激励
互联网隐私
信息隐私
竞赛(生物学)
消费者隐私
隐私政策
业务
设计隐私
隐私软件
计算机科学
价值(数学)
计算机安全
个人可识别信息
隐私保护
微观经济学
经济
生物
机器学习
生态学
标识
DOI:10.1145/3391403.3399493
摘要
I study a dynamic model of consumer privacy and platform data collection. In each period, consumers choose their level of platform activity. Greater activity generates more precise information about the consumer, thereby increasing platform profits. Although consumers value privacy, a platform is able to collect much information by gradually lowering the level of privacy protection. In the long-run, consumers become "addicted" to the platform, whereby they lose privacy and receive low payoffs, but continue to choose high activity levels. Competition is unhelpful because consumers have a higher incentive to use a platform to which they have lower privacy.
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