The Effect of Applying Combined Forecasting Methods on Bullwhip Effect in a Multilevel Supply Chain

Abstract

Nowadays, supply chain management comprises the dominant paradigm of business areas around the world and facing major challenges of this concept, is the most essential and basic topics of interest of researchers. One of the major challenges in supply chain management is bullwhip effect and the factors affecting it. An important factor that many researchers have mentioned is forecasting methods used in supply chains. In this paper, a three-level supply chain is considered in which each of the levels uses one of the forecasting methods; Moving Average, Exponential Smoothing, and Linear Regression. The results of the simulation and the comparison performed by ANOVA - respect to the assumptions - shows that the best combinations of forecasting methods are moving average - Linear regression - Exponential Smoothing and Linear regression - Exponential Smoothing - Moving average, and other combinations have less utility.

Keywords

• supply chain
• bullwhip effect؛ forecasting method
• simulation
• anova