovations in public sector governance toward increased stakeholder participation as an important fourth lever to address the current global ecological and social crisis (UN, 2019). This strengthening of multistakeholder governance aims to foster enhanced coop eration among a multitude of actors who drive sustainability transforma tions, often operating at diferent scales of governance. According to the outcomes of an international expert workshop on multistakeholder governance, held in Zürich in June 2017, the capacity of multistakeholder governance can be best enhanced by integrating the vari ous knowledge inputs at the various stages of the policy cycle. It can be achieved through a combination of strategies, such as considering system characteristics at the policy formulation stage, building confict resolution and leadership skills at the implementation stage, and fostering adaptive and generic learning at the evaluation stage of the policy cycle (Hitziger et al., 2019). Conventional disciplinary ivory tower science seems ill equipped to generate the knowledge base to support such highly inter active and evolving multistakeholder policy design and implementation processes. A stylized paradigmatic case of a classic disciplinary ivory tower science approach can illustrate the challenges of analyzing multistakeholder policy implementation processes in interdependent social and ecological systems. For instance, prominent research tools in the social sciences for obtaining data on the impacts of policy interventions, so called random controlled trials, have become popular to analyze the impact of policy interventions over the last decades (Banerjee and Dufo, 2011). In these methods, scientists randomly allocate individuals to several groups that are subject to diferent interventions and compare the measured responses. Copied on the model of laboratory science, these real world trials, while appropriate to analyze the efect of specifc measures on specifc groups, fail to capture the multiple interdependent socio ecological features and the heterogeneous perspectives of multiple societal actors in real world sustainability policies. 78 Actionable knowledge outputs through collaborative research co-design First, in random trials, to control for possible bias between diferent situ ations of various individuals, the number of individuals to include rapidly increases with the number of policy measures or variables to be included in the analysis (Black, 1996). Therefore, in practice, to keep the number of indi viduals to include in the study within reasonable limits, random controlled trials must focus on one or a few dimensions of the problem to be addressed. The case of the successful North Karelia health prevention research on cor onary heart diseases in the sub sample of cases is a good example of the importance of this methodological constraint. Indeed, in this case, a ran dom approach to sampling was abandoned in favor of a more feasible and robust multi dimensional case study approach to health surveying (Puska et al., 1983). Second, for rigorous control, the researchers must apply the interventions to a unique and complete group of people belonging to a given category (e.g., school students, members of associations, and inhabitants of a region) and in similar contexts (Melia, 2015). The latter is rarely the case in the implementation of policy measures for multi dimensional sustainability transformations. Finally, the method requires comparing the results with a control group that does not beneft from the envisioned policy interventions. Nevertheless, in some situations, isolating a control group that does not ben eft from proposed policy interventions is ethically inappropriate (Goodkind et al., 2011; cf. the Montréal case study in the sub sample) or unrealistic (Puska et al., 1983). In contrast to the laboratory like random controlled trials, to understand multistakeholder policy implementation processes, researchers must address the multiple dimensions of sustainability transformations in an integrated manner (Poteete et al., 2010). Typically, such integrated approaches will use tools that combine quantitative and qualitative feld surveying over multiple dimensions or rely on thick and contextual feldwork. Indeed, to analyze multistakeholder policies for sustainability, researchers must consider the impact of policy interventions on interdependent social and ecological system features, which cannot be separated from each other as in random controlled trials. Overall, to gather reliable scientifc data and information and support efective policy implementation of integrated sustainability transformations, researchers and societal actors must integrate knowledge on multiple system dimensions and from the perspective of a diversity of evolving societal actor perspectives 3.2.4.2 Community health surveying of asthma prevalence in New York A well documented case illustrating the failures of ivory tower, disciplinary research for data gathering on policy implementation in multistakeholder governance contexts is Jason Coburn’s study of environmental health in the Actionable knowledge outputs through collaborative research co-design 79 Williamsburg neighborhood of New York City, in southeast Manhattan (Corburn, 2005). The context of this study is the involvement of disenfran chised population groups in policies for addressing the increase of asthma prevalence in urban areas with high levels of pollution (Flies et al., 2019). Gathering data on asthma prevalence can be challenging, as patients do not systematically search for or have access to formal medical care, especially in low income urban neighborhoods. In this context, through improvements in mix methods research (i.e., combining conventional quan titative surveys and qualitative community led data collection and interven tion studies), public health researchers have identifed general trends in the evolution of asthma prevalence. They established correlations with envi ronmental factors such as exposure to major traffic and industry related pollutants (New York City Mayor’s Office, 2015, p. 190). Nevertheless, as shown in the Williamsburg neighborhood case, documented by Corburn, such general aggregated data must be refned with the knowledge of the specifc socio ecological path dependent evolutions in the problem feld if policymakers and societal actors want to understand the specifc causal pathways leading to high asthma incidence and formulate policies for the most impacted social groups. In 1992, a confict over the operation of an incinerator in the heavily industrialized Williamsburg neighborhood led to a highly contested neigh borhood health study. In this study, researchers from the City University of New York Medical School (CUNY CHASM), along with the New York City Department of Health (DOH), analyzed the statistics produced by the local neighborhood hospital (Kaminsky et al., 1993). Accordingly, the research team concluded that there may not be a major asthma problem in the neigh borhood. As noted by Corburn in his feldwork on the 1992 study, from the outset, the residents dismissed the methodology of the epidemiological study for using hospitalization data from a local hospital, which many residents from local communities rarely, if ever, visited, and for failing to disaggregate results by age, gender, ethnicity or type of daily activities (Corburn, 2005, p. 119). By ignoring crucial local knowledge, the CUNY CHASM/DOH study compiled poor scientifc evidence and, more importantly, failed to identify the appropriate research questions to understand the causes of the health con cerns in the community. In response to the community concerns, El Puente, a local community organization, together with Community Information and Epidemiological Technologies (CIET), a non proft research consultant spe cialized in community based survey tools, organized three community wide surveys between 1995 and 1999. Through these surveys, the researchers could show high asthma rates among sub groups of the community, most prominently among school children and women aged over 45, which previ ously did not appear in any statistics. Follow up focus groups could relate 80 Actionable knowledge outputs through collaborative research co-design this high prevalence to the women’s occupations in laundries, dry cleaners, beauty salons, or sweatshop like textile factories. As documented by Corburn, none of the major scientifc results of the study could have been obtained by a traditional top down, principal inves tigator led, epidemiological study into asthma prevalence and its environ mental causes. Two processes served the successful generation of reliable and usable knowledge: the organization of collaborations between researchers and societal actors in the production of various types of knowledge and the organization of efective research co design. First, the collaboration between researchers and societal actors at all stages of the project was crucial in reaching successful scientifc and societal out comes of the project. The main reason is that the research team, trained by El Puente and CIET, had to act as community health workers, not just survey administrators, to overcome distrust (Corburn, 2005, p. 127). Particularly, to organize the collaboration in data gathering, El Puente recruited 10 com munity members with a personal or family stake in asthma and trained them with the help of the New York City DOH and public health professionals from Hunter College at the City University of New York. Second, per Cecilia Iglesias Garden, one of the coordinators of the research team, to understand the specifc causal pathways leading to health concerns, health workers must speak credibly about more issues than just asthma and pollution. If the researchers could not address questions related to health and social issues other than asthma and pollution, the residents were not going to trust them or talk to them. Therefore, the survey team decided to focus the frst round of surveying on the multi dimensional social welfare and well being issues of the community. The results of the survey in the frst year were discussed with the com munity members, which led to the identifcation of topics for investigation for the next year of feldwork (Corburn, 2005, p. 121). Using this kind of iterative process, the information gathered during one phase provided the starting point for a critical dialogue on the analysis of the results, their local relevance, and the selection of follow up research questions. It led to three major surveys, conducted between 1995 and 1999. The frst focused on the general community problems related to environmental health issues and gen eral community concerns. The second targeted specifc categories of the pop ulation with identifed asthma problems, such as women and school children. The third helped improve the understanding of the efficacy of traditional remedies widely used in the immigrant communities of the neighborhood. The results of these studies were widely publicized and induced a series of peer reviewed publications in high profle medical journals (Ledogar et al., 1999, 2000). Beyond these scientifc results, the project induced vari ous health interventions that signifcantly advanced the situation of the population. For instance, after learning from the second round of surveying Actionable knowledge outputs through collaborative research co-design 81 that adults, particularly women, exposed to pollution in laundries and dry cleaning in the community also sufered from asthma, an asthma plan for adults was developed by the community organization. Another innovative community outcome was the initiation of a program addressed to profes sional healthcare providers to inform them about asthma home remedies and their cultural signifcance in immigrant communities. Further, beyond the community specifc initiatives, the research project also contributed to advancing the research tradition of community health surveys, adding to the body of the partnership methodologies in public health research worldwide. 3.2.4.3 Co-designing socio-ecological systems analysis in policy implementation research As shown in the case study of community health surveys documented by Corburn (2005), involving societal actors in research co design at various moments of the research process contributes to successful usable knowl edge production in multistakeholder governance contexts. In general, such transdisciplinary co design helps societal actors to address the integration challenge of the various knowledge types mobilized in multistakeholder gov ernance at various moments of the policy cycle (Hitziger et al., 2019). Another transdisciplinary research project on multistakeholder policy implementation cases that illustrates this challenge is the so called cascade model of ecosystem services (Spangenberg et al., 2014). Typically, as shown through a review of recently published studies, most research on ecosystem services starts with the identifcation of natural processes that support the production of various ecosystem services (Menzel and Teng, 2010). Only in a later phase are stakeholders included to discuss the recommendations from the analysis (see, e.g., Cowling et al., 2008). By separating the biophysi cal identifcation of ecosystem services from their social valuation by local stakeholders, researchers suggest that the ecosystem services can be defned without reference to ongoing societal debates on societal values in the specifc implementation context. However, to make ecosystem service research useful in highly diverse multistakeholder policy implementation contexts, the values and the needs of local users should guide the process from the beginning. Therefore, as illustrated by the cascade model developed by Spangenberg et al. (2014), users of the ecosystem should be engaged early in the design of the research process. In the cascade model, societal actors are directly involved in a sequence of research steps with the scientifc researchers in attributing the use value to various ecosystem functions, identifying real world ecosystem service potentials related to these use values, and analyzing how the potentials can be mobilized and appropriated via appropriate policy planning and implementation. 82 Actionable knowledge outputs through collaborative research co-design Similarly, regarding environmental justice concerns, multistakeholder policy implementation research should combine objective measurements of the distribution of outcomes for the various social groups with an improved understanding of how individuals perceive justice and injustice of distribu tional outcomes. For instance, in a research project on implementing pay ment schemes for ecosystem services, Adrian Martin and his team at Sussex University found that local respondents mostly preferred an egalitarian approach to distributing the payments (each household receiving the same amount). Such a contextual understanding is contrary to dominant utilitar ian ideas, which hold that payments according to the household’s contribu tion to the service provision would be fairer (Martin, 2017, p. 158). This context based analysis of local conceptions of justice is crucial to understand how social legitimacy can be built around the contextual implementation of general and more abstract principles of justice. The organization of broad stakeholder participation in defning the general framework for assessing various approaches to equity and justice can contribute to strengthening the social legitimacy of the envisioned policies for ecosystem service provision (ibid). As highlighted in the introduction to this section, multistakeholder gov ernance approaches raise a set of challenges that must be addressed for efec tive policymaking on multi sectoral and multi actor sustainability issues. These challenges are related to building capacities for knowledge integration among the involved actors. As illustrated through the case studies, trans disciplinary research approaches that actively organize research co design can contribute to building such knowledge integration capacity required for improved coordination and cooperation among various stakeholders. 3.2.5 3.2.5.1 Including the diversity of sociocultural perspectives on sustainability transformations From expert-driven qualitative data collection to community-based qualitative research The ffth lever of change identifed in the Global Sustainability report is the inclusion of the diversity of sociocultural perspectives on change (UN, 2019). Thus, to strengthen the science base to understand the sociocultural perspec tives on sustainability transformations, scientists mobilize the broad diver sity of qualitative sources at their disposal, ranging from direct statements contributed by the participants in workshops, textual sources in paper and online media, informal reports by civil society and policy organizations, and photo and video material (Singleton and Strait, 2005, ch. 11). Although this is sometimes less obvious, qualitative research is not auto matically based on knowledge co production processes nor easily integrated Actionable knowledge outputs through collaborative research co-design 83 within interdisciplinary research frameworks. A key undertaking in this con text for researchers is to integrate qualitative research methods with knowl edge co production processes on the various social and ecological dimensions of the ongoing sustainability transformations. To successfully use these methods in transdisciplinary sustainability research, qualitative research on sociocultural levers of change must consider how global and system wide social and ecological issues interact with the sociocultural dynamics. Indeed, through the multi level and multi sectoral nature of sustainability issues, such as climate change or the biodiversity extinction crisis, civil society and organ ized collectivities are increasingly confronted with evolutions in other sectors of activity that question their value perspectives and problem understand ings. Thus, the sociocultural perspectives of such actors are continuously questioned, applied, and evaluated from the perspective of multi sectoral and multi level system wide changes. Further, similar to the analysis of the other levers of change, to produce usable knowledge on the various sociocultural drivers and barriers, schol ars must integrate these conventional qualitative research methodologies in partnership research processes that contribute to a socially relevant and legitimate research framing of the sustainability issues. Indeed, qualitative research methods are also used in conventional expert led research processes without research co design (Willis, 2007). A quick “Google Scholar” search for publications that use methods such as focus groups or qualitative systems modeling shows that many non participatory uses and expert led uses of such tools have been developed. A prominent example of non participatory uses includes the so called focus groups used in marketing research (Belk, 2007). Group based assessment of new consumer products in focus groups is a pow erful method to uncover participants’ emotional and nonverbal reactions and observe group based imitation behavior. In such cases, the focus group is not used in the context of knowledge co production but as an improved data col lection method for the marketing researcher and a useful qualitative comple ment to statistical user surveys. 3.2.5.2 Energy poverty in the informal urban settlements of Enkanini, South Africa The case of qualitative research on energy poverty in an informal urban set tlement in South Africa aptly illustrates the role of research co design in qual itative research on sociocultural perspectives on change (Smit et al., 2018, 2019). In this case, a follow up research project of a successful public private partnership for small scale of grid solar energy provision led to deepen the engagement with the potential community of benefciaries. The initial framework of the of grid solar energy project focused on the lack of technical infrastructure as the key explanatory factor of energy 84 Actionable knowledge outputs through collaborative research co-design poverty. Through a process of co construction in a series of follow up research projects, this perspective was reframed in terms of a lack of involvement of all social groups in social innovations related to energy infrastructure, energy saving, and access to afordable technologies. These follow on projects lead to highlight the importance of strengthening community control and deci sion over energy choices (so called energy democracy) (Bloem et al., 2021). In particular, a set of participatory workshops with energy poor households showed the potential benefts for the community of a more meaningful and representative engagement of women in co designing socio technological innovations (Smit at al., 2018, 2019). The Enkanini informal settlement in South Africa is an illegal settlement at 30 km from Cape Town, established in 2006 on land owned by the municipal ity of Stellenbosch. By 2015, approximately 8,000 people lived in Enkanini in approximately 2,000 rudimentary shacks (Van Breda and Swilling, 2019). They provide labor to the neighboring cities, mainly in services and govern ment, such as cleaning and security work. Moreover, the inhabitants organ ize a small but vibrant informal economy ofering a range of products and services, such as the sale of food and beverages, hair and beauty salons, and childcare facilities (Smit et al., 2018). The crux of the Enkanini case is the lack of provision of basic infrastruc ture services to this informal settlement by the local government, mainly in the areas of electricity, water, and waste management (Van Breda and Swilling, 2019). The problems from this lack of services include high levels of vermin invasions (especially rats), indoor air pollution from paraffin and candle use, frequent fres and foods, and the associated increased health risks mentioned earlier. Since 2010, a group of Master students and researchers at the Centre for Sustainability Transitions of Stellenbosch University have partnered with inhabitants of the settlement to set up a series of research projects on improv ing basic services (Bloem et al., 2021). After two years of applied research in Enkanini, iShack (which stands for “improved shacks”), a social enter prise, was established. This initiative brought solar panels to 767 households between 2011 and 2016 and was widely advertised as a major solution to decentralized renewable energy provision in of grid settlements (Ambole et al., 2019). It beneftted from a two year funding for a pilot project by the Bill and Melinda Gates Foundation and was subsequently supported by a zero interest loan of the Development Bank of Southern Africa and a subsidy from the municipality of Stellenbosch. In spite of the success of this social enterprise, major challenges for addressing the energy poverty in the community remain. Indeed, the focus on a single technological solution has failed to generate a broader uptake by the community. Only 27% of the dwellings stepped into the solar panel scheme, and most inhabitants who took part in the scheme continued to rely Actionable knowledge outputs through collaborative research co-design 85 on gas or kerosene (so called paraffin) for their main energy needs. Second, by providing support to this initiative through a basic electricity subsidy for solar energy, the municipality has awakened fears in the population that this support would be used to postpone a more structural solution to the needs of developing basic infrastructure services in the informal settlement. Hence, to better understand these issues, researchers conducted a series of follow up research projects, which illustrate the use of research co design with societal actors in qualitative research methods. These projects aimed at better understanding the local energy system in the Enkanini settlement, from the point of view of the various social groups. The following projects highlighted, in particular, the potential benefts of a more meaningful repre sentation of women in local social innovation: the participatory integrated assessment project (PARTICIPIA, 2013–2016); the qualitative systems dynamic mapping project, funded by the Southern African Systems Analysis Centre (2016–2018); and the project on Co Designing Energy Communities with Energy Poor Women (funded by “Leading Integrated Research for Agenda 2030” from 2017 to 2019) (Smit et al., 2018, 2019). In the frst project, PARTICIPIA, researchers organized a three day work shop together with the community members to collaboratively design a framework for analyzing the possible pathways to address the energy pov erty situation. These workshops involved the main energy user groups: solar users, users with contracts for indirect access to the grid of the neighbor ing township, and users of traditional of grid sources of gas and kerosene. The main shift in the design of the conceptual framework realized by the mutual learning in this initial workshop was a shift from a focus on techni cal solutions for energy provision to a recognition of the sociocultural and aspirational factors that drive the energy behavior of these various groups of inhabitants. For instance, women are searching for solutions that are afordable and less time consuming regarding access to fuel sources for livelihood activities such as cooking to free time for income generating activities. Other inhab itants sought alternatives to kerosene (paraffin), as it “smokes and burns the eyes” (Smit et al., 2019, table 3). Thus, despite divergent opinions on the (dis)advantages of the solar solution, the participants converged on the importance of a deeper engagement of the population in social innovations around energy use and the strengthening of the community organization to involve all members in these social innovations. These insights were further deepened in the subsequent research projects. A qualitative systems design mapping (Hovmand, 2014) helped identify a set of interrelated feedback loops in the local energy system between energy sav ing behavior, access to technologies, and infrastructure improvements, which indicate possible pathways for improving upon the current situation (Batinge et al., 2021). These pathways integrate the idea of a deeper engagement of the 86 Actionable knowledge outputs through collaborative research co-design main users of the energy solutions in innovation, such as via the involvement of women in community co design of appliances for cooking and refrigerat ing that generate energy savings and address their main livelihood concerns. Combined with governmental support for making the solutions accessible to the largest number, a dynamic of change can be initiated. The results of the initial participatory assessment of the problem dimen sions and the qualitative systems dynamic mapping project led to a series of peer reviewed publications (Smit et al., 2018, 2019). Moreover, the research results were used in various strands of follow up research on the implementa tion of the envisioned organizational changes. From a political perspective, the results of the research project were used in the organization of a pol icy seminar in 2017 in the context of the project on “Co Designing Energy Communities with Energy Poor Women.” In this policy seminar, policymak ers from diferent levels of government, community members, and research ers discussed the various relations between energy, health, and gender that were highlighted in the research project. One institutional proposition that resulted from the seminar is to organize increased multi level coordi nation between the regional government (Western Cape government) and the Stellenbosch municipality to address the identifed livelihood challenges (Ambole et al., 2019). 3.2.5.3 Co-designing socio-ecological systems analysis in community-based qualitative research Many of the case studies in the sub sample on understanding sociocultural dynamics explicitly address environmental justice issues. Indeed, qualitative research, combined with research co design of common relevant and legiti mate research questions, ofers some key ingredients that are conducive to promoting the efective participation of disenfranchised social groups in sus tainability research. Another example in this sub sample that addresses environmental justice issues is the research project on food assistance and food waste in the Brussels Region, Belgium. This project was conducted from October 2018 to March 2019 by ATD Quart Monde, the Federation of social services of the Brussels Region, and an interdisciplinary research team at the University UCLouvain and the University of Antwerp. The proposed protocol for organizing quali tative research on food assistance for people living in poverty was based on the method of “merging of knowledge” developed in various research programs co conducted by ATD Quart Monde (Ferrand, 1999; ATD Quart Monde, 2016; Godinot and Walker, 2020; Osinski, 2020). In this protocol, persons living in poverty are directly involved as situation experts on equal footing with co researchers from social assistance services and university researchers (Joos Malfait et al., 2019). Actionable knowledge outputs through collaborative research co-design 87 Further, to co design the research framework, the project frst organized a workshop to co construct the main research question. The discussion in this workshop led to re framing the initial focus of the project, which initially focused on new urban food sharing initiatives and their potential to con tribute to food assistance. However, food donation often fails to address the basic aspirations for social inclusion and improved livelihood opportunities for persons living in poverty (ibid). In particular, this frst co design work shop showed that the free provision of food cannot be separated from the creation of spaces where persons living in poverty can access resources that can contribute to lifting them out of poverty. Accordingly, the research pur pose was reframed in terms of the question of the contribution of diferent solutions of food assistance to enhanced dignity of the urban poor and access to new opportunities to lift them out of poverty. The ATD Quart Monde project on food assistance and food waste sub sequently organized four successive workshops and a collaborative process of writing the project report with the persons living in poverty and local social welfare workers (ibid). One main result of this group based qualita tive research is that an excessively strong conditionality in food aid delivery creates competition for satisfying the eligibility conditions among groups of people in poverty, which goes against the community spirit of solidarity and mutual support that otherwise prevails. Further, the research shows that, even though an increase in the diversity of food items is a real concern, the most important demands are related to the defense of their broader socioeconomic rights to work, housing, education, and culture. Finally, participants in the workshops identifed alternative channels for distribution, such as neighbor hood restaurants and social groceries, as places with a more humane way of food distribution and ofering protective spaces for discussing opportunities for multi dimensional learning and capacity building. Other examples in the sub sample illustrate the contribution of the knowl edge co production process in qualitative research to identifying sociocultural perspectives that drive citizen engagements in sustainability transformation processes. For instance, the methodology of future visioning workshops, developed in particular by the scholars of the Dutch Research Institute for Transition, is a well known research tool for organizing group based quali tative research on the involvement of citizens and so called change agents in disruptive innovations for sustainability (Loorbach and Rotmans, 2010). The method of future visioning aims to elaborate new perspectives on sus tainability transformations that are disruptive of the existing status quo by combining the exploration of desirable futures and the analysis of social pos sibilities of change. In the frst step, the research partners organize a work shop on the visioning of a desirable long term future. This visioning process is informed by existing system diagnosis and analysis and a discussion on legitimate sustainability orientations. The key point of this workshop for 88 Actionable knowledge outputs through collaborative research co-design future visioning is that, by referring to the long term desirable future, the group identifes research perspectives that go beyond business as usual and are not constrained by vested interests (Roorda et al., 2014, p. 10, p. 30). Next, starting from this common strategic vision, the research team organ izes a group based qualitative research process for identifying solutions, innovation pathways, and societal change agents that contribute to disrup tive transformations. One tool often used in this context is “backcasting,” which is an iterative method that takes the desired future as a starting point (e.g., 50 years from now) and proceeds step by step back in time, identifying at each time interval the incremental innovation needed to foster progress toward the desired end goal. One case of this sub sample of qualitative research projects on sociocul tural levers applied a future visioning method, which is the MUSIC project (Mitigation in Urban Context, Solutions for Innovative Cities, 2010–2015). In this project, city officers, together with local stakeholders, organized visioning workshops on climate change mitigation initiatives in six difer ent cities to identify innovations and mobilize change agents for disruptive transformation (Tillie et al., 2012). In the city of Ghent, the backcasting exer cise led to embedding radical innovations such as neighborhood initiatives for temporary car free streets into a larger narrative of Ghent as a climate neutral city. Since this frst qualitative research project, the social movement has spread to other neighborhoods, and the creation of temporary “living streets” has now been recognized as a legitimate tool within sustainability mobility policies in the city. The examples of transdisciplinary research projects from the sub sample of research on sociocultural levers of change illustrate the need to integrate dis cussions on broader system wide transformations in the research co design of qualitative approaches to sociocultural perspectives. This research co design is conducive to better understanding the impact of system constraints on the evolution of sociocultural perspectives on change and enhancing the capacities of societal actors to address multi scale social justice issues and build more com prehensive visions for supporting multi scale civic activism. Further, from the Enkanini energy poverty and the ATD Food Assistance case, partnership based research approaches to qualitative research efectively empower disenfranchised social groups to actively participate in knowledge co production. The latter top ics, which concern the broader issues of capacity building for knowledge co production, will be further developed in Chapters 4 and 5. 3.3 A pragmatist constructivist approach to knowledge co-production Research partners embarking upon usable knowledge production on sustain ability transformations must mobilize diferent types of knowledge to cover the Actionable knowledge outputs through collaborative research co-design 89 coordination needs arising in the management of coupled social and ecological systems. Indeed, the interdependent dynamics often cross diferent societal sec tors of activities and involve very heterogeneous societal actors. Therefore, these research endeavors are inherently collaborative and pluralist, as highlighted in the review paper on knowledge co production in sustainability research by Norström et al. (2020), discussed in the introduction to this chapter. At frst glance, specialized multi disciplinary approaches seem to ade quately address the needs for organizing such research on sustainability trans formations involving heterogeneous types of knowledge and values. Indeed, multi disciplinary collaborations can mobilize diferent types of specialized expertise to understand the various social and natural system dimensions. However, such multi disciplinary and multi method approaches, as shown through the analysis of the case studies, are likely to be insufficient for, at least, two reasons. First, the mere juxtaposition of specialized disciplinary analysis of social and ecological system dimensions does not allow for cap turing the case specifc systemic interaction processes among the dimensions. The latter requires identifying the interactions at the overall system level and focusing on a subset of desirable and feasible transformation pathways within the space of possible interaction dynamics, and accordingly adjust ing the research design in each of the mobilized disciplines in a coordinated manner. Second, the diferent value laden perspectives are not just diferent ways of evaluating independently existing social and ecological interaction dynam ics. Rather, the researchers and societal actors are active participants in the debate over sustainability values, and how they frame the socio ecological system dynamics is already a result of their prior value laden perspectives on the unsustainable problem situation. For instance, to conduct a survey or other forms of feld research or iden tify key actors and societal values reliably, the project partners require a research framework. Regarding interdependent social and ecological sys tems, such a research framework will have a diferent focus per the specifc pathways that the research team decides to analyze. The latter choice already involves prior decisions on how to characterize the initial problem situation and how to evaluate the sustainability values that defne the overall orienta tion of the societal transformations analyzed in the research. Transdisciplinary research aims to address this double need for analyz ing specifc socio ecological interdependencies and understanding the value laden orientations through knowledge co production between scientifc researchers and societal actors. As discussed, this knowledge co production involves knowledge integration and co management of the research process and the co design of the various aspects of the research framework. The lat ter includes identifying socially relevant research questions, the conceptual framework, the legitimate purposes, and the research methodology. 90 Actionable knowledge outputs through collaborative research co-design This approach, which recognizes the pragmatic need for collaboration among many perspectives and the co construction of a common framework for collaborative research, has been characterized in the literature as an exam ple of a pragmatist constructivist position to the learning of common frame works for collaboration (Reich, 2009; Klein, 2018, p. 14; Boix Mansilla, 2017). From the pragmatist constructivist view, collaborative learning does not yield a unifed fnal framework, such as in some theoretical approaches to interdisciplinary research that foster methodological unifcation and the building of new common conceptual categories (Klein, 2010). Rather, the result is an inherently pluralistic framework, hence respecting the various heterogeneous disciplinary research styles and non academic approaches to knowledge. Further, the adopted framework is characterized as purposeful and accepted by the partners regarding the purpose of a given inquiry into unsustainable problem situations while remaining provisional (i.e., open for further adjustment based on subsequent learning on the systems features and the sustainability values). In her literature review on learning from a perspective of philosophi cal pragmatism, Boix Mansilla characterizes the validity of this pluralistic, purposeful, and provisional framework as one of “refective equilibrium” between prior perspectives of the partners and new insights gained through social deliberation processes (Boix Mansilla, 2017). Other prominent schol ars of philosophical pragmatism characterize the validity of these provisional frameworks as based on the convergence of the perspectives to a position that “cannot be improved under present circumstances” (see, e.g., Misak, 2000, p. 95). In this perspective, both scientifc knowledge and knowledge from societal actors infuence the purposeful learning of common perspectives that do jus tice to the diversity of perspectives on sustainability transformations. Indeed, pragmatist constructivism does not require a prior privileged perspective, whether being a priority given to the perspective of the scientifc research ers or societal actors. Therefore, various types of knowledge contribute to improving the purposeful and provisional common framework, whether it is scientifc knowledge on the social and natural system features, laypersons’ experiential knowledge on case specifc dynamics, or the deliberation on value perspectives. The over three decades of research on collaborative planning by Judith Innes and David Booher allows for illustrating the role of the various types of knowledge inputs in the pragmatist constructivist perspective. In their review of 30 years of experience with research for collaborative planning, Judith Innes and David Booher (2010) indicate at least three reasons that knowledge co production between researchers and societal actors is needed to understand sustainability transformations. Actionable knowledge outputs through collaborative research co-design 91 First, understanding ongoing system wide transformations in specifc problem felds requires gathering lay knowledge from involved actors to understand the unique characteristics of the interactions in the socio ecolog ical systems. As elaborated by Innes and Booher, the latter is grounded in a combination of “frst hand experience, conversations with those with direct knowledge, conversations that help individuals to make sense of what is hap pening, and logic based on familiarity with comparable situations” (Innes and Booher, 2010, p. 171). Thus, to access this experiential knowledge, quantitative surveying must be combined with qualitative research methods that are better equipped to address thick case specifc knowledge and with informal exchanges to access difficult to codify information on the system. One example discussed by Innes and Booher aptly illustrates the contri bution of such integration of experiential knowledge (ibid, pp. 176–177). After the nuclear catastrophe of Chernobyl in 1986, researchers working in the United Kingdom initially failed to anticipate the long term impact of the radioactive fallout on lambs. They could only map the full extent of the nuclear radiation fallout by integrating the knowledge of local sheep farm ers. The farmers’ knowledge of the local soils was essential to understand ing the dissemination of the radioactive cesium particles in the environment. Similarly, as discussed in the case study on pollution related asthma in New York City, researchers initially missed important context specifc local knowl edge. In both cases, researchers only reached an integrated understanding of the socio ecological interactions by combining scientifc analysis with par ticipatory observation and informal exchange on experience based insights of local societal actors. The second reason highlighted by Innes and Booher on why knowl edge co production is important is the need for learning on the plurality of value related perspectives on interdependent socio ecological systems. Innes and Booher provide a telling illustration of the failure to integrate difer ent perspectives on desirable and feasible socio ecological pathways through the case of research projects on Potato Farming in the Peruvian Andes. By neglecting the contributions of indigenous knowledge systems and institu tions for seed exchange and improvement, major studies failed to understand how the knowledge from traditional innovation systems is a major resource to build upon to overcome the current deadlocks of the high input industrial farming system (ibid, p. 178). The third reason knowledge co production is important, according to Innes and Booher, directly touches on the issues of environmental justice and the recognition of marginalized voices (ibid, p. 170). In practice, this third reason often overlaps with the frst two arguments around knowledge co production: the integration of experiential knowledge and the integration of the plurality of value related perspectives on interdependent socio ecological 92 Actionable knowledge outputs through collaborative research co-design systems. In some cases, diferences in power between societal actors or soci etal actors and researchers lead to overshadowing the voices of social groups that are part of the research project. In other cases, researchers must factor in the possible social or political consequences of the sharing of experiential knowledge for the individuals afected by social transformation processes. In these circumstances, to consider such marginalized knowledge perspectives, Innes and Booher suggest that researchers mobilize less intrusive methods of information gathering and “be proactive in encouraging and assisting those marginalized populations to participate meaningfully and to recognize that their local knowledge is useful” (ibid, p. 170). The analysis by Innes and Booher of the various reasons for knowledge co production with societal actors resonates with the broader pragmatist constructivist perspective. Indeed, pragmatist constructivism underlines not only the importance of knowledge co production but also the importance of referring to the practical context of ongoing societal transformations to cre ate transversality and dialogue among project partners with heterogeneous disciplinary perspectives and diverging societal value orientations (cf. also Hirsch Hadorn, 2004). Thus, both analyses call for a crucial complement of abstract scientifc knowledge with knowledge coming from practice. In short, pragmatist constructivism underlines the important role of soci etal actors and researchers as active agents of transformations, who bring specifc views to the research partnership on the most relevant problems and the desirable sustainability orientations. As active agents, societal actors and researchers introduce a pluralist and open ended perspective on the sustain ability transformation pathways, which directly afects the enterprise of sus tainability science (Klenk and Meehan, 2015). Therefore, to design adequate scientifc frameworks for analyzing real world socio ecological dynamics, research partners should mutually learn the various legitimate and relevant perspectives on specifc transformation pathways. 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(2019), even though social learning also plays a role in the frst research style focused on usable knowledge pro duction, there is a key diference with the research projects that specifcally identify social learning as the key goal of the research partnership. In this second research style, the learning is not only oriented toward matching pre existing societal values that drive specifc sustainability transformation pro cesses in the given problem context through collaborative co design. Rather, societal values emerge from the interactions among the researchers and soci etal actors who collaborate in the various stages of the research process. A good illustration of this second research style is the agent based par ticipatory modeling of an irrigation system with local farmers in Thailand (Barnaud et al., 2008, 2010). The main purpose of the transdisciplinary research project was to improve the mutual understanding among the par ticipants of their value laden perceptions of a problem situation. In this case, a proposed sustainability improvement method based on the introduction of erosion resistant perennial crops exacerbated social tensions around equita ble access to agricultural water, as these crops require intense irrigation. To address this situation of high distrust among the farmers, the objective of the participatory modeling was to “facilitate communication and coordination among stakeholders across institutional levels while taking into account the diversity of interests at the grassroots level” (Barnaud et al., 2008, p. 562). To this purpose, the researchers organized a set of role playing games in various villages that allowed to visualize and discuss the socio ecological relation ships highlighted by the simulation model. This role playing game facilitated DOI: 10.4324/9781032624297 5 This chapter has been made available under a CC BY NC ND 4.0 international license. Social learning among actors on societal values 101 a “diferent form of communication, which allowed less powerful villagers to raise their problem and to create a collective awareness of its existence” (Barnaud et al., 2010, p. 66). Therefore, in the context of this second style of transdisciplinary research, social learning is not a product that can be separated from the social context of interactions among the research partners, as was the case with the analy sis of usable knowledge products. Rather, social learning aims to address failures in mutual understanding among the project partners and create the conditions for productive collaboration (Schneider et al., 2019). The latter also accords with the general scholarly literature on social learning. As stated, for instance, by Mark Reed and his colleagues in a review paper on this literature, social learning is a process that is defned by improved understanding and the embedding of this new understanding in social networks (Reed et al., 2010). According to their review, social learning can be defned through a combination of three process features: a process (1) leading to a change in understanding; (2) resulting from the exchange of ideas, arguments, and information; and (3) going beyond the individual and becoming situated in wider social units and communities of practice. The analysis in this chapter is based on the sub set of cases in our overall sample, where social learning on sustainability values plays an important role (see a detailed list in Annex 2). The selected cases explicitly reported failures to collaborate given a lack of structuring of the diversity of societal value perspectives among the project partners and the lack of organized processes to overcome these failures. To analyze these cases, this chapter adopts a rep resentative case study approach based on a clustering of the cases in difer ent types of social learning processes. Indeed, instead of focusing on generic features of social learning on sustainability values across all the cases, which is unlikely to do justice to the diferent social learning needs in the difer ent projects, it seems more relevant to cluster the cases according to distinct learning needs and types of structuring of societal value perspectives among the project partners. Further, to investigate the observed types of social learning in the case study sample, the chapter proceeds in two steps. First, the chapter reviews the key theoretical insights from deliberative approaches to social learning in complex social choice situations. These deliberative approaches are intro duced through the work of Bryan Norton on environmental confict man agement. Second, the various forms of social learning are further analyzed through the deliberative approach to social choice in the framework of analy sis elaborated by Amartya Sen. The choice of this latter framework is based on the similarities between Amartya Sens’ diagnosis of social choice prob lems and the social learning challenges in transdisciplinary research. In both cases, societal actors are confronted with the need to structure the diversity of societal value perspectives to improve collaboration among actors with 102 Social learning among actors on societal values mutually incompatible value rankings. Based on these similarities, the types of social learning elaborated in the deliberative approach to social choice by Sen will be briefy reviewed and subsequently adapted to better match the type of coordination failures observed in our case study sample of transdis ciplinary research. 4.1 Building common perspectives for research collaboration in highly diverse societal value settings A key insight from the research on social learning in transdisciplinary sus tainability research is that working with a diversity of societal values is not necessarily an obstacle to successful collaboration among project partners (Pohl and Hirsch Hadorn, 2007). Nevertheless, comparative analysis of social learning in transdisciplinary research projects shows that coordination among the project partners is greatly facilitated by some level of agreement on a part of these societal values, without necessarily striving for a consensus over the entire value set (Herrero et al., 2019). Therefore, the focus on social learning in transdisciplinary research aims to strengthen such agreements in a collective and adaptive search for appropriate partnership composition and areas of convergence among project participants. As highlighted, the need for such deeper agreements on some sustainabil ity values depends on the sustainability issues at hand and the type of actors involved in the partnerships. Given this diversity of situations, no standard of convergence can ft all situations beyond a diversity of degrees of conver gence per project needs. This section aims to introduce the discussion on the diversity of such agreements in the context of sustainability research to build a typology that can guide further case study analyses. The lively debates in environmental philosophy on the balancing of mul tiple legitimate sustainability goals is a good starting point to introduce this discussion. For instance, Bryan Norton, in his reference work on the philoso phy of adaptive ecosystem management (Norton, 2005) develops a vision of environmental management as a process of evaluating multiple goals, which remains open for revision given further evidence. Precisely, this process of evaluation is an iterative process. Adaptive ecosystem management is based on evaluating various arguments for combining ecological and social system values, and, subsequently, on a further refnement of these values, reviewing the evidence of various impacts of decisions made based on these arguments. The starting point of the analysis of Norton is his personal experience with failures in the management of public programs of wetland management at the US Environmental Protection Agency in the early 1970s. As stated by Norton, given the functional specialization of the departments in the Agency, only ecologists sat on the committee for the wetland policy (ibid, p. 35). Therefore, the committee had no defnition of a wetland that included Social learning among actors on societal values 103 considerations of economic value or sociocultural values associated with the wetlands for the surrounding population. According to Norton, conse quently, the management models used by the Agency failed to develop mod els that are useful in complex public decisions, which include considerations of ecology, economic opportunities, and social acceptance of environmental regulations. Moreover, to contrast this technocratic approach with an adaptive approach to wetland management, Norton cites the case of a successful social learning process on land and water use around the Platte River in Colorado, United States. As in many situations of biodiversity protection, in this case, the top down designation of river habitat to be protected resulted frst in over a decade of protests by homeowners close to the river bank and water users, including threats to multiply individual court cases to contest the application of the habitat protection rulings to individual land plots. Given such threats, the US Fish and Wildlife service granted a temporary continuance of activi ties, provided that serious and fruitful negotiations were undertaken by all interested parties to seek approval for a river basin wide solution (Norton, 2015, p. 242). Norton highlights two main mechanisms that contributed to a successful agreement on the key principles to organize habitat protection. First, par ties identifed areas of convergence and divergence on the values that should guide collective decision making. Such convergence does not mean all par ties adhered to these values. However, at least, they could understand and accept the provisional validity within the space of common action. One area of agreement was the importance of protecting the rare species of Whooping Crane whose river habitat was endangered. The other area was to orient the choice of land acquisition for habitat protection frst to land plots with lower economic development value. Second, within this space of convergence, the parties still had diferent perspectives on many details of habitat protection. Parties held diferent views on the need (or not) to actively improve the river habitat, such as by regulating the fow of the river or building small ponds. Moreover, opinions diverged on house development plans on the riverbank, which contribute to the tax revenues of the municipalities. Nevertheless, to explore common action strategies within this diversity of perspectives, the parties adopted a social learning approach based on scientifc experimentation and monitoring. Through a common research protocol for real world testing of the proposi tions made by the diferent parties, parties aimed at assessing if and how the real world impacts of their proposed action strategies ftted the commonly agreed upon minimum set of sustainability values. Norton’s approach to social learning places the accent on the pragmatist revision of societal values based on the deliberation over the consequences of proposed action strategies. However, to understand the diversity of social 104 Social learning among actors on societal values learning needs in transdisciplinary research, this approach must be broad ened for at least two reasons. First, the type of convergence, or “balancing” in the terms of Norton, on a set of core sustainability values envisioned by Norton is not always possible or needed in practice. A less ambitious objective, such as social learning for building an agreement on process values might also be a desirable outcome of the social learning process. In the example of the Platte River habitat, the Fish and Wildlife service created a framework for negotiation among the par ties. The parties implicitly used and accepted the process values embedded in this framework. Without such an external institutional actor, learning might be required to set up the key process values, such as social inclusiveness or representation of citizens that can act as spokespersons for the non human living world in the process. Second, the main criterion proposed for evaluating the impact of the value based management decisions is its practical impact on problem solving. It is an important criterion that is grounded in well recognized approaches to validity in philosophical pragmatism based on classical authors, such as John Dewey and William James. In this perspective of philosophical pragmatism, societal values are considered valid in a given community of inquiry if they stand the test of practical experimentation with these values in concrete problem solving at a given point in time and if there is a willingness to fur ther submit them to this process of testing and possible revision. Nevertheless, without entering a deep philosophical debate, the concept of revision used by Norton, where the values are evaluated in terms of their instrumental impact on problem solving, is too restrictive to cover all situa tions of social learning that contribute to convergence over sustainable values or process values in transdisciplinary research. In addition to the impact on problem solving, debates over legitimacy and relevancy among project part ners also play a role in the process of revision. This broader approach can be captured through the concept of “comprehensive consequences” (Sen, 2009, p. 215). From a comprehensive outcome perspective, societal actors assess societal values regarding their impact on problem solving, their legitimacy as part of a broader value framework, and the fairness of the process that led to the acceptance of these values. 4.2 Amartya Sen’s deliberative approach to social choice with incommensurable societal values One of the merits of the work of Amartya Sen—who was awarded the 1998 Nobel Prize in economics for his work on social choice—is that it broadens our understanding of the role of deliberation over societal values in com plex social choice situations characterized by heterogeneous and sometimes antagonistic societal values. In particular, the approach of Sen helps further Social learning among actors on societal values 105 broaden the trial and error approach to partial convergence over societal values discussed in the context of Bryan Norton’s environmental philosophy to other types of social learning needs and mechanisms. A key foundation of the work of Amartya Sen is the realization that so called incommensurability* among societal values in a broad sense—the impossibility to establish a comparison between the values that specify what societal value choice is better or worse than another (Chang, 1997)—is not a problem for everyday decision making. Indeed, incommensurability over societal values is everywhere, despite which human actors can reach com mon decisions on action strategies and broad societal orientations over many collective issues. The shift in perspective proposed by Sen to overcome many of the par adoxes of social choice under diverse and incommensurable values is to abandon the idea of the need for an absolute ranking of the values to reach decisions considered reasonably valid by all. To paraphrase Sen (2009, p. 102), when two mountains are within reach, one can use various clues to validly affirm that one has climbed the highest mountain of these two without requiring further investigation into the height of the absolute highest mountain on Earth or even without agreeing on all the clues used to arrive at this conclusion. Similarly, in everyday decision making, human actors can take common decisions based on partially overlapping agreements or con sider decisions that are provisionally valid and open for revision given the availability of more information. In his major works on social choice, Rationality and Freedom (Sen, 2002) and The Idea of Justice (Sen, 2009), Sen further develops this idea of deci sion making with partial ordering and incomplete information. These works allow for distinguishing between three major ideal types of convergence over values between actors with diferent or incomplete value rankings. The frst ideal type concern situations where each of the individuals can rank the societal values in a reasonably consistent manner, though the rank ing between these individuals is not congruent. Sen considers two ideal types of agreement that actors use to solve a situation of incompatible value rank ings. The frst ideal type is based on a partial agreement on the ranking. The most advanced form of agreement exists if the individuals have a shared belief regarding the validity of some part of the ranking, which Sen calls a “fair agreement on particular pairwise rankings” (ibid, p. 105). For instance, if two individuals rank fve values respectively in the order V1 > V2 > V3 > V4 > V5 (for the frst individual) and V5 > V4 > V1 > V2 > V3 (for the second), they share at least an agreement over the ranking V1 > V2 > V3. As stated by Sen, in such cases, they can use this partial agreement to make common judgments on how to “enhance justice” or “reduce injustice” in specifc problem situations. The second ideal type is based on a minimum agreement on some core values. Indeed, even if there is no advanced agreement on pairwise rankings, 106 Social learning among actors on societal values some common judgments remain possible when rankings are incongruent among individuals. Indeed, there may be one salient value that is so impor tant that it is sufficient to motivate a common judgment of justice or injustice in a situation, even if ambiguity remains over the other value rankings (ibid, p. 397). For instance, in the example of fve values, V4 might represent acting against famine or exclusion from access to healthcare. These values might be recognized by all parties involved as a key value to defend, even if there is no straightforward manner to compare the other values of the overall value set in a mutually consistent way. The third ideal type described by Sen concerns the situation where each of the individuals expresses doubts or hesitation about his value ranking, as they lack key information or clues on how to manage the available informa tion to decide upon the ranking. In these situations, any value statement would be provisional and should be accompanied by a shared understanding of how and under what circumstances the value statements can be adjusted, completed, re examined, or extended to include new problem features. This type is labeled by Sen as “tentative incompleteness” (ibid, p. 107). As argued, this tentative incompleteness requires agreements on “process values,” such as acceptable means for assessing the credibility of new information or guar antees for inclusiveness in the deliberation over the revision process. In practice, these three ideal types must be combined to enhance over all justice in society. However, depending on the situation, the actors might consider that the most urgent social learning must occur frst within one of the types. Based on the level of value incongruence or incompleteness, they might consider that the priority lies in the identifcation of a set of minimum substantial value agreements, a more advanced pairwise ranking of several substantial values, or agreements on the process to gather and deliberate over new information on a tentatively accepted common value framework. To illustrate these various types, Sen discusses the hypothetical dilemma of three individuals claiming a fute (ibid, p. 12; pp. 396–397). Although it is an extreme case of incommensurability rarely encountered in real life, the case shows how the various types of social learning might be mobilized to attenu ate the incommensurability and converge on some common value judgments. Similarly, the case is also a reminder of the gradual nature of the convergence process through social learning, as per many contextual factors and prior levels of collaboration and trust. In the hypothetical dilemma constructed by Sen, three children “Anne, Bob, and Carla” quarrel about a fute. Each refers to a diferent social justice value to substantiate their demand for the fute. The frst, Anne, is the only one who can play the fute, and she claims the fute on the basis that it would be unjust to deny the fute to the only one who can play it. The second, Bob, defends his case by pointing out that he is so poor that he has no toys of his own, and the other two concede that they are richer and already well of. The Social learning among actors on societal values 107 third, Carla, is the person who made the fute, and one might be inclined to give the fute to her in recognition of her understandable claim to something she has made. Indeed, there is no real good solution to the dilemma, as one can mobilize arguments from various ethical traditions to justify each of these positions. However, Sen highlights that there remains some room for further learning, which shows some possible ways out of the dilemma. First, a possibility regards the minimum level of congruence. It could be the case that Bob is extremely poor such that the arguments based on eco nomic fairness prompt one to opt for ranking the inequality considerations highest to judge the situation. A second possibility suggested by Sen regards some fuzzy boundaries between the societal values perspectives. For instance, the diference between the three children might be not as strict as in the theo retical dilemma, and not only Bob but also Carla is poor. If the deliberation would lead to ranking both economic inequality and the right to the fruits of one’s labor above utilitarian arguments, then this would lend some support to give the fute to Carla. Finally, a third possibility (not explicitly mentioned by Sen) could use the incompleteness argument and organize processes of further information gathering and testing of provisional solutions. Indeed, to decide upon the allocation of the fute, one might temporarily give it to Anne but also ask for further information regarding the arguments over the other societal values. For instance, it might be unclear how challenging it is for the others to learn to play the fute, and Anne could help in this regard, including any other means available to overcome the poverty gap between Bob and the two other children. Further information on these issues might lead to a diferent appre ciation of what societal values has the highest relevance in the given problem situation. The interesting point in the example of the three children given by Sen is that the diference between the children’s arguments does not represent divergences about what constitutes individual advantage (getting the fute is considered advantageous by each of the children) but about the societal val ues that can generally justify decisions (here, about the allocation of goods). As underlined by Sen, the arguments are about “how social arrangements should be made and what social institutions should be chosen, and through that, about what social realizations would come about.” According to Sen, “it is not simply that the vested interests of the three children difer (though, of course, they do), but that the three arguments each point to a diferent type of impartial and non arbitrary reason” (ibid, p. 15). The strength of Sen’s analysis, in line with many other scholars of public deliberation, is how it shows the working of a framework for social learning over societal values that do not need an absolute viewpoint but still aim at a strong level of the objective validity of the structuring of the diversity of 108 Social learning among actors on societal values value perspectives. Indeed, the societal values under discussion are not the subjective values of individual participants but publicly shared values that can withstand critical scrutiny by a community of discussants. The end goal is to reach a level playing feld for communication on an intersubjective basis such that the various statements about partial rankings or process values are not inescapably confned to a subjective appraisal that others may not understand. 4.3 Illustrating the various types of social learning in transdisciplinary research practices The analysis of some key insights of the literature on the deliberative approach to social choice shows the diversity of possible outcomes of social learning processes over issues of common concern in situations of hetero geneous societal values. At frst glance, sustainability transformations with highly heterogeneous values leave few opportunities for consensus around the basic values or organizing the process for building new common val ues perspectives. However, when abandoning the viewpoint of reaching a consensus over complete value rankings and adopting a bounded rational perspective on the real world situations of collaboration with incomplete and partial agreements, societal actors have at their disposal a much wider set of opportunities for social learning. From a general perspective, based on the analysis by Sen, one can expect various types of social learning with varying degrees of demanding targets. The more demanding targets can strive for pairwise agreements on several value rankings adopted by societal actors. The less demanding targets may focus on one clear case of a societal value to which all parties adhere. Further, beyond these two contrasted outcomes, one might expect situations where the rankings of societal actors are so incomplete that no agreement on the ranking is possible. In such situations, societal actors may aim to adopt pro visional common action strategies that can support further learning and com pletion of the value framework. Moving from the analysis of the literature on social choice to the con text of building transdisciplinary research commons requires more infor mation from real world practices of transdisciplinary research deliberation. Therefore, this section proceeds along two steps to analyze the mechanisms of social learning. First, the various types discussed by Sen will be confronted with the mechanisms of social learning processes documented in the case study sample of transdisciplinary research projects presented in Chapter 3. Through a cluster analysis of the sub sample of cases with strong investment in social learning, the cases from this sub sample will be grouped around the most similar social learning mechanisms. Second, for each identifed type, one example of a transdisciplinary research process will be discussed in depth. Social learning among actors on societal values 109 The selection of cases is based on more and less successful research pro jects. Both cases with a high and low direct impact on usable knowledge production will be used. Indeed, for the analysis of social learning, both are potentially useful. In cases with high direct impact, specifc eforts for deliberation may not be vital to overcoming situations of divergence over key sustainability values. However, in the cases with low impact, partners may have implemented social learning processes for fostering convergence that successfully laid the groundwork for further collaboration in follow up research. Overall, the screening of the 44 cases in the overall sample led to identify ing 12 transdisciplinary research projects that actively implemented delib erative mechanisms for social learning and where these mechanisms are documented in research publications (see the detailed list in Annex 2, column “SL”). For each of the 12 cases, the key variables used by Sen in his analysis of the types of social learning processes were coded based on the information available in the research publications and accompanying project documents. These key variables include (1) the level of agreement targeted by the social learning process, from minimal agreements to partial overlapping rankings; (2) the defnition of some or various common action strategies that satisfy the societal value perspectives of the partners; and (3) the use of specifc tools for confict resolution. The clustering of the most similar cases based on these variables induces a modifcation of the key types identifed by Sen. The modifcation can be accommodated by including a fourth type of convergence process. The clus ter analysis confrms the relevancy of the two paradigmatic cases of agree ment in pairwise rankings and minimal agreement over salient societal value categories. Even so, the analysis of the situation of absence of agreement over the ranking or absence of individual consistent rankings yields two sub types. The frst sub type concerns situations where actors, despite divergence, adopt common action strategies that support further learning. A second sub type concerns situations where no such common action strategy is identifed through the research, but social learning still allows for agreeing on a set of process values to organize collaboration for trust building and improving mutual understanding. Hence, the cluster analysis of the social learning cases in the overall sample leads to identifying the following four types: 1 Agreement on process values for common inquiry into the problem identifcation • Cases where social learning yields an agreement over the process val ues that should lead the interaction among the partners (no common action, no agreement on ranking) 110 Social learning among actors on societal values 2 Common action strategies accommodating divergent perspectives • Cases where social learning yields a common strategy that satisfies the key societal values of the partners (only specifc common action, no agreement on ranking) 3 Identifying converging and diverging perspectives • Cases where social learning leads to identifying some area of conver gence around one or some salient societal values (one or some specifc common actions, based on the convergence around one or some sali ent societal values and divergence on the ranking of the other societal values) 4) Common action programs with a substantial overlap in value rankings • Cases where social learning leads to identifying substantial overlaps in value rankings—so called partial ordering—and a set of specifc com mon action strategies that satisfy the overlapping societal values An important caveat applies to this presentation of key features of social learning. As noted, in practice, many projects combine diferent social learn ing types, whether by implementing one type after another or by combining features of various types. Nevertheless, the analysis of specifc types can pro vide important insights. Each of the ideal types addresses specifc social learn ing challenges and mobilizes diferent deliberative mechanisms. Furthermore, knowledge of these types can fulfll a heuristic role in shaping and adjusting expectations among the research partners. Indeed, the identifcation of these types by the research partners allows them to clarify the social learning needs and the level of social learning appropriate for the given project resources, the history of collaboration among the partners, and the problem situation at hand. The remainder of this section illustrates each of the four types through an example from the case study sample. Each of these cases mainly addresses one of the social learning types and explicitly discusses this type in the project publications. 4.3.1 Agreement on process values for common inquiry The frst example illustrates the absence of congruent value rankings on the core sustainability values in a situation of persistent distrust among the pro ject partners. Social learning corresponds to the needs identifed in the frst social learning type, which is the creation of a community of inquiry that respects agreed upon process values to improve mutual understanding. Social learning among actors on societal values 111 The research partnership of the multistakeholder “working group for waders” that emerged from a research project on ground nesting birds in Scottish Moorlands is a good illustration of the use of various capacity build ing tools to foster the building of a community of inquiry (Ainsworth et al., 2020). The case mainly relies on insights from the confict transformation literature, particularly regarding the role of a protected or informal environ ment in trust building among the parties (Redpath et al., 2013; Van Breda and Swilling, 2019). The Moorlands are well known for high conservation value habitats for several ground nesting birds. All stakeholders and scientists agree that bird populations are declining in Scotland at an alarming rate but disagree about the solutions and the evidence behind diferent proposed solutions (Hodgson et al., 2018, 2019). However, in the Moorlands, there is a lack of data on the causes of the near extinction of a bird of prey, the hen harrier. This decline may stem from the change in habitat management or the illegal shooting of the hen harrier. The latter occurs to increase the presence of one of its preys, the red grouse, which is a ground nesting bird specifcally managed for rec reational hunting. Further, for other ground nesting birds, such as the curlew, the nesting habits are not well known, and their protection requires close col laboration between farmers, hunters, and nature protection organizations. In response to this dispute over the available knowledge on the causes of bird decline, the Scottish Government provided funding support to a stakeholder group—the Moorland Forum—to organize and supervise the “Understanding Predation” project, whose objective was to initiate a confict transformation process. The Forum decided to organize a transdisciplinary research project, involving hunters, recreationists, farmers, and members of environmental associations. According to Ainsworth et al. (2020), two major shifts in the framing of the confict played an important role in successfully overcoming the lack of collaboration. First, the focus on gathering evidence on predator prey dynamics of ground nesting birds more generally allowed the research team to take a step back from the more acute confict around hen harrier conser vation and red grouse management. As stated by the team: “we aimed to build a publicly accessible evidence base . . . from science and stakeholders’ local knowledge . . . highlighting where these forms of knowledge agreed or disagreed and analyzing the reasons for any diferences” (ibid, p. 47). Accordingly, the stakeholders and scientists realized that conservation man agement of ground nesting birds was a priority objective for almost all par ticipants. Moreover, the defnition of healthy populations of predator and prey species was crucial, despite diferent ideas on the appropriate manage ment methods to reach this objective among scientists and conservationists and recreational users and hunters. 112 Social learning among actors on societal values Second, based on insights from the confict transformation literature, the research team used small group and plenary meetings to build trust among stakeholder groups. For instance, before gathering all the stakeholders and scientists in a formal plenary workshop, the research team organized a set of nine small scale group meetings in a more confdential environment. At the start of each meeting, the participants agreed on a confdentiality state ment and could approve the workshop report before the analysis or dis semination by the research team. Further, as the confict was too acute in the earlier stages of the project, the research team only invited stakeholders from like minded organizations to the small group meeting by using the results of an online survey that allowed for a prior mapping of the main stakeholder values and areas of confict. The research team asked the par ticipants in the small peer groups to compare their sources of data with the data from literature reviews to understand the potential disagreements between the two sources of knowledge. This approach enabled participants to engage in meaningful deliberations while maintaining overall consist ency by covering the same topics in all the groups and referring to the com mon literature review and prior survey. The combination of small group “safe space” and regular plenary co pro duction workshops did not aim to reach a consensus on all the issues but to create the conditions for trust and mutual understanding. In the frst plenary meeting, participants with diferent interests were voluntarily seated next to each other to encourage informal confdence building. In the fnal seminar, stakeholders mutually prioritized a list of future collaboration actions in the Moorlands. The continuing collaboration for knowledge gathering in the “Working for Waders” program around a set of shared goals for conserva tion management is also a clear indication of the success of the research project. 4.3.2 Common action strategies accommodating divergent perspectives The second example regards the emergence of common action strategies around a core objective in a situation with highly divergent social actor per spectives. The case aims to identify income generation activities from coastal ecosystems in a sustainable manner in Southern Kenya. In the coastal ecosystems in Southern Kenya, the local communities expe rience major security issues regarding illegal fshing techniques and cross border robbery and trafficking along the Kenya Tanzania border. In response to these challenges, the SPACES project consortium set up a group based qualitative research in four villages each in Southern Kenya and Mozambique to better understand the opportunities for men and women to improve their Social learning among actors on societal values 113 well being through the sustainable use of the coastal ecosystem services (Galafassi et al., 2018). From the beginning of the project, it was clear that the community mem bers diverged on two possible implementation paths for poverty alleviation in the coastal ecosystem (Galafassi et al., 2018). Some members saw the lack of economic opportunities and the lack of security as issues related to indi vidual capacities. Therefore, they asserted the need to access education and capacity building as promoted by external actors. Other members highlighted historical social inequalities in the community as a major barrier, especially regarding gendered access rules to ecosystem resources that induce difer ent access to capital, education, and mobility for men and women (Fortnam et al., 2019). The proposed protocol for social learning in this situation was based on a combination of concept mapping and storytelling. The concept mapping aimed to identify the main factors afecting the well being of the community members and the strengths and direction of causal relations between these factors. A team of professional facilitators accompanied the process, organiz ing some of the prior knowledge through participants’ surveys and engaging the community members in assessing the main fndings. However, as shown in an in depth analysis of the workshop recordings and transcripts, the major learning in the workshops occurred through the sharing of lived stories and narratives. The latter provided insights into the diverse meanings given by the community members to key concepts such as insecurity and well being (Galafassi et al., 2018). Despite a lack of convergence among participants around the main path ways to poverty alleviation in the coastal ecosystems, the “shared conceptual repertoire” (ibid) that emerged from the research process allowed for iden tifying some common action strategies that are relevant from the perspec tive of diferent societal values. These common areas of action include the organization of the sustainable use of products from the fragile mangrove forests and coral reefs (Directorate, E.S.P.A., 2018) and the empowering of women who are currently excluded in this area from developing key income generation activities regarding ecosystem services from the mangrove ecosys tem (Galafassi et al., 2018). For instance, in the case of one of the project villages in Southern Kenya, situated along the Tsunza Mangrove, the increased mutual understanding among community members and associations resulting from the research process induced a set of new initiatives. Among these initiatives are the for mation of joint saving groups by women, the submission of funding applica tions for community forest conservation programs, and training for women entrepreneurship activities related to identifed small scale business oppor tunities such as oyster trading and traditional poultry farming (Daw, 2018). 114 4.3.3 Social learning among actors on societal values Identifying converging and diverging perspectives The third example corresponds to a situation of high initial trust among the project partners and a willingness to build collaboration around common values identifed through a set of multistakeholder deliberative workshops. The case is a research project to understand the options for sustainable mobil ity in the large metropolitan area of Stockholm, Sweden. Initially, this project had an important focus on technical solutions for so called smart mobility, which can lower car use and improve multi modality. Indeed, digitalization and electrifcation of mobility are likely to be key com ponents of any energy efficient mobility future. Digitalization enables more efficient transport logistics, the development of integrated booking systems among diferent modes of transport, better known as mobility as a service (MAAS), and social networking. Electrifcation, if based on renewable energy provision, can lower the carbon footprint of cars and trucks and lower air pollution. As noted in the previous chapters, the transformation toward more sus tainable mobility will require more than just proposing an array of techni cal solutions. Nevertheless, existing research and development remain biased toward technical dimensions for reaching possible sustainability outcomes, while user perspectives and institutional dimensions are seldom explored in depth. Thus, to overcome this research gap, the Mistra SAMS research center in Stockholm has set up two living labs that combine the development of digital innovations with behavioral, environmental, and economic analysis of sustainability choices (Bieser et al., 2021; Sjöman et al., 2020; Vaddadi et al., 2022). One living lab organizes a space for telework from a co work ing space in Tullinge, located 20 km south of Stockholm, in a neighborhood center where this type of service did not yet exist. This so called telecommut ing center ofers 14 workplaces plus conferencing facilities. The second living lab explores the use of smartphone applications to improve mobility choices. As mentioned on its project website, Mistra SAMS used a deep trans disciplinary approach, which involves interdisciplinary analysis and close collaboration with users and practitioners. Specifcally, as explained by the project coordinator Anna Kramers (personal interview, October 3, 2019), the choices of the technology to be tested and the specifc research questions to be addressed in the living lab research were not all specifed in advance at the start of the project. In a workshop with the 16 partners from academia, industry, and the public sector, the project participants tried to understand what the living lab research would contribute to solving the problems of Stockholm city. As observed by the stakeholders, there were many co working places; so, how could this project afect the ongoing transforma tion of work and workplace organization in a positive way? An important question raised by the city of Stockholm was the inclusive nature of the Social learning among actors on societal values 115 proposed digitalization of mobility and work solutions. The partners con verged on investigating the sustainability impacts of the co working space from the perspective of a more diversifed public, including both the work ers from the company and the freelance workers in the neighborhood, and the broader relation with the revitalization of the neighborhood (personal interview, September 19, 2019). Overall, the social learning among the scientifc researchers and soci etal actors was important to further deepen the research question beyond the technological innovations. This situation led Mistra SAMS to address research questions around the societal values of the two main social actor partners, which were the Ericsson Company and the city. In particular, the living labs allowed for mapping a set of strategies for more efective energy saving through teleworking at a hub: providing energy efficient transport options at the hub, such as bike sharing services; creating local destina tions, such as local groceries or lunch places; and energy savings at the hub (Vaddadi et al., 2022). Nevertheless, despite the convergence around the issues of behavioral change for sustainable mobility, the project did not dig deeper into the broader social equity questions around mobility, as the living lab was situated in a well of neighborhood. The project not only achieved behavioral change of both neighborhood inhabitants and participants of the Erickson company but also called for further research to analyze the type of impact telecommuting hubs might have for instance in a poorer neighborhood. Thus, the project laid the groundwork for further learning beyond the issue of smart mobility solutions and multi modality. A follow up project awarded to Mistra SAMS (2021–2024) further explored these questions, in particular through setting up a third Living Lab at a remote location, in the municipality of Botkyrka. In the case of Mistra SAMS, the secret of the suc cessful gradual learning process seems to lie in the strong partnerships with some key societal partners, the systematic consultation of the partners before moving to the next step, and the agile adaptation of the research tasks based on new inputs and insights from the research (Kramers and Akerman, 2019). 4.3.4 Common action program with a substantial overlap in the value rankings The fourth example illustrates a complete social learning process that can structure the diversity of value perspectives of diferent societal actors from the public sector, local communities, and associations and from diferent cul tural backgrounds. Based on this social learning, the partners could open up new opportunities for collaboration within a strong mutual understanding of each other’s value perspectives and an identifcation of areas of overlap between the respective value rankings. 116 Social learning among actors on societal values The case concerns a long term and well documented research project on healthcare delivery to nomadic pastoralists in Chad (the health intervention project) with diferent phases running from 1996 to 2006 (Bergmann et al., 2012, ch. III.F; Hirsch Hadorn et al., 2008, ch. 17). This project was set up in Chad after the observation in the early 1990s that nomadic pastoralists did not visit the local health centers. It revealed a social justice problem: health care services were organized by the State in a form that the nomads did not use; thus, in practice, they were virtually excluded from primary social ser vices. According to a report by the Swiss Tropical Institute, polio vaccination coverage was 11.6% among mobile pastoralists communities, against 80% among settled communities (Lechthaler and Abakar, 2015). Notably, among mobile pastoralist communities, vaccination coverage among livestock was signifcantly higher than vaccination coverage for children (Abakar et al., 2018). As shown in a qualitative focus group study, major barriers to vacci nation uptake by the nomadic population were mistrust and access to health system challenges (ibid). Therefore, the research tasks were defned as follows. The frst aim was to get an overall picture of the traditional forms of healthcare practiced by the nomads. Second, the team wanted to understand the barriers to the use of medical services ofered by the State and develop healthcare services nomads would efectively use. Hence, the project combined anthropological feld work into the traditional health system of the pastoralists with clinic surveys to map the main needs for interventions and socio geographical surveys to understand their daily livelihood concerns. The health intervention project illustrates a successful knowledge integra tion process based on an iterative research design. In this project, similar to the New York asthma study, after each phase of feld research and survey ing, the researchers organized a workshop with the main societal actors to discuss the results and set the priorities for the next phase of research. The main diference with the New York study is that, in addition, at the start of the research project, the research team organized an explicit social learning process among the project members to foster a mutual understanding of the diferent value oriented perspectives on healthcare delivery. Indeed, the frst rounds of research diagnosed many health problems within the population and revealed the importance of animal health for nomadic pastoralists. Livestock is the basis of the pastoralists’ economic wealth and social respect. Moreover, relative to Western medicinal practice, in the nomads’ traditional healthcare approach, the same health practitioners treat animals and humans. Thus, to address these diferent value frameworks, the project organized social learning among the partners to implement a so called one health approach to the delivery of health services, which considers the animal human health improvement synergies and promotes the collabo ration between human health and veterinary services (Schwabe, 1984). Social learning among actors on societal values 117 The involved researchers mention three main reasons for the success of the research program. First, the research team took the perspectives of the tradi tional community on the organization of the health system seriously, which created trust and provided an entry point for the development of the new healthcare services. Second, the research was based on a solid institutional partnership between the Swiss Tropical Institute, the Chadian Veterinary Laboratory, and the Chadian Ministry of Health, which secured a long term commitment of all partners. This commitment allowed for a highly fexible and adaptive research design. Third, efective knowledge sharing among all partners facilitated knowledge integration between livestock owners, tradi tional healers, and scientists. For instance, the detailed monitoring by the traditional livestock owners of animal health resulted in doubts about the efficacy of one of the livestock vaccines. This knowledge was taken up by the research team and later confrmed by laboratory analysis. The latter led to the replacement of the vaccine with a new one and an increase in trust in the usefulness of vaccination. Overall, the knowledge co production process was highly structured, with a clear division of work and well identifed moments of sharing of results and joint planning, especially during the fve national workshops held during the entire project. The formulation of the problem was gradually broadened from problems of capacity building for health care delivery infrastructure to a broader concern for livelihood problems of the pastoralists, such as access to safe migration routes for the livestock and access to grazing lands allowing for improved management of animal health and milk production. In subse quent rounds of research and intervention, the program was further extended and eventually embedded in government health schemes for the entire pas toralist community, which represents around 10% of the total population in Chad. 4.4 Fostering critical engagement across differences As the examples in this chapter show, without appropriate procedures for social learning among the partners, transdisciplinary research pro cesses can fail to organize efective collaboration among project partners. Examples of failures in generating efective collaboration are the lack of common purpose when co constructing the initial research design or mis understandings that emerge later in the project when discussing the inter mediary research results. In such cases of efective or potential failure, research partners might decide to invest in diferent social learning pro cesses among the partners. The four types of social learning analyzed in this chapter aim to illus trate various mechanisms for structuring the diversity of value perspectives. Project partners can decide to invest in one or several of the mechanisms as a 118 Social learning among actors on societal values condition for successful knowledge co production. The choice of the appro priate type of social learning process depends on the perceived complexity of the coordination needs among the partners and the initial levels of trust. Indeed, not all situations of divergence are conducive to collaboration failure in all felds of sustainability research or for all research purposes. In some projects, minimal convergence over some process values may be sufficient. In other cases, more encompassing substantial agreements over key sustainabil ity values may be required, such as when the scale of common actions to be undertaken is especially broad. In the latter case, where enhanced coordina tion is required, what seems essential is not to reach a convergence over all social values but to structure the diversity of societal values such that partici pants can explore the opportunities for workable compromises on common action strategies. Furthermore, as shown in some of the case studies in our sample, the history of collaboration among partners or the experience of the individual partners with social learning has a strong impact on the degree to which partners are willing to invest in fostering social learning. Partners with diver gent views but with positive experiences from social learning processes in other projects are more likely to adopt a collaborative attitude at the onset than other participants who may need more time to build trust and embark on a collaborative research endeavor (Innes and Booher, 2010). Therefore, social learning in some cases can be a gradual process, where the progress in one research project, even if quite modest, can lay the ground for further social learning and more ambitious collaborative undertakings in subsequent research eforts. A common thread from this analysis of social learning in transdiscipli nary research is the importance of a critical engagement of research part ners to refect on their own societal value backgrounds. Indeed, to engage in social learning, partners must adopt a critical approach to their value related positions. In this context, scholars highlight a set of process standards to embed the critical role of social learning in heterogeneous actor networks (Sørensen and Torfng, 2007; Dryzek, 2007). In his work on network governance in highly pluralistic and multi scale problem settings, John Dryzek proposes an adaptation of the Habermasian principles of authentic deliberation to the organization of fair and inclusive communication within heterogeneous actor networks. Specifcally, Dryzek highlights three important process standards that apply to the governance of heterogeneous actor networks (Dryzek, 2002, 2007, p. 268): impartiality, non coercive dialogue, and generality (see Figure 4.1). Satisfying these process standards contributes to fostering efec tive engagement of all participants in discussing the multiplicity of points raised by diferent concerned actors. Social learning among actors on societal values 119 Different social learning targets depending on the perceived needs for improved trust building and/or coordination Institutional conditions for effective social learning in collaborative research Common action program within a substantial overlap in the value rankings Impartiality Rational authentic dialogue Non-coercive dialogue Broad inclusive perspective Social learning outcomes amongst scientists and social actors Identifying converging and diverging perspectives Common action strategies accommodating divergent perspectives Agreement on process values for common inquiry FIGURE 4.1 Process standards for authentic deliberation in heterogeneous actor networks The frst standard concerns the organization of impartial refection on one’s value position and the value related positions of each of the partici pants. This attitude has been described in various terms in the literature, such as “open impartiality” (Sen, 2009, p. 123), “neutrality” (Misak, 2000, p. 109), or “cooperative efort to reach intersubjective validity” (Habermas, 1986, pp. 88–89) among others. What is common between these diferent notions is the idea that each participant must be capable of being reason able in taking note of other people’s perspectives. Indeed, to efectively create engagement with a multiplicity of discourses, each participant must articu late their perspective in the debate and welcome information and arguments from the perspective of others. The second standard goes beyond the condition of impartiality and addresses power related issues more explicitly. This standard requires a criti cal attitude to guarantee the non coercive character of the dialogue, requiring equality in the capacity to raise and challenge points. This second standard aims to overcome the potential undue exercise of power and rent seeking strategies of participants in public deliberation. For instance, in situations of strong confict or power diferentials between partners, social learning is not necessarily geared toward overcoming the antagonism between societal actors. Instead, when deep diferences are entrenched, at least during the research period, establishing respectful engagement requires a critical atti tude to the undue exercise of power or rent seeking. Further, guaranteeing the non coercive character of the dialogue is more important in situations with less direct power diferentials. This perspective is, for instance, refected in critical theory perspectives on social learning, 120 Social learning among actors on societal values which aim to unearth relationships involving distorted communication pro cesses, in particular by understanding how manipulation of information con tributes to resistance to mutually benefcial change (Willis, 2007, pp. 81–87). In general, in this critical role of social learning, partners aim to deconstruct unquestioned societal value perspectives that perpetuate dominating relation ships and fow from unequal capacities to participate in the debate (Fraser and Honneth, 2003). The third standard—the generality of the common perspectives—requires that the participants are capable of connecting the particular experiences to some general point that applies to a broad diversity of stakeholder groups. As stated by Dryzek, “if communications cannot connect the particular to the gen eral, they may reinforce and harden the position of an enclave or a subculture but not reach those with diferent viewpoints” (Dryzek, 2007, p. 268). The relevance of these process standards for organizing procedures for critical analysis of the various value perspectives depends on the available capacities for social learning and how these capacities are perceived by partici pants. Overall, as in the discussion of co management and research co design in Chapter 3, the choice among various ways for organizing the procedures for social learning will be highly context specifc and might change during the course of the project. Indeed, divergence in societal values is not a prob lem per se for successful collaboration. On the contrary, as mentioned in the introduction to this chapter, diversity can be a source of innovation and may broaden the possibilities for fnding workable compromises around common value perspectives on sustainability orientations that satisfy the mutual inter ests of the participants. However, given the absence of an external benchmark on the desired level of divergence and convergence, the project partners must adjust their expectations for social learning based on their appreciation of social learning needs. As argued in this chapter, research partners can use vari ous indications for evaluating the required intensity of social learning. These indications do not only include the complexity of the coordination needs in the problem feld. Other factors play a role as well, such as the pre vious experience of the research partners with boundary crossing research collaborations, which may lead to high or low levels of initial trust among the partners. Moreover, as highlighted in the more general literature on public deliberation, social learning may be motivated by the aspiration to strengthen the general process standards of authentic deliberation in het erogeneous actor networks. References Abakar, M. F., Seli, D., Lechthaler, F., Schelling, E., Tran, N., Zinsstag, J. and Muñoz, D. C. (2018). Vaccine hesitancy among mobile pastoralists in Chad: A qualitative study. International Journal for Equity in Health, 17(1), 1–10. Social learning among actors on societal values 121 Ainsworth, G. B., Redpath, S. M., Wilson, M., Wernham, C. and Young, J. C. (2020). Integrating scientifc and local knowledge to address conservation conficts: To wards a practical framework based on lessons learned from a Scottish case study. Environmental Science and Policy, 107, 46–55. Barnaud, C., Trebuil, G., Dumrongrojwatthana, P. and Marie, J. (2008). Area study prior to companion modelling to integrate multiple interests in upper watershed management of northern Thailand. Journal of Southeast Asian Studies, 45(4), 559–585. Barnaud, C., van Paassen, A., Trébuil, G., Promburom, T. and Bousquet, F. (2010). Dealing with power games in a companion modelling process: Lessons from com munity water management in Thailand highlands. The Journal of Agricultural Education and Extension, 16(1), 55–74. Bergmann, M., Jahn, T., Knobloch, T., Krohn, W., Pohl, C. and Schramm, E. (2012). Methods for transdisciplinary research: A primer for practice. Frankfurt: Campus Verlag. Bieser, J. C., Vaddadi, B., Kramers, A., Höjer, M. and Hilty, L. M. (2021). Impacts of telecommuting on time use and travel: A case study of a neighborhood telecom muting center in Stockholm. Travel Behaviour and Society, 23, 157–165. Chang, R. (Ed.). (1997). Incommensurability, incomparability, and practical reason. Cambridge, MA: Harvard University Press. Daw, T. (2018). Uncovering the amazing behind the scenes achievements by Tzunza community to build on SPACES knowledge and dialogues. www.espa spaces.org/ uncovering the amazing behind the scenes achievements by tzunza community to build on spaces knowledge and dialogues/. Accessed 26 February 2023. Directorate, E.S.P.A. (2018). Mangrove conservation is protecting both livelihoods and carbon stores. Report on Impact Stories. Research into Results, Edingburgh. Dryzek, J. S. (2002). Deliberative democracy and beyond: Liberals, critics, contestations. Oxford: Oxford University Press. Dryzek, J. S. (2007). Networks and democratic ideals: Equality, freedom, and com munication. In E. Sørensen and J. Torfng (Eds.), Theories of democratic network governance (pp. 262–273). London: Palgrave Macmillan. Fortnam, M., Brown, K., Chaigneau, T., Crona, B., Daw, T. M., Gonçalves, D., . . . and Schulte Herbruggen, B. (2019). The gendered nature of ecosystem services. Ecological Economics, 159, 312–325. Fraser, N. and Honneth, A. (2003). Redistribution or recognition?: A political-philosophical exchange. New York: Verso Books. Galafassi, D., Daw, T. M., Thyresson, M., Rosendo, S., Chaigneau, T., Bandeira, S., . . . and Brown, K. (2018). Stories in social ecological knowledge cocreation. Ecology and Society, 23(1), 23. Habermas, J. (1986). Morale et communication (translated by Christian Bouchind homme). Paris: Les Editions du Cerf. Herrero, P., Dedeurwaerdere, T. and Osinski, A. (2019). Design features for social learning in transformative transdisciplinary research. Sustainability Science, 14(3), 751–769. Hirsch Hadorn, G., Hofmann Riem, H., Biber Klemm, S., Grossenbacher Mansuy, W., Joye, D., Pohl, C., . . . and Zemp, E. (Eds.). (2008). Handbook of transdisciplinary research. Dordrecht: Springer. Hodgson, I. D., Redpath, S. M., Fischer, A. and Young, J. (2018). Fighting talk: Organisational discourses of the confict over raptors and grouse moor manage ment in Scotland. Land Use Policy, 77, 332–343. 122 Social learning among actors on societal values Hodgson, I. D., Redpath, S. M., Fischer, A. and Young, J. (2019). Who knows best? Understanding the use of research based knowledge in conservation conficts. Journal of Environmental Management, 231, 1065–1075. Innes, J. E. and Booher, D. E. (2010). Planning with complexity: An introduction to collaborative rationality for public policy. Abingdon: Routledge. Kramers, A. and Akerman, J. (2019). Mistra Sams annual report 2018. KTH Royal Institute of Technology, Stockholm. Lechthaler, F. and Abakar, M. F. (2015). Étude de base sur l’utilisation des services de santé maternelle et infantile au Tchad : une enquête en milieu rural auprès des populations sédentaires et nomades à Yao et à Danamadji [Unpublished report]. Swiss Tropical and Public Health Institute, Basel. Misak, Ch. (2000). Truth, politics, morality. London: Routledge. Norton, B. (2015). Sustainable values, sustainable change. Chicago: The University of Chicago Press. Norton, B. G. (2005). Sustainability. Chicago, IL: The University of Chicago Press. Pohl, C. and Hirsch Hadorn, G. (2007). Principles for designing transdisciplinary research. Munich: Oekom Verlag. Redpath, S. M., Young, J., Evely, A., Adams, W. M., Sutherland, W. J., Whitehouse, A., . . . and Gutierrez, R. J. (2013). Understanding and managing conservation conficts. Trends in Ecology and Evolution, 28(2), 100–109. Reed, M. S., Evely, A. C., Cundill, G., Fazey, I., Glass, J., Laing, A., . . . and Stringer, L. C. (2010). What is social learning? Ecology and Society, 15(4). Schneider, F., Giger, M., Harari, N., Moser, S., Oberlack, C., Providoli, I., . . . and Zimmermann, A. (2019). Transdisciplinary co production of knowledge and sus tainability transformations: Three generic mechanisms of impact generation. Environmental Science and Policy, 102, 26–35. Schwabe, C. W. (1984). Veterinary medicine and human health. Philadelphia: Wil liams and Wilkins. Sen, A. (2002). Rationality and freedom. Cambridge, MA: Harvard University Press. Sen, A. (2009). The idea of justice. Cambridge, MA: Harvard University Press. Sjöman, M., Ringenson, T. and Kramers, A. (2020). Exploring everyday mobility in a living lab based on economic interventions. European Transport Research Review, 12(1), 5. Sørensen, E. and Torfng, J. (Eds.). (2007). Theories of democratic network governance. Heidelberg: Springer. Vaddadi, B., Ringenson, T., Sjöman, M., Hesselgren, M. and Kramers, A. (2022). Do they work? Exploring possible potentials of neighbourhood telecommuting centres in supporting sustainable travel. Travel Behaviour and Society, 29, 34–41. Van Breda, J. and Swilling, M. (2019). The guiding logics and principles for design ing emergent transdisciplinary research processes: Learning experiences and refec tions from a transdisciplinary urban case study in Enkanini informal settlement, South Africa. Sustainability Science, 14(3), 823–841. Willis, J. W. (2007). Foundations of qualitative research: Interpretive and critical approaches. Thousand Oaks, CA: Sage Publishing. 5 DEVELOPING INTEGRATED BOUNDARY-CROSSING ORGANIZATIONAL NETWORKS As argued throughout the book, to successfully produce usable knowledge on interdependent social and ecological system dynamics within basic and applied transdisciplinary research, research partners must engage actively in various knowledge co production and social learning activities. Important aspects of these activities are the co construction of research design, the co management of the knowledge co production process, and social learning on sustainability values by researchers and societal actors. To consolidate transdisciplinary research in more diverse and comprehensive research net works, researchers and science policy officials must, however, look beyond the level of these collaborations within research projects and develop a set of higher level institutional mechanisms for building transdisciplinary research competences and research networks in larger communities. This chapter aims to take a fresh look at this question of the institution alization of transdisciplinary research partnerships into larger organizational structures for research capacity building. The key hypothesis of this chapter is that the capacity building can be organized by involving researchers and societal actors in larger polycentric organizational networks. The acquisition of competences in these larger networks can be organized through a diversity of exploratory research activities, which are part of the regular repertoire of activities at institutions of higher education. For instance, teachers can organ ize initiations in co constructed research in the context of courses on sustain ability issues, or researchers can gather in open ended workshops to identify new transdisciplinary research strands. Furthermore, capacity building for research can rely on well known mechanisms such as organizing discussion platforms in larger clusters of thematic research or organizing meta analyses of general process principles for transdisciplinary research. DOI: 10.4324/9781032624297 6 This chapter has been made available under a CC BY NC ND 4.0 international license. 124 Developing integrated boundary-crossing organizational networks What is key in the implementation of these well known mechanisms in the context of transdisciplinary sustainability research is the need to con sider the requirements of knowledge co production and social learning at the level of larger organizational networks. Hence, the institutional mecha nisms for building the larger networks should also foster the acquisition of competences that are not always part of the regular academic curricula, such as broad interdisciplinary competences spanning the social and ecological dimensions and competences for research co design and research co manage ment with societal actors. Building upon contemporary research in organizational theory, this chap ter frst discusses the general institutional logic behind the design of fexible, polycentric networks. As highlighted, this organizational approach is only a frst step to understand the specifc needs for the institutionalization of transdisciplinary research. In a second step, the institutional analysis of the networks will be broadened to consider knowledge co production and trans formational and critical social learning within the piloting, clustering, and networking of transdisciplinary project work. 5.1 From disciplinary divisions and departments to flexible network organizations The work of Oliver Williamson on governance networks (for which he was awarded the 2009 Nobel Laureate in Economics jointly with Elinor Ostrom) provides a good starting point for the institutional analysis of building fex ible network organizations. Indeed, the now classical synthesis by Oliver Williamson of the key economic aspects of large scale organizational archi tectures allows for understanding why networks can provide a third alter native to the classical forms of organizational hierarchies and case by case market like interactions (Williamson, 1996). First, Oliver Williamson shows how, under certain conditions, actors go beyond case by case interactions by integrating a set of tasks in an organization with a common purpose, instead of solving all problems by case by case contracting over such tasks between individual agents, such as in freelance labor or decentralized bargaining between competing groups. Second, Williamson shows that the alternative to case by case contracting is not only large scale centralized organizations (so called functional hierarchies) but that this organization can take a more decentralized form with the building of autonomous teams or fexible net works (see Figure 5.1). Williamson’s economic analysis hints neither at one best organiza tional form to overcome the insufficiencies of market like cases by case transactions nor at a pure form. In practice, actors build hybrids between the abstract categories of hierarchies and networks. The key insight of Williamsons’ synthesis is that there is no unifed theory of organization Developing integrated boundary-crossing organizational networks Func˙onal hierarchy 125 Autonomous team work in an organisational hierarchy Flexible network organisation embedded in an organisational hierarchy Legend General direction and generic staff support Division heads and middle management Operational units and teams Enabling of boundary crossing network collaborations Research groups Societal actor groups FIGURE 5.1 Ideal types of organizational forms for dealing with diferent types of task environments 126 Developing integrated boundary-crossing organizational networks forms nor is there a silver bullet to be found. Instead, the advantage of one organizational type over another, whether it be diferent types of hierar chies or networks or various hybrids between these two forms, depends on many factors. Important factors include the nature of the task environment of the organization, which can be somewhat fxed or evolving, and the complexity of the interaction processes between the actors that are needed to achieve the common organizational purpose. In this context, as shown in the work of Williamson, actors search for improvements by aligning the organizational structure to the specifcities of the organizational context and exploiting opportunities for organizational innovation within the con straints of past organizational choices (ibid). Regarding science commons, organizations must address highly specifc knowledge creation processes by researchers and societal actors that are challenging to work out and monitor on a centralized basis. Thus, the more decentralized forms of organizations such as networks or hybrids between networks and hierarchies are especially relevant in this context, though the type of networked organizational forms is diferent between disciplinary and transdisciplinary science commons. The overview of the main alternatives to conventional organizational structures by Kuipers et al. (2018), in their companion volume on new organizational forms, allows for disentangling the diferent organizational choices in decentralized modes of organization. Kuipers et al. (2018) con trast two main types of decentralized organizations that are distinct from the conventional functional hierarchy, as illustrated in Figure 5.1. The frst is the division into functionally autonomous units, which closely refects how disciplinary science commons are organized, and the second is the fexible network organization, which considers many of the key features of transdis ciplinary science commons. According to Kuipers et al. (2018), the benefts to choose one of these organizational forms depend on the degree of variation of the tasks of the organization at various points in time and the complexity to monitor their execution. A short snapshot of the key features of functional hierarchies allows for understanding why the science commons radically departs from this central ized mode of organization. As specifed by Kuipers et al. (ibid), in its pure form, a conventional functional hierarchy is characterized by centralized management and specialization of tasks in a set of separate operational divi sions whose execution is planned and monitored by the general managers (ibid, p. 164, see also upper left part of Figure 5.1). Such an organization is especially appropriate and efective in the context of a well specifed and only moderately evolving task environment. Paradigmatic examples of such task environments are the mass production of basic consumption goods by a frm or the delivery of standard administrative services to citizens by a municipality. Developing integrated boundary-crossing organizational networks 127 A key feature of functional hierarchies is the layered nature of the organi zation, typically comprising a minimum of three layers (Miller, 2005, p. 357). Indeed, monitoring the contribution of all individuals to a common purpose in a large organization is not a trivial task, and there is no special reason to believe the central manager is the best person to supply all the monitoring services. Someone else, a specialist, typically the division head in an organiza tion with several divisions, is often better placed to provide the monitoring more expertly than the principal herself. The result is a three level (at least) hierarchy, in which the managers attempt to guide the division heads to act in the organizations’ interest, while the latter regards monitoring the agents within the organizational divisions. The second type of large scale organization, the so called functional specialization in autonomous teams, departs from this conventional model (Kuipers et al., 2018, p. 136). In the organization through autonomous teams, the managers delegate part of the supervision of tasks and defni tion of strategy directly to the teams themselves. The resulting organizational architecture is diferent. Instead of a top down organization in organizational divisions that execute tasks defned by the central managers, in this second type, each team has a large autonomy in setting its goals and monitoring the execution of tasks. Obviously, the decentralized defnition of tasks and strat egies is much more appropriate for the complex and highly evolving knowl edge environments researchers face in their respective areas of expertise. In the structure of decentralized autonomous teams, for those func tions that are delegated to the teams, the role of the manager shifts from a command and control role to a role of enabler of decentralized coordina tion and cooperation processes (ibid). Therefore, in practice, the functional specialization in autonomous teams is a hybrid between pure networks, as the researchers have a large autonomy in goal setting and execution, and hierarchies. Indeed, how the units are divided and resources are allocated in a research organization remains structured in an identifable functional hierarchy by the central management. The latter is typically the case in the conventional disciplinary organization of universities and public research institutions for instance. The third organization type, the fexible network organization, is closer to a pure network organization. Indeed, in this case, the organizational hierarchy does not specify the boundaries of the decentralized networks of researchers involved in autonomous teamwork (ibid, p. 138). The topics addressed by the teams are much more open ended and teams can compose and re compose constantly to adapt to a highly changing and diverse task environment. In this context, as in the second type, the manager also has an enabling role in decentralized collaboration dynamics. However, addi tional management tasks need to be fulflled regarding the constant forma tion of new teams with diferent combinations of competences to address 128 Developing integrated boundary-crossing organizational networks case specifc issues and the building of boundary crossing competences such that actors can fexibly operate in several teams. In general, the organization of publicly funded scientifc research fts most of the features of the decentralized modes of organization (the second and the third organizational type). Indeed, the standard economic analysis of pub licly funded research shows that research organizations must satisfy a set of constraints that imply a decentralized organizational architecture. As shown in the seminal contributions of Kenneth Arrow and Richard Nelson in the economics of knowledge, knowledge produced in basic and applied research share important public good characteristics, such as non rivalry in use and non divisibility (Antonelli, 2005). Hence, the case for undersupply through markets or voluntary action alone arises. This poten tial undersupply is a major argument for public intervention in scientifc research, such as through public endowments to universities and other public research institutes. Therefore, public authorities and (by delegation) authorities at universities have a key role to play in the centralized funding of research and monitor the overall productivity of researchers in the use of these funds. However, public research funders who distribute the funding to the researchers (directly or indirectly) through the research organizations are not best placed to judge the allocation of the funds. Indeed, the informa tion about promising avenues of research and the best available scientifc knowledge is not centralized but dispersed among scientifc researchers and professionals in their specifc felds of investigation (Dasgupta, 1988). Hence, research funding bodies delegate a large part of the project assessment and research evaluation to peer review panels of scientists (Li and Agha, 2015). Thus, a major part of the quality management of publicly funded scientifc research is organized at the level of the autonomous disciplinary units and communities. Moreover, the disciplinary communities are organized on a decentralized basis to conduct the peer review of the research outputs, mainly through peer reviewed scholarly journals, to organize knowledge exchange on further theory development within the respective disciplines. The transdisciplinary research commons inherit many of the basic organi zational features of this public sector science. However, instead of a fairly stable set of autonomous teams organized along disciplinary and sub disci plinary boundaries, it is based on a fexible network structure along the lines of the third type identifed in the overview by Kuipers et al. (2018). Indeed, the research topics are not merely clustered according to similar specialized expertise within given disciplines. Instead, for each specifc transformation pathway, understanding the key social and ecological system interdependen cies and identifying the legitimate and relevant societal values perspectives results from a co production process among researchers and societal actors’ partners of the project. Developing integrated boundary-crossing organizational networks 129 Further, concerning disciplinary research, the task environment of the researchers is defned relative to a set of evolving research questions that emerge from the advancement in scientifc understanding within the dis cipline. In this context, team formation can be organized by looking for researchers interested in such closely related research questions and who have the right competences per the standards of the discipline. In transdisciplinary research, as the research tasks are co produced in interdisciplinary networks of researchers and societal actors, the task environment is much more open when forming new research teams. The match with the required competences of potential research partners is also less defned, as the evolving nature of the research tasks might require the mobilization of knowledge types or process competences not foreseen at the start of the co production process. Further, transdisciplinary research requires also a set of new competences, such as competences for research co design and research co management with soci etal actors. 5.2 Embedding knowledge co-production and social learning in the institutional enabling of transdisciplinary research The literature on fexible networks, reviewed by Kuipers et al. (ibid), iden tifes three core enabling functions of decentralized fexible networks that directly apply to the creation of an institutional environment for transdis ciplinary research at universities and institutions of higher education. They include the generic functions of training, knowledge exchange, and building social networks. This section briefy presents the challenge of embedding the knowledge co production features of transdisciplinary research in these three research enabling functions. The next section will zoom in on the implemen tation and present some illustrative examples. First, for the training functions, innovative teaching formats will be required to foster the building of co production and social learning com petences. Moreover, the teaching must propose methods and approaches for the learning of interdisciplinary knowledge integration across social and ecological system aspects. Typically, it will involve teaching programs that mobilize multi disciplinary expertise in specifc felds of sustainabil ity transformations but involve students in the transdisciplinary research design of common integrated frameworks for socio ecological systems analysis. Per the arguments developed in Chapter 3 on knowledge co pro duction on sustainability challenges in integrated socio ecological systems, these frameworks cannot be defned in advance, as they cannot be speci fed independently from the choice of feasible and desirable sustainability transformation pathways. Thus, part of the innovative teaching on trans disciplinary sustainability research involves real world analysis of specifc transformation pathways by co constructing common frameworks among 130 Developing integrated boundary-crossing organizational networks Enabling platform level • Building competences for co-produced socio•co-production of enabling initiatives for ecological analysis in teaching curricula and boundary crossing research collaborations research training • Organizing boundary crossing knowledge exchange in thematic or generic clusters/networks/workshops • Exploring opportunities for knowledge coproduction/social learning among potential project partners Research projects Level • Usable knowledge co-production on sustainability transformations • Social learning on sustainability values in transdisciplinary research FIGURE 5.2 Co produced transdisciplinary research enabling functions. Legend: project boundaries—full line; boundary crossing interactions—dotted line; black circles designate research groups, and white circles, social actor groups. disciplinary perspectives, along with deliberation over societal values with concerned societal actors. The second enabling function addresses the organization of the exchange of knowledge on the transdisciplinary processes and methods in the fex ible organizational networks. Given the diverse nature of the research activi ties involving diferent combinations of disciplines and types of social actor partnerships, it is unlikely to fnd a reasonably uniform approach to the main process features of transdisciplinary research across these activities. Nevertheless, knowledge exchange can be organized in a multitude of net work clusters. This clustering across various networks allows researchers and societal actors to gather around topics of common interest for transdiscipli nary research, while still acknowledging the broad heterogeneity of knowl edge types that are mobilized. Therefore, the goal of the knowledge exchange in these clusters is to strengthen the capacity of the potential research part ners to address knowledge co production and social learning challenges in a wide range of partnership types and possible combinations of disciplinary knowledge. Given the central role of knowledge co production and social learning with societal actors, these network clusters for knowledge exchange should Developing integrated boundary-crossing organizational networks 131 strive to actively include societal actors’ perspectives on sustainability trans formations. Indeed, even though processes for improving social legitimacy and social relevancy likely difer from one project to another, research ers and societal actors involved in various projects can learn from each other and broaden the possible perspectives on likely causes of success and failure. Moreover, the knowledge exchange clusters may ofer new opportunities for pursuing discussions on the validation of results from various social actor viewpoints and contribute to more efective knowledge transfer. Finally, a key enabling function for transdisciplinary research concerns social networking among potential research partners. Indeed, in capacity building for transdisciplinary sustainability research, the research topics can only partially be defned independently of the constitution of the research team and the choices made by the members of the team on the framing of the plurality of possible interdependent social and ecological system dynamics. Therefore, the programming of new research topics also partially depends on their co production in a gradual learning process among disciplinary researchers and societal actors on possible avenues for collaborative research. One interesting tool that integrates such elements of enabling knowledge co production at the stage of exploring team formation is documented in management studies on fexible network organizations. They are the so called search conferences (Weisbord and Janof, 1995; Kuipers, 2018, pp. 347, 411, 431). In such meetings, diverse members of an organization gather to imag ine common projects across boundaries of organizational tasks and areas of expertise. Similarly, in the so called open space conferences (Owen, 2008), cooperative arrangements are sought around a specifed topic among all the relevant persons in an organization without a pre defned agenda or group composition. These tools have been developed mainly in the context of busi ness and non proft organizations. As described later, some research organi zations have designed their version of these tools to enable social networking for research programming in transdisciplinary research. 5.3 Implementing integrated boundary-crossing networks for teaching, knowledge exchange, and team formation This section discusses examples of implementing the three institutional ena bling mechanisms discussed in the literature on fexible network organizations (i.e., building competences, knowledge exchange, and strategic programming of future research). As noted, in the case of transdisciplinary sustainability research, the implementation of these mechanisms cannot be disconnected from knowledge co production and social learning with societal actors on feasible and desirable sustainability transformations in the various thematic areas of concern. 132 5.3.1 Developing integrated boundary-crossing organizational networks Building transdisciplinary teaching and training curricula The frst important task is building transdisciplinary collaboration and research competencies in the teaching curricula at universities and institu tions of higher education (Fam et al., 2018; Herweg et al., 2021; Ahrend and Podann, 2021; Schmohl and Philipp, 2021; Griffin et al., 2022; Vienni Baptista and Klein, 2022). Accordingly, various organizations have set up transdisciplinary teaching programs. Such programs often build upon former pedagogical innovations developed since the 1970s that included training for research approaches that involve social actor partnerships, such as urban studies or development cooperation (Nicolaides et al., 2022). Nevertheless, not all innovative teaching programs are automatically transdisciplinary. In many cases, they remain purely multi disciplinary or do not explicitly organ ize deliberation around heterogeneous sustainability values to co construct specifc socially legitimate and relevant transformation pathways. Two prominent educational initiatives can illustrate the organization of transdisciplinary education at the university that meets some of the chal lenges. The frst is organized by the transdisciplinary research and teaching group, TdLab, at ETH Zürich, and the second is piloted by Gothenburg University in Sweden in the context of the Mistra Urban Futures research consortium. The TdLab at the polytechnical institute ETH in Zürich comprises a group of professors, lecturers, researchers, and graduate students collectively in charge of teaching and research activities across disciplinary and secto ral boundaries. The TdLab organizes a series of teaching activities on issues of sustainable development with societal stakeholders. As specifed in two articles on building transdisciplinary competences through the TdLab cur riculum, these courses actively address transdisciplinary research co design and social learning on sustainability values (Krütli et al., 2018; Pearce et al., 2018; Pohl et al., 2018). First, the proposed teaching activities actively organize a discussion with societal actors on the problem co construction and the co validation of the research results. As stated in the presentation of the curriculum, “the stu dents frame the problem, along with non academic actors who have an inter est in the problem” (Pearce et al., 2018, p. 168). The authors directly link this approach to the concept of transformational learning based on real world problems developed by Meeth (1978, p. 173): “Whereas interdisciplinary programs start with the discipline, transdisciplinary programs start with the issue or problem and, through the processes of problem solving, bring to bear the knowledge of these disciplines that contribute to a solution or reso lution.” Such transformative learning assumes not only that learning is based on personal experience but that learning often requires to be challenged by the experiences and perceptions of others (König, 2015). Developing integrated boundary-crossing organizational networks 133 Second, the teaching activities directly address value related learning by combining interdisciplinary system analysis with discussing the sustainability targets and the social possibilities of change in the specifc thematic context with the students. The various objectives are designated more theoretically by referring to the three objectives of usable knowledge production intro duced in Chapter 2, which are the production of systems knowledge, tar get knowledge, and transformational knowledge. In the context of usable knowledge production on sustainability transformations, systems knowledge covers the interdisciplinary analysis of the socio ecological system interde pendencies. The second, so called target knowledge, addresses the legitimate goals that society “should set in order to create an improved or transformed system” (Pearce et al., 2018, p. 168). The third, transformation knowledge, deals with the strategy to adopt “to get where we want to go” (ibid), which implies engaging with the perspectives of the change agents and identify ing the socially most relevant value related orientations in the given feld of sustainability transformations. As stated by the authors, this focus on value related discussion in the courses represents a paradigm shift “from relying on science to describe and to explain phenomena in the world to expanding its use for also clarifying societal goals (target knowledge) and how to get to those goals (transformation knowledge)” (ibid, p. 169; see also König et al., 2021). Two courses provide a good illustration of this approach to transdisci plinary learning. The frst course is called “Transdisciplinary Case Study” and can be selected by all the students of ETH. Within this program, the students co construct a research item with stakeholders around solutions to a society wide sustainability challenge. During the course, the students must collaborate with stakeholders to defne the relevant research questions, work in an interdisciplinary team, and frame the case and its content from a variety of perspectives. The second course was an eight day extracurricular course designed for Ph.D. and post doc students, the so called TdLab Winter School “Science meets practice,” organized nearly every year from 2011 to 2020 (Staufacher et al., 2012; Pearce et al., 2018, 2022). In these Winter Schools, Ph.D. and post doc students engaged during a full week with the residents of a small town in Switzerland to collaboratively frame problems encountered by these residents and learn from each other, using stakeholder workshops and other transdisciplinary knowledge co production tools and methods. Coached by experienced transdisciplinary researchers, the goal was to pro vide an opportunity for the students to learn how to make a meaning ful connection between their own research and the concerns of the wider public. The teaching program in Gothenburg, Sweden, connected to both Gothenburg University and Chalmers University of Technology, shows a 134 Developing integrated boundary-crossing organizational networks second set of prominent initiatives on transdisciplinary teaching at the uni versity in the context of the Mistra Urban Futures research consortium (Hemström et al., 2021, ch3). The course for doctoral students organized from 2017 to 2019 is a good illustration of initiation into knowledge co production processes. The practice based core of the course was formed by the case studies conducted in Gothenburg on just and sustainable city development as part of the larger research program at the center. Each com ponent of the course addressed one case study, developed through diferent themes including holistic thinking, collaborative methods, border manage ment, and transdisciplinary theory. Knowledge co production was fostered by combining perspectives, literature, and lectures, from researchers and practitioners in all of the themes. Joint deliberation over legitimate and rel evant sustainability challenges was structured via group work and in a col laborative writing process. In the collaborative writing process, researcher and practitioner pairs focused on sustainability challenges in their current work and an evaluation of the transdisciplinary research process (ibid, p. 85). A third example of active knowledge co production for enabling trans disciplinary training is situated at the master’s thesis level. Since 2019, UCLouvain University, Belgium, through the initiative of a university vice president specifcally in charge of sustainability transformations, has adopted an ambitious sustainability transition plan for the University (UCLouvain, 2023a). One core activity for promoting transdisciplinary research in the sus tainability transition plan is the transdisciplinary “Oikos” master thesis pro gram, launched at UCLouvain in 2021 by the Louvain Learning Lab and the research platform for transdisciplinary research (LPTransition) (UCLouvain, 2023b). The Oikos master theses are conducted by pools of students from difer ent disciplines on topics co constructed with research directors from vari ous disciplines and societal actors. In the context of this program, potential research directors interested in the initiative are invited to participate in a major “search conference” that takes place every year to form pools around topics that cross the boundaries between the social and natural sciences and provide a clear added value for understanding socio ecological interdepend encies. Following the discussions in the search conference, the research direc tors of a given pool meet in the next academic year to fne tune the proposed research questions and propose these to the students in master 1. In master 2 and the second part of master 1, the students who have chosen the pro posed topic form a group that regularly meets to foster synergies and mutual enrichment of the work in their respective master theses. The originality of these group based thesis projects is to give a large place to knowledge co production and social learning in the formation of groups that work on a common research topic. Developing integrated boundary-crossing organizational networks 5.3.2 135 Fostering knowledge exchange on transdisciplinary process features The second important task for the building of a truly integrated fexible net work organization of transdisciplinary research is the organization of the network clusters for knowledge exchange on transdisciplinary process fea tures and project outcomes. As stated earlier, these network clusters for knowledge exchange can be quite specifc. However, they may address issues that are relevant to all kinds of transdisciplinary research. For instance, researchers and societal actors can work in thematic clusters that address specifc sustainability transforma tion areas. In other cases, research partners may gather without specifed thematic concern but organize knowledge exchange for a sub group of the community such as doctoral students. They may build knowledge exchange platforms around cross cutting meta issues, such as evaluating protocols or certain features. For instance, the Leuphana University in Lüneburg, Germany, actively invested in such knowledge exchange platforms in the context of strengthen ing its ecosystem of transdisciplinary research projects (Ahrend and Podann, 2021). Since 2006, the university reorganized its faculties and departments in an interdisciplinary and transdisciplinary way around grand societal chal lenges directly related to societal actors’ demands in the area around the university. According to scholars of transdisciplinarity, the success of this case espe cially regards establishing an inter faculty center for transdisciplinary research methods, which can raise transdisciplinary research at the heart of the uni versities’ activities. In particular, the key strength of the inter faculty center is related to the building of a high level joint understanding of transdiscipli nary process values in Leuphana university, while fostering an increase in the degree of formal institutionalization of the center (Vienni Baptista and Rojas Castro, 2020). Indeed, instead of centralizing the sustainability issues in a new overarching institute, which is challenging to integrate with the co constructed nature of each transdisciplinary research perspective on specifc sustainability transformations, the center established a research enabling relationship with the existing disciplinary departments by organizing knowl edge exchange and capitalization around ongoing transdisciplinary research projects. The example of Leuphana University is not a standalone initiative, even though it is remarkable in the scope of the involvement of the universi ty’s central management. Many research organizations established, on a more decentralized basis, so called communities of practice to exchange knowledge on key process features of transdisciplinary research. As stated by Schneider et al. (2019, p. 31), such communities of practice “want to 136 Developing integrated boundary-crossing organizational networks improve their competences and practices through sharing experiences, refecting on own practices and values, and engaging in or learning from research.” Through its link with practice, knowledge co production with societal actors is a key aspect of the communities of practice. For instance, as suggested by Schneider et al. (2019), these communities can “create refective spaces by connecting interested actors, enhance refexivity by mir roring their practices, and presenting alternative perspectives or help actors to better understand the context they are working in or causal relations they are not aware of” (ibid). Many network enabling initiatives explicitly refer to this concept. One example is the Community of Practice on change oriented approaches in Partnership Research in Agronomy, established in February 2021 at the International Cooperation Center in Agronomic Research for Development (CIRAD) (Louaf et al., 2023). This Community of Practice is directly related to a CIRAD cross sectoral initiative on impact evaluation, which also addresses issues regarding transdisciplinary research. In this context, the Community of Practice organizes knowledge exchange on the ex ante design of impact trajectories and their follow up (Barret et al., 2018; Blundo Canto et al., 2020; and personal communication, coordinator of the Community Practice, 13th June 2022, Agropolis International, Montpellier, France). A key feature, in line with the general discussion on communities of practice, is the active inclusion of practice partners in this initiative, such as the mem ber organizations of the network of development cooperation organizations F3E (2023). A third initiative regards the “Louvain4” research clusters organized at UCLouvain, Belgium. They are quite similar to the communities of practice (UCLouvain, 2023c). The Louvain4 clusters stem from a bottom up team formation around fagship themes for organizing integrated interdisciplinary and practice related research on topics such as water governance, energy, or food. Through this clustering in smaller well identifable thematic communi ties, the idea is to develop knowledge transfer on transversal issues and build specifc competences for transversal work. Telling examples of the success of this process of building network clusters around integrated interdisciplinary research are the follow up collaborations on the impact of extreme weather events at the level of municipalities. Indeed, after the extreme weather of 2021, various municipalities contacted the university to update the maps for the prediction of fooding, which are not adapted to the most recent data on the likely impacts of climate change. The success in setting set up these new collaborations in such a short time is a direct result of the preliminary work on team identifcation and building synergies among various disciplinary competences dealing with water governance issues at the university. Further, to complete this overview of enabling knowledge exchange in boundary crossing networks, it is important to mention the role of Developing integrated boundary-crossing organizational networks 137 inter university initiatives. Indeed, the illustrations in this section mainly focused on internal organizational innovations at each university, as these are likely to provide the best long term guarantee for the institutionaliza tion of transdisciplinary research. Nevertheless, inter university initiatives also play a key role in contributing to the consolidation of knowledge on transdisciplinary processes. In Europe, the long standing involvement of the Swiss Academy of Sciences in various enabling activities around the team of the “Network for Transdisciplinary Research” (Swiss Academies of Arts and Sciences, 2023) is a prominent example of such highly efective inter university initiatives for promoting transdisciplinary research. 5.3.3 Knowledge co-production and social learning in social networking among potential project partners The third enabling function—social networking among potential project partners—has a cross cutting nature, as it has an impact on the identifcation of potential partners in the various teaching and knowledge clustering initia tives and the programming of new research avenues in project work. The initiatives organized at the Technical University of Berlin (TU Berlin) provide a good example of the organization of open ended meetings for pro spective team formation and strategic research programming. Since 2014, TU Berlin promotes transdisciplinary research through a combination of cen tralized management initiatives and enabling bottom up team formation and knowledge exchange (Ahrend and Podann, 2021). As a frst step, the cen tralized management of the university organized university wide discussion arenas to defne fagship themes for transdisciplinary research. In the second step, the researchers were invited to network their respective research pro jects around these transdisciplinary research themes. Finally, in the third step, the university launched a series of pilot projects on some of these themes. In each of these pilots, societal actors play an active role as research partners to co design the research frameworks and co validate the results through col laborative knowledge transfer. Along with the role of these open ended meetings in the gradual institu tionalization of research clusters and transdisciplinary pilot projects, the TU Berlin team has contributed to the transdisciplinary research program of the Berlin University Alliance, comprising TU Berlin, Humboldt University, Freie Universität, and Charité Universitätsmedizin Berlin. A highly original activ ity of the University Alliance in this context is the so called research fora on grand challenges. These research fora, not unlike the “search conferences,” gather researchers from partner universities to co construct socially relevant and legitimate research perspectives with societal actors around selected top ics of sustainability (University Alliance, 2022a). According to the organizers, each forum contributes to more permanent structures for transdisciplinarity 138 Developing integrated boundary-crossing organizational networks in the Alliance by implementing “innovative formats, new collaborations and networks” (University Alliance, 2022b). 5.4 New management functions for boundary-crossing network integration Studies on the governance of fexible networks and overcoming possible net work failures provide key insights into the main ingredients for realizing an organization wide institutionalization process of transdisciplinary research. From the review in this chapter, a combination of a set of new horizon tal network enabling functions, along with the adjustment of conventional centralized management functions to the needs of transdisciplinary research, is a promising way to successfully support the institutionalization process. Distilling some of the key lessons of this literature (Kuipers et al., 2018, pp. 272–304) and the examples reviewed, it is possible to highlight the fol lowing governance features contributing to the efective institutionalization of transdisciplinary research: At the level of the adjustment of centralized management functions: • Promote the hiring of professors with transdisciplinary research compe tences in various specifc disciplinary felds of expertise • Earmark funding streams for so-called strategic research on grand societal challenges, which require transdisciplinary competences • Develop specialized generic services for supporting transdisciplinary meth odologies, such as training in specifc workshop formats with societal actors on co constructing research designs • Embed the promotion of transdisciplinary research within the more gen eral procedures for democratic decision making and strategy formulation within the organization At the level of the enabling functions for fostering the integration of bound ary crossing networks: • Promote the building of transdisciplinary competences in the courses at the Bachelor’s, Master’s, and Ph.D. levels by integrating • active discussion with societal actors on problem co-construction • learning on value-related issues that impact the design of the research framework (for instance, on sustainability orientations in a specifc feld of investigation) • Organize knowledge exchange clusters on transdisciplinary process fea tures by • involving existing transdisciplinary researchers and teams that wish to initiate transdisciplinary research Developing integrated boundary-crossing organizational networks 139 • involving academic research and societal actors in clusters on the matic areas of concern in various specifc felds of sustainability transformations • Enable social networking for transdisciplinary team formation, in par ticular through open ended workshop formats leading to the co design of socially relevant and legitimate questions among emerging teams for transdisciplinary teaching or research Even though each of the three decentralized enabling functions of collabo ration in a fexible network organization (focused on organizing training, knowledge exchange, and social networking) results in diferent organi zational tasks, it is important to underline the many synergies that exist between them. These synergies create various opportunities for students and researchers to become involved in transdisciplinary research at various stages of their curriculum. For instance, an early experience with trans disciplinary research to address a given sustainability issue at a master’s student level can be a stepping stone for participating in a more in depth transdisciplinary research project in the same feld at a later stage. Another pathway for involvement runs from interdisciplinary to transdisciplinary research. For example, a researcher who participates in a specifc task of interdisciplinary mixed methods research in a transdisciplinary research project may become interested in understanding the process of the research co design in transdisciplinary collaborations better. In a workshop that gathers research partners from several projects, they might subsequently get involved in knowledge exchange on various process features of trans disciplinary knowledge co production. Further, to strengthen the possible synergies between the research enabling functions, scholars underline the importance of the social interactive and emotional features of collaboration across heterogeneous actors. Creating a feeling of belonging to a group within a fexible network with very het erogeneous members and diverse ongoing projects might be quite challeng ing (Kuipers et al., 2018, pp. 428–429). Indeed, scholars of transdisciplinary research underline the importance of emotional and social interactional dimensions for building efective knowledge commons. Such features include collaborative culture, a climate of conviviality, and promoting positive feel ings about network members, including respect, admiration, and recogni tion (Lux et al., 2019, p. 188; Pohl et al., 2017, p. 23). The emotional and social interactional features can be especially challenging to promote in the distributed network of heterogeneous and distributed boundary crossing transdisciplinary research commons. Therefore, it is important to invest in various mechanisms to improve these social interactional and emotional dimensions of teamwork, such as the strengthening of “a climate of con viviality, social interactive qualities of the participants, efective leadership, 140 Developing integrated boundary-crossing organizational networks meaningful personal relations, group identity, complementary team roles and socializing outside meetings” (Boix Mansilla et al., 2016, p. 589). Finally, as also highlighted by Kuipers et al. (2018), introducing new tools for fexible networking while staying under the general umbrella of a con ventional functional hierarchy is unlikely to be sufficient to generate an efec tive uptake of the fexible network architecture. On the contrary, members can perceive new measures as just another constraint imposed by the central managers who remain in their role of task supervision from a hierarchical management perspective. This situation, in turn, might induce frustration or loss of time among the members who invested their eforts in new horizontal and fexible organizational practices. Regarding transdisciplinary sustainability research, implementing the various tools for transdisciplinary collaborations while under the general umbrella of disciplinary research divisions and centralized monitoring may induce similar frustrations regarding inconsistent institutional incentives. Therefore, without actively integrating the envisioned measures for support ing fexible boundary crossing networks in a comprehensive institutional strategy, the practices of transdisciplinary co production and partnership based social learning may remain limited to a few institutional niches. In such cases, the investment in sustainability research may fail to reach a sufficiently large critical mass of opportunities for learning by motivated researchers from various disciplines or stakeholders with specifc thematic knowledge interests. Moreover, without a general institutional strategy, the niches for trans disciplinary research may only survive in areas where they are promoted by external incentives, such as business oriented partnerships or specifc advo cacy coalitions, instead of organizing support for diferent groups of trans disciplinary research partners on various topics of concern. Obviously, for a broader involvement of various types of research partners and topics, special attention should be given to empowering research and societal actors with fewer resources and initial capacities to step into transdisciplinary research. The possible failures of institutionalization of organizational networks for transdisciplinary research hint at an important cross cutting challenge of building fexible network based organizations. This challenge is the embed ding of the networks in more general procedures for democratic decisions within the organization by discussing the purposes of these networks within the established collective decision making procedures of the organization. There is extensive scholarship on the various approaches to this question of organizing democratic governance of organizational networks (see for instance Dryzek, 2002; Sørensen and Torfng, 2007). Some common princi ples highlighted in this literature are the expansion of the concerned actors to be involved in the collective decision making; that is, involving spokesper sons of the transdisciplinary research communities, extending the scope of Developing integrated boundary-crossing organizational networks 141 the issues addressed in the deliberations, and promoting the efective partici pation by all (Dryzek, 2007). A more in depth analysis of the application of these democratic standards to the institutionalization of fexible network architectures falls outside the scope of the analysis of institutional design of transdisciplinary knowledge co production in this book. 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Research forums. www.berlin university alliance.de/en/ commitments/knowledge exchange/research forums/index.html. Accessed 17 Oc tober 2022. Vienni Baptista, B. and Klein, J. T. (Eds.). (2022). Institutionalizing interdisciplinarity and transdisciplinarity: Collaboration across cultures and communities. Abing don: Routledge. Vienni Baptista, B. and Rojas Castro, S. (2020). Transdisciplinary institutionaliza tion in higher education: A two level analysis. Studies in Higher Education, 45(6), 1075–1092. Weisbord, M. R. and Janof, S. (1995). Future search. New York: Berret Koehler. Williamson, O. E. (1996). The mechanisms of governance. Oxford: Oxford Univer sity Press. 6 IMPLEMENTING KNOWLEDGE COPRODUCTION ON SUSTAINABILITY TRANSFORMATIONS IN ACADEMIA AND BEYOND The analysis in this book of over three decades of transdisciplinary sustain ability research shows the urgent need for new modes of organizing scientifc research. The reform of the science fabric is particularly urgent, given the multiple social and ecological crises humanity is facing today. As aptly sum marized by Christian Pohl et al. (2021, p. 19), these new modes of transdisci plinary research can be characterized by (1) specifc process features based on knowledge co production among partners who actively explore boundaries as learning opportunities and (2) specifc research outputs regarding the pro duction of transformative and critical knowledge on sustainability challenges. The frst characteristic highlighted by Pohl et al. (2021) requires the organi zation of knowledge co production processes that transcend the conventional separation between various knowledge types, such as between practition ers’ and researchers’ knowledge and between descriptive and normative per spectives on societal transformation. Indeed, transdisciplinary sustainability research aims to grasp the complex coupled dynamics of social and ecologi cal systems at multiple scales with heterogeneous societal actors. Thus, trans disciplinary research partners mobilize both case specifc knowledge, which is often non codifed, and more generic interdisciplinary scientifc knowledge frameworks to analyze feasible real world transformation pathways. The organization of these boundary crossing knowledge generation pro cesses is neither an attempt to produce an illusionary unity among hetero geneous perspectives nor a means to highlight irreducible diferences that stife all possibilities of collaboration. On the contrary, in transdisciplinary research, boundaries are actively explored as opportunities for learning from diferent perspectives. As underlined by Akkerman and Bakker (2011), based on this mutual learning, participants in boundary crossing practices can DOI: 10.4324/9781032624297 7 This chapter has been made available under a CC BY NC ND 4.0 international license. Knowledge co-production in academia and beyond 145 develop various socially negotiated modes of interaction, ranging from the simple recognition of a shared problem space to coordinated action, continu ous joint work, or the co construction of new common action strategies. The second characteristic, the production of transformative and critical knowledge, regards the open ended and pluralistic nature of sustainability challenges. Indeed, the coupled dynamics between social and ecological sys tems can induce a plurality of feasible and desirable sustainability transfor mation pathways. Therefore, researchers and societal actors must understand the socially legitimate and relevant values that orient the context specifc choices among this diversity of possible pathways. This understanding has a transformative dimension for both societal actors and researchers. First, understanding specifc sustainability transformations requires the identifca tion of the most relevant sustainability challenges from the perspective of the societal change agents that drive the societal transformations in the spe cifc context. Second, addressing specifc sustainability transformations also involves a critical stance from the researchers. Indeed, some of the necessary changes may challenge the dominant value based frameworks that inform socio ecological modeling practices. By disregarding social learning on these value based frameworks, the research outcomes might perpetuate unsustain able practices or maintain unbalanced power relationships to the beneft of the incumbent actors. However, for the individual researchers, societal actors, and research man agers, given the long history of the specialized disciplinary organization of research, a main challenge regards the implementation of such boundary crossing and transformative knowledge generation processes in practice. For sure, there is no single best way forward, and each research organization must consider the local constraints in developing these tools and mechanisms. Further research is therefore needed to document the various options to do so and to build so called toolbox environments providing inspiration and advice (see, e.g., https://itd alliance.org/ and https://transdisciplinarity.ch/en). Nevertheless, the literature review and case study analysis in this book give some indications of research questions on the measures that are needed to further build a larger organizational network of transdisciplinary research commons. In the frst place, the analysis shows that regarding transdisciplinary knowl edge co production, research funders, policy officials, and research managers should strive to multiply the opportunities for knowledge co production by researchers and societal actors in research projects on sustainability trans formations. These opportunities can be quite modest, such as through the inclusion of a transdisciplinary case study chapter in a Ph.D. project or a transdisciplinary analysis of a sub topic by a researcher within a conven tional multi disciplinary consortium. Alternatively, they can include more comprehensive transdisciplinary initiatives, such as the funding of research 146 Knowledge co-production in academia and beyond projects or consortia that orchestrate the co construction of research design and co validation of results throughout the entire research cycle. Multiplying such opportunities for the emergence and implementation of transdiscipli nary initiatives is especially important, as no centralized approach to the consolidation of transdisciplinary research is likely to cover the diversity of societal actors and knowledge types mobilized in each case specifc transdis ciplinary knowledge co production process. Further, to meet the social learning needs on sustainability values, each transdisciplinary research project should foresee the possibility of investing time and resources in structuring the space of the diferent value perspec tives of societal actors and researchers. Indeed, as in the various case stud ies, the growing scope and impact of the interdependencies between social and ecological systems imply the development of new environmental, social, and civic value orientations that forsake the modern myth of continuous growth with unlimited resources. Most of these values, such as the orienta tion toward environmental justice or reconciliation of human prosperity with planetary boundaries, are intensely debated. Depending on the specifc feld of sustainability transformations and the involved societal actors, the disrup tive learning of sustainability values can be somewhat consensual among the partners, inducing various degrees of convergence. In other cases, the learn ing will be more critical, such as when powerful interests attempt to perpetu ate unsustainable development paths. Moreover, a set of measures at the level of research organizations can contribute to consolidating the transdisciplinary knowledge commons. As discussed, important mechanisms for the integration of the boundary crossing networks built around the transdisciplinary research projects are the overall building of transdisciplinary competences, social networking for partner identifcation, and systematization of knowledge exchange on modes of organization of knowledge co production and social learning. Hence, to support these cross cutting mechanisms, research organizations can create new professional profles and promote transdisciplinary research skills. For instance, research organizations can organize a supporting service to accompany teachers who implement transdisciplinary competence building in teaching curricula. Such a service could train a dedicated staf person to assist organizational units and departments to promote teaching practices based on knowledge co production with societal actors on specifc sustain ability transformation topics. As discussed in Chapter 5, such teaching cur ricula reform might include full fedged transdisciplinary partnerships with real world actors, such as in the collaborative visioning exercises organized with partners in the city of Gothenburg in the context of the course for doc toral students organized at the University of Gothenburg. In other cases, it may focus on specifc transdisciplinary competences, such as the analysis Knowledge co-production in academia and beyond 147 of real world case studies in the courses on sustainable development at the TdLab of the Swiss Federal Institute of Technology (ETH). Likewise, research organizations might organize supporting services for social networking among potential project partners of transdisciplinary research projects and teaching initiatives. These social network building activities could take the form of so called search conferences discussed in Chapter 5. The search conferences are open ended meetings to identify and defne possible topics for knowledge co production among societal actors and various disciplinary researchers. Examples of such meetings include the sandpit workshops funded by the UK Research and Innovation Council (Bridle et al., 2013; UKRI, 2021) or the transdisciplinary research fora on grand challenges organized by the Berlin University Alliance (see Chapter 5), to cite just a few. Other initiatives for transdisciplinary network building may be organized at the master’s student level, such as the interdisciplinary and transdisciplinary master thesis project on sustainability development at UCLouvain (see Chapter 5) or the master theses of the citizen academy organ ized by the University of Ghent (Block et al., 2022). The distinguishing feature of these various transdisciplinary network building activities is the fact that the teams are constituted based on discussions to explore a common research design on interdependent social and ecological system dynamics. Given the partnership dimension of transdisciplinary research, network building activi ties cannot be dissociated from the identifcation of potentially productive areas of knowledge co production on sustainability transformations. A third area of organizational support for consolidating transdisciplinary research commons concerns the systematization of knowledge exchange on transdisciplinary process features. By organizing knowledge exchange on process features, research organizations can strengthen the capacities of researchers and societal actors to conduct transdisciplinary research on a broad variety of topics of concern. Moreover, by organizing various oppor tunities for knowledge exchange in thematic clusters and in more generic organization wide initiatives, research organizations can create additional support for researchers and societal actors with less access to learning plat forms on process features. An example of such a platform is the “Liaison and Transfer Organisations on Social Innovation,” established at various universities in Québec. These platforms connect societal actors and research ers to create a discussion on the co validation of transdisciplinary project results and transdisciplinary approaches in various thematic areas of socio ecological research (Dagenais et al., 2008). As discussed in Chapter 5, the cross cutting activities of knowledge exchange on process features allow researchers and societal actors to identify further needs for co validation or explore opportunities for using certain tools and mechanisms for knowledge co production and social learning in new thematic areas of inquiry. 148 Knowledge co-production in academia and beyond To wrap up this journey through these diferent organizational and insti tutional measures, it is important to indicate some limits of our analysis and highlight perspectives for future research. The analysis in this book focused on transdisciplinary knowledge commons for sustainability research. Though important, the analysis did not dig deeper into the contributions of the purely disciplinary, multi disciplinary, and interdisciplinary research projects that address sustainability issues. In many cases, these more conventional approaches are mobilized to furnish more insight into well identifed sub system components or operate within relatively well defned value orienta tions, such as in calls for proposals on the implementation of policy measures for sustainability transformations, as defned ex ante by research funders. However, in practice, the boundary between purely transdisciplinary research, where co constructing research design with societal actors plays a central role throughout the research, and conventional research prac tices is not always clear cut (Klein, 2010). Conventional research practices often include consultation and feedback from societal actors, though with out including them as full fedged partners in the knowledge co production process. When researchers and societal actors intensify the consultation and feedback activities, the research process may be gradually adjusted to include transdisciplinary process features. The case of so called broad interdisciplinarity can illustrate this point. According to the analysis of Klein (ibid), broad interdisciplinarity is char acterized by research that bridges disparate approaches—for instance ecol ogy and history—and develops comprehensive general views or synthetic frameworks (cf. also Pohl et al., 2021). In broad interdisciplinary research, research partners face heterogeneous methodologies, distinct approaches to problem identifcation, and a diversity of diferent conceptual frameworks. Hence, even when societal actors are not directly involved in building a com mon research design, the collective action challenges them to bridge the dif ferent knowledge types that are often similar to the case of transdisciplinary research. For instance, interdisciplinary knowledge co production can also be hampered by the instrumentalization of the research process by one of the partners who mainly focus on their disciplinary knowledge interests or by unstructured diversity of conceptual approaches. Given this proximity of the collective action problems, transdisciplinary research can beneft from the lessons learned from knowledge co production in such broad interdisciplinary research projects. Moreover, from the case study analysis, broad interdisciplinarity is often a key ingredient of trans disciplinary sustainability research. In such cases, learning about knowledge co production in broad interdisciplinarity may directly contribute to the suc cessful implementation of transdisciplinary research processes. Another illustration of the gray zone between transdisciplinarity and some more conventional modes of research organization is the case of so called Knowledge co-production in academia and beyond 149 mission oriented research. As discussed in a widely disseminated discus sion paper by Mariana Mazzucato (2018), mission oriented research is a key problem solving centered research approach to innovation that is often embedded in calls for proposals on grand societal challenges, such as cyber security, mental health, or sustainability issues. Often these calls for propos als do not formally require transdisciplinary knowledge co production with societal actors. Moreover, these calls are often defned regarding measurable and time bound targets or require project consortia to provide such targets regarding so called key performance indicators. However, as highlighted throughout the book, research funders can nei ther always specify ex ante the full scope of relevant problems to address nor identify the list of societal actors to include to discuss the value related issues. It may be related to the value laden nature of the desirable societal solutions to some of the grand societal challenges or path dependent con straints on real world social possibilities for implementing these solutions. Therefore, in practice, research funders often favor projects that also propose some level of knowledge co production with societal actors throughout the research process. In such cases (as in the case of broad interdisciplinarity), the overlap between collective action problems encountered in mission driven research and transdisciplinary research can create fruitful opportunities for cross fertilization between successful research practices. A second limit of the analysis in the book is related to the collaboration with other transdisciplinary researchers beyond the feld of sustainability research. Indeed, the book focuses on transdisciplinary sustainability research and does not explore the many overlaps with other transdisciplinary areas of investigation that do not have a specifc focus on sustainability (Hirsch Hadorn et al., 2008). Although such exploration is beyond the scope of this book, the general defnition of transdisciplinarity that is used for the analysis hints at such a further dialogue. Indeed, as specifed in the introduction, the book uses a general defnition of transdisciplinarity as an approach that is broadly interdisciplinary and based on a research partnership with societal actors. Moreover, as devel oped in depth above, this partnership is characterized by a set of process features (regarding knowledge co production for integrating diferent knowl edge types) and the production of transformative and critical knowledge out puts. This general defnition is highly relevant to the broad feld of research on sustainability. As articulated through the various examples analyzed in the book, the combination of broad interdisciplinarity and knowledge co production with societal actors can efectively tackle socio ecological system interdependencies with heterogeneous value perspectives on the overall ori entation of the system dynamics. However, as amply illustrated by the systematic review of transdiscipli nary scholarship by the Swiss Academies of Arts and Sciences (2023), this 150 Knowledge co-production in academia and beyond general approach is also highly relevant and widely used in other felds of advanced research on society wide challenges. Some of the theoretical discussions in the book already referred to some of these felds, such as collaborative planning research in urban studies (see Section 3.1.1) or the socio technical approach to living labs (see Section 3.2.1). The illustrations in this book focused on cases in these felds of research that deal with sus tainability issues in socio ecological systems. Nevertheless, many of these cases also covered research felds that address other issues, such as social welfare concerns in urban neighborhoods (see Section 3.2.4) or research on socioeconomic distributional consequences of technological choice (see Section 4.3.3). Other prominent felds of research illustrate the use of this general approach for transdisciplinarity based on combining broad interdisciplinar ity and partnership research. One case in point is the feld of research in the social economy in Québec, which develop a broad set of transdisciplinary research practices through over two decades of research funding for so called community research alliances (Hall and MacPherson, 2011). Other exam ples, in a diferent feld, are partnerships between scientifc researchers and societal actors for translation research in criminology, focusing on the pro cess through which criminological research is generated and used by practi tioners and policymakers (Pesta et al., 2019). Obviously, even though these research felds all develop transdisciplinary modes of organization, the organization of the knowledge co production and social learning process will be based on choices that are specifc to each area of investigation. Nevertheless, the use of broad interdisciplinarity and partnership approaches in diferent felds creates cross fertilization opportu nities. These opportunities cover knowledge exchange on transdisciplinary process features and their usefulness to tackle various collective action chal lenges in building transdisciplinary knowledge commons. Furthermore, at the institutional level, the experience acquired from successful transdiscipli nary research in these diferent felds may also contribute to the broad rec ognition of transdisciplinarity as a promising mode of organizing scientifc research on complex societal challenges. Therefore, this recognition may be promoted by identifying, within a given research organization, the similari ties between various felds of transdisciplinary research and jointly exploring and supporting the design features for successful transdisciplinary knowledge co production. Finally, the analysis in the book mainly focused on transdisciplinary research at universities, high schools, and national research organizations as the key players for organizing transdisciplinary research of a more basic and applied nature. However, along with the development of transdis ciplinary research in the academic environment, a wealth of associations, Knowledge co-production in academia and beyond 151 entrepreneurs, and managers in public administrations are using tools from transdisciplinary research in applied settings (OECD, 2020). The strength of the academic transdisciplinary research approaches is to combine the production of transdisciplinary knowledge with an interest in generic methodological and theoretical development and contribute to knowl edge transmission, education, and competence building. On the other hand, the strength of the applied and directly policy related approaches is the strong motivation of societal actors to reach a broad critical mass of transdiscipli nary research practices. Even though such approaches do not systematically strive at peer review validation of the research outputs, as is the case in aca demic research, policy related transdisciplinary research practices ofer invalu able opportunities for further mutual learning on boundary crossing research practices. Overall, the entry point in this book on transdisciplinary sustainabil ity research in academic research therefore hints at a much broader feld of work, which includes broad interdisciplinary approaches with extensive social actor interaction, related felds of transdisciplinary research on grand societal challenges, and directly policy related transdisciplinary research practices. Given the many complementarities between the approaches, the best way forward to foster the urgently needed sustainability transformations is to explore the many synergies between the diferent approaches to support various collective learning processes on feasible and desirable interdependent sustainability transformations of social and ecological systems. References Akkerman, S. F. and Bakker, A. (2011). Boundary crossing and boundary objects. Review of Educational Research, 81(2), 132–169. Block, T., Prové, C., Dehaene, M., Abeele, P. V. and Beeckmans, L. (2022). Under standing urban sustainability from mode 2 science and transdisciplinary educa tion: How Master Thesis Ateliers of the Ghent Stadsacademie tackle wicked issues. Environment, Development and Sustainability, 1–26. Bridle, H., Vrieling, A., Cardillo, M., Araya, Y. and Hinojosa, L. (2013). Preparing for an interdisciplinary future: A perspective from early career researchers. Futures, 53, 22–32. Dagenais, C., Janosz, M. and Dutil, J. (2008). Étude des besoins des chercheurs de l’Université de Montréal en matière de transfert des connaissances issues de la recherche. Bureau de la Recherche Développement Valorisation. Université de Mon tréal, Montréal, Canada. Hall, P. V. and MacPherson, I. (2011). Community-university research partnerships: Refections on the Canadian social economy experience. Victoria, Canada: Uni versity of Victoria. Hirsch Hadorn, G., Hofmann Riem, H., Biber Klemm, S., Grossenbacher Mansuy, W., Joye, D., Pohl, C., . . . and Zemp, E. (Eds.). (2008). Handbook of transdisciplinary research. Dordrecht: Springer. 152 Knowledge co-production in academia and beyond Klein, J. T. (2010). A taxonomy of interdisciplinarity. In R. Frodeman, J. Thomp son Klein and C. Mitcham (Eds.), The Oxford handbook of interdisciplinarity (pp. 15–30). Oxford: Oxford University Press. Mazzucato, M. (2018). Mission-oriented research and innovation in the European Union. Final Report. Publications Office of the European Commission, Luxembourg. OECD. (2020). Addressing societal challenges using transdisciplinary research. OECD Science, Technology and Industry Policy Papers 88, OECD Publishing, Paris. Pesta, G. B., Blomberg, T. G., Ramos, J. and Ranson, J. W. (2019). Translational criminology: Toward best practice. American Journal of Criminal Justice, 44(3), 499–518. Pohl, C., Klein, J. T., Hofmann, S., Mitchell, C. and Fam, D. (2021). Conceptualising transdisciplinary integration as a multidimensional interactive process. Environmental Science and Policy, 118, 18–26. Swiss Academies of Arts and Sciences. (2023). Network for transdisciplinary research. https://transdisciplinarity.ch/en/about td net/. Accessed 4 January 2023. UKRI. (2021). Sandpits. www.ukri.org/councils/epsrc/guidance for applicants/types of funding we ofer/transformative research/sandpits/. Accessed 1 February 2023. CONCLUSION Contemporary sustainability challenges, characterized by socio ecological interdependencies of unprecedented scale, require new modes of knowledge generation to identify feasible and desirable transformation pathways. In this context, conventional disciplinary and expert led only modes of research organization seem ill suited for managing the wicked problem features of many sustainability issues, such as strongly coupled social and ecological system dynamics, value controversies over sustainability orientations, and the involvement of societal actors in cross sectoral and multi scale actor networks. Diferent types of transdisciplinary research have emerged over many years in response to these challenges, labeled partnership research (Hoekstra et al., 2020), community science (Khandor and Mason, 2011; Charles et al., 2020), participatory action research (Wittmayer et al., 2014; Chevalier and Buckles, 2013), mode 2 science (Nowotny et al., 2001), and team science (Killion et al., 2018), among others. This book builds upon the experience gained with these transdisciplinary research processes over the last three dec ades, with the objective of strengthening the efectiveness of transdiscipli nary research methods that are mobilized to improve our understanding of society wide sustainability transformations. The core hypothesis of this book is that researchers and societal actors must overcome a series of collective action problems to meet the need for knowledge integration from science and practice in transdisciplinary sustain ability research. This book examined the institutional design of transdisci plinary research processes from the perspective of the theory of knowledge commons to disentangle the basic components of collective action challenges. DOI: 10.4324/9781032624297 8 This chapter has been made available under a CC BY NC ND 4.0 international license. 154 Conclusion In fact, the collective action problems in transdisciplinary research, such as the instrumentalization of the collaborative process by one of the part ners or the lack of coordination among heterogeneous value perspectives, show a great deal of similarity to the problems examined in the theory of decentralized collective goods production through non state collective action, or the so called theory of commons based production. While the theory of the commons initially focused on the community based manage ment of natural resources, it has gradually broadened its scope to other commons based production domains, including immaterial goods, such as knowledge commons. As discussed in Chapter 2, scholars of the commons highlight the impor tance of three general design features that contribute to successfully over coming collective action challenges, which also play a vital role in the case of transdisciplinary knowledge commons. First, to efectively manage the provi sion of common goods in decentralized settings—whether in the community management of natural resources or in scientifc research commons—societal actors need entitlements to develop and implement self organized strategies for decision making and control over collective good provision. Second, as elaborated in the so called second generation collective action theory by Elinor Ostrom (1998), such self organized management is facilitated by the develop ment of common value orientations. The latter contributes to building mutual trust and reduces the efort required to coordinate the production of common action strategies. Finally, decentralized solutions to collective action problems require an appropriate supportive institutional environment. Such an environ ment plays a signifcant role in building the generic competencies of actors who wish to engage in decentralized collective action and social learning. The transdisciplinary research practices reviewed in the diferent book chapters highlight how each of these design features is relevant to transdis ciplinary sustainability research. Specifcally, the qualitative comparative analysis of cases of transdisciplinary sustainability research identifed the fol lowing general design features that play an important role in enhancing the likelihood of successful co production of usable knowledge on sustainability transformations. 1) First, regarding collective action for collaborating on a common trans disciplinary research purpose, the analysis of the various components of knowledge co production in Chapter 3 indicates i. the importance of efectively integrating societal actors’ knowledge (along with the knowledge from scientifc researchers) in the analysis of sustainability transformations of interdependent social and ecological systems Conclusion 155 ii. the importance of the co construction of the research design with soci etal actors, particularly in building a common framework of analysis between heterogeneous disciplinary perspectives and diferent types of knowledge from science and practice iii. the need to involve societal actors and scientifc researchers in co man agement processes of various degrees of strength 2 Second, regarding the common understanding of diverse value orienta tions, the analysis of social learning processes in Chapter 4 shows i. the need to identify demands of societal actors and scientifc research ers for social learning, including learning for reaching improved mutual understanding of sustainability values and structuring of the various perspectives on societal values ii. the contribution of social learning processes on societal values to fos tering processes of convergence over core values and critical decon struction of value perspectives that perpetuate rent seeking and the undue exercise of power 3 Third, regarding the supportive institutional environment, the analysis of the building of larger organizational networks for transdisciplinary research in Chapter 5 shows i. the importance of building fexible boundary crossing networks among diferent disciplines, researchers, and societal actors ii. the contribution of the organization of cross cutting activities for i. the development of transdisciplinary competences in the teaching curricula ii. the organization of knowledge exchange on transdisciplinary pro cess features iii. the networking of researchers and societal actors around copro duced research frameworks on specifc sustainability transforma tion topics. The case studies of transdisciplinary research examined in this book and the analysis of scholarly literature aim to improve our understanding of these design principles. Nevertheless, additional comparative case study research, further feldwork, and systematic surveying is needed to further develop this analysis of the most salient governance mechanism for collective action in transdisciplinary research. Further work might also deepen the epistemological framework of pragma tist constructivism discussed in Chapter 4, which summarizes the core guiding principles of transdisciplinary research as an innovative mode of knowledge 156 Conclusion generation. This epistemological framework combines the key strengths of constructivism, refected in design features such as the co construction of research among researchers and societal actors, and philosophical pragma tism, refected in design features such as the practical building of commu nities of collaborative inquiry through co management and social learning. From a pragmatist constructivist perspective, both scientifc knowledge and knowledge from societal actors contribute to knowledge generation about wicked sustainability problems. Pragmatist constructivism allows searching for a middle ground in transdisciplinary research between the risks of tech nocratic excesses and scientifc dogmatism, on the one hand, and losing any idea of robust and validated scientifc research outcomes as a common good, on the other, through the risk of the reduction of the validity to the outcome of power relationships and social conficts. Finally, the organization of institutional support for transdisciplinary research will involve the development of a new type of research enabling environment, based on interactions within polycentric networks. In particu lar, the enabling of transdisciplinary research places emphasis on crossing disciplinary boundaries and building process competences for boundarycrossing learning* in hybrid networks of societal actors and researchers. The latter competences are essential assets for dealing with diferent stakeholder contexts and transitioning from projects with relatively consensual sustain ability values to those that necessitate carefully managing value conficts. The focus placed in this book on involving researchers and societal actors in integrated polycentric networks as an important governance feature of transdisciplinary research refects similar developments in the more general analysis of polycentric approaches to deliberation in environmental gov ernance. As emphasized by scholars of deliberation, such as John Dryzek, Simon Niemeyer, and David Schlosberg, the institutionalization of delibera tive processes on a larger scale needs to integrate deliberation at local sites with a larger polycentric approach (Schlosberg et al., 2019; Niemeyer, 2020; Dryzek, 2022). This polycentric approach organizes capacity building in a system of nested governance, already called for by Elinor Ostrom in her work on polycentric network governance. However, as underscored by scholars of deliberation, for the wider activation of deliberative capacities, such a polycentric system also needs to implement diferent governance mechanisms for guaranteeing authentic deliberation in each of the problem solving and social learning processes in local sustainability transformations (Owen and Smith, 2015; Niemeyer, 2020; Niemeyer et al., 2023). Although the above arguments on local deliberative capacities are devel oped in a more general framework—analyzing the general conditions for authentic deliberation—they nicely summarize the key message on capacity building for transdisciplinary research in this book. Indeed, the more general discussions on the conditions for efective deliberation hint at the danger of Conclusion 157 dissociating the building of larger institutional systems of transdisciplinary capacity building from the context specifc activities of research co design, co management, and social learning. More specifcally, it allows us to pin down, in a more general manner, the point made in Chapter 5 on combin ing the institutional enabling of transdisciplinary research with activities of knowledge co production and social learning. In short, building larger nested polycentric institutional architectures relies on designing, testing and evalu ating new modes of organization also through co produced activities and processes by societal actors and researchers. The articulation of knowledge co production activities and institutional mechanisms for capacity building implies that a considerable upscaling of transdisciplinary co production will only be possible by involving both academic researchers and a broad array of diferent societal actors in this endeavor. What is the role of citizens or professionals in contributing to transdisciplinary research on society wide transformations in specifc sec tors? What kind of policy mix do we need to promote these collaborative processes that require intense social learning between the involved societal actors around new values and modes of coordination? How can universities support promising trends in transdisciplinary research and produce evidence based knowledge to move from trial and error processes to robust and long lasting societal transformations? These questions are at the heart of initiatives by societal actors, scientists, and policymakers worldwide, who are building new networks and research partnerships to contribute to sustainable human development. Regarding transdisciplinary sustainability research, citizens, members of social move ments, and members of mission driven organizations are partners that con tribute knowledge and information to scientifc endeavors. At the same time, they operate as societal actors fully engaged in collective action in their com munities and social networks. Through their privileged position as change agents, societal actors acquire knowledge of possible solutions, frst hand knowledge of social drivers, and motivations for implementing feasible and desirable solutions for sustainability challenges. Hence, through knowledge co production between scientifc researchers and societal actors, new solution pathways actively promoted by societal actors can co evolve with innovative scientifc perspectives and accelerate sustainability transformation processes. Efective policies must support transdisciplinary research partnerships. Public sector officials are directly involved in the design, planning, implemen tation, and evaluation of the support measures for public research funding. Moreover, through their expertise and access to various policies and social networks, public sector officials provide and use many forms of expertise that can promote sustainability transformations. Policymakers, governments, and public administrators can play primary roles in supporting transdisciplinary research. This role can include both the direct participation of public sector 158 Conclusion officials in transdisciplinary partnership research and, more broadly, the organization of institutional recognition and support for scientifc research ers’ and societal actors’ knowledge co production through transdisciplinary research. Finally, universities play a pivotal role in the emergence and consolida tion of relatively recent transdisciplinary research traditions. First, through the university’s basic research mission, academic researchers add value to transdisciplinary research projects by ofering innovative perspectives and critical refections on transdisciplinary research methodologies. Second, and even more importantly, by actively engaging in transdisciplinary partnership research, universities can provide training and capacity building for a new generation of young scholars and students, who are not yet acquainted with the new set of tools and methods for scientifcally credible and socially robust knowledge co production processes through transdisciplinary research. Thus, universities can actively contribute to the integration of the various approaches developed in transdisciplinary partnership science into the over all science fabric. However, the steps required to achieve these goals are challenging. Indeed, to address multiple social and ecological crises, we need new knowledge to understand the nature of large scale regenerative societal systems, such as sustainable cities, rural territories, and production systems. Moreover, the systemic, multi dimensional, and highly pluralistic nature of collaborative eforts is required to resist the traditional disciplinary and ivory tower modes of conducting scientifc research. Fortunately, as many examples in this book show, researchers at universities and research organizations actively experi ment and innovate with integrated and collaborative modes of transdiscipli nary research to address these challenges. This book aimed to take stock of these inspiring and crucial developments in the context of institutional chal lenges to further consolidate transdisciplinary research in the organization of contemporary scientifc research. References Charles, A., Loucks, L., Berkes, F. and Armitage, D. (2020). Community science: A typology and its implications for governance of social ecological systems. Environmental Science and Policy, 106, 77–86. Chevalier, J. M. and Buckles, D. J. (2013). Handbook for participatory action research, planning and evaluation. Ottawa: SAS2 Dialogue. Dryzek, J. S. (2022). The politics of the earth: Environmental discourses. Oxford: Oxford University Press. Hoekstra, F., Mrklas, K. J., Khan, M., McKay, R. C., Vis Dunbar, M., Sibley, K. M., . . . and Gainforth, H. L. (2020). A review of reviews on principles, strategies, out comes and impacts of research partnerships approaches: A frst step in synthesizing the research partnership literature. Health Research Policy and Systems, 18, 1–23. Conclusion 159 Khandor, E. and Mason, K. (2011). The street health report 2007: Community based research for social change. In M. Kirst, N. Schaefer Mc Daniel, S. Hwang and P. O’Campo (Eds.), Converging disciplines. A transdisciplinary research agenda to urban health problems (pp. 57–68). New York: Springer. Killion, A. K., Sterle, K., Bondank, E. N., Drabik, J. R., Bera, A., Alian, S., . . . and Thayer, A. W. (2018). Preparing the next generation of sustainability scientists. Ecology and Society, 23(4). Niemeyer, S. (2020). Deliberation and ecological democracy: From citizen to global system. Journal of Environmental Policy and Planning, 22(1), 16–29. Niemeyer, S., Veri, F., Dryzek, J. S. and Bächtiger, A. (2023). How deliberation hap pens: Enabling and activating deliberative reasoning. American Political Science Review, 1–18. Nowotny, H., Scott, P. B. and Gibbons, M. T. (2001). Re-thinking science: Knowledge and the public in an age of uncertainty. Cambridge: Polity Press. Ostrom, E. (1998). A behavioral approach to the rational choice theory of collective action: Presidential address, American Political Science Association, 1997. American Political Science Review, 92(1), 1–22. Owen, D. and Smith, G. (2015). Survey article: Deliberation, democracy, and the systemic turn. Journal of Political Philosophy, 23(2), 213–234. Schlosberg, D., Bäckstrand, K. and Pickering, J. (2019). Reconciling ecological and democratic values: Recent perspectives on ecological democracy. Environmental Values, 28(1), 1–8. Wittmayer, J. M., Schäpke, N., van Steenbergen, F. and Omann, I. (2014). Making sense of sustainability transitions locally: How action research contributes to ad dressing societal challenges. Critical Policy Studies, 8(4), 465–485. ANNEX 1 Glossary of key conceptual terms Terms defned in the glossary are marked in italic and with an asterisk upon their frst appearance in the text. Boundary-crossing learning The literature on boundary crossing learning defnes a boundary as socio cultural diferences leading to discontinuities in interaction and action (Akkerman and Bakker, 2011). Defning boundaries as discontinuities rather than diferences without mutual interactions, it becomes clear how bounda ries are real in their consequences while being malleable and dynamic con structs. Diferent forms of dialogue between multiple perspectives can be organized at the boundaries, which can induce boundary crossing learning. Overall, people and objects that cross or stand between boundaries articu late meanings and perspectives of various intersecting worlds while negotiat ing meanings beyond the boundary from which something new may emerge (ibid). Incommensurability of societal values In this book, we follow many authors who defne the incommensurability of societal values in a broad sense. In this broad sense, it designates the impos sibility to establish a comparison between the set of societal values at hand that allows for specifying what societal value choice is better or worse for each of the societal values (Chang, 1997). Thus, the term “measure” does not strictly refer to quantitative measures but to all kinds of justifed choices based on a ranking of the values according to a better worse scale. As argued Annex 1 161 in Chapter 5 and the literature, incommensurability does not lead to the impossibility of choice, as various other criteria can be used to make a justi fed choice. One example among such justifcations is choosing the option that is not overall better but improves the situation per one consideration of importance to all actors (Levi, 2004). Another justifcation is to choose the set of options that satisfes a partial ranking among the values, for which there is a reasonable consensus among societal actors (Sen, 2009). Institutional rules The term “institutional rules” is used in this book according to the con vention in institutional analyses in the social sciences to denote rules gov erning the behavior of actors (Pahl Wostl, 2009). Formal institutional rules are linked to the official channels of governmental bureaucracies. They are codifed in regulatory frameworks or any kind of legally binding document. Correspondingly, they can be enforced by legal procedures. Informal institu tional rules refer to socially shared rules such as social or cultural norms. In most cases, they are not codifed or written down. They are enforced outside of legally sanctioned channels. In this broad context, institutions can be defned as a structural feature of social systems that provides a certain degree of order and stability to social interaction by regulating and afecting the beliefs and behavior of the actors (Sørensen and Torfng, 2007). This defnition covers various approaches in institutional analysis. For instance, in so called rational choice institutional ism, institutions are analyzed according to the rules of the game to which individual actors respond based on their individual preferences (Ostrom, 1990; North, 1999). Sociological institutionalism refers to the set of rules, norms, and cognitive paradigms that shape the identities, capacities, and aspirations of societal actors (Hall and Taylor, 1996). Integrated socio-ecological systems research Socio ecological system research difers in the degree to which the social and ecological are viewed as merely interacting sub systems or part of a single, integrated system (Binder et al., 2013). The interactive approach considers the social and ecological as relatively independent sub systems, with a one way interaction between them, such as the impact of human behavior on eco logical outcomes. The integrated systems approach focuses on the emergent system patterns that result from the strong social ecological system inter dependencies (Schlüter et al., 2019). The interdependencies can result from diferent types of feedback between the social and ecological systems, such as the relation between the impacts of human actions on the ecological systems, the adaptation of the decision making process to the ecological impacts, 162 Annex 1 and the link back to new types of behavior and impacts (Binder et al., 2013). In other approaches, interdependencies result in higher level system proper ties, such as adaptive capacity building in the overall system by enhancing a diversity of solutions to deal with external perturbations (Pahl Wostl, 2009). Knowledge co-production in transdisciplinary research It designates a mode of research based on collaboration between research ers and societal actors to generate scientifcally sound, socially relevant, and legitimate knowledge (Polk, 2015; Pohl et al., 2021). Hence, the collabora tion includes knowledge integration between researchers and societal actors, co designing various components of the research framework (Schneider et al., 2019), and clarifying the societal background values of the research participants (Hirsch Hadorn et al., 2008; Herrero et al., 2019). Research styles The notion of research style is an analytical tool that allows for identifying the emergence of specifc enduring approaches to scientifc inquiry (Hacking, 2012). Historical examples are the research styles of Greek geometry, con trolled experimentation, and statistical analysis (Crombie, 1995). Each research style introduces new types of objects and evidence related to these objects and involves specifc standards of validity of the scientifc statements about these objects (Sciortino, 2017). Moreover, each research style (an epis temological notion) can further be diferentiated into so called community related thought styles. The latter is characterized by the emergence within specifc research styles of communities with a common knowledge base, style of communicative behavior and literary expression, and approach to the problem of interest (Fleck, 1979). Scientific research commons In the general commons based production framework, covering commu nity managed natural resources, urban commons, and knowledge com mons, commons refer to collective goods that are jointly shared, used, and managed by groups of varying sizes and interests (Hess and Ostrom, 2007, p. 5). Especially since the mid 1990s, an increasing number of schol ars started to analyze the conditions for commons based knowledge pro duction to counter the increased production of knowledge behind digital fences or privately owned knowledge providers with the rise of distributed, digital information (Kranich, 2007). Regarding scientifc research, “sci entifc research commons” refers to the many collective aspects of scien tifc research that are jointly used and produced by research communities, Annex 1 163 networks, and umbrella organization researchers (Benkler, 2008). These collective aspects include the quality management of the research results, such as research community managed peer review, the organization of the dissemination of research results, the organization of sharing of pre pub lication and post publication research data and information in research consortia and beyond, and agenda setting of promising research topics to advance research (Frischmann et al., 2014). Social and ecological sustainability This book defnes the sustainability of socio ecological systems from within the framework of mere sustainability, which is the pursuit of environmen tal sustainability while integrating environmental sustainability challenges with wider issues of justice, equity, and governance (Agyeman and Evans, 2004; Coleman and Gould, 2019). The issue of environmental sustainabil ity can be defned along the lines of the defnition of sustainable devel opment by the 1987 United Nations Brundtland Commission as the goal of meeting the needs of the present without compromising the ability of future generations to meet their own needs. The latter implies, as an impor tant sustainability component, considering the planetary resource limits in human development to maintain the functioning of basic life supporting systems and processes on the planet Earth for present and future gener ations (Rockström et al., 2009). However, reaching these goals requires addressing the root causes of unsustainability, regarding the wider issues of justice, equity, and governance. As shown in the literature on environmen tal justice and environmental citizenship, socioeconomic and power related distributive concerns, fair collective decision making processes, recognition of the contribution of all sociocultural groups, and building capacities for meaningful participation of all parties beyond merely formal process guar antees for inclusive governance of all parties in societal transformations (Dobson, 2007; Schlosberg, 2013). Social learning Studies on governing socio ecological systems conceptualize social learn ing as a process of change of understanding in the individuals involved that becomes situated in wider social units given the exchange of ideas, argu ments, and information in social networks and communities of practice (Reed et al., 2010). This defnition provides a criterion for evaluating whether social learning occurred in certain groups and networks without confating the social learning notion with broader expected results, such as generating improved participation or governance outcomes that depend on contribu tions from other factors (ibid). 164 Annex 1 Socio-ecological systems Socio ecological systems are complex adaptive systems characterized by feed back across multiple social and ecological dynamics scales (Fischer et al., 2015). In the literature on socio ecological systems, the term “social” is used in a broad sense to include various behaviors of individual human beings in social contexts, the social relationships between human beings, and the evolution of cultural cognitive meanings among human beings (Levin et al., 2013; Hicks et al., 2016). Thus, the term “socio ecological systems” is used as a synonym for coupled human environment systems (Scholz, 2011) or coupled human and natural systems (Liu et al., 2007). Transdisciplinary sustainability research Transdisciplinary research is an integrative mode of organizing scientifc research to solve or transition societal and related scientifc problems by dif ferentiating and integrating knowledge from various scientifc and societal bodies of knowledge (Lang et al., 2012). Transdisciplinary sustainability research designates basic and applied research to solve sustainability issues practices based on knowledge co production among researchers from vari ous scientifc disciplines from the natural science and social science (humani ties) for the interdisciplinary analysis of integrated socio ecological systems (Klein, 2010) and (among scientifc researchers and societal actors) the improved understanding of the socially legitimate and relevant perspectives on the solution pathways (Lux et al., 2019). References Agyeman, J. and Evans, B. (2004). “Just sustainability”: The emerging discourse of environmental justice in Britain? The Geographical Journal, 170(2), 155–164. Akkerman, S. F. and Bakker, A. (2011). Boundary crossing and boundary objects. Review of Educational Research, 81(2), 132–169. Benkler, Y. (2008). The wealth of networks. New Haven, CT: Yale University Press. Binder, C. R., Hinkel, J., Bots, P. W. and Pahl Wostl, C. (2013). Comparison of frame works for analyzing social ecological systems. Ecology and Society, 18(4), 26. Chang, R. (Ed.). (1997). Incommensurability, incomparability, and practical reason. Cambridge, MA: Harvard University Press. Coleman, K. and Gould, R. (2019). Exploring just sustainability across the disciplines at one university. The Journal of Environmental Education, 50(3), 223–237. Crombie, A. C. (1995). Commitments and styles of European scientifc thinking. History of Science, 33(2), 225–238. Dobson, A. (2007). Environmental citizenship: Towards sustainable development. Sustainable Development, 15(5), 276–285. Fischer, J., Gardner, T. A., Bennett, E. M., Balvanera, P., Biggs, R., Carpenter, S., . . . and Luthe, T. (2015). Advancing sustainability through mainstreaming a social— ecological systems perspective. Current Opinion in Environmental Sustainability, 14, 144–149. Annex 1 165 Fleck, L. (1979 [1935]). Genesis and development of a scientifc fact. Chicago: The University of Chicago Press. Frischmann, B. M., Madison, M. and Strandburg, C. (2014). Governing knowledge commons. Oxford: Oxford University Press. Hacking, I. (2012). Language, truth and reason’ 30 years later. Studies in History and Philosophy of Science, 43(4), 599–609. Hall, P. A. and Taylor, R. C. R. (1996). Political science and the three new institution alisms. Political Studies, 44(4), 936–957. Herrero, P., Dedeurwaerdere, T. and Osinski, A. (2019). Design features for social learning in transformative transdisciplinary research. Sustainability Science, 14(3), 751–769. Hess, C. and Ostrom, E. (Eds.). (2007). Understanding knowledge as a commons: From theory to practice. Cambridge, MA: MIT Press. Hicks, C. C., Levine, A., Agrawal, A., Basurto, X., Breslow, S. J., Carothers, C., . . . Levin, P. S. (2016). Engage key social concepts for sustainability. Science, 352(6281), 38–40. Hirsch Hadorn, G., Hofmann Riem, H., Biber Klemm, S., Grossenbacher Mansuy, W., Joye, D., Pohl, C., . . . and Zemp, E. (Eds.). (2008). Handbook of transdisciplinary research. Dordrecht: Springer. Klein, J. T. (2010). A taxonomy of interdisciplinarity. In R. Frodeman, J. Thomp son Klein and C. Mitcham (Eds.), The Oxford handbook of interdisciplinarity (pp. 15–30). Oxford: Oxford University Press. Kranich, N. (2007). Countering enclosure: Reclaiming the knowledge commons. In Ch. Hess and E. Ostrom (Eds.), Understanding knowledge as a commons: From theory to practice (pp. 85–122). Cambridge, MA: MIT Press. Lang, D. J., Wiek, A., Bergmann, M., Staufacher, M., Martens, P., Moll, P., . . . and Thomas, C. J. (2012). Transdisciplinary research in sustainability science: Practice, principles, and challenges. Sustainability Science, 7(1), 25–43. Levi, I. (2004). The second worst in practical confict. In P. Baumann and M. Betzler (Eds.), Practical conficts. Cambridge: Cambridge University Press. Levin, S., Xepapadeas, T., Crépin, A. S., Norberg, J., De Zeeuw, A., Folke, C., . . . and Walker, B. (2013). Social ecological systems as complex adaptive systems: Mod eling and policy implications. Environment and Development Economics, 18(2), 111–132. Liu, J., Dietz, T., Carpenter, S. R., Alberti, M., Folke, C., Moran, E., . . . and Ostrom, E. (2007). Complexity of coupled human and natural systems. Science, 317, 1513–1516. Lux, A., Schäfer, M., Bergmann, M., Jahn, T., Marg, O., Nagy, E., Ransiek, A. C. and Theiler, L. (2019). Societal efects of transdisciplinary sustainability research— How can they be strengthened during the research process? Environmental Science and Policy, 101, 183–191. North, D. (1999). Understanding the process of institutional change. Princeton, NJ: Princeton University Press. Ostrom, E. (1990). Governing the commons: The evolution of institutions for collective action. Cambridge: Cambridge University Press. Pahl Wostl, C. (2009). A conceptual framework for analysing adaptive capacity and multi level learning processes in resource governance regimes. Global Environmental Change, 19(3), 354–365. Pohl, C., Klein, J. T., Hofmann, S., Mitchell, C. and Fam, D. (2021). Conceptualising transdisciplinary integration as a multidimensional interactive process. Environmental Science and Policy, 118, 18–26. 166 Annex 1 Polk, M. (2015). Transdisciplinary co production: Designing and testing a transdis ciplinary research framework for societal problem solving. Futures, 65, 110–122. Reed, M. S., Evely, A. C., Cundill, G., Fazey, I., Glass, J., Laing, A., . . . and Stringer, L. C. (2010). What is social learning? Ecology and Society, 15(4). Rockström, J., Stefen, W., Noone, K., Persson, Å., Chapin, F. S., Lambin, E. F., . . . and Foley, J. A. (2009). A safe operating space for humanity. Nature, 461(7263), 472–475. Schlosberg, D. (2013). Theorising environmental justice: The expanding sphere of a discourse. Environmental Politics, 22(1), 37–55. Schlüter, M., Haider, L. J., Lade, S. J., Lindkvist, E., Martin, R., Orach, K., . . . and Folke, C. (2019). Capturing emergent phenomena in social ecological systems. Ecology and Society, 24(3), 11. Schneider, F., Giger, M., Harari, N., Moser, S., Oberlack, C., Providoli, I., . . . and Zimmermann, A. (2019). Transdisciplinary co production of knowledge and sus tainability transformations: Three generic mechanisms of impact generation. Environmental Science and Policy, 102, 26–35. Scholz, R. W. (2011). Environmental literacy in science and society. From knowledge to decisions. Cambridge: Cambridge University Press. Sciortino, L. (2017). On Ian Hacking’s notion of style of reasoning. Erkenntnis, 82(2), 243–264. Sen, A. (2009). The idea of justice. Cambridge, MA: Harvard University Press. Sørensen, E. and Torfng, J. (Eds.). (2007). Theories of democratic network governance. Heidelberg: Springer. ANNEX 2 Case study list Case studies from the “most diferent” case study sampling of well docu mented transdisciplinary research projects within the fve levers of change. Initial sampling from a keyword search in four journals between 2005 and 2020 (Ecological Economics, Ecology and Society, Environmental Science and Policy, Sustainability Science) and the case study volume by Bergmann et al. (2012). In a second step, the sample was completed to reach a minimum of fve papers for each lever of change through a general search in Google Scholar on “transdisciplinary sustainability research” or “participatory sus tainability research” and keywords representative of that lever of change (cf. the detailed discussion of the sampling strategy in Section 3.1.2). Projects with marked with “(*video*)” are documented with a short video interview and background materials on www.lptransition.be/td co-M co-D SL C4 C5 C6 None or very few usable knowledge outputs Green infrastructure in Eindhoven to combat the summer heat, the Netherlands L1 Bodilis (2018) Intensive grazing in mountain landscapes, France L2 Lamarque et al. (2013) Sustainable land use in the Upper Valais mountain area, Switzerland L2 Brand et al. (2013) (Continued) 168 Annex 2 (Continued) co-M co-D SL C4 C5 C6 Housing insulation for the energy transition in Bottrop, Germany (*video*) L2 Bierwirth et al. (2017) Loss of peatland through reforestation, Finland L3 Saarikoski et al. (2019) Scenarios for biofuel use in Europe L3 Baudry et al. (2018a, 2018b) Sustainable energy options, (electricity, heating) in Ebhausen, Germany L3 McKenna et al. (2018) Sustainable energy options (electricity, heating) in Urnach, Switzerland L3 Trutnevyte et al. (2011, 2012) Nature conservation and agricultural production in the Elbe valley, Germany L4 Bergmann et al. (2012, ch. III.K) Understanding values and impacts of bicycle infrastructure, Auckland, New Zeeland L5 Macmillan and Woodcock (2017) A framework for housing refurbishment, United Kingdom L5 Macmillan et al. (2016) Water management in an urban context, Switzerland L5 Pahl Wostl and Hare (2004) Sustainable mobility and urban densifcation in Las Vegas, Nevada, US L2 Stave (2002, 2010) Assessing the social and environmental value of urban green in Gothenburg, Sweden L3 Klingberg et al. (2017), Andersson Sköld et al. (2018) Partnerships with housing renovation companies in the Rhine Main area, Germany L4 Bergmann et al. (2012, ch. III.G) L1 Newman et al. (2020) Moderate to significant usable knowledge outcomes, for a limited part of the intended users/beneficiaries Citizen science in Manchester neighborhoods with industrial pollution, United Kingdom Annex 2 169 co-M co-D SL C4 C5 C6 Scenario building and empowerment in rural development, India, Philippines, and Indonesia L5 Bourgeois et al. (2017) Farming activities in biodiversity rich mountain areas in the Piedmont, Italy L4 Höchtl et al. (2006) Sustainable agriculture and small scale tourism in a mountain area, France (*video*) L4 Lavorel et al. (2019) Income generation activities from mangrove ecosystems, Kenya SL L5 78 Galafassi et al. (2018), Fortnam et al. (2019) ATD Food assistance project with the urban poor in Brussels, Belgium (*video*) SL L5 64 Joos Malfait et al. (2019), Osinski (2020) Mitigation in Urban Context, Rotterdam, the Netherlands (*video*) L5 65 Roorda et al. (2014), Tillie et al. (2012) Renewable energy options through local/regional energy sources, Austria L2 co-M co-D SL Binder et al. (2014) C4 C5 C6 Moderate to significant project outcomes, for a large part of the intended users/ beneficiaries Nuclear radiation around mines, Niger and Namibia L1 Renovation of historic houses in the inner city of Cahors, France L1 47 Claude et al. (2017) L1 79 Bieser et al. (2021), Sjöman et al. (2020) L3 55 Schmale et al. (2015, 2016) Digital services for sustainable mobility solutions in Stockholm, Sweden (*video*) Public transport in park and ride facilities for urban mobility in Potsdam, Germany SL Conde (2014) (Continued) 170 Annex 2 (Continued) co-M co-D SL C4 C5 C6 Changing a rural diet with high saturated fat, Finland L4 Puska et al. (2009) Mobility style analysis in various cities, Germany L4 Bergmann et al. (2012, ch. III.B), HirschHadorn et al. (2008, ch. 6) Indigenous knowledge of basket weaving in the Brazilian Amazon L4 Athayde et al. (2017) Energy poverty in the informal urban settlements of Enkanini, South Africa SL Protection of lobster fsheries and sensitive coastal habitats, Belize Community mapping of land use and ecosystem based plan, Xáxli’p community, Canada SL Urban traffic slowing and cultural identity, Australia L5 62 Van Breda and Swilling (2019) L2 53 Verutes et al. (2017), Arkema et al. (2019) L4 Diver (2017) L2 51 Macmillan et al. (2014), Macmillan and Mackie (2016), Mackie et al. (2018) L1 49 Goutiers et al. (2016), Lacombe et al. (2017) Very comprehensive usable knowledge outcomes, for a large part of the intended users/beneficiaries Seed selection for forage autonomy, France SL Adding value to the food value chain in small holder dairy farming, Kenya L1 Restrepo et al. (2020) Creation of a Nature Park designation in the Black Forest, Germany L4 Rhodius et al. (2020, ch. 6) Small scale sustainable forestry in Larzac, France SL L2 53 Simon and Etienne (2010) Annex 2 co-M co-D SL C4 C5 C6 Conservation management in Scottish Moorlands, United Kingdom SL L4 Management and re use of organic waste in Brussels, Belgium (*video*) SL L2 Community health surveying of asthma prevalence from pollution in New York, USA SL L4 Urban homeless communities feld surveys in Toronto, Canada 171 77 Bortolotti et al. (2019) 58 L4 Improved access to health services for nomadic pastoralists, Chad SL L4 River pollution and recreational fshing, Switzerland SL L2 Ainsworth et al. (2020) Corburn (2005) Khandor and Mason (2011) 80 Bergmann et al. (2012, ch. III.F); Hirsch Hadorn et al. (2008, ch. 17) Burkhardt and Zehnder (2018) Legend • List of case studies represented in 4 clusters of increasingly strong coproduction of usable knowledge outputs (cf. Annex 3 for the coding scale that was used) • Co-M (co-management), Co-D (co-design), SL (social learning): average values of the Likert scale, for the cases listed in each of the 4 clusters (cf. Annex 3 for the coding scale that was used) very strong and comprehensive very strong strong moderate weak • SL: in the column on social learning, cases with extensive documentation of the social learning process (independently of the level of social learning) are indicated with SL; these cases served as the basis for the cluster analy sis in chapter 4. • C4: Thematic field according to one of the five levers of change, as defined in section 3.1.2: (L1) Socio technical levers of change, (L2) Biophysical 172 Annex 2 levers of change in socio ecological systems, (L3) Socioeconomic levers of change, (L4) Multistakeholder governance for policy implementation, and (L5) Including the diversity of sociocultural perspectives • C5: Page number of discussion of the case in the main text • C6: References of the project publications References Ainsworth, G. B., Redpath, S. M., Wilson, M., Wernham, C. and Young, J. C. (2020). Integrating scientifc and local knowledge to address conservation conficts: To wards a practical framework based on lessons learned from a Scottish case study. Environmental Science and Policy, 107, 46–55. Andersson Sköld, Y., Klingberg, J., Gunnarsson, B., Cullinane, K., Gustafsson, I., Hedblom, M., . . . and Thorsson, P. (2018). A framework for assessing urban greenery’s efects and valuing its ecosystem services. Journal of Environmental Management, 205, 274–285. Arkema, K. K., Rogers, L. A., Toft, J., Mesher, A., Wyatt, K. H., Albury Smith, S., . . . and Samhouri, J. (2019). Integrating fsheries management into sustainable development planning. Ecology and Society, 24(2), 1. Athayde, S., Silva Lugo, J., Schmink, M., Kaiabi, A. and Heckenberger, M. (2017). Re connecting art and science for sustainability: Learning from indigenous knowledge through participatory action research in the Amazon. Ecology and Society, 22(2), 36. Baudry, G., Macharis, C. and Vallee, T. (2018a). Range based multi actor multi crite ria analysis: A combined method of multi actor multi criteria analysis and Monte Carlo simulation to support participatory decision making under uncertainty. European Journal of Operational Research, 264(1), 257–269. Baudry, G., Macharis, C. and Vallée, T. (2018b). Can microalgae biodiesel contribute to achieve the sustainability objectives in the transport sector in France by 2030? A comparison between frst, second and third generation biofuels though a range based multi actor multi criteria analysis. Energy, 155, 1032–1046. Bergmann, M., Jahn, T., Knobloch, T., Krohn, W., Pohl, C. and Schramm, E. (2012). Methods for transdisciplinary research: A primer for practice. Frankfurt: Campus Verlag. Bierwirth, A., Augenstein, K., Baur, S., Bettin, J., Buhl, J., Friege, J., . . . and Vond ung, F. (2017). Knowledge as transformative energy: On linking models and experiments in the energy transition in buildings. Wuppertal: Wuppertal Institute for Climate, Energy and the Environment. Bieser, J. C., Vaddadi, B., Kramers, A., Höjer, M. and Hilty, L. M. (2021). Impacts of telecommuting on time use and travel: A case study of a neighborhood telecom muting center in Stockholm. Travel Behaviour and Society, 23, 157–165. Binder, C. R., Absenger Helmli, I., Bedenik, K., Chappin, E., Dijkema, G., Goetz, A., . . . and Vilsmaier, U. (2014). TERIM—transition dynamics in energy regions: An integrated model for sustainable policies. Tagungsband 15. Klimatag: 2–4 April 2014 (pp. 78–79). Innsbruck: Universität Innsbruck. Bodilis, C. (2018). Integration and visualisation of urban sprawl and urban heating indicators from complex data in a context of nature-based solutions [Master the sis]. Aveiro: Universidade de Aveiro. Annex 2 173 Bortolotti, A., Kampelmann, S., De Muynck, S., Papangelou, A. and Zeller, V. (2019). Conditions and concepts for interdisciplinary urban metabolism research—the case of an inter project collaboration on biowaste. Flux, 2, 112–127. Bourgeois, R., Penunia, E., Bisht, S. and Boruk, D. (2017). Foresight for all: Co elaborative scenario building and empowerment. Technological Forecasting and Social Change, 124, 178–188. Brand, F. S., Seidl, R., Le, Q. B., Brändle, J. M. and Scholz, R. W. (2013). Con structing consistent multiscale scenarios by transdisciplinary processes: The case of mountain regions facing global change. Ecology and Society, 18(2), 43. Burkhardt Holm, P. and Zehnder, A. J. (2018). Fischnetz: Assessing outcomes and impacts of a project at the interface of science and public policy. Environmental Science and Policy, 82, 52–59. Claude, S., Ginestet, S., Bonhomme, M., Moulène, N. and Escadeillas, G. (2017). The Living Lab methodology for complex environments: Insights from the thermal re furbishment of a historical district in the city of Cahors, France. Energy Research and Social Science, 32, 121–130. Conde, M. (2014). Activism mobilising science. Ecological Economics, 105, 67–77. Corburn, J. (2005). Street science: Community knowledge and environmental health justice. Cambridge, MA: MIT Press. Diver, S. (2017). Negotiating Indigenous knowledge at the science policy interface: Insights from the Xáxli’p Community Forest. Environmental Science and Policy, 73, 1–11. Fortnam, M., Brown, K., Chaigneau, T., Crona, B., Daw, T. M., Gonçalves, D., . . . and Schulte Herbruggen, B. (2019). The gendered nature of ecosystem services. Ecological Economics, 159, 312–325. Galafassi, D., Daw, T. M., Thyresson, M., Rosendo, S., Chaigneau, T., Bandeira, S., . . . and Brown, K. (2018). Stories in social ecological knowledge cocreation. Ecology and Society, 23(1), 23. Goutiers, V., Charron, M. H., Deo, M. and Hazard, L. (2016). Capfor®: un outil pour concevoir des mélanges de prairies à fore variée. Fourrages, 228, 243–252. Hirsch Hadorn, G., Hofmann Riem, H., Biber Klemm, S., Grossenbacher Mansuy, W., Joye, D., Pohl, C., . . . and Zemp, E. (Eds.). (2008). Handbook of transdisciplinary research. Dordrecht: Springer. Höchtl, F., Lehringer, S. and Konold, W. (2006). Pure theory or useful tool? Experi ences with transdisciplinarity in the Piedmont Alps. Environmental Science and Policy, 9(4), 322–329. Joos Malfait, V., Myaux, D. and Osinski, A. (coord.). (2019). L’expérience de l’aide alimentaire. Quelles alternatives. Rapport d’une recherche en croisement des savoirs. Bruxelles: Fédération des Services Sociaux (FdSS). Khandor, E. and Mason, K. (2011). The street health report 2007: Community based research for social change. In M. Kirst, N. Schaefer Mc Daniel, S. Hwang and P. O’Campo (Eds.), Converging disciplines. A transdisciplinary research agenda to urban health problems (pp. 57–68). New York: Springer. Klingberg, J., Broberg, M., Strandberg, B., Thorsson, P. and Pleijel, H. (2017). Infu ence of urban vegetation on air pollution and noise exposure—a case study in Gothenburg, Sweden. Science of the Total Environment, 599, 1728–1739. Lacombe, C., Couix, N. and Hazard, L. (2017). Envisager l’accompagnement du changement des systèmes agricoles vers l’agroécologie comme un processus 174 Annex 2 co-conçu. Cas de la co-conception locale d’un outil de diagnostic agroécologique des fermes ovin-lait dans le Sud-Aveyron [Conference presentation]. 7ième Col loque du réseau OPDE, Des Outils pour Décider Ensemble, 26–27 October, Mont pelier, France. HAL Archive ouverte de l’Institut national de recherche pour l’agriculture, l’alimentation et l’environnement (INRAE), Paris. Lamarque, P., Artaux, A., Nettier, B., Dobremez, L., Barnaud, C. and Lavorel, S. (2013). Taking into account farmers’ decision making to map fne scale land man agement adaptation to climate and socioeconomic scenarios. Landscape Urban Plann, 119, 147–157. Lavorel, S., Collof, M. J., Locatelli, B., Gorddard, R., Prober, S. M., Gabillet, M., . . . and Peyrache Gadeau, V. (2019). Mustering the power of ecosystems for adapta tion to climate change. Environmental Science and Policy, 92, 87–97. Mackie, H., Macmillan, A., Witten, K., Baas, P., Field, A., Smith, M., . . . and Woodward, A. (2018). Te Ara Mua—Future Streets suburban street retroft: A researcher community government co design process and intervention outcomes. Journal of Transport and Health, 11, 209–220. Macmillan, A., Connor, J., Witten, K., Kearns, R., Rees, D. and Woodward, A. (2014). The societal costs and benefts of commuter bicycling: Simulating the ef fects of specifc policies using system dynamics modeling. Environmental Health Perspectives, 122(4), 335–344. Macmillan, A., Davies, M., Shrubsole, C., Luxford, N., May, N., Chiu, L. F., . . . and Chalabi, Z. (2016). Integrated decision making about housing, energy and wellbe ing: A qualitative system dynamics model. Environmental Health, 15(1), 23–34. Macmillan, A. and Mackie, H. (2016). Optimising low carbon mobility for health and equity. In D. Hopkins and J. Higham (Eds.), Low carbon mobility transition. Oxford: GoodFellow Publishers. Macmillan, A. and Woodcock, J. (2017). Understanding bicycling in cities using sys tem dynamics modelling. Journal of Transport and Health, 7, 269–279. McKenna, R., Bertsch, V., Mainzer, K. and Fichtner, W. (2018). Combining local preferences with multi criteria decision analysis and linear optimization to develop feasible energy concepts in small communities. European Journal of Operational Research, 268(3), 1092–1110. Newman, G., Shi, T., Yao, Z., Li, D., Sansom, G., Kirsch, K., . . . and Horney, J. (2020). Citizen science informed community master planning: Land use and built environment changes to increase food resilience and decrease contaminant expo sure. International Journal of Environmental Research and Public Health, 17(2), 486. Osinski, A. (2020). Evaluating transition pathways beyond basic needs: A transdisci plinary approach to assessing food assistance. Food Ethics, 5(1), 1–34. Pahl Wostl, C. and Hare, M. (2004). Processes of social learning in integrated re sources management. Journal of Community and Applied Social Psychology, 14(3), 193–206. Puska, P., Vartiainen, E., Laatikainen, T., Jousilahti, P. and Paavola, M. (2009). The North Karelia project: From North Karelia to national action. Helsinki: National Institute for Health and Welfare. Restrepo, M. J., Lelea, M. A. and Kaufmann, B. A. (2020). Assessing the quality of collaboration in transdisciplinary sustainability research: Farmers’ enthusiasm to Annex 2 175 work together for the reduction of post harvest dairy losses in Kenya. Environmental Science and Policy, 105, 1–10. Rhodius, R., Bachinger, M. and Koch, B. (Eds.). (2020). Wildnis, Wald, Mensch. Forschungsbeiträge sur Entwicklung einer Nationalparkregion am Beispiel des Schwarzwalds. Munich: Oekom Verlag. Roorda, C., Wittmayer, J., Henneman, P., Van Steenbergen, F., Frantzeskaki, N. and Loorbach, D. (2014). Transition management in the urban context: Guidance manual. Rotterdam: Dutch Research Institute for Transition (DRIFT), Erasmus University Rotterdam. Saarikoski, H., Mustajoki, J., Hjerppe, T. and Aapala, K. (2019). Participatory multi criteria decision analysis in valuing peatland ecosystem services—Trade ofs re lated to peat extraction vs. pristine peatlands in Southern Finland. Ecological Economics, 162, 17–28. Schmale, J., Von Schneidemesser, E., Chabay, I., Maas, A. and Lawrence, M. G. (2016). Building interfaces that work: A multi stakeholder approach to air pollu tion and climate change mitigation. In J. L. Drake, Y. Y. Kontar, J. C. Eichelberger, S. T. Rupp and K. M. Taylor (Eds.), Communicating climate-change and natural hazard risk and cultivating resilience (pp. 65–76). Heidelberg: Springer. Schmale, J., Von Schneidemesser, E. and Dörrie, A. (2015). An integrated assessment method for sustainable transport system planning in a middle sized German city. Sustainability, 7(2), 1329–1354. Simon, C. and Etienne, M. (2010). A companion modelling approach applied to forest management planning. Environmental Modelling and Software, 25(11), 1371–1384. Sjöman, M., Ringenson, T. and Kramers, A. (2020). Exploring everyday mobility in a living lab based on economic interventions. European Transport Research Review, 12(1), 5. Stave, K. (2002). Using system dynamics to improve public participation in environ mental decisions. System Dynamics Review: The Journal of the System Dynamics Society, 18(2), 139–167. Stave, K. (2010). Participatory system dynamics modeling for sustainable environmen tal management: Observations from four cases. Sustainability, 2(9), 2762–2784. Tillie, N., Aarts, M., Marijnissen, M., Stenhujs, L., Borsboom, J., Rietveld, E., . . . and Lap, S. (2012). Rotterdam. People make the inner city. Rotterdam: Gemeente. Trutnevyte, E., Staufacher, M., Schlegel, M. and Scholz, R. W. (2012). Context spe cifc energy strategies: Coupling energy system visions with feasible implementa tion scenarios. Environmental Science and Technology, 46(17), 9240–9248. Trutnevyte, E., Staufacher, M. and Scholz, R. W. (2011). Supporting energy initia tives in small communities by linking visions with energy scenarios and multi criteria assessment. Energy Policy, 39(12), 7884–7895. Van Breda, J. and Swilling, M. (2019). The guiding logics and principles for design ing emergent transdisciplinary research processes: Learning experiences and refec tions from a transdisciplinary urban case study in Enkanini informal settlement, South Africa. Sustainability Science, 14(3), 823–841. Verutes, G. M., Arkema, K. K., Clarke Samuels, C., Wood, S. A., Rosenthal, A., Rosado, S., . . . and Ruckelshaus, M. (2017). Integrated planning that safeguards ecosystems and balances multiple objectives in coastal Belize. International Journal of Biodiversity Science, Ecosystem Services and Management, 13(3), 1–17. ANNEX 3 Coding scales Coding scales used to code the cases from the case study list for the core explanatory variables (research co design, co management, social learning, information gathering and communication) and the outcome variable (co production of usable knowledge outputs). Similar scales were used to code the control variables (types of involved societal actors, disciplines and the matic felds); however, they did not lead to signifcant correlations with the usable knowledge outcomes. Explanatory variables Research co-design Did the project publication explicitly mention the co construction of research questions or research frame as a core component of the research process? Likert scale 1) 2) 3) 4) 5) not at all on very little aspects of the produced knowledge on a few key aspects covering a substantial number of the aspects covering nearly all aspects Process co-management Did societal actors participate in governing the research process at least through one of the following types? Annex 3 177 • co-research (societal actors jointly organizing the data gathering with the researchers) • co-intervention (joint organization of real-world interventions as part of the research protocol) • co-decision (joint supervision of doctoral or post-doctoral research or joint decision making in the consortium board, if applicable). Likert scale 1) 2) 3) 4) 5) not at all on very little aspects of the produced knowledge on a few key aspects covering a substantial number of the aspects covering nearly all aspects Organized processes of social learning Was there an explicit workshop for social learning among the project mem bers, situated within one of the four social learning categories of the main text, defned in Section 4.3: • Agreement on process values for common inquiry into the problem identifcation • Common action strategies accommodating divergent perspectives • Identifying converging and diverging perspectives • Common action program with a substantial overlap in the value rankings Likert scale 1) 2) 3) 4) 5) not at all on very little aspects of the produced knowledge on a few key aspects covering a substantial number of the aspects covering nearly all aspects Consultation of societal actors for information gathering in the research process Was there science practitioners interaction through one of the following modes? • Information gathering on context-specific (local or global) features of the problem situation or the variables of the research framework • Informing on the project and on outcomes and collect comments, for solic iting feedback from societal actors 178 Annex 3 Likert scale 1) 2) 3) 4) 5) not at all on very little aspects of the produced knowledge on a few key aspects covering a substantial number of the aspects covering nearly all aspects Outcome variable Usable knowledge outputs Did the project produce one of the following project outputs (if several out puts, then code the sum of the evaluation on the Likert scale of each of the output categories)? • New solutions (technical solutions, but also diagnosis and evaluation tools) used by societal actors during the project or within the two years that fol low the project, beyond the interventions that were already planned in the research protocol at the beginning of the project • Common action plans (for societal actors, government) with clear imple mentation plans accepted by the intended users and benefciaries of the project • New organizational mechanisms established (hierarchies/networks) dur ing the project or within the two years that follow the project, beyond the interventions that were already planned in the research protocol at the beginning of the project Likert scale 1 Not at all 2 A small project outcome, for a limited part of the intended users/ beneficiaries 3 Moderate to significant project outcome, for a limited part of the intended users/beneficiaries 4 Moderate to significant project outcome, for a large part of the intended users/beneficiaries INDEX Africa 83–86 applied research 14, 55 Asia 100 ATD Quart Monde 37, 86, 87 basic research 14, 55 Benkler, Yochai 26, 27, 35 boundary crossing knowledge exchange: boundary objects 40; and learning 160; trading zones 40 co design of research frameworks 62; interdisciplinary 52, 53; multi disciplinary 17, 52; reciprocal reference 53, 58; transdisciplinary 54 collaborative governance 7; multistakeholder governance 77–79 collective action 24–26, 148, 149; institutional conditions 33, 34 co management between researchers and social actors 36–38; common governing board 36; joint data gathering 36; joint research supervision 36 commons 24, 25; centralized and decentralized management 24; digital knowledge commons 25; knowledge commons 26; natural resource commons 25; scientifc research commons 33, 162 community science 153; community based survey methods 79 confict situations 111–119; conficts over values 103–110; confict transformation 111, 112 deliberation 118–120; building deliberation capacities 156; in complex social choice situations 104; deliberative approaches to social learning 102; impartiality 118, 119; inclusive perspective 118; non coercive dialogue 119; process standards 118 disciplinary research 11; multi disciplinary research 11; and progress in human well being 10 Dryzek, John 118–120, 154 economics of knowledge 128; public good characteristics 24, 25 energy 63–64; energy poverty 83–86; housing renovation 64–66; of grid photovoltaic solar cells 68 environmental justice 7; and ecosystem services 112, 113; and environmental health 78–81 failures of transdisciplinary research partnerships 27–32; inconsistent 180 Index institutional incentives 140; instrumentalization 28, 29; small niche research 32; technocratic management 102, 103; unstructured value diversity 30, 31 Fleck, Ludwik 26 food and agriculture: food assistance 86, 87; participatory seed selection 67 Hacking, Ian 42 healthcare: asthma 78–81; coronary heart disease 78; one health approach 115–117 housing: bio based building materials 64–66 immigrant communities 32, 79, 80 impact 40–45; pathways of impact generation 41 incommensurability 105; incompatible value rankings 106; of societal values 106–108, 160 indigenous communities 70, 71 institutional enabling mechanisms 129–131; capacity building 123, 138, 139; emotional features 139; knowledge exchange 135–137; social interactive features 139; teaching 132–134; team formation 137–138 institutional rules 17, 18, 161 Institutions of higher education 34, 60, 123, 129, 132 interdisciplinarity 52, 53; broad interdisciplinarity 148, 149; collective action failures 54 Intergovernmental Panel on Climate Change 11 knowledge co production 162; ladder of knowledge co production 59, 61; in polycentric networks 39, 40; research co design 50–54; research co management 36; and social learning 38, 39 knowledge integration 50, 51 living lab 66–68; use centered technological innovation 63, 64 mission oriented research 149 mobility 74–76; air pollution 71, 74, 84; congestion charging 76; traffic calming 70 multi criteria assesment 76 National research agencies: Swiss Academy of Sciences 13,137; United States National Academies of Sciences 12 natural resource management: ecosystem services 112, 113; fsheries 72; irrigation systems 25, 100; wetland management 102, 103 organisational support: new professional profles 146; promotion of transdisciplinary skills 146, 147 organizational architectures: autonomous team work 127; democratic governance of 140, 141; fexible network organization 127, 128; functional hierarchies 126, 127 Organization for Economic Cooperation and Development (OECD) 2, 14 Ostrom, Elinor 24, 25, 38, 39 participation: companion modeling 72, 73; instrumental forms of participation 37; ladder of participation 36; participatory modeling 69, 70; systems dynamic modeling 85–86 partner identifcation 137, 138; search conferences 131, 137, 147 polycentric governance 39, 156; enabling functions 39, 40 power 7, 9; power imbalances in transdisciplinary research 37, 92, 119 pragmatist constructivism 92; and comprehensive consequences 104; and environmental justice 91; experiential knowledge 91; pluralism of value related perspectives 91 qualitative research: concept mapping 113; focus group research 83; Index 181 future visioning workshops 88; merging of knowledge 86; participatory qualitative research 84–86; qualitative systems dynamics mapping 85; storytelling 113 random controlled trials 77 Reed, Mark 101 research styles 42, 162 risk assessment 28, 29 role playing games 100 Sen, Amartya 104–106 social choice: accommodation of divergent perspectives 112, 113; agreement over process value 110–112; pairwise agreement over values 105; salient societal values 106, 110 social learning 162; in adaptive management 102; identifying needs 120; typology of social learning outputs 119 socio ecological systems 164; historical interdependencies 5, 6; and integrated research 161; socio ecological interdependency 9 sustainability: environmental citizenship 7, 8; environmental justice 7; planetary boundaries 6, 7; social and ecological 162 sustainability transformations 6; levers of change 57, 58 thought styles 26, 162 transdisciplinarity: transdisciplinarity beyond academia 149–151; transdisciplinary sustainability research 164 transdisciplinary teaching: doctoral training 134; master courses 131–133; master theses 134 usable knowledge production: actionable knowledge 2; frst order efects 56; second order efects 56; usable knowledge outputs 54, 55 values: convergence amongst 110; heterogeneity of societal values 14, 15, 17; see also incommensurability; social choice wicked problems 1 Williamson, Oliver 124, 126