Simulation analysis for the bullwhip effect in supply chain model

Authors:
Kun-Lin Hsieh;Yan-Kwang Chen
Affiliations:
Department of Information Management, National Taitung University, Taitung, Taiwan, R.O.C.;Department of Logistics Engineering & Management, National Taichung Institute of Technology, Taichung, Taiwan, R.O.C.
Venue:
SMO'06 Proceedings of the 6th WSEAS International Conference on Simulation, Modelling and Optimization
Year:
2006

Citing 3
Cited 0

Information distortion in a supply chain: the bullwhip effect

Management Science - Special issue on frontier research in manufacturing and logistics
Quantifying the Bullwhip Effect in a Simple Supply Chain: The Impact of Forecasting, Lead Times, and Information

Management Science
Comments on "Information Distortion in a Supply Chain: The Bullwhip Effect"

Management Science

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Abstract

This paper introduces the confidence interval estimate for measuring the bullwhip effect, which has been observed across most industries. Calculating a confidence interval usually needs the assumption about the underlying distribution. Bootstrapping is a non-parametric, but computer intensive, estimation method. In this paper, a simulation study on the behavior of the 95% bootstrap confidence interval for estimating bullwhip effect is made. Effects of sample size, autocorrelation coefficient of customer demand, lead time, and bootstrap methods on the 95% bootstrap confidence interval of bullwhip effect are presented and discussed.