The evolution of a collaboration network and its impact on innovation performance under the background of government-funded support: an empirical study in the Chinese wind power sector.

To accelerate the transformation and application of basic research results, the Chinese government has repeatedly mentioned in a government work report that it is necessary to support research and innovation collaborations between knowledge research institutions and enterprises. However, few studies have focused on the evolution of collaborations between these organizations and the impact of collaborations on innovation performance (IP) in the field of renewable energy under the background of government-funded support (GFS). Based on scientific publications, we construct a GFS collaboration network in the wind power field to investigate the evolution of network structure characteristics, attribute proximity variables, and applied research collaboration (ARC), and we study the impact of network evolution on the IP of actors. The results show that the focal actor of the collaboration network prefers to engage in ARC with partners who are familiar and have the same knowledge base in different provinces. This collaboration tendency will reduce geographical proximity and increase the direct ties, indirect ties, technological proximity, and ARC of the ego network. Among them, direct ties have an inverted U-shaped effect on IP, geographical proximity has a significantly negative impact on IP, and the remaining variables have positive impacts on IP. Taken together, when the direct ties is within a certain range, these collaboration tendencies in a GFS collaboration network positively affect the IP of research institutions and enterprises.