OECD Science, Technology and Innovation Outlook 2018
Adapting to Technological and Societal Disruption
The OECD Science, Technology and Innovation Outlook 2018 is the twelfth edition in a series that biennially reviews key trends in science, technology and innovation (STI) policy in OECD countries and a number of major partner economies. The 14 chapters within this edition look at a range of topics, notably the opportunities and challenges related to enhanced data access, the impacts of artificial intelligence on science and manufacturing, and the influence of digitalisation on research and innovation. The report also discusses the shortcomings of current policy measures, how the Sustainable Development Goals are re-shaping STI policy agendas, and the need for new - more flexible and agile - approaches to technology governance and policy design. While these disruptive changes challenge policy makers in a number of ways, the digital revolution underway also provides solutions for better policy targeting, implementation and monitoring.
This report relies on the latest academic work in the field, research and innovation statistical data, as well as data on wider trends and issues. It makes extensive use of country responses to the 2017 EC OECD STI policy survey (https://stip.oecd.org) and features contributions by renowned experts and academics to broaden the debate and provide more personal, sometimes controversial, angles to it.
Also available in: French
Mixing experimentation and targeting: innovative entrepreneurship policy in a digitised world
Innovative entrepreneurship plays a key role in our societies, being an engine of job creation, innovation, and inclusiveness. In light of that, policy makers are aware of the importance of creating a fertile entrepreneurial ecosystem. However, only a tiny minority of new firms eventually becomes a successful innovative business. Improving the prediction of this success ex ante would allow governments to target their support to start-ups, and could alter the balance between targeted and non-targeted (e.g. reducing entry and exit barriers) policy approaches. This chapter first presents the main arguments in favour of public support to innovative entrepreneurship. It then discusses how newly available big data and machine learning techniques could help policy makers design more effective policies through more precise targeting of firms with the highest growth potential. The chapter then focuses on venture capital, which, besides filling the equity gap, also aims to target these innovative firms. It concludes with a discussion of the factors that will affect the balance between targeted and non-targeted policies in the future.
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