Modeling the Network of Loyalty-Profit Chain In Chemical Industry

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