The role and the position of the Hungarian counties in research collaboration networks

Abstract

The main drivers of long-term economic growth are technological progress and innovation, which are increasingly built on collaborative relationships embedded in knowledge networks. However, such cooperation manifests through different channels and across different types of institutions. In this study, we examine the research cooperation links of the Hungarian NUTS 3 regions (counties) based on their participation in the projects of three Framework Programs (1999-2017) Pnanced by the European Union. We map the cooperation links between the regions with the help of a multi-layer network in order to explore the specificities between the different types of institutions (companies, higher education institutions, government institutions, research institutions). Data on framework program collaboration is extracted from the Cordis dataset and inter-regional links are defined on this basis as joint participation in a given funded research project. This way we can proxy knowledge spillovers across institutions which are participants in these projects. The knowledge network built from these inter-regional links is then examined using network analytic tools in order to explore the structure of the complex cooperation links in more depth. The primary focus of the paper is to differentiate between the network connections (dimensions) observed across diRerent types of institutions. In addition to the number of cooperation links of the Hungarian regions along each dimension (institution-type pairs), we also examine the density of cooperation (proportion of observed collaborative connections relative to all possible relations). Moreover, we measure the average distance of the regions in network terms, i.e. the number of links through which knowledge can be accessed by a given region. The results of the network analysis show that the role of different types of institutions in the cooperation network differs significantly in every region in terms of the flow of information. Moreover, the number of cooperation links in Budapest is outstandingly high, and these connections have been built across a wide range of European regions. But the high number of connections in Budapest and Pest county is also due to the concentrated presence of institutions in the region. Two important conclusions can be drawn from the results. First, different types of institutions play different roles in knowledge spillover. In Veszprém county and Borsod-Abaúj-Zemplén county, companies play a prominent role, while in Baranya county, higher education institutions, in Csongrád-Csanád county, research institutions and in Bács-Kiskun county, government institutions are the main sources of the interregional knowledge spillover. The analysis also highlights the important role of scientific co-operation in higher education institutions and research institutes (Baranya, Hajdú-Bihar, Győr-Moson-Sopron, and Csongrád-Csanád). Finally, we point out that some regions (Heves, Nógrád, Tolna, Jász-Nagykun-Szolnok, Szabolcs-SzatmárBereg) have developed less cooperative relations and less access to knowledge.