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Framework to Measure the Mobility of Technical Talents: Evidence from China’s Smart Logistics

Author

Listed:
  • Jun Guan

    (School of Economics and Management, Beijing University of Technology, Beijing 100124, China)

  • Chunxiu Liu

    (School of Economics and Management, Beijing University of Technology, Beijing 100124, China)

  • Guoqiang Liang

    (School of Economics and Management, Beijing University of Technology, Beijing 100124, China)

  • Lizhi Xing

    (School of Economics and Management, Beijing University of Technology, Beijing 100124, China)

Abstract

Talent mobility is the key driving force to accelerate innovation and economic development. Prior studies focused much attention on the mobility of scientific talents from the angle of bibliometrics. Still, the mobility of technical talents was not thoroughly analyzed through the lens of the complex network. In consideration of technical talents being the primary and direct labor force to foster innovation and economic growth, in this paper, we provide a framework to measure the mobility of technical talents based on patents from the perspective of the complex network. The Technical Talent Mobility Network (TTMN) model is constructed to measure the changes of network topology on the levels of network, node, and edge aspects, respectively, thus deepening our understanding of the important node and mobility channels of technical talents. We then take China’s smart logistics as an example to verify the framework promoted, and results show the framework can reveal the actual situation of technical talent mobility that was reported by the government gazette and related articles. The framework proposed in this paper points out a new method and perspective to measure technological talent mobility, which is essential to facilitate regional innovation and economic soar.

Suggested Citation

  • Jun Guan & Chunxiu Liu & Guoqiang Liang & Lizhi Xing, 2023. "Framework to Measure the Mobility of Technical Talents: Evidence from China’s Smart Logistics," Sustainability, MDPI, vol. 15(3), pages 1-16, January.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:3:p:2481-:d:1051494
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    References listed on IDEAS

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    1. Melissa Bjelland & Bruce Fallick & John Haltiwanger & Erika McEntarfer, 2011. "Employer-to-Employer Flows in the United States: Estimates Using Linked Employer-Employee Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(4), pages 493-505, October.
    2. Lissoni, Francesco, 2010. "Academic inventors as brokers," Research Policy, Elsevier, vol. 39(7), pages 843-857, September.
    3. Federica Angeli & Alessandro Grandi & Rosa Grimaldi, 2014. "Directions and Paths of Knowledge Flows through Labour Mobility: A Social Capital Perspective," Regional Studies, Taylor & Francis Journals, vol. 48(11), pages 1896-1917, November.
    4. Tarique, Ibraiz & Schuler, Randall S., 2010. "Global talent management: Literature review, integrative framework, and suggestions for further research," Journal of World Business, Elsevier, vol. 45(2), pages 122-133, April.
    5. Filippo Simini & Marta C. González & Amos Maritan & Albert-László Barabási, 2012. "A universal model for mobility and migration patterns," Nature, Nature, vol. 484(7392), pages 96-100, April.
    6. Robinson-Garcia, Nicolás & Sugimoto, Cassidy R. & Murray, Dakota & Yegros-Yegros, Alfredo & Larivière, Vincent & Costas, Rodrigo, 2019. "The many faces of mobility: Using bibliometric data to measure the movement of scientists," Journal of Informetrics, Elsevier, vol. 13(1), pages 50-63.
    7. Birgitta Rabe & Mark P. Taylor, 2012. "Differences in Opportunities? Wage, Employment and House-Price Effects on Migration," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(6), pages 831-855, December.
    8. Xing, Lizhi & Dong, Xianlei & Guan, Jun & Qiao, Xiaoyong, 2019. "Betweenness centrality for similarity-weight network and its application to measuring industrial sectors’ pivotability on the global value chain," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 19-36.
    9. Qiongqiong Chen & Yuan Li, 2019. "Mobility, Knowledge Transfer, and Innovation: An Empirical Study on Returned Chinese Academics at Two Research Universities," Sustainability, MDPI, vol. 11(22), pages 1-14, November.
    10. 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.
    11. Maarten van Ham & Clara H Mulder & Pieter Hooimeijer, 2001. "Spatial Flexibility in Job Mobility: Macrolevel Opportunities and Microlevel Restrictions," Environment and Planning A, , vol. 33(5), pages 921-940, May.
    12. Rikard H. Eriksson, 2011. "Localized Spillovers and Knowledge Flows: How Does Proximity Influence the Performance of Plants?," Economic Geography, Clark University, vol. 87(2), pages 127-152, April.
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