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Open Access Research article

Patterns of collaboration in complex networks: the example of a translational research network

Janet C Long1*, Frances C Cunningham12, Peter Carswell13 and Jeffrey Braithwaite1

Author Affiliations

1 Centre for Clinical Governance Research, Australian Institute of Health Innovation, Faculty of Medicine, University of New South Wales, Kensington 2052, Australia

2 Centre for Primary Health Care Systems Research, Menzies School of Health Research, Level 1, 147 Wharf Street, Spring Hill, QLD 4000, Australia

3 School of Population Health, University of Auckland, Auckland, New Zealand

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BMC Health Services Research 2014, 14:225  doi:10.1186/1472-6963-14-225

Published: 20 May 2014

Abstract

Background

This paper examines collaboration in a complex translational cancer research network (TRN) made up of a range of hospital-based clinicians and university-based researchers. We examine the phenomenon of close-knit and often introspective clusters of people (silos) and test the extent that factors associated with this clustering (geography, profession and past experience) influence patterns of current and future collaboration on TRN projects. Understanding more of these patterns, especially the gaps or barriers between members, will help network leaders to manage subgroups and promote connectivity crucial to efficient network function.

Methods

An on-line, whole network survey was used to collect attribute and relationship data from all members of the new TRN based in New South Wales, Australia in early 2012. The 68 members were drawn from six separate hospital and university campuses. Social network analysis with UCInet tested the effects of geographic proximity, profession, past research experience, strength of ties and previous collaborations on past, present and future intended partnering.

Results

Geographic proximity and past working relationships both had significant effects on the choice of current collaboration partners. Future intended collaborations included a significant number of weak ties and ties based on other members’ reputations implying that the TRN has provided new opportunities for partnership. Professional grouping, a significant barrier discussed in the translational research literature, influenced past collaborations but not current or future collaborations, possibly through the mediation of network brokers.

Conclusions

Since geographic proximity is important in the choice of collaborators a dispersed network such as this could consider enhancing cross site interactions by improving virtual communication technology and use, increasing social interactions apart from project related work, and maximising opportunities to meet members from other sites. Key network players have an important brokerage role facilitating linkages between groups.

Keywords:
Network theory; Collaboration; Translational research; Proximity; Brokerage; Health; Silos; Interorganisational alliances; Collaboratives for leadership in applied health research and care (CLAHRCs)