Paper Title
An Application Of Demand Forecasting In A Global Furniture Retailer Via Combined Forecasts

Abstract
Business must make decisions and formulate plans in order to maintain or improve their positions in the market. Having accurate forecasts for demand helps decision makers in reaching their targets. With this purpose, a large number of forecasting techniques have developed and used widely with success. Also, another significant breakthrough in the field of forecasting is to consider the combining methods to improve forecasting performances. In this study, demand forecasts for an international furniture company have been made through five forecasting techniques and the widely-used combining methods. The results confirmed by the nonparametric tests indicate that none of the single models is superior to the others, and combined forecasts result in statistically significant improvements in forecasting performance as compared with the single models considered.