RECOGNIZING KEY SERVICE FACTORS OF ATTRACTING NEW VIRTUAL COMMUNITY MEMBERS

Abstract

Recently, we observed a great movement of Internet users from blogs and wiki to Myspace, Facebook, Twitter, and Plurk. To increase profit margins, identifying the service factors that attract customers to join a new virtual community is crucial for website enterprises. Most works focus on social networks, success factors, and reasons for participating. Relatively few works have attempted to address this issue. Additionally, feature selection techniques have been widely used to extract crucial attributes. However, domain knowledge, which is hard to obtain, is needed to select meaningful features. Therefore, this work proposes a Kano's model based Neural Network (KANN) method combining Kano's model and neural networks to identify the key service factors. Finally, a real case study of a survey of virtual community users is provided to identify the key service factors.