Abstract
It is a well-known challenge to assess and know the effectiveness of Innovation Policy in steering the Innovation Systems towards Transformative Change. Still today, impact studies on innovation support usually take a linear approach with limited room for dynamics. This does not take into account that the impacts emerging from the real-world cyclic, complex and long-term innovation process. Moreover, ‘transformations’ are long-term processes that show up in the direction of innovation and human capital development over time. The INNOPACT project is predicated on these more up-to-date assumptions. The project aims to go beyond the production of usual comparable indicators by exploiting new types of micro data and analyses that cover extensive information both on large numbers of individual innovations and S&T-related human capital stocks and flows (big data based), which are widely acknowledged to be key to innovative businesses. We study the long-term effects of public funding for innovation in Finland with help of these extensive micro data, and take these empirical results -along with co-developed process theories from policy-makers- as input for a pilot System Dynamics model if the Finnish Innovation System. This model then allows for ex-ante impact assessment of policy options, looking forward into the future.