Vulnerability evaluation and resilience enhancement of the LNG shipping network: From the perspective of alliances

This study constructs a dynamically weighted global LNG shipping network using spatiotemporal-dense AIS data. An important port (IP) index integrating topological and functional attributes is proposed to identify critical hubs. Vulnerability is assessed under random and targeted attack scenarios using multidimensional metrics. Furthermore, a port alliance mechanism is introduced to simulate cooperative protection, where the Louvain algorithm identifies alliances and a load redistribution model based on geographic distance, IP, and Port Mutual Information (PMI) is developed. Results indicate the network exhibits scale-free properties and is highly vulnerable to targeted attacks, where the failure of critical hubs triggers systemic collapse. The port alliance mechanism significantly reduces vulnerability under random attacks but demonstrates limited improvement under targeted attacks, revealing a binary resilience characteristic of being strong against random, weak against targeted disruptions. Sensitivity analysis shows that assigning higher weights to geographic proximity and PMI enhances the mechanism's effectiveness. This research furnishes both conceptual grounding and empirical evidence for enhancing risk governance and fostering cross-border collaboration within global LNG shipping network.