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Patterns of collaboration in complex networks: the example of a translational research network
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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4033678/ https://www.ncbi.nlm.nih.gov/pubmed/24885971 http://dx.doi.org/10.1186/1472-6963-14-225 |
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author | Long, Janet C Cunningham, Frances C Carswell, Peter Braithwaite, Jeffrey |
author_facet | Long, Janet C Cunningham, Frances C Carswell, Peter Braithwaite, Jeffrey |
author_sort | Long, Janet C |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-4033678 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-40336782014-05-27 Patterns of collaboration in complex networks: the example of a translational research network Long, Janet C Cunningham, Frances C Carswell, Peter Braithwaite, Jeffrey BMC Health Serv Res Research Article 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. BioMed Central 2014-05-20 /pmc/articles/PMC4033678/ /pubmed/24885971 http://dx.doi.org/10.1186/1472-6963-14-225 Text en Copyright © 2014 Long et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Long, Janet C Cunningham, Frances C Carswell, Peter Braithwaite, Jeffrey Patterns of collaboration in complex networks: the example of a translational research network |
title | Patterns of collaboration in complex networks: the example of a translational research network |
title_full | Patterns of collaboration in complex networks: the example of a translational research network |
title_fullStr | Patterns of collaboration in complex networks: the example of a translational research network |
title_full_unstemmed | Patterns of collaboration in complex networks: the example of a translational research network |
title_short | Patterns of collaboration in complex networks: the example of a translational research network |
title_sort | patterns of collaboration in complex networks: the example of a translational research network |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4033678/ https://www.ncbi.nlm.nih.gov/pubmed/24885971 http://dx.doi.org/10.1186/1472-6963-14-225 |
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