Cascading Failure Modeling and Resilience Analysis of Coupled Centralized Supply Chain Networks Under Hybrid Loads

As manufacturing and logistics-oriented supply chains continue to expand in scale and complexity, and the coupling between their physical execution layers and information–decision layers deepens, the resulting high interdependence within the system significantly increases overall fragility. Driven by key technological barriers, economies of scale, and the trend toward resource centralization, supply chains have increasingly evolved into centralized structures, with critical functions such as decision-making highly concentrated in a few focal firms. While this configuration may enhance coordination under normal conditions, it also significantly increases dependency on focal nodes. Once a focal node is disrupted, the intense task, information, and risk loads it carries cannot be effectively dispersed across the network, thereby amplifying load spillovers, coordination imbalances, and information delays, and ultimately triggering large-scale cascading failures. To capture this phenomenon, this study develops a coupled network model comprising a Physical Network and an Information and Decision Risk Network. The Physical Network incorporates a tri-load coordination mechanism that distinguishes among theoretical operational load (capacity), actual production load (production output), and actual delivery load (order fulfillment), using a load sensitivity coefficient to describe the asymmetric propagation among them. The Information and Decision Risk Network is further divided into a communication subnetwork, which represents transmission efficiency and delay, and a decision risk subnetwork, which reflects the diffusion of uncertainty and risk contagion caused by information delays. A discrete-event simulation approach is employed to evaluate system resilience under various failure modes and parametric conditions. The results reveal the following: (1) under a centralized structure, poorly allocated redundancy can worsen local imbalances and amplify disruptions; (2) the failure of a focal firm is more likely to cause a full network collapse; and (3) node failures in the Communication System Network have a greater destabilizing effect than those in the Physical Network.