Retail-price drivers and retailer profits.

What are the drivers of retailer pricing tactics over time? Based on multivariate time-series analysis of two rich data sets, we quantify the relative importance of competitive retailer prices, pricing history, brand demand, wholesale prices, and retailer category-management considerations as drivers of retail prices. Interestingly, competitive retailer prices account for less than 10% of the over-time variation in retail prices. Instead, pricing history, wholesale price, and brand demand are the main drivers of retail-price variation over time. Moreover, the influence of these price drivers on retailer pricing tactics is linked to retailer category margin. We find that demand-based pricing and category-management considerations are associated with higher retailer margins. In contrast, dependence on pricing history and pricing based on store traffic considerations imply lower retailer margins.

Key words: retail-price drivers; retailer profits; time-series models; generalized forecast error variance decomposition

History: This paper was received July 21, 2004, and was with the authors 11 months for 3 revisions; processed by Marnik G. Dekimpe.

1. Introduction

In today's competitive environment, retailers face the complicated task of setting prices for many items. A typical grocery store in the United States carries around 31,000 items in approximately 600 product categories (Kahn and McAlister 1997). A recent article underscores the complexity of the pricing problem: "While most companies are savvy about cutting costs, few have figured out how much money they are giving up by using 'lunk-headed' pricing due to a lack of detailed information about market demand" (Business Week 2000). Also, the trade press suggests that retailers lack good tools for making pricing decisions (AMR Research 2000), as they have been slow to adopt sophisticated pricing models (Stores 2002). Therefore, the actual retail prices observed over time may differ greatly from model-recommended courses of action.

As a result, uncovering the drivers of retail prices is of great importance to marketing executives and academics. Surprisingly, there has been little empirical research in this area. Two notable exceptions are Chintagunta (2002) and Shankar and Bolton (2004). The former investigates category pricing behavior by decomposing retail prices into wholesale price, markup, additional promotional payments, retailer store brand objectives, and interretail competition for a single category in a single retail chain. Our study extends Chintagunta's (2002) work by using time-series models to develop empirical generalizations on the impact dynamics of cost-, customer-, company-, competitor-, market-, and category-drivers of retail prices over time and across brands, categories, and stores/chains. Shankar and Bolton (2004) use a cross-sectional design to study pricing strategies, focusing on price consistency, price-promotion intensity, price-promotion coordination, and relative brand price level. In contrast, we study dynamic pricing tactics with a focus on uncovering the drivers of retail prices over time.

From a modeling perspective, our study shares the basic VARX approach with Srinivasan et al. (2004). However, our research offers contributions in substantive, data, and methodological areas. First, Srinivasan et al. (2004) consider whether manufacturers or retailers benefit more from price promotions, while we focus on the drivers of retail prices across brands and categories over time. Second, they study which brand, category, and market conditions influence price-promotion elasticities and the allocation of their benefits across manufacturers and retailers. In contrast, we link the influence of price drivers on retailer pricing tactics to retailer category margin while controlling for brand and category characteristics. Our study also offers several methodological contributions that are discussed in [section]3.