The Network Law Review is pleased to present you with a Dynamic Competition Initiative (“DCI”) symposium. Co-sponsored by UC Berkeley, EUI, and Vrije Universiteit Amsterdam’s ALTI, the DCI seeks to develop and advance innovation-based dynamic competition theories, tools, and policy processes adapted to the nature and pace of innovation in the 21st century. The symposium features guest speakers and panelists from DCI’s first annual conference held in April 2023. This contribution is co-authored by Johannes M. Bauer, Quello Chair in Media and Information Policy at Michigan State University, and Tiago S. Prado, Research Fellow at the Quello Center, Michigan State University.
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Start-up acquisitions by larger technology firms, including by “big techs” such as Google, Amazon, Apple, Facebook, and Microsoft, were long regarded as an integral part of innovation in fast-paced, high-technology sectors. For entrepreneurs and venture capital investors, a sale to big tech companies offered an attractive option to realize the value of accumulated intangible capital and a return on start-up investment. With their vast technology infrastructures and reach, big tech companies offer capabilities to scale products and services quickly to large numbers of consumers. They can accelerate the process to market and facilitate growth beyond the critical threshold required for sustainable operations.
Integrating knowledge from start-ups also makes sense from an innovation perspective. Innovation is best conceptualized as combination and recombination of knowledge, a directed search into an unknown space of technological opportunities (Arthur, 2009). Novelty is often embedded in tacit, private knowledge that cannot yet be codified. It therefore cannot be patented and exchanged in markets. Acquiring a start-up is a rational strategy to diversify innovation searches into directions that complement a firm’s own activities. It is not necessary that the start-up is continued as a brand or an organizational unit for these benefits to materialize. Often, start-up knowledge and capabilities will be integrated with the existing stock of explicit and tacit knowledge. Even if part of the new knowledge is not developed further, innovation overall may advance.
During the past few years, these benefits have been reevaluated critically and often discounted. Instead, the potential negative effects of aggressive acquisition strategies by big tech players have received most of the attention. Some observers are concerned that the existence of big techs may narrow the direction of innovation. If entrepreneurs aim at a sale to a big tech firm, they will seek to innovate in similar technologies at the cost of pursuing bolder, disruptive innovations (Callander & Matouschek, 2022). Others are concerned that the rationale of start-up acquisitions has changed over time. Whereas initially acquisitions may have accelerated innovation, as a platform grows their incremental value may diminish, creating a moral hazard-like problem (e.g., Cusumano et al., 2021). Consequently, acquisitions might increasingly be used as defenses of an established market position against potentially disruptive innovators. In extreme cases, such acquisitions may be systematically and strategically abused to create “kill zones”, a protective area around big tech operations into which neither start-ups nor venture capital dare to veer (Cunningham et al., 2021; Kamepalli et al., 2020).
These are all possible outcomes of dynamic competition in complex technology sectors. Empirical support for some of these claims is often limited to a small number of case studies. Focusing on specific cases is an important first step, but more robust evidence based on a larger number of cases is needed to assess the plausibility of the scenarios. Our research seeks to contribute to a more solid evidentiary basis for these important discussions. It analyzes 32,367 venture capital deals worldwide, including 392 big tech start-up acquisitions by Google, Facebook, Amazon, Apple, and Microsoft. A dataset of quarterly observations was assembled from CB Insights data (accessed via our university license). The data documents venture capital activity and related transactions, such as initial public offerings (IPOs) and venture capital-backed mergers and acquisitions, between 2010 and 2020.
We were interested in the effects of big tech acquisitions on venture capital funding for other start-ups. Particularly, we wanted to examine whether acquisitions were associated with a pattern of diminished funding and fewer deals, as suggested by the kill zones argument. Such funding is an important factor influencing innovation in start-ups, in addition to the appropriability conditions, the contestability of an activity, the dynamic capabilities of the start-ups and other factors known to affect innovation (Bauer & Prado, 2023). Absent measures of innovation output, such as patents, for most start-ups, we used venture capital funding as a proxy for accessible resources to support innovation broadly construed, including for the development of new products and services and their commercialization in the market.
Empirical analysis of the rich and complex dataset needed to overcome several challenges. Venture capital investment (“treatment”) could occur in one or more quarters during the observation period and with variable breaks in between rounds of funding. Two statistical approaches were employed to deal with these issues. A two-way fixed effects Poisson estimation with covariates served to examine the response of venture capital activity to an increased level of big tech acquisitions in each e industry segment. An innovative approach developed by Imai et al. (2021) was employed to overcome the challenges of staggered and variable funding. This dynamic difference-in-differences (DiD) setup allowed examining the causality of the observed relations.
The findings offer numerous nuanced insights for the effects of big tech acquisitions in the United States, Europe, and worldwide activities (see Prado & Bauer, 2022 and Prado, 2023 for more details). Controlling for other factors, such as IPOs and general M&A activity, we find statistically significant positive effects of big tech start up acquisitions on venture capital funding and on the number of venture capital deals across the examined sectors. In other cases, we find positive associations that are not statistically significant at the conventional levels. These effects materialize mainly in the two quarters following an acquisition. They vary over time and typically fade out after a few quarters. Importantly, contrary to the kill zone argument, we do not find any evidence of a systematic pattern of reduced venture capital funding or fewer venture capital deals. This does not exclude that such effects may exist in certain cases, but it questions whether this is a general pattern that holds across many cases.
Worldwide, the number of venture capital deals increased by 20.1% in the four quarters following a big tech acquisition. The effect on funding was positive but not statistically significant. In the United States the number of deals went up 21.1% and funding 30.7%. In Europe, funding increased by 130.6%, but the positive effect on the number of venture capital deals was not statistically significant. The effects are more consistent in the United States, but the response of venture capital funding is stronger for Europe. This seems to suggest that big-tech start-up acquisitions are seen by other players as a signal for increased future interest in an area. Not surprisingly, this signaling function is weaker in the United States with its vibrant venture capital market.
To examine whether the observed effects are causally related to big-tech start-up acquisitions, we examined the average treatment effects with a DiD approach. Given the complex patterns of treatments, this required first to define an appropriate, synthetic control group with the same treatment history up to a certain point before the treatment. Once that control set was established, we could employ a propensity matching procedure to define a counterfactual, which could be used in the DiD estimation.
Considering only deals in the United States or in Europe, the patterns were weak. In the United States, we detected statistically significant positive effects for the first treatment. However, we did not detect statistically significant effects when all treatments were considered. For the European region, we found positive effects for the first quarter after treatments when all treatments were considered. In contrast to the United States, we did not detect statistically significant effects for the initial treatment. Despite the lower number of statistically significant findings in this part of the analysis, it is important to emphasize that we did not uncover evidence of systematic negative effects.
In contrast to these regional analyses, the analysis consistently found statistically significant average effects on a worldwide level. Big tech start-up acquisitions have positive effects on the total number of venture capital deals, the total amount of venture capital funding, and the average amount of venture capital funding per deal in treated industry segments. Higher effects were found in the first quarter whereas the effects tapered off in subsequent quarters. Similarly, the first acquisition in an industry segment had higher effects on venture capital funding than subsequent ones. Our analysis shows that these positive, global effects are explained by cross-regional effects. For example, acquisitions in the United States contribute to higher venture capital funding in Europe and Asia in an industry segment. This suggests that big tech acquisitions in one region are used as a signal by investors in other regions.
What does all this mean for the current policy discussion on merger policy in digital platform industries? The absence of evidence of kill zones across many start-up acquisitions does not imply that they do not exist or that the lenient merger policy of recent decades was the correct policy approach. However, it raises serious concerns about proposals, currently advanced by proponents of precautionary merger enforcement, that would prohibit big-tech acquisitions altogether. Although we detect robust positive effects of big-tech acquisitions on venture capital funding for competing start-ups, they are typically short-lived. This does not imply that they cannot have lasting effects on innovation activity, which may be boosted by multiple spurts of additional venture capital funding. However, a conclusive answer to this question would have to examine innovation outcomes in addition to inputs to the entrepreneurial process. All this suggests that big tech acquisitions play an important, and largely positive, role in the bigger, dynamic competition ecosystem.
Our analysis provides an aggregate view. Although we have not developed it in that direction, it might be able to assist in the evaluation of specific merger cases, for example, by assessing the historical track record of acquisitions by a platform. Rational merger policy, therefore, needs additional tools to discern cases in which the positive effects of an acquisition are likely to prevail from cases in which this is unlikely. Doing this well requires bringing theories of dynamic competition (e.g., Petit & Teece, 2021), appropriate theories of innovation (e.g., Bauer & Prado, 2023), and the application of rigorous principles of decision making under uncertainty to individual cases.
And it requires a more differentiated approach to the design of rules to govern markets with high levels of uncertainty. Other things being equal, policy regimes that are flexible to adapt as new information becomes available will outperform those that are built around rigid ex ante rules. This suggests that per se rules, non-rebuttable presumptions about the undesirability of certain behaviors, and narrowly construed regulations and legislation are generally poor instruments for the digital economy. The art of institutional design is to find constitutions for digital markets that remain flexible and adaptable.
Johannes M. Bauer & Tiago S. Prado
References
- Arthur, W.B. (2009). The nature of technology: What it is and how it evolves. Free Press.
- Bauer, J.M., & Prado, T.S. (2023). Digital innovation: An information-economic perspective. In: D.R. Raban & J. Włodarczyk (Eds.), The Elgar companion to information economics. Edward Elgar.
- Callander, S., & Matouschek, N. (2022). The novelty of innovation: Competition, disruption, and antitrust policy. Management Science, 68(1), 37-51.
- Cunningham, C., Ederer, F., & Ma, S. (2021). Killer acquisitions. Journal of Political Economy, 129(3), 649-702.
- Cusumano, M.A., Gawer, A., & Yoffie, D.B. (2021). Can self-regulation save digital platforms? Industrial and Corporate Change, 30(5), 1259-1285.
- Imai, K., Kim, I.S., & Wang, E.H. (2021). Matching methods for causal inference with time‐series cross‐sectional data. American Journal of Political Science. Published online 11 December 2021, https://doi.org/10.1111/ajps.12685.
- Kamepalli, S.K., Rajan, R., & Zingales, L. (2020). Kill zone. National Bureau of Economic Research. Working Paper Series No. 27146. http://www.nber.org/papers/w27146.
- Petit, N., & Teece, D.J. (2021). Innovating big tech firms and competition policy: Favoring dynamic over static competition. Industrial and Corporate Change, 30(5), 1168-1198. https://doi.org/https://doi.org/10.1093/icc/dtab049.
- Prado, T.S. (2023). Digital platform economics: Essays on innovation effects, assessment of market power, and policy approaches to promote competition. Ph.D. Dissertation, Michigan State University.
- Prado, T.S., & Bauer, J.M. (2022). Big tech platform acquisitions of start-ups and venture capital funding for innovation. Information Economics and Policy, 59, June, 100973. https://doi.org/10.1016/j.infoecopol.2022.100973.
| Citation: Johannes M. Bauer & Tiago S. Prado, “Big-Tech Acquisitions and Venture Capital Funding for Start-ups”, Network Law Review, Summer 2023. |
