<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Researchers have acknowledged that the flow of knowledge is influenced by the non-structural and structural features of networks. This paper aims to further develop an understanding of the institutional and structural features of knowledge networks by relating the brokerage roles of actors to the types and locations of organisations in biotechnology and software networks. The study is set within the context of the European Union (EU) research and innovation policy. It is designed as a social network analysis of EU research projects in biotechnology and software that took place between 1995 and 2016, wherein organisations from the Baltic States participated. The results of the study revealed that higher education and research organisations and public bodies acted as the main knowledge brokers and brokered more frequently across different regions in biotechnology networks. In software, it was the universities and research organisations that fulfilled this role. Thus, this study contributes to an understanding about the institutional and structural aspects of knowledge networks by focusing on brokers and their brokerage roles and relating these factors to specific organisation types and the locations of actors within the two sectors. It also adds the empirical context of the Baltic States in the areas of biotechnology and software collaborative research projects to the studies of knowledge networks, and offers practical suggestions for implementing collaborative research projects.</p>
</abstract>

Researchers have acknowledged that the flow of knowledge is influenced by the non-structural and structural features of networks. This paper aims to further develop an understanding of the institutional and structural features of knowledge networks by relating the brokerage roles of actors to the types and locations of organisations in biotechnology and software networks. The study is set within the context of the European Union (EU) research and innovation policy. It is designed as a social network analysis of EU research projects in biotechnology and software that took place between 1995 and 2016, wherein organisations from the Baltic States participated. The results of the study revealed that higher education and research organisations and public bodies acted as the main knowledge brokers and brokered more frequently across different regions in biotechnology networks. In software, it was the universities and research organisations that fulfilled this role. Thus, this study contributes to an understanding about the institutional and structural aspects of knowledge networks by focusing on brokers and their brokerage roles and relating these factors to specific organisation types and the locations of actors within the two sectors. It also adds the empirical context of the Baltic States in the areas of biotechnology and software collaborative research projects to the studies of knowledge networks, and offers practical suggestions for implementing collaborative research projects.

Brokers in Biotechnology and Software Networks in EU Research Projects

TalTech Journal of European Studies

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Brokers in Biotechnology and Software Networks in EU Research Projects"}

Researchers have acknowledged that the flow of knowledge is influenced by the non-structural and structural features of networks. This paper aims to further...

Brokers in Biotechnology and Software Networks in EU Research Projects

Published Online: Jun 17, 2020

Page range: 195 - 236

DOI: https://doi.org/10.1515/bjes-2020-0010

Keywords
brokers, differentiated knowledge base, knowledge networks, social network analysis, brokers, the Baltic States

© 2020 Merle Küttim et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Brokers in Biotechnology and Software Networks in EU Research Projects

Published Online: Jun 17, 2020

Page range: 195 - 236

DOI: https://doi.org/10.1515/bjes-2020-0010

Keywordsbrokers, differentiated knowledge base, knowledge networks, social network analysis, brokers, the Baltic States

© 2020 Merle Küttim et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Keywords
brokers, differentiated knowledge base, knowledge networks, social network analysis, brokers, the Baltic States