Reviewed by
Cesar Garcia-Diaz
Pontificia Universidad Javeriana
Sustainability transitions research has been long dominated by the use of narratives and case studies as the main means to accumulate knowledge. Although the documentation of case studies has been absolutely important in this now-established field, this books calls for a more rigorous approach. Further progress entails dealing with the intricacies of multi-level dynamics, co-evolution, and different forms of stakeholder participation, for which other tools are needed. The book ultimately advocates a scientific attitude that allows to build theories across different cases, data-driven studies, and formal models that bridge theory construction and empirical data. Thus, modelling is called to play a major role in understanding sustainability transitions. Transitions are processes that involve technical, economic, societal and cultural changes, so modelling efforts need to move beyond the traditional integrated assessment models (Siebers et al. 2020). That is also what the book poses (p. 11). The book exhibits a diverse set of viewpoints on how modelling can contribute to transition research and highlights that modelling endeavours “should lead and not follow” (p. 258) the development of a strong foundation of a transitions science.
The book is divided into fourteen chapters, grouped in four blocks: an introductory section (consisting of a foreword, a prologue and an overview chapter on transition modelling by J. Köhler and G. Holtz), and three major parts: virtues and vices, the state of the art, and the future of modelling transitions.
The first part (virtues and vices) offers two engaging chapters: one on why a transitions science is needed (F.J. de Haan) and another on how transitions researchers could benefit from the knowledge developed by modellers in the social science community (F. Bianchi and F. Squazzoni). The second part (state of the art) presents an interesting chapter on modelling the so-called multi-level perspective (chapter 6 by J. Köhler), the MATISSE project. This part also presents accounts of contributions of two major computational modelling techniques, namely agent-based modelling (chapter 7 by G. Holtz and E.J.L. Chappin), and system dynamics (chapter 8 by G. Papachristos and J. Struben); it finalises with the presentation of an analytical framework to study electricity systems (chapter 9 by A. Rojas and F.J. de Haan). The third part (the future of modelling transitions), explores potential directions where transitions modelling could have a great impact: long-term planning under uncertainty (chapter 10 by S. Malekpour), participatory modelling (chapter 11 by J. Halbe), data-driven research (chapter 12 by F.J. de Haan, A.M. Arranz and W. Spekkink), and exploratory modelling (chapter 13 by E.A. Moallemi, F.J. de Haan and J. Köhler). An epilogue that summarises the main ideas closes the book.
Perhaps the most remarkable application of (computational) modelling presented in the book is that of chapter 6, the MATISSE framework. It shows that the multi-level perspective concepts of niche, regime and landscape can be formalised by using an agent-based representation embedded in a “practice space”. The MATISSE project is an example that illustrates how a general, standard framework can be adapted to study specific transition cases. In the book, these cases correspond to sustainable mobility and low-emissions shipping.
Throughout the chapters, the book greatly discusses the epistemological implications of the use of different modelling approaches to investigate problems in sustainability transitions research, including their potentials and challenges. I highlight the fact that the book is inclusive in terms of both the various modelling perspectives (agent-based modelling, system dynamics, graph theory, network science, et cetera), and the mixing of qualitative and quantitative approaches.
I find this book inspiring in several ways. Modelling undertakings are appreciated in both curiosity-driven and problem-driven perspectives. The book’s ideas are also compatible with considering that transformative change can even be undertaken under partial or little understanding (e.g. robust adaptive planning under deep uncertainty), when there is no yet reliable science (Edmonds 2018). Such efforts will eventually contribute to build scientific knowledge (García-Díaz and Olaya 2018) that will refine our understanding and intervention methodologies.
Last, I would like to refer to the consideration of prediction. Prediction in complex socio-technical systems might be hardly achievable (in the sense of Edmonds 2017). Instead, we should probably aim to “influence” courses of change but not “predict” them (Edmonds 2017; Pennock and Rouse 2016). Nonetheless, a fair argument of the book is that if we want to develop refutable theories and testable hypotheses, so transitions research moves to a scientific field (as argued in chapter 4 and the epilogue), theories should aim to predict.
To sum up, this book is a very good resource for social systems modellers, inspiring resource for sustainability researchers, and a good reference for learning how modelling can contribute to sustainability transitions.
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