Abstract
Knowledge networks play a crucial role in contemporary organisations to improve participation for knowledge sharing. Examining employees’ knowledge contribution play an important role for in success implementing knowledgenetworks. Whereas most part of studies emphasis on the quantity aspect of knowledge contributions, the success of knowledge networks also depends strongly on quality aspect of participants’ voluntarily contributions. Further, employees’ central positions can make a strategic position for participants for both locally and globally in the overall structure of the knowledge network. The purpose of this study is to explore the relationships between centrality positions of participants with knowledge contribution quality in knowledge networks. Five hypotheses are designed to evaluate relations of employees’ centrality positions with the quality aspect of knowledge contributions using correlation analysis. The network data are collected from a knowledge network of a corporate group in the energy industry. The research results signify degree centrality; closeness centrality and betweenness centrality of participants have significant relations with the quality of shared knowledge. The research outcomes draw initial guides for organisations to evaluate the quality aspect of knowledge contributions by network analysis in knowledge networks.
Original language | English |
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Title of host publication | Proceedings of International Conference on Intellectual Capital, Knowledge Management & Organisational Learning |
Pages | 302-310 |
Publication status | Published - 2016 |
Event | International Conference on Intellectual Capital, Knowledge Management & Organisational Learning - Ithaca College, Ithaca, United States Duration: 14 Oct 2016 → 15 Oct 2016 http://www.academic-conferences.org/conferences/icickm/ |
Conference
Conference | International Conference on Intellectual Capital, Knowledge Management & Organisational Learning |
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Abbreviated title | ICICKM |
Country/Territory | United States |
City | Ithaca |
Period | 14/10/16 → 15/10/16 |
Internet address |
Keywords
- Knowledge Networks
- Centralization
- Social Network Analysis
- Knowledge Contribution