Collaborative Research: Targeting Privacy

合作研究：针对隐私

• 批准号: 1919493
• 负责人: Simon Anderson
• 金额: $ 16.1万
• 依托单位: University of Virginia Main Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1919493&HistoricalAwards=false
• 关键词: Collaborative; Research; Targeting; Privacy

The project will advance three crucial themes on markets for targeted advertising and consumer privacy. The first will address whether consumers benefit or are harmed when a firm they do business with can sell their data on to other firms they might deal with. It will study whether giving individuals the right to opt out of such data sales is an effective means of protecting consumer interests. The second theme will study the consequences of giving consumers ownership over their own data with the right to sell it themselves, if they choose. The third theme will study whether the increasing precision of targeted advertising leads to excessively specialized choices for consumers in media markets supported by advertising. Regulators including the US Congress and the European Union (with the adoption of the General Data Privacy Regulation) have underscored the urgent need to understand these issues to draft appropriate policies to protect consumers and their data without stifling innovative business practices. The project will provide guidance on the merits of policies that restrict targeting, give consumers opt-out rights, and give consumers the right to sell their own data. The project will be primarily theoretical in its methodology, although the themes are inspired from actual current (and expanding) practices and policy debates. The first part will innovate a joint equilibrium analysis of the market where data is harvested and the market where it is deployed. The analysis will begin with a monopoly information-harvesting firm collecting data from its market to sell it on to firms in a second market. While the first firm will want to render its market attractive to consumers (through low prices, say), consumers are wary about participating, for they will rationally anticipate that their data might be used against them (in the form of high prices, say) in the secondary market. Data-sharing may benefit consumers because markets where data are used operate more efficiently and consumers can command part of this gain by exacting discounts in the first market. Perversely, letting individual consumers choose whether to opt out of data sharing may hurt them collectively, as consumers with "something to hide" are penalized with higher prices. This is a stepping stone for analyzing competition in data collection and how data harvesters parcel out data for sale. The second part will examine who should be able to sell consumer data. It will compare when firms collect and sell on the data with when consumers can sell their own data. When data are used to craft discount offers, consumers may engineer greater discount competition by pricing their data below the cost of lost privacy. Individuals eager to be targeted might inflict negative externalities on others who are revealed to have strong product preferences and may face higher prices. Equilibrium consequences of consumer pricing have not been previously addressed and are quite intricate. Furthermore, firms should anticipate that consumers may strategically manipulate the information they sell on. This analysis will be a springboard for studying how savvy consumers will make the most of their data by selectively curating what they sell into one or more digital personas. The third part will draw on different modeling approaches of product differentiation and will meld these to an advertising-financed business model of media economics. Advertisers and content consumers (who are prospective consumers of the advertised goods) constitute the two sides of the market, and they are intermediated by media platforms which choose advertising prices (and consumer subscription fees when relevant). Competing platforms connect advertisers with viewers: a platform's content is most appealing to viewers with "nearby" tastes, and the bundle of viewers at a platform is most attractive to "nearby" advertisers. Before internet-enabled tracking and targeting, bucketing of advertisers to consumers was crudely enabled through specialized media content. Now that individuals are tracked and targeted, market performance might be enhanced through better matching but worsened through too many platforms. Advertisers with broad appeal may crowd out narrow ones under the old business model, and foster insufficiently few specialized, but the new business model may go too far in the other direction. These topics have not been broached in media economics.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目将推进定向广告和消费者隐私市场的三个关键主题。第一个问题是，当与消费者有业务往来的公司将他们的数据出售给他们可能打交道的其他公司时，消费者是受益还是受损。它将研究赋予个人选择不参与此类数据销售的权利是否是保护消费者利益的有效手段。第二个主题将研究让消费者拥有自己数据的所有权，并有权自行出售数据（如果他们愿意的话）的后果。第三个主题将研究定向广告精确度的提高是否会导致广告支持的媒体市场中消费者的选择过于专业化。包括美国国会和欧盟在内的监管机构（通过了《通用数据隐私条例》）强调，迫切需要了解这些问题，以便起草适当的政策，在不扼杀创新商业实践的情况下保护消费者及其数据。该项目将为限制目标定位、赋予消费者选择退出权以及赋予消费者出售自己数据的权利等政策的优点提供指导。该项目的方法论将主要是理论性的，尽管其主题受到当前（和不断扩大的）实际实践和政策辩论的启发。第一部分将创新一个联合均衡分析的市场，其中数据的收获和市场部署。分析将从垄断信息收集公司从其市场收集数据并将其出售给第二市场的公司开始。虽然第一家公司想要让它的市场对消费者有吸引力（比如通过低价），但消费者对参与持谨慎态度，因为他们会理性地预测，他们的数据可能会在二级市场上被用来对付他们（比如以高价的形式）。数据共享可能使消费者受益，因为使用数据的市场运作效率更高，消费者可以通过在第一个市场要求折扣来获得部分收益。相反，让个人消费者选择是否退出数据共享可能会损害他们的整体利益，因为“有些事情要隐瞒”的消费者会受到更高价格的惩罚。这是分析数据收集竞争以及数据收集者如何出售数据的垫脚石。第二部分将审查谁应该能够出售消费者数据。它将比较公司收集和出售数据的时间与消费者可以出售自己数据的时间。当数据被用于制定折扣优惠时，消费者可能会通过将其数据定价低于失去隐私的成本来制造更大的折扣竞争。渴望成为目标的个人可能会对其他被发现有强烈产品偏好并可能面临更高价格的人造成负面外部性。消费者定价的均衡后果以前没有被讨论过，而且相当复杂。此外，公司应该预料到消费者可能会战略性地操纵他们所销售的信息。这种分析将成为研究精明的消费者如何通过有选择地向一个或多个数字角色出售商品来充分利用他们的数据的跳板。第三部分将借鉴不同的产品差异化建模方法，并将这些方法融合到媒体经济学的广告融资商业模式中。广告主和内容消费者（即广告商品的潜在消费者）构成了市场的两个方面，他们是媒介平台的中介，媒介平台选择广告价格（以及相关的消费者订阅费）。竞争平台将广告商与观众联系起来：一个平台的内容对“附近”口味的观众最具吸引力，而一个平台上的观众群对“附近”的广告商最具吸引力。在互联网启用跟踪和定位之前，广告商对消费者的拦截是通过专门的媒体内容来实现的。现在，个人被跟踪和定位，市场表现可能会通过更好的匹配而提高，但由于平台太多而恶化。在旧的商业模式下，具有广泛吸引力的广告商可能会挤掉那些狭窄的广告商，并培养出足够少的专业广告商，但新的商业模式可能会在另一个方向上走得太远。这些话题在媒体经济学中还没有被提及。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Decoupling the Ces Distribution Circle with Quality and Beyond: Equilibrium Distributions and the Ces-Logit Nexus

• DOI: 10.1093/ej/ueaa001
• 发表时间: 2019-12
• 期刊: CEPR Discussion Paper Series
• 作者: Simon P. Anderson;A. de Palma

Aggregative games and oligopoly theory: short‐run and long‐run analysis

聚合博弈和寡头垄断理论：短期和长期分析

• DOI: 10.1111/1756-2171.12322
• 发表时间: 2020
• 期刊: The RAND Journal of Economics
• 作者: Anderson, Simon P.;Erkal, Nisvan;Piccinin, Daniel
• 通讯作者: Piccinin, Daniel

The importance of consumer multi-homing (joint purchases) for market performance: mergers and entry in media markets

消费者多归属（联合购买）对市场表现的重要性：媒体市场的合并和进入

• 发表时间: 2019
• 期刊: Journal of economics and management sciences
• 作者: Anderson, Simon P.;Foros, Oystein;Kind, Hans Jarle
• 通讯作者: Kind, Hans Jarle

Media See-Saws: Winners and Losers in Platform Markets

• DOI: 10.1016/j.jet.2019.104990
• 发表时间: 2017-08
• 期刊: CEPR Discussion Paper Series
• 作者: Simon P. Anderson;M. Peitz

Opaque selling

销售不透明

• DOI: 10.1016/j.infoecopol.2020.100869
• 发表时间: 2020
• 期刊: Information Economics and Policy
• 影响因子: 2.8
• 作者: Anderson, Simon P.;Celik, Levent
• 通讯作者: Celik, Levent