A system dynamics-based framework for examining Circular Economy transitions

Abstract

Decision-makers in the public policy and business arenas need tools to deal with multiple sources of complexity in Circular Economy (CE) transitions. System Dynamics (SD) facilitates coping with increased complexity by enabling closed-loop thinking via identifying the causal structures underlying behaviour and permitting to proactively experiment with the system through simulation. This research aims to propose and test an SD-based framework for examining CE transitions to supporting decision-making at the micro-, meso-, and macro-levels. Two inductive model-based cases studies led to formalising the framework, finally tested in a third deductive model-based case study. The framework is built upon the well-known stages for building SD simulation models and complemented with domain-specific activities, guiding questions, and expected outcomes when examining CE transitions. The SD-based framework is the first modelling-oriented prescriptive approach to help researchers and practitioners examining CE transitions on their journeys to understand and facilitate changes through SD simulation models.