Modeling the Network of Loyalty-Profit Chain In Chemical Industry

Author

Lee, Carl ; Rey, Tim ; Tabolina, Olga ; Mentele, James ; Pletcher, Tim

Author_Institution

Central Michigan Univ., Mount Pleasant, MI

fYear

2006

fDate

10-12 July 2006

Firstpage

492

Lastpage

499

Abstract

This article presents a technique, namely, structured neural network, to model the network of cause-and-effect relationships of the loyalty-profit chain for a chemical industry. A comparison between the structured neural network, the traditional neural network and regression models is presented. It is concluded that a strictly empirical modeling approach is not satisfactory when modeling a complex network. It is crucial to take the contextual knowledge and/or theoretical framework into consideration

Keywords

cause-effect analysis; chemical industry; neural nets; profitability; cause-effect relationship; chemical industry; complex network modeling; contextual knowledge; loyalty-profit chain; regression model; structured neural network; Chemical industry; Companies; Complex networks; Costs; Customer satisfaction; Electronic mail; Intelligent networks; Marketing and sales; Neural networks; Predictive models;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Information Science, 2006 and 2006 1st IEEE/ACIS International Workshop on Component-Based Software Engineering, Software Architecture and Reuse. ICIS-COMSAR 2006. 5th IEEE/ACIS International Conference on

Conference_Location

Honolulu, HI

Print_ISBN

0-7695-2613-6

Type

conf

DOI

10.1109/ICIS-COMSAR.2006.62

Filename

1652038