内生性
偏爱
模式选择
公共交通
模式(计算机接口)
经济
计量经济学
显示偏好
工具变量
测量数据收集
智能卡
服务(商务)
拥挤
计量经济模型
公共物品
控制(管理)
微观经济学
公共经济学
人气
挤出效应
控制功能
支付意愿
人群
旅游行为
作者
Raúl Pezoa,Franco Basso,Marco Batarce,Louis de Grange,Rodrigo De la Puerta,Fernando Feres,Mauricio Varas
标识
DOI:10.1016/j.tranpol.2026.104019
摘要
The rapid growth of ride-hailing platforms has fundamentally altered urban mobility patterns, creating new competitive dynamics with established public transit systems. This study examines modal preferences using trip-level behavioral data from Santiago, Chile, combining smart card transactions and ride-hailing records to understand how travelers trade off service attributes. Our analysis employs econometric models that address endogeneity in both crowding levels and dynamic pricing through instrumental variables. Results demonstrate that passenger density significantly amplifies travel time disutility, with crowding effects substantially higher than previous stated preference estimates suggest. In this regard, the presence of a premium mobility alternative increases commuters’ aversion to crowded conditions. These findings have significant policy implications, as they suggest that in contexts where premium mobility alternatives are available or emerging, capacity planning based on traditional crowding valuations may be inadequate for contemporary urban environments and could result in insufficient public transportation provision. • We combine smart card transit data, trip-level crowding, and ride-hailing records. • Control function method addresses endogeneity in crowding and dynamic pricing. • Crowding valuations higher than prior estimates. • Low-crowding option amplifies commuters’ aversion to crowded public transport. • Findings suggest traditional crowding values may underestimate transit capacity needs.
科研通智能强力驱动
Strongly Powered by AbleSci AI