Tag Archives: Network effects

Network Effects and the Assessment of Market Power in the Sharing Economy

By Francisco Beneke*

You may have heard of unicorns and venture capital in the Silicon Valley. Unicorns are startup companies that have not generated a single cent in revenue but are able to marshal multimillion-dollar amounts of capital from investors and cross the one-billion-dollar threshold in market value. Why? Their potential, of course. Venture capital firms don’t want to miss on the next Facebook. But in what exactly does this potential consist? In the particular case of platforms like the one just mentioned, the hope of the investors is that the company will have an exponential growth in consumers and providers, which in itself will make the product more attractive to other buyers and sellers, which in turn generates a virtuous circle in the company’s growth. That is, investors covet companies that can generate network effects or demand-side economies of scale, which enable them not only to monetize customers but also to get their hands on the data they generate.

In some markets, sharing economy platforms like Uber and Airbnb have grown so much that they are attracting lawsuits of abuse of dominance. That is, plaintiffs consider that these firms have become the main players in their markets. If these companies have already generated a critical mass of providers and customers, their position may be entrenched just for the fact that they are big. Providers will choose a given platform because the potential demand is bigger and customers will rather buy services through it because there are more options (in the case of Uber, for example, more drivers means shorter wait times and wider geographical coverage for passengers within a city).

There is much to be said about network effects and market contestability. However, I will focus just on one aspect. An important point in the case of sharing economy platforms is the geographical scope of these effects.[1] More Lyft drivers in San Francisco mean nothing to a customer in Munich. More Airbnb listings, on the other hand, are a different story.

You may have already guessed the direction of the argument in this post. The global (or at least transnational) character of Airbnb’s network effects makes it a more powerful company against its competitors than Uber. The battle for passengers is fought city by city, which means that companies have to attain a lower critical mass of consumers and providers to contest Uber or Lyft’s foothold. There can still be, to a certain extent, an international component in ride-hailing apps’ network effects. A part of their demand is composed of tourists. However, if we expect the bulk of passengers to be city residents then network effects will tend to be more local.  If any of these companies is being scrutinized for monopolization/abuse of dominance, this factor has to be taken into account.

That is not the same as saying that the geographical location of the market has to be correctly assessed. I’ll give you an example. If you are analyzing a short-term accommodation market you may define the relevant geographical dimension as that of a city. The company in question, however, may have a global reach, which makes it likelier that a tourist or a business traveler will use its platform to search for a place to stay.

I admit that network effects are a complicated issue from an antitrust perspective. The source of concern is something that benefits consumers in the first place. If the platform is attractive, among other things, because of its size, then all the better for it. That should lead to view mergers in any such markets with less suspicion, right? My bet is that it will not be that way except in the cases when national champions, like Didi in China, buy foreign threats, like Uber.

*Co-editor, Developing World Antitrust

[1] Sundararajan, A. (2016). The Sharing Economy–The End of Employment and the Rise of Crowd-Based Capitalism, p. 20. Cambridge, MA: MIT Press.

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