ABSTRACT
Demand fluctuation accounts for an important consideration in a restaurant's daily operational decisions. Good short-term planning and management require accurate forecasts of daily demand. The objective of this study is three-fold: to apply, evaluate, and compare different methods of forecasting customer counts for an on-premises buffet restaurant of a local casino in Las Vegas, to describe and propose a combined forecasting approach for this casino buffet restaurant, and to explore the concept of revenue and capacity management for this buffet restaurant. Eight forecasting models were tested and evaluated by two common error measures. The results suggest that a double moving average model was the most accurate model with the smallest mean absolute percentage error (MAPE) and root mean squared percentage error (RMSPE). Extensive discussions on forecasting and management in buffet operations are provided along with recommended future research. Both MAPE and RMSPE are relative measures and widely employed in forecasting studies to facilitate the comparison of accuracy among different methods.
