Risk propagation modelling and resilience assessment of supply chain networks based on an improved SIS model
提出一个嵌入决策的SIS动力学模型，整合性能触发的干预检测、动态资源调配和拓扑感知的资源分配，构建四维韧性评估框架，揭示极端冲击下动态性能韧性比结构因素更关键。
Traditional assessment methods fail to capture the dynamic interplay between risk propagation and managerial interventions, and cannot precisely quantify the evolutionary mechanisms underlying Supply Chain Network Resilience (SCNR). This study proposes a decision-embedded SIS dynamics model that explicitly integrates performance-state-triggered intervention detection, dynamic resource mobilisation, and topology-aware resource allocation into the modelling framework, enabling intervention behaviours to be endogenously activated by real-time system performance dynamics. Grounded in the complete life-cycle trajectory of disruption–intervention–recovery–adaptation, this study constructs a comprehensive four-dimensional resilience assessment framework encompassing absorptive, recovery, adaptive, and structural dimensions. The findings demonstrate that, while physical topology integrity governs SCNR under low-intensity shocks, the contribution of dynamic performance resilience metrics significantly surpasses that of structural factors under extreme shocks inducing large-scale structural fragmentation, thereby emerging as the decisive determinant of system viability. By breaking the autonomy constraint inherent in classical risk propagation models, this study provides a quantitative decision-making benchmark for differentiated resilience governance of SCNs under resource constraints.