Are You Worried About Personalized Service? An Empirical Study of the Personalization-Privacy Paradox

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.