Open AccessForecasting Restaurant Sales Using Multiple Regression And Box-Jenkins Analysis
Author(s) -
Frank G. Forst
Publication year - 2011
Publication title -
journal of applied business research
Language(s) - English
Resource type - Journals
eISSN - 2157-8834
pISSN - 0892-7626
DOI - 10.19030/jabr.v8i2.6157
Subject(s) - sales forecasting , box–jenkins , regression analysis , econometrics , sales management , regression , retail sales , linear regression , statistics , marketing , business , economics , mathematics , time series , autoregressive integrated moving average
Several regression and Box-Jenkins models were used to forecast weekly sales at a small campus restaurant for Years 1 and 2. Forecasted sales were compared with actual sales to select the three most promising forecasting models. These three models were then used to forecast sales for the first 44 weeks of Year 3, and compared against actual sales. The results indicate that a multiple regression model with two predictors, a dummy variable and sales lagged one week, was the best forecasting model considered.