Product variety in local grocery stores: Differential effects on stock‐keeping unit level sales

Abstract

AbstractWe empirically examine the effect of product variety on sales at the stock‐keeping unit (SKU) level. Prior empirical operations management studies generally treat product variety as a single‐dimensional measure (e.g., the number of SKUs carried by the store, distribution center, or firm) and study its impact on aggregate sales (e.g., sales at the store, distribution center, or firm). As such, SKUs from different brands are assumed to contribute equally to total sales, which is not always the case. To address this, we need to conceptualize product variety within brands and investigate its impact on sales at a more granular level. In this study, we propose and theoretically articulate two product variety dimensions (within‐brand variety [WV] and average WV of other brands [AWVO]) to investigate the mechanisms that connect product variety to SKU‐level sales. Using a detailed transaction dataset from a local grocery retailer, we first show that product variety conceptualized within brands (i.e., the mean of WVs [MWV]) does have an impact on aggregate subcategory sales, as the literature suggests. At the SKU level, we find WV increases same‐brand SKU sales, while AWVO reduces it. Our work provides an alternative explanation to the inverted U‐shaped relationship between product variety and aggregate sales observed in the literature: Increasing variety only increases sales of SKUs belonging to the brand whose variety has increased, while it decreases sales of the other SKUs. We also find that variety effects vary significantly across different profitability levels and product categories. Product variety appears to have the strongest positive effect on high‐margin products. The impact of product variety on specific product category sales varies from as high as 11% to negligible. We further discuss the practical value of our findings and show the robustness of our results through multiple tests while addressing endogeneity using the control function approach.