Port hierarchical structure mining and pattern analysis in global shipping hypergraph network

With the increasing complexity of the global container shipping network, it exhibits multi-level collaborative relationships and high-order interactions among multiple ports. This study proposes a directed weighted hypergraph model analysis framework based on global AIS data, considering port berthing order and throughput capacity. By applying weighted K-core and motif methods, it analyzes the structural hierarchy and connectivity patterns of global ports. Results reveal a 7-level global container port hierarchy. Between 2015 and 2023, the network evolved into a more decentralized and structurally stable system. Strong dependencies surged from 31.5% to 50.5%, concentrating in the top three tiers, while direct subordinates of mega-hubs decreased, fostering balanced, collaborative clusters. Furthermore, transportation between higher-level ports (Levels 1–3) primarily forms hub-and-spoke structures, whereas lower-level ports rely on bridging structures. Consequently, we suggest lower-level ports strengthen hinterland routes to enhance hub collaboration. This research provides theoretical support for authorities to clarify port positioning and plan development. It also identifies smaller ports with locational advantages, encouraging them to develop local import and export industries.