Fare Elasticity of Passengers in Mountainous Urban Rail Transit Considering Station Heterogeneity

Promoting sustainable mobility and socio-economic sustainability through demand management is critical for mountainous urban rail systems. This study investigates urban rail transit in mountainous cities, focusing on how passenger travel behavior responds to time-based pricing policies across different station types, with the aim of informing differentiated fare policy design. Using Chongqing—a city with pronounced mountainous terrain—as a case study, we classified stations into 12 categories based on 11 indicators, including road slope, bus transfer density, average housing price, and peak-hour train crowding within a 500 m radius. This classification was then combined with questionnaire data to quantify fare elasticity of departure time. The results show that high-value bus-transfer congested stations are concentrated in central urban clusters with dense bus networks, mitigating terrain constraints and encouraging active travel. In contrast, low-value pedestrian-transfer comfort-oriented stations are predominantly located on the urban periphery, where sparse road networks and steep terrain exert greater influence. Low-value pedestrian-transfer congested stations exhibit the highest fare elasticity across all periods, indicating greater sensitivity to fare changes, while high-value bus-transfer comfort-oriented stations demonstrate the lowest elasticity, with passengers more likely to maintain existing travel patterns. Multiple linear regression identifies six significant determinants of fare elasticity, including section-level passenger crowding, average housing price, and bus route density. Sensitivity analysis using multinomial logistic regression further reveals that increasing bus route availability enhances the stability of low-value balanced-transfer comfort-oriented stations, whereas improving walkability can shift stations toward pedestrian-transfer types. By tailoring time-of-day pricing to station heterogeneity, policymakers can achieve equitable and environmentally friendly demand management, enhance operational efficiency and support sustainable urban development in mountainous regions.

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Publication Details

Journal
Sustainability
Published
2025-11-24
DOI
https://doi.org/10.3390/su172310530
Primary Topic
Transportation Planning and Optimization
Type
article
Field-Weighted Citation Impact
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article

Fare Elasticity of Passengers in Mountainous Urban Rail Transit Considering Station Heterogeneity

Xinchen Ran, Qingru Zou, Yue Xia, Jiaxiao Feng et al.
Sustainability
Transportation Planning and Optimization
article

Fare Elasticity of Passengers in Mountainous Urban Rail Transit Considering Station Heterogeneity

Xinchen Ran, Qingru Zou, Yue Xia, Jiaxiao Feng, Yi Yang
article en

Abstract

Promoting sustainable mobility and socio-economic sustainability through demand management is critical for mountainous urban rail systems. This study investigates urban rail transit in mountainous cities, focusing on how passenger travel behavior responds to time-based pricing policies across different station types, with the aim of informing differentiated fare policy design. Using Chongqing—a city with pronounced mountainous terrain—as a case study, we classified stations into 12 categories based on 11 indicators, including road slope, bus transfer density, average housing price, and peak-hour train crowding within a 500 m radius. This classification was then combined with questionnaire data to quantify fare elasticity of departure time. The results show that high-value bus-transfer congested stations are concentrated in central urban clusters with dense bus networks, mitigating terrain constraints and encouraging active travel. In contrast, low-value pedestrian-transfer comfort-oriented stations are predominantly located on the urban periphery, where sparse road networks and steep terrain exert greater influence. Low-value pedestrian-transfer congested stations exhibit the highest fare elasticity across all periods, indicating greater sensitivity to fare changes, while high-value bus-transfer comfort-oriented stations demonstrate the lowest elasticity, with passengers more likely to maintain existing travel patterns. Multiple linear regression identifies six significant determinants of fare elasticity, including section-level passenger crowding, average housing price, and bus route density. Sensitivity analysis using multinomial logistic regression further reveals that increasing bus route availability enhances the stability of low-value balanced-transfer comfort-oriented stations, whereas improving walkability can shift stations toward pedestrian-transfer types. By tailoring time-of-day pricing to station heterogeneity, policymakers can achieve equitable and environmentally friendly demand management, enhance operational efficiency and support sustainable urban development in mountainous regions.

SustainabilityVol. 17(23)
Chongqing Jiaotong University (CN)
Openalex Percentile: Top 64%
Transportation Planning and Optimization
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