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Research on the co-movement between high-end talent and economic growth: A complex network approach

Author

Listed:
  • Zhang, Zhen
  • Wang, Minggang
  • Xu, Hua
  • Zhang, Wenbin
  • Tian, Lixin

Abstract

The major goal of this paper is to focus on the co-movement between high-end talent and economic growth by a complex network approach. Firstly, the national high-end talent development efficiency from 1990 to 2015 is taken as the quantitative index to measure the development of high-end talent. The added values of the primary industry, secondary industry, tertiary industry are selected as economic growth indexes, and all the selected sample data are standardized by the mean value processing method. Secondly, let seven months as the length of the sliding window, and one month as the sliding step, then the grey correlation degrees between systems are measured using the slope correlation degrees, and the grey correlation degree sequence is mapped into the symbol series composed by three symbols {Y,O,N} based on the coarse graining method. Let three characters as a mode, the nodes are obtained by the modes according to the time sequence. Let the transformation between the modal be the edge, and the times of the transformation be weight, then the co-movement networks between national high-end talent development efficiency and the added values of the primary industry, secondary industry, tertiary industry are built respectively. Finally, the dynamic characteristics of the networks are analysed by the node strength, strength distribution, weighted clustering coefficient, conversion cycle of the modes and the transition between the co-movement modes. The results indicate that there are mutual influence and promotion relations between the national high-end talent development efficiency and the added values of the primary, secondary and tertiary industry.

Suggested Citation

  • Zhang, Zhen & Wang, Minggang & Xu, Hua & Zhang, Wenbin & Tian, Lixin, 2018. "Research on the co-movement between high-end talent and economic growth: A complex network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 1216-1225.
    • Handle: RePEc:eee:phsmap:v:492:y:2018:i:c:p:1216-1225
    DOI: 10.1016/j.physa.2017.11.049
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    Citations

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    Cited by:

    1. Suwan Lu & Guobin Fang & Mingtao Zhao, 2023. "Towards Inclusive Growth: Perspective of Regional Spatial Correlation Network in China," Sustainability, MDPI, vol. 15(7), pages 1-19, March.
    2. Jincheng Jiang & Jinsong Chen & Wei Tu & Chisheng Wang, 2019. "A Novel Effective Indicator of Weighted Inter-City Human Mobility Networks to Estimate Economic Development," Sustainability, MDPI, vol. 11(22), pages 1-18, November.
    3. Chenhui Hu & Haining Jiang, 2021. "Causal Nexus between Sci-Tech Talent and Economic Growth in the Pan-Yangtze River Delta of China," Sustainability, MDPI, vol. 13(12), pages 1-18, June.
    4. Wang, Minggang & Xu, Hua & Tian, Lixin & Eugene Stanley, H., 2018. "Degree distributions and motif profiles of limited penetrable horizontal visibility graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 620-634.
    5. Yi Zhang & Guangqiu Huang, 2023. "Identifying network structure characteristics and key factors for the co-evolution between high-quality industrial development and ecological environment," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(7), pages 6591-6625, July.

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