Researchers examined the role and economic impacts of recommender systems, and how they affect consumers’ decisions.
These recommender systems are used in retail, entertainment, social networking and more. In a recently published study, two researchers from The University of Texas at Dallas investigated the informative role of these systems and the economic impacts on competing sellers and consumers.
«Recommender systems have become ubiquitous in e-commerce platforms and are touted as sales-support tools that help consumers find their preferred or desired product among the vast variety of products,» said Dr. Jianqing Chen, professor of information systems in the Naveen Jindal School of Management. «So far, most of the research has been focused on the technical side of recommender systems, while the research on the economic implications for sellers is limited.»
In the study, published in the December 2020 issue of MIS Quarterly, Chen and Dr. Srinivasan Raghunathan, the Ashbel Smith Professor of information systems, developed an analytical model in which sellers sell their products through a common electronic marketplace.
The paper focuses on the informative role of the recommender system: how it affects consumers’ decisions by informing them about products about which they otherwise may be unaware. Recommender systems seem attractive to sellers because they do not have to pay the marketplace for receiving recommendations, while traditional advertising is costly.
The researchers note that recommender systems have been reported to increase sales on these marketplaces: More than 35% of what consumers purchase on Amazon and more than 60% of what they watch on Netflix result from recommendations. The systems use information including purchase history, search behavior, demographics and product ratings to predict a user’s preferences and recommend the product the consumer is most likely to buy.
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Materials provided by University of Texas at Dallas. Original written by Brittany Magelssen. Note: Content may be edited for style and length.