Will the Global Village Fracture Into Tribes? Recommender Systems and Their Effects on Consumer Fragmentation
Kartik Hosanagar (),
Daniel Fleder (),
Dokyun Lee () and
Andreas Buja ()
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Kartik Hosanagar: Operations and Information Management, The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104
Daniel Fleder: Operations and Information Management, The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104
Dokyun Lee: Operations and Information Management, The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104
Andreas Buja: Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104
Management Science, 2014, vol. 60, issue 4, 805-823
Abstract:
Personalization is becoming ubiquitous on the World Wide Web. Such systems use statistical techniques to infer a customer's preferences and recommend content best suited to him (e.g., “Customers who liked this also liked...”). A debate has emerged as to whether personalization has drawbacks. By making the Web hyperspecific to our interests, does it fragment Internet users, reducing shared experiences and narrowing media consumption? We study whether personalization is in fact fragmenting the online population. Surprisingly, it does not appear to do so in our study. Personalization appears to be a tool that helps users widen their interests, which in turn creates commonality with others. This increase in commonality occurs for two reasons, which we term volume and product-mix effects. The volume effect is that consumers simply consume more after personalized recommendations, increasing the chance of having more items in common. The product-mix effect is that, conditional on volume, consumers buy a more similar mix of products after recommendations. This paper was accepted by Sandra Slaughter, information systems.
Keywords: information systems; electronic commerce; recommendation systems; collaborative filtering; filter bubble (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (38)
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