Impact of Initial Level and Growth Rate in Multiplicative HW Model on Bullwhip Effect in a Supply Chain

Abstract

Bullwhip effect (BWE) in a supply chain, attributed as the amplification of variance of demand along its route of propagation, compels a manufacturer to bear additional costs in the form of non-optimal resource usage. An accurate forecasting approach for demand prediction can be instrumental in mitigating the BWE. Numerous researchers have attempted to assess the impact of several forecasting approaches such as Moving Average, Single, Double and Triple Exponential Smoothing models, ARIMA, AI-based methods on BWE. However, Multiplicative Holt-Winters approach in mitigating the BWE is not widely exploited particularly with respect to the influence of the initial values of the level and growth rate of this approach. Hence, in this research endeavour, an attempt is made to study the impact of these parameters of the Multiplicative Holt-Winters model on the bullwhip effect in a two-echelon supply chain. Accordingly a simulation is performed in MS Excel along with ANOVA to reveal the significance of the parametric values. The preliminary results demonstrate that the initial values of the level have a significant impact over the bullwhip effect whereas the initial values of the growth rate maintain a U-type relationship. Thus, a scope is revealed for further study to improve the widely adopted Multiplicative Holt-Winters forecasting approach for tackling the BWE through exploration of optimal conditions.