Analysis of the Impact of Seamless Transportation on Airport Passenger Mode Choice: A Quantitative Study of Airport Train Services
Abstract
Seamless transportation is increasingly important for improving airport accessibility, yet the mechanisms through which multimodal integration shapes passengers’ transportation choices remain insufficiently understood. This study develops an integrated framework to examine the relationship between seamless transportation and airport passenger mode choice, focusing on the mediating roles of perceived convenience and perceived reliability. Drawing on discrete choice theory and the hybrid choice modelling framework, the study conceptualizes seamless transportation through physical, temporal, informational, and ticketing integration. The proposed Hybrid Choice Model (HCM) integrates passengers’ latent perceptions with observed travel attributes, including travel time, travel cost, waiting time, and access distance, to explain the relative utility of airport rail compared with competing ground transportation alternatives. The framework further specifies direct and indirect pathways through which seamless transportation may influence mode choice. Methodologically, the study proposes a quantitative explanatory design using passenger survey data and, where feasible, revealed-preference and stated-preference observations. The proposed analysis evaluates measurement quality, structural relationships, mediation effects, and discrete choice model performance. The framework contributes to transportation research by distinguishing convenience from reliability as complementary behavioral mechanisms and by integrating these perceptions into a utility-based choice model. From a managerial perspective, it highlights the importance of coordinated transfers, integrated passenger information, interoperable ticketing, and dependable service operations alongside competitive travel times and costs. The framework provides a basis for evaluating passenger-oriented airport access strategies and informing multimodal transport planning. Its empirical conclusions, however, require validation using observed passenger data and an appropriately estimated HCM.
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