Spatio‐Temporal Dynamics of China's Researcher Mobility Network, 1968–2020. Na, Y. & Liu, X. Transactions in GIS, 29(7):e70133, November, 2025. ![Spatio‐Temporal Dynamics of China's Researcher Mobility Network, 1968–2020 [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex ABSTRACT The mobility of scientific researchers is a key driver of knowledge flow and regional innovation; however, its spatial organization and structuring in China remains incompletely understood. Using the Web of Science data spanning more than five decades (1968–2020), this study reconstructs the evolution of China's researcher mobility network at both the urban agglomeration and city levels. Through network analysis and additional structural indicators, we identify a four‐stage progression from a sparse, coastal‐centered system to a nationally integrated yet increasingly divided network. The Yangtze River Delta, Beijing–Tianjin–Hebei, and the Greater Bay Area have historically been the dominant coastal regions. At the same time, the Middle Reaches of the Yangtze River became a secondary hub, and most inland areas mainly acted as sources of researchers. Inflows grew more concentrated over time, with the Gini coefficient rising from 0.12 (1968–2000) to 0.53 (2016–2020). At the city level, analyzing betweenness centrality alongside the Talent Mobility Balance Index reveals a structural–functional mismatch: some hubs, such as Beijing and Wuhan, serve as key connectors but experience persistent net outflows, while cities like Shenzhen and Zhengzhou attract large inflows despite having limited structural importance. This typology—dual‐advantage, hub‐loss, magnet non‐hub, and peripheral‐vulnerable—illustrates a “bridge–magnet” division of labor within China's scientific mobility system. The findings expand theories of scientific mobility by linking multi‐scalar structures with their functional impacts, and they offer insights for tailored governance strategies aimed at balancing efficiency and fairness in the distribution of research talent.
@article{na_spatiotemporal_2025,
title = {Spatio‐{Temporal} {Dynamics} of {China}'s {Researcher} {Mobility} {Network}, 1968–2020},
volume = {29},
issn = {1361-1682, 1467-9671},
url = {https://onlinelibrary.wiley.com/doi/10.1111/tgis.70133},
doi = {10.1111/tgis.70133},
abstract = {ABSTRACT
The mobility of scientific researchers is a key driver of knowledge flow and regional innovation; however, its spatial organization and structuring in China remains incompletely understood. Using the Web of Science data spanning more than five decades (1968–2020), this study reconstructs the evolution of China's researcher mobility network at both the urban agglomeration and city levels. Through network analysis and additional structural indicators, we identify a four‐stage progression from a sparse, coastal‐centered system to a nationally integrated yet increasingly divided network. The Yangtze River Delta, Beijing–Tianjin–Hebei, and the Greater Bay Area have historically been the dominant coastal regions. At the same time, the Middle Reaches of the Yangtze River became a secondary hub, and most inland areas mainly acted as sources of researchers. Inflows grew more concentrated over time, with the Gini coefficient rising from 0.12 (1968–2000) to 0.53 (2016–2020). At the city level, analyzing betweenness centrality alongside the Talent Mobility Balance Index reveals a structural–functional mismatch: some hubs, such as Beijing and Wuhan, serve as key connectors but experience persistent net outflows, while cities like Shenzhen and Zhengzhou attract large inflows despite having limited structural importance. This typology—dual‐advantage, hub‐loss, magnet non‐hub, and peripheral‐vulnerable—illustrates a “bridge–magnet” division of labor within China's scientific mobility system. The findings expand theories of scientific mobility by linking multi‐scalar structures with their functional impacts, and they offer insights for tailored governance strategies aimed at balancing efficiency and fairness in the distribution of research talent.},
language = {en},
number = {7},
urldate = {2026-01-12},
journal = {Transactions in GIS},
author = {Na, Ying and Liu, Xintao},
month = nov,
year = {2025},
pages = {e70133},
}
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Through network analysis and additional structural indicators, we identify a four‐stage progression from a sparse, coastal‐centered system to a nationally integrated yet increasingly divided network. The Yangtze River Delta, Beijing–Tianjin–Hebei, and the Greater Bay Area have historically been the dominant coastal regions. At the same time, the Middle Reaches of the Yangtze River became a secondary hub, and most inland areas mainly acted as sources of researchers. Inflows grew more concentrated over time, with the Gini coefficient rising from 0.12 (1968–2000) to 0.53 (2016–2020). At the city level, analyzing betweenness centrality alongside the Talent Mobility Balance Index reveals a structural–functional mismatch: some hubs, such as Beijing and Wuhan, serve as key connectors but experience persistent net outflows, while cities like Shenzhen and Zhengzhou attract large inflows despite having limited structural importance. This typology—dual‐advantage, hub‐loss, magnet non‐hub, and peripheral‐vulnerable—illustrates a “bridge–magnet” division of labor within China's scientific mobility system. 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