Investigating Consumers’ Purchase Incidence and Brand Choice Decisions Across Multiple Product Categories: A Theoretical and Empirical Analysis

Abstract

W e propose a framework to investigate consumers' brand choice and purchase incidence decisions across multiple categories, where both decisions are modeled as an outcome of a consumer's basket utility maximization. We build the model from first principles by theoretically explicating a general model of basket utility maximization and then examining the reasonable restrictions that can be placed to make the solution tractable without sacrificing its flexibility. Comparing with prior models, we show why prior multicategory purchase incidence models overemphasize the role of the cross effects of a market mix of brands in other categories on the purchase incidence decision of a given category. Additionally, we show that prior singlecategory models are a special case of the proposed model when further restrictions are placed on the basket utility structure. We estimate the model on household basket data for the laundry family of categories. We show (i) why prior single-category and multicategory models would systematically bias the estimates of the own-and crossprice/promotional purchase incidence elasticities; and (ii) how the market mix of each brand in each category affects the purchases across all categories, which can help retailers make promotional decisions across a portfolio of products.Key words: multicategory brand choice and purchase incidence decision making; microeconomic theory of demand; basket utility maximization; simulated maximum likelihood History: This paper was received March 8, 2005, and was with the authors 5 months for 2 revisions; processed by Tülin Erdem.

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“…These are the conditional moment restrictions (22)- (24) and the unconditional moment restrictions (32)- (36) and (41)- (42).…”

“…2004)) or repeated purchases by the same consumer (like in our data), help to pin down the effects of unobserved and observed sources of taste heterogeneity, since both drive correlation between choices, and cross-sectional data alone is sufficient to estimate the latter. 36 Each of the taste shocks in our model influences one observed outcome in particular, such as total spending, store used or distance traveled. By matching the observed covariance of each such outcome across time periods, in the same way that Berry et al (2004, p. 74-5) "matched .…”

“…Bell et al (1998), Fox et al (2004)) and another studying multi-category demand (e.g. Chintagunta and Song (2007), Mehta (2006)) by studying these different aspects of demand in a unified multi-store multi-category utility framework.…”