题 目：To Whom Should I Listen? Finding Reputable Reviewers in Opinion-Sharing Communities
主讲人：Ku Yi-cheng博士 （Department of Computer Science and Information Management, Providence University）
时 间：2012.6.25（周一）下午4:00
地 点：主楼418会议室
主讲人简介：
Yi-Cheng Ku is an Assistant Professor at the Department of Computer Science and Information Management at Providence University in Taiwan. He received his Ph.D. in Information Management from National Sun Yat-sen University. In 2009-2010, he was a Fulbright visiting scholar at the College of Management, Georgia Institute of Technology. His research interests include recommendation systems, information system adoption and diffusion, and knowledge management. His research has appeared in Journal of Management Information Systems (JMIS), Decision Support Systems (DSS), International Journal of Medical Informatics, International Journal of Business, and various conference proceedings.
内容简介：
Online opinion-sharing communities, which allow members to express personal opinions and preferences about specific products, provide important channels for consumers to learn about product quality and support their purchase decision process. Firms can use these reviews to understand customers’ responses to their products and improve their products accordingly. Furthermore, opinion-sharing communities provide an alternative, effective marketing channel to firms by offering electronic word of mouth (eWOM). However, due to the openness and anonymity of opinion-sharing communities, their members face a challenging issue, that is, whether to believe or disbelieve information provided by other members. This study attempts to discriminate members (i.e., reviewers) with a high reputation from those with a low reputation on the basis of members’ web trust network and review behaviors in an opinion-sharing community. We collected sample data pertaining to four product categories from Epinions.com to test our research model. The results indicate that four variables (trust intensity, average trust intensity of trustors, degree of review focus in the target category, and average product rating in the target category) successfully discriminate reviewers into the two groups, and product type is a significant control variable. These findings not only help firms identify reputable reviewers for marketing campaign purposes but also enable the members of an opinion-sharing community to determine who reputable reviewers are and whose reviews they should trust.