Impact of Recommendations on Advertising-Based Revenue Models

机译：建议对基于广告的收入模型的影响

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Online content providers need a loyal user base tor achieving a profitable revenue stream. Large number of visits and long clickstreams are essential for business models based on online advertising. In e-commerce settings, personalized recommendations have already been extensively researched on their effect on both user behavior and related economic performance indicators. We transfer this evaluation into the online content realm and show that recommender systems exhibit a positive impact for online content provider as well. Our research hypotheses emphasize on those components of an advertising-based revenue stream, which are manipulable by personalized recommendations. Based on a rich data set from a regional German newspaper the hypotheses are tested and conclusions are derived.

机译：在线内容提供商需要忠实的用户群来实现可观的收入流。大量访问和长点击流对于基于在线广告的业务模型至关重要。在电子商务环境中，个性化推荐对用户行为和相关经济绩效指标的影响已得到广泛研究。我们将此评估转移到在线内容领域，并显示推荐系统也对在线内容提供商产生了积极影响。我们的研究假设强调基于广告的收入流中的那些组成部分，这些组成部分可以通过个性化推荐进行操作。基于德国一家地区性报纸的丰富数据集，检验了假设并得出了结论。

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来源
《E-Life: web-enabled convergence of commerce, work, and social life》|2011年|p.110-118|共9页
会议地点 Shanghai(CN);Shanghai(CN)
作者
Philipp Bodenbenner; Markus Hedwig; Dirk Neumann;
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作者单位

University of Freiburg, Germany;

University of Freiburg, Germany;

University of Freiburg, Germany;

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会议组织
原文格式 PDF
正文语种 eng
中图分类电子贸易、网上贸易;
关键词
E-business; information economics; business model; digital goods; recommendation agent; online customer loyalty; empirical research/study; web metrics;

机译：电子商务；信息经济学；商业模式;数字商品;推荐代理;在线客户忠诚度；实证研究/研究；网络指标;

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Impact of Recommendations on Advertising-Based Revenue Models

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