Market share modeling within a switching regression framework

Marketers often need to analyze and predict market share for a brand or a firm. These predictions can be based on product attributes and marketing variables. Two analytical techniques have been shown to be better at this task than other models: Multinomial Logit (MNL) and the Multiplicative Competitive Interaction (MCI) models. This study shows that the MNL and MCI models can be derived from a common foundation. It also extends the MNL model by integrating it with switching regression techniques. This new model, switching multinomial logit (SMNL), provides several theoretical advantages over both the basic MCI and MNL models. With a sample data set, the SMNL model outperforms the simple MNL model with a 10% reduction in errors.