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From Knowledge to Innovation: Building the evidence base to inform innovative entrepreneurship and risk-finance policies

Periodic Reporting for period 2 - KNOWINN (From Knowledge to Innovation: Building the evidence base to inform innovative entrepreneurship and risk-finance policies)

Reporting period: 2020-07-01 to 2020-12-31

Creating the right conditions for innovative start-ups to thrive is a priority across all European countries. Innovative start-ups play a crucial role in the creation of radical innovations through research and development. In particular, they may be more effective in introducing advanced digital technologies in fields such as biotechnology and robotics. Beyond the economic benefits, innovative start-ups play a key role in fostering structural changes such as the digital transformation and in addressing important societal challenges such as ageing or climate change.

As primary producers of knowledge, public research institutions play a key role in fostering innovative start-ups. Nonetheless, there are wide differences across regions in the ability of entrepreneurs to commercialize public research. The policy environment likely plays an important role in explaining these differences. From a business dynamics perspective, policies dealing with firm creation, growth, and exit may affect how academics attempt to commercialize public research. The level of development of financial markets, in particular of venture capital finance, and the local environment, such as the stock of knowledge and the quality of physical and technological infrastructure likely also play a role on the extent and location of new ventures.
Surprisingly, only few academic studies examine the relationship between public research efforts, and birth and scaling-up of innovative start-ups. In light of this, this project aims to analyse the role of public research institutions in fostering innovative entrepreneurship; and to examine the role of national policies and framework conditions in catalysing the translation of scientific knowledge into innovative entrepreneurship. The project examines how different dimensions affect the commercialization of public research. At the same time, the project aims to assess the effectiveness of selected policies, such as direct public investment, in addressing the numerous gaps that start-ups building on public research face.
The key activities undertaken to date have focused on the analysis of the core database created in the project.

The analysis of the micro-level database brought several main policy-relevant findings. First, the analysis finds that innovative firms whose founders have a research degree tend to specialize in selected high-tech industries such as biotechnology and artificial intelligence. The evidence also suggests that founders with higher levels of education receive higher funding amounts, a higher number of deals, and have a lower probability of ceasing operations than those with an undergraduate degree.
Second, the results show that research institutions play an important albeit heterogeneous, role in the success of innovative start-ups. Third, the results provide evidence of the importance of “knowledge districts” between public research institutions and firms. More than half of innovative start-ups analysed in this report are located within 1 km of a public research institution.

The analysis of GovVCs brought two main policy relevant findings. First, assessing the role of GovVCs in promoting the transfer of knowledge from the lab to the market, the report finds that GovVCs tend to disproportionately support new technology-based firms (NTBFs) with close ties to academic research. Compared to private VCs, GovVCs are more likely to provide financing to firms whose founders have a research degree (PhDs), to firms whose innovations are more closely grounded in the academic literature, and to firms specializing in fields and technologies that have closer links to academia, such as healthcare and biotechnology. Interestingly, within firms founded by PhD holders, those who also own patents are less likely to receive funding from GovVCs, suggesting that public VCs give priority to early-stage academic start-ups compared to firms at later stage of product development. Second, comparing the financial and innovative outcomes of firms receiving GVC versus those receiving private VC support, the report finds that firms supported by GVC tend to raise lower amounts of VC, are less likely to have a successful exit, and do not differ in the number of patents applied for. While these findings corroborate those reported in previous studies, they do not necessarily imply that GVC is an inefficient tool to help support NTBFs as these differences in performance could well be explained by differences in the characteristics of start-ups selected by GVC and private VC. Indeed, an important contribution of this analysis is to show that non-academic firms drive these differences. When focusing on firms with stronger ties with academia, the results show that academic firms supported by GVC perform as well as academic firms backed by private VC in terms of financial measures, and produce patents of higher quality. This suggests that GVC funding may be more effective when targeted at NTBFs with closer ties to academic research.

A presentation of these findings was shared with delegates of the OECD’s Committee on Industry, Innovation and Entrepreneurship during the CIIE November 2020 meeting as well as a joint European Commission-OECD innovation seminar.
The findings of the project provide novel insights on the factors that contribute to the development of vibrant innovative ecosystems and how these factors affect the transition of ideas from the laboratory to the market. They also inform the policy debate by providing evidence on the characteristics associated with productive innovative ecosystems and may be useful in identifying priority areas or target groups.

By sharing non-technical executive summaries of the main findings of the results of the project with policy makers across countries, the results also contribute to an improvement in the quality of policy decisions in the general area of innovation. Furthermore, the project also provides new indicators to measure venture capital investments and may therefore offer opportunities to collect these type of data on a more coordinated and systematic manner.

Beyond the policy debate, the results from this project contribute to the economic and financial academic literature in several ways. First, they will provide a comparable landscape of innovative ecosystems to study the role that formal and informal channels have on the transmission of academic knowledge to the industry and to assess how these spillovers are affected by geographical, social, and technological distances. In addition, they contribute to the literature that examines the effectiveness of public investments in developing successful start-ups ecosystem and help identify the factors that relate to the successful commercialization of public research.

The project also provide several methodological contributions, including: new open source machine learning models to disambiguate university names, new natural language processing algorithms to identify industries from textual data, and new programs to calculate the technological distance between patents of similar patent classes.