時(shí)間：1月6日（星期三）下午14:00-15:30
騰訊會(huì)議號(hào)：744 196 441
報(bào)告人：臺(tái)灣輔仁大學(xué)企業(yè)管理學(xué)系Yi-Cheng Ku教授
報(bào)告人簡(jiǎn)介：
Yi-Cheng Ku教授，臺(tái)灣輔仁大學(xué)工商管理系教授。博士畢業(yè)于中山大學(xué)信息管理專業(yè)。2009-2010年，赴佐治亞理工學(xué)院偉德國(guó)際1946bv官網(wǎng)訪問(wèn)。他的研究興趣包括推薦系統(tǒng)，信息系統(tǒng)的采用和傳播，以及服務(wù)設(shè)計(jì)。他的研究成果發(fā)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。
報(bào)告內(nèi)容摘要：
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.
（承辦：管理工程系、科研與學(xué)術(shù)交流中心）
