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1. An Empirical Study of Healthy Consumption.
Research Team: Cheng-Ting Chen (UG student University at Buffalo), Vijay Ganesh Hariharan (PhD Student, University at Buffalo) and Minakshi Trivedi (University at Buffalo).
Details: Part of marketing research is to understand the consumption patterns in the consumer market, with regards to healthy and unhealthy products. The information to be derived from such research will be valuable to the producers of food and beverages that may have certain health risks associated with it. In this study, using the Buffalo CRM data base, we empirically look at differences in patterns of consumption for several product categories across geographic regions and demographics.
2. A Field Examination of the Influence of Brand Equity on Behavioral Loyalty and Factors that Moderate this Relationship.
Research Team: Kalpesh Desai (University at Binghamton), Jan Hofmeyr, Dr. J. Jeffrey Inman (University of Pittsburgh) and Debabrata Talukdar (University at Buffalo). Authors listed alphabetically.
Details: While prior research has highlighted the critical role of brand equity in influencing customer retention, the mapping between brand equity and customer retention has been less than perfect. In this research, we posit that this linkage is moderated by individual difference variables of brand equity of other alternatives in the category, importance of brand choice, and ambivalence (arising from perceived low differentiation between alternatives). Across several product categories, we will relate consumer’s purchases (available from scanner data) with their attitudinal data (to be collected through surveys) about the equity of distinct brands in the category. We will measure at individual level nine dimensions of brand equity and the individual difference variables specified above along with other factors that moderate the influence of brand equity on brand choice. This will enable us to test hypotheses about consumer moderators responsible for heterogeneity in the brand equity – choice linkage. In addition, it will facilitate testing hypotheses about the contexts in which the influence of brand equity on choice is higher and also investigate the specific dimension(s) of brand equity that result in the enhanced influence of brand equity on choice in those contexts. We define these contexts with respect to brand factors (e.g., the market leader, the private label brand), household factors (e.g., heavy category users, older consumers), and marketing mix factors (e.g., price promotion of non-target brands).
3. Implications of Consumer Variety Seeking for Retailers’ Product Line Decisions.
Research Team: Kalpesh Desai (University at Binghamton), P. B. (Seethu) Seetharaman (Rice University) and Minakshi Trivedi (University at Buffalo). Authors listed alphabetically.
Details: We investigate the consequences of consumers’ variety-seeking along product attributes for retailers’ product line decisions. Using scanner and survey data from a sample of households in the database of a local grocery chain, we estimate a demand model that is based on the assumption that consumers switch between brands over time in response to their desire for variety in the attributes being consumed. Using the estimates of the demand model, we then perform managerial policy simulations that show the degree to which retail profits can be improved by appropriately extending or pruning the length of product lines in response to the documented variety-seeking effects in demand. In doing so, we are able to explicitly disentangle the separate roles of (i) across-consumer heterogeneity in preferences for product attributes (which are constant over time), and (ii) within-consumer variety-seeking in product attributes over time. We plan to confirm some of the findings from the above model estimation by running lab experiments.
4. Context-Specific Positive Influence of Walmart on Value-Priced Grocery Stores.
Research Team: Kalpesh Desai (University at Binghamton), Karthik Sridhar (PhD Student, University at Buffalo), Andrei Strijnev (University of Texas, Dallas) and Debabrata Talukdar (University at Buffalo). Authors listed alphabetically.
Details: A widespread expectation of Walmart’s entry into grocery business is that it will have a uniformly adverse impact on the businesses of grocery stores, both across products types and types of grocery stores. Using the literature on context effects as theoretical underpinning, we propose that Walmart’s entry may produce beneficial effects for value-priced grocery stores in those markets where prior to the entry of Walmart, these stores were primarily competing against a more upscale grocery store. The positive influence will be restricted to products with high price-high quality associations (e.g., wine, flowers, expensive bakery products) and private label products (including produce) because the low price-low quality associations for these products that were earlier linked to value-priced grocery stores will now shift to Walmart.
5. Does Ingredient Branding Help Choice of Host and Ingredient Brands?
Research Team: Kalpesh Desai (University at Binghamton), Dinesh Kumar Gauri (PhD student, University at Buffalo), Yu Ma (University of Alberta) and S. Ratneshwar (University of Missouri, Columbia).
Details: In this study we investigate if and how both host and ingredient brands benefit from the ingredient branding alliance. After controlling for some covariates, our model specifically ascertains if the sale of ingredient brand, post incorporation into the host brand, increased, decreased, or remained steady. Moreover, if it improved, what is the source – current ingredient brand consumers using the ingredient brand more and/or new consumers (how many are host brand users vs. non host brand users)? On the other hand, if the ingredient brand sales declined, is it because current consumers of ingredient brand are now “satisfying” their need for the ingredient product through the use of host brand? Our model ascertains answers to similar questions for the host brand and investigates the role of three moderating variables.
6. Benchmarking Performance in the Retail World: An Integrated Approach.
Research Team: Dinesh Kumar Gauri (PhD student, University at Buffalo), Gabor Pauler (University of Pécs, Hungary) and Minakshi Trivedi (University at Buffalo).
Details: Standardizing performance expectations across different stores within a chain, differing in store features, its consumers, and the nature of competition it faces, can be an onerous task. We develop an integrated, non-linear, market share model of store expectations that draws upon the existing trade area as well as store performance literatures. By incorporating and normalizing a large number of external and internal factors impacting performance, we are able to offer a means for the retailer to determine equitable standards. The model is estimated using Maximum Likelihood Estimation, on a data set fashioned from several sources. Finally, we propose a set of indices that allows us to evaluate relative performances of stores and regions given the competitive environments they face.
7. Variety Seeking and the Two Stage Model of Choice.
Research Team: Minakshi Trivedi (University at Buffalo), Amresh Kumar (PhD Student, University at Buffalo) and Kalpesh Desai (University at Binghamton). Authors listed alphabetically.
Details: In this study we investigate the notion that since high variety seekers prefer and seek variety, they are likely to perceive differences between two options that low variety seekers might not notice. Combining scanner and survey data, we examine this issue in the context of the two stage model of choice — brand consideration and brand evaluation resulting in choice (Nedungadi 1990). When translated into the two stage choice model, the above seeking of differences suggests that if high variety seekers seek variety at the consideration stage, they will consider very different options that are still perceived to satisfy their goals i.e., they will exaggerate similarities among the very different options compared to low variety seekers. In contrast, if they seek variety at choice stage, they will exaggerate differences among the chosen options compared to low variety seekers.
8. Optimizing Purchase Behavior at the Basket Level.
Research Team: Vijay Ganesh Hariharan (PhD Student, University at Buffalo) and Minakshi Trivedi (University at Buffalo).
Details: Multi-category choice models are an increasingly popular class of models, whereby consumer preferences for brands in multiple categories are modeled using a joint distribution that allows different categories to be correlated. Thus, for example, when choosing a salty snack, researchers will typically analyze, say, potato chips, pretzels and nachos. We argue, however, that in many cases the study of consumption behavior cannot be constrained to a limited number of categories. We plan to show, using a multi-category, latent structure model, corroborated by survey data to explore the ‘whys’, that consumers optimize utility not just over a few similar categories, but in fact, over a strategically pre-selected set of categories, and the entire shopping basket. Such basket level utility maximizing behavior has tremendous implications for retail and manufacturer strategy.
9. Disaggregating the Promotional Bump.
Research Team: Karthik Sridhar (PhD Student, University at Buffalo), Sanjib Mohanty (PhD Student, University of Rochester) and Minakshi Trivedi (University at Buffalo).
Details: In this paper, we disaggregate the promotional impact to model separately the advantages to the retailer and the manufacturer. Using an integrated model for purchase behavior, we evaluate the impact of promotions on profitability measures and address issues such as financial implications for category expansion or purchase feedback effect.