Quantification of circular economy (CE) is essential for effective implementation, yet also fundamentally challenging, because it is inherently complex, featuring multiple interactions and system-level dynamicity. Two main approaches of systems thinking, commonly used to model complexities in intricate systems, are: system dynamics (SD), providing a top-down, macroscopic view; and agent-based modelling and simulation (ABMS), offering a bottom-up, microscopic perspective. Here we conducted a Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews (PRISMA-ScR) review, examining 60 studies applying SD or ABMS to CE, across sectors such as bio-based materials, construction and industrial symbiosis. Both methods capture aspects of circularity’s feedback loops and time evolution, but they are often used in isolation in the absence of integrated platforms along with concerns over computational costs. This limits their capacity to comprehensively model internal dynamics at multiple scales and provide system-wide decision support. Few studies explore the potential of combining SD and ABMS or attempt to integrate them with static tools, such as life-cycle assessment and multi-criteria decision analysis. Standardised metrics and operational holistic evaluation tools incorporating economic, environmental, technical and social sustainability aspects are missing – especially with the latter. A more unified and comprehensive systems approach to support informed decisions on circularity would improve evidence-based policymaking and empower wider industrial adoption.
Boral et al. (2026) studied this question.