Abstract

http://ssrn.com/abstract=1321962
 
 

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


Kartik Hosanagar


University of Pennsylvania - Operations & Information Management Department

Daniel M. Fleder


University of Pennsylvania - The Wharton School

Dokyun Lee


University of Pennsylvania - The Wharton School

Andreas Buja


University of Pennsylvania - Statistics Department

October 2013

NET Institute Working Paper No. 08-44

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.

Number of Pages in PDF File: 33

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

JEL Classification: D83, O3

working papers series


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Date posted: December 31, 2008 ; Last revised: November 27, 2013

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 (October 2013). NET Institute Working Paper No. 08-44. Available at SSRN: http://ssrn.com/abstract=1321962 or http://dx.doi.org/10.2139/ssrn.1321962

Contact Information

Kartik Hosanagar (Contact Author)
University of Pennsylvania - Operations & Information Management Department ( email )
Philadelphia, PA 19104
United States

Daniel M. Fleder
University of Pennsylvania - The Wharton School ( email )
Philadelphia, PA 19104
United States
Dokyun Lee
University of Pennsylvania - The Wharton School ( email )
3733 Spruce Street
Philadelphia, PA 19104-6374
United States

Andreas Buja
University of Pennsylvania - Statistics Department ( email )
Wharton School
Philadelphia, PA 19104
United States

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