Abstract
Innovation has attracted attention of researches in last 20 years, while networks and clusters are relatively new research subjects. In our paper we made an attempt to find the relationship between network centrality indexes and innovation performance. Each index represents different features of being in the network. To find the network indexes we have constructed adjacency matrixes based on alliance data. For our research we have chosen China’s automobile industry network as an example, for the reason that Chinese automobile industry showed tremendous growth in recent decade and is fit to research scope which we are conducting. 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 5 models, with total of 7 variables. We have analyzed the relationship between innovation performance and three network centrality measures. According to our new findings firms in the network with more total number of connections and firms with more connections with well-connected firms have better innovation performance. We found that there is no effect on innovation performance when firms have capability to pass information fast.
Highlights
Economic theories of firms mostly were focused on external environment of organizations in context of competition and resource availability and networks were considered as beneficial sources for partnership until the researches proved that it is broader than that
Results on relationship with innovation performance Positive. Two centrality measures, such as eigenvector centrality and degree centrality were confirmed to be positively and significantly related to innovation performance, which was proposed in hypothesis
Closeness centrality is measured in order to find the speed of information flow, and as we see in our network it does not make an essential effect on innovation performance, beside of it, it had a negative relationship; it is different vector than what we were expecting
Summary
Economic theories of firms mostly were focused on external environment of organizations in context of competition and resource availability and networks were considered as beneficial sources for partnership until the researches proved that it is broader than that. Firms can be interconnected with other firms through a wide array of social and economic relationships, each of which can constitute a social network. These include supplier relationships, resource flows, trade association memberships, interlocking directorates, relationships among individual employees, and prior strategic alliances. Network perspectives are based on common understanding that economic actions occur not in vapid social context, but integrated into social network relationships. Networks can benefit in a lot of aspects such as expanding the customer base of a firm, sharing costs and risks, learning new technologies through knowledge exchange and trainings, conducting common R&D projects (NESC, 1996), increasing the speed of reacting to market and technological changes
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