The Choice Theory Approach to Market Research

TLDR

Economic choice theory has evolved to enable market demand forecasts from psychometric and conjoint experiment data. This paper surveys those developments to facilitate such forecasting. The authors review alternatives to multinomial logit, present a new multinomial probit estimator, integrate choice models with attitudinal scaling and perceptual mapping in a latent variable framework, discuss random and fixed‑effect heterogeneity, address conjoint experiment issues, and introduce diagnostic tests for multinomial logit consistency.

Abstract

This paper surveys economic choice theory, stressing developments that permit use of data from psychometric and conjoint experiments to produce market demand forecasts. Alternatives to the widely used multinomial logit model are summarized, and a new method for estimating multinomial probits is described. An integration of choice models with attitudinal scaling and perceptual mapping, within a latent variable system, is described. Estimation of such systems under either “random effects” or “fixed effects” descriptions of heterogeneity across individuals is discussed. Issues in the use of choice models to describe responses from conjoint experiments are presented. New regression diagnostic tests for the consistency of multinomial logit representations are discussed.