Abstract
With to the impact of economic globalization, the talent construction of key disciplines in science and technology should be administrated with humanism. An analysis of existing articles shows that the research of talent development mainly relates to the following aspects: cultivating objectives, cultivator, cultivation way, and evaluation criteria. In recent years, with the continuous improvement of education system in China and the increased awareness of talents, the talent construction of key discipline in science and technology has been greatly improved. With the actuality and circumstance analysis of the talent construction of key disciplines, a talent planning model is proposed to the key disciplines in science and technology. The proposed model is III-level tree structure, of which there are 2 I-level indexes, 8 II-level indexes and 23 III-level indexes. The Analytic Hierarchy Process is employed to determine the weights of talent planning indexes. This research will make the more scientific, systematic, strategic talent planning, and adapt to the development needs of key disciplines.
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Acknowledgements
This work is supported by the Development Project of Jilin Province of China (No. 20170101006JC, 20160414009GH, 20160204022GX, 20170203002GX), China Postdoctoral Science Foundation (No. 2016M601379), Premier-Discipline Enhancement Scheme supported by Zhuhai Government and Premier Key-Discipline Enhancement Scheme supported Guangdong Government Funds. This work is also supported by the National Natural Science Foundation of China (71331008), Foundation for the Author of National Excellent Doctoral Dissertation of PR China (2014-92), the Outstanding Youth Fund Project of Hunan Provincial Natural Science Foundation (S2015J5050), the Fundamental Research Funds for the Central Universities (531107050772) and Shenzhen Basic Research Project for Development of Science and Technology (JCYJ20160530141956915).
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Xu, H., Wu, D., Xing, L. et al. The talent planning model and empirical research to the key disciplines in science and technology. Cluster Comput 20, 3275–3286 (2017). https://doi.org/10.1007/s10586-017-1060-8
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DOI: https://doi.org/10.1007/s10586-017-1060-8