Digital platforms can acquire potential competitors, dissuading others from entering the market and protecting them against disruptive innovations. In a sense, digital incumbents create a “Kill Zone” around their areas of activity, which might discourage new investments. However, the idea that acquisitions discourage new investments is at odds with a standard economic arguments: if incumbents pay handsomely to acquire new entrants, why should entry be curtailed? Why would the prospect of an acquisition not be an extra incentive for entrepreneurs to enter the space, in the hope of being acquired at hefty multiples?

This paper, available here, explores why high-priced acquisitions of entrants by an incumbent may not necessarily stimulate more innovation and entry in an industry (like that of digital platforms) where customers face switching costs and network externalities. The prospect of an acquisition by the incumbent platform undermines early adoption by customers, reducing prospective payoffs to new entrants. This creates a “kill zone” in the start-up space, as described by venture capitalists, where new ventures are not worth funding. Evidence from changes in investment in startups by venture capitalists after major acquisitions by Facebook and Google suggests this is more than a mere theoretical possibility.

Section 1 contains the authors’ model.

The model builds on the assumption that there are two types of customers for digital startups. Early adopters amongst customers (“techies”) choose their favoured platform mainly for its technical characteristics, and have the incentive to uncover the underlying quality of each rival platform. The mass of early techie adopters, in turn, drives the adoption by ordinary non-techie customers by providing a signal about the fundamental quality improvement brought about by the new platform. Techies care primarily about the fundamental technical quality of the platform. However, they also engage deeply with the underlying technology, and as a result they have high switching costs (of learning every minor aspect of any platform they adopt).

Intuitively, if mergers are prohibited an entrant will attract a greater customer base for two reasons. First, anticipating a longer period over which they will enjoy the quality differential, a greater set of techies will switch to the entrant platform. Second, the greater number of techies will generate a greater network externality which will attract an even greater number of ordinary customers. Since an entrant will attract more customers when mergers are prohibited, this new entrant will generate more surplus by itself under this scenario than in the scenario where the merger is anticipated to occur.

If techies expect two platforms to merge, they will be reluctant to pay the switching costs and adopt the new platform early on, unless the new platform significantly outperforms the incumbent one. After all, they know that, if the entering platform’s technology is a net improvement over the existing technology, it will be adopted by the merged entity. Thus, the prospect of a merger will dissuade many techies from trying the new technology. By staying with the incumbent, however, they reduce the stand-alone value of the entering platform. Since the stand-alone value represents the entrant’s reservation value in any merger negotiation with the incumbent, the prospect of a future acquisition can sufficiently reduce adoption by techies, and thus the entrant’s payoff, so as to discourage more entry.

Section 2 looks at the data, while Section 3 discusses the results.

The model presented above explains why banning mergers may positively affect innovation and investment. To assess whether this model works empirically, one would like to study the impact on start-up investments of a decision by antitrust authorities to strike down a big acquisition by a major digital platform. Unfortunately, no such decision has been adopted yet. Instead, the authors have to rely on proxies. They assume that announcements of major acquisitions by digital companies provide signals that a merger will be cleared, and observe the impact of the announcement on investment decisions by related early stage companies. To do so, they extracted from Pitchbook all major acquisitions (more than USD 500 million) by Google and Facebook of software companies between 2006 and 2018. They find nine relevant acquisitions – seven by Google and two by Facebook.

They then use the same data source to determine how much venture capital was invested in start-ups belonging to the same space as the acquired company in the three years prior and after the acquisition. The paper finds that, relative to the mean in the entire software sector, VC investments in start-ups in the same spaces as those of companies acquired by Google and Facebook dropped by 40%, and the number of deals by 43%, in the three years following an acquisition. Similarly, the financing of new startups in the same spaces decreased by 51% relative to the financing of all new start-ups in the software industry.

An alternative explanation for these results is that most of the start-ups that are very similar to the one acquired by Google or Facebook were created with the hope of being acquired by Google or Facebook. Thus, when the two tech giants chose a specific target, the potential alternatives lose financing. To address this concern, the authors look at startups that are in a similar space but are not too close to the space of the acquired ones (so that they cannot be considered perfect substitutes). The decrease in financing is, if anything, even stronger.

Section 4 looks at policy implications.

Allowing incumbent platforms to acquire new entrants enhances ex post efficiency (because bringing all the customers under the same platform will maximise the number of people enjoying the superior technology and network externalities), but may reduce the ex ante incentives to innovate. Thus, the overall welfare implications of allowing mergers depend on the relative importance of pro- and anticompetitive factors. A case-by-case approach will inevitably lead to the antitrust authorities approving all acquisitions, since ex post efficiency considerations would prevail. A blunt non-contingent rule (e.g., no large acquisitions by main incumbent platforms will be allowed) will provide greater predictability of outcomes, stimulating greater innovation, but it can be very costly. Before adopting such a rule, a better understanding of the market is necessary.

A crucial friction in the model is the cost of switching, which is something that regulatory authorities can influence. A simple way to reduce switching costs is to mandate a common standard. Another key friction is the presence of network externalities associated with each competitor’s network. When everyone can get access to the externalities associated with the whole network, there is no distortion in the incentive to innovate because the better product will always prevail. Thus, by forcing interoperability, the regulatory authorities can restore the proper incentive to innovate.

In the digital world, past customer-generated data are crucial to fine tune new products offered to consumers. Thus, incumbent-collected customer data represents an important barrier to entry for newcomers. The greater access entrants have to customer data, the more they can fine-tune their products, leveling the playing field with the incumbent. Thus, default allocation of data ownership is crucial in spurring competition and innovation. The new European data protection rule – also known as GDPR – limits the use of these data by incumbents, and in so doing it reduces the incumbent’s advantage somewhat, promoting innovation. There have also been proposals to allow customers to own their data, and sell it to whomsoever they desire. This would level the playing field, provided data collectors are compensated for their cost of collection, and data intermediaries arise to facilitate storage and sales.

Comment:

This is an interesting paper that revels a bit too much in its catchy title and counter-intuitive results. It achieves the latter by means of a very simplified model – e.g. the authors provide no evidence whatsoever that ‘techies’ play such a prominent role in technology adoption, and the proposition that certain acquisitions reduce innovation incentives rests on rather narrow assumptions. These assumptions not only limit the usefulness of the model, but lead to some odd results as well.

For example, it is unclear to me how the authors can conclude that the absence of innovation in a sector is linked to the levels of venture capital investment without also concluding that mergers are fundamental to promote this type of investment in the first place. To me, their data seems to me to support the idea that the prospects of initial venture capital investment is enhanced by the prospect of a start-up being acquired by an incumbent, and diminishes once the digital incumbents buy a start up in the relevant business/technological segment. This, in turn, is in line with the idea that these markets are consolidating and further investment/entry in those segments makes little business sense – regardless of whether there was a merger or not. Such a development merits attention from policy-makers, but it also seems to indicate that the prospect of acquisition by a digital incumbent currently provides an important incentive for investment and innovation in these sectors – a conclusion which runs against the paper’s argument that the prospect of acquisition by digital incumbents diminishes innovation and investment.

Another odd result is the conclusion that big tech mergers will always be efficient, if considered individually. This conclusion is a rather extraordinary one, and runs against all the literature I have been reviewing recently. It strikes me that the authors could only have reached this conclusion by ignoring the possibility of the acquired product simply being discontinued, or of the incumbent avoiding cannibalisation of its monopoly profits. This is only possible because the authors seem to be conflating innovation, user bases and efficiency – when the concepts strike me as being not only distinct, but as performing different roles within the paper.

Yet, I also understand the point the authors are trying to make with the model: assuming that individual mergers are efficient, are acquisitions by digital incumbents nonetheless detrimental to welfare? This is a valid question, but one that moves us away from looking at individual mergers. Instead (and assuming there is indeed a problem), it indicates that other, more systemic reactions may be required – and, to their credit, the authors go on to discuss them, even if at a very high level. I enjoyed the paper, but I would have liked it even more if it had dealt with these systemic issues in more detail.

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