Original scientific paper
https://doi.org/10.7307/ptt.v34i3.3942
Modelling the Passenger Choice Behaviour of Buying High-Speed Railway Tickets
Zhenying Yan
; Transportation Institute, Inner Mongolia Engineering Research Center for Urban Transportation Data Science and Applications, Inner Mongolia University
Meiying Jian
; Transportation Institute, Inner Mongolia Engineering Research Center for Urban Transportation Data Science and Applications, Inner Mongolia University
Xiaojuan Li
; Transportation Institute, Inner Mongolia Engineering Research Center for Urban Transportation Data Science and Applications, Inner Mongolia University
Jinxin Cao
; Inner Mongolia Academy of Science and Technology
Abstract
Passenger choice behaviour of buying tickets has a great impact on the high-speed rail (HSR) revenue management. It is very critical to find out the sensitive factors that prevent passengers with high willingness to pay for a ticket from buying low-price tickets. The literature on passenger choice behaviour mainly focuses on travel mode choice, choice between a conventional train and a high-speed train and choice among high-speed trains. To extend the literature and serve revenue management, this paper investigates passenger choice behaviour of buying high-speed railway tickets. The data were collected by the stated preference (SP) survey based on Beijing-Hohhot high-speed railway. The conditional logit model was established to analyse influencing factors for business travel and non-business travel. The results show that: business passengers have the higher inherent preference for full-price tickets, while non-business passengers have the higher inherent preference for discount tickets; the number of days booked in advance and frequent passenger points have a significant impact on the ticket choice of business travellers, but not on non-business travellers; passengers are unwilling to buy tickets that depart after 16:00 for non-business travel; factors have different effects on the passengers' choice in business travel and non-business travel. The results can provide parameters for revenue management models and references for the ticket-product design.
Keywords
railway transportation; passenger choice behaviour; conditional logit model; SP survey; revenue management
Hrčak ID:
278627
URI
Publication date:
1.6.2022.
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