Article
An empirical investigation and comparison of neural networks and regression for scanner data analysis.
USF St. Petersburg campus Faculty Publications
Document Type
Article
Publication Date
1999
Abstract
The objective of this study is to examine neural networks as an alternative to traditional statistical methods for the analysis of scanner data. The results of the study showed that neural networks can be an effective alternative to regression for modeling and predicting the effects of retailer activity on brand sales. The neural network models exhibited better performance in terms of both mean squared error and R2 than the regression model.
Comments
Abstract only. Full-text article is available only through licensed access provided by the publisher. Published in Journal of Retailing
and Consumer Services, 6(4), 205-217. Members of the USF System may access the full-text of the article through the authenticated link provided.
Language
en_US
Publisher
Pergamon
Creative Commons License
Creative Commons Attribution-Noncommercial-No Derivative Works 4.0
Citation Information
Ainscough, T. L. & Aronson, J.E. (1999). An empirical investigation and comparison of neural networks and regression for scanner data analysis. Journal of Retailing and Consumer Services, 6(4), 205-217.