We offer an econometric framework that models consumer's consideration set formation as an outcome of her costly information search behavior. Because frequently purchased products are characterized by frequent price promotions of varying depths of discounts, a consumer faces significant uncertainty about the prices of the brands. The consumers engage in a fixed-sample search strategy that results in their discovering the posted prices of a subset of the available brands. This subset is referred to as the consumer's “consideration set.” The proposed model is estimated using the scanner data set for liquid detergents. Our key empirical results are: (i) consumers zincur significant search costs to discover the posted prices of the brands; (ii) whereas in-store displays and feature ads do not influence consumers' quality perceptions of the brands, they significantly reduce search costs for observing the prices of the brands; (iii) per capita income of consumer's household significantly increases her search costs; and (iv) the consumers' price sensitivity is seriously underestimated if we were to assume that consumers get to know all the posted prices at zero cost. The proposed model is also estimated for the ketchup category to enable us to do cross-category comparisons of consumers' price search behaviorprice uncertainty, consumer search, consideration set, quality uncertainty, consumer learning, bayesian updating, structural model, econometric estimation
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.
Prior behavioral research has suggested that advertising can influence a consumer's quality evaluation through informative and transformative effects. The informative effect acts directly to inform a consumer of product attributes and hence shapes her evaluations of brand quality. The transformative effect affects the consumer's evaluation of brand quality by enhancing her assessment of her subsequent consumption experience. In addition, advertising may influence a consumer's utility directly, even without providing any explicit information—this is the persuasive effect. In this paper, we propose a framework that formally models the processes through which all three effects of advertisements impact consumers' brand evaluations and their subsequent brand choice decisions. In particular, we model source credibility, confirmatory bias, and bounded rationality on the part of consumers, by appropriately modifying the standard Bayesian learning approach. Our model conforms closely to prior behavioral literature and the experimental findings therein. In our empirical analysis, we get significant estimates of both informative and transformative effects across brands. We find interesting temporal patterns across the effects; for instance, the importance of transformative effects seem to grow over time, while that of informative effects diminishes. Finally, we conduct policy experiments to examine the impact of increased ad intensity on advertising effects, as well as the role played by consumption ambiguity.advertising effects, informative effects, persuasive effects, structural models, consumer learning, policy experiments, bounded rationality, confirmatory bias
Given the advent of basket-level purchasing data of households, choice modelers are actively engaged in the development of statistical and econometric models of multi-category choice behavior of households. This paper reviews current developments in this area of research, discussing the modeling methodologies that have been used, the empirical findings that have emerged so far, and directions for future research. We also motivate the use of Bayesian methods to overcome the computational challenges involved in estimation. Copyright Springer Science + Business Media, Inc. 2005multi-category, multivariate choices, basket data, bayesian estimation,
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