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Maximizing revenue in the airline industry under one-way pricing

Author

Listed:
  • M F Anjos

    (University of Southampton)

  • R C H Cheng

    (University of Southampton)

  • C S M Currie

    (University of Southampton)

Abstract

The paper describes a methodology that has been implemented in a major British airline to find the optimal price to charge for airline tickets under one-way pricing. An analytical model has been developed to describe the buying behaviour of customers for flights over the selling period. Using this model and a standard analytical method for constrained optimization, we can find an expression for the optimal price structure for a flight. The expected number of bookings made on each day of the selling period and in each fare class given these prices can then be easily calculated. A simulation model is used to find the confidence ranges on the numbers of bookings and these ranges can be used to regulate the sale of tickets. A procedure to update the price structure based on the remaining capacity has also been developed.

Suggested Citation

  • M F Anjos & R C H Cheng & C S M Currie, 2004. "Maximizing revenue in the airline industry under one-way pricing," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(5), pages 535-541, May.
    • Handle: RePEc:pal:jorsoc:v:55:y:2004:i:5:d:10.1057_palgrave.jors.2601721
    DOI: 10.1057/palgrave.jors.2601721
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    References listed on IDEAS

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    1. Guillermo Gallego & Garrett van Ryzin, 1994. "Optimal Dynamic Pricing of Inventories with Stochastic Demand over Finite Horizons," Management Science, INFORMS, vol. 40(8), pages 999-1020, August.
    2. Wen Zhao & Yu-Sheng Zheng, 2000. "Optimal Dynamic Pricing for Perishable Assets with Nonhomogeneous Demand," Management Science, INFORMS, vol. 46(3), pages 375-388, March.
    3. Gabriel R. Bitran & Susana V. Mondschein, 1997. "Periodic Pricing of Seasonal Products in Retailing," Management Science, INFORMS, vol. 43(1), pages 64-79, January.
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    Citations

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    Cited by:

    1. A Corominas & R Pastor, 2011. "Designing greedy algorithms for the flow-shop problem by means of Empirically Adjusted Greedy Heuristics (EAGH)," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(9), pages 1704-1710, September.
    2. C S M Currie & R C H Cheng & H K Smith, 2008. "Dynamic pricing of airline tickets with competition," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(8), pages 1026-1037, August.
    3. Joshan, Saeid & Maertens, Sven, 2020. "Low cost carriers in the Middle East and North Africa (MENA) region: Emergence and barriers to development," Journal of Transport Geography, Elsevier, vol. 87(C).
    4. Jacek Krawczyk & Christopher Sissons & Daniel Vincent, 2012. "Optimal versus satisfactory decision making: a case study of sales with a target," Computational Management Science, Springer, vol. 9(2), pages 233-254, May.
    5. Ryan Donnelly & Zi Li, 2022. "Dynamic Inventory Management with Mean-Field Competition," Papers 2210.17208, arXiv.org.
    6. Gillen, David & Gados, Alicja, 2008. "Airlines within airlines: Assessing the vulnerabilities of mixing business models," Research in Transportation Economics, Elsevier, vol. 24(1), pages 25-35.
    7. Rana, Rupal & Oliveira, Fernando S., 2014. "Real-time dynamic pricing in a non-stationary environment using model-free reinforcement learning," Omega, Elsevier, vol. 47(C), pages 116-126.
    8. Anjos, Miguel F. & Cheng, Russell C. H. & Currie, Christine S. M., 2005. "Optimal pricing policies for perishable products," European Journal of Operational Research, Elsevier, vol. 166(1), pages 246-254, October.

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