Choice Map: Inferring a Product-Market Map from Panel Data

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Abstract
This paper describes Choice Map, a model that infers a product-market map from panel data. Choice Map is a stochastic brand choice model, a random utility quantal choice model, and a multidimensional scaling procedure. Choice Map combines the parsimony of stochastic choice models, the rationale of random utility models, and the ability of multidimensional scaling procedures to simultaneously infer both brand positions and consumer preferences from preference (choice) data. Choice Map assumes that consumers have stationary purchase probabilities for the observational period, which makes the model best suited to frequently-bought mature product categories. Neither experimental nor survey data are required. Traditional mapping methods that scale such data may not yield the same structure for low-involvement products as will a procedure like Choice Map that scales behavioral data. Choice Map's descriptive and predictive validity exceeds that of an alternative stochastic brand choice model (the Dirichlet-multinomial) for a test data set.

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