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This study developed a simple statistical model for forecasting a company’s sparkling beverage sales in the 14 provinces of Southern Thailand. Data comprised sales revenue from January 2000 to December 2006 obtained from the company. We fitted an observation-driven multiple regression model to log-transformed monthly revenue containing season of year (month), location and beverage flavour as factors, as well as lagged observations for the preceding four months. The model gave a r-squared of 0.95 and was effective for forecasting revenues for up to 12 future months. Using such models for forecasting sales revenue can assist company managers with planning more effectively.

Statistical Model For Short-Term Forecasting Sparkling Beverage Sales In Southern Thailand