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Personalization in airline revenue management – Heuristics for real-time adjustment of availability and fares

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  • Michael D. Wittman

    (International Center for Air Transportation)

  • Peter P. Belobaba

    (International Center for Air Transportation)

Abstract

Through improvements in information technology and distribution, airlines are increasingly gaining access to detailed information about potential passengers at the time of booking. Airlines could use this passenger information to provide availability or a fare quote that is tailored specifically toward the passenger that is making the request. For instance, IATA’s New Distribution Capability (NDC) will allow airlines to offer passengers a personalized fare offer that could include a customized price. By strategically targeting personalized offers toward the right customers, airlines could gain new bookings from price-sensitive passengers while encouraging more price-inelastic travelers to buy-up to higher price points. This paper, the second in a series on dynamic availability in airline revenue management, proposes two heuristics that could be used to provide targeted availability or fare offers to specific customers or segments of customers after making a simple estimate of the passenger’s willingness-to-pay (WTP). Tests in the Passenger Origin–Destination Simulator (PODS) show that the heuristics are generally revenue-positive for airlines and are stable in a competitive revenue management environment. Of particular interest is “dynamic discounting,” which increases both yields and load factors by offering targeted discounts to leisure passengers in specific situations. The results improve on past work on dynamic availability and introduce new possibilities for personalization in airline revenue management.

Suggested Citation

  • Michael D. Wittman & Peter P. Belobaba, 2017. "Personalization in airline revenue management – Heuristics for real-time adjustment of availability and fares," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 16(4), pages 376-396, August.
    • Handle: RePEc:pal:jorapm:v:16:y:2017:i:4:d:10.1057_s41272-016-0002-z
    DOI: 10.1057/s41272-016-0002-z
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    Cited by:

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    2. Fukushi, Mitsuyoshi & Delgado, Felipe & Raveau, Sebastián & Santos, Bruno F., 2022. "CHAIRS: A choice-based air transport simulator applied to airline competition and revenue management," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 297-315.
    3. Ren, Xinhui & Pan, Na & Jiang, Hong, 2022. "Differentiated pricing for airline ancillary services considering passenger choice behavior heterogeneity and willingness to pay," Transport Policy, Elsevier, vol. 126(C), pages 292-305.
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    5. Christine S. M. Currie & Trivikram Dokka & John Harvey & Arne K. Strauss, 2018. "Future research directions in demand management," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 17(6), pages 459-462, December.
    6. Zhao, Guihong & Cui, Yue & Cheng, Shaoyu, 2021. "Dynamic pricing of ancillary services based on passenger choice behavior," Journal of Air Transport Management, Elsevier, vol. 94(C).
    7. 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.
    8. Klein, Robert & Koch, Sebastian & Steinhardt, Claudius & Strauss, Arne K., 2020. "A review of revenue management: Recent generalizations and advances in industry applications," European Journal of Operational Research, Elsevier, vol. 284(2), pages 397-412.
    9. 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.
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