The database is organized into five categories—platform competition, the role of apps and complements on the platform, behavioral biases and competition, the role of data on competition, and potential competition—with an additional section that samples the law-related literature on these topics. We encourage readers to browse the entire literature review as some papers may fall into more than one category. As researchers and competition authorities continue to learn about competition among digital platforms, we invite readers to nominate new papers to the database, as well as important contributions we have missed. Please email

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Illustrations below by Michelle Fang

Platform Competition

Digital platforms operate in multi-sided markets with network effects. In the case of an ad-supported social media platform, users want to join a platform that other users are a part of. On the other side, advertisers want to advertise on a platform with many users. Participants in the digital economy may also substitute between platforms or “multi-home.” This section examines how features such as network effects and multi-homing affect competition and welfare in digital markets. For example, the presence of multi-homing may influence a platform’s decision about content or pricing, which could leave one side of the platform better off at the expense of the other. This section also examines the characteristics and effects of mergers in digital markets and tools for merger analysis that incorporate network effects and the multi-sided nature of digital platforms

From Mad Men to Maths Men: Concentration and Buyer Power in Online Advertising

By: Francesco Decarolis and Gabriele Rovigatti. For search engine giants like Google, advertising is their primary source of profits. This paper explores what happens to these profits when advertisers let intermediary companies bid in ad auctions on their behalf. The authors discuss strategies that intermediaries employ to distort and coordinate bids. Using a novel market definition and approach to analyzing intermediary concentration, the authors show that intermediaries may be powerful countervailing forces against Google’s market dominance.

The Role of Complements and Apps on the Platform

Digital platforms may be intermediaries between end users and complements on the platform. For example, an online marketplace connects buyers to an array of sellers and a search engine connects users to publisher content. When an intermediary faces competition from a complement on its own platform (e.g. a marketplace competes with sellers to sell products) or a vertically integrated complement faces competition from another complement (e.g. a search engine integrated with a publisher competes with other publishers to sell ad space), the platform may foreclose a complement that poses a competitive threat. This section examines the incentives for platforms to engage in tying, bundling, vertical integration, and other behavior that leverages market power and forecloses competition from complements.

Integration and Search Engine Bias

By: Alexandre de Cornière and Greg Taylor. How does integration between a dominant search engine and a publisher affect a search engine’s incentives to bias towards its own content? In addition, how does integration affect the quantity of ads on an integrated publisher’s site? In this paper, the authors develop a theoretical model to demonstrate the effects of no integration, partial integration, and full integration on search engine bias and quantity of publisher ads. The model also sheds lights on user and advertiser welfare after integration.

Behavioral Biases and Competition

Research in the behavioral sciences reveals that consumers do not always behave as rational agents. In the context of digital platforms, there is evidence that consumers favor salient search results, have limited attention, and skim through long privacy disclosures, even when they value privacy. Platforms that are aware of these consumer biases may be incentivized to design platform environments or structure privacy disclosures in a way that harms consumers but benefits the platform itself. This section examines platform decisions about design and content given consumers’ behavioral biases and the implications for market power and quality of content experienced by consumers.

Price Salience and Product Choice

By: Thomas Blake, Sarah Moshary, Kane Sweeney, and Steven Tadelis. How does price salience, or when fees are listed more clearly upfront, affect the quantity and quality of the product purchased? In this paper, the authors use a dataset from the online ticketing platform StubHub to show the effects of hiding buyer fees until the checkout page on consumer decisions for product choice, total revenue, and possible forces that might influence salience.

The Role of Data on Competition

In the digital economy, access to user-specific data is a key source of market power. This section examines the value of data for advertising, network effects, and barriers to entry. In addition, user-specific data affects the quality of content experienced by consumers. Many products and services are offered free of charge, which means that anticompetitive conduct results in harms to quality (e.g. biased search results) rather than prices. In markets with non-zero prices, consumers may experience lower quality and higher prices. For example, online retailers may price discriminate based on data profiles of consumers. Data is also the key input for machine learning models used to choose prices and direct users to content, though there is evidence that these algorithms are susceptible to discriminatory and collusive behavior.

The Economics of Social Data

By: Dirk Bergemann, Alessandro Bonatti, and Tan Gan. Big tech companies like Google, Amazon, and Facebook have amassed an unprecedented collection of individual data. The authors demonstrate why data ownership is insufficient to give consumers control over their data and how individual data is actually social data due to data externalities. The paper explores the effects of collecting individual data, terms of trade between consumers and digital platforms, the social dimension of data, and how data intermediaries change the level of aggregation and precision of information they provide. The authors find that the revenue-maximizing data policy is to collect consumer data but not forward it to producers.

Peaches, Lemons, and Cookies: Designing Auction Markets with Dispersed Information

By: Ittai Abraham, Susan Athey, Moshe Babaioff, and Michael D. Grubb. This paper explores the relationship between two ubiquitous phenomena in the digital economy: online ad auctions and tracking cookies. The authors assess what happens to ad auction revenue when competing advertisers receive different kinds of information from their cookies. They find that the revenue to ad sellers like Google and Facebook changes dramatically based on ad auction structure and on the quantity and quality of information available to advertisers.

The Limits of Price Discrimination

By: Dirk Bergemann, Benjamin Brooks, and Stephen Morris. The more information a monopolist seller has about consumer preferences, the more power it has to price selectively and maximize profits. This paper analyzes the welfare consequences of price discrimination via market segmentation. The authors use formal mathematical arguments to show that a market can be segmented to produce all feasible surplus combinations. They conclude that consumer welfare can be prioritized through the proper structuring of information transmission and data collection.

Artificial Intelligence, Algorithmic Pricing, and Collusion

By: Emilio Calvano, Giacomo Calzolari, Vincenzo Denicolo, and Sergio Pastorello. Firms are increasingly turning to artificial intelligence to analyze marketplace trends and determine pricing strategies. This paper demonstrates how AI pricing algorithms may actually learn, with no human instruction, to set anti-competitive prices under standard economic conditions. The authors’ findings highlight the need for antitrust reform that recognizes the potential for algorithms to autonomously collude.

Potential Competition

Competitive markets have relatively low barriers to entry. In digital markets where only a few platforms have access to large amounts of data and are strong incumbents, potential competitors face high barriers to entry. Even if firms manage to enter, incumbent platforms may threaten to foreclose competitors or buy up competition through mergers and acquisitions. Competitive markets also incentivize innovation such as venture capital investment and R&D. When markets are highly concentrated, investors may be hesitant to invest in potential competitors and incumbents may free ride on R&D efforts by acquiring nascent competitors. However, though the dominance of incumbent platforms may harm innovation, empirical studies show that these platforms have raised consumer surplus and introduced disruptive innovations in established markets such as hotel bookings. This section examines how incumbency advantage affects entry and tools to identify innovation harms in digital markets.

Cost of Experimentation and the Evolution of Venture Capital

By: Michael Ewens, Ramana Nanda, and Matthew Rhodes-Kropf. Following the advent of Amazon Web Services (AWS) in 2006, the cost of starting a new business substantially decreased, leading venture capital firms to adapt their investment approach. The authors analyze why investors are increasingly adopting the “spray and pray” investment approach in early stages, provide limited governance, and prefer businesses where the future potential is revealed quickly and cheaply. Additionally, they use the technological shock of AWS to explain the rise of new financial intermediaries such as accelerators.

Legal Papers

This section contains a small list of papers related to the topics above, as a sample of the law-related literature on digital platform enforcement.