How does the built environment affect intermodal transit demand across different spatiotemporal contexts?

Jiayou Lei, Min He, Zhuangbin Shi, Mingwei He, Yang Liu, Qian Qian and Huimin Qian

Journal of Transport Geography, 2024, vol. 121, issue C

Abstract: Bus and metro are the two primary modes of public transportation in many megacities worldwide. Understanding their cooperation is crucial for the integration of the public transportation system. Despite extensive research on public transportation demand, studies focusing on bus-metro cooperation remain limited. Intermodal transit demand directly reflects the level of cooperation between the two modes in travel behavior. In this study, intermodal transit demand is extracted from smart card data in Beijing, China. The extreme gradient boosting algorithm is employed to investigate the determinants of intermodal transit demand considering spatiotemporal variation. The SHapley Additive exPlanations method further interprets these models. Findings reveal that (1) the relative spatial relationship between bus and metro service facilities significantly influences their cooperation; however, these influences gradually weaken as urban space expands from the core to the peripheral area; (2) in peripheral area, the characteristics of the bus network hold the highest average importance ranking; (3) extensive nonlinear relationships and threshold effects exist between the built environment and intermodal transit demand, with the magnitude, pattern, and direction of these impacts varying significantly across different spatiotemporal contexts; and (4) changes in the spatial layout of transportation service supplies impact their competition and cooperation, such as adequate bus service supplies potentially reducing the cooperation between bus and metro to some extent. These findings will assist planners and public transit operators in developing regulations that encourage cooperation between bus and metro, thereby increasing the attraction and competitiveness of the public transit system.

Keywords: Public transportation; Intermodal transit demand; Built environment; Nonlinear effects; Spatiotemporal variation; Smart card data (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jotrge:v:121:y:2024:i:c:s0966692324002424

DOI: 10.1016/j.jtrangeo.2024.104033

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