社会ネットワークが基礎研究に与える影響 : 内資系大手医薬品企業の事例

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The aim of this research is to conduct empirical analysis of the effects of social capital on basic research performance. This research uses typical network variables to measure social capital and compares the following effects: degree centrality, betweenness centrality, network constraint, strong ties and outside ties. I used the approved patents of Japanese pharmaceutical firms during 1980-1999 to make a relationship matrix of corporate researchers. In order to check the difference of effects of past and current network, the dataset was divided into two periods: past network i.e. 1980 to 1989 and current network i.e. 1990 to 1999. The final dataset contains 404 researchers from the five largest pharmaceutical firms in Japan: Daiichi, Eisai, Fujisawa, Sankyo and Takeda. Using this dataset and independent variables, I conducted regression analysis on individual researchers' performance during the said periods. Results show that structure variables and outside tie in past network have no significant effects on current performance. Only strong ties in past networks are negatively associated with performance. Conversely, in current networks, betweenness centrality, network constraint, strong ties and outside ties have significant effects on current performance. Furthermore, degree centrality does not have a significant effect in either network. These results indicate several implications. First, past networks have a weaker impact on current performance than they do on current networks. Second, the impact of strong ties changes depending on past or current network. Third, as degree centrality does not have significant effects but betweenness centrality has, mediation between people is more important than mere connection to people. Along with these implications, practitioners should try to utilize current network more and operate positioned between connections.
2010-10-30

社会ネットワークが基礎研究に与える影響 : 内資系大手医薬品企業の事例

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