腾讯会议号：744 196 441
Yi-Cheng Ku教授，台湾辅仁大学工商管理系教授。博士毕业于中山大学信息管理专业。2009-2010年，赴佐治亚理工学院管理学院访问。他的研究兴趣包括推荐系统，信息系统的采用和传播，以及服务设计。他的研究成果发表在Computers in Human Behavior、Decision Support Systems (DSS)、Information & Management (I&M)、International Journal of Medical Informatics, Journal of Electronic Commerce Research, Journal of Management Information Systems (JMIS)等知名期刊。
Many e-stores adopt personalized recommender systems to provide service for the customers nowadays, which they can rely on to predict customers’ preferences based on the detailed individual customer information. Customers got better services provided by the personalized recommender systems. However, customers also concerned that the websites may steal, misuse or sell their information to a third party. Such situation causes the “personalization- privacy paradox”. This study proposed a research model based on the privacy calculus theory to explore how the customers make decision between personalized service and privacy concern. An online survey was conducted to collect empirical data in order to test our research model. The results of PLS analysis indicate that personalized service is positively affects perceived benefit. Both information sensitivity and privacy concern positively affects perceived risk. However, when customers with low information sensitivity and low privacy concern, they are less likely to evaluate associated risks. Perceived value is influenced by perceived benefit and perceived risk and in term, affects customers’ willingness to provide personal information. The findings of this study provide implications for both researchers and practitioners of using personalized recommender systems.
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