TY - JOUR
T1 - Creating and Managing EU Funded Research Networks
T2 - An Exploratory Case
AU - Dooly, Zeta
AU - Duane, Aidan
AU - O’Driscoll, Aidan
N1 - Funding Information:
This research adopts a case study approach examining an EU funded research network, called AquaSmart1 (Aquaculture Smart and Open Data Analytics as a Service). It is a high-tech2 information communication technology (ICT) network funded by the EU Horizon 2020 research programme over the period 2016-2018. AquaSmart is using ICT to improve its data utilization and operations. High-tech organisations provide a rich context for the study, given their heavy reliance on network ties that stem from, and are embedded within, social relationships (Larson and Starr, 1993). The high-tech sector of the economy uses the most advanced technology available, it is often seen as having the most potential for future growth and this perception has led to high investment in high-tech sectors of the economy. The European Commission places a large emphasis on its H2020 research programme to foster innovation and competitiveness in Europe through excellence in ICT research and development. The choice of a high-tech context for this case study builds upon recent research on research networks in high-technology industries (Perkmann et al., 2013; Perkmann and Schildt, 2015; Perkmann et al., 2015; Scherngell and Barber, 2011; Scherngell and Lata, 2013; Wanzenböck, Scherngell and Lata, 2015; Hite, 2005).
Publisher Copyright:
© 2022,Electronic Journal of Business Research Methods. All Rights Reserved.
PY - 2022
Y1 - 2022
N2 - The collaborative European funded research and development landscape drives competitiveness among innovative organisations. Recently it has seen the rise of public private partnerships significantly impacting the dynamics of these networks. Thus, the complexity of managing research networks has intensified with the increased diversity of research network members. Additionally, the emergence of the academic entrepreneur has augmented the focus of educational institutions to include innovation and building start-up organisations. The impact of research is scalable if an optimum research network is created and managed effectively. This paper investigates network embeddedness; the nature of relationships, links and nodes within a research network, specifically their structure, configuration and quality. The contribution of this paper extends our understanding for establishing and maintaining effective collaborative research networks. The effects of network embeddedness are recognized in the literature as pertinent to innovation and the economy. Network theory literature claims that networks are essential to innovative clusters such as Silicon valley and innovation in high tech industries. The concept of embeddedness is what differentiates network theory from economic theory. This study adopts a qualitative approach and uncovers some of the challenges of multi-disciplinary research through case study insights. One challenge is competition between network members over ownership and sharing of data. The contribution of this paper recommends the establishment of scaffolding to accommodate cooperation in research networks, role appointment, and addressing contextual complexities early to avoid problem cultivation. Furthermore, it suggests recommendations in relation to network formation, incubation and operations. The network capability is enhanced by the recognition of network theory, open innovation and social exchange with the understanding that the network structure has an impact on innovation and social exchange in research networks and subsequently on research output. The research concludes that the success of collaborative research is reliant upon establishing a common language and understandingbetween network members to realise their research objectives.
AB - The collaborative European funded research and development landscape drives competitiveness among innovative organisations. Recently it has seen the rise of public private partnerships significantly impacting the dynamics of these networks. Thus, the complexity of managing research networks has intensified with the increased diversity of research network members. Additionally, the emergence of the academic entrepreneur has augmented the focus of educational institutions to include innovation and building start-up organisations. The impact of research is scalable if an optimum research network is created and managed effectively. This paper investigates network embeddedness; the nature of relationships, links and nodes within a research network, specifically their structure, configuration and quality. The contribution of this paper extends our understanding for establishing and maintaining effective collaborative research networks. The effects of network embeddedness are recognized in the literature as pertinent to innovation and the economy. Network theory literature claims that networks are essential to innovative clusters such as Silicon valley and innovation in high tech industries. The concept of embeddedness is what differentiates network theory from economic theory. This study adopts a qualitative approach and uncovers some of the challenges of multi-disciplinary research through case study insights. One challenge is competition between network members over ownership and sharing of data. The contribution of this paper recommends the establishment of scaffolding to accommodate cooperation in research networks, role appointment, and addressing contextual complexities early to avoid problem cultivation. Furthermore, it suggests recommendations in relation to network formation, incubation and operations. The network capability is enhanced by the recognition of network theory, open innovation and social exchange with the understanding that the network structure has an impact on innovation and social exchange in research networks and subsequently on research output. The research concludes that the success of collaborative research is reliant upon establishing a common language and understandingbetween network members to realise their research objectives.
KW - Case study
KW - Network theory
KW - Research networks
KW - Structural embeddedness
UR - http://www.scopus.com/inward/record.url?scp=85125538540&partnerID=8YFLogxK
U2 - 10.34190/ejbrm.20.1.2556
DO - 10.34190/ejbrm.20.1.2556
M3 - Article
AN - SCOPUS:85125538540
VL - 20
JO - Electronic Journal of Business Research Methods
JF - Electronic Journal of Business Research Methods
SN - 1477-7029
IS - 1
ER -