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.

National Science Foundation (NSF)
Division of Social and Economic Sciences (SES)
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Nancy Lutz
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University of Virginia
United States
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