Modeling cascading risk diffusion in global container shipping network under dynamic flow reassignment

Unexpected port disruptions, caused by severe congestion or geopolitical conflicts, can lead to reassignment of shipping flows and trigger cascading hazards across the Global Container Shipping Network (GCSN), with far-reaching socioeconomic impacts. Understanding the mechanisms of such cascading risk propagation requires accurate simulation of dynamic flow reassignment and the development of a tailored diffusion model for maritime scenarios. This research introduces a novel cascading modeling framework that captures port-level dynamic shipping flow reassignment and assesses cascading failure diffusion in the GCSN. Using massive container vessel trajectory data, we design a directed and weighted GCSN, identify alternative ports for disrupted nodes through a combination of network topology analysis and geographic nearest-neighbor search, and refine port selection with a nonlinear trajectory cost function incorporating maritime distance, vessel load differences, and port size. Cascading failure is simulated by integrating the Motter-Lai load-capacity model with the dynamic reassignment process, and three maritime-specific vulnerability indicators are proposed to evaluate network resilience. The findings show that limiting port loads to 60 % of capacity or increasing port capacity by 40 to 60 % significantly mitigates cascading risk. It also appears that the European port system is found to be more susceptible to cascading disruptions than its East Asian counterpart. The proposed approach provides actionable insights and risk mitigation strategies for enhancing the resilience of global maritime logistics in the face of unexpected disruptions.