Scale-free growth in regional scientific capacity building explains long-term scientific dominance


The regional capability of performing front-running research and technological development has been identified as a necessary condition for future wealth creation.

The quality and amount of scientific capabilities in specific fields vary dramatically across different world regions. Capabilities, knowledge, and skills are embodied by scientists working in research institutions or companies. The conditions for the emergence of a leading regional scientific environment – and the resulting early technological leadership – are poorly understood. The existence of a critical mass – the threshold above which a region can build comparably strong scientific capabilities – of scientists is often assumed.

Using a unique dataset of global scientific activity and researcher mobility over several decades, we present empirical evidence in three scientific areas (semiconductor research, embryonic stem cells, and Internet research) that the process of scientific knowledge accumulation is remarkably general and applies to practically all regions.

Regional knowledge accumulation data  obtained from an analysis of scientists’ geolocated trajectories follow a preferential attachment mechanism characterized by a sub-linear kernel with a robust growth exponent. Scale-free growth patterns suggest that regions that move early into new technologies tend to dominate the corresponding scientific fields.

We find no evidence that critical mass is required to achieve prolonged scientific dominance.

We propose a simple preferential attachment model that explains the empirical data and allows us to understand deviations from the growth exponent as focused interventions to strategically attract scientists at regional level.

We demonstrate this explicitly for China in the three scientific fields examined.

V.D.P. Servedio, M. R. Ferreira, N. Reisz, R. Costas, S. Thurner, Scale-free growth in regional scientific capacity building explains long-term scientific dominance, Chaos, Solitons & Fractals 167 (2023) 113020