Modeling Multiple Sources of Heterogeneity in Multinomial Logit Models: Methodological and Managerial Issues

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Abstract
We offer a framework to specify and estimate various sources of heterogeneity in multinomial logit brand choice models. We let each brand-specific intercept and each parameter of the explanatory variable vector vary randomly across households. In addition, we distinguish loyal households from the rest. Our results suggest that incorporating multiple sources of heterogeneity improves the model fit and suggests higher impact of marketing mix elements on brand choice. We highlight the importance of incorporating multiple sources of heterogeneity. The model we implement yields valuable managerial insights.