The Passenger Preferences for Flexible Tickets and Key Attributes for Ticket Design of High-speed Railway: A Case Study from China

Jian Bai , Junchao Peng , Yingfeng Wei , Shuo Xu , Zhenying Yan , Jiaqing Lu

Urban Rail Transit ›› 2025, Vol. 11 ›› Issue (3) : 321 -334.

PDF
Urban Rail Transit ›› 2025, Vol. 11 ›› Issue (3) : 321 -334. DOI: 10.1007/s40864-025-00249-5
Original Research Papers
research-article

The Passenger Preferences for Flexible Tickets and Key Attributes for Ticket Design of High-speed Railway: A Case Study from China

Author information +
History +
PDF

Abstract

The high-speed railway (HSR) has become an important means of sustainable transportation, but most HSR lines are facing losses, especially China. Properly selling HSR flexible tickets has been verified to be an effective means to improve revenue. However, passengers’ choice behavior for flexible tickets directly determines whether revenue increases. There is no research identifying the factors influencing HSR flexible ticket choice to help operators appeal potential buyers and design popular flexible tickets. To fill this gap, this research conducted the stated preference survey and constructed the Integrated Choice and Latent Variables model to analyze the key factors that affect passengers’ purchase behavior toward HSR flexible tickets, including individual attributes, travel characteristics, scheme attributes, and potential factors. The results show that HSR flexible tickets are more attractive to passengers with higher education, longer travel distances, traveling alone, and traveling at their own expense, and those with lower perceived risk, higher environmental awareness, and higher technological interests. In addition, through data analysis, it is found that the fare, the earliest and latest departure time interval among the corresponding alternative trains, and the period in which the departure time interval is located will affect passengers’ willingness to purchase a flexible ticket as well as key elements in the design of the HSR flexible ticket. The study’s results can provide references for the design of HSR flexible tickets, suggestions for enhancing the passengers’ willingness to purchase flexible tickets, and choice behavior parameters for flexible ticket revenue management models.

Keywords

High-speed railway / Flexible product / Travel choice behavior / ICLV model

Cite this article

Download citation ▾
Jian Bai, Junchao Peng, Yingfeng Wei, Shuo Xu, Zhenying Yan, Jiaqing Lu. The Passenger Preferences for Flexible Tickets and Key Attributes for Ticket Design of High-speed Railway: A Case Study from China. Urban Rail Transit, 2025, 11(3): 321-334 DOI:10.1007/s40864-025-00249-5

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Ben-AkivaM, McFaddenD, TrainK, WalkerJ, BhatC, BierlaireM, BolducD, Boersch-SupanA, BrownstoneD, BunchDS, DalyA, PalmaAD, GopinathD, KarlstromA, MunizagaMA. Hybrid choice models: progress and challenges. Mark Lett, 2002, 13: 163-175.

[2]

BursaB, MailerM, AxhausenKW. Travel behavior on vacation: transport mode choice of tourists at destinations. Transp Res Pt A-Policy Pract, 2022, 166: 234-261.

[3]

ChenJ, BellPC. Enhancing revenue by offering a flexible product option. Int Trans Oper Res, 2017, 24: 801-820.

[4]

CartenìA, PariotaL, HenkeI. Hedonic value of high-speed rail services: quantitative analysis of the students’ domestic tourist attractiveness of the main Italian cities. Transp Res Pt A-Policy Pract, 2017, 100: 348-365.

[5]

GallegoG, PhillipsR. Revenue management of flexible products. M&SOM-Manuf Serv Oper Manag, 2004, 6: 321-337.

[6]

KochS, GönschJ, SteinhardtC. Dynamic programming decomposition for choice-based revenue management with flexible products. Transp Sci, 2017, 51: 1046-1062.

[7]

KavtaK, GoswamiAK. Estimating mode choice of motorized two-wheeler commuters under the influence of combined travel demand management measures: An ICLV modeling approach. Transp Policy, 2022, 126: 327-335.

[8]

LeJ, TengJ. Understanding influencing factors of travel mode choice in urban-suburban travel: a case study in Shanghai. Urban Rail Transit, 2023, 9: 127-146.

[9]

MaB, AdamSWB, TeoCC, WongYD. How do consumers’ fashion lifestyles differentiate their logistics preferences for fashion products?. J Retail Consum Serv, 2024, 79. 103798

[10]

MangS, PostD, SpannM. Pricing of flexible products. Rev Manag Sci, 2012, 6: 361-374.

[11]

PanX, LiuS. Modeling travel choice behavior with the concept of image: a case study of college students’ choice of homecoming train trips during the Spring Festival travel rush in China. Transp Res Pt A-Policy Pract, 2022, 155: 247-258.

[12]

PanH, GaoY, ShenQ, MoudonAV, TuoJ, HabibKN. Does high-speed rail mitigate peak vacation car traffic to tourist city? Evidence from China. Transp Policy, 2023, 143: 93-105.

[13]

PengW, TengJ, WangH. Understanding heterogeneous passenger route choice in municipal rail transit with express and local trains: an empirical study in Shanghai. Urban Rail Transit, 2024, 10: 122-143.

[14]

RenX, ChenZ, WangF, DanT, WangW, GuoX, LiuC. Impact of high-speed rail on social equity in China: evidence from a mode choice survey. Transp Res Pt A-Policy Pract, 2020, 138: 422-441.

[15]

SuH, XuG, ZengQ, PengS, JiaX. Collaborative optimization of differential pricing and seat allocation for multiple high-speed trains considering passenger demand. J Railw Sci Eng, 2022, 4: 1-10

[16]

ThorhaugeM, HausteinS, CherchiE. Accounting for the theory of planned behaviour in departure time choice. Transp Res Pt F-Traffic Psychol Behav, 2016, 38: 94-105.

[17]

WangY, YanX, ZhouY, XueQ. Influencing mechanism of potential factors on passengers’ long-distance travel mode choices based on structural equation modeling. Sustainability, 2017, 91943.

[18]

Yadlin M (1985) Development of a model for probabilistic discrete decisions. Dissertation, University of California

[19]

YanZ, ZhangJ, HanB, LiX, CaoJ. Research on optimization of high-speed rail ticket allocation with flexible tickets. J China Railw Soc, 2022, 44: 17-25.

Funding

National Natural Science Foundation of China(72061028)

Natural Science Foundation of Inner Mongolia Autonomous Region(2022MS07020)

RIGHTS & PERMISSIONS

The Author(s)

AI Summary AI Mindmap
PDF

371

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/