Cascading failure and robustness in supply chain networks: A case study of new energy vehicles

The increasing complexity and vulnerability of new energy vehicle supply chain networks (NEVSNs) pose significant challenges to sustaining industrial robustness and mitigating cascading risks. This study evaluates the robustness of NEVSNs under multi-source disturbances, emphasizing the interactive roles of innovation capability, resource dependence, and network heterogeneity in collectively enhancing supply chain robustness. A dynamic four-layer directed weighted network model is developed to integrate these factors, incorporating a load-capacity interaction mechanism and probabilistic node failure to simulate cascading disruptions. Empirical data from Chinese NEV manufacturers and core suppliers are used for calibration and validation. Simulation results reveal that (1) enhancing innovation improves network efficiency and redundancy, while high resource dependence and centralization increase fragility; (2) battery and critical component suppliers are most sensitive to shocks, while network resilience is strengthened by diversified resources and collaboration; and (3) the proposed robustness metrics better capture vulnerability and recovery than conventional measures. These findings offer insights and recommendations for risk mitigation, network optimization, and robustness enhancement in NEV supply chains.