论文标题
在线平台何时支付数据股息
When would online platforms pay data dividends
论文作者
论文摘要
包括社交媒体和搜索平台在内的在线平台通常将其用户的数据用于有针对性的广告，改善其服务，并卖给第三方买家。但是，人们对用户数据隐私的重要性的越来越多的意识导致了新的法律，该法律通过平台来调节数据共享。此外，关于引入数据股息的政治讨论，即向用户支付其数据。那是三个有趣的问题：什么时候激励这些在线平台支付数据股息？他们的决定如何取决于用户是否比平台的免费服务重视隐私？平台应该投资于保护用户数据吗？本文考虑了通过实用程序功能影响用户和平台决策的各种因素。我们使用Stackelberg游戏来构建主要代理模型，以计算其最佳决策并定性地讨论含义。我们的结果可能会为一项试图理解强制数据股息的后果的决策制定者提供信息。
Online platforms, including social media and search platforms, have routinely used their users' data for targeted ads, to improve their services, and to sell to third-party buyers. But an increasing awareness of the importance of users' data privacy has led to new laws that regulate data-sharing by platforms. Further, there have been political discussions on introducing data dividends, that is paying users for their data. Three interesting questions are then: When would these online platforms be incentivized to pay data dividends? How does their decision depend on whether users value their privacy more than the platform's free services? And should platforms invest in protecting users' data? This paper considers various factors affecting the users' and platform's decisions through utility functions. We construct a principal-agent model using a Stackelberg game to calculate their optimal decisions and qualitatively discuss the implications. Our results could inform a policymaker trying to understand the consequences of mandating data dividends.
