European Knowledge Neighbourhood: Knowledge Production in EU Neighbouring Countries and Intensity of the Relationship with EU Countries

Abstract

This study aims to analyse the creation of knowledge in the European neighbourhood and the diffusion of knowledge among EU countries and European neighbouring countries (ENCs). We first collate different indicators of knowledge production and diffusion in order to characterise the main feature of ENCs. In this respect, we contribute not only with an overview of potential knowledge interactions between EU and ENCs, but also suggest original ways to account for the different facets of knowledge diffusion. We use these indicators to assess the efficiency of ENC and EU in their use of knowledge resources, relying on data envelopment analysis (DEA). Contrary to the rare DEA studies in the field, inputs are both internal and external. The results show that, despite their weakness, ENCs may benefit from their orientation towards the EU for access to external knowledge, with some of them successfully turning their rare knowledge resources into knowledge creation and innovation.

Cross-border knowledge transfer and innovation in the European neighbourhood: Tourism cooperation at the Finnish-Russian border

“…However, despite differences between border regions, the EU's external border regions do also share common features, for example, in terms of their (poor) economic performance and (weak) knowledge transfer links (Petrakos & Topaloglou, 2008;Autant-Bernard et al, 2017). Therefore, even if it is not possible to generalise the research results gained in one external border region to all the others, the experiences and lessons learnt in the Finnish-Russian CBR can be reflected upon and provide insights for understanding the relationships between other border regions in the EU external border context.…”

“…Based on the previous discussion, it would seem that initially many of the EU's external borders, such as the Finnish-Russian CBR, are at a disadvantage (technological gap; low permeability; low similarity) in terms of their prospects for cross-border innovations, but have definite potential in developing these (due to cross-border differences). Indeed, earlier studies have shown that, while the EU has gradually been integrating in terms of its internal science, technology and innovation cooperation (Scherngell & Lata, 2013;Makkonen & Mitze, 2016), the situation is quite different when it comes to collaboration with its neighbours (Autant-Bernard et al, 2017). An important factor influencing this is access to EU funding; Makkonen and Mitze (2016), for example, have shown how the new member states of the EU have been able to boost rapidly their cross-border scientific collaboration with the established EU members after joining the EU, and have gained access to improved research funding.…”

“…An important factor influencing this is access to EU funding; Makkonen and Mitze (2016), for example, have shown how the new member states of the EU have been able to boost rapidly their cross-border scientific collaboration with the established EU members after joining the EU, and have gained access to improved research funding. Contrarily, when it comes to knowledge transfer, a recent study by Autant-Bernard et al (2017), for example, has shown that knowledge diffusion between the EU and its neighbours has remained weakly developed. This applies also for the situation between Finland and Russia, where "genuine innovation activity aiming at jointly creating new products and services is still in its infant stage", and cooperation is dominated by rather unilateral flows of (high-tech) products and knowledge from Finland to Russia (Liuhto, 2011: p.164).…”

Economic drivers and specialization patterns in the spatial distribution of Framework Programme's participation

“…In this field, findings show a clear emergence of transnational R&D dynamics, but anchored in ‘core’ regions where FP participations tend to concentrate (Breschi and Cusmano ; Protogerou et al ; Heller‐Schuh et al ; Scherngell and Barber ; Hoekman et al ). In this core‐periphery geography, some sub‐clusters of co‐operation have been identified providing a more complex picture (Autant‐Bernard and Chalaye ). This literature identified a progressive polarization in favour of some nodes, which are nevertheless open to co‐operate with newcomers (Protogerou et al ; Heller‐Schuh et al ; Hoekman et al ).…”

A new social network analysis-based approach to extracting knowledge patterns about research activities and hubs in a set of countries

“…In [45], the author shows that both the links and the h-indexes of co-inventors and co-authors highly enhanced the flows of academic knowledge into industrial patents in South Africa's firms, as well as knowledge diffusion in large R&D and innovation clusters and hubs. In [12], the authors investigate the diffusion of European knowledge. Specifically, they analyze the diffusion of knowledge between European countries and European Neighboring Countries (ENCs).…”