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

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 autoregressive moving average (ARMA) processes). The authors' 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.

• Record URL:
  https://doi.org/10.7307/ptt.v25i2.1294
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/03535320
• Supplemental Notes:
  • Copyright © 2013 Campuzano-Bolarín, F. et al.
• Authors:
  • Campuzano-Bolarin, Francisco
  • Guillamon Frutos, Antonio
  • Ruiz Abellon, Ma Del Carmen
  • Lisec, Andrej
• Publication Date: 2013

Language

• English

Media Info

• Media Type: Print
• Features: Figures; References; Tables;
• Pagination: pp 177-188
• Serial:
  • PROMET-Traffic & Transportation
  • Volume: 25
  • Issue Number: 2
  • Publisher: University of Zagreb
  • ISSN: 0353-5320
  • EISSN: 1848-4069
  • Serial URL: https://traffic2.fpz.hr/index.php/PROMTT
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Regression analysis; Simulation; Supply chain management; Traffic forecasting
• Identifier Terms: System Dynamics Simulation Modeling
• Uncontrolled Terms: Bullwhip effect (Supply chains)
• Subject Areas: Freight Transportation; Planning and Forecasting; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01482797
• Record Type: Publication
• Files: TRIS
• Created Date: Jun 3 2013 9:20AM