Accelerating Transition Initiatives : The role of modelling tools

It is increasingly recognized that achieving a sustainable, low-carbon society with a high share of renewable energy requires societal transitions, involving structural societal changes across multiple dimensions. Whereas current-day research has mostly focused on the initiation stages of societal transitions, relatively little is known about how transition initiatives interact and accelerate in terms of an increase in scale, pace and diversity. The EU FP7 project `ARTS´ (Accelerating and Rescaling Transitions to Sustainability) aims to address this knowledge and practice gap. ARTS analyses transition initiatives from across Europe operating at the scale of a city-region and situated within national and wider European contexts. Through a transdisciplinary approach, the project aims to identify conditions, mechanisms and strategies to move transition initiatives forward in their contribution to local sustainability. Our presentation reflects on the potential role of qualitative and quantitative models for supporting such a (participatory) assessment and actual acceleration practice. The central question is how to design and apply models that capture complex transition dynamics (including interactions among transition initiatives), thereby supporting the critical reflection on potential acceleration strategies in the best possible way? To this end, we: . review previous examples of dynamic modelling applications for modelling transition dynamics; . describe a prototype generic agent-based model based on a theoretical conceptualization of the acceleration process; . describe a prototype context specific qualitative model (Fuzzy Cognitive Map) that aims to capture the particular acceleration dynamics for a case study on energy efficiency at the city level. Based on our findings, we identify key properties and mechanisms that drive acceleration processes and we discuss how to capture, understand and potentially reinforce those key properties and mechanisms with different modelling approaches. We conclude with a brief outlook towards the envisaged future modelling work and the methodology for co-creating models with stakeholders in participatory learning labs.