Recommender systems in the offline retailing domain: A systematic literature review

Abstract

Recommender systems have over the years proved to be effective in overcoming the challenges related to the incredible growth of the information on the Web, and nowadays they are evidently popular in a variety of apparently disparate domains, e.g., e-commerce, tourism and healthcare. Nonetheless, no Systematic Literature Review (SLR), and even no literature survey, aimed at analyzing the current state of academic and industrial research knowledge on recommender systems for the offline retailing domain is reported in the literature. There is, therefore, a need for conducting a SLR that allows revealing the trends and challenges in the research and development of recommender systems for that domain. In this chapter, we present the details about the planning, execution and analysis of results of a SLR of the state of the art of recommender systems for the offline retailing domain. The findings of the analysis of results shed light, among other things, on the necessity of further research on recommendation systems and algorithms for the offline retailing domain, specially, for small local stores and chain stores in the categories of department stores, drugstores and convenience stores.