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Data neutrality and market competition (2021)

October 11, 2021


  • Hanming Fang, Professor of Economics, University of Pennsylvania
  • Soo Jin Kim, Assistant Professor, ShanghaiTech University

This blog article is derived from the authors’ paper titled Data Neutrality and Market Competition, a project of the Economics of Digital Services (EODS) research initiative led by Penn’s Center for Technology, Innovation and Competition (CTIC) and The Warren Center for Network & Data Services. CTIC and The Warren Center are grateful to the John S. and James L. Knight Foundation for its generous support of the EODS initiative.


Internet platforms such as social media and e-commerce websites serve as data intermediaries. They often provide free services to users but monetize the personal data collected from their utilization of that free service. The personal data collected by platforms can enable online sellers to learn about potential users’ specific wants or needs, which facilitates targeted advertisements (ads) to increase the match value of the product and the consumer, and all other things being equal, to increase sales.

If the platform, as a data intermediary, is affiliated with a downstream seller, then the affiliated firm may be able to use the extensive platform data for free, while its competitors either must pay higher fees to use the data or be excluded from data use. For example, Amazon started offering in-house products under the label AmazonBasics and achieved great success in a short period of time. A key factor behind the success of AmazonBasics is the huge amount of data Amazon has—using these data, Amazon can effectively target the optimal customer set and direct these customers to its private-label brands.

By focusing on the source of platforms’ market power, i.e., the preferential use of upstream data for the affiliated downstream seller, we examined how flexible and open access to the platform’s data, regardless of vertical affiliation, affects the relevant downstream market competition, the platform’s incentives to produce data, and, ultimately, the consumers’ surplus (a measure of consumers’ well-being from the products they purchase net the prices they pay for the products). Specifically, we introduced a new hypothetical regulation called data neutrality.

What is data neutrality?

We define data neutrality as the regulation requiring that the platform treat all firms that want to access and use its data “equally.” We considered two versions of data neutrality regulations: weak data neutrality and strong data neutrality. Under weak data neutrality, the platform is required to make the same quantity of data available for all downstream firms, regardless of whether they are affiliated with the platform, but the platform has much latitude in setting different prices to different downstream sellers, except for the restriction that the price cannot be exorbitant to foreclose a downstream seller from purchasing any data. Under strong data neutrality, the platform is required to offer all downstream firms, regardless of whether they are affiliated with the platform, the same amount of data at the same price.

Findings and conclusion

We found that absent any data neutrality regulation the platform will foreclose the unaffiliated seller from data access and grant the affiliated seller exclusive access. While either data neutrality regulation guaranteed symmetric data acquisition, if the regulation does not regulate data pricing but only requires a symmetric amount of data across downstream sellers, the platform can always bypass the regulation and bar the unaffiliated seller from obtaining data access by charging a price higher than that unaffiliated seller’s maximum willingness to pay. Given that such weak data neutrality may have de facto no impact on the market, we suggest a stricter regulation—strong data neutrality—that requires nondiscriminatory data pricing in addition to symmetric data provision.

But weak and strong data neutrality regulations that create a level playing field for the downstream sellers do not necessarily enhance welfare because the platform reduces the amount of data under the regulations: we showed that the amount of data under no regulation is always greater than that under either type of data neutrality regulations. Because of the data-amount-reducing effects, a data neutrality regulation does not always enhance consumer surplus despite its competition-enhancing effects.

Given these countervailing effects of data neutrality, we identified the conditions under which data neutrality results in greater welfare. We find that data neutrality regulations result in greater data-amount-reducing effects when the initial targeting qualities of the two downstream sellers are less differentiated. Thus, data neutrality regulations are more likely to reduce consumer well-being if the two downstream sellers are more similar in their initial qualities to tailor their product to consumers.