Indicator: Knowledge Concentration Index

The concentration-per-population index is the Gini index. High values of the indicator show a high spa-tial concentration of flows, and low values show a low spatial concentration of flows in a given region.
In the knowledge basket the concentration of H2020 project flows is particularly high in Central and Eastern Europe, while the more differentiated H2020 flows are in strong, network-forming centers such as Madrid, Paris, Catalonia, and southeastern Germany. In the case of patents, there is greater variation in concentration in the ESPON space. In Central and Eastern Europe, there is still a very strong concen-tration, probably because the number of patents is small and there are no numerous networks of flows. The greatest diversification of patent links is visible in France and northern Italy. Interestingly, the con-centration is relatively higher in the patent "basin", i.e. western Germany and Switzerland. The Erasmus program is characterized by a highly mosaic-like spatial pattern in the concentration of flows. Regions with a high concentration are adjacent to those in which the flow is dispersed. Regions with spatially diversified networks of connections in the Erasmus program include the whole of Finland, Warsaw, and the Małopolskie voivodeship with Kraków in Poland and Andalusia, Valencia, and Castile in Spain.
The synthetic matrix of flows within the knowledge basket indicates a large differentiation in the con-centration of flows between neighboring countries and regions. For example, knowledge flows are spa-tially dispersed in Finland, and quite concentrated in Norway. Similarly, the flow is spatially diversified in Poland’s Warsaw and Krakow, mainly because of the network of connections in the Erasmus program, and it is strongly concentrated in eastern Poland, as well as in Romania, Bulgaria, and Greece. In the ESPON space, the largest areas with highly dispersed knowledge flows are Spain, France, and the north of Italy, although even in these countries there are single regions with a strong concentration of flows, e.g. Extremadura. This leads us to conclude that knowledge flows are to a large extent based on a lim-ited number of nodes (university cities, research and development centres and regions). It is with them that most other regions are linked. They are often dominated by relations with one region: the node. As a result, the concentration of knowledge flows is high.