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

K. Hosanagar, D. Fleder, Dokyun Lee, A. Buja
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引用次数: 12

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.
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地球村是否会分裂成部落:推荐系统及其对消费者的影响
个性化在万维网上变得无处不在。这样的系统使用统计技术来推断客户的偏好,并推荐最适合他的内容(例如,“喜欢这个的客户也喜欢……”)。关于个性化是否有缺点的争论已经出现。通过使网络对我们的兴趣高度专门化,它是否分裂了互联网用户,减少了共享体验并缩小了媒体消费?我们研究的是,个性化是否真的在分化在线人群。令人惊讶的是,在我们的研究中似乎并没有这样做。个性化似乎是一种帮助用户扩大兴趣的工具,这反过来又创造了与其他人的共性。共同性的增加有两个原因,我们称之为数量效应和产品组合效应。数量效应是消费者在个性化推荐后消费更多,增加了拥有更多共同商品的机会。产品组合效应是指,在数量的条件下,消费者在推荐后购买更相似的产品组合。
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