From structure to function: A comprehensive benchmark on the estimation of hubs in air transportation through complex network metrics

Hubs play a critical role in air transportation systems by switching/sorting/collecting and providing a consolidation/breakbulk function. Previous research has extensively employed network centrality measures, including degree, betweenness, and closeness, as primary indicators for identifying hubs within air transportation networks. These metrics serve to quantify an airport's significance based on its local/global connectivity and influence within the network. However, relying on topological indicators can be misleading due to the lack of empirical flow data, potentially resulting in an inaccurate assessment of an airport's true importance within the network. In this study, we provide a comprehensive evaluation of how useful complex network metrics are in the task of identifying hubs. Integrating worldwide aircraft movement and passenger origin–destination data, our study offers a comprehensive benchmark for hub identification through structural complex network techniques. The benefits of this research include a more informed usage of the quality obtained from complex network indicators as proxy for indicating the extent of hubs as well as, downstream, an enhanced network planning and optimized resource allocation.