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An Econometric Investigation of the Bullwhip Effect---The Influence of Demand and Supply in the Automobile Industry.

机译：牛鞭效应的计量经济学研究-汽车行业供求关系的影响。

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摘要

The issues relating to the bullwhip effect have been studied rigorously in past, even before the advent of supply chain management concepts. The bullwhip phenomenon refers to the increasing amplification of demand variation as one moves upstream in the supply chain. A variety of causes and resulting unfavorable performance effects in supply chains have been investigated, using wide-ranging methodologies. Many beneficial solutions have also been provided to counter bullwhip effects and improve overall supply chain performance. However, despite considerable research efforts in the past, the number of empirical studies conducted to date is rather limited. This study, consisting of three essays, is aimed at contributing to this body of literature. It is based on secondary data obtained from the U.S. automotive industry to test and investigate bullwhip effect-related issues.;The automobile industry is considered due to availability of data, its important role in the economy, and dynamic business environment. The first essay is aimed at investigating individually: (1) the existence of bullwhip effect, (2) the impact of inaccurate demand process specification on bullwhip effect, (3) the effects of the demand forecasting policies on bullwhip effect, and, (4) demand-supply equilibrium at the product level, in selected U.S. automobile industry supply chain. It is concluded that, first, the bullwhip effects were present in the automobile supply chain. Second, it is found that mis-specified demand series may cause poorer forecast accuracies and stronger bullwhip effects. Third, the choice of forecasting policy is found to have an impact on forecast accuracy, and the use of relatively more complex forecasting techniques such as Holt-Winters and time series method (compared to moving average and simple exponential smoothing methods) leads to less pronounced bullwhip effects. Finally, pair-wise correlations among demand, production and inventory were significant, but the equilibrium status was not found to be present. This essay contributes to the field in the following ways. First, the results, confirming the existence of bullwhip effect in specific manufacturing supply chain, differs from the conclusions of studies such as Cachon et al. (2007) which was an aggregate industry-level study. Second, in contrast of the conclusions of studies such as Hosoda and Disney (2009), it was found that demand process misspecification has impacts on the bullwhip effect and the accuracy of demand forecasting.;The second essay is aimed at investigating the relative forecasting accuracies of univariate and multivariate time series approaches to further examine whether multivariate time series methods are more effective than the simpler, univariate methods. In addition, this essay is aimed at evaluating causal relationships among demand, supply and inventory variables. This essay contributes to the supply chain literature in the following aspects. First, multivariate time series model is introduced into the supply chain management field for the first time to investigate the forecast accuracy and test the relationship among the considered variables. The choice of univariate and multivariate forecasting methods was a major research target in the forecasting field. Second, although a few prior studies used the multivariate approach to describe the demand process, this study is the first to present the numerical results of the model specification and conduct forecasting based on the model. Third, this study is the first to investigate the causal relationships among demand, supply, and inventory using multivariate time series method. Finally, this study provides another effective and theoretically-robust tool to test the existence of equilibrium conditions in the supply chain.;The major objective of the third essay is to describe the transition of different types of volatility in the supply chain. This essay contributes to the literature in the several aspects. First, a multivariate generalized autoregressive heteroscedasticity model is used for the first time to empirically establish the existence of the volatility transition in the supply chain. Second, this study is also the first to consider the influence of a balanced demand-supply system where the demand, supply, and inventory are all stationary processes. The major contribution for this finding is that it is necessary to explicitly consider the effect of volatility when developing policies for supply chain inventory management in the presence of bullwhip effects. (Abstract shortened by UMI.)
机译：甚至在供应链管理概念出现之前，就已经对牛鞭效应相关的问题进行了严格的研究。牛鞭现象是指随着供应链上游的需求变化，需求变化越来越大。使用广泛的方法，已经研究了供应链中各种原因以及由此产生的不利绩效影响。还提供了许多有益的解决方案来应对牛鞭效应并改善整个供应链绩效。然而，尽管过去进行了大量研究工作，但迄今为止进行的实证研究的数量相当有限。这项由三篇论文组成的研究旨在为这一文学体系做出贡献。它基于从美国汽车工业获得的辅助数据来测试和调查与牛鞭效应相关的问题。;由于数据的可用性，其在经济中的重要作用以及动态的商业环境，因此对汽车工业进行了研究。第一篇文章旨在针对个人进行调查：（1）牛鞭效应的存在；（2）不正确的需求过程规范对牛鞭效应的影响；（3）需求预测政策对牛鞭效应的影响；以及（4） ）在选定的美国汽车产业供应链中，产品层面的供求平衡。结论是，首先，牛鞭效应存在于汽车供应链中。其次，发现错误指定的需求序列可能会导致较差的预测准确性和更强的牛鞭效应。第三，发现预测策略的选择会影响预测准确性，并且使用相对更复杂的预测技术（如Holt-Winters和时间序列方法（与移动平均数和简单的指数平滑方法相比））会导致不太明显牛鞭效应。最后，需求，生产和库存之间的成对相关性很显着，但是没有发现平衡状态。本文通过以下方式为该领域做出了贡献。首先，该结果证实了牛鞭效应在特定制造业供应链中的存在，这与诸如Cachon等人的研究结论不同。 （2007年）是一项行业整体研究。其次，与Hosoda和Disney（2009）等研究结论相反，发现需求过程的错误指定会对牛鞭效应和需求预测的准确性产生影响。;第二篇文章旨在调查相关的预测准确性单变量和多元时间序列方法的比较，以进一步检查多元时间序列方法是否比简单的单变量方法更有效。此外，本文旨在评估需求，供应和库存变量之间的因果关系。本文从以下几个方面为供应链文献做出了贡献。首先，将多元时间序列模型首次引入供应链管理领域，以研究预测准确性并检验所考虑变量之间的关系。单变量和多变量预测方法的选择是预测领域的主要研究目标。其次，尽管一些先前的研究使用多元方法来描述需求过程，但这项研究还是第一个介绍模型规格的数值结果并基于模型进行预测的研究。第三，本研究是首次使用多元时间序列方法研究需求，供应和库存之间的因果关系。最后，本研究提供了另一种有效且在理论上稳健的工具来检验供应链中均衡条件的存在。第三篇论文的主要目的是描述供应链中不同类型的波动的转变。本文从多个方面为文学做出了贡献。首先，首次使用多元广义自回归异方差模型以经验方式建立供应链中波动率转移的存在。其次，该研究也是第一个考虑平衡的供需系统的影响的系统，其中需求，供应和库存都是固定过程。这一发现的主要贡献在于，在存在牛鞭效应的情况下制定供应链库存管理政策时，有必要明确考虑波动性的影响。 （摘要由UMI缩短。）

著录项

  • 作者

    Chiang, Chung-Yean.;

  • 作者单位

    State University of New York at Buffalo.;

  • 授予单位 State University of New York at Buffalo.;
  • 学科 Business Administration General.;Business Administration Management.
  • 学位 Ph.D.
  • 年度 2011
  • 页码 144 p.
  • 总页数 144
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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