The Author: Nicolas Knotzer studied business administration with the focus on information systems, management control and project management. From 2001 to 2006 he joined the Institute for Management Information Systems at the Vienna University of Economics and Business Administration. The author received his doctoral degree in 2006.

• Contents: Classification and application models of recommender systems – Business goals – The consumer decision process – Virtual communities and network effects – Consumer-generated content (product reviews) – Functional aspects of recommender systems – Design aspects – Personalized and non-personalized recommendation methods – Research model and hypothesis – Influence of psychographic and sociodemographic determinants on the interest in personalized recommendations.

The Author: Nicolas Knotzer studied business administration with the focus on information systems, management control and project management. From 2001 to 2006 he joined the Institute for Management Information Systems at the Vienna University of Economics and Business Administration. The author received his doctoral degree in 2006.

• Contents: Classification and application models of recommender systems – Business goals – The consumer decision process – Virtual communities and network effects – Consumer-generated content (product reviews) – Functional aspects of recommender systems – Design aspects – Personalized and non-personalized recommendation methods – Research model and hypothesis – Influence of psychographic and sociodemographic determinants on the interest in personalized recommendations.

The Author: Nicolas Knotzer studied business administration with the focus on information systems, management control and project management. From 2001 to 2006 he joined the Institute for Management Information Systems at the Vienna University of Economics and Business Administration. The author received his doctoral degree in 2006.

• Contents: Classification and application models of recommender systems – Business goals – The consumer decision process – Virtual communities and network effects – Consumer-generated content (product reviews) – Functional aspects of recommender systems – Design aspects – Personalized and non-personalized recommendation methods – Research model and hypothesis – Influence of psychographic and sociodemographic determinants on the interest in personalized recommendations.