IDEAS home Printed from https://ideas.repec.org/a/pal/jorapm/v21y2022i2d10.1057_s41272-021-00323-0.html
   My bibliography  Save this article

Clustering as an approach for creating data-driven perspectives on air travel itineraries

Author

Listed:
  • Sebastian Vock

    (Opremic trade GmbH)

  • Laurie A. Garrow

    (Georgia Institute of Technology)

  • Catherine Cleophas

    (Christian-Albrechts-Universität Kiel)

Abstract

This paper proposes to create data-driven perspectives on airline ticketing data by defining groups of air travel itineraries independently of geographical or temporal attributes. We demonstrate the approach by analysing an extensive empirical data set featuring ticketing data from several carriers as collected by the Airlines Reporting Corporation. The analysis compares five cluster quality indicators to evaluate effects of pre-processing and clustering decisions. Benchmarking the results against a more traditional geographical grouping demonstrates the potential for data-driven analysis. Finally, we highlight ways in which the resulting cluster perspectives could support demand forecasting, performance evaluation, and analyst interventions.

Suggested Citation

  • Sebastian Vock & Laurie A. Garrow & Catherine Cleophas, 2022. "Clustering as an approach for creating data-driven perspectives on air travel itineraries," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(2), pages 212-227, April.
    • Handle: RePEc:pal:jorapm:v:21:y:2022:i:2:d:10.1057_s41272-021-00323-0
    DOI: 10.1057/s41272-021-00323-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41272-021-00323-0
    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/s41272-021-00323-0?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. Coldren, Gregory M. & Koppelman, Frank S. & Kasturirangan, Krishnan & Mukherjee, Amit, 2003. "Modeling aggregate air-travel itinerary shares: logit model development at a major US airline," Journal of Air Transport Management, Elsevier, vol. 9(6), pages 361-369.
    2. Herring, Jordan & Lurkin, Dr Virginie & Garrow, Dr Laurie A. & John-Paul Clarke, Dr & Bierlaire, Dr Michel, 2019. "Airline customers’ connection time preferences in domestic U.S. markets," Journal of Air Transport Management, Elsevier, vol. 79(C), pages 1-1.
    3. Lurkin, Virginie & Garrow, Laurie A. & Higgins, Matthew J. & Newman, Jeffrey P. & Schyns, Michael, 2017. "Accounting for price endogeneity in airline itinerary choice models: An application to Continental U.S. markets," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 228-246.
    4. Sumit Kunnumkal & Kalyan Talluri, 2019. "Choice Network Revenue Management Based on New Tractable Approximations," Transportation Science, INFORMS, vol. 53(6), pages 1591-1608, November.
    5. Dong Liang & Richard Ratliff & Norbert Remenyi, 2017. "Robust revenue opportunity modeling with quadratic programming," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 16(6), pages 569-579, December.
    6. Vivek F. Farias & Srikanth Jagabathula & Devavrat Shah, 2013. "A Nonparametric Approach to Modeling Choice with Limited Data," Management Science, INFORMS, vol. 59(2), pages 305-322, December.
    7. Garrett van Ryzin & Gustavo Vulcano, 2015. "A Market Discovery Algorithm to Estimate a General Class of Nonparametric Choice Models," Management Science, INFORMS, vol. 61(2), pages 281-300, February.
    8. Claudia Schütze & Catherine Cleophas & Monideepa Tarafdar, 2020. "Revenue management systems as symbiotic analytics systems: insights from a field study," Business Research, Springer;German Academic Association for Business Research, vol. 13(3), pages 1007-1031, November.
    9. Meisel, Stephan & Mattfeld, Dirk, 2010. "Synergies of Operations Research and Data Mining," European Journal of Operational Research, Elsevier, vol. 206(1), pages 1-10, October.
    10. Boone, Tonya & Ganeshan, Ram & Jain, Aditya & Sanders, Nada R., 2019. "Forecasting sales in the supply chain: Consumer analytics in the big data era," International Journal of Forecasting, Elsevier, vol. 35(1), pages 170-180.
    11. Romero Morales, Dolores & Wang, Jingbo, 2010. "Forecasting cancellation rates for services booking revenue management using data mining," European Journal of Operational Research, Elsevier, vol. 202(2), pages 554-562, April.
    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. Morlotti, Chiara & Birolini, Sebastian & Malighetti, Paolo & Redondi, Renato, 2023. "A latent class approach to estimate air travelers’ propensity toward connecting itineraries," Research in Transportation Economics, Elsevier, vol. 99(C).
    2. Redondi, Renato & Birolini, Sebastian & Morlotti, Chiara & Paleari, Stefano, 2021. "Connectivity measures and passengers’ behavior: Comparing conventional connectivity models to predict itinerary market shares," Journal of Air Transport Management, Elsevier, vol. 90(C).
    3. Barbier, Thibault & Anjos, Miguel F. & Cirinei, Fabien & Savard, Gilles, 2020. "Product-closing approximation for ranking-based choice network revenue management," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1002-1017.
    4. Sanjay Dominik Jena & Andrea Lodi & Claudio Sole, 2021. "On the estimation of discrete choice models to capture irrational customer behaviors," Papers 2109.03882, arXiv.org.
    5. Dimitris Bertsimas & Velibor V. Mišić, 2019. "Exact First-Choice Product Line Optimization," Operations Research, INFORMS, vol. 67(3), pages 651-670, May.
    6. Keji Wei & Vikrant Vaze, 2020. "Airline Timetable Development and Fleet Assignment Incorporating Passenger Choice," Transportation Science, INFORMS, vol. 54(1), pages 139-163, January.
    7. Lurkin, Virginie & Garrow, Laurie A. & Higgins, Matthew J. & Newman, Jeffrey P. & Schyns, Michael, 2018. "Modeling competition among airline itineraries," Transportation Research Part A: Policy and Practice, Elsevier, vol. 113(C), pages 157-172.
    8. Xiyuan Ren & Joseph Y. J. Chow & Prateek Bansal, 2023. "Estimating a k-modal nonparametric mixed logit model with market-level data," Papers 2309.13159, arXiv.org, revised Aug 2024.
    9. Gunay, Gurkan & Gokasar, Ilgin, 2021. "Market segmentation analysis for airport access mode choice modeling with mixed logit," Journal of Air Transport Management, Elsevier, vol. 91(C).
    10. Ruxian Wang & Ozge Sahin, 2018. "The Impact of Consumer Search Cost on Assortment Planning and Pricing," Management Science, INFORMS, vol. 64(8), pages 3649-3666, August.
    11. Philipp Bartke & Natalia Kliewer & Catherine Cleophas, 2018. "Benchmarking filter-based demand estimates for airline revenue management," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 7(1), pages 57-88, March.
    12. Qi Feng & J. George Shanthikumar & Mengying Xue, 2022. "Consumer Choice Models and Estimation: A Review and Extension," Production and Operations Management, Production and Operations Management Society, vol. 31(2), pages 847-867, February.
    13. 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.
    14. Birolini, Sebastian & Cattaneo, Mattia & Malighetti, Paolo & Morlotti, Chiara, 2020. "Integrated origin-based demand modeling for air transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    15. Catherine Cleophas & Daniel Kadatz & Sebastian Vock, 2017. "Resilient revenue management: a literature survey of recent theoretical advances," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 16(5), pages 483-498, October.
    16. Lesgourgues, Augustin & Malavolti, Estelle, 2023. "Social cost of airline delays: Assessment by the use of revenue management data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 170(C).
    17. Johannes F. Jörg & Catherine Cleophas, 2022. "Nonparametric estimation of customer segments from censored sales panel data," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(4), pages 393-417, August.
    18. Sanjay Dominik Jena & Andrea Lodi & Claudio Sole, 2022. "On the Estimation of Discrete Choice Models to Capture Irrational Customer Behaviors," INFORMS Journal on Computing, INFORMS, vol. 34(3), pages 1606-1625, May.
    19. Qi Feng & J. George Shanthikumar, 2022. "Developing operations management data analytics," Production and Operations Management, Production and Operations Management Society, vol. 31(12), pages 4544-4557, December.
    20. 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.

    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:21:y:2022:i:2:d:10.1057_s41272-021-00323-0. 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.