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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Zou et al. (2025) studied this question.
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