Structural effects of R&D collaboration network on knowledge diffusion performance |
| |
| Authors: | Hyukjoon Kim Yongtae Park |
| |
| Affiliation: | 1. Technology Management and Economics Policy Program, School of Engineering, Seoul National University, San 56-1, Shillim-Dong, Kwanak-Gu, Seoul 151-742, Republic of Korea;2. Department of Industrial Engineering, School of Engineering, Seoul National University, San 56-1, Shillim-Dong, Kwanak-Gu, Seoul 151-742, Republic of Korea;1. School of Management, Xiamen University, No. 422, Siming South Road, Xiamen, Fujian 361005, PR China;2. Complex Systems Research Center, Shanxi University, No. 92, Wucheng Road, Taiyuan, Shanxi 030006, PR China;1. School of Economics and Management, Beihang University, Beijing 100191, PR China;2. School of Mathematics and Statistics, University of Western Australia, Perth, WA 6009, Australia;3. Mineral Resources, CSIRO, Kensington, Perth, WA 6151, Australia;1. China Merchants Group Postdoctoral Research Station, Room 3008A, 30/F., Times Plaza, No 1 Taizi Road, Shenzhen, China;2. Dept. of Real Estate and Construction, The University of Hong Kong, Hong Kong;1. School of Finance and Economics, Jiangsu University, Zhenjiang, 212013, Jiangsu, China;2. Research Center of the Central China for Economic and Social Development, Nanchang University, China;3. School of Economics and Management, Nanchang University, Nanchang, China;4. Beijing IncoPat CO., LTD, Beijing, 100000, Beijing, China |
| |
| Abstract: | With the advent of knowledge-based economy, the process and structure of knowledge diffusion mechanism in R&D collaboration networks have become more complex and dynamic. However, regardless of the complexity and importance of these R&D collaboration networks, previous empirical analyses have focused mainly on statics, which cannot be a sufficient basis to thoroughly explore knowledge diffusion in the R&D collaboration network. Furthermore, there has been little research done on the relationship between knowledge diffusion and the structure of an R&D collaboration network. Hence, this paper modeled knowledge diffusion based on social network analysis. It also investigated the impact of network structure on the performance of knowledge diffusion, focusing on average knowledge stock and knowledge variance. The results confirm that the small-world network is the most efficient and equitable structure toward effective knowledge diffusion. |
| |
| Keywords: | |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
