Measure of bullwhip effect in supply chains with first-order bivariate vector autoregression time-series demand model
Measure of bullwhip effect in supply chains with first-order bivariate vector autoregression time-series demand model
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DOI：
10.1016/j.cor.2016.08.005
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发表时间：
2017-02
期刊：
影响因子：
--
通讯作者：
K. Sirikasemsuk;H. T. Luong
中科院分区：
文献类型：
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作者：
K. Sirikasemsuk;H. T. Luong
随着供应链的全球化，供应链上游需求波动引起的牛鞭效应问题越来越受到研究者的关注。然而，大多数现有的量化牛鞭效应的研究都是在一阶自回归[AR（1）]输入需求过程或其变体作为基本需求过程的情况下进行的，因此未能考虑零售商需求依赖性。因此，本研究的工作，研究牛鞭效应的一阶二元向量自回归[VAR（1）]需求过程中的一个供应商和两个零售商组成的两阶段供应链。研究了需求过程的相关参数、两个误差项之间的相关系数以及误差项的方差对牛鞭效应的影响。因此，牛鞭效应的措施，建立了一个分析方法，其中最小均方误差（MMSE）预测方法和基本库存政策适用于所有成员的供应链。然后进行了数值实验，以说明牛鞭效应的行为与需求过程的各种参数，看看在哪些情况下，牛鞭效应将缺席。此外，还对库存差异率的评价进行了分析.
With supply chains becoming increasingly global, the issue of bullwhip effect, a phenomenon attributable to demand fluctuation in the upstream section of the supply chains, has received greater attention from many researchers. However, most existing research studies on quantifying the bullwhip effect were conducted under the first-order autoregressive [AR(1)] incoming demand process or its variants as the fundamental demand process, thereby failing to account for the retailer demand dependency. This research work thus examined the bullwhip effect for the first-order bivariate vector autoregression [VAR(1)] demand process in a two-stage supply chain consisting of one supplier and two retailers. The impacts of the correlation parameters of the demand process, the correlation coefficient between the two error terms, and the variances of the error terms on the bullwhip effect were investigated. As such, the measure of the bullwhip effect was established using an analytical approach in which the minimum mean square error (MMSE) forecasting method and the base stock policy were applied to all members of the supply chain. Numerical experiments were then conducted to illustrate the behavior of the bullwhip effect with respect to various parameters of the demand processes to see in which situations the bullwhip effect would be absent. In addition, an evaluation of the inventory variance ratio was analyzed.