IDEAS home Printed from https://ideas.repec.org/a/pal/jorapm/v22y2023i2d10.1057_s41272-022-00399-2.html
   My bibliography  Save this article

A heuristic for incorporating ancillaries into air choice models with personalization (Part 1: estimating preferences using hedonic regression)

Author

Listed:
  • Michal Sznajder

    (Sabre Research)

  • Richard Ratliff

    (Sabre Research)

  • Cuneyd Kaya

    (Sabre Research)

Abstract

In recent years, airlines have begun selling “branded fares” which are bundles of a travel “right-to-fly” plus assorted amenities (e.g., first bag included, extra legroom, priority boarding, extra loyalty miles, etc.). Branded fares allow airlines to further differentiate their products and have proven popular with customers. However, the explanatory features considered in previous air choice models in use at Sabre were limited to price and itinerary schedule attributes only; they did not consider the value-added utility of the new amenities included in airline branded fares. This paper is the first of a two-part series about incorporating ancillaries into air choice models. In Part 1, the authors describe a hedonic regression (HR) heuristic to measure the additional customer value-added utility from bundling ancillary amenities into airline branded fares. We found the estimated market pricing from HR models to be useful in determining travelers’ valuation and preferences across different categories of popular air ancillaries. Furthermore, we will show how to extend this approach to include personalization by customer segment.

Suggested Citation

  • Michal Sznajder & Richard Ratliff & Cuneyd Kaya, 2023. "A heuristic for incorporating ancillaries into air choice models with personalization (Part 1: estimating preferences using hedonic regression)," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 22(2), pages 122-139, April.
  • Handle: RePEc:pal:jorapm:v:22:y:2023:i:2:d:10.1057_s41272-022-00399-2
    DOI: 10.1057/s41272-022-00399-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41272-022-00399-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1057/s41272-022-00399-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Octavian Oancea, 2021. "The implications of behavioural economics for pricing in a world of offer optimisation," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(6), pages 626-633, December.
    2. Diana, Tony, 2010. "`Discrete Choice Modelling and Air Travel Demand: Theory and Applications` by Laurie A. Garrow," Journal of Airport Management, Henry Stewart Publications, vol. 5(1), pages 88-89, September.
    3. Rodrigo Acuna-Agost & Eoin Thomas & Alix Lhéritier, 2021. "Price elasticity estimation for deep learning-based choice models: an application to air itinerary choices," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(3), pages 213-226, June.
    4. Ben Vinod & Richard Ratliff & Vikram Jayaram, 2018. "An approach to offer management: maximizing sales with fare products and ancillaries," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 17(2), pages 91-101, April.
    5. Warnock-Smith, David & O'Connell, John F. & Maleki, Mahnaz, 2017. "An analysis of ongoing trends in airline ancillary revenues," Journal of Air Transport Management, Elsevier, vol. 64(PA), pages 42-54.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Michal Sznajder & Richard Ratliff & Cuneyd Kaya, 2023. "A heuristic for incorporating ancillaries into air choice models with personalization (part 2: integrated multinomial logit and hedonic regression models)," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 22(2), pages 140-151, April.
    2. 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.
    3. O'Connell, John F. & Avellana, Raquel Martinez & Warnock-Smith, David & Efthymiou, Marina, 2020. "Evaluating drivers of profitability for airlines in Latin America: A case study of Copa Airlines," Journal of Air Transport Management, Elsevier, vol. 84(C).
    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. Maung, Yun Shwe Yee & Douglas, Ian & Tan, David, 2022. "Identifying the drivers of profitable airline growth," Transport Policy, Elsevier, vol. 115(C), pages 275-285.
    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. MadhuSudan Rao Kummara & Bhaskara Rao Guntreddy & Ines Garcia Vega & Yun Hsuan Tai, 2021. "Dynamic pricing of ancillaries using machine learning: one step closer to full offer optimization," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(6), pages 646-653, December.
    8. Ku, Edward C.S., 2022. "Developing business process agility: Evidence from inter-organizational information systems of airlines and travel agencies," Journal of Air Transport Management, Elsevier, vol. 103(C).
    9. John V. Colias & Stella Park & Elizabeth Horn, 2021. "Optimizing B2B product offers with machine learning, mixed logit, and nonlinear programming," Journal of Marketing Analytics, Palgrave Macmillan, vol. 9(3), pages 157-172, September.
    10. Jeon, Mi-Sun & Lee, Jang-Ho, 2020. "Estimation of willingness-to-pay for premium economy class by type of service," Journal of Air Transport Management, Elsevier, vol. 84(C).
    11. Morlotti, Chiara & Mantin, Benny & Malighetti, Paolo & Redondi, Renato, 2024. "Price volatility of revenue managed goods: Implications for demand and price elasticity," European Journal of Operational Research, Elsevier, vol. 312(3), pages 1039-1058.
    12. Paula Margaretic & Christine Thomas-Agnan & Romain Doucet, 2017. "Spatial dependence in (origin-destination) air passenger flows," Papers in Regional Science, Wiley Blackwell, vol. 96(2), pages 357-380, June.
    13. Resul Aydemir & Mehmet Melih Değirmenci & Abdullah Bilgin, 2023. "Estimation of passenger sell-up rates in airline revenue management by considering the effect of fare class availability," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 22(6), pages 501-513, December.
    14. Özlem Atalık & Mahmut Bakır & Şahap Akan, 2019. "The Role of In-Flight Service Quality on Value for Money in Business Class: A Logit Model on the Airline Industry," Administrative Sciences, MDPI, vol. 9(1), pages 1-15, March.
    15. 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.
    16. 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.
    17. Onur Bas & Tamer Aksoy, 2022. "Examining the impact of cargo and ancillary revenues on net profit for full service carrier airlines," International Journal of Business Ecosystem & Strategy (2687-2293), Bussecon International Academy, vol. 4(3), pages 48-72, July.
    18. Li, Suyang & Pawlak, Jacek & Sivakumar, Aruna, 2024. "Implications of air travel shopping for non-aeronautical revenue streams: A cross-national empirical analysis," Journal of Air Transport Management, Elsevier, vol. 119(C).
    19. Song, Woon-Kyung & Lee, Hyun Cheol, 2020. "An analysis of traveler need for and willingness to purchase airline dynamic packaging: A Korean case study," Journal of Air Transport Management, Elsevier, vol. 82(C).
    20. Michael Byrd & Ross Darrow, 2021. "A note on the advantage of context in Thompson sampling," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(3), pages 316-321, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:jorapm:v:22:y:2023:i:2:d:10.1057_s41272-022-00399-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.