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Model of Price Optimization as a Part of Hotel Revenue Management—Stochastic Approach

Author

Listed:
  • Martin Petricek

    (Department of Economy and Economics, Institute of Hospitality Management in Prague, 181 00 Prague, Czech Republic)

  • Stepan Chalupa

    (Department of Economy and Economics, Institute of Hospitality Management in Prague, 181 00 Prague, Czech Republic)

  • David Melas

    (Department of Economy and Economics, Institute of Hospitality Management in Prague, 181 00 Prague, Czech Republic)

Abstract

The paper is focusing on the problem of price optimization in the area of accommodation services. The main aim is to propose a novel simulation-based methodology of price optimization based on the customer’s price acceptance. The authors create a model based on the known approaches but extended by the stochastic approach and optimization based on the coefficient of price elasticity. The whole model is created, the price is set and optimized in two steps. The first step makes segmentation and optimization (with the price elasticity approach). The second step then sets the price of the reservation—the final price for a customer. This reservation price is mainly determined by knowledge of the length of stay, occupancy and booking lead time. All those parameters are described in the text from the economic point of view and make the base for the whole and complex revenue management model.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:13:p:1552-:d:587021
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    References listed on IDEAS

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    1. Timothy Webb & Misuk Lee & Zvi Schwartz & Ira Vouk, 2024. "Beyond accuracy: The advantages of the k-nearest neighbor algorithm for hotel revenue management forecasting," Tourism Economics, , vol. 30(5), pages 1216-1236, August.

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