IDEAS home Printed from https://ideas.repec.org/a/pal/jorapm/v20y2021i6d10.1057_s41272-021-00346-7.html
   My bibliography  Save this article

Traveler centric airline offer design and optimization

Author

Listed:
  • Mourad Boudia

    (Amadeus)

  • Suraj Mohamed

    (Amadeus Commercial Office, Singapore)

  • Nicolas Bondoux

    (Amadeus)

  • Thierry Delahaye

    (Amadeus Asia Limited, Bangkok)

Abstract

In the airline industry’s very competitive landscape, being traveler-centric and offering an adapted set of products and services for different customer segments is crucial for airlines to resist and keep growing. By correctly designing and pricing product offers, airlines will reinforce their travelers’ loyalty and open upsell opportunities and strengthen their competitive position and revenue. This paper presents a new approach to design and optimizing airline offers, aiming to better consider travelers’ needs and preferences and improve airline revenue. The proposed method is based on market research and conjoint analysis techniques, combined with a revenue simulation framework. To better understand travelers, airline historical bookings data are used to cluster them in different segments based on their trip characteristics and booking behavior. In addition to the segmentation, a large sample of several thousands of travelers is surveyed using an adapted questionnaire per segment. The survey required participants to select one option among an assortment of a few products with different features. The data collected are used to build a choice model and evaluate the price elasticity. Travelers’ segments, estimated utilities, and choice modeling combined with the price elasticity and product preference shares are used to design the new product offer. A revenue simulation framework is developed to evaluate the revenue impact of introducing these new products in a competitive landscape. It simulates the flight booking life cycle from the flight’s opening for booking until the day of departure. Several scenarios of demand and willingness to pay are evaluated. Our approach is tested on a mid-size, full-service carrier. It allowed a better understanding of the travelers’ segments and behavior and resulted in a revenue improvement ranging from 1.6 to 4%, depending on the cabin and simulation scenario. Following the obtained results, the study recommendations’ are being implemented in production with an airline partner.

Suggested Citation

  • Mourad Boudia & Suraj Mohamed & Nicolas Bondoux & Thierry Delahaye, 2021. "Traveler centric airline offer design and optimization," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(6), pages 634-645, December.
  • Handle: RePEc:pal:jorapm:v:20:y:2021:i:6:d:10.1057_s41272-021-00346-7
    DOI: 10.1057/s41272-021-00346-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41272-021-00346-7
    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/s41272-021-00346-7?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. Jerry Wind & Paul E. Green & Douglas Shifflet & Marsha Scarbrough, 1989. "Courtyard by Marriott : Designing a Hotel Facility with Consumer-Based Marketing Models," Interfaces, INFORMS, vol. 19(1), pages 25-47, February.
    2. 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.
    3. Kalyan Talluri & Garrett van Ryzin, 2004. "Revenue Management Under a General Discrete Choice Model of Consumer Behavior," Management Science, INFORMS, vol. 50(1), pages 15-33, January.
    4. Vithala R. Rao, 2014. "Applied Conjoint Analysis," Springer Books, Springer, edition 127, number 978-3-540-87753-0, October.
    5. Thierry Delahaye & Rodrigo Acuna-Agost & Nicolas Bondoux & Anh-Quan Nguyen & Mourad Boudia, 2017. "Data-driven models for itinerary preferences of air travelers and application for dynamic pricing optimization," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 16(6), pages 621-639, December.
    6. Lhéritier, Alix & Bocamazo, Michael & Delahaye, Thierry & Acuna-Agost, Rodrigo, 2019. "Airline itinerary choice modeling using machine learning," Journal of choice modelling, Elsevier, vol. 31(C), pages 198-209.
    7. Robert Thorndike, 1953. "Who belongs in the family?," Psychometrika, Springer;The Psychometric Society, vol. 18(4), pages 267-276, December.
    8. 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.
    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. 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. Hu, Qiying & Wei, Yihua & Xia, Yusen, 2010. "Revenue management for a supply chain with two streams of customers," European Journal of Operational Research, Elsevier, vol. 200(2), pages 582-598, January.
    3. Lingxiu Dong & Panos Kouvelis & Zhongjun Tian, 2009. "Dynamic Pricing and Inventory Control of Substitute Products," Manufacturing & Service Operations Management, INFORMS, vol. 11(2), pages 317-339, December.
    4. Christian Borgs & Ozan Candogan & Jennifer Chayes & Ilan Lobel & Hamid Nazerzadeh, 2014. "Optimal Multiperiod Pricing with Service Guarantees," Management Science, INFORMS, vol. 60(7), pages 1792-1811, July.
    5. Dongdong Yu & Miyu Wan & Chunlin Luo, 2022. "Dynamic pricing and dual‐channel choice in the presence of strategic consumers," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(6), pages 2392-2408, September.
    6. Wang, Xiubin & Regan, Amelia, 2006. "Dynamic yield management when aircraft assignments are subject to swap," Transportation Research Part B: Methodological, Elsevier, vol. 40(7), pages 563-576, August.
    7. Paat Rusmevichientong & Mika Sumida & Huseyin Topaloglu, 2020. "Dynamic Assortment Optimization for Reusable Products with Random Usage Durations," Management Science, INFORMS, vol. 66(7), pages 2820-2844, July.
    8. Huseyin Topaloglu & S. Ilker Birbil & J. B. G. Frenk & Nilay Noyan, 2012. "Tractable Open Loop Policies for Joint Overbooking and Capacity Control Over a Single Flight Leg with Multiple Fare Classes," Transportation Science, INFORMS, vol. 46(4), pages 460-481, November.
    9. Constantinos Maglaras & Joern Meissner, 2006. "Dynamic Pricing Strategies for Multiproduct Revenue Management Problems," Manufacturing & Service Operations Management, INFORMS, vol. 8(2), pages 136-148, July.
    10. Asdemir, Kursad & Jacob, Varghese S. & Krishnan, Ramayya, 2009. "Dynamic pricing of multiple home delivery options," European Journal of Operational Research, Elsevier, vol. 196(1), pages 246-257, July.
    11. Qian Liu & Garrett van Ryzin, 2008. "On the Choice-Based Linear Programming Model for Network Revenue Management," Manufacturing & Service Operations Management, INFORMS, vol. 10(2), pages 288-310, October.
    12. Ma, Wenliang & Wang, Qiang & Yang, Hangjun & Zhang, Guoquan & Zhang, Yahua, 2020. "Understanding airline price dispersion in the presence of high-speed rail," Transport Policy, Elsevier, vol. 95(C), pages 93-102.
    13. Jacob Feldman & Nan Liu & Huseyin Topaloglu & Serhan Ziya, 2014. "Appointment Scheduling Under Patient Preference and No-Show Behavior," Operations Research, INFORMS, vol. 62(4), pages 794-811, August.
    14. Ferreira, Kevin D. & Wu, Desheng Dash, 2011. "An integrated product planning model for pricing and bundle selection using Markov decision processes and data envelope analysis," International Journal of Production Economics, Elsevier, vol. 134(1), pages 95-107, November.
    15. Syed Asif Raza & Rafi Ashrafi & Ali Akgunduz, 2020. "A bibliometric analysis of revenue management in airline industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(6), pages 436-465, December.
    16. Selçuk Korkmaz & O. Erhun Kundakcioglu & Orhan Sivrikaya, 2022. "A fluid approximation for the single-leg fare allocation problem with nonhomogeneous poisson demand," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(1), pages 81-96, February.
    17. Pornpawee Bumpensanti & He Wang, 2020. "A Re-Solving Heuristic with Uniformly Bounded Loss for Network Revenue Management," Management Science, INFORMS, vol. 66(7), pages 2993-3009, July.
    18. Aldric Vives & Marta Jacob & Eugeni Aguiló, 2019. "Online hotel demand model and own-price elasticities: An empirical application in a mature resort destination," Tourism Economics, , vol. 25(5), pages 670-694, August.
    19. Miju Ahn & Xiaodong Luo & Sergey Shebalov, 2020. "Variable pricing: an integrated airline pricing and revenue management model," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(6), pages 421-435, December.
    20. 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.

    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:20:y:2021:i:6:d:10.1057_s41272-021-00346-7. 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.