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Estimating Air-Cargo Overbooking Based on a Discrete Show-Up-Rate Distribution

Author

Listed:
  • Andreea Popescu

    (School of Industrial and Systems Engineering, Georgia Institute of Technology, 765 Ferst Drive, Atlanta, Georgia 30332)

  • Pinar Keskinocak

    (School of Industrial and Systems Engineering, Georgia Institute of Technology, 765 Ferst Drive, Atlanta, Georgia 30332)

  • Ellis Johnson

    (School of Industrial and Systems Engineering, Georgia Institute of Technology, 765 Ferst Drive, Atlanta, Georgia 30332)

  • Mariana LaDue

    (Sabre Airline Solutions, 1 East Kirkwood Boulevard, Southlake, Texas 76092)

  • Raja Kasilingam

    (Sabre Airline Solutions, 1 East Kirkwood Boulevard, Southlake, Texas 76092)

Abstract

Most airlines overbook their actual capacity (for both passengers and cargo) because part of the booked demand often does not show up at the flight departure. A key element of overbooking is a model that accurately predicts the show-up rate of the current bookings. Given the increasing importance of cargo within their business, most major airlines now scrutinize estimates of show-up rates for cargo bookings. The current practice is to apply the same methodology to the cargo sector as in the passenger business. We investigate the suitability of the current practice, and based on the results, we propose an alternate show-up-rate estimator for cargo and demonstrate its benefits. Tested on real-world data from a major airline as well as on simulated data, the study shows that improved estimation of the show-up rate can improve profits and customer service.

Suggested Citation

  • Andreea Popescu & Pinar Keskinocak & Ellis Johnson & Mariana LaDue & Raja Kasilingam, 2006. "Estimating Air-Cargo Overbooking Based on a Discrete Show-Up-Rate Distribution," Interfaces, INFORMS, vol. 36(3), pages 248-258, June.
    • Handle: RePEc:inm:orinte:v:36:y:2006:i:3:p:248-258
    DOI: 10.1287/inte.1060.0211
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    References listed on IDEAS

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    1. Lawrence R. Weatherford & Samuel E. Bodily, 1992. "A Taxonomy and Research Overview of Perishable-Asset Revenue Management: Yield Management, Overbooking, and Pricing," Operations Research, INFORMS, vol. 40(5), pages 831-844, October.
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    Cited by:

    1. Shaban, Ibrahim Abdelfadeel & Chan, F.T.S. & Chung, S.H., 2021. "A novel model to manage air cargo disruptions caused by global catastrophes such as Covid-19," Journal of Air Transport Management, Elsevier, vol. 95(C).
    2. Tatsiana Levina & Yuri Levin & Jeff McGill & Mikhail Nediak, 2011. "Network Cargo Capacity Management," Operations Research, INFORMS, vol. 59(4), pages 1008-1023, August.
    3. Luo, Sirong & Çakany?ld?r?m, Metin & Kasilingam, Raja G., 2009. "Two-dimensional cargo overbooking models," European Journal of Operational Research, Elsevier, vol. 197(3), pages 862-883, September.
    4. Feng, Bo & Li, Yanzhi & Shen, Huaxiao, 2015. "Tying mechanism for airlines’ air cargo capacity allocation," European Journal of Operational Research, Elsevier, vol. 244(1), pages 322-330.
    5. Michael F. Gorman & John-Paul Clarke & Amir Hossein Gharehgozli & Michael Hewitt & René de Koster & Debjit Roy, 2014. "State of the Practice: A Review of the Application of OR/MS in Freight Transportation," Interfaces, INFORMS, vol. 44(6), pages 535-554, December.
    6. Amaruchkul, Kannapha & Sae-Lim, Patipan, 2011. "Airline overbooking models with misspecification," Journal of Air Transport Management, Elsevier, vol. 17(2), pages 143-147.
    7. Dalalah, Doraid & Ojiako, Udechukwu & Chipulu, Maxwell, 2020. "Voluntary overbooking in commercial airline reservations," Journal of Air Transport Management, Elsevier, vol. 86(C).
    8. Guo, Xiaolong & Dong, Yufeng & Ling, Liuyi, 2016. "Customer perspective on overbooking: The failure of customers to enjoy their reserved services, accidental or intended?," Journal of Air Transport Management, Elsevier, vol. 53(C), pages 65-72.
    9. Masato Wada & Felipe Delgado & Bernardo K. Pagnoncelli, 2017. "A risk averse approach to the capacity allocation problem in the airline cargo industry," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(6), pages 643-651, June.
    10. Bo Feng & Jixin Zhao & Zheyu Jiang, 2022. "Robust pricing for airlines with partial information," Annals of Operations Research, Springer, vol. 310(1), pages 49-87, March.
    11. Andreea Popescu & Earl Barnes & Ellis Johnson & Pinar Keskinocak, 2013. "Bid Prices When Demand Is a Mix of Individual and Batch Bookings," Transportation Science, INFORMS, vol. 47(2), pages 198-213, May.
    12. Zou, Li & Yu, Chunyan & Dresner, Martin, 2013. "The application of inventory transshipment modeling to air cargo revenue management," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 57(C), pages 27-44.
    13. 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.
    14. Ku, Cheng-Yuan & Chang, Yi-Wen, 2012. "Optimal production and selling policies with fixed-price contracts and contingent-price offers," International Journal of Production Economics, Elsevier, vol. 137(1), pages 94-101.
    15. Bo Feng & Zheyu Jiang & Fujun Lai, 2020. "Robust approach for air cargo freight forwarder selection under disruption," Annals of Operations Research, Springer, vol. 291(1), pages 339-360, August.

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