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The “When” and “Where” Dimensions of Cherry Picking.
Research Team: Dinesh Kumar Gauri (PhD student, University at Buffalo), K. Sudhir (Yale University), and Debabrata Talukdar (University at Buffalo). Authors listed alphabetically.
Details: In this study, we do an integrated analysis of spatial and temporal price search in response to price promotions and its impact on retailer profitability. We seek answers to three questions: First, how effective are the temporal, spatial and spatio-temporal price search strategies in obtaining lower prices? Second, what is the impact of alternative price search strategies on retailer profit? Finally, what are the predictors of household decisions to perform either spatial or temporal price search, both or neither? We use a unique data collection approach that combines household surveys with purchase data to address these questions.
Impact of Loss Leader Promotion on Store and Category Performances: Empirical Insights from Grocery Supermarkets.
Research Team: Dinesh Kumar Gauri (PhD student, University at Buffalo), Debabrata Talukdar (University at Buffalo), and B. T. Ratchford (University of Texas, Dallas)
Details: In this research we do what we believe to be the most comprehensive empirical analysis of the role of promotions on store performance. Specifically, we focus on the widely popular “loss leader” promotion, in which a subset of product items are priced below marginal costs to increase store traffic with the expectation that the people coming to the store will end up purchasing non-loss leader products. The existing research on loss leader promotions has been quite limited, especially with no study focusing on cross-category effects. In the context of grocery supermarkets, we analyze the effects of loss leader promotions (with and without feature promotion) on the different dimensions (traffic, sales and profit) of performance measures at both aggregate (store) and disaggregate (category) levels. In this research, we: (1) Study the overall impact of loss leader promotion strategy on critical store performance measures; (2) Identify the relative effectiveness of different product categories for loss leader and feature promotion on various measures of performance at store level; (3) Estimate own and cross-category relationship between loss leader promotions and performance.