Abstract for: Social learning through virtual experimentation - Participatory modeling in transition processes

The field of sustainability transitions continues to attract scholars and practitioners interested in utilizing computer-aided modeling and simulation tools to provide decision support for transition processes. This study offers empirical insights into a participative modeling process of an industry sector’s transition towards a Circular Economy (CE). We use participative system dynamics modeling to engage with diverse stakeholders to understand the structure and behavior of the complex interlinkages between xxx, xxx, and xxx. Findings highlight how (1) transition barriers can be reinforced by misperceptions of stock and flow dynamics and (2) unintended consequences of institutionalized decision-rules can be uncovered by a dynamic feedback perspective. Both examples illustrate that learning occurs along the participative model development process. Reflecting on insights of this process, we highlight the value of increasing the analytical depth of the orientation phase, to identify leverage points for transition experiments. Here, the role and level of involvement of different stakeholders during the iterative model development is decisive for the level of insight. We conclude that participative system dynamics modeling supports transition processes by providing a reflexive tool for double loop learning in the development of transition experiments.