Title
Explaining consumer choice through neural networks: The stacked generalization approach
Abstract
This paper uses neural network models and the ensemble technique of stacked generalization to investigate the relative importance of situational and demographic factors on consumer choice. We discuss the theoretical justification for this approach and develop the level-0 and level-1 models which we estimate using a consumer choice data set from AT&T. The findings confirm the superiority of situational factors in explaining the consumers’ choice of communication modes and support the strength of stacked generalization. Important clues that emerge from the analysis regarding the factors to be accounted for when developing efficient neural network structures are also discussed.
Year
DOI
Venue
2003
10.1016/S0377-2217(02)00368-5
European Journal of Operational Research
Keywords
Field
DocType
Neural networks,Consumer behavior
Consumer behaviour,Computer science,Consumer choice,Artificial intelligence,Situational ethics,Artificial neural network,Machine learning
Journal
Volume
Issue
ISSN
146
3
0377-2217
Citations 
PageRank 
References 
12
0.86
4
Authors
2
Name
Order
Citations
PageRank
Michael Y. Hu142655.74
Christos Tsoukalas2121.20