IDEAS home Printed from https://ideas.repec.org/a/pal/jorapm/v16y2017i2d10.1057_rpm.2016.26.html
   My bibliography  Save this article

Dynamic availability of fare products with knowledge of customer characteristics

Author

Listed:
  • Michael D Wittman

    (Massachusetts Institute of Technology, International Center for Air Transportation)

  • Peter P Belobaba

    (Massachusetts Institute of Technology, International Center for Air Transportation)

Abstract

Recent advancements in airline distribution technology, including IATA’s New Distribution Capability (NDC), could offer airlines a wealth of information about the characteristics of individual customers arriving to book. Recent literature has envisioned a world where airlines, enabled by this new distribution technology, are able to make personalized fare quotes in real time, effectively heralding the end of traditional booking classes. However, academic literature suggests that this type of price discrimination may intensify competition and lead to lower revenues for firms. In this article – the first in a series of papers exploring models of dynamic product availability with knowledge of customer characteristics – we test a simple dynamic availability (DynA) heuristic that adjusts fare class availability after inheriting information about a customer’s trip purpose. Through results from the Passenger Origin-Destination Simulator, we find that this DynA heuristic is often revenue-negative for airlines and unstable in competitive environments. The results raise questions about airline benefits from simple approaches to personalized pricing enabled by NDC, and open up opportunities for future research regarding more nuanced and advanced strategies for customized pricing and availability in the airline industry.

Suggested Citation

  • Michael D Wittman & Peter P Belobaba, 2017. "Dynamic availability of fare products with knowledge of customer characteristics," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 16(2), pages 201-217, April.
    • Handle: RePEc:pal:jorapm:v:16:y:2017:i:2:d:10.1057_rpm.2016.26
    DOI: 10.1057/rpm.2016.26
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/rpm.2016.26
    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/rpm.2016.26?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. Greg Shaffer & Z. John Zhang, 2002. "Competitive One-to-One Promotions," Management Science, INFORMS, vol. 48(9), pages 1143-1160, September.
    2. Kalyan Talluri & Garrett van Ryzin, 1998. "An Analysis of Bid-Price Controls for Network Revenue Management," Management Science, INFORMS, vol. 44(11-Part-1), pages 1577-1593, November.
    3. Alessandro Acquisti & Hal R. Varian, 2005. "Conditioning Prices on Purchase History," Marketing Science, INFORMS, vol. 24(3), pages 367-381, May.
    4. Seelhorst, Michael & Liu, Yi, 2015. "Latent air travel preferences: Understanding the role of frequent flyer programs on itinerary choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 80(C), pages 49-61.
    5. Alamdari, Fariba & Mason, Keith, 2006. "The future of airline distribution," Journal of Air Transport Management, Elsevier, vol. 12(3), pages 122-134.
    6. Yuri Levin & Jeff McGill & Mikhail Nediak, 2009. "Dynamic Pricing in the Presence of Strategic Consumers and Oligopolistic Competition," Management Science, INFORMS, vol. 55(1), pages 32-46, January.
    7. Toshihiro Matsumura & Noriaki Matsushima, 2015. "Should Firms Employ Personalized Pricing?," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 24(4), pages 887-903, October.
    8. Yuxin Chen & Chakravarthi Narasimhan & Z. John Zhang, 2001. "Individual Marketing with Imperfect Targetability," Marketing Science, INFORMS, vol. 20(1), pages 23-41, November.
    9. Peter P. Belobaba, 1989. "OR Practice—Application of a Probabilistic Decision Model to Airline Seat Inventory Control," Operations Research, INFORMS, vol. 37(2), pages 183-197, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. Strauss, Arne K. & Klein, Robert & Steinhardt, Claudius, 2018. "A review of choice-based revenue management: Theory and methods," European Journal of Operational Research, Elsevier, vol. 271(2), pages 375-387.

    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. 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.
    2. Esteves, Rosa-Branca & Carballo-Cruz, Francisco, 2023. "Can data openness unlock competition when an incumbent has exclusive data access for personalized pricing?," Information Economics and Policy, Elsevier, vol. 64(C).
    3. Fay, Scott & Mitra, Deb & Wang, Qiong, 2009. "Ask or infer? Strategic implications of alternative learning approaches in customization," International Journal of Research in Marketing, Elsevier, vol. 26(2), pages 136-152.
    4. Chen, Yuxin & Zhang, Z. John, 2009. "Dynamic targeted pricing with strategic consumers," International Journal of Industrial Organization, Elsevier, vol. 27(1), pages 43-50, January.
    5. Ham, Sung H. & He, Chuan & Zhang, Dan, 2022. "The promise and peril of dynamic targeted pricing," International Journal of Research in Marketing, Elsevier, vol. 39(4), pages 1150-1165.
    6. Zhijun Chen & Chongwoo Choe & Noriaki Matsushima, 2020. "Competitive Personalized Pricing," Management Science, INFORMS, vol. 66(9), pages 4003-4023, September.
    7. Vincent Conitzer & Curtis R. Taylor & Liad Wagman, 2012. "Hide and Seek: Costly Consumer Privacy in a Market with Repeat Purchases," Marketing Science, INFORMS, vol. 31(2), pages 277-292, March.
    8. Chongwoo Choe & Stephen King & Noriaki Matsushima, 2018. "Pricing with Cookies: Behavior-Based Price Discrimination and Spatial Competition," Management Science, INFORMS, vol. 64(12), pages 5669-5687, December.
    9. John Aloysius & Cary Deck & Amy Farmer, 2013. "Sequential Pricing of Multiple Products: Leveraging Revealed Preferences of Retail Customers Online and with Auto-ID Technologies," Information Systems Research, INFORMS, vol. 24(2), pages 372-393, June.
    10. Dror Hermel & Benny Mantin & Yossi Aviv, 2022. "Can coupons counteract strategic consumer behavior?," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(3), pages 262-273, June.
    11. Flavio Pino, 2022. "The microeconomics of data – a survey," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 49(3), pages 635-665, September.
    12. Esteves, Rosa-Branca, 2022. "Can personalized pricing be a winning strategy in oligopolistic markets with heterogeneous demand customers? Yes, it can," International Journal of Industrial Organization, Elsevier, vol. 85(C).
    13. Stefano Colombo & Clara Graziano & Aldo Pignataro, 2023. "Personalized Pricing with Imperfect Customer Recognition," CESifo Working Paper Series 10455, CESifo.
    14. Chen, Bintong & Chen, Jing, 2017. "Compete in Price or Service?—A Study of Personalized Pricing and Money Back Guarantees," Journal of Retailing, Elsevier, vol. 93(2), pages 154-171.
    15. Qiuyu Lu & Noriaki Matsushima, 2023. "Personalized pricing when consumers can purchase multiple items," ISER Discussion Paper 1192, Institute of Social and Economic Research, Osaka University.
    16. Chatwin, Richard E., 2000. "Optimal dynamic pricing of perishable products with stochastic demand and a finite set of prices," European Journal of Operational Research, Elsevier, vol. 125(1), pages 149-174, August.
    17. Grigoriev, A. & Hiller, B. & Marban, S. & Vredeveld, T. & van der Zwaan, G.R.J., 2010. "Dynamic pricing problems with elastic demand," Research Memorandum 053, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    18. Bita Hajihashemi & Amin Sayedi & Jeffrey D. Shulman, 2022. "The Perils of Personalized Pricing with Network Effects," Marketing Science, INFORMS, vol. 41(3), pages 477-500, May.
    19. Jentzsch, Nicola & Sapi, Geza & Suleymanova, Irina, 2013. "Targeted pricing and customer data sharing among rivals," International Journal of Industrial Organization, Elsevier, vol. 31(2), pages 131-144.
    20. Aniruddha Dutta, 2019. "Capacity Allocation of Game Tickets Using Dynamic Pricing," Data, MDPI, vol. 4(4), pages 1-12, October.

    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:16:y:2017:i:2:d:10.1057_rpm.2016.26. 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.