Passenger choice between demand-responsive train and pre-scheduled train in high-speed railway: A stated preference study

Demand-responsive transportation has been introduced in many cities around the world. However, whether it is applicable in the railway is still questionable, an exploration of passenger choice behavior between demand-responsive trains and pre-scheduled trains is pivotal in addressing this issue. To delve into passengers’ choice preferences when facing demand-responsive trains and to dissect the feasibility of implementing demand-responsive service in high-speed railways, the stated preference survey method is employed to investigate travel intention of passengers. Based on the survey data obtained in China, the heterogeneity of passengers is analyzed from three aspects: personal socio-economic characteristics, travel characteristics, and travel mode choice. Considering the situation that demand-responsive train cannot operate, the risk attributes are considered. To bolster the appeal of demand-responsive trains, personalized service product attributes are added. Mixed Logit mode, which takes into account the heterogeneous travel choice behavior of passengers, is developed, and Maximum Likelihood Estimation and the Monte Carlo method are used to calibrate model parameters. The willingness to pay in terms of different factors of passengers is determined. The results indicate that early arrival deviation time, late arrival deviation time, demand response time, and success rate of ticket purchase remarkable influence passengers’ decision regarding demand-responsive train, with only the success rate of ticket purchase positively impacting train choice. Moreover, the significant difference in train ticket price is observed solely in the self-funded long distance scenario, while demand-responsive trains are found to be particularly appealing in self-funded short distance scenario. Through the Willingness To Pay (WTP) analysis, it is discovered that by shortening demand response time, enhancing the success rate of ticket purchase, and minimizing the deviation times of early arrival and late arrival of trains, the attractiveness of the demand-responsive train to passengers under three travel scenarios can be augmented. This study provides profound insights into the possibility of railway enterprises operating demand-responsive trains. • First to explore the passenger choice behavior between demand-responsive train and pre-scheduled train in railway. • Risk and personalized service product attributes are considered. • We consider the passenger heterogeneity from both observable and unobservable aspects. • The impact of personal socio-economic attributes on the random parameters is considered.

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Publication Details

Journal
High-speed Railway
Published
2025-04-27
DOI
https://doi.org/10.1016/j.hspr.2025.04.002
Primary Topic
Transportation Planning and Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Passenger choice between demand-responsive train and pre-scheduled train in high-speed railway: A stated preference study

Jiefang Ma, Yongsheng Wang, Tao Li, Dewei Li et al.
High-speed Railway
Transportation Planning and Optimization
article

Passenger choice between demand-responsive train and pre-scheduled train in high-speed railway: A stated preference study

Jiefang Ma, Yongsheng Wang, Tao Li, Dewei Li, Han Gao, Haifeng Ji
article en

Abstract

Demand-responsive transportation has been introduced in many cities around the world. However, whether it is applicable in the railway is still questionable, an exploration of passenger choice behavior between demand-responsive trains and pre-scheduled trains is pivotal in addressing this issue. To delve into passengers’ choice preferences when facing demand-responsive trains and to dissect the feasibility of implementing demand-responsive service in high-speed railways, the stated preference survey method is employed to investigate travel intention of passengers. Based on the survey data obtained in China, the heterogeneity of passengers is analyzed from three aspects: personal socio-economic characteristics, travel characteristics, and travel mode choice. Considering the situation that demand-responsive train cannot operate, the risk attributes are considered. To bolster the appeal of demand-responsive trains, personalized service product attributes are added. Mixed Logit mode, which takes into account the heterogeneous travel choice behavior of passengers, is developed, and Maximum Likelihood Estimation and the Monte Carlo method are used to calibrate model parameters. The willingness to pay in terms of different factors of passengers is determined. The results indicate that early arrival deviation time, late arrival deviation time, demand response time, and success rate of ticket purchase remarkable influence passengers’ decision regarding demand-responsive train, with only the success rate of ticket purchase positively impacting train choice. Moreover, the significant difference in train ticket price is observed solely in the self-funded long distance scenario, while demand-responsive trains are found to be particularly appealing in self-funded short distance scenario. Through the Willingness To Pay (WTP) analysis, it is discovered that by shortening demand response time, enhancing the success rate of ticket purchase, and minimizing the deviation times of early arrival and late arrival of trains, the attractiveness of the demand-responsive train to passengers under three travel scenarios can be augmented. This study provides profound insights into the possibility of railway enterprises operating demand-responsive trains. • First to explore the passenger choice behavior between demand-responsive train and pre-scheduled train in railway. • Risk and personalized service product attributes are considered. • We consider the passenger heterogeneity from both observable and unobservable aspects. • The impact of personal socio-economic attributes on the random parameters is considered.

High-speed RailwayVol. 3(2)
Beijing Jiaotong University (CN), China Railway Shanghai Design Institute Group (China) (CN)
National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 91%
Transportation Planning and Optimization
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