Estimation of posterior probabilities of consumer situational choices withneural network classifiers

This study shows how neural networks can be used to estimate the posterior probabilities in a consumer choice situation. We provide the theoretical ba sis for its use and illustrate the entire neural network modeling procedure with a situational choice data set from AT&T. Our findings supported the a ppropriateness of this application and clearly illustrate the nonlinear mod eling capability of neural networks. The posterior probability estimates cl early add to the usefulness of the technique for marketing research. (C) 19 99 Elsevier Science B.V. All rights reserved.