Forecasting hotel occupancy rates in Egypt using time series models

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Summary

Forecasting occupancy rates is important for effective hotel management. This study examines empirically the use of five time series models (moving average, Brown's, Holt's, Winter's and ARIMA) in forecasting hotel occupancy rates in Egypt. These models were fitted and tested using actual monthly occupancy rates for two types of hotels (city center and resort). For the city center hotel, ARIMA model forecasted more accurately than the other investigated models. Results were different for the resort hotel where Brown's model outperformed all other models in prediction. Results of this study showed generally that simple time series models (Brown's, Holt's & moving average) performed as well as or better than sophisticated models (Winter's & ARIMA) in forecasting hotel occupancy rates in Egypt. Since simple time series models are easy to develop and economical in terms of time and skill levels of users, results of this study have important implications for the use of time series forecasting techniques in the hotel industry.