The research field Innovation Dynamics & Modelling shifts attention to the quantitative analysis and modelling of innovation systems and their dynamics. Understanding innovation systems as sets of actors interlinked via joint research and innovation activities, we address questions, like: How can we empirically observe the (spatial, thematic and institutional) development of such systems? How do certain framework characteristics, like e.g. policy interventions, determine their development? How can we measure the performance of an innovation system and their elements (e.g. research actors) by meaningful indicators? Which data can we use to construct such indicators, and how can we collect them?

 

The backbone for our research field is comprised of methodological competencies in advanced quantitative – statistical and mathematical – methods, and the development and maintenance of large scale data infrastructures as a basis for empirical insights into innovation dynamics. With our data infrastructures, we contribute to the largest pan-European research infrastructure on science, technology and innovation studies (risis.eu). Next to the advancement of our established datasets, in particular the EUPRO database R&D networks within the EU Framework Programme (FP), we develop new datasets for different questions using Big Data and Horizon Scanning methods.  

 

Methodologically, we focus on network analytics approaches, e.g. on Social Network Analysis. Further, we use advanced econometric techniques, in particular from spatial econometrics and spatial interaction modelling, to get a better understanding on determinants and drivers of innovation dynamics. To characterise the dynamics of innovation systems a micro-level, we make use of simulation and Agent Based Modelling (ABM) techniques, e.g. for assessing ex-ante the influence of specific policy interventions into innovation systems. An additional methodological focus of our group lies in Science and Technology Mapping, e.g. for identifying emerging research fields and technologies using publication and patent data, or the analysis of trends using Horizon Scanning techniques.  

 

 

 

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