摘要
高层次科技创新人才的引进越来越受到世界各国的重视,我国高层次科技创新人才引进存在着盲目性和随意性、人才信息的有限性和匮乏性以及人才集聚效应差等问题,这些问题阻碍了我国高层次科技创新人才引进工作的有效开展。高层次科技创新人才迭代引进模型将人才引进视为一个持续、反复进行的迭代过程,由内外双迭代的总循环和三个子循环构成;科学知识图谱、社会网络分析以及迭代算法为模型的运行提供了方法保障。山东省海洋科技创新人才引进的案例分析表明,高层次科技创新人才迭代引进模型能够提高高层次科技创新人才引进的科学性和有效性,实现我国高层次科技创新人才的持续集聚效应。
The introduction of high-level scientific and technological innovation talents has been paid increasing attention by all the countries in the world.There exist such problems as blindness and randomness,limitation and scarcity of talent information,and poor talent aggregation effect in China’s introduction of high-level scientific and technological innovation talents,which hinder China’s effective implementation of high-level scientific and technological innovation talent introduction.The iterative introduction model of high-level scientific and technological innovation talents regards talent introduction as a continuous and repeated iterative process which consists of a total cycle of internal and external double iterations and three sub-cycles,and the scientific knowledge atlas,social network analysis and iterative algorithm provide the method guarantee for the operation of the model.The case analysis of Shandong Province’s introduction of marine scientific and technological innovation talents shows that the iterative introduction model of high-level scientific and technological innovation talents can improve the scientificalness and effectiveness of high-level scientific and technological innovation talent introduction and realize the continuous aggregation effect of high-level scientific and technological innovation talents in China.
作者
杨明海
王天哲
刘桐桐
YANG Minghai;WANG Tianzhe;LIU Tongtong(School of Business Administration,Shandong University of Finance and Economics,Jinan 250014,China)
出处
《山东财经大学学报》
2022年第6期85-97,共13页
Journal of Shandong University of Finance and Economics
基金
山东省社会科学规划研究项目“山东省实施创新驱动和人才强省战略研究”(19BJCJ14)。
关键词
高层次科技创新人才
PII迭代引进模型
科学知识图谱
社会网络分析
迭代算法
high-level scientific and technological innovation talent
PII iterative introduction model
scientific knowledge atlas
social network analysis
iterative algorithm
