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Will the Global Village Fracture into Tribes: Recommender Systems and Their Effects on Consumers

Management Science, Vol. 60, No. 4, pp. 805-823, April 2014

33 Pages Posted: 31 Dec 2008 Last revised: 5 Aug 2015

Kartik Hosanagar

University of Pennsylvania - Operations & Information Management Department

Daniel M. Fleder

University of Pennsylvania - The Wharton School

Dokyun Lee

Carnegie Mellon University - David A. Tepper School of Business

Andreas Buja

University of Pennsylvania - Statistics Department

Date Written: April 1, 2014

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 hyper-specific 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.

Keywords: recommender systems, collaborative filtering, fragmentation, personalization, long tail

JEL Classification: D83, O3

Suggested Citation

Hosanagar, Kartik and Fleder, Daniel M. and Lee, Dokyun and Buja, Andreas, Will the Global Village Fracture into Tribes: Recommender Systems and Their Effects on Consumers (April 1, 2014). Management Science, Vol. 60, No. 4, pp. 805-823, April 2014. Available at SSRN: https://ssrn.com/abstract=1321962 or http://dx.doi.org/10.2139/ssrn.1321962

Kartik Hosanagar (Contact Author)

University of Pennsylvania - Operations & Information Management Department ( email )

Philadelphia, PA 19104
United States

Daniel Fleder

University of Pennsylvania - The Wharton School ( email )

Philadelphia, PA 19104
United States

Dokyun Lee

Carnegie Mellon University - David A. Tepper School of Business ( email )

5000 Forbes Avenue
Pittsburgh, PA 15213-3890
United States

Andreas Buja

University of Pennsylvania - Statistics Department ( email )

Wharton School
Philadelphia, PA 19104
United States

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