How strong clustering and centrality position in the alliance network impacts on innovation performance?

Abstract

Innovation in networks and in clusters recently attracted attention of scholars from management science and engineering. In our paper we made an attempt to find the relationship between centrality position with short path length between nodes and innovation performance. Also we examined another relationship between clustering coefficient and innovation performance. In order to find the network indexes we have constructed adjacency matrixes based on alliance data. As a sample we have used China’s automobile industry network. We have collected the data on innovation performance for 59 firms in China’s automobile industry. We used UCINET software program to get the data regarding network properties. After we ran the negative binomial regression model on Gretl software program and constructed 4 models, with total of 6 variables. According to our new findings there is no effect on innovation performance when firms have a short path length between nodes in the network and found that strong local clustering has a negative effect on innovation performance.