A comparison of bullwhip effect in a single-stage supply chain for autocorrelated demands when using Correct, MA, and EWMA methods

Jui Lin Wang, Ju Hsiu Kuo, Shih yu Chou, Sheng Zhi Wang

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)

Abstract

In this paper, the three Correct, MA, and EWMA Methods for series demand function model (ARiMA(1, 0, 0), ARiMA(0, 0, 1), ARiMA(1, 0, 1)) have been described, formulated, and presented to examine the influence of forecast-updating methods between order quantity and actual demand in the amplifications of bullwhip effect. By using these forecast-updating methods comparison, the optimal solution of the bullwhip effect control Policies with a time-series technique under a basic one supply chain stage perspective can be obtained. Through the comparison of the more flexible bullwhip effect control Policies, a more efficient demand function model strategy of the parameter setting, using and the integrated application method in the supply chain management procedure was decided to use. In addition, a simulated procedure and systems analysis regarding these series demand uncertainty modeling parameters will be conducted to investigate the fluctuation effects on the amplifications of bullwhip effect. The proposed method permits controlling the retailer orders' variability above the other factors in the bullwhip effect.

Original languageEnglish
Pages (from-to)4726-4736
Number of pages11
JournalExpert Systems with Applications
Volume37
Issue number7
DOIs
Publication statusPublished - 2010 Jul

Keywords

  • Supply chain management
  • Systems analysis
  • Time series
  • Uncertainty modeling

ASJC Scopus subject areas

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence

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