The impact of pricing policy on sales variability in a supermarket retail context

Abstract The bullwhip effect is recognized to be a significant cost driver in supply chains. One of the measures proposed frequently to counter bullwhip effect is price stability, through everyday low pricing (EDLP). However, this study suggests that with an auto-regressive (AR1) demand process, the use of constant, instead of dynamic pricing may result in lower profitability and higher-demand volatility. An optimal price and stocking level policy is developed with normally distributed demand in this study and the model is tested using parameters from a supermarket scanner data set to determine the impact of two pricing policies. The hypothesis that low prior-period demand leads to discounted pricing is also tested and partially supported.

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