Figure 1. Market capitalisation and employment for selected platforms and other firms
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Figure 2. Overview of inferior quality problems related to business users
Figure 3. Value creation when data is used for a specific purpose
![However, note that data can also be re-purposed, thus bringing additional value. For example, in cases where algorithms wish to capture consumer preferences that shift frequently, the size of the data sample can help firms to quickly identify these shifts and adjust their digital services accordingly. Moreover, the data sample in one market, when it is sufficiently large, can be helpful when entering a closely adjacent market. Overall, when data is used only in algorithmic systems with a specific task, it is more likely to exhibit diminishing returns to scale. But, when it is used in additional applications or in capturing dynamic trends, then it can also exhibit increasing returns to scale. Further empirical research is needed to assess the exact magnitude of economies of scale in such cases. Proposed solutions One of the most widely discussed solutions has to do with breaking up the big platforms. If the breakup is horizontal and involves breaking a monopoly platform to two (or more) within the same market, then, as Figure 3 suggests, value created can decrease. Consider that the monopoly platform before the break has accumulated a lot of training data and it is at point A. If the breakup has as an outcome the creation of two equivalent platforms at point B, then the new policy can significantly decreased the value created. Consider now an alternative scenario: that the break up allows each of the firms to use the same amount of data as before the break up (both platforms are at point A), thus cloning the platform. Then, there is no loss of value in the short-run, but this equilibrium may be unstable in the long-run. Since both platforms offer the same services, under the presence of network externalities and economies of scale, competition for the market ensues. The first platform that manages to increase its users will start growing and, in the end, there might again be a dominant platform. Competition between MySpace and Facebook was at one time very intense but Facebook emerged as the winner and became a dominant platform in social networks. The growth of platforms such as Twitter and LinkedIn can be explained by the fact that they offered sufficiently differentiated services and found room to increase their market position. So, a horizontal break up may not work as intended because it can lead to efficiency losses and may only reduce market power in the short run. We could also consider a vertical break up, similar to Senator E Warren’s proposal. As already discussed, many platforms have extended their operations along the vertical line. They not only facilitate interactions between consumers and external producers but they also produce upstream products and services themselves. Vertical integration in this case can provide an information advantage for the platform’s upstream subsidiary over demand and the strategies of upstream competitors. Vertical integration can generate extra value because the upstream provider has better information about what consumers want and it can also solve the double marginalisation problem. Nevertheless, it may provide incentives for the platform to preferentially treat its own subsidiary at the expense of external suppliers. A break up could remove such anticompetitive incentives. But, it could also reduce the value creation from the production by the upstream subsidiary. What we argue below is that a well-designed regulatory framework that eliminates the risk of mistreatment of the external suppliers and facilitates symmetric information sharing at the upstream level could work better because at the same time value creation would not decrease and a level playing field in the upstream market can be restored. Some big tech platforms are present in multiple closely adjacent, parallel markets. A breakup could also occur by restricting each platform to operate in only one market. There are two challenges with this approach. First, in some cases, it is very difficult to find a clear separating line between different digital markets. Second, the data and information in one market can have a strong positive spillover effect in another one that is closely related. Thus, a breakup can again lead to a reduction in the value creation. Another solution that received extensive coverage is to treat data as labour (Posner and Weyl, 2018): Data has an immense value for platforms. It can be used to train algorithms and improve products. As a result, they argue that platforms should provide a fair payment to each individual for using their data. In other words, the use of these platforms should be viewed as a labour contract for each individual. This proposal calls for the formation of independent data labour unions which will regulate the price individuals will be paid and will manage the transaction. Since individuals have both limited time and attention, unions will need to solve the allocation problem by setting prices in an appropriate way. Unions should also set lower prices (or zero prices) for small entrant platforms to counterbalance network effects, data value effects, and economies to scale. Obviously, direct monetary transfers to users could increase consumer surplus. In fact, in the case of Facebook, in a static environment, Benzell and Collis (2019) find that this increase will be around 24%. But, there are a number of reasons that this approach may not work, at least, at the current stage where a formal model for its implementation is missing. First, it is empirically unclear whether the users of the platforms derive lower value than the value the platforms derive from them. In the former case, any monetary transfers from platforms to consumers may have negative dynamic effects on incentives for investments on innovation and improvement of services. So, such transfers can be welfare reducing in the long run. Second, it is very difficult to imagine the formation of new state independent data unions that will have the power to impose the market prices for data. History has shown that labour unions in many cases lack bargaining power (especially in work provided through digital platforms) and that prices can only be restricted by formal (state) regulatory intervention. As we argue below, it is the regulatory framework that will be put in place that can be instrumental in incentivising data sharing mechanisms with benefits for individuals. Finally, we should not ignore that, in many applications, it is not the individual data but its aggregation that significantly increases value creation. There are also proposals that move away from competition by considering other instruments that can apply. For example, taxation of digital platforms has been proposed as a way to redistribute in a better way the value created in platform ecosystems. While such a tax can have important redistributive implications, it does not seem so promising in solving the theories of harm associated with market power. We also need to put in place other instruments that can lead us directly to a more efficient dynamic market competition. The way forward Our5 main takeaway is that traditional antitrust intervention (typically taking place ex-post) will be less effective in markets driven by network effects unless it is combined with a proper regulatory framework (which is set ex-ante). Hence, instead of discussing whether antitrust should change its legal standards and principles as proposed by the New Brandeis approach (as well as the consumer welfare criterion as it has been suggested by legal scholars like Steinbaum and Stucke, forthcoming) to address concerns of platform market power, we propose an alternative as follows. The rest of this section is based on our forthcoming research where we develop the details of our proposal (Parker, Petropoulos and Van Alstyne, 2020). In the remainder of this piece, we summarise its main features. Antitrust tools should focus on value creation before focusing on competition. The scope of regulatory intervention should satisfy the following three criteria: i) Value creation from operation of a platform does not decrease because of the policy intervention; in particular, interventions should not reduce network effects. ii) Allocative efficiency is based on distributing the value created in a fair way among market participants e.g. through use of the Shapley Value. Fair and transparent rules must govern the platform ecosystem. iii) Dynamic efficiency and competition ensure that incentives for market misconduct and anticompetitive strategies such as artificial entry barriers are eliminated. This approach requires a harmonic relationship between antitrust and regulation with several implications. The first one has to do with the definition of the relevant market. It can become extremely difficult to define the market, especially in the case of the provision of free goods. Free goods platforms typically bundle complements so that interactions across search, mapping, email, and home devices create network effects. Instead of examining markets, it may be better to focus on the provision of the specific service and the value they generate to the digital ecosystem. In this way, we can be more concrete in defining substitutable services and assess the level of competition for each particular service. In fact, Brynjolfsson and Collis (2019) provide a new methodology on how to assess the substitutability of free goods in an incentive compatible way at the service level. They use digital survey techniques to run massive online choice experiments examining the preferences of hundreds of thousands of consumers. They estimate the consumer surplus for a great variety of goods, including the ones that are offered at zero price. They find that the median compensation Facebook users were willing to accept to give up the service for one month was $48. On this basis they estimate that US consumers have derived $231 billion in value from Facebook since 2004 (Brynjolfsson et al 2019). Such an experiment can be easily be extended by assessing what would have been the choice of a user if one of the platforms would not have been available. Users’ choices in such a case can assess the degree of substitutability between platforms. If such an approach is combined with an assessment of the substitutability on the other side of the market (eg. advertising), which typically exhibits positive prices and where it is therefore easier to apply standard antitrust methodology, we can get a more comprehensive picture over the competitive pressure for the provision of that service. On the side of antitrust and its only ex-ante instrument, merger control, authorities should develop a more forward looking perspective when they evaluate merger cases, especially the ones that raise the suspicion of a killer acquisition. For this they need to assess what the potential competition effect is if the merger is not allowed. Would WhatsApp become a direct competitor of Facebook if the merger was not allowed? If the answer is likely to be yes, then the merger may decrease consumer welfare as it restricts potential competition that could lead to lower prices and higher quality and therefore be prevented. But, in practice, it is very challenging to assess potential competition. One avenue that can be helpful with this respect could be to measure the substitutability of platforms’ services during the merger evaluation (which could be based on the methodology suggested in the previous paragraph). That can take place with the employment of surveys and online questionnaires and experiments that ask users (through a design that satisfied incentive compatibility) about what platforms would attract their attention if a specific platform was no longer available. For the impact of the merger on concentration in the other side of the market where positive prices are used to clear the market, traditional tools in merger simulation can be applied. Hence, in this way we can assess the impact of a proposed merger. Closely substitutable platforms can potentially lead to a competitive equilibrium with direct welfare implications for the merger case. At the same time, we should strengthen ex-post evaluation of merger cases and be ready to impose remedies that are contingent to specific future outcomes. If it becomes clear that the remedies attached to the past approval of a merger do not have the desired effects, there should be flexibility so that such remedies could be modified accordingly. It would be helpful if remedies are periodically reviewed to assess whether they have the desired effect and are updated accordingly. The specific targets in terms of the welfare impact of a merger should be clearly communicated at the time of the approval of the merger. Remedies should be flexible to change in order to ensure that the specific targets are reached, if needed. Last but not least, particular attention should be paid to the details of the merger deal (eg. price of the takeover), as it may signal strategic motives, as well as at the impact of the merger on the incentives and ability of firms to innovate. Mergers that are classified as killer acquisitions are more likely to have negative impact on innovation (Kamepalli, Rajan and Zingales, 2020). Regardless of the specific merger cases that are being evaluated, the option of well targeted market surveys at different points of time could be very useful. They could provide a better understanding of the substitutability between alternative options and how they evolve over time, even if they do not operate in the same markets. With respect to the second instrument of antitrust on price fixing agreements and tacit collusion, the empirical challenge is that it is very difficult for the authorities to assess what the competitive price is in real time. Algorithms have accurate information at any point of time on demand conditions and the selling strategies of competitors. The approach with respect to tacit collusion should have two dimensions: i) authorities need to be more active in market data collection (prices, sales) to allow them to better estimate demand conditions and assess whether prices are well above competitive levels. With this respect, authorities may have to develop their own algorithms to resemble market conditions; ii) authorities should also engage in a dialogue with the concerned firms as well as the platforms with which these firms operate in order to find the best possible way to restore consumer welfare. This second dimension follows in spirit the participative antitrust approach proposed by Tirole (2017). It is unrealistic to expect that authorities will be able to get as good information about the market conditions and characteristics as platforms have. Platforms, because of their position in the digital ecosystem, have better chances to detect abnormal pricing behaviour from their external producers that suggest some form of tacit collusion. Even if authorities in the course of evaluating a given case, get access to good quality market data, it will take a large amount of time to understand its implications for the case. In the Google shopping case, the European Commission broke records on the amount of data they collected and processed, but the case itself took more than 7 years for the publication of the decision6. So, the approach we propose here requires frequent interaction between authorities and platforms that will lead to mutual recognition and understanding of the firms’ strategies that do not reduce consumer welfare. During the COVID-19 pandemic crisis, authorities were working closely with platforms7 to identify price gouging practices by online sellers using their services. Such forms of cooperation can continue during normal times to assess excessive, tacit collusive pricing. A third instrument of competition law is that firms with dominant positions are restricted in the market strategies they can adopt. Since antitrust intervention is ex-post in this case, antitrust has a limited ability to address successfully the associated theories of harm, even if authorities rely more on interim measures. While the above antitrust measures can be helpful, they are unlikely to be effective without further policy intervention. What we suggest is a regulatory framework that will address the problem ex-ante with respect to the principles of competition law that apply ex-post. Competition policy should be viewed as a measure of last resort that is applied ex-post only when regulation does not have the desired effect. On the demand side it is important to ensure that multihoming is possible between platforms. A first step to achieve this is to reduce the switching costs and ensure data portability. Experience from banking services can inform how data portability might work. The Open Banking Initiative allows consumers to obtain and transmit their banking activity in a standardised and secure fashion to regulated and approved third-party firms in UK (final report from the Stigler Committee on digital platforms, 2019). At the same time, open standards should be encouraged where interoperability between different competing platforms is enforced. Regulation on the supply side is also crucial. First, transparency needs to be enforced in the platform environment so that external suppliers have access to all the necessary information that they need for their efficient operation on the platform. The European Commission has recently implemented regulation to improve transparency and establish trust in the platform ecosystem. Second, platform access policies should follow the principle of non-discrimination (unless an objective justification of no consumer harm over discriminatory policies in place can be provided) in order to ensure the level playing field between external suppliers and platform’s upstream subsidiaries. As we argued above, data accumulation leads to higher value creation. The challenge we need to address is that it also confers a competitive advantage. Big platforms with large amounts of data generate high value and efficient services. But, that also makes it more difficult for smaller firms to compete with them and provide alternative options to consumers. Ideally, what we want is to both keep value creation at high levels while also encouraging small firms to compete more effectively with high-tech giants. To do that, we need to design data sharing mechanisms that enable small firms to get access to data. In this way, data will not only confer value to the market leaders but also to their competitors, to the benefit of the whole ecosystem. Then we will be able to keep value creation at high levels, while also increasing market competition, contributing to allocative and dynamic efficiency. The market design for data sharing can be challenging. Fortunately, regulators of financial services like the PSD2 regulation in the EU have created one possible path. PSD2 explicitly empowers account holders with the authority to share data, removing the financial institution’s role as gatekeeper. The motivation for this regulation is to reshape the financial sector in a way that small fintech firms have sufficient room to grow and compete with established banking institutions. The incumbents raised the possibility that such regulation would have the unintended consequence of giving preferential access to large technology companies. Applying a similar regulation to other sectors could level the playing field as the issue becomes more evident with the entry of big digital platforms into the financial service sector that do not have to follow PSD2 regulations. Data sharing should take place without providing incentives for data exploitation. GDPR provides a framework of rules for data sharing, but only in the case that data is related to an identified or identifiable person (personal data). In principle, the consent of the user is required. However, according to the Article 6(1)(f) of the GDPR8, data sharing of personal data can be lawful without user’s consent when: “processing is necessary for the purposes of the legitimate interests pursued by the controller or by a third party, except where such interests are overridden by the interests of fundamental rights and freedoms of data subject [user] which require protection of personal data.” Namely, a consent is not required in a limited number of cases when the risks of data sharing are small and potential usefulness of data sharing is high. So, with consent or without, the GDPR provides an avenue that facilitates data sharing if that increases consumer welfare (as in our proposal) when privacy risks are low. It should be noted that anonymised data that is aggregated faces a lower risk of exploitation (Li et al 2017). While, in principle, the GDPR does not apply to anonymous datasets, research has shown that anonymising individual level personal data in such a way that individuals cannot be re-identified is very difficult, especially, for rich datasets that include multidimensional information (Montjoye et al 2015). In cases where anonymity becomes a challenge, the employment of methods such as homomorphic encryption or secure multiparty computation can become helpful. Despite these concerns, we expect that the welfare benefits from data sharing are going to be higher than the risks so long as those risks are appropriately managed. To sum up, the way forward requires both specific innovations in the use of antitrust instruments, as well as a regulatory intervention that will set the necessary standards for facilitating data sharing between competitors. Given the global reach of digital platforms, this approach requires a base level of coordination and collaboration at the international level. To see this, consider the following example: In Europe, antitrust authorities adopt a more dynamic view in merger control, across the lines illustrated above, but US authorities continue to apply the same old-fashioned and ineffective static framework. It is clear that this situation is not ideal for solving the market power issues of digital platforms. Platforms can merge with their potential competitors in the US market and use their increased market power in the US market in a way that provides them with a competitive advantage even in the European market. So, the proposed updates of antitrust tools require a platform of continuous exchange and coordination between enforcement bodies and legislators. The International Competition Network can be the nexus of coordination between antitrust authorities and practitioners among the countries that are members. Despite its extensive global coverage, some major economies like the Russian Federation and the People’s Republic of China are not members of this body. So, additional discussions should take place between this network and the competition authorities that participate in the BRICs association. Authorities can innovate by adopting practical new techniques in the application of competition law in digital markets and coordinate on studying specific markets through surveys and other tools. In terms of case law and legislative actions, when needed, some further coordination and convergence will be particularly welcome, maybe through extending interaction under the OECD umbrella on these issues. On our recommendations for data sharing mechanisms, we need to ensure the free flow of data and minimise the cases of data localisation. To achieve this, we need to make sure that strong privacy protection is in place when data transfers take place. A promising avenue can be the bilateral data transfer agreements between different jurisdictions under some common characteristics and principles. For example, the EU-US Privacy Shield dictates that Europeans are protected according to the GDPR standards even when their data is transferred to the US. Similar bilateral agreements have been signed with other countries that wish to have access to data of European citizens. By building on such agreements and expanding their reach, we can solve coordination problems in terms of privacy rules. Consequently, we can design flexible data sharing mechanisms that solve market power problems that go beyond the borders of specific jurisdiction. While some base level of coordination across boundaries is important, jurisdictions should also keep their freedom and flexibility to adjust specific rules to their own economic realities and characteristics in a way that does not contradict the basic principles. Besides, we expect that such flexibility will be critical for establishing the necessary common ground. From the lengthy reports published from jurisdictions across the world, we see that they frequently identify the same market competition challenges from the operation of digital platforms. So, why not also adopt, in principle, common solutions? A potential risk that may threaten this necessary coordination at the global scale is the industrial policy goals of different countries and jurisdictions that are divergent. For example, the US, EU and China are ambitious in their artificial intelligence strategies and are trying to increase their prominence and influence. A particular dimension of this ambition is reflected in the industrial strategies adopted in each of these three jurisdictions. Such strategies try often to influence the way competition policy is applied (recall for example the intensive debate behind the Alstom-Siemens merger case) and made it more lenient to protectionism motives. The new approach we propose here requires both ex-ante regulation as well as ex-post competition policy measures to be applied without any dependence on political or industrial policy motives. It is necessary to keep the application of competition principles independent and consider them as the basis for any industrial policies that come into force (see for example Petropoulos, 2019, on the harmonic relationship between competition and industrial policy). Competition policy should not serve any protectionism function. It should serve market efficiency and consumer welfare. Of course, we recognise that suppressing national aspirations for the common good poses diplomatic challenges, but that should not prevent us from establishing common goals.](images/u149892-268.png?crc=439960866)
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