The Evolution of Global and Local Scientist Mobility Network: Evidence From ORCID Profiles
The global and local mobility of scientists are two critical aspects influencing national innovation systems. However, existing research primarily analyzes the scientist mobility network at either a global or local scale, failing to capture the structure and dynamic of networks at the coupled global...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11079595/ |
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| Summary: | The global and local mobility of scientists are two critical aspects influencing national innovation systems. However, existing research primarily analyzes the scientist mobility network at either a global or local scale, failing to capture the structure and dynamic of networks at the coupled global-local scale. To address this gap, we develop a conceptual model of the global and local scientist mobility network. Empirically, based on a dataset containing approximately two million profiles from ORCID, we construct a mobility network encompassing 206 countries and 16,049 universities. Using social network analysis methods and the core-periphery profile algorithm, we analyze the structural evolution of the network. Furthermore, we employ community detection algorithms and a random network null model to examine the driving role of the proximity in this evolution. The main findings are as follows: (1) Over time, the size of the scientist mobility network has expanded significantly, with increasingly small-world properties and network centralization, which are more evident at the global scale; (2) Geographical and institutional proximity play a crucial role in the evolution of the scientist mobility network, with geographical proximity primarily influencing local networks. The findings of this study provide more robust and generalizable empirical evidence for universities, local governments, and national policymakers to better understand the competitive dynamics of domestic and international talent, and also offer important implications for optimizing talent management policies. |
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| ISSN: | 2169-3536 |