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A Bayesian Multi-Level Factor Analytic Model of Consumer Price Sensitivities Across Categories

Published online by Cambridge University Press:  01 January 2025

Sri Devi Duvvuri  and
Thomas S. Gruca
Sri Devi Duvvuri*
Affiliation:
SUNY at Buffalo
Thomas S. Gruca
Affiliation:
University of Iowa
*
Requests for reprints should be sent to Sri Devi Duvvuri, 215F Jacobs Management Center, SUNY at Buffalo, Buffalo, NY 14260, USA. E-mail: sduvvuri@buffalo.edu
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Abstract

Identifying price sensitive consumers is an important problem in marketing. We develop a Bayesian multi-level factor analytic model of the covariation among household-level price sensitivities across product categories that are substitutes. Based on a multivariate probit model of category incidence, this framework also allows the researcher to model overall price sensitivity (i.e., indicated by higher-order factor scores) as a function of household-level covariates. All model parameters are estimated simultaneously to circumvent the downward bias resulting from two-stage estimation. The modeling framework is illustrated using scanner panel data from multiple categories of instant coffee.

Keywords

cross category analysisrelated categoriesprice sensitivitymultivariate probitBayesian factor analysisheterogeneityMCMC proceduresMetropolis–Hastings algorithm
Type
Original Paper
Information
Psychometrika , Volume 75 , Issue 3 , September 2010 , pp. 558 - 578
Copyright
Copyright © 2010 The Psychometric Society

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Footnotes

The authors thank Asim Ansari, Don Lehmann, and Kamel Jedidi, Columbia University; Sunil Gupta, Harvard University; and Gary Russell, University of Iowa, for their valuable comments.

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