Forecasting hotel arrivals and occupancy using Monte Carlo simulation

Journal of Revenue and Pricing Management - Tập 10 - Trang 344-366 - 2009
Athanasius Zakhary1, Amir F Atiya2, Hisham El-Shishiny3, Neamat E Gayar1
1Department of Information Technology, Faculty of Computers and Information, Cairo University, Giza, Egypt
2Department of Computer Engineering, Cairo University, Berkeley, Giza, Egypt
3Advanced Technology and Center for Advanced Studies at IBM Technology Development Center, Cairo, Egypt

Tóm tắt

Forecasting hotel arrivals and occupancy is an important component in hotel revenue management systems. In this article, we propose a new Monte Carlo simulation approach for the arrivals and occupancy forecasting problem. In this approach, we simulate the hotel reservations process forward in time, and these future Monte Carlo paths will yield forecast densities. A key step for the faithful emulation of the reservations process is the accurate estimation of its parameters. We propose an approach for the estimation of these parameters from the historical data. Then, the reservations process will be simulated forward with all its constituent processes such as reservation arrivals, cancellations, length of stay, no shows, group reservations, seasonality, trend and so on. We considered as a case study the problem of forecasting room demand for Plaza Hotel, Alexandria, Egypt. The proposed model gives superior results compared to existing approaches.

Tài liệu tham khảo

Andrawis, R. and Atiya, A.F. (2009) A new Bayesian formulation for Holt's exponential smoothing. Journal of Forecasting 28: 218–234.

Andrew, W., Cranage, D. and Lee, C. (1990) Forecasting hotel occupancy rates with time series models: An empirical analysis. Hospitality Research Journal 14: 173–181.

Bailey, N. (1964) The Elements of Stochastic Processes with Applications to the Natural Sciences. New York: Wiley.

Ben-Akiva, M. (1987) Improving airline passenger forecasts using reservations data. In Presentation at Fall ORSA/TIMS Conference, St. Louis, MO.

Ben Ghalia, M. and Wang, P. (August 2000) Intelligent system to support judgmental business forecasting – The case of estimating hotel room demand. IEEE Transaction on Fuzzy Systems 8 (4): 380–397.

Bitran, G. and Caldentey, R. (2003) An overview of pricing models for revenue management. Manufacturing & Service Operations Management 5: 203–229.

Bitran, G. and Gilbert, S. (1998) Forecasting for Airline Network Revenue Management: Revenue and Competitive Impacts. MIT Flight Transportation Lab Report R98-4.

Bitran, G. and Mondschein, S. (1995) An application of yield management to the hotel industry considering multiple day stays. Operations Research 43: 427–443.

Chiang, W.-C., Chen, J.C.H. and Xu, X. (2007) An overview of research on revenue management: Current issues and future research. International Journal of Revenue Management 1 (1): 97–128.

Chow, W.S., Shyu, J.-C. and Wang, K.-C. (1998) Developing a forecast system for hotel occupancy rate using integrated ARIMA models. Journal of International Hospitality, Leisure Tourism Management 1: 55–80.

Franses, P.H. (1998) Time Series Models for Business and Economic Forecasting. Cambridge, UK: Cambridge University Press.

Gardner, E.S. (2006) Exponential smoothing: The state of the art – Part II. International Journal of Forecasting 22: 637–666.

Hyndman, R.J., Koehler, A.B., Ord, J.K. and Snyder, R. (2008) Forecasting with exponential smoothing: The state space approach. Berlin, Germany: Springer Verlag.

Ingold, A., McMahon-Beattie, U. and Yeoman, X.I. (eds.) (2003) Yield Management: Strategies for the Service Industries, 2nd edn. London and New York: Continuum.

Kimes, S.E. (1999) Group forecasting accuracy for hotels. Journal of the Operational Research Society 50: 1104–1110.

Lee, A. (1990) Airline Reservations Forecasting. Erewhon, NC: Prentice-Hall.

L’Heureux, E. (1986) A new twist in forecasting short-term passenger pickup. In: Proceedings of the 26th Annual AGIFORS Symposium.

Liu, P., Smith, S., Orkin, E. and Carey, G. (2002) Estimating unconstrained hotel demand based on censored booking data. Journal of Revenue & Pricing Management 1: 121–138.

Liu, S., Lai, K.K., Dong, J. and Wang, S.-Y. (2006) A stochastic approach to hotel revenue management considering multiple-day stays. International Journal of Information Technology & Decision Making 5: 545–556.

Pfeifer, P. and Bodily, S. (1990) A test of space – Time ARMA modelling and forecasting of hotel data. Journal of Forecasting 9: 255–272.

Queenan, C.C., Ferguson, M., Higbie, J. and Kapoor, R. (2009) Comparison of unconstraining methods to improve revenue management systems. Production and Operations Management 16: 729–746.

Rajopadhye, M., Ben Ghalia, M., Wang, P.P., Baker, T. and Eister, C.V. (2001) Forecasting uncertain hotel room demand. Information Sciences 132: 1–11.

Sa, J. (1987) Reservations forecasting in airline yield management. PhD thesis, MIT, Flight Transformation Lab, Cambridge, MA.

Schwartz, Z. and Hiemstra, S. (1997) Improving the accuracy of hotel reservations forecasting: Curves similarity approach. Journal of Travel Research 36: 3–14.

Shehata, H.S. (2005) Measuring the concepts and practices of revenue management system in Egyptian hotels. Master's thesis, Faculty of Tourism and Hotels, Alexandria University, Egypt.

Sivillo, J., Ahlquist, J. and Toth, Z. (1997) An ensemble forecasting primer. Weather Forecasting 12: 809–817.

Skwarek, D.K. (1996) Competitive Impacts of Yield Management System Components: Forecasting and Sell-up Models. MIT Flight Transportation Lab Report R96-6.

Talluri, K.T. and Van Ryzin, G.J. (2005) The Theory and Practice of Revenue Management. New York, NY: Springer Science and Buisness Media.

Vinod, B. (2004) Unlocking the value of revenue management in the hotel industry. Journal of Revenue and Pricing Management 3 (4): 178–190.

Weatherford, L.R. (1997) A review of optimization modeling assumptions and their impact on revenue. In Presentation at Spring INFORMS Conference, San Diego, CA.

Weatherford, L.R. and Kimes, S.E. (January 2003) A comparison of forecasting methods for hotel revenue management. International Journal of Forecasting 99 (19): 401–415.

Wickham, R.R. (1995) Evaluation of forecasting techniques for short-term demand of air transportation. PhD thesis, MIT, Flight Transformation Lab, Cambridge, MA.

Yuksel, S. (2007) An integrated forecasting approach to hotel demand. Mathematical and Computer Modelling 46: 1063–1070.

Zakhary, A., El Gayar, N. and Atiya, A.F. (2008) A comparative study of the pickup method and its variations using a simulated hotel reservation data. ICGST International Journal on Artificial Intelligence and Machine Learning 8: 15–21.

Zeni, R.H. (2001) Improved forecast accuracy in airline revenue management by unconstraining demand estimates from censored data. PhD dissertation, Graduate School-Newark Rutgers, The State University of New Jersey.

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Journal of Revenue and Pricing Management

Tập 10

344-366

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