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The practice of so-called “self-preferencing” has come to embody the zeitgeist of competition policy for digital markets, as legislative initiatives are undertaken in jurisdictions around the world that to seek, in various ways, to constrain large digital platforms from granting favorable treatment to their own goods and services. The core concern cited by policymakers is that gatekeepers may abuse their dual role—as both an intermediary and a trader operating on the platform—to pursue a strategy of biased intermediation that entrenches their power in core markets (defensive leveraging) and extends it to associated markets (offensive leveraging).

In addition to active interventions by lawmakers, self-preferencing has also emerged as a new theory of harm before European courts and antitrust authorities. Should antitrust enforcers be allowed to pursue such a theory, they would gain significant leeway to bypass the legal standards and evidentiary burdens traditionally required to prove that a given business practice is anticompetitive. This should be of particular concern, given the broad range of practices and types of exclusionary behavior that could be characterized as self-preferencing—only some of which may, in some specific contexts, include exploitative or anticompetitive elements.

In a new working paper for the International Center for Law & Economics (ICLE), I provide an overview of the relevant traditional antitrust theories of harm, as well as the emerging case law, to analyze whether and to what extent self-preferencing should be considered a new standalone offense under EU competition law. The experience to date in European case law suggests that courts have been able to address platforms’ self-preferencing practices under existing theories of harm, and that it may not be sufficiently novel to constitute a standalone theory of harm.

European Case Law on Self-Preferencing

Practices by digital platforms that might be deemed self-preferencing first garnered significant attention from European competition enforcers with the European Commission’s Google Shopping investigation, which examined whether the search engine’s results pages positioned and displayed its own comparison-shopping service more favorably than the websites of rival comparison-shopping services. According to the Commission’s findings, Google’s conduct fell outside the scope of competition on the merits and could have the effect of extending Google’s dominant position in the national markets for general Internet search into adjacent national markets for comparison-shopping services, in addition to protecting Google’s dominance in its core search market.

Rather than explicitly posit that self-preferencing (a term the Commission did not use) constituted a new theory of harm, the Google Shopping ruling described the conduct as belonging to the well-known category of “leveraging.” The Commission therefore did not need to propagate a new legal test, as it held that the conduct fell under a well-established form of abuse. The case did, however, spur debate over whether the legal tests the Commission did apply effectively imposed on Google a principle of equal treatment of rival comparison-shopping services.

But it should be noted that conduct similar to that alleged in the Google Shopping investigation actually came before the High Court of England and Wales several months earlier, this time in a dispute between Google and Streetmap. At issue in that case was favorable search results Google granted to its own maps, rather than to competing online maps. The UK Court held, however, that the complaint should have been appropriately characterized as an allegation of discrimination; it further found that Google’s conduct did not constitute anticompetitive foreclosure. A similar result was reached in May 2020 by the Amsterdam Court of Appeal in the Funda case.  

Conversely, in June 2021, the French Competition Authority (AdlC) followed the European Commission into investigating Google’s practices in the digital-advertising sector. Like the Commission, the AdlC did not explicitly refer to self-preferencing, instead describing the conduct as “favoring.”

Given this background and the proliferation of approaches taken by courts and enforcers to address similar conduct, there was significant anticipation for the judgment that the European General Court would ultimately render in the appeal of the Google Shopping ruling. While the General Court upheld the Commission’s decision, it framed self-preferencing as a discriminatory abuse. Further, the Court outlined four criteria that differentiated Google’s self-preferencing from competition on the merits.

Specifically, the Court highlighted the “universal vocation” of Google’s search engine—that it is open to all users and designed to index results containing any possible content; the “superdominant” position that Google holds in the market for general Internet search; the high barriers to entry in the market for general search services; and what the Court deemed Google’s “abnormal” conduct—behaving in a way that defied expectations, given a search engine’s business model, and that changed after the company launched its comparison-shopping service.

While the precise contours of what the Court might consider discriminatory abuse aren’t yet clear, the decision’s listed criteria appear to be narrow in scope. This stands at odds with the much broader application of self-preferencing as a standalone abuse, both by the European Commission itself and by some national competition authorities (NCAs).

Indeed, just a few weeks after the General Court’s ruling, the Italian Competition Authority (AGCM) handed down a mammoth fine against Amazon over preferential treatment granted to third-party sellers who use the company’s own logistics and delivery services. Rather than reflecting the qualified set of criteria laid out by the General Court, the Italian decision was clearly inspired by the Commission’s approach in Google Shopping. Where the Commission described self-preferencing as a new form of leveraging abuse, AGCM characterized Amazon’s practices as tying.

Self-preferencing has also been raised as a potential abuse in the context of data and information practices. In November 2020, the European Commission sent Amazon a statement of objections detailing its preliminary view that the company had infringed antitrust rules by making systematic use of non-public business data, gathered from independent retailers who sell on Amazon’s marketplace, to advantage the company’s own retail business. (Amazon responded with a set of commitments currently under review by the Commission.)

Both the Commission and the U.K. Competition and Markets Authority have lodged similar allegations against Facebook over data gathered from advertisers and then used to compete with those advertisers in markets in which Facebook is active, such as classified ads. The Commission’s antitrust proceeding against Apple over its App Store rules likewise highlights concerns that the company may use its platform position to obtain valuable data about the activities and offers of its competitors, while competing developers may be denied access to important customer data.

These enforcement actions brought by NCAs and the Commission appear at odds with the more bounded criteria set out by the General Court in Google Shopping, and raise tremendous uncertainty regarding the scope and definition of the alleged new theory of harm.

Self-Preferencing, Platform Neutrality, and the Limits of Antitrust Law

The growing tendency to invoke self-preferencing as a standalone theory of antitrust harm could serve two significant goals for European competition enforcers. As mentioned earlier, it offers a convenient shortcut that could allow enforcers to skip the legal standards and evidentiary burdens traditionally required to prove anticompetitive behavior. Moreover, it can function, in practice, as a means to impose a neutrality regime on digital gatekeepers, with the aims of both ensuring a level playing field among competitors and neutralizing the potential conflicts of interests implicated by dual-mode intermediation.

The dual roles performed by some platforms continue to fuel the never-ending debate over vertical integration, as well as related concerns that, by giving preferential treatment to its own products and services, an integrated provider may leverage its dominance in one market to related markets. From this perspective, self-preferencing is an inevitable byproduct of the emergence of ecosystems.

However, as the Australian Competition and Consumer Commission has recognized, self-preferencing conduct is “often benign.” Furthermore, the total value generated by an ecosystem depends on the activities of independent complementors. Those activities are not completely under the platform’s control, although the platform is required to establish and maintain the governance structures regulating access to and interactions around that ecosystem.

Given this reality, a complete ban on self-preferencing may call the very existence of ecosystems into question, challenging their design and monetization strategies. Preferential treatment can take many different forms with many different potential effects, all stemming from platforms’ many different business models. This counsels for a differentiated, case-by-case, and effects-based approach to assessing the alleged competitive harms of self-preferencing.

Antitrust law does not impose on platforms a general duty to ensure neutrality by sharing their competitive advantages with rivals. Moreover, possessing a competitive advantage does not automatically equal an anticompetitive effect. As the European Court of Justice recently stated in Servizio Elettrico Nazionale, competition law is not intended to protect the competitive structure of the market, but rather to protect consumer welfare. Accordingly, not every exclusionary effect is detrimental to competition. Distinctions must be drawn between foreclosure and anticompetitive foreclosure, as only the latter may be penalized under antitrust.

We will learn more in the coming weeks about the fate of the proposed American Innovation and Choice Online Act (AICOA), legislation sponsored by Sens. Amy Klobuchar (D-Minn.) and Chuck Grassley (R-Iowa) that would, among other things, prohibit “self-preferencing” by large digital platforms like Google, Amazon, Facebook, Apple, and Microsoft. But while the bill has already been subject to significant scrutiny, a crucially important topic has been absent from that debate: the measure’s likely effect on startup acquisitions. 

Of course, AICOA doesn’t directly restrict startup acquisitions, but the activities it would restrict most certainly do dramatically affect the incentives that drive many startup acquisitions. If a platform is prohibited from engaging in cross-platform integration of acquired technologies, or if it can’t monetize its purchase by prioritizing its own technology, it may lose the motivation to make a purchase in the first place.

This would be a significant loss. As Dirk Auer, Sam Bowman, and I discuss in a recent article in the Missouri Law Review, acquisitions are arguably the most important component in providing vitality to the overall venture ecosystem:  

Startups generally have two methods for achieving liquidity for their shareholders: IPOs or acquisitions. According to the latest data from Orrick and Crunchbase, between 2010 and 2018 there were 21,844 acquisitions of tech startups for a total deal value of $1.193 trillion. By comparison, according to data compiled by Jay R. Ritter, a professor at the University of Florida, there were 331 tech IPOs for a total market capitalization of $649.6 billion over the same period. As venture capitalist Scott Kupor said in his testimony during the FTC’s hearings on “Competition and Consumer Protection in the 21st Century,” “these large players play a significant role as acquirers of venture-backed startup companies, which is an important part of the overall health of the venture ecosystem.”

Moreover, acquisitions by large incumbents are known to provide a crucial channel for liquidity in the venture capital and startup communities: While at one time the source of the “liquidity events” required to yield sufficient returns to fuel venture capital was evenly divided between IPOs and mergers, “[t]oday that math is closer to about 80 percent M&A and about 20 percent IPOs—[with important implications for any] potential actions that [antitrust enforcers] might be considering with respect to the large platform players in this industry.” As investor and serial entrepreneur Leonard Speiser said recently, “if the DOJ starts going after tech companies for making acquisitions, venture investors will be much less likely to invest in new startups, thereby reducing competition in a far more harmful way.” (emphasis added)

Going after self-preferencing may have exactly the same harmful effect on venture investors and competition. 

It’s unclear exactly how the legislation would be applied in any given context (indeed, this uncertainty is one of the most significant problems with the bill, as the ABA Antitrust Section has argued at length). But AICOA is designed, at least in part, to keep large online platforms in their own lanes—to keep them from “leveraging their dominance” to compete against more politically favored competitors in ancillary markets. Indeed, while covered platforms potentially could defend against application of the law by demonstrating that self-preferencing is necessary to “maintain or substantially enhance the core functionality” of the service, no such defense exists for non-core (whatever that means…) functionality, the enhancement of which through self-preferencing is strictly off limits under AICOA.

As I have written (and so have many, many, many, many others), this is terrible policy on its face. But it is also likely to have significant, adverse, indirect consequences for startup acquisitions, given the enormous number of such acquisitions that are outside the covered platforms’ “core functionality.” 

Just take a quick look at a sample of the largest acquisitions made by Apple, Microsoft, Amazon, and Alphabet, for example. (These are screenshots of the first several acquisitions by size drawn from imperfect lists collected by Wikipedia, but for purposes of casual empiricism they are well-suited to give an idea of the diversity of acquisitions at issue):

Apple:

Microsoft:

Amazon:

Alphabet (Google):

Vanishingly few of these acquisitions go to the “core functionalities” of these platforms. Alphabet’s acquisitions, for example, involve (among many other things) cybersecurity; home automation; cloud computing; wearables, smart glasses, and AR hardware; GPS navigation software; communications security; satellite technology; and social gaming. Microsoft’s acquisitions include companies specializing in video games; social networking; software versioning; drawing software; cable television; cybersecurity; employee engagement; and e-commerce. The technologies and applications involved in acquisitions by Apple and Amazon are similarly varied.

Drilling down a bit, consider the companies Alphabet acquired and put to use in the service of Google Maps:

Which, if any, of these companies would Google have purchased if it knew it would be unable to prioritize Maps in its search results? Would Google have invested more than $1 billion in these companies—and likely significantly more in internal R&D to develop Maps—if it had to speculate whether it would be required (or even be able) to prove someday in the future that prioritizing Google Maps results would enhance its core functionality?

What about Xbox? As noted, AICOA’s terms aren’t perfectly clear, so I’m not certain it would apply to Xbox (is Xbox a “website, online or mobile application, operating system, digital assistant, or online service”?). Here are Microsoft’s video-gaming-related purchases:

The vast majority of these (and all of the acquisitions for which Wikipedia has purchase-price information, totaling some $80 billion of investment) involve video games, not the development of hardware or the functionality of the Xbox platform. Would Microsoft have made these investments if it knew it would be prohibited from prioritizing its own games or exclusively using data gleaned through these games to improve its platform? No one can say for certain, but, at the margin, it is absolutely certain that these self-preferencing bills would make such acquisitions less likely.

Perhaps the most obvious—and concerning—example of the problem arises in the context of Google’s Android platform. Google famously gives Android away for free, of course, and makes its operating system significantly open for bespoke use by all comers. In exchange, Google requires that implementers of the Android OS provide some modicum of favoritism to Google’s revenue-generating products, like Search. For all its uncertainty, there is no question that AICOA’s terms would prohibit this self-preferencing. Intentionally or not, it would thus prohibit the way in which Google monetizes Android and thus hopes to recoup some of the—literally—billions of dollars it has invested in the development and maintenance of Android. 

Here are Google’s Android-related acquisitions:

Would Google have bought Android in the first place (to say nothing of subsequent acquisitions and its massive ongoing investment in Android) if it had been foreclosed from adopting its preferred business model to monetize its investment? In the absence of Google bidding for these companies, would they have earned as much from other potential bidders? Would they even have come into existence at all?

Of course, AICOA wouldn’t preclude Google charging device makers for Android and thus raising the price of mobile devices. But that mechanism may not have been sufficient to support Google’s investment in Android, and it would certainly constrain its ability to compete. Even if rules like those proposed by AICOA didn’t undermine Google’s initial purchase of and investment in Android, it is manifestly unclear how forcing Google to adopt a business model that increases consumer prices and constrains its ability to compete head-to-head with Apple’s iOS ecosystem would benefit consumers. (This excellent series of posts—1, 2, 3, 4—by Dirk Auer on the European Commission’s misguided Android decision discusses in detail the significant costs of prohibiting self-preferencing on Android.)

There are innumerable further examples, as well. In all of these cases, it seems clear not only that an AICOA-like regime would diminish competition and reduce consumer welfare across important dimensions, but also that it would impoverish the startup ecosystem more broadly. 

And that may be an even bigger problem. Even if you think, in the abstract, that it would be better for “Big Tech” not to own these startups, there is a real danger that putting that presumption into force would drive down acquisition prices, kill at least some tech-startup exits, and ultimately imperil the initial financing of tech startups. It should go without saying that this would be a troubling outcome. Yet there is no evidence to suggest that AICOA’s proponents have even considered whether the presumed benefits of the bill would be worth this immense cost.