Traditional market share response (multiplicative competitive interaction or MCI) models have been gainfully employed in marketing research practice as an effective methodology for estimating competitive effects. Legions of books and articles on MCI models and their use have been published documenting the successful formulation and implementation of this class of models. In this spirit, this paper proposes a generalization of this class of models to a latent structure framework incorporating within-segment random brand effects. We apply and contrast this new formulation against the traditional aggregate MCI model formulations in an application involving physician prescription shares for three major brands of central nervous system (CNS) ethical pharmaceuticals (known as CNS drugs). We conclude the manuscript with managerial implications and suggestions for future research.
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