DS0801 - Rapport au risque et innovation sociale

University Technology Transfer & its Optimization – UTTO

University Technology Transfer and its Optimization

Though it is often assumed that university-generated knowledge contributes to innovation and thus to long-term economic growth, the social mechanisms and policies which ultimately favor academic inventions and achieve their transfer to the economy are still to be uncovered. Thanks to the creation of a nation-wide database, the project analyzes new dimensions of academic knowledge and technologies production and their transfer to the economy, with a special focus on the impact of science policy.

Towards an enriched view of academic knowledge and technology transfer and of science policy

After the WWII, the public funding of Open Science, a dedicated non-market social institution, was mostly justified by market failures due to the non-appropriability of fundamental research. Its contribution to the economy was most often only conceptualized as a “knowledge spillover”. The understanding of the social arrangements and the design of efficient policies and that would actually favor the transfer of scientific knowledge was limited. As stakeholders perceived academic knowledge and technologies were under-exploited, a “new standard policy model” has been introduced (Bayh-Dole Act) granting US universities the rights over inventions stemming from federally-funded research and therefore conferring them the role of managing the transfer –to their own profit. Other “local models” were progressively abandoned worldwide to adopt equivalent legislations under the alleged superiority of this new model. It is however not clear whether this new model is optimal as it may reduce professors’ incentives to innovate and discourage contractual research collaborations with industry. Further, the sole focus on technology transfer has hidden the fact that other science policies such as blue-sky project based funding or clusters of excellence programs may efficiently stimulate academic inventions, when properly designed. <br /><br />The UTTO project analyses the production and the transfer of academic knowledge and inventions in its richer context. It reconsiders, on clear and precise empirical grounds, fundamental questions such as: To what extent researchers and professors invent directly or produce knowledge which is directly used in patents? How is this affected by tech transfer policy? Is there a relation between research excellence, novelty and risk taking on the one hand and societal impact on the other hand? How does science funding ultimately affect invention, companies R&D and innovation?

UTTO project builds a nation-wide data set on French academic research. Those data allow us to document the research activity of nearly all tenured researchers and professors employed in universities and research institutes till year 2016. Research activity (labs), publication information (WoS data), patent data (Patstat), research and consultancy contracts with companies (universities and research institutes), project funding (ANR), PIA clusters of excellence (LabEx) and universities of excellence (IdEx) policies are matched at the individual level.

This database allows us 1/ to appreciate new dimensions the production of scientific knowledge and technologies, and 2/ to better trace and quantify direct contributions of academic research to the economy.

The methods used in this project fall essentially under the “quantitative data analysis” umbrella. When possible, we make an extensive use of control/case analyses to identify the impact of some policies on agents relying on observational data.

The specific research projects performed in this project can synthesized around the following two dimensions:

1/ Appreciate new dimensions the production of scientific knowledge and technologies:

We show how networks (Bergé, Carayol, and Roux, 2018) and teams (Akcigit et al, 2018) affect research productivity; We propose a new measurement of novelty in science and discover its relation to impact (Carayol, Lahatte and Llopis, 2018); We analyze the relation between risk aversion and risk taking and scientific and technological outcomes (forthcoming); We reinterpret the relation between knowledge complexity and interdisciplinarity (Carayol and Maublanc, 2018); We analyze the selection of research projects (Lanoe, 2018) and the impact of different funding instruments in science (Carayol and Lanoe, 2018; Carayol and Henry, 2019).


2/ Better trace and quantify direct contributions of academic research to the economy:

We analyze which researchers produce patented inventions in France and the impact of changing tech transfer policy (Carayol and Carpentier, 2018); We show how professors influence technology transfer (Carayol and Sterzi, 2018), the impact of transfer management (Sterzi, Lissoni and Pezzoni, 2018) and of IP policies (Sterzi and Martinez, 2018); We assess to what extent and which scientific articles are directly cited in patents (Carayol, Tijssen and Winnink, 2019); We analyze research contracts of public labs with industry (Bianchini, Llerena and Patsalis, 2018) and how it affect companies productivity (Carayol, Carpentier and Roux, 2019); We analyze the impact of project funding on invention (Carayol, Carpentier and Roux, 2019) and the impact of excellence clusters program on employment R&D (Henry, Monras and Sapanos, 2018).

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Economists, as well as policy-makers, agree nowadays that university-generated knowledge contributes decisively to the economic growth of nations and local economies. The Bayh-Dole Act introduced in the US in the early 80's, was the key policy initiative aimed at encouraging the commercialization of academic research results. Many observers suggest that the recent technological success of the USA owes a lot to this new “commercial model” of university technology transfer. Similar reforms have now been initiated in many advanced countries and most research universities and public research organizations have set up technology transfer offices (TTOs) which commercialize academic knowledge and manage the rights. France in particular, has adopted a series of policy reforms progressively introducing this new model, aiming at improving the social and economic returns of academic research.

We show in this proposal, thanks to a first investigation of the French data that we intend to expand and reliabilize in this project, that if public patenting has significantly raised in the last decade (up to 14% of all patent families in 2012), it is mainly due to a sharp modification in the ownership structure of academic patents that is accompanied by a contrasted evolution of their quality indicators. These first results stress a series of interesting questions that we will address in this project. Are traditional academic incentives aligned with this new goal of contributing to technology transfer? Are the different scenarios of technology transfer associated with different levels of effectiveness, and if so, why? What are the impacts of the recent changes of the legislation and of new policy instruments on technology transfer?

To answer these questions, we need to rely on a consistent micro-economic understanding of the new commercial model of university technology transfer, at the interplay between the three typical actors of the transfer: the professor (or researcher), the TTO and the company. On the empirics side, we need to rely on very recent, and very complete data. Therefore, we will match, at the professor and researcher level, individual information, patent data, publication data and project funding data. To some extent, France will be considered as a case study in itself. No such precise and complete empirical analysis has already been performed in any large industrialized country. A survey of academic inventors, interviews of TTO CEOs, as well as case studies on the Bordeaux and Strasbourg sites will complement our information when national wide data are not available.

So as to contribute to the policy debate on technology transfer, we will identify the impact of policy initiatives which target only some part of the reference population and evidence the differential behavior of “treated” and their controls. We will also expand our investigations to the European level and exploit cross-country policy variations in time. Our goal is to provide robust policy recommendations to improve (tentatively optimize) university technology transfer.

The team members are experts on the issue of academic patenting and technology transfer. They are spread over four sites, but many of them have already collaborated in the past. The cohesiveness of the team, including the strong reliability of the connection with the OST (as data provider) will ensure a timely execution of the project. New collaborations will also be undertaken, by matching, in this project, expertises on microeconomic theory, professional practices, applied micro-econometrics, identification techniques for observational data, and different data collection methods. The project should, in addition, significantly contribute to building a strong French research base on university technology transfer, in connection with policy makers, practitioners and students.

Project coordinator

Monsieur Nicolas CARAYOL (Groupe de Recherche en Economie Théorique et Appliquée)

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.

Partner

GRETHA Groupe de Recherche en Economie Théorique et Appliquée
CNRS-CES (UMR8174) CES - Centre d'Économie de la Sorbonne (UMR8174 CNRS/UP1)
FNSP Fondation Nationale des Sciences Politiques
BETA - UNISTRA Bureau d'Economie Théorique et Appliquée
CES (CNRS DR PARIS B) CES - Centre d'Économie de la Sorbonne

Help of the ANR 283,760 euros
Beginning and duration of the scientific project: November 2015 - 36 Months

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