Retail pricing decisions and product category competitive structure

摘要

This study addresses the use of demand forecasting techniques by retailers to support their decision making. Specifically, the authors propose a pricing decision support model for retailers to estimate optimal prices, whose output depends on the configuration of a supporting measurement model. The measurement model is a demand function that relates sales and prices within the category; optimal prices are those whose effects on demand and retail margins maximize the category's profitability. This investigation focuses particularly on the role of competitive structure, such that the authors consider two types of price competition asymmetries for demand forecasting: those depending on the brand (differential price effects) and those dealing with demand for competing brands (cross-price effects). By explicitly modeling competitive asymmetries in the demand function that underlies the decision support model, the authors assess implications for pricing decisions, sales, and profitability. The empirical application of the model to store-level, aggregated scanner data for two frequently purchased categories reveals the impact of an asymmetric competitive structure on demand forecasting and optimal pricing decisions. Furthermore, this article quantifies the costs of ignoring asymmetric competitive interactions in retailers' decision making.