Research on Innovation Performance in Multi-level Collaborative Innovation Network

DOI

10.2991/icedem-19.2019.65How to use a DOI?

Keywords

multi-level network; synergetic innovation; ERGM; innovation performance

Abstract

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.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

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  - 10.2991/icedem-19.2019.65
ID  - Li2019/10
ER  -