Global labor flow network reveals the hierarchical organization and dynamics of geo-industrial clusters in the world economy Jaehyuk Park∗a , Ian Wood*a,b , Elise Jinga , Azadeh Nematzadeha,c , Souvik Ghoshb , Michael arXiv:1902.04613v1 [cs.SI] 12 Feb 2019...
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Global labor flow network reveals the hierarchical organization and dynamics of geo-industrial clusters in the world economy Jaehyuk Park∗a , Ian Wood*a,b , Elise Jinga , Azadeh Nematzadeha,c , Souvik Ghoshb , Michael arXiv:1902.04613v1 [cs.SI] 12 Feb 2019 Conover†b,d , and Yong-Yeol Ahn‡a a Indiana University, Bloomington, IN 47408, USA b LinkedIn, Sunnyvale, CA 94043, USA c S&P Global, New York, NY 10004, USA d Workday, Inc., Pleasanton, CA 94588, USA Abstract Groups of firms often achieve a competitive advantage through the formation of geo-industrial clusters. Although many exemplary clusters, such as Hollywood or Silicon Valley, have been frequently studied, systematic approaches to identify and analyze the hierarchical structure of the geo-industrial clusters at the global scale are rare. In this work, we use LinkedIn’s employment histories of more than 500 million users over 25 years to construct a labor flow network of over 4 million firms across the world and apply a recursive
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