Research on Innovation Performance in Multi-level Collaborative Innovation Network
Jing Li, Huimin Tang, Haibin Tang
Available Online October 2019.
- https://doi.org/10.2991/icedem-19.2019.65How to use a DOI?
- multi-level network; synergetic innovation; ERGM; innovation performance
- Taking the patent data of Guangzhou bio pharmaceutical industry in 2017 as an example, this paper constructs a double-level collaborative innovation network, which consists of the R & D institution network and the R & D staff network. Exponential Random Graph Models is used to analyze the present collaborative innovation situation of the constructed network. Factors that affect R & D staff’s innovation performance are tested. We find that the centrality nodes in R & D staff network has a significant positive effect on their innovation performance, and the clustering coefficient of the nodes has a significant negative impact on innovation performance. The centrality of R & D institutions can moderate the effect of R & D staff’s centrality and clustering coefficient on innovation performance. The number of structural holes of R & D institutions can also moderate the impact of R & D staff’s clustering coefficient on innovation performance.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Jing Li AU - Huimin Tang AU - Haibin Tang PY - 2019/10 DA - 2019/10 TI - Research on Innovation Performance in Multi-level Collaborative Innovation Network BT - Proceedings of the 2019 3rd International Conference on Economic Development and Education Management (ICEDEM 2019) PB - Atlantis Press SP - 277 EP - 282 SN - 2352-5398 UR - https://doi.org/10.2991/icedem-19.2019.65 DO - https://doi.org/10.2991/icedem-19.2019.65 ID - Li2019/10 ER -