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Dynamic Pricing in Airline Seat Management for Flights with Multiple Flight Legs

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  • Peng-Sheng You

    (Department of Business Administration, Chang Jung University, 396, Section 1, Chang Jung Road, Town of Kway Jen, Tainan 711, Taiwan)

Abstract

Consider a multiple booking class airline-seat inventory control problem that relates to either a single flight leg or to multiple flight legs. During the time before the flight, the airline may face the problems of (1) what are the suitable prices for the opened booking classes, and (2) when to close those opened booking classes. This work deals with these two problems by only using the pricing policy. In this paper, a dynamic pricing model is developed in which the demand for tickets is modeled as a discrete time stochastic process. An important result of this work is that the strategy for the ticket booking policy can be reduced to sets of critical decision periods, which eliminates the need for large amounts of data storage.

Suggested Citation

  • Peng-Sheng You, 1999. "Dynamic Pricing in Airline Seat Management for Flights with Multiple Flight Legs," Transportation Science, INFORMS, vol. 33(2), pages 192-206, May.
    • Handle: RePEc:inm:ortrsc:v:33:y:1999:i:2:p:192-206
    DOI: 10.1287/trsc.33.2.192
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    References listed on IDEAS

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    Cited by:

    1. Shuihua Han & Bin Cao & Yufang Fu & Zongwei Luo, 2018. "A liner shipping competitive model with consideration of service quality management," Annals of Operations Research, Springer, vol. 270(1), pages 155-177, November.
    2. Pak, K. & Piersma, N., 2002. "Airline revenue management: an overview of OR techniques 1982-2001," Econometric Institute Research Papers EI 2002-03, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Jeffrey I. McGill & Garrett J. van Ryzin, 1999. "Revenue Management: Research Overview and Prospects," Transportation Science, INFORMS, vol. 33(2), pages 233-256, May.
    4. Zhuang, Weifen & Li, Michael Z.F., 2012. "Monotone optimal control for a class of Markov decision processes," European Journal of Operational Research, Elsevier, vol. 217(2), pages 342-350.
    5. Alec Morton, 2006. "Structural properties of network revenue management models: An economic perspective," Naval Research Logistics (NRL), John Wiley & Sons, vol. 53(8), pages 748-760, December.
    6. William L. Cooper, 2002. "Asymptotic Behavior of an Allocation Policy for Revenue Management," Operations Research, INFORMS, vol. 50(4), pages 720-727, August.
    7. William L. Cooper & Tito Homem-de-Mello, 2007. "Some Decomposition Methods for Revenue Management," Transportation Science, INFORMS, vol. 41(3), pages 332-353, August.
    8. Li, Juan & Tang, Ou, 2012. "Capacity and pricing policies with consumer overflow behavior," International Journal of Production Economics, Elsevier, vol. 140(2), pages 825-832.
    9. Gabriel Bitran & René Caldentey, 2003. "An Overview of Pricing Models for Revenue Management," Manufacturing & Service Operations Management, INFORMS, vol. 5(3), pages 203-229, August.
    10. Wen Chen & Adam J. Fleischhacker & Michael N. Katehakis, 2015. "Dynamic pricing in a dual‐market environment," Naval Research Logistics (NRL), John Wiley & Sons, vol. 62(7), pages 531-549, October.
    11. Kyle Y. Lin, 2004. "A sequential dynamic pricing model and its applications," Naval Research Logistics (NRL), John Wiley & Sons, vol. 51(4), pages 501-521, June.
    12. You, Peng-Sheng, 2008. "An efficient computational approach for railway booking problems," European Journal of Operational Research, Elsevier, vol. 185(2), pages 811-824, March.
    13. Xiao, Baichun & Yang, Wei, 2010. "A revenue management model for products with two capacity dimensions," European Journal of Operational Research, Elsevier, vol. 205(2), pages 412-421, September.
    14. Marlin W. Ulmer, 2020. "Dynamic Pricing and Routing for Same-Day Delivery," Transportation Science, INFORMS, vol. 54(4), pages 1016-1033, July.
    15. Pak, K. & Piersma, N., 2002. "airline revenue management," ERIM Report Series Research in Management ERS-2002-12-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    16. 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.
    17. You, Peng-Sheng, 2003. "Dynamic rationing policies for product with incremental upgrading demands," European Journal of Operational Research, Elsevier, vol. 144(1), pages 128-137, January.
    18. Andrei M. Bandalouski & Natalja G. Egorova & Mikhail Y. Kovalyov & Erwin Pesch & S. Armagan Tarim, 2021. "Dynamic pricing with demand disaggregation for hotel revenue management," Journal of Heuristics, Springer, vol. 27(5), pages 869-885, October.
    19. Fernando S. Oliveira, 2008. "A Constraint Logic Programming Algorithm for Modeling Dynamic Pricing," INFORMS Journal on Computing, INFORMS, vol. 20(1), pages 69-77, February.
    20. Marcus, Benjamin & Anderson, Chris K., 2008. "Revenue management for low-cost providers," European Journal of Operational Research, Elsevier, vol. 188(1), pages 258-272, July.
    21. Christopher P. Wright & Harry Groenevelt & Robert A. Shumsky, 2010. "Dynamic Revenue Management in Airline Alliances," Transportation Science, INFORMS, vol. 44(1), pages 15-37, February.
    22. Alavi Fard, Farzad & Sy, Malick & Ivanov, Dmitry, 2019. "Optimal overbooking strategies in the airlines using dynamic programming approach in continuous time," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 384-399.

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