USE OF INNER-ENTERPRISE INFORMATION RECOMMENDER SYSTEMS AND ITS IMPACTS

Abstract

The rapid development of information technologies (Internet, SNS, user-generated content) has increased the speed of information overload. The Information Recommender Systems (IRS) that are automated information filtering systems seem to be the remedies to address this problem. Many organizations have adopted the Information Recommender Systems in order to streamline users’ information search efforts and enhance their productivity. While researchers have been addressing the filtering algorithm accuracy problem and the recommender systems’ design features mainly in the Internet and ecommerce recommender systems field , studies addressing the revisit (reuse ) of the information recommender system within an organization are still very scarce. Therefore , this study attempted to establish a new model and find out how the IRS related capabilities influence an employee’s behavior or tendency to reuse the system . Capabilities such as information sources accessibility, user’s preference capture, and notification were investigated. Data was gathered from 205 employees of Korean companies. Based on the framework that mainly uses the IS success model and the IT post adoption literature, a structural equation modeling approach was used to test the relationships between variables. The results show a similar influence of each capability with the notification much more powerful. And the revisit intension was directly influenced only by the user’s satisfaction while the benefits have no direct impact on the revisit intension. Theoretical and practical implications are discussed.