TY - GEN
T1 - Modeling the network of loyalty-profit chain in chemical industry
AU - Lee, Carl
AU - Rey, Tim
AU - Tabolina, Olga
AU - Mentele, James
AU - Pletcher, Tim
PY - 2006
Y1 - 2006
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=33947663010&partnerID=8YFLogxK
U2 - 10.1109/ICIS-COMSAR.2006.62
DO - 10.1109/ICIS-COMSAR.2006.62
M3 - Conference contribution
AN - SCOPUS:33947663010
SN - 0769526136
SN - 9780769526133
T3 - Proceedings - 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
SP - 492
EP - 499
BT - Proceedings - 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
Y2 - 10 July 2006 through 12 July 2006
ER -