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Determine the cost of denying boarding to passengers: An optimization-based approach

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  • Chen, Lijian

Abstract

We present an optimization-based method to evaluate the financial impact of denying boarding to the lowest-fare customers under airline network overbooking. Airlines are demanding quantitative support to evaluate the impact on revenue when facing the decision to deny boarding to customers. Although overbooking is a well-regulated operation for decades, it has drawn considerable criticism due to, at least partially, disagreement regarding compensation. Usually, airlines deny boarding to the lowest-fare customers to assure seat availability for customers in higher-paying booking classes. We model such an assurance by chance-constrained optimization, and we gain managerial implications for overbooking practices, for low-cost airlines in particular. We conclude that low-cost airlines are vulnerable regarding revenue growth under network overbooking in comparison to other airlines. We explore possible revenue-improving suggestions, which will ease the effects of network booking for airlines both analytically and numerically.

Suggested Citation

  • Chen, Lijian, 2020. "Determine the cost of denying boarding to passengers: An optimization-based approach," International Journal of Production Economics, Elsevier, vol. 220(C).
    • Handle: RePEc:eee:proeco:v:220:y:2020:i:c:s0925527319302452
    DOI: 10.1016/j.ijpe.2019.07.008
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    References listed on IDEAS

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    1. Lijian Chen & Tito Homem-de-Mello, 2010. "Re-solving stochastic programming models for airline revenue management," Annals of Operations Research, Springer, vol. 177(1), pages 91-114, June.
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    Cited by:

    1. Liang, Jinpeng & Li, Liming & Zheng, Jianfeng & Tan, Zhijia, 2023. "Service-oriented container slot allocation policy under stochastic demand," Transportation Research Part B: Methodological, Elsevier, vol. 176(C).

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