Analysis of Travel Mode Choice Behavior between High-Speed Rail and Air Transport Utilizing Large-Scale Ticketing Data

模式选择 多项式logistic回归 门票 旅游行为 离散选择 模式(计算机接口) 计量经济学 采购 竞赛(生物学) 市场份额 运输工程 罗伊特 计算机科学 统计 营销 业务 经济 数学 工程类 公共交通 生态学 计算机安全 生物 操作系统
作者
Weiwei Cao,Zibing Chen,Feng Shi,Jin Xu
出处
期刊:Transportation Research Record [SAGE Publishing]
标识
DOI:10.1177/03611981241270169
摘要

As essential infrastructure, high-speed rail (HSR) and air transport (AT) play crucial roles in socioeconomic development. With their continuous expansion in China, the overlap of HSR and AT networks has increased, providing travelers with more choices for intercity travel. Because fierce competition in the medium-to-long-distance segment affects the market share and transport capacity dispatching, the travel choice between HSR and AT has been of intense interest. This study utilized a unique fusion dataset collected from two separate organizations to conduct an empirical analysis of the travel mode choice behaviors of individuals when choosing between HSR and AT. A multinomial logit (MNL) model was adopted to examine the influences of key factors on passenger choice preferences. The results showed that the fitting effect of the MNL model was satisfactory, and the parameters were strongly interpretable. The McFadden Pseudo R 2 with a city-pair fixed effect in the MNL model increased by 17.3% compared with that without the city-pair fixed effect. All the related explanatory variables, including the trip distance by high-speed train, demography, ticket purchasing, and travel behavior characteristics, had significant positive effects on the passengers’ choice of AT, with trip distance having the largest effect. According to the parameter estimation, 1,160 km was the division for individual choice between HSR and AT. This study also compared the prediction accuracies of the MNL model and eight classical machine-learning models and found that random forest had the best performance. This study provides a new framework for analyzing travel choice modeling when choosing between HSR and AT.
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