A Synthesis of Semantic Social Network and Attraction Theory for Innovating Community-Based e-Service

Abstract

There is a growing market for services and an increasing dominance of services in economies worldwide. From an economic perspective, services grow steadily more important and will be increasingly offered and deployed via the Internet. A good example is a community-based e-service that represents the provision of e-service to a community of individuals or business partners. This paper presents a method that can identify the promising and valuable new service features for innovating a given community e-service. Based on a service ontology and the combination of semantic social network and perception science, the method has three steps. First, through the semantic social network, identify the customer segments based on the same need. Second, to sustain the service attraction to the customers of a customer segment, manipulate the service choice set based on the attraction effect defined in perception science. Third, for service innovation and transformation, identify the new necessary enhanced service components based on a social-network-based analysis of the emergence behavior of customers on the e-service platform. The preliminary evaluation results also justify our claimed contributions for community-based e-services, i.e., a systematic method to manage customer segmentation well, sustain the service attraction, and identify new services required through a combination of semantic social network, perception science, and social network analysis.