Dynamic resilience assessment of global shipping networks against cascading effects: An AIS data-driven complex network analysis

• Develops an AIS data-driven framework for dynamic resilience assessment of global shipping networks. • Integrates network modelling, cascading failure simulation, and resilience quantification. • Identifies port communities and critical hubs using DBSCAN and trajectory simplification. • Reveals regional resilience disparities and provides insights for port and policy optimization. Assessing the resilience of global shipping networks is essential for understanding and mitigating systemic disruptions in maritime transport and their cascading impacts on global trade. Existing studies, however, have largely emphasized static network structures while overlooking the dynamic processes that govern cascading failures. To bridge this gap, this study proposes an Automatic Identification System (AIS) data-driven framework integrating network modeling, cascading failure simulation, and resilience quantification. A deadweight tonnage (DWT)-weighted global shipping network is constructed by combining 2022 AIS data with vessel capacity information. Unlike conventional analyses at the terminal level, this study advances resilience assessment to the port level, enabling evaluation of large-scale disruptions that affect entire ports or strategic maritime corridors (e.g., the Suez Canal blockage and Red Sea crisis). Port communities are identified through DBSCAN-based clustering, while ship trajectories are simplified using the Douglas-Peucker algorithm to preserve key navigational nodes. Four attack scenarios, random, degree-based, betweenness-based, and TOPSIS-based hybrid attacks, are simulated to examine how static robustness metrics evolve during cascading failure propagation. Results show that targeted attacks on high-betweenness nodes can triple cascading failure severity compared with random disruptions. Regional analyses further indicate that European networks suppress failure propagation 22 % more effectively than Asia-Pacific systems, where single-node capacity losses above 20 % can trigger systemic collapse. These findings reveal significant regional disparities in resilience and highlight the importance of safeguarding hub ports and optimizing port capacity. The proposed framework provides new empirical insights into the dynamic resilience of global shipping networks and offers valuable implications for maritime policymakers and port authorities to strengthen global supply chain stability.