This paper uses a unique database that combines Brazilian patent data and personal microdata on formal employees from 2000 to 2011 to study the effect of inventor’s individual attributes on the propensity to cooperate. Our main contributions derive from (1) using a dominance coefficient decomposition to examine each individual’s returns based on the non-explicit hierarchy of the link and (2) finding what attributes inventors take into consideration when seeking working partnerships. The main results reveal that inventors tend to collaborate with others with similar educational background and centrality level, and there is a great likelihood of connectivity if educational and centrality levels are high. The dominance coefficient decomposition revealed that a type of social hierarchy emerges in the network.

中文翻译：

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个人属性和发明人匹配：一项使用来自巴西共同专利网络的数据的研究

本文使用一个独特的数据库，结合了巴西专利数据和 2000 年至 2011 年正式雇员的个人微数据，研究了发明人的个人属性对合作倾向的影响。我们的主要贡献来自 (1) 使用优势系数分解来检查基于链接的非显式层次结构的每个人的回报，以及 (2) 找出发明者在寻求工作伙伴关系时考虑的属性。主要结果表明，发明人倾向于与具有相似教育背景和中心性水平的其他人合作，如果教育和中心性水平高，则很有可能建立联系。优势系数分解表明，网络中出现了一种社会等级。