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Suggesting Forecasting Methods for Dietitians at University Foodservice Operations  

Ryu Ki-Sang (Lester E. Kabowff School of Hotel, Restaurant, and Tourism Administration, University of New Orleans)
Publication Information
Nutritional Sciences / v.9, no.3, 2006 , pp. 201-211 More about this Journal
Abstract
The purpose of this study was to provide dietitians with the guidance in forecasting meal counts for a university/college foodservice facility. The forecasting methods to be analyzed were the following: naive model 1, 2, and 3; moving average, double moving average, simple exponential smoothing, double exponential smoothing, Holt's, and Winters' methods, and simple linear regression. The accuracy of the forecasting methods was measured using mean squared error and Theil's U-statistic. This study showed how to project meal counts using 10 forecasting methods for dietitians. The results of this study showed that WES was the most accurate forecasting method, followed by $na\ddot{i}ve$ 2 and naive 3 models. However, naive model 2 and 3 were recommended for using by dietitians in university/college dining facilities because of the accuracy and ease of use. In addition, the 2000 spring semester data were better than the 2000 fall semester data to forecast 2001spring semester data.
Keywords
Forecasting; Meal counts; University foodservice; Forecasting methods; Accuracy; Ease of use;
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