Minimizing the Bullwhip Effect by Forecasting Supply Chain Demand: Case Study of the Argentine Automotive Sector

EasyChair Preprint 4787

Abstract

This article studies the uncertainty caused by the Bullwhip effect in the supply chain. The supply chain evaluated in this study is made up of a manufacturer, a distributor, and a retailer, and we studied the effect of demand between the links in the supply chain. The research uses data from the demand for Argentine automotive parts for 48 months and compares the forecast using the Holt-Winters and ARIMA methods over 4 years to minimize the Bullwhip effect.

Keyphrases: ARIMA models, Holt-Winters method, automotive industry, bullwhip effect, supply chain, time series

@booklet{EasyChair:4787,
  author    = {Claudio Aballay and Luis Quezada and Miguel Alfaro and Guillermo Fuertes and Marc Dahmen and Manuel Vargas},
  title     = {Minimizing the Bullwhip Effect by Forecasting Supply Chain Demand: Case Study of the Argentine Automotive Sector},
  howpublished = {EasyChair Preprint 4787},
  year      = {EasyChair, 2020}}