Standardizing Variables in Multiplicative Choice Models

Abstract

To use multiplicative competitive interaction (MCI) models as part of a theory of the evaluative process in choice, we need a method to transform interval scale consumer judgments into positive, ratio scales. We develop a coefficient—zeta-squared—that possesses the needed scale requirements and other theoretically desirable properties, and report four research studies to demonstrate the diversity of applications of multiplicative choice models using zeta-squared. We also discuss the relations of MCI models to Luce choice models to illustrate the potential of zeta-squared for representing the effects of similarity on choice, and consider some of the benefits of standardizing variables in MCI models or multinomial logit models.