A local social network approach for research management

  • Authors:
  • Xiaoyan Liu;Zhiling Guo;Zhenjiang Lin;Jian Ma

  • Affiliations:
  • Department of Information Systems, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong;Department of Information Systems, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong;Advanced Analytics Institute, University of Technology Sydney, NSW 2007, Australia;Department of Information Systems, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong

  • Venue:
  • Decision Support Systems
  • Year:
  • 2013

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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.