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Optimization of Differential Pricing and Seat Allocation in High-Speed Railways for Multi-Class Demands: A Chinese Case Study

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  • Wenliang Zhou

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China)

  • Ziyu Zou

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China)

  • Naijie Chai

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China)

  • Guangming Xu

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China)

Abstract

There are many options for passengers choosing to travel by train. In order to maximize price revenue requests, railway companies must consider the differences between passenger types in the process of formulating ticket strategies. This study firstly subdivides passenger demand according to the latent class model based on Stated Preference (SP) and Revealed Preference (RP) survey data, then the passenger’s preference for train service attributes is identified. Based on the prospect theory, logit model and passenger flow transfer model, the final passenger flow assignment result is obtained. A differential pricing and seat allocation model aiming at maximizing price revenue is established, and a simulated annealing (SA) algorithm is designed to solve it. The results of the case show that the proposed model can increase revenue by 3.52% and by 1.02% compared with the result under single fares and without demand division.

Suggested Citation

  • Wenliang Zhou & Ziyu Zou & Naijie Chai & Guangming Xu, 2023. "Optimization of Differential Pricing and Seat Allocation in High-Speed Railways for Multi-Class Demands: A Chinese Case Study," Mathematics, MDPI, vol. 11(6), pages 1-17, March.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:6:p:1412-:d:1097483
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    References listed on IDEAS

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    1. Eldeeb, Gamal & Mohamed, Moataz, 2020. "Quantifying preference heterogeneity in transit service desired quality using a latent class choice model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 119-133.
    2. Ulrich Schmidt & Chris Starmer & Robert Sugden, 2008. "Third-generation prospect theory," Journal of Risk and Uncertainty, Springer, vol. 36(3), pages 203-223, June.
    3. van Vuuren, Daniel, 2002. "Optimal pricing in railway passenger transport: theory and practice in The Netherlands," Transport Policy, Elsevier, vol. 9(2), pages 95-106, April.
    4. Jin Qin & Wenxuan Qu & Xuanke Wu & Yijia Zeng, 2019. "Differential Pricing Strategies of High Speed Railway Based on Prospect Theory: An Empirical Study from China," Sustainability, MDPI, vol. 11(14), pages 1-17, July.
    5. Hetrakul, Pratt & Cirillo, Cinzia, 2014. "A latent class choice based model system for railway optimal pricing and seat allocation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 61(C), pages 68-83.
    6. Ching-Cheng Chao & Taih-Cherng Lirn & Kuo-Chung Shang, 2013. "Market segmentation of airline cargo transport," The Service Industries Journal, Taylor & Francis Journals, vol. 33(15-16), pages 1672-1685, December.
    7. Brons, Martijn & Pels, Eric & Nijkamp, Peter & Rietveld, Piet, 2002. "Price elasticities of demand for passenger air travel: a meta-analysis," Journal of Air Transport Management, Elsevier, vol. 8(3), pages 165-175.
    8. Nuzzolo, Agostino & Crisalli, Umberto & Gangemi, Francesca, 2000. "A behavioural choice model for the evaluation of railway supply and pricing policies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 34(5), pages 395-404, June.
    9. Drabas, Tomasz & Wu, Cheng-Lung, 2013. "Modelling air carrier choices with a Segment Specific Cross Nested Logit model," Journal of Air Transport Management, Elsevier, vol. 32(C), pages 8-16.
    10. Piet Rietveld & Stefan van Woudenberg, 2007. "Second-best Decision Making of Railway Operators: How to Fix Fares, Frequency and Vehicle Size," Journal of Transport Economics and Policy, University of Bath, vol. 41(3), pages 363-385, September.
    11. Hetrakul, Pratt & Cirillo, Cinzia, 2013. "Accommodating taste heterogeneity in railway passenger choice models based on internet booking data," Journal of choice modelling, Elsevier, vol. 6(C), pages 1-16.
    12. Paulley, Neil & Balcombe, Richard & Mackett, Roger & Titheridge, Helena & Preston, John & Wardman, Mark & Shires, Jeremy & White, Peter, 2006. "The demand for public transport: The effects of fares, quality of service, income and car ownership," Transport Policy, Elsevier, vol. 13(4), pages 295-306, July.
    13. Basu, Debasis & Hunt, John Douglas, 2012. "Valuing of attributes influencing the attractiveness of suburban train service in Mumbai city: A stated preference approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(9), pages 1465-1476.
    14. Santos, Georgina & Maoh, Hanna & Potoglou, Dimitris & von Brunn, Thomas, 2013. "Factors influencing modal split of commuting journeys in medium-size European cities," Journal of Transport Geography, Elsevier, vol. 30(C), pages 127-137.
    15. Lin, Kyle Y. & Sibdari, Soheil Y., 2009. "Dynamic price competition with discrete customer choices," European Journal of Operational Research, Elsevier, vol. 197(3), pages 969-980, September.
    16. Jung, Se-Yeon & Yoo, Kwang-Eui, 2016. "A study on passengers' airport choice behavior using hybrid choice model: A case study of Seoul metropolitan area, South Korea," Journal of Air Transport Management, Elsevier, vol. 57(C), pages 70-79.
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