Title

An empirical investigation and comparison of neural networks and regression for scanner data analysis.

SelectedWorks Author Profiles:

Thomas L. Ainscough

Document Type

Article

Publication Date

1999

Date Issued

January 1999

Date Available

December 2011

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 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.