System Dynamics in Transition Management : Participative modeling for transitioning towards a circular construction material industry

Abstract

Climate change and biodiversity degradation are only two of humanity's major social and environmental issues. Scientists, global policy experts, and the general public are increasingly concluding that traditional interventions to reduce un-sustainability are inadequate and that change in all sectors of society is needed. Change processes of societal innovations are complex, non-linear, and dynamic transitions, for which scientific research increased in recent years. However, the concept of transitions and the proper role of science in promoting change is still debated. In this dissertation, I am especially interested in using scientific methods to understand drivers and barriers of societal innovation, engaging with societal actors, and increasing the effectiveness of interventions. To test the adequacy of System Dynamics modeling as a tool to support transition management, I conduct a case study in the construction material industry in Switzerland. The construction material industry is a traditional industry sector that faces public pressure to change dominant practices towards more sustainability. Yet recycling activities stagnate, and the potential of secondary resources is not utilized. I use six participative modeling workshops with public policy experts and seven interviews with extraction, disposal, recycling companies to develop a quantitative simulation model. This simulation model allows for virtual experiments to accelerate the transition of Switzerland's mineral construction material industry towards a circular economy. In this simulation model, I explain how the dynamic interaction between public policy and industry actors complicates the management of natural resource stocks. The co-production of extraction and disposal policies emerges as the central structure that forms a barrier to a circular economy. These spatial planning policies increase the incentive for companies to extract resources to generate volume for waste disposal. The resulting oversupply of primary resources locks out the use of secondary resources. I suggest experimenting with cooperative spatial planning between urban resource consumers and the hinterlands as a resource supplier to overcome this barrier. This cooperative spatial planning format is a leverage point for the local utilization of secondary resources without increasing material transports between regions. Based on this case study, I discuss integrating system dynamics in applied research for sustainability transitions, providing an empirical perspective on the intersection of System Dynamics (SD) and Transition Management (TM). Beyond the empirical findings for the governance of the transition of the industry sector in the case study, I focus on the methodological contribution of SD for TM. The findings are twofold. Firstly, by documenting participants' mental models during the participative modeling workshops, I gain insights into their learning process. These insights are essential to understand common misperceptions about the governance of the industry sector. For example, identifying the informal policy of extending gravel licenses rather than foreclosing after the expiration of the licensed duration was a critical insight. Furthermore, the discussion surrounding this policy clarified the role of adaptive expectations for the uptake of secondary resources. If new licensing processes do not consider the potential of secondary resources, a structural oversupply of primary resources results. Secondly, SD modeling adds operational guidance to the identification of fields for governance experimentation. These fields for governance experimentation are presented as more than just policy recommendations. They intend to induce more systemic changes, e.g., move from local spatial planning towards interregional spatial planning concepts. The insight that such systemic changes are necessary results from a formal model that clarified the scale of the problem (e.g., interregional arbitrage inhibits local recycling initiatives) and scope for required solutions (interregional spatial planning instead of local policy adjustments). I conclude that SD adds to the orientation phase of TM processes by providing an operational toolbox to engage with policy-relevant actors in a learning process and point at fields for experimentation. However, I also identify that the formal SD perspective in parts inhibited more daring and radical propositions for experimentation. While some might argue this is a weakness, I respond that SD modeling provides feasible recommendations based on identifying leverage points for long-term change.