Digital Regulation Platform

Explanation of externalities on digital platforms



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One of the reasons why digital platform are special is the presence of externalities. Externalities (which are also known as network effects[1]) are an economic concept: they are a cost or benefit of an economic activity experienced by a third party which has no relation with the one causing the activity. Externalities arise from digital platforms because they act as economic agents matching two distinct groups of users, one on each side of the platform.[2] The users on one side have no direct relationship with the users on the other side of the platform, but each is affected by the presence of the other.

A typical example is that of consumers accessing Google to search the Internet. They will pay an Internet service provider (ISP) a monthly fee for connectivity but they will not pay Google for making the search. In turn Google will collect information regarding consumers’ behaviour while searching (anonymously and/or in aggregate form so as to preserve privacy) and then sell to interested advertisers. With this information, advertisers target consumers more efficiently whenever they are online and searching the Internet.

Consider the impact of a consumer starting to use Google’s services. This action has no direct impact on existing consumers, but it creates a marginal benefit for advertisers (who now have slightly more data to work with when setting their advertising algorithms). This, in turn, marginally enhances the utility of Google advertising to all consumers. So, the utility of Google to both existing consumers and advertisers is affected by the actions of a new consumer joining the platform. This is the work of an externality.

Network effects on a digital platform

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In the case of digital platform, analysis of externalities or network effects is more complicated. For each new user that joins the platform, the existing user base is affected. But there may be different effects for users on either side of the platform, and the impact of a new user may be either positive or negative, depending on the application being supported by the platform. For example, congestion is a negative network effect whereby having too many users on the platform can degrade the value of using it.

Because platforms may have two or more sides, the network effects can be within-group, when a new user affects the value of the platform for all other users on the same side; but it can also be cross-group, when an additional user makes affects the value of the platform for users on the opposite side.[3] The figure above schematically shows the different types of network effects that can arise in two-sided platforms. The presence of cross-group effects on digital platforms, particularly when they are positive on both sides, may have a considerable impact on market structure.

Within-group effects

Within-group effects usually mean the impact of the addition of one more participant to a network on other participants in the same group. They can be either positive or negative. Consider a social network, such as Linkedin. Such a platform may provide just contacts between people on one side or act as a matchmaker between professionals looking for a job and companies looking to hire qualified people. An additional person joining the platform increases the size of the network and, in doing so, increases the number of people all other members can connect with. This is a positive within-group network effect.

However, if someone joins this platform with a job search in mind and starts competing with other members with the same type of merits for the same job offers, this decreases the probability of everyone getting the job. Hence, an additional participant makes the other participants on the same side of the platform worse off. Another example would be when more participants join an auction on a digital platform, thereby increasing the value of the winning bid. These are examples of negative within-group network effects.

Cross-group effects

Cross-group effects refer to the impact of the addition of one more participant on a platform to the participants on the other side of the platform.

For a positive cross-group network effect, consider the case of Google and Facebook business models.[4] Both are based on attracting a large number of users and amassing huge amounts of data associated with their usage habits. This, in turn, enables them to offer advertisers an efficient way of targeting end consumers. The corresponding revenue allows them to improve the consumer experience through new and better functionalities, either organically developed or through mergers and acquisitions (M&A), attracting even more users to the platform, and increase the effectiveness of predictive algorithms.

As the number of users on the Google or Facebook platform grows, users on the other side perceive the increasing value of the platform as a place to advertise. So, there are positive and strong cross-group externalities which gives rise to significant economies of scale and ultimately to larger and fewer competing platforms.

However, if consumers do not see any value in being targeted with advertisements, or, worse still, they see advertisements as a significant nuisance and intrusion, this may motivate them to cut their usage or even to abandon the platform altogether. This would then become an example of a negative cross-group effect.

The conflict between different types of network effects, particularly positive and negative cross-group effects, has significant implications on the business models of digital platform providers, the intensity of competition, price structures, and consumer welfare.

Implications of network effects

As the economics literature on two-sided markets recognizes (Schmalensee and Evans 2007: 27), the intermediation role of digital platforms is, in many cases, characterized by large and positive cross-group network effects. When positive on both sides, the stronger they are, the more value each side places on the other side. The strength of these cross-group externalities may play a decisive role and, therefore, these platforms are prone to achieve a large scale.

For competition authorities, ultimately concerned with consumer welfare, the presence of cross-group effects together with economies of scale require particular attention as they can allow digital platforms to become dominant through feedback loops. Before digital platforms became a concern to competition authorities, the economic theory on multisided platforms had already demonstrated that indirect network effects are important across a number of sectors, such as in payment cards.

However, in many of the sectors in which cross-group network effects are strong, there is, nevertheless, effective competition. There are several examples within the digital platform environment: platforms that provide dating opportunities, real estate transactions, financial advisory, online magazines, restaurant booking, and so on. The economic literature attests to a number of factors that can, even in the presence of cross-group effects and economies of scale, lead to a healthy competitive process. Such factors include the prevailing types of use on the opposite platform side (i.e. single-homing or multihoming), the degree of differentiation, and platform congestion. How intense these factors are, and how they interact with each other, will ultimately determine the relative size of competing platforms and, therefore, the prevailing market structure.

In digital platforms network effects can be either inter-group or cross-group, with different strengths and either positive or negative. These effects, interacting with a range of other factors, determine the market structure outcome. But contrary to a common view in many public statements, not all digital platforms are prone to tip and become large and dominant. A recent report (Bruno and Sand-Zantman 2019) points to how users can be quite heterogeneous in their reasons for joining a digital platform. So, even where strong network effects exist, there is scope for market segmentation, service differentiation, and alternative pricing strategies. This may result in substantial and healthy competition among digital platforms and, more important, allow relatively large incumbents to be displaced.

Still, in digital platforms, it is clear that network effects are fundamental and important. This fact has, for instance, led to amendments to the German antitrust laws, with the introduction of a number of additional criteria that the German competition authority and the courts now need to consider when assessing market power in platform markets. One of them is direct (inter-group) and indirect (cross-group) network effects.[5]


  1. In mobile or fixed telecommunication networks the same effect is at play: the utility of a user increases with the number of other users using the network. These are also called direct network effects. If there are only a few subscribers, that network will be of relatively low value to any given user compared with a larger competing network with many users. As a consequence, a new entrant, because of its small scale, may have difficulty attracting new users relative to a large incumbent. Direct network effects create barriers to entry and expansion of the market.
  2. Multisided platforms also exist, but for simplicity this article refers mainly to two-sided platforms.
  3. In the economic literature, these effects are sometimes called “indirect network effects” or “indirect externalities.” However, this term is confusing because it is also possible for network effects to be indirect but one-sided. To give an example, one-sided indirect network effects are at play when the increased usage of the product originates the production of increasingly valuable complementary goods, and this results in an increase in the value of the original product.
  4. See also Digital Regulation Platform Case Study on “Australia’s Digital Platforms Inquiry.“
  5. The other criteria are: the parallel use of several services and user’s switching costs, economies of scale in relation with network effects, access to data relevant for competition and competitive forces of innovation. For more details, see Digital Regulation Platform thematic section on “Amending German competition law for digital regulation.”


Schmalensee, Richard, and David S. Evans. 2007. “Industrial Organization of Markets with Two-Sided Platforms.” Competition Policy International (3) 1.

Jullien, Bruno, and Wilfried Sand-Zantman. 2019. “The Economics of Platforms: A Theory Guide for Competition Policy.” TE Digital Center Policy Papers series, No.1.