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The Flow Network of Chinese Scientists and Its Driving Mechanisms Based on the Spatial Development Path of CAS and CAE Academicians

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  • Wentian Shi

    (Institute for Global Innovation and Development, East China Normal University, Shanghai 200062, China
    School of Urban and Regional Sciences, East China Normal University, Shanghai 200241, China)

  • Debin Du

    (Institute for Global Innovation and Development, East China Normal University, Shanghai 200062, China
    School of Urban and Regional Sciences, East China Normal University, Shanghai 200241, China)

  • Wenlong Yang

    (Institute of World Economy, Shanghai Academy of Social Sciences, Shanghai 200020, China)

Abstract

Scientists are a core element of regional technological innovation and economic growth. Academicians of the Chinese Academy of Sciences (CAS) and Chinese Academy of Engineering (CAE) are outstanding representatives of Chinese scientists. The purpose of this paper is to reveal the characteristics of Chinese scientists’ space migration, depict the structural topology of their flow network and to analyze the driving mechanisms behind the characteristics of their space migration. We mainly used spatial statistics, complex network analysis, and a modified location quotient. Our main conclusions are as follows: (1) The spatial distribution of Chinese scientists at different development stages tends to converge. The Chinese scientists’ birthplaces are highly concentrated in the eastern coastal areas and the Yangtze River basin. Education locations are highly consistent, with clusters of global high-level educational resources at home and abroad, and their workplaces are mainly distributed in economically developed cities. (2) In terms of network characteristics, the spatial heterogeneity of the growth of Chinese scientists is obvious. Only a few cities, such as Beijing, Shanghai, and Nanjing, have higher degrees of node centrality, strength centrality, and betweenness centrality, so their networks’ hierarchical structures are pyramid-shaped and their core-periphery structures are prominent. By identifying the roles of the cities as network nodes, we found that only Beijing plays accomplished and stable roles, whereas other cities play a single role. (3) Regarding driving mechanisms, Chinese scientists’ spatial migration has been influenced by national policy, regional economic level, education level, and individual traits at national, regional, and personal scales. Therefore, the combined effects of various forces have driven the evolution of the flow network of Chinese scientists.

Suggested Citation

  • Wentian Shi & Debin Du & Wenlong Yang, 2019. "The Flow Network of Chinese Scientists and Its Driving Mechanisms Based on the Spatial Development Path of CAS and CAE Academicians," Sustainability, MDPI, vol. 11(21), pages 1-22, October.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:21:p:5938-:d:280298
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    Cited by:

    1. Wentian Shi & Wenlong Yang & Debin Du, 2020. "The Scientific Cooperation Network of Chinese Scientists and Its Proximity Mechanism," Sustainability, MDPI, vol. 12(2), pages 1-18, January.
    2. Wentian Shi & Quansheng Fu & Wenlong Yang & Fan Yang & Xiao Lin & Xueying Mu, 2022. "The spatial relationship between the mobility and scientific cooperation of Chinese scientists," Growth and Change, Wiley Blackwell, vol. 53(2), pages 951-971, June.
    3. Cheng Peng & Zhepeng (Lionel) Li & Chaojiang Wu, 2023. "Researcher geographic mobility and publication productivity: an investigation into individual and institutional characteristics and the roles of academicians," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 379-406, January.
    4. Haining Jiang & Wenzhong Zhang & Jian Duan, 2020. "Location Choice of Overseas High-Level Young Returned Talents in China," Sustainability, MDPI, vol. 12(21), pages 1-16, November.

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