The thematic area Innovation Systems Modelling constitutes one research focus in the business unit RTI-policy, shifting attention to the quantitative analysis and modeling of innovation systems. We focus on the conception, implementation and interpretation of models for innovation systems to understand the relationships between their different components, and to draw corresponding conclusions suited to RTI-policy. We particularly put emphasis on interactions within the innovation system, i.e. networks of innovating actors, and on dynamics of the innovation system, i.e. the evolution of local and global characteristics, such as the thematic and spatial development of the innovation systems and its determinants.

The backbone for our research in the thematic area constitutes, on the one hand, methodological competencies in advanced quantitative – statistical and mathematical – methods and, on the other hand, large scale data infrastructures as a basis for empirical insights into innovations systems. Given our strong focus on networks in innovation systems, methods from social network analysis and complex network analysis are central in our research. Further, we rely on advanced econometric methods, particularly spatial econometrics and spatial interaction modelling techniques, to model the influence of exogenous factors on specific innovation system characteristics, such as knowledge production intensity evidenced by patenting activities. To address such questions from a micro perspective, the thematic area also develops and applies Agent Based Modelling methods, enhancing our understanding of the potential impacts of different kinds of policy interventions on innovation systems.

Without suitable data, meaningful quantitative analysis or modelling of innovation systems is impossible. Thus, the thematic area also puts major efforts into developing, maintaining and using large-scale data infrastructures that can be used to measure different aspects of innovation systems. The most prominent example is the EUPRO database on R&D projects, which enables us to empirically trace the pan-European network of actors jointly performing EU-funded R&D. In addition, we use patent databases and publication databases to grasp other types of innovation activities, while we also conduct surveys to gather quantitative empirical insights into more specific aspects of the innovation system.