Product Recommendations in E-Commerce Retailing Applications

The book deals with product recommendations generated by information systems referred to as recommender systems. Recommender systems assist consumers in making product choices by providing recommendations of the range of products and services offered in an online purchase environment. The quantitative research study investigates the influence of psychographic and sociodemographic determinants on the interest of consumers in personalized online book recommendations. The author presents new findings regarding the interest in recommendations, importance of product reviews for the decision process, motives for submitting ratings as well as comments, and the delivery of recommendations. The results show that opinion seeking, opinion leading, domain specific innovativeness, online shopping experience, and age are important factors in respect of the interest in personalized recommendations.

Autorentext

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.

Inhalt

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.