Abstract
The authors argue that for the cross-sectional multiattribute approach to choice modeling, the multinomial logit is theoretically and empirically superior to the more commonly used regression approach. Other choice methodologies also are discussed briefly in relation to logit. The difference between individual level (where regression is appropriate) and cross-sectional analysis is recognized. Most marketing managers, because of their research goals, will be using a cross-sectional approach. The derivation of the logit from an underlying behavioral model of choice is illustrated. It is this underlying behavioral model of choice that provides logit with several conceptual advantages for modeling a multiattribute choice structure.