A local social network approach for research management

Liu, X; Guo, Z; Lin, Z; Ma, J

A local social network approach for research management

Liu, X Guo, Z Lin, Z Ma, J

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Publication Type:: Journal Article
Citation:: Decision Support Systems, 2013, 56 (1), pp. 427 - 438
Issue Date:: 2013-12-01

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Field	Value	Language
dc.contributor.author	Liu, X	en_US
dc.contributor.author	Guo, Z	en_US
dc.contributor.author	Lin, Z	en_US
dc.contributor.author	Ma, J	en_US
dc.date.issued	2013-12-01	en_US
dc.identifier.citation	Decision Support Systems, 2013, 56 (1), pp. 427 - 438	en_US
dc.identifier.issn	0167-9236	en_US
dc.identifier.uri	http://hdl.handle.net/10453/30705
dc.description.abstract	Traditional methods to evaluate research performance focus on citation count, quality and quantity of research output by individual researchers. These measures overlook the roles an individual plays in research collaboration, which is critical in an institutional research management environment due to the inherent interdependency among research entities. In order to address the organizational research management needs, we propose a research social network approach to better analyze local collaboration networks. For this purpose, we develop a new "collaboration supportiveness" measure to quantify an individual researcher's collaboration ability. Insights derived from this research are very helpful for managers to effectively allocate resources, identify research priorities, promote collaboration, and grow research in directions aligned with the organizational strategies. © 2012 Elsevier B.V.	en_US
dc.relation.ispartof	Decision Support Systems	en_US
dc.relation.isbasedon	10.1016/j.dss.2012.10.055	en_US
dc.subject.classification	Information Systems	en_US
dc.title	A local social network approach for research management	en_US
dc.type	Journal Article
utslib.citation.volume	1	en_US
utslib.citation.volume	56	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	01 Mathematical Sciences	en_US
utslib.for	08 Information and Computing Sciences	en_US
utslib.for	15 Commerce, Management, Tourism and Services	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
utslib.copyright.status	closed_access
pubs.issue	1	en_US
pubs.publication-status	Published	en_US
pubs.volume	56	en_US

Abstract:

Traditional methods to evaluate research performance focus on citation count, quality and quantity of research output by individual researchers. These measures overlook the roles an individual plays in research collaboration, which is critical in an institutional research management environment due to the inherent interdependency among research entities. In order to address the organizational research management needs, we propose a research social network approach to better analyze local collaboration networks. For this purpose, we develop a new "collaboration supportiveness" measure to quantify an individual researcher's collaboration ability. Insights derived from this research are very helpful for managers to effectively allocate resources, identify research priorities, promote collaboration, and grow research in directions aligned with the organizational strategies. © 2012 Elsevier B.V.

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http://hdl.handle.net/10453/30705