Competition authorities are increasingly concerned that their tools are not fit to deal with digital multi-sided platforms, which operate in markets that have a tendency to ‘tip’. However, the academic literature does not yet provide guidance on how to identify the likelihood of tipping in a market. Instead, the literature identifies a number of factors that might foster or mitigate tipping under certain circumstances.

This paper, available here, reviews the literature and identifies the key market characteristics that facilitate tipping and those that mitigate it. It also advances four key questions to guide policy makers in the development of methods to identify the likelihood of tipping.

Section 2 discusses factors that facilitate market tipping.

The authors identify six key factors that foster tipping in markets with multisided platforms: positive network effects, single-homing and switching costs, free services, data-enabled learning, trust, and platforms’ complementary offerings. Markets with multisided platforms typically also exhibit classical factors that foster concentration, like economies of scale due to high fixed costs for IT, R&D and marketing, which are largely independent of the number of users.

Section 3 looks at factors that mitigate the odds of a market tipping.

The authors focus on factors that lead to market segmentation as factors mitigating tipping. While one could argue that, in a segmented market, the segments have tipped, these factors leading to increased market segmentation likely mitigate full-scale market tipping since they make it easier to challenge a strong platform in a neighbouring segment. Given this, six key factors are identified as mitigating tipping in markets with platforms: negative network effects, user heterogeneity, ‘local’ network effects, multi-homing, horizontal differentiation and innovation.

Section 4 considers the implications for competition policy.

The above discussion of the factors that influence the likelihood of a market tipping suggests four questions that can be asked to assess that likelihood. First, are there factors present that may negatively impact the value of a multisided platform? An increase in a platform’s user base and market power can lead to countervailing effects that can slow or stop the forces promoting market tipping, e.g. higher prices on one market side when essential network effects are across groups and negative network effects within a user group, among others. A second question is whether there are factors that make it easier for small rivals to acquire users, such as generalised multi-homing. Third, are smaller rivals attractive to at least some users? This may be the case when there are local network effects or platforms are horizontally differentiated. Finally, one may ask whether a multisided platform already has a strong market position in a different market. Such a market position can foster tipping, while its absence makes tipping less likely.

These questions capture the entire list of issues discussed in the literature on factors that influence the likelihood that a market will tip. However, by themselves they are unable to fully determine whether a market will tip. As such, it is advisable that the proposed analysis is complemented by consideration of whether any multisided platform already stands out in the market, and of generic market trends. In addition, competition authorities will have to take into account the expected welfare effects of market tipping. Most of the factors that facilitate tipping will also lead to short-term welfare benefits when the market tips, which will then have to be balanced against potential long-term harm to welfare arising from market tipping.

There are a number of available policy alternatives when dealing with a market with a propensity to tip. Ongoing debates very much focus on adapting intervention thresholds better to target multisided platforms with a strong market position, to prevent them from tipping other markets in their favour. Alternatively, some suggest lowering intervention thresholds to target platforms with the potential to become dominant before they acquire such a position in a market that might tip (e.g. by referring to relative power or intermediary power). Other initiatives argue for a ban on certain practices which may unduly constrain the business model of smaller platforms across the board; on the other hand, the adoption of envelopment or tying strategies by small platforms should be allowed since this is likely to facilitate competition in markets with multisided platforms – in particular when it is used to overcome an entry barrier or challenge a dominant incumbent.

Comment:

The paper provides a useful overview of the literature on market tipping, and, on that account alone, it is recommended reading. My main quibble with the paper is that it is unclear to me why we would need to know whether a market is prone to tipping in practice, and this is not made clear even in the section devoted to the implications to competition policy. If I understand the paper correctly, the argument seems to be that ‘tipping’ might be welfare enhancing, but we should ensure that it occurs naturally and not as a result of a multisided platform leveraging its market power into a (still) competitive market. If this were the case, I suspect the authors’ analysis would be useful for prioritising enforcement efforts, but I see no reference to this in the paper. Another possibility is that the concern is with ‘gatekeepers’ that are not dominant, but it is unclear to me how that is relevant to the market tipping – instead, that strikes me as being about regulating market power in markets where a ‘dominant’ or ‘quasi-dominant’ position is the natural equilibrium. Given this, it would have been useful if the authors had more clearly articulated the relationship between the control of market power and market tipping. This would have added clarity to the proposed objectives of public policy as regards tipping markets – and, hence, about the value of the authors’ attempt to devise a method that facilitates the identification of tipping markets.

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