Global labor flow network reveals the hierarchical organization and dynamics of geo-industrial clusters.

ABSTRACT: Groups of firms often achieve a competitive advantage through the formation of geo-industrial clusters. Although many exemplary clusters are the subjects of case studies, systematic approaches to identify and analyze the hierarchical structure of geo-industrial clusters at the global scale are scarce. In this work, we use LinkedIn's employment history data from more than 500 million users over 25 years to construct a labor flow network of over 4 million firms across the world, from which we reveal hierarchical structure by applying network community detection. We show that the resulting geo-industrial clusters exhibit a stronger association between the influx of educated workers and financial performance, compared to traditional aggregation units. Furthermore, our analysis of the skills of

SUBMITTER: Park J 

PROVIDER: S-EPMC6671949 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature