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Booking models for hotel revenue management considering multiple-day stays

Author

Listed:
  • S. Liu
  • K.K. Lai
  • S.Y. Wang

Abstract

This study presents several revenue optimisation models for hotel room reservations for a future target day with multiple-day stays. Assume that the hotel has only one type of room but the unit rate for the room may be different during every booking period and every reservation may cover several days. A stochastic programming model with semi-absolute deviations for measuring the risk for hotel revenue under an uncertain environment is proposed. And this stochastic model can be changed into a linear programming model by applying linearisation techniques. Numerical examples are presented to illustrate the efficiency of these models.

Suggested Citation

  • S. Liu & K.K. Lai & S.Y. Wang, 2008. "Booking models for hotel revenue management considering multiple-day stays," International Journal of Revenue Management, Inderscience Enterprises Ltd, vol. 2(1), pages 78-91.
    • Handle: RePEc:ids:ijrevm:v:2:y:2008:i:1:p:78-91
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    Citations

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    Cited by:

    1. Martin Petricek & Stepan Chalupa & David Melas, 2021. "Model of Price Optimization as a Part of Hotel Revenue Management—Stochastic Approach," Mathematics, MDPI, vol. 9(13), pages 1-16, July.
    2. Aydin, N. & Birbil, S.I., 2018. "Decomposition methods for dynamic room allocation in hotel revenue management," European Journal of Operational Research, Elsevier, vol. 271(1), pages 179-192.
    3. Dan Zhang & Larry Weatherford, 2017. "Dynamic Pricing for Network Revenue Management: A New Approach and Application in the Hotel Industry," INFORMS Journal on Computing, INFORMS, vol. 29(1), pages 18-35, February.
    4. Valerio Lacagnina & Davide Provenzano, 2016. "An integrated fuzzy-stochastic model for revenue management," Tourism Economics, , vol. 22(4), pages 779-792, August.

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