In today’s world, all enterprises in a supply chain are attempting to increase both their and the supply chain’s efficiency and effectiveness. Therefore, identification and consideration of factors that prevent enterprises to attain their expected/desired levels of effectiveness are very important. Since bullwhip effect is one of these main factors, being aware of its reasons help enterprises decrease the severity of bullwhip effect by opting proper decisions. Now that forecasting method is one of the most important factors in increasing or decreasing the bullwhip effect, this chapter considers and compares the effects of various forecasting methods on the bullwhip effect. In fact, in this chapter, the effects of various forecasting methods, such as Moving Average, Exponential Smoothing, and Regression, in terms of their associated bullwhip effect, in a four echelon supply chain- including retailer, wholesaler, manufacturer, and supplier- are considered. Then, the bullwhip effect measure is utilized to compare the ineffectiveness of various forecasting methods. Owing to this, the authors generate two sets of demands in the two cases where the demand is constant (no trend) and has an increasing trend, respectively. Then, the chapter ranks the forecasting methods in these two cases and utilizes a statistical method to ascertain the significance of differences among the effects of various methods.
Analysis of the bullwhip effect with multi-echelon, multi-product supply chains