Neural network applications in consumer behavior

被引:11
作者
Briesch, Richard [1 ]
Rajagopal, Priyali [1 ]
机构
[1] So Methodist Univ, Edwin L Cox Sch Business, Dallas, TX 75275 USA
关键词
Methodology; Regression; Structural equations; Discriminant analysis; Nonparametric; PRINCIPAL COMPONENT ANALYSIS; DISCRIMINANT-ANALYSIS; CLASSIFICATION; EXPERIENCE; REGRESSION; SYSTEMS; MODELS; CHOICE;
D O I
10.1016/j.jcps.2010.06.001
中图分类号
F [经济];
学科分类号
02 ;
摘要
This article introduces the concepts and terminology of artificial neural networks. The approach is demonstrated on data that represent a domain of interest to the consumer psychologist. ANNs are mathematical models that are commonly used in business applications to model relationships between variables. A key strength of ANNs is their flexibility, i.e. their ability to easily accommodate linear and non-linear relationships without any a priori functional form specification. They can easily be used to study topics of interest to consumer psychologists such as persuasion, influence, segmentation etc and can oiler distinct advantages over traditional statistical techniques such as ANOVA and regression. We demonstrate the application of ANNs in three different areas: regression, non-linear principal component analysis and classification. (C) 2010 Society for Consumer Psychology. Published by Elsevier Inc. All rights reserved.
引用
收藏
页码:381 / 389
页数:9
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