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Revenue management under customer choice behaviour with cancellations and overbooking

Author

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  • Sierag, D.D.
  • Koole, G.M.
  • van der Mei, R.D.
  • van der Rest, J.I.
  • Zwart, B.
Abstract
In many application areas such as airlines and hotels a large number of bookings are typically cancelled. Explicitly taking into account cancellations creates an opportunity for increasing revenue. Motivated by this we propose a revenue management model based on Talluri and van Ryzin (2004) that takes cancellations into account in addition to customer choice behaviour. Moreover, we consider overbooking limits as these are influenced by cancellations. We model the problem as a Markov decision process and propose three dynamic programming formulations to solve the problem, each appropriate in a different setting. We show that in certain settings the problem can be solved exactly using a tractable solution method. For other settings we propose tractable heuristics, since the problem faces the curse of dimensionality. Numerical results show that the heuristics perform almost as good as the exact solution. However, the model without cancellations can lead to a revenue loss of up to 20 percent. Lastly we provide a parameter estimation method based on Newman et al. (2014). This estimation method is fast and provides good parameter estimates. The combination of the model, the tractable and well-performing solution methods, and the parameter estimation method ensures that the model can efficiently be applied in practice.

Suggested Citation

  • Sierag, D.D. & Koole, G.M. & van der Mei, R.D. & van der Rest, J.I. & Zwart, B., 2015. "Revenue management under customer choice behaviour with cancellations and overbooking," European Journal of Operational Research, Elsevier, vol. 246(1), pages 170-185.
    • Handle: RePEc:eee:ejores:v:246:y:2015:i:1:p:170-185
    DOI: 10.1016/j.ejor.2015.04.014
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    References listed on IDEAS

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    Cited by:

    1. Daniel Hopman & Ger Koole & Rob van der Mei, 2017. "Single-leg revenue management with downsell and delayed decision making," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 16(6), pages 594-606, December.
    2. Shuyu Zhou & Yeming (Yale) Gong & René de Koster, 2016. "Designing self-storage warehouses with customer choice," International Journal of Production Research, Taylor & Francis Journals, vol. 54(10), pages 3080-3104, May.
    3. Fatemeh Binesh & Amanda Belarmino & Carola Raab, 2021. "A meta-analysis of hotel revenue management," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(5), pages 546-558, October.
    4. Seung Hyun Lee & Cynthia S. Deale & Jaeyong Lee, 2022. "Does it pay to book direct?: Customers’ perceptions of online channel distributors, price, and loyalty membership on brand dimensions," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(6), pages 657-667, December.
    5. Naragain Phumchusri & Phatsakorn Sangsukiam & Nannapat Chariyasethapong, 2020. "Optimal overbooking model for car rental business with two levels of prices having stochastic joint booking and show-up levels," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(3), pages 190-209, June.
    6. Chua, Geoffrey A. & Lim, Wei Shi & Yeo, Wee Meng, 2016. "Market structure and the value of overselling under stochastic demands," European Journal of Operational Research, Elsevier, vol. 252(3), pages 900-909.
    7. Simović, Olivera & Rađenović, Žarko & Perović, Djurdjica & Vujačić, Vesna, 2020. "Tourism in the Digital Age: E-booking Perspective," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2020), Virtual Conference, in: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Virtual Conference, 10-12 September 2020, pages 616-627, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb.
    8. Aldric Vives & Marta Jacob & Marga Payeras, 2018. "Revenue management and price optimization techniques in the hotel sector," Tourism Economics, , vol. 24(6), pages 720-752, September.
    9. Ming Yin & Zheng Wan & Kap Hwan Kim & Shi Yuan Zheng, 2019. "An optimal variable pricing model for container line revenue management systems," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 21(2), pages 173-191, June.
    10. Robert Hjorth & Thomas Fiig & Jesper Larsen & Nicolas Bondoux, 2018. "Joint overbooking and seat allocation for fare families," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 17(6), pages 436-452, December.
    11. Saito, Taiga & Takahashi, Akihiko & Koide, Noriaki & Ichifuji, Yu, 2019. "Application of online booking data to hotel revenue management," International Journal of Information Management, Elsevier, vol. 46(C), pages 37-53.
    12. 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.
    13. Dirk Sierag & Rob Mei, 2016. "Single-leg choice-based revenue management: a robust optimisation approach," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 15(6), pages 454-467, December.

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