Dynamic Governance of Electric Vehicle Supply Chain Network Resilience Under Disruption Risks

In the context of multiple overlapping uncertainties, upstream disruptions in electric vehicle supply chain networks are becoming increasingly frequent. Given the dynamic and sudden nature of disruption risks, this paper introduces a stochastic stopping model to incorporate disruption risks into resilience governance. This study constructs a differential game model for resilience governance in electric vehicle supply chain networks, involving governments, suppliers, and core manufacturers. This study proposes a dynamic resilience differential equation, which integrates resilience investment efforts. Then, this study explores optimal resilience strategies and dynamic equilibrium trajectories of resilience levels under three game models. The results indicate that optimal resilience investment efforts are negatively correlated with the effort-cost coefficients, resilience decay rates, disruption probability, and damage rate. Conversely, these efforts are positively correlated with supply chain network resilience, benefits, and the resilience influence coefficients. Disruption probability and damage rate are negatively correlated with benefits. Disruption risks distort the time preferences of governance entities, causing them to overvalue immediate gains and undervalue future returns. Finally, both supply chain resilience and total benefits reach their optimal levels under the collaborative game model.