Abstract
Modelling the complex nature of regional knowledge creation is high on the research agenda. It deals with the identification of drivers for regional knowledge creation of different kinds, among them inter-regional networks and agglomeration factors, as well as their interplay; i.e., in which way they influence regional knowledge creation and accordingly, innovation capabilities—in the short- and long-term. Complementing a long line of tradition—establishing a link between regional knowledge input indicators and knowledge output in a regression framework—we propose an empirically founded agent-based simulation model that intends to approximate the complex nature of the multi-regional knowledge creation process for European regions. Specifically, we account for region-internal characteristics, and a specific embedding in the system of region-internal and region-external R&D collaboration linkages. With first exemplary applications, we demonstrate the potential of the model in terms of its robustness and empirical closeness. The model enables the replication of phenomena and current scientific issues of interest in the field of geography of innovation and hence, shows its potential to advance the scientific debate in this field in the future.
Highlights
Understanding and explaining the complexities of regional knowledge creation constitutes an ongoing challenge for empirical scholars in regional science
Complementing a long line of tradition—establishing a link between regional knowledge input indicators and knowledge output in a regression framework—we propose an empirically founded agent-based simulation model that intends to approximate the complex nature of the multi-regional knowledge creation process for European regions
We demonstrate the potential of the simulation model by means of three small example applications derived from current scientific debates
Summary
Understanding and explaining the complexities of regional knowledge creation constitutes an ongoing challenge for empirical scholars in regional science. Modelling regional knowledge creation follows a long line of research tradition, often applying the Knowledge Production Function (KPF) framework to model determinants of regional knowledge creation and innovation [7,8,9] These studies typically attempt to establish a direct link between some kind of regional knowledge input, such as industrial and university R&D, and knowledge outputs measured in terms of patents, innovation or publication counts (see e.g., [7,10,11,12]) In this context, the role of knowledge spillovers [8,13,14], spatial proximity [15,16,17], and nonspatial forms of proximity [18,19,20] on regional knowledge creation and innovation are widely studied. Considering these aspects allows the observation of emergent phenomena such as specialisation and concentration tendencies in regional knowledge creation driven by the structure of R&D collaborations
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
