Simon Business School
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Bhoomija Ranjan

Area of Study: Marketing


Ex: 585-775-7113



Research Statement

Teaching Statement

Prior Education

  • Master of Science in Business Administration, University of Rochester, 2014
  • M.A. Economics, University of Rochester, 2012
  • M.Sc. Mathematics & Scientific Computing, Indian Institute of Technology Kanpur, 2010

Research Interests

  • Consumer & Retailer learning
  • Retailer assortment & pricing
  • Brand & Category building
  • Quantitative Marketing & Structural Econometrics

Research Papers/Publications

  • Essay I: Effect of Location and Assortment on Category Consideration, Learning, and Choice, with Paul Ellickson & Mitchell Lovett (Job Market Paper)
    Retailers aim to maximize profits given the constraints of space and existing infrastructure. They frequently face the problem of department management, to overhaul the assortments and locations of multiple product categories sharing a common area in the store.  Although category and departmental resets are frequently performed by retailers, an empirical analysis of the effects of these department layout changes has not been done. To analyze this question, we exploit a “natural” experiment of a large-scale departmental reset of dairy in a supermarket store location, with two other stores acting as controls. With a rare dataset of floorplans and category planograms, we characterize 11 reset treatments related to location and assortment changes. Analyzing both aggregate and household-level purchase data, we present descriptive evidence that the reset made a significant (2.6%) improvement in sales. We find that the changes affect purchase probabilities through the channel of attention/consideration, and induce learning among customers. We then specify a structural model of demand that incorporates multi-category consideration, learning, and choice at the individual-level. The model enables us to leverage the exogenous variation in location and assortments to identify the effects on attention/consideration and choice. Preliminary results indicate that the location of the category within the store layout has a significant effect on consideration. We find that being adjacent to popular categories has a negative effect on consideration among customers who have tried the category earlier, but has a much larger positive effect among customers who have never bought the category, thus inducing trial. Our learning estimates also indicate that consumers’ perceptions of category match values are positively biased on average, which leads them to try the product but that far fewer individuals make it a regular feature of the on-going shopping basket.

       Works in Progress

  • Data-driven Private Brand Launches: A Conjoint-Shopper Panel Technique for Estimating Demand, Selecting Products, and Setting Prices, with  Mitchell Lovett & Paul Ellickson
    Private brands have not traditionally used choice experiments, such as conjoint analysis, to determine the best product profiles for new product launches. In this paper, we demonstrate that such choice experiments can improve predictions and aid in choice when combined with revealed preference data contained in rich shopper panel that are readily data available to retailers. We develop a model that addresses two inconsistencies between conjoint estimates and estimates from actual choices--(1) contextual differences between hypothetical and real-life choice scenarios and (2) sample selection. We apply this framework to a managerial problem of estimating demand and setting prices for a new Greek Yogurt product. Our dataset includes a conjoint questionnaire and the actual purchase histories of the same survey respondents. Preferences across these data are combined using a multi-dimensional scaling approach. We then integrate these these two datasets for the surveyed individuals with a third dataset of retail shopper-panel data for a random sample of consumers. Combining these three data sources helps us to estimate parameters that have greater predictive power for managerial outcomes for new product introductions. We evaluate the model predictions and make optimal choices for a new product launch. We then compare these predictions and decisions against the actual field outcomes in a field test.
  • Investigating the Role of Product Line length in Preference Learning, with Mitchell Lovett
    We study a rapidly growing CPG category with multiple brand entries and new variety offerings. Consumers learn about true brand quality from advertisements as well as product experience. They also face differing availability of brands and varieties depending on the stores they frequent, inducing heterogeneity in learning rates. Product-line length can affect brand perceptions in two ways. First, a bigger product-line can signal to the consumer that the brand is an expert in the category, affecting brand-specific utility directly. Second, a bigger product-line makes it more likely for consumers to be aware of and interact with the brand. This information can allow the consumer to recognize products that match their tastes. We develop a model of consumer learning and choices that incorporates signals from advertising, product-line length and experience. We apply this model to a unique retail shopper-panel dataset of yogurt purchases across store locations of a major supermarket chain for a random sample of consumers. During our 101-week sample period, 4 brands and 7 new flavors were introduced in Greek yogurt. In the same period, Greek yogurt category share tripled, probability of purchase per store visit quadrupled from 1.8% to 7.8%, and average weekly category-level advertising expenditures increased from $22,000 in the first quarter to $286,000 in the last quarter. Combining this shopper panel purchase information with advertising data, we investigate the relative effects of advertising and product-line on brand learning and category growth.
  • Optimal department location and assortment allocations
    In an extension to my job market paper, I am looking at the supply side and the retailer's decision of planning the department layout to enhance consumers' shopping experiences. This involves allocating a fixed total store area among different categories and managing their individual product assortment to maximize total future revenue streams. Previous studies have focused on optimal space allocations for single standalone categories. Yet, my other research shows that neighboring categories have a significant effect on category demand through the channel of attention. Therefore, planning the optimal layout involves a careful analysis of individual preferences attention within and across categories. In this study, I study how the retailers should make layout decisions given the complex consumer response to layout and adjacency. Further, I investigate how often the retailer should change the layout in order to induce consideration and learning among consumers across categories.
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