Product Recommendations in E-Commerce Retailing Applications

Abstract

1st, New ed. Thesis (Doctoral). 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. 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.