Will the Global Village Fracture Into Tribes? Recommender Systems and Their Effects on Consumer Fragmentation

• 成果类型: Article
• 署名作者: Hosanagar, Kartik; Fleder, Daniel; Lee, Dokyun; Buja, Andreas
• 署名单位: University of Pennsylvania; University of Pennsylvania
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2013.1808
• 发表日期: 2014
• 页码: 805-823
• 关键词: information systems; electronic commerce; Recommendation systems; collaborative filtering; filter bubble

摘要

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.