Intelligent Decision Making and Risk Analysis of B2c E-Commerce Customer Satisfaction

Customer satisfaction and relationship is complex, demanding, and yet crucial to an organization success and its competitive position in the marketplace. Due to rapid changes in emerging technologies there is a need for constant improvement and adjustment of product and services offered using e-commerce systems. Customer satisfaction is dependent on a large number of organizational as well as product and services attributes. These attributes require continuous development, improvement and monitoring. The interdependencies of these attributes make it very difficult for managers and product and services development teams to comprehend and be aware of effect (Pires et al 2004, Rohm et al 2004, Sirdeshmukh et al 2002, Yang 2007) of inefficiencies that may exist in development and offering of their products and services. This paper considers the implementation of an intelligent decision making system using Fuzzy Cognitive Maps (FCMs) to provide facilities to capture and represent complex relationships in a customer satisfaction management and modelling to improve the understanding of managers and product developers about their customers and associated risks related to products and services that are offered online using e-commerce sites. By using FCMs, customer satisfactions can regularly be reviewed and improved. Managers can perform what-if analyses to better understand vulnerabilities and pitfalls in the way their product and services are provided to customers. Intelligent Decision Making and Risk Analysis of B2c E-Commerce Customer Satisfaction