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.