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Journal of library and information science in agriculture ›› 2021, Vol. 33 ›› Issue (6): 66-80.doi: 10.13998/j.cnki.issn1002-1248.21-0389

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• Bibliometrics • Previous Articles     Next Articles

Academic Origin Structure and Mobility Network of Technological Talent in Chinese Universities

HOU Jianhua, GENG Bingbing, ZHANG Yang*   

  1. School of Information Management, Sun Yat-Sen University, Guangzhou 510006
  • Received:2021-03-15 Online:2021-06-05 Published:2021-06-15

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Abstract: [Purpose/Significance]This paper analyzes the structure of academic origin and the characteristics of talent mobility between universities, and puts forward suggestions on optimizing the structure of academic origin and rationally arranging talent resource to optimize the structure of the scientific research team and promote academic innovation and scientific research output. [Method/Process] This article uses statistical analysis and social network analysis methods to analyze the academic origin structure of scientific and technological talent in the field of artificial intelligence in Chinese universities from the aspects of hierarchy, extensiveness, and aggregation. At the same time, the talent mobility network between universities in this field is explored from the aspects of trans-school mobility, trans-regional mobility and university attribute. [Results/Conclusions] This article proposes that universities should change their concept of employment, introduce talent competition mechanisms, openly recruit talent from all over the world, and create more academic exchange opportunities such as increasing learning exchange programs between universities. The government needs to strengthen policy guidance, increase funding support, formulate laws and regulations, etc., in order to achieve the goal of optimizing the structure of academic origin, promoting the mobility of talent, and rationalizing the structure of the scientific research team.

Key words: scientific and technological talent, academic origin structure, talent mobility, social network analysis

CLC Number: 

  • G353.1
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