An integrated modelling framework for feedback-driven and mass-balanced circular economy analysis

Achieving a circular economy requires not only quantifying material stocks and flows but also understanding the dynamic processes that shape them over time. While Material Flow Analysis (MFA) is widely used to track physical stocks and flows, MFA has limited capacity to represent behavioral feedback, endogenous system responses, and temporal delays. System Dynamics (SD), by contrast, is well suited to capturing feedback structures and non-linear system behavior, but it does not inherently enforce mass conservation. Despite these fundamental differences, the two approaches are often applied without a clear conceptual distinction. Here, we compare and integrate MFA and SD to develop a modelling framework that is both mass balanced and feedback driven. Using three simplified models (MFA, SD, and integrated SD-MFA), we demonstrate that the integrated approach can simultaneously preserve mass balance and represent causal relationships, feedback loops, and time delays. The combined framework offers a more robust basis for analyzing circular economy transitions, enabling the assessment of not only how materials flow through systems, but also how socio-technical dynamics influence those flows over time.