Online serendipity: The case for curated recommender systems

When used effectively, recommender systems provide users with suggestions based on their own preferences. These systems first showed their value with e-commerce sites like Amazon and eBay, which provided recommendations algorithmically. A key drawback of these systems is that some items need persona...

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Bibliographic Details
Published inBusiness horizons Vol. 60; no. 5; pp. 613 - 620
Main Authors Kim, Henry M., Ghiasi, Bita, Spear, Max, Laskowski, Marek, Li, Jiye
Format Journal Article
LanguageEnglish
Published Elsevier Inc 01.09.2017
Subjects
Curated recommender systems
E-business
E-commerce strategy
Online retail
Recommender systems
E-commerce strategy
Online retail
Curated recommender systems
Recommender systems
E-business
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Summary:When used effectively, recommender systems provide users with suggestions based on their own preferences. These systems first showed their value with e-commerce sites like Amazon and eBay, which provided recommendations algorithmically. A key drawback of these systems is that some items need personal touch recommendations to spur on purchase, use, or consumption. A recommender system that facilitates personal touch recommendations by enabling users to discover good recommenders as opposed to focusing on recommending items algorithmically addresses this drawback. In this article, we discuss such a system—a curated recommender system. A curated recommender system is optimal for online retailers and service providers, especially those that sell books, stream content, or provide social networking platforms.
ISSN:0007-6813
1873-6068
DOI:10.1016/j.bushor.2017.05.005