The impact of forecasting methods on bullwhip effect in supply chain management

Abstract

Recently there has been a surge of interest and research on a phenomenon popularly called the bullwhip effect in supply chain management. The focus of this paper is the impact of demand forecasting on the bullwhip effect. Based on a thorough literature review, we classify existing researches into different categories in terms of modeling methods. Then we show quantification results of the bullwhip effect for simple, two-stage, supply chains consisting of a single retailer and a single manufacturer. Order-up-to inventory policy is assumed. The modeling results of three important forecasting methods (moving average, exponential smoothing, and minimum mean square error) are studied. A comparison is made between these forecasting methods, and some practical guidelines are developed to help managers to select a forecasting method that yields the greatest desired benefit. Finally, possible future research directions in this area are proposed.