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A cabin capacity allocation model for revenue management in the cruise industry

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  • Daniel Sturm

    (Hamburg University of Technology)

  • Kathrin Fischer

    (Hamburg University of Technology)

Abstract

The cruise industry is a profitable field for the application of revenue management methods. Existing model formulations for booking limit determination usually assume that the different elements of booking requests are independent. In this work, it is shown that this approach can lead to non-feasible capacity allocations, which consequently are neither optimal nor applicable in practical planning situations. Therefore, a new improved integer linear model formulation is developed here which by explicitly assigning booking requests to cabins derives a feasible and revenue-maximizing capacity allocation. The model and its results are illustrated with a real-world sized case study.

Suggested Citation

  • Daniel Sturm & Kathrin Fischer, 2019. "A cabin capacity allocation model for revenue management in the cruise industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 18(6), pages 441-450, December.
    • Handle: RePEc:pal:jorapm:v:18:y:2019:i:6:d:10.1057_s41272-019-00205-6
    DOI: 10.1057/s41272-019-00205-6
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    References listed on IDEAS

    as
    1. Ladany, Shaul P. & Arbel, Avner, 1991. "Optimal cruise-liner passenger cabin pricing policy," European Journal of Operational Research, Elsevier, vol. 55(2), pages 136-147, November.
    2. Josep Mª Espinet Rius, 2018. "Global and local pricing strategies in the cruise industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 17(5), pages 329-340, October.
    3. Jeffrey I. McGill & Garrett J. van Ryzin, 1999. "Revenue Management: Research Overview and Prospects," Transportation Science, INFORMS, vol. 33(2), pages 233-256, May.
    4. Richard Metters & Carrie Queenan & Mark Ferguson & Laura Harrison & Jon Higbie & Stan Ward & Bruce Barfield & Tammy Farley & H. Ahmet Kuyumcu & Amar Duggasani, 2008. "The “Killer Application” of Revenue Management: Harrah's Cherokee Casino & Hotel," Interfaces, INFORMS, vol. 38(3), pages 161-175, June.
    5. Maddah, Bacel & Moussawi-Haidar, Lama & El-Taha, Muhammad & Rida, Hussein, 2010. "Dynamic cruise ship revenue management," European Journal of Operational Research, Elsevier, vol. 207(1), pages 445-455, November.
    6. Wen-Chyuan Chiang & Jason C.H. Chen & Xiaojing Xu, 2007. "An overview of research on revenue management: current issues and future research," International Journal of Revenue Management, Inderscience Enterprises Ltd, vol. 1(1), pages 97-128.
    7. Donghui Ma & Jin Sun, 2012. "Revenue Management System for the Cruise Industry: A Simulation Study," Springer Books, in: Alexis Papathanassis & Michael H. Breitner & Cornelia Schoen & Nadine Guhr (ed.), Cruise Management, chapter 11, pages 223-232, Springer.
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    Cited by:

    1. Mahmoud Dehghan Nayeri & Amir-Nader Haghbin & Abdolkarim Mohammadi-Balani & Karim Bayat, 2020. "A multi-objective mean–variance mathematical programming approach to combined phase-out and clearance pricing strategy for seasonal products: case study of a Jeans retailer," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(3), pages 210-217, June.

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