In this article we propose a new dynamic pricing approach for the hotel revenue management problem. The proposed approach is based on having ‘price multipliers’ that vary around ‘1’ and provide a varying discount/premium over some seasonal reference price. The price multipliers are a function of certain influencing variables (for example, hotel occupancy, time until arrival). We apply an optimization algorithm for determining the parameters of these multipliers, the goal being to maximize the revenue, taking into account current demand, and the demand-price sensitivity of the hotel's guest. The optimization algorithm makes use of a Monte Carlo simulator that simulates all the hotel's processes, such as reservations arrivals, cancellations, duration of stay, no shows, group reservations, seasonality and trend, as faithfully as possible. We have tested the proposed approach by successfully applying it to the revenue management problem of Plaza Hotel, Alexandria, Egypt, as a case study.
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We acknowledge Professor Hanan Kattara of Alexandria University (and the owner of Plaza Hotel) for her generous help and willingness to supply all Plaza Hotel's data. We also thank Emad Mourad, the manager of Plaza Hotel, for his assistance.
3received his BS from Cairo University, Egypt, and an MS and PhD from Caltech, Pasadena, CA, all in electrical engineering. Dr Atiya is currently a professor in the Department of Computer Engineering, Cairo University. He has recently held several visiting appointments, such as at Caltech and at Chonbuk National University, South Korea. His research interests are in the areas of machine learning, theory of forecasting, computational finance and Monte Carlo methods, and business application of these fields. He has received several awards, such as the Kuwait Prize in 2005. He was an associate editor for IEEE Transactions on Neural Networks from 1998 to 2008, and is currently an associate editor for the International Journal of Forecasting.
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Bayoumi, AM., Saleh, M., Atiya, A. et al. Dynamic pricing for hotel revenue management using price multipliers. J Revenue Pricing Manag 12, 271–285 (2013). https://doi.org/10.1057/rpm.2012.44
- revenue management system
- dynamic pricing
- price elasticity
- Monte Carlo simulation
- hotel room forecasting