Mostly organised in international collaborative projects, our research uses a social science perspective to analyse

• the production
• structures and dynamics
• effects and impacts
• scenarios
• governance

of technology and innovation.

For example, we investigate research and innovation networks, Science, Technology, Innovation (STI) Policy, technology transfer and entrepreneurship.

Societal key technologies such as digitalisation or biotech and high-potential innovation fields such as energy transition, e-mobility or industry 4.0 are central.

Our research projects use a specific methodological approach: we combine quantitative and qualitative methods of empirical research with methods from Computational Social Science for analysing large datasets (BigData), for visualisation, and for modelling and simulation. For this, we use our computational research infrastructure around the agent-based simulation platform SKIN (Simulating Knowledge Dynamics in Innovation Networks) called TIS-Lab.

Work targets open questions from basic research but also application contexts from

• Scientifically-based policy advice
• Policy modelling
• Technology and innovation management
• Evaluation of research and innovation funding schemes