Modeling the network of loyalty-profit chain in chemical industry

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationProceedings - 5th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2006. In conjunction with 1st IEEE/ACIS International Workshop on Component-Based Software Engineering, S
Pages492-499
Number of pages8
DOIs
StatePublished - 2006
Externally publishedYes
Event5th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2006. In conjunction with 1st IEEE/ACIS International Workshop on Component-Based Software Engineering, Software Architecture and Reuse, COMSAR 2006 - Honolulu, HI, United States
Duration: Jul 10 2006Jul 12 2006

Publication series

NameProceedings - 5th IEEE/ACIS Int. Conf. on Comput. and Info. Sci., ICIS 2006. In conjunction with 1st IEEE/ACIS, Int. Workshop Component-Based Software Eng., Softw. Archi. and Reuse, COMSAR 2006
Volume2006

Conference

Conference5th IEEE/ACIS International Conference on Computer and Information Science, ICIS 2006. In conjunction with 1st IEEE/ACIS International Workshop on Component-Based Software Engineering, Software Architecture and Reuse, COMSAR 2006
Country/TerritoryUnited States
CityHonolulu, HI
Period07/10/0607/12/06

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