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Customized dynamic pricing of airline fare products

Author

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  • Michael D. Wittman

    (Massachusetts Institute of Technology)

  • Peter P. Belobaba

    (Massachusetts Institute of Technology)

Abstract

Firms practice dynamic pricing when they charge different customers different prices for the same products, as a function of an observable state of nature. In the airline industry, dynamic pricing has historically been limited by the capabilities of distribution systems, which require filing a finite set of fare products with fixed prices. However, advancements in airline distribution technology will soon allow the generation of “customized offers,” which could include a dynamically generated price. In this paper, we propose a heuristic for customized dynamic pricing of airfares when the observable state of nature includes an observation of passenger characteristics. We first introduce a general model for decoupling the customized offer generation problem from the well-studied airline revenue management problem. After generating a baseline assortment of fare products and observing the characteristics of a passenger’s request, an airline can choose to customize that passenger’s offer by dynamically incrementing or discounting the prices that would ordinarily be offered. The methodology could be applied with existing airline revenue management methods, and would be compatible with IATA’s New Distribution Capability (NDC). For implementation, we propose a straightforward heuristic approach based on simple estimates of passenger willingness-to-pay distributions. The heuristics are simulated in the Passenger Origin–Destination Simulator, a complex airline revenue management simulation environment that takes into account passenger choice and competition. The results show that the heuristics can lead to revenue gains of up to 3–4% when practiced by one airline. Furthermore, the heuristics remain revenue positive in competitive environments.

Suggested Citation

  • Michael D. Wittman & Peter P. Belobaba, 2018. "Customized dynamic pricing of airline fare products," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 17(2), pages 78-90, April.
  • Handle: RePEc:pal:jorapm:v:17:y:2018:i:2:d:10.1057_s41272-017-0119-8
    DOI: 10.1057/s41272-017-0119-8
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    References listed on IDEAS

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    2. Michael D. Wittman & Peter P. Belobaba, 2019. "Dynamic pricing mechanisms for the airline industry: a definitional framework," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 18(2), pages 100-106, April.
    3. Stacey Mumbower & Susan Hotle & Laurie A. Garrow, 2023. "Highly debated but still unbundled: The evolution of U.S. airline ancillary products and pricing strategies," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 22(4), pages 276-293, August.
    4. Kevin K. Wang & Michael D. Wittman & Adam Bockelie, 2021. "Dynamic offer generation in airline revenue management," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(6), pages 654-668, December.
    5. Daniel Schubert & Christa Sys & Rosário Macário, 2022. "Customized airline offer management: a conceptual architecture," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(5), pages 553-563, October.
    6. Merkert, Rico & Bushell, James & Beck, Matthew J., 2020. "Collaboration as a service (CaaS) to fully integrate public transportation – Lessons from long distance travel to reimagine mobility as a service," Transportation Research Part A: Policy and Practice, Elsevier, vol. 131(C), pages 267-282.
    7. Muzaffer Buyruk & Ertan Güner, 2022. "Personalization in airline revenue management: an overview and future outlook," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(2), pages 129-139, April.
    8. Bertalan Juhasz, 2021. "Optimal prices for multiple products in classless revenue management," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(5), pages 588-595, October.
    9. Kevin K. Wang & Michael D. Wittman & Thomas Fiig, 2023. "Dynamic offer creation for airline ancillaries using a Markov chain choice model," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 22(2), pages 103-121, April.
    10. Peng Du & Lei Xu & Rou Luo & Mingzhu Hou, 2024. "Competing with Low Cost Carrier in a Sustainable Environment: Airline Ticket Pricing, Carbon Trading, and Market Power Structure," Sustainability, MDPI, vol. 16(2), pages 1-17, January.
    11. Yanbin Long & Peter Belobaba, 2024. "Airline revenue management with segmented continuous pricing: methods and competitive effects," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 23(1), pages 14-27, February.

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