Alternative Forecasting Techniques that Reduce the Bullwhip Effect in a Supply Chain: A Simulation Study

  • Francisco Campuzano-Bolarín
  • Antonio Guillamón Frutos
  • Ma Del Carmen Ruiz Abellón
  • Andrej Lisec
Keywords: Bullwhip effect, supply chain, kernel regression, system dynamics model

Abstract

The research of the Bullwhip effect has given rise to many papers, aimed at both analysing its causes and correcting it by means of various management strategies because it has been considered as one of the critical problems in a supply chain. This study is dealing with one of its principal causes, demand forecasting. Using different simulated demand patterns, alternative forecasting methods are proposed, that can reduce the Bullwhip effect in a supply chain in comparison to the traditional forecasting techniques (moving average, simple exponential smoothing, and ARMA processes). Our main findings show that kernel regression is a good alternative in order to improve important features in the supply chain, such as the Bullwhip, NSAmp, and FillRate.

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How to Cite
1.
Campuzano-Bolarín F, Frutos AG, Ruiz Abellón MDC, Lisec A. Alternative Forecasting Techniques that Reduce the Bullwhip Effect in a Supply Chain: A Simulation Study. PROMET [Internet]. 1 [cited 2019Dec.14];25(2):177-88. Available from: http://traffic.fpz.hr/index.php/PROMTT/article/view/1294
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