Exploring the configuration and management of an EU funded research network

The objective of this research is to investigate social and economic aspects of structural embeddedness in an ICT research network based in the European Union. The effects of network embeddedness are recognized in the... [ view full abstract ]

The objective of this research is to investigate social and economic aspects of structural embeddedness in an ICT research network based in the European Union. The effects of network embeddedness are recognized in the literature as pertinent to innovation and the economy (Gilsing et al., 2008; Owen-Smith and Powell, 2004; Rowley et al., 2000). This paper focuses on the configuration and management aspects within the network.

The contextual setting for the study is a European funded research network, specifically, the AquaSmart[1]  network, a project funded by the European Commission Horizon 2020 research programme that converges aquaculture and technology.  A single case study approach is adopted as a suitable method to investigate this phenomenon in its natural context, as it enables the capture of the subjective and contextual experiences of the participants, supported by in-depth interviewing and documentation analysis. Data is analysed using both manual and computer assisted methods (NVivo) based on the Miles and Huberman (1994) and Braun and Clarke (2006; 2013) models. To satisfy the research objective and to establish a comprehensive network perspective, this study has approached interviewees from all network nodes in the EU research network, AquaSmart. A purposive sampling strategy of 10 targeted researchers was chosen. This network includes participants from industry and academic organisations active in ICT research, from five different EU member states (Ireland, Greece, Spain, Portugal and Slovenia) and one associated country (Israel). Coverage of all network nodes to gain insights from each member of the network rather than dilute the investigation to a portion of the network, is considered a crucial research design choice.  In addition, use of archival data is common in this domain (Greer and Lei, 2012; Geisler, 2003; Kirschner et al., 2004; Perkmann and Schildt, 2015), and a documentation analysis has been conducted. The selection of a single case study fits particularly well with the qualitative approach required in this study as “rigorous qualitative case studies afford researchers the opportunities to explore or describe a phenomenon in context using a variety of data sources” (Baxter and Jack, 2008).

The collaborative European funded research and development landscape hosts research networks, their dynamics, how they operate, collaborate, and acquire new knowledge and products. Research networks provide a rich setting to analyse network strategy, formation, and configuration. Network embeddedness refers to the nature of relationships, links and nodes within a network. This paper focuses on configuration and management aspects of embeddedness within the case study. Network theory literature claims that networks are essential to innovative clusters such as Silicon Valley (Fleming and Frenken, 2007) and innovation in high tech industries (Owen-Smith and Powell, 2004).  Network capability development poses significant challenges and opportunities such as driving competitive advantage, resource constraints and recognising network capability as a resource of the firm (McGrath and O'Toole, 2013; Walter, Auer, & Ritter, 2006).

Perkmann and Schildt (2015) focus on large partnerships and the benefits such as reduced cost and balance between risks and rewards. They suggest a hierarchical nature within these partnerships that seems to place control of intellectual property licensing with industrial partners. The extant literature overlooks references to the concepts of trust, power and authority within these partnerships. Furthermore, Ahuja (2000) and Ahuja et al. (2013) declare that the extant research on university-industry partners focuses on primary appropriability, that is the control and ownership of intellectual property which seems consistent with the emergent themes in the literature focussing on other concepts within the collaboration of these partnerships.  Ahuja (2000) builds upon the seminal work of Burt (2009), Coleman (1988) and Granovetter (1973) to identify the optimal structure of inter-firm networks, whereas Perkmann and Schildt (2015) seem to exclude the specific network characteristics and opt to focus more on research outputs, benefits, challenges accrued to partners.

The data has identified insights in relation to the configuration of research networks, and the distinct qualities and social characteristics prevalent in these types of networks. From the initial findings, diversity within research networks between academia and industry is identified as a challenge and that convergence of research priorities is difficult but can yield successful outcomes.  In addition, the formation of a network seems to be indicative of the quality of the network nodes and their ability to work effectively together.  There was a focus from respondents on the social characteristics in relation to a strong correlation about reaching the research objectives and trust between nodes within the network. While the research has limitations in relation to generalisability, its objective to delve deep into a single qualitative case study has provided greater understanding to the context and the complexity of the network.

The results from this research contributes directly to theory in two ways, firstly, by providing rich qualitative insights into structural embeddedness (Herz et al., 2014). Secondly, structural embeddedness has not previously been investigated in the context of a European Union research network, and thus, this research will provide novel contextual insights. The contribution to practice will equip research networks to purse an optimised network strategy, cognisant of configuration and management aspects. In addition, the research management function will gain insights to enablers and barriers of structural embeddedness which supports their operations. From a policy perspective, funding agencies will further understand the structural embeddedness of research networks and the complexities therein. 

[1] http://www.aquasmartdata.eu