Global labor flow network reveals the hierarchical organization and dynamics of geo-industrial clusters
There is a lack of systematic approaches to identify and analyze the hierarchical structure of geo-industrial clusters at the global scale. Here the authors use LinkedIn's employment history data to construct a global labor flow network from which they find that the resulting geo-industrial clu...
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| Autores principales: | , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2019
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/19ac37b569f44c51953b1343772035bc |
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| Sumario: | There is a lack of systematic approaches to identify and analyze the hierarchical structure of geo-industrial clusters at the global scale. Here the authors use LinkedIn's employment history data to construct a global labor flow network from which they find that the resulting geo-industrial clusters exhibit a stronger association between the influx of educated-workers and financial performance compared to existing aggregation units. |
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