DescriptionDevelopment and implementation of products and services offered using e-commerce websites requires effective customer satisfaction management. 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 of inefficiencies that may exist in development and offering of their products and services. This talk considers the implementation of a Computational Intelligence techniques to provide facilities to capture and represent complex relationships in a customer satisfaction management and modeling 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 Computational Intelligence techniques (such as Fuzzy Logic and Evolutionary Algorithms) customer satisfactions can regularly be reviewed and improved. By changing and modifying the attributes that have impacts on customer satisfaction the customer satisfaction and loyalty can be enhanced. This approach will provide greater improvement in development, monitoring of customers’ needs. Managers can perform what-if analyses to better understand vulnerabilities and pitfalls in the way their product and services are provided to customers.
|Period||30 Aug 2018|
|Event title||7th International Conference on Reliability, Infocom Technologies and Optimization: Trends and Future Directions|
|Degree of Recognition||International|