Based on a national survey of Chinese scientific personnel in 2008, this paper sheds new light on the relationship between social networks and scientific performance. In this study, we used position generator to measure scientists’ ego-centered social networks. The scientists’ performance was measured by multiple indexes, including recognitions from the academic (papers), governmental (awards), and market (patents) sectors. The findings show that size and composition of scientists’ social networks have significant effect on their scientific performance. The notions of “information communication mechanism” and “resource acquisition mechanism” are introduced to explain how network composition affects scientific performance along multiple dimensions. The policy implications of the study are also discussed.
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