Collaborative research is not only about linking top scientists for a project, but encouraging learning across the network. Using social network analysis, we will capture learning paths across the Alliances and new collaborative linkages to continue.

Ultimately, this collaboration has aims to encourage greater knowledge transfer, better science and a faster route to market for resulting technologies. This area of our research design addresses these goals directly.

Knowledge Transfer

We will explore how individuals engaged in the Alliances have shared knowledge. This will be captured through social network analysis as well as through case studies. We will test whether knowledge sharing has been increased and/or shaped by participation in the Alliance. We will also test whether and how ICT-mediating technologies have supported this knowledge transfer.

Fig1. Social Network Analysis of the AtlanTICC Alliance Participants. For a larger version please click here

Better Science

Much more difficult to establish but equally important is an understanding of the impact of collaboration on the scientific outcomes. There is some quantitative assessment to be gained at the level of the individual, by considering trend-breaking patterns of publications, IPR (including patents), international recognition and subsequent funding. However, we will also look for evidence of better science in our interviews with project participants.

Faster Science and Faster-to-Market Science

In capturing gains in speed, quantitative estimates become largely unworkable. Nevertheless, one of the key rationales for virtual science teams lies in the potential to reach breakthroughs more quickly. We will explore these questions through interviews at the project levels, considering counterfactual options at staged points in the project and relying upon the estimates of the expert participants.

Do we get faster, better science?

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Collaboration across distance
Big Pipe Communication
Learning Paths
Method
Research Team