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

Document Type : Research Article (Original Article)


1 PhD in Production and Operation Management, Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran, Iran.

2 MSc in Industrial Engineering, Faculty of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran.

3 Associate Professor, Faculty of Management and Accounting, Allameh Tabataba'i University, Tehran, Iran.


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.