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Social cost of airline delays: Assessment by the use of revenue management data

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  • Lesgourgues, Augustin
  • Malavolti, Estelle

Abstract

We develop a schedule delay model using advanced econometrics techniques, while computing the social cost of passenger delays, in order to propose an alternative to the method of defining such cost that is actually found in the literature. This study has been made possible by obtaining private revenue management and operational data directly from a main European legacy airline. Thanks to MNL models, we compute the arrival time preferences, for all groups of passengers, namely arriving or departing, and short or long stay passengers, and for every day of departure that we have collected in our dataset. Then, we compute the effect of the ex-post modification of the arrival time, created by a delay, on the passenger’s utility. We finally compute two effects on the social welfare cost of delays regarding ex-post schedule displacement: the price effect, which is the sensitivity of passengers regarding schedule displacement, and the volume effect measured by the level of airline delays in terms of time. Then, we compare those two effects across the day, in order to consider the social cost of airline delays as a two-effect phenomenon, instead of being only defined by the aggregated airline delay, in terms of time. Our results show that delays are costlier for passengers making the departing portion of their journey, with a short stay upon arrival, and during certain periods of the day. The originality of our paper principally lies in two aspects: first, studies about the precise computation of the social cost of airline delays regarding ex-post schedule displacement do not exist in the literature. Our paper fills this gap by providing an original method aiming at defining this cost. Second, our study is, to the best of our knowledge, the first to consider the effect of airline delays on the passenger’s utility, at the time of day level, by jointly analyzing revenue management and operational data.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:transa:v:170:y:2023:i:c:s0965856423000332
    DOI: 10.1016/j.tra.2023.103613
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    References listed on IDEAS

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    1. Joachim Grammig & Reinhard Hujer & Michael Scheidler, 2005. "Discrete choice modelling in airline network management," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(4), pages 467-486, May.
    2. 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.
    3. Forbes, Silke J., 2008. "The effect of air traffic delays on airline prices," International Journal of Industrial Organization, Elsevier, vol. 26(5), pages 1218-1232, September.
    4. Brey, Raúl & Walker, Joan L., 2011. "Latent temporal preferences: An application to airline travel," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(9), pages 880-895, November.
    5. Michael Scheidler & Reinhard Hujer & Joachim Grammig, 2005. "Discrete choice modelling in airline network management," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(4), pages 467-486.
    6. Tseng, Yin-Yen & Verhoef, Erik T., 2008. "Value of time by time of day: A stated-preference study," Transportation Research Part B: Methodological, Elsevier, vol. 42(7-8), pages 607-618, August.
    7. Hess, Stephane & Adler, Thomas & Polak, John W., 2007. "Modelling airport and airline choice behaviour with the use of stated preference survey data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(3), pages 221-233, May.
    8. Koppelman, Frank S. & Coldren, Gregory M. & Parker, Roger A., 2008. "Schedule delay impacts on air-travel itinerary demand," Transportation Research Part B: Methodological, Elsevier, vol. 42(3), pages 263-273, March.
    9. Dobruszkes, Frédéric & Lennert, Moritz & Van Hamme, Gilles, 2011. "An analysis of the determinants of air traffic volume for European metropolitan areas," Journal of Transport Geography, Elsevier, vol. 19(4), pages 755-762.
    10. Merkert, Rico & Beck, Matthew, 2017. "Value of travel time savings and willingness to pay for regional aviation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 96(C), pages 29-42.
    11. James D. Dana Jr., 1999. "Using Yield Management to Shift Demand When the Peak Time is Unknown," RAND Journal of Economics, The RAND Corporation, vol. 30(3), pages 456-474, Autumn.
    12. 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.
    13. Proussaloglou, Kimon & Koppelman, Frank S., 1999. "The choice of air carrier, flight, and fare class," Journal of Air Transport Management, Elsevier, vol. 5(4), pages 193-201.
    14. Shan Lan & John-Paul Clarke & Cynthia Barnhart, 2006. "Planning for Robust Airline Operations: Optimizing Aircraft Routings and Flight Departure Times to Minimize Passenger Disruptions," Transportation Science, INFORMS, vol. 40(1), pages 15-28, February.
    15. Yimga, Jules, 2020. "Price and marginal cost effects of on-time performance: Evidence from the US airline industry," Journal of Air Transport Management, Elsevier, vol. 84(C).
    16. Frédéric Dobruszkes & Moritz Lennert & Gilles Van Hamme, 2011. "An analysis of the determinants of air traffic volume for European metropolitan areas," ULB Institutional Repository 2013/95858, ULB -- Universite Libre de Bruxelles.
    17. Hess, Stephane & Bierlaire, Michel & Polak, John W., 2005. "Estimation of value of travel-time savings using mixed logit models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(2-3), pages 221-236.
    18. 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.
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