Evaluating sustainable urban mobility for public transit incorporating the geospatial modeling approach

Jae-Yeon Hwang, Shin-Hyung Cho and Shin Hyoung Park

Journal of Transport Geography, 2025, vol. 123, issue C

Abstract: Cities have established public transit infrastructures to provide equitable services to every citizen at a low cost, thus minimizing traffic congestion. Public transportation facilities, including bus stops, urban railway stations, and terminals, provide physical convenience to passengers. Considering economic efficiency, the location selection of public transport facilities causes an imbalance in public transit accessibility within the city. Therefore, to alleviate spatial imbalance, it is necessary to devise a public transportation system evaluation method. This study uses revealed travel data to develop a competitiveness index for sustainable urban mobility in public transit. The developed competitiveness index considers two aspects: (1) mobility factors referring to in-vehicle, transfer, and waiting times, and (2) travel demand and economic factors of travel costs. Square cells of 500 m × 500 m were used to apply the geographical explanatory variables in Seoul. The developed competitiveness index ranged from −22.7 to 23.25, thus confirming the difference in sustainable mobility services between the urban center and outskirts. Notably, a spatial cell with subway stations has a high competitiveness index because subway facilities are the main factors that increase the competitiveness of public transit. Multiscale geographically weighted regression, which identifies interactions through spatial dependence and heterogeneity, is employed to analyze the causal relationship between spatial mode competitiveness and socioeconomic characteristics. The developed index is expected to contribute to the establishment of public transportation policies and systems to alleviate imbalances by identifying areas vulnerable to public transit services.

Keywords: Sustainable urban mobility; Public transit; Competitiveness; Multiscale geographically weighted regression (MGWR); Revealed travel data (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jotrge:v:123:y:2025:i:c:s0966692325000018

DOI: 10.1016/j.jtrangeo.2025.104110

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