Predicting Consumer Situational Choice with Neural Networks

Abstract

This study shows how neural networks can be used to model posterior probabilities of consumer choice and a backward elimination procedure can be implemented for feature selection in neural networks. Two separate samples of consumer choice situations were selected from a large consumer panel maintained by AT&T. Our findings support the appropriateness of using neural networks for these two purposes.