US Leadership in Digital Platform Policy

Johannes M. Bauer
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The cards have changed in digital platform pol­icy. Within a decade, Big Tech companies lost much of their luster as vanguards of the digital trans­formation. There is a sense that Big Tech companies have not met the responsibilities that come with size and ubiquitous presence. Now, the public considers them contributors to fragmentation, polarization, and other social ills that plague the United States and other countries. In a 2021 Gallup survey, 57 percent of Americans felt the government should increase Big Tech regulation.1

Despite concerted efforts and improvements during the Biden administration, technology pol­icy collaboration between the United States and the European Union is tenuous. These sector-specific developments are intertwined with other geopo­litical tensions and stressors, such as changing relations with China. Economic policy measures, such as domestic efforts to combat inflation, are affecting the US position globally. Consequently, after decades during which US high-tech and com­munications policy was viewed with envy, the appeal of the US market-based approach is gradually fading worldwide.

Internationally, the General Data Protection Reg­ulation (GDPR)2 of 2016 and legal cases, such as Schrems I and II,3 sent a strong signal of the willing­ness of EU players to chart their own course of stron­ger privacy protections, with ramifications for the global digital economy. GDPR not only created a dif­ferent regime for EU member states but also is struc­tured in ways that force other countries to adapt to its key provisions.4 The Digital Markets Act (DMA)5 and Digital Services Act6 show a similar resolve in matters of competition policy, innovation policy, and trade policy.

Countries such as Australia, Japan, and South Korea have adopted a stronger pro-regulatory stance. Sim­ilar discussions are emerging among Brazil, Russia, India, and China and a growing number of countries in the global south, where there is rising concern about the negative repercussions of a digital economy dominated by companies from the global north.

That its market-oriented technology policy approach is increasingly met with suspicion or out­right rejection will have implications for the United States’ role in the world and technology ecosystem. The United States has historically relied more than other countries and regions on limited regulation and free trade. That model has generated numerous benefits, but its limitations are showing. Given the difficulties of passing legislation in a divided US Congress, the benefits have not yet resulted in appro­priate adjustments of relevant competition and com­munication laws. Consequently, regulatory agencies, executive orders, state legislatures, and community initiatives have become areas of innovative policy experiments, but they are often second- or third-best instruments without appropriate enabling legislation.

The more interventionist values embraced in GDPR and DMA resonate with countries that historically have relied on stronger state involvement in telecom­munications. Therefore, these countries will likely emulate and imitate such interventionist policies. GDPR had differential effects that likely benefited large players.7 In contrast, DMA and similar initiatives in other countries are designed to target a select set of US companies.

The US position is weakened by its difficulties updating existing legislation and passing new legis­lation governing the digital economy. Alternative approaches in the US that could serve as blueprints for the global discussion are mainly discussed by competition policy and regulatory agencies. Most likely, these policies will be subject to numerous court challenges.

How then should the United States engage to shape global developments in platform policy and regulation? Can it do so effectively, and, if so, how could this be accomplished? The remainder of this report explores these issues and sketches multiple areas for constructive engagement, with an emphasis on US-EU relations.

Shaping Digital Platform Policy

American players, including the US government, pri­vate companies, business associations, civil society, and researchers, have historically influenced plat­form policy via direct and indirect channels. Private companies were a strong driving force contributing to standards development—for example, in wireless communications. In emerging high-tech areas, these companies often set de facto standards as leaders of technology development. Together with government and civil society representatives, private companies also deeply shaped internet governance.

During the past decade, however, a new dynamic emerged as digital platforms began to invest more aggressively in global infrastructures. Companies such as Amazon, Apple, Facebook, Google, and Microsoft have developed data centers, cloud infra­structure, and network facilities. This rapidly grow­ing private internet coexists and coevolves with the public internet.8 It can support the security and quality-of-service differentiation needed by many advanced services better than the public internet can.

The global presence and dominant role of US digital platforms have further altered the geopolit­ical constellation of interests. It had already begun to shift with initiatives by a group of countries that sought to strengthen the role of the International Telecommunication Union (ITU) in internet pol­icy. At the 2012 World Conference on International Telecommunications in Dubai, a majority of nations supported proposals to amend the International Telecommunications Regulations, but a group of more than 80 countries joined the dissent by the United States and effectively invalidated the pro­posed amendments. Even though these tensions were less visible at the 2022 ITU Plenipotentiary Conference in Bucharest, divisions among countries about approaches to internet policy persist.

New tensions and differences in approaches have reappeared. One manifestation is the intense lob­bying efforts by European network operators and the European Telecommunications Network Oper­ators’ Association in Brussels. Ignoring that content is requested by end users and not “caused” by the sender, these players argue that large content provid­ers, such as Amazon, Facebook, Google, and Netflix, should contribute to the cost of infrastructure invest­ment.9 The two main concerns articulated in this context are asymmetric bargaining power between European national players and digital platforms and asymmetric regulatory treatment of network opera­tors and Big Tech companies. The Body of European Regulators for Electronic Communications has reit­erated its positions that such termination charges are unnecessary and undesirable. Nonetheless, European policymakers are expected to start hearings on “fair share” payments in 2023.10

Similar debates and policy demands are emerg­ing in other countries, including Australia, Japan, and South Korea. They have long been in the playbook of countries such as China.11 They are growing in the global south as well, where they are also framed as an effort to mitigate “digital colonialism.”12

The United States can no longer rely on the wide acceptance of the Washington Consensus. Trust in this framing of an efficient approach to economic and technology policy has faltered. Thus, the questions arise of whether the United States should seek more proactively to influence foreign national debates on platform policy and whether it has the credibility to do so.

International relations theory suggests that a coun­try has four principal options available to influence policy choices by others. Such influence can be either accepted voluntarily or imposed involuntarily. More­over, it can rest in policy visions or in practice. The resulting two-by-two matrix includes consensus (voluntary, vision), exemplification (voluntary, prac­tice), hegemony (nonvoluntary, vision), and dom­inance (nonvoluntary, practice). During the past decades, the United States derived strong credibility and leadership in technology policy from consensus and exemplification, and the other modes assumed auxiliary roles.

These two dominant mechanisms have been weakened considerably with the increasingly hostile stance toward digital platforms in the United States and abroad. Several strategies could help the United States regain momentum and influence.

First, the country would gain stature if it clarified the principles that should be applied to platform pol­icy in the United States. Many domestic policymakers are critical of digital platforms, but for vastly dif­ferent economic, political, and ideological reasons.13 Given the political divisions, developing the innova­tive policy frameworks needed may not be possible. However, as a diverse polity, the country is positioned to develop agile and adaptive forms of policy that may work well in the digital economy.

As a second contribution, the United States could help clarify the conditions under which policy inter­ventions are desirable and which instruments are best suited to address a problem. The DMA intro­duced an untested governance model located insti­tutionally between regulation and antitrust policy; other countries are considering similar responses. Much of the current policy debate and many of the proposed remedies are based on static economic models that do not fully capture the interdependen­cies in platform ecosystems. Dynamic frameworks for the design of competition policy toward digi­tal platforms are available but have not been widely embraced by policymakers.14 The United States could advance this cause.

Third, the United States could help shape a forward-looking view of platform governance. The pervasive adoption of digital technologies in all realms of life has changed the global governance dynamics toward a multicentric system. Clear leadership can and must ensure that the centripetal forces outweigh the centrifugal forces, so that such multicentric dif­ferentiation does not result in undesirable, dysfunc­tional fragmentation. This will require acceptance of value and policy differentiation combined with strong efforts to develop a common base of widely shared foundational values and principles.

Sound Principles of Platform Policy

Two-sided and multisided platforms have existed since the late 19th century. They were examined by media economists long before the current surge in interest.15 Digital technology has facilitated new busi­ness models that allow businesses to scale in new ways and accelerate processes of dynamic change. The term “platform” is increasingly used generi­cally, as indicated in the far-ranging discussion about the “platformization”16 of the economy. It obfus­cates the major differences among companies, such as Amazon, Apple, Facebook, Google, Netflix, and diverse other businesses that are commonly classified as platforms.

The management literature groups platforms into transaction platforms, innovation platforms, and hybrid platforms, which combine aspects of the first two.17 Because both types of platforms generate innovations, Steven Wildman refers to the first type as transaction-coordination platforms and the second as technology-coordination platforms.18 Within the first group, one can further distinguish among product-purchase platforms (e.g., Amazon Marketplace and Etsy), service-provision platforms (e.g., Uber and DoorDash), social media platforms (e.g., Facebook and YouTube), and apps-acquisition platforms (e.g., Apple App Store, Google Play, and Aptoide). The first three types pursue specific busi­ness models, whereas the last type orchestrates more sprawling app innovation and business ecosystems.

Sound principles of platform governance must start from the recognition that the system of digital value creation has changed multiple times over the past century. In the 1960s, the historical model of vertically integrated providers of telecommunication services gradually morphed into the horizontal archi­tecture of the early internet. By the late 20th century, with the ubiquitous adoption of Internet Proto­col networking principles, value generation became organized around the horizontally layered model of the internet.

This layered, modular model was highly genera­tive and spawned a tremendous wave of edge inno­vations, such as applications and services, that can be configured via software on the logical “edges” of the internet. Because most of these innovations do not require changes in the hardware of the network infrastructure, they have lower initial costs, which stimulates innovation activity.

However, the internet’s decentralized organization is also related to instances of governance failure. Most notably, the absence of mechanisms to implement protocols across the more than 60,000 autonomous systems created challenges, such as the implementa­tion of reasonable quality-of-service differentiation and information security. In response, digital plat­forms began to organize and manage the space dif­ferently, not least by investing tremendous resources into building a global infrastructure of data centers and high-capacity connectivity. Software-defined net­works and institutional reforms, such as localized spectrum allocations, have further contributed to the emergence of a hybrid network architecture.19

This emerging, matrix-like architecture combines horizontal and vertical aspects (e.g., network virtual­ization and network slicing). The analysis of the eco­nomics of this new value system is bifurcated between experts who rely on traditional industrial organiza­tion and those who value antitrust approaches. From this antitrust perspective, they regularly observe the presence of pervasive market power and domi­nance.20 Management and business strategy scholars often emphasize the concept of agile, yet fragile, busi­ness ecosystems in which even the largest businesses cannot rest on their laurels but need to succeed con­tinuously in the innovation game.21

Both perspectives contribute important insights, but they also have shortcomings. Traditional eco­nomic analysis fails to capture the nonlinear inter­dependencies in platform ecosystems. On the other hand, ecosystem approaches may be overly vague about the conditions under which innovation flour­ishes. To identify those conditions, a better theory of dynamic competition and innovation in digital eco­systems is needed. Such a framework can be created by adapting elements from evolutionary and systemic approaches to innovation.22

From this conceptual vantage point, novelty is a combinatorial process, in which information and knowledge are combined and recombined to form new components, modules, subassemblies, assem­blies, and entire systems that provide new products and services.23 Complementarities between differ­ent players require the coordination of technical and business solutions. In highly modular systems, such coordination is possible with technological inter­faces, such as open and standardized application pro­gramming interfaces (APIs).

Modular innovation is one of the generative engines of the digital era. However, the system’s overall architecture typically enables and constrains modular coordination.24 Thus, the end-to-end archi­tecture of the public internet stimulated edge inno­vations but also imposed limitations on innovation opportunities that could not be realized within that architecture. Architectural innovations that can over­come such limitations are riskier and hence happen less frequently, except when they can be achieved incrementally in a cumulative innovation process.

Platforms orchestrate the major architectural components of digital ecosystems. By reducing the combinatorial complexity of the innovation space for other players, they reduce coordination costs in the system. However, they are subject to potentially ambiguous incentives. If they are not myopic, they will realize the benefits to the innovation ecosystem generated by complementors and grant access to the resources these players need. This might include access to technological features, but often it also includes access to data that the platform has har­vested from across areas of operation.

However, important caveats are in order. First, without further exploration of the dynamics of plat­form competition and innovation, one cannot assume that platforms always behave in non-myopic ways. Dominant platforms may try to extract rents from complementors, or they may restrict access to plat­form resources in the knowledge that such behavior may not unleash competitive responses. Such behav­ior resembles the problem of moral hazard in mar­kets with asymmetric and incomplete information.25

Second, not all participants in platform ecosystems are complementors. Some firms offer services that are full or partial substitutes for services also offered by the platform. This changes platforms’ incentives and may influence the incentives toward complemen­tors that might develop into competitors. A set of prin­ciples would be desirable to address such situations. These problems are not entirely new, because similar vertical industry constellations have existed through­out the history of electronic communications.

Dynamic Competition and Innovation in Platform Ecosystems

Interventions into digital platforms would ideally be based on a dynamic model of competition and innovation. The model of complementary innova­tion offers a conceptual framework to address these matters. Early formulations of this model empha­sized the synergistic interdependence of players. For example, innovation in platform capabilities would expand the innovation opportunities of complementors. In turn, more complementary innovation would boost incentives for platforms to improve their capabilities.26

Information markets often exhibit high concen­tration because of network effects on the supply and demand side and advantages of agglomeration. Dominant platforms may have biased incentives to grant access to the resources complementors need. Because the platform designs the digital architec­ture of the transactions it offers, it has great discre­tion in the market environment in which it operates. Knowing that complementors may have no or few other options, the platform may share a suboptimally low level of resources or may extract a price above a market rate.

Platforms may have incentives to take over poten­tial competitors to reduce the intensity of competi­tion and slow the emergence of future rivals; however, the evidence for this is weak. Although the existence of kill zones (areas in which platforms directly or indirectly eliminate competitors) is widely believed, supporting empirical evidence is often based on a relatively small number of observations.27 In con­trast, venture capitalists and founders believe that takeovers facilitate innovation by either offering opportunities for venture capitalists to realize a return on an initial investment or allowing the plat­form to absorb technologies into its operation. More­over, there is evidence that platform acquisitions stimulate further venture capital investment.28

The economics of innovation permits the expan­sion of this idea. Innovation activities by each player in the complementary innovation system are affected by the accessible technical, economic, and regulatory innovation opportunities; the intensity of contest­ability in the market; the appropriability of innova­tion rents; and other strategic options that a player has available (e.g., an option to wait or innovate incrementally). Similar factors influence innovation by complementors. In addition, the strength of comple­mentarities and the relevance of coordination costs affect the level of innovation activity.29

The available innovation opportunities and the appropriateness of innovation rents are positively related to innovation activities. Contestability is in a nonlinear relationship with the strengths of innova­tion incentives: Both weak and hyper-contestability are associated with lower innovation rates. In between, innovation incentives are strongest, resulting in an inverted U-shaped relationship between contestabil­ity and innovation. Empirical evidence suggests that the specific shape of the relationship is contingent on the sector and the type of innovation (e.g., modular, architectural, incremental, and radical).30

Coordination costs also have ambiguous effects on innovation. They will often reduce the expected profits from an innovation. Thus, platforms that lower coordination costs by, for example, offering standardized, open APIs will typically boost inno­vation. At the same time, high coordination costs may initiate a search for innovative solutions to avoid such costs and hence stimulate innovation. The net effect depends on the relative size of these two forces.

In a similar way, complementarities will have ambiguous effects. Often, innovation incentives will be positively associated with the strengths of com­plementarities (positive spillovers). However, high complementarities could reduce the breadth of inno­vation searches.

Innovation in platform ecosystems, therefore, is the outcome of numerous positive and negative feed­backs that are difficult to analyze. In contrast to the partial equilibrium models currently used in much of regulation and competition policy, analyzing innova­tion in platform ecosystems would require applying a nonequilibrium systems model or at least adopting a general equilibrium framework.

This discussion shows that the ecosystem dynamic could lead to undesirable and inefficient outcomes. Some of these outcomes resemble traditional forms of market failure, but more often they must be analyzed from a broader systemic perspective. This allows the identification of cases of moral hazard, externalities, and public-good situations when the systemic pro­cess of platform coordination reaches suboptimal outcomes. Much is needed to advance a program of research to do this reliably.

Tools to do this, such as computational modeling and simulation models, are available. They are not sufficiently developed, however, to be readily applied to specific cases. An ecosystem perspective of mar­ket failure often leads to more cautious conclusions regarding the effects of market concentration. And it will result in different policy recommendations for remedies that could address forms of market failures in platforms.

For example, almost any regulatory intervention will have differential, positive, and negative effects on relevant stakeholders. Often, the policy design ignores these effects. However, interventions can only achieve their stated goals if these positive and negative feedbacks do not prevent the desired out­come. Information about these feedbacks is often incomplete. To overcome this problem, one option is to design policies that can activate self-healing forces in the ecosystem.

An example of such a design could impose obli­gations on dominant players to engage in good-faith negotiations, backed by mediation by a regulatory agency, combined with a most-favored-nation clause that allows other players to opt for similar condi­tions. Such generic, and often symmetric, general obligations have worked well to govern vertical rela­tions in other market segments, such as wireless communications.

Toward a Multicentric Digital Platform Governance Model

A key insight from dynamic models of ecosystem competition is that, rather than specific forms of (often rigid) ex ante regulation or (often slow) ex post regulation, establishing guardrails for players that support self-healing forces might be a superior approach.31 Guardrails are elements of the “order” or “constitution” of digital markets. They shape play­ers’ behavioral incentives in ways that do not overly constrain their ability to compete dynamically and explore innovation opportunities.

In the present national and global environment, such forms of governance will be multicentric by necessity. That is, they are orchestrated by gov­ernment and nongovernment players that are not necessarily acting in close coordination. Such multi-centricity exists at the national level and will pre­vail, as illustrated by states that have taken legal and regulatory initiatives that affect platforms.32 It also exists and will grow at the international level, where regional and national initiatives foreshadow increas­ing heterogeneity.

This differentiation exists in terms of the actors and agencies that are involved and in terms of the economic principles and values that guide interven­tions. Differentiation may allow the navigation of the policy challenges of digital platforms better than a homogenous system. One could look at a number of diverse policy models as natural experiments that facilitate insights about how social, technical, eco­nomic, and cultural forces interact. If properly exam­ined, this will allow dynamic policy learning and the emulation of successful approaches.

There are downsides to such diversity among models. The biggest risk is that diversity turns into the fragmentation that is associated with increased coordination costs. Given the negative effects of escalating coordination costs on how platform eco­systems work, there is a need for strong efforts to agree on common-ground rules both domestically and internationally. Within an integrative framework of common principles, differentiation can actually improve the ecosystem’s performance.

Research on the governance of common-pool resources shows that polycentric solutions to the management of such resources are often effective. These may include natural resources such as forests, water resources, and fisheries; broader environmen­tal conditions, such the global climate; or created resources, such as knowledge commons.33 We know the most about how various economic interventions into such systems affect outcomes.

As the discussion in the previous section explained, the dynamic and interdependent nature of platform ecosystems suggests that instruments that constitute guardrails are particularly promising. Differentiation in technical, economic, and organizational dimen­sions can best serve the heterogeneity of services and the diversity of user needs in platform ecosystems. Policymakers need to ask whether the different posi­tions held by players, typically with differential market power, impede the working of the innovation ecosys­tem and whether policies can improve outcomes.

The question of how to prevent large players with a high market share in one or more segments of the innovation system from sabotaging or disadvantaging other players has attracted considerable attention. Here, it is necessary to differentiate three scenar­ios. If the players offer complementary services, the above analyses apply. Another scenario is one in which a large player controls resources needed by a competitor who relies on access to their resources. Here, the risk of manipulation of competition is real. Another, third scenario is a situation in which large players are trying to extract supernormal rents from complementors.

In all of these cases, however, it is possible to design policy principles (“guardrails”) that allow the ecosystem players to coordinate in workable ways. Dis­cretionary, specific regulatory interventions are less advisable than general rules that delineate acceptable and unacceptable behaviors. For example, a general obligation to negotiate in good faith combined with transparency and most-favored-nation provisions can mitigate the exclusion of competitors.

Similar general rules could address concerns about the extraction of supernormal rents from complementors and overly restrictive conditions to join a platform.34 Such rules would ideally apply generically and symmetrically to all players, unlike the approach embedded in the European DMA, which singles out specific players. In addition to such guardrails, a multicentric governance model would also recognize the benefits of institutional diversity for innovation.

As discussed, innovation is a directed, evolution­ary search process—an entrepreneurial exploration of new processes, products, services, business mod­els, and designs. The knowledge, skills, and economic and regulatory incentives under which specific inno­vators operate will narrow their search to a specific segment of the vast, digital, innovation-opportunities space. From a societal perspective, it is therefore desirable to explore multiple directions simultane­ously, because it is not known a priori which search strategies will reveal the most promising innovations.

Workable competition among innovators is one mechanism to promote such searching. There is rea­son to believe, however, that players with commercial incentives will not explore all directions that might yield societally beneficial novelty—and if they do find such an opportunity, they may not realize it as part of their operations. This suggests that it would be a use­ful meta-strategy to support diversity of innovation in the private sector, public-private partnerships, the public sector, and the nonprofit sector. Moreover, it would be useful to facilitate collaboration and knowledge sharing among participants in the innova­tion ecosystem.

We know less about differentiation as it relates to the values that govern policies, such as different notions of privacy, different interpretations of the meaning of free speech, or different views on eco­nomic interventions, such as the behavioral provi­sions included in the DMA. This short list already illustrates that these may be highly contested and politically charged issues, both domestically and internationally. Finding a common base will be chal­lenging and will require sustained effort. Thus, broad engagement by US government and nongovernment actors will be important.

Such engagement will have to be based on open­ness, respect for other values, and willingness to find common ground. It will also require engagement with the different types of normative frameworks that gov­ern policy choices. These may include the “capability approach” promoted by the United Nations Devel­opment Program and the “ethics of care” and “vir­tue ethics,” which have experienced a strong revival in technology policy.35 Ethics are no panacea for the challenges discussed above, but they can help estab­lish common ground while allowing differentiation.

Rather than seeking to eliminate policy differen­tiation, a strategy that embraces a nested system of policy experiments might be superior. Institutional and policy differentiation generate evidence of how different approaches affect outcomes. Under con­ditions of incomplete information and uncertainty, such differentiation is one way of learning about which policies work. Performance gaps between the American and European information and communi­cation systems have historically generated incentives to improve policy models, and they continue to do so. Some degree of policy variation therefore creates a dynamic learning system to assist in finding tech­nological and governance trajectories that serve the public interest.36

Summary and Conclusion

This report examined three interrelated ideas to guide the thinking of US actors from government, industry, research, and civil society, as they engage with and influence global discussions about the proper regulation of the digital economy. That the United States has not found its own approach to platform policy is both a hindrance and an opportu­nity to engage with other ongoing discussions.

These discussions would benefit from stron­ger conceptual foundations. A better-articulated, dynamic view of competition and innovation in digital platform ecosystems would provide a critical component. To this end, the report first clarified the principles that should guide platform policy, building on a model of innovation as a combinatorial process. Second, it identified basic criteria to assess the condi­tions under which interventions are reasonable. Third, it explored how such approaches could be translated to practical policy.

Platform governance, like internet governance, is already highly multicentric. These developments will likely continue, and some areas may benefit from regional and national differentiation. US engagement with global discussions, however, will benefit from a focus on finding consensus on basic shared princi­ples of governance that are essential for an open and democratic digital economy.

The stakes are high. Some of the tussles about plat­form governance could result in differences that can­not be reconciled within the existing US and European legal frameworks. One way to avoid this outcome is to discuss the fundamental principles that should guide platform policy and the digital economy.


  1. See Megan Brenan, “Views of Big Tech Worsen; Public Wants More Regulation,” Gallup, February 18, 2021, com/poll/329666/views-big-tech-worsen-public-wants-regulation.aspx.
  2. See European Parliament, Regulation (EU) No. 2016/679 of 27 April 2016, on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Pro-tection Regulation).
  3. The two cases are colloquially named after Austrian lawyer and privacy advocate Maximilian Schrems. The first case, Maximillian Schrems v. Data Protection Commissioner (Schrems I), challenged the adequacy of the US safe-harbor policies to meet the equiva­lency requirements under EU law. The second case, Data Protection Commissioner v. Facebook Ireland Limited (Schrems II), chal­lenged the equivalence of the US successor policy, Privacy Shield. On October 7, 2022, President Joe Biden signed an executive order on Enhancing Safeguards for United States Signals Intelligence Activities, directing the steps the country will undertake to implement the commitments made in the European Union–US Data Privacy Framework that had been announced in March 2022. Although the European Commission’s first response was positive, it is widely anticipated that an adequacy determination will again be challenged in European Courts.
  4. See Anu Bradford, The Brussels Effect: How the European Union Rules the World (Oxford, UK: Oxford University Press, 2020).
  5. See European Commission, Regulation (EU) No. 2022/1925 of the European Parliament and of the Council of 14 September 2022 on contestable and fair markets in the digital sector and amending Directives (EU) 2019/1937 and (EU) 2020/1828 (Digital Markets Act), Official Journal of the European Union, L 265/1 (October 10, 2022), OJ%3AL%3A2022%3A265%3ATOC&uri=uriserv%3AOJ.L_.2022.265.01.0001.01.ENG. The European Council approved the Digital Markets Act on July 18, 2022. The rules will take effect in early to mid-2024.
  6. See Proposal for a Regulation of the European Parliament and of the Council on a Single Market for Digital Services (Digital Ser­vices Act) and amending Directive 2000/31/EC, COM/2020/825 final.
  7. See Rebecca Janssen et al., “GDPR and the Lost Generation of Innovative Apps” (working paper, National Bureau of Economic Research, Cambridge, MA, May 2022),
  8. See Volker Stocker, Guenter Knieps, and Christoph Dietzel, “The Rise and Evolution of Clouds and Private Networks— Internet Interconnection, Ecosystem Fragmentation,” August 23, 2021,; and K. C. Claffy and David D. Clark, “Adding Enhanced Services to the Internet: Lessons from History,” Journal of Information Policy 6 (2016): 206–51, Services-to-the-Internet-Lessons.
  9. See Axon Partners Group, “Europe’s Internet Ecosystem: Socio-Economic Benefits of a Fairer Balance Between Tech Giants and Telecom Operators,” May 2, 2022,
  10. See Competition Policy International, “Internet Providers Rail Against EU Plans to Make Big Tech Pay for Telco Costs,” January 3, 2023, See also the critical analysis in Volker Stocker and William Lehr, “Regulatory Policy for Broadband: A Response to the ‘ETNO Report’s’ Proposal for Intervention in Europe’s Internet Ecosystem,” October 16, 2022,
  11. This report mainly focuses on US-EU relations and does not discuss the tensions with China. It also does not examine the national security framing that is often brought to these discussions.
  12. See Nick Couldry and Ulises A. Mejias, The Costs of Connection: How Data Is Colonizing Human Life and Appropriating It for Capitalism (Stanford, CA: Stanford University Press, 2019).
  13. See Mark A. Lemley, “The Contradictions of Platform Regulation,” February 3, 2021,
  14. The debate on whether static or dynamic efficiency should guide policy dates to the writings of Joseph A. Schumpeter. Joseph A. Schumpeter, The Theory of Economic Development: An Inquiry into Profits, Capital Credit, Interest, and the Business Cycle (Cambridge, MA: Harvard University Press, 1934); and Joseph A. Schumpeter, Capitalism, Socialism, and Democracy (New York: Harper, 1942). Schumpeter made compelling arguments in favor of dynamic competition. Renewed arguments in favor of the need to use dynamic models in competition policy and regulation for information and communication industries were made by Johannes M. Bauer and Erik Bohlin, “From Static to Dynamic Regulation: Recent Developments in US Telecommunications Policy,” Intereconomics 43, no. 1 (January/February 2008): 38–50, David Teece has long argued for the need to bring dynamic capabilities analysis to public policy. For a recent update applied to Big Tech firms, see Nicolas Petit and David J. Teece, “Innovating Big Tech Firms and Competition Policy: Favoring Dynamic over Static Competition,” Industrial and Cor­porate Change 30, no. 5 (October 2021): 1168–98,
  15. For an early contribution that did not yet use the term “two-sided markets” but explores many of the relevant issues, see, for example, James N. Rosse, “Estimating Cost Function Parameters Without Using Cost Data: Illustrated Methodology,” Econometrica 38, no. 2 (March 1970), 256–75,
  16. See Natascha Just, “Governing Online Platforms: Competition Policy in Times of Platformization,” Telecommunications Policy 42, no. 5 (2018): 386–94,; and José van Dijck, Thomas Poell, and Martijn De Waal, The Platform Society: Public Values in a Connective World (Oxford, UK: Oxford University Press, 2018).
  17. Michael A. Cusumano, Annabelle Gawer, and David B. Yoffie, The Business of Platforms: Strategy in the Age of Digital Competition, Innovation, and Power (New York: Harper Business, 2019).
  18. This classification is based on discussions in the context of the Quello Center Platform Innovation project and based on an internal Quello Center working paper authored by Steven S. Wildman.
  19. See Hari Balakrishnan et al., “Revitalizing the Public Internet by Making It Extensible,” ACM SIGCOMM Computer Communica­tion Review 51, no. 2 (April 2021): 18–24,
  20. Fiona Scott Morton et al., Committee for the Study of Digital Platforms: Market Structure and Antitrust Subcommittee Report, Uni­versity of Chicago Booth School of Business, George J. Stigler Center for the Study of Economy and State, May 15, 2019, https://www.; and Jacques Crémer, Yves-Alexandre de Montjoye, and Heike Schweitzer, Competition Policy for the Digital Era, European Commission, Directorate-General for Competition, 2019,
  21. Arnoud De Meyer and Peter J. Williamson, Ecosystem Edge: Sustaining Competitiveness in the Face of Disruption (Redwood City, CA: Stanford University Press, 2019); and Geoffrey A. Parker, Marshall W. Van Alstyne, and Sangeet Paul Choudary, Platform Revolu­tion: How Networked Markets Are Transforming the Economy and How to Make Them Work for You (New York: W. W. Norton, 2016).
  22. One of the classic contributions to evolutionary approaches to innovation is Richard R. Nelson and Sidney G. Winter, An Evolutionary Theory of Economic Change (Cambridge, MA: Belknap Press, 1982). The literature on systemic approaches to innovation is vast and fragmented across multiple disciplines, ranging from innovation economics to socio-technical systems analyses. See, for example, Gerald Midgley and Erik Lindhult, “A Systems Perspective on Systemic Innovation,” Systems Research and Behavioral Science 38, no. 5 (2021): 635–70,; and Frank W. Geels, “From Sectoral Systems of Innovation to Socio-Technical Systems: Insights About Dynamics and Change from Sociology and Institutional Theory,” Research Pol­icy 33, no. 6–7 (September 2004): 897–920,
  23. W. Brian Arthur, The Nature of Technology: What It Is and How It Evolves (New York: Free Press, 2009); and Johannes M. Bauer and Tiago S. Prado, “Digital Innovation: An Information-Economic Perspective,” in The Elgar Companion to Information Economics, ed. Daphne R. Raban and Julia Włodarczyk (Cheltenham, UK: Edward Elgar, 2023).
  24. See Christopher S. Yoo, “Modularity Theory and Internet Regulation,” University of Illinois Law Review 1 (2016): 1–62, https://
  25. See, for example, Cusumano, Gawer, and Yoffie, The Business of Platforms; and Michael A. Cusumano, Annabelle Gawer, and David B. Yoffie, “Can Self-Regulation Save Digital Platforms?,” Industrial and Corporate Change 30, no. 5 (October 2021): 1259–85,
  26. See Timothy F. Bresnahan and M. Trajtenberg, “General Purpose Technologies: ‘Engines of Growth’?,” Journal of Econometrics 65, no. 1 (January 1995): 83–108,; Timothy F. Bresnahan, “General Purpose Technologies,” in Handbook on the Economics of Innovation, ed. Bronwyn H. Hall and Nathan Rosenberg (Amsterdam, Netherlands: Elsevier, 2010), 2:761–91; and Johannes M. Bauer and Günter Knieps, “Complementary Innovation and Network Neutrality,” Telecommunications Policy 42, no. 2 (March 2018): 172–83, S0308596117304615.
  27. See, for example, Sai Krishna Kamepalli, Raghuram G. Rajan, and Luigi Zingales, “Kill Zone” (working paper, University of Chicago, Becker Friedman Institute for Economics, Chicago, April 27, 2020), id=3555915.
  28. See Tiago S. Prado and Johannes M. Bauer, “Big Tech Platform Acquisitions of Start-Ups and Venture Capital Funding for Innovation,” Information Economics and Policy 59 (June 2022),
  29. See Johannes M. Bauer, “Regulation and Digital Innovation,” in The Future of the Internet: Innovation, Integration and Sustain­ability, ed. Gunter Knieps and Volker Stocker (Baden-Baden, Germany: Nomos, 2019), 77–108.
  30. See the discussion in Philippe Aghion et al., “Competition and Innovation: An Inverted-U Relationship,” Quarterly Journal of Economics 120, no. 2 (May 2005): 701–28,; Philippe Aghion, Céline Antonin, and Simon Bunel, The Power of Creative Destruction (Cambridge, MA: Harvard University Press, 2021); and Ulrich Heimeshoff, “What Drives Investment in Telecommunications Markets? Evidence from OECD Countries,” Review of Economics 64, no. 1 (2013): 7–28,
  31. See Johannes M. Bauer, “Toward New Guardrails for the Information Society,” Telecommunications Policy 46, no. 5 (June 2022): 102350,
  32. See Adam Thierer, Governing Emerging Technology in an Age of Policy Fragmentation and Disequilibrium, American Enterprise Institute, April 29, 2022,
  33. See Elinor Ostrom, “Beyond Markets and States: Polycentric Governance of Complex Economic Systems,” American Economic Review 100, no. 3 (June 2010): 641–72,; and Brett M. Frischmann, Michael J. Madison, and Katherine J. Strandburg, eds., Governing Knowledge Commons (Oxford, UK: Oxford University Press, 2014).
  34. See, for example, the cases in Damien Geradin and Dimitrios Katsifis, “The Antitrust Case Against the Apple App Store,” Journal of Competition Law & Economics 17, no. 3 (September 2021): 503–85,
  35. See Shannon Vallor, Technology and the Virtues: A Philosophical Guide to a Future Worth Wanting (Oxford, UK: Oxford University Press, 2016); Virginia Dignum, Responsible Artificial Intelligence: How to Develop and Use AI in a Responsible Way (Chum, Switzerland: Springer Nature, 2019); and World Economic Forum, Ethics by Design: An Organizational Approach to Responsible Use of Technology, December 2020,
  36. See René von Schomberg and Jonathan Hankins, eds., International Handbook on Responsible Innovation: A Global Resource (Cheltenham, UK: Edward Elgar, 2019).
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