Measurement and Influencing Mechanism of Operational Efficiency for High-Speed Railway Hub Stations: Empirical Evidence from China’s Major HSR Nodes

As the key node of the high-speed railway network, hub stations undertake the core functions of passenger collection and distribution, train connection and network transfer, and their operational efficiency directly determines the overall service level and network operation quality of the high-speed railway system. Different from traditional train schedule optimization research, this paper focuses on the operational efficiency of HSR hub stations, constructs a comprehensive efficiency evaluation index system covering infrastructure scale, passenger organization capacity, and train operation level. Samples are screened via stratified grouping by region and station grade; a detailed roster of 28 selected hub stations and data elimination criteria are supplemented in Section 4.1, while the definition, statistical unit, and computational formula of all evaluation indicators and regression explanatory variables are supplemented in Section 2.2 and Section 3.3, respectively. Based on the actual panel operation data of 28 major national HSR hub stations from 2022 to 2024, the Super-SBM model is used to measure the static operational efficiency of hub stations, and the Malmquist index is introduced to analyze dynamic efficiency changes. All undesirable output indicators, including passenger complaint rate and average transfer time, are converted by reciprocal transformation before efficiency calculation, with a specific transformation rule stated in Section 2.2; the matching rationality between the number of decision-making units and indicator quantity is explained in Section 2.2, and the applicable reason and censoring threshold setting of the Tobit model are supplemented in Section 3.3. On this basis, a Tobit regression model is constructed to empirically test the key influencing factors and internal mechanism of station operational efficiency. The regression adopts full panel data consisting of 84 station-year observations, and regional dummy variables and station-scale dummy variables are added into the regression equations to control the heterogeneous impacts brought by geographical location and station size. The results show that the overall operational efficiency of China’s major HSR hubs presents a steady upward trend, but there are significant regional and scale differences; large-scale central hub stations have prominent scale efficiency advantages, while medium and small regional hubs generally have input redundancy and resource allocation imbalance. Passenger flow aggregation degree, train departure density, and station equipment intelligent level