Empirical estimation of the bullwhip effect poses several challenges, although the bullwhip effect has been well studied in modeling papers. Using a dataset from a large supermarket chain, we estimate the product level bullwhip effect using various methods, analyze consequences of its different measurements and aggregations, and examine its impact on supply chain performance in terms of inventory ratio and stockouts. We have three major findings. (a) Bullwhip effect estimates exhibit different magnitudes dependent on how they are measured. The material bullwhip effect is greater in magnitude than the information bullwhip effect in our data, where demand correlations are sufficiently low. (b) The aggregated bullwhip effect ratios by store and by time are lower than the disaggregated bullwhip effect ratios, indicating that the aggregated bullwhip effect ratios underestimate the bullwhip effect. The aggregated bullwhip effect ratios by product are lower than the disaggregated bullwhip effect ratios, indicating the bullwhip effect is not as strong as theory predicts due to order pooling. (c) The bullwhip effect is associated with poor supply chain performance, as measured by elevated inventory ratio and stockouts. However, if the bullwhip effect is measured inaccurately, these benefits can be underestimated as much as 75% for inventory and 25% for stockouts.

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关于经验估计牛鞭效应：度量，汇总和影响

尽管对牛鞭效应进行了建模研究，但对牛鞭效应的经验估计提出了一些挑战。使用来自大型超市链的数据集，我们使用各种方法估算产品水平的牛鞭效应，分析其不同度量和汇总的结果，并从库存比率和缺货角度检查其对供应链绩效的影响。我们有三个主要发现。（a）牛鞭效应估计值显示不同的幅度，具体取决于其度量方式。在我们的数据中，物质牛鞭效应的幅度大于信息牛鞭效应，因为需求相关性足够低。（b）按商店和时间划分的总牛鞭效应比率低于经分类的牛鞭效应比率，表明总的牛鞭效应比率低估了牛鞭效应。各个产品的总牛鞭效应比率低于分解的牛鞭效应比率，这表明由于订单合并，牛鞭效应不如理论预测的那么强。（c）牛鞭效应与供应链绩效不佳有关，以提高的库存比率和缺货来衡量。但是，如果对牛鞭效应的衡量不正确，则这些收益可能会被低估多达75％（库存）和25％（缺货）。（c）牛鞭效应与供应链绩效不佳有关，以提高的库存比率和缺货来衡量。但是，如果对牛鞭效应的衡量不正确，则这些收益可能会被低估多达75％（库存）和25％（缺货）。（c）牛鞭效应与供应链绩效不佳有关，以提高的库存比率和缺货来衡量。但是，如果对牛鞭效应的衡量不正确，则这些收益可能会被低估多达75％（库存）和25％（缺货）。