Abstract for: Beyond Deterministic Assumptions: A Stochastic System Dynamics Approach to Comparing Resilience in Linear vs. Circular Supply Chains

Supply chain resilience is critical amid global disruptions. While Circular Supply Chains (CSCs) are advocated for enhanced resilience, existing literature predominantly relies on deterministic disruption parameters, failing to capture stochastic realities. Only 40% of studies consider uncertainty, with little attention to multiple simultaneous uncertainties. We develop two comparative System Dynamics models: a 5-echelon Linear and a 9-echelon Circular Supply Chain with reverse logistics. Four stochastic factors (occurrence probability 5-55%, random start time, variable duration, severity) are integrated. Monte Carlo simulations (200 runs per scenario) assess resilience metrics. Findings challenge assumptions about circular network vulnerability. The resilience benefits of reverse flows dominate exposure risk even at high disruption probabilities (up to 55%). This suggests investing in circular capabilities is a viable resilience strategy in volatile environments, providing managers with evidence for circular transition decisions. AI used for language editing. All intellectual content is authors' own.