Abstract
The purpose of this paper is to analyze the effects of networks on research output and impact. The analysis was done using a database of 2150 Mexican engineers who have been members of the National System of Researchers. Results show that although there are several methods to measure centrality and structure in the social network analysis theory, not all variables show the same impact on performance. Our results suggest that the centrality measures that show a positive effect on publications and citations are degree and closeness, betweenness is only significant with publications, and eigenvector has a negative effect on publications. Related to the measures of network structure, our analysis suggests that both structural holes and density have a positive effect on research output and impact, confirming that there are networks in which closure and brokerage can benefit the performance of the members of the network.
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