Transit connectivity is a critical indicator for evaluating the transfer efficiency and network performance of hub airports within integrated transport systems. However, conventional connectivity models primarily rely on flight frequency and schedule coordination, while passenger path choice behavior and multimodal competition effects are often overlooked. To address this limitation, this study develops an enhanced transit connectivity evaluation framework that incorporates passenger path choice preferences and air–rail intermodal effects. A novel air–rail intermodal gain coefficient is introduced to capture the context-dependent interplay between aviation and high-speed rail, quantifying synergistic effects when HSR complements air transfer and substitution effects when it competes with it. The proposed model integrates direct transfer connectivity (Cd) and indirect transfer connectivity (Cind) within a unified quantitative framework, embedding transfer time compliance and detour factor constraints to improve behavioral realism and operational applicability. A case study of Xi’an Xianyang International Airport demonstrates that the introduction of the intermodal gain mechanism increases overall transit connectivity from 3606.3 to 3664.1, with the gain concentrated in the 500 to 800 km distance band where HSR journey times are most competitive with door-to-door air travel. The results reveal strong polarization in direct transfer connectivity and the limited effectiveness of indirect transfer routes due to transfer time constraints. The proposed framework offers a replicable assessment tool for hub airport network connectivity and multimodal transport planning, with potential for broader application across hub airports operating within integrated air–rail networks.
Li et al. (Wed,) studied this question.
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