Consumer attitudes toward personalization features and intention to purchase online

In this study, a model of attitude toward personalization and purchase intention is developed to investigate how consumer attitudes and intention to purchase using personalization features are influenced by privacy and security concerns and by previous online purchase experiences. The behavioral intention model (Fishbein, 197 5) has been adopted for theoretical model building. To collect data, an e-mail survey was distributed to 7,000 online consumers who had at least online shopping experience and a sample of 1140 usable responses were used for data analysis. The results indicated that 1) attitudes toward personalization features were important determinants of consumer intentions to purchase online, 2) consumer concerns about privacy and security had a significant influence on consumer attitudes toward personalization features, and 3) previous online purchase experience had no influence on consumer attitudes toward personalization features. Implications and directions for future research are discussed

Fenix: personalized information filtering system for www pages

Nowadays the Intemet offers a large amount of infonmation to a wide range of users, making it difficult to deal with. The present work suggests the use of intelligent agents for the personallzed flltering of Web pages. A set of autonomous, non-mobile and adaptive agents was developed, aiming to satisfy the user's need for infonmation. The agents learn from the users' feedback and attempt to produce better preferences results over time. This work presents the system description and the promising results of tests performed in a simulated environment. The proposed system has proven to be a useful tool in reducing the amount of information with which the user has to deal