铁路科技人才胜任力模型构建研究OA北大核心
Competency Model Construction for Railway Science and Technology Talents
铁路科技人才是实现铁路高水平科技自立自强、增强中国铁路战略科技力量的关键要素,建设高水平铁路科技人才队伍是推动铁路高质量发展、率先实现铁路现代化的重要举措.基于冰山模型理论,从专业素养、学习创新、管理能力、动机、人际能力、个性品质等6个维度,提出铁路科技人才胜任力模型理论框架,通过BEI访谈、问卷调查等实证研究编制铁路科技人才胜任特征词典,构建铁路科技人才胜任力模型,提出细化完善铁路科技人才培养目标、健全铁路科技人才教育培训体系、健全铁路科技人才梯队培养机制、完善铁路科技人才数字化管理模式、构建有效的铁路科技人才胜任力测评方式方法体系等铁路科技人才胜任力提升对策,以期为高水平铁路科技人才队伍建设提供支持.
Railway science and technology talents are a key factor in realizing self-reliance in high-level railway science and technology and strengthening the strategic scientific and technological force of China's railway.Building high-level railway technology and science talent team is an important measure to promote high-quality railway development and take the lead in realizing railway modernization.Based on the iceberg theory,this paper proposed a competency model framework for railway science and technology talents from six dimensions:professional competency,learning and innovation,management ability,motivation,interpersonal ability,and personality quality.Through empirical research such as BEI interviews and questionnaire surveys,this paper compiled a dictionary of competency characteristics for railway science and technology talents and developed a competency model for railway science and technology talents.Measures for enhancing the competency of railway science and technology talents were suggested,including refining training goals,enhancing the education and training system,improving the development mechanism for backup talents,establishing digital management modes,and constructing effective competency evaluation method systems,to provide support for high-level railway science and technology talents team building.
路云军;张力;刘剑;赵会军
中国铁道科学研究院集团有限公司,北京 100081中国铁道科学研究院集团有限公司人力资源部(党委组织部),北京 100081中国铁道科学研究院集团有限公司 科技和信息化部,北京 100081中国铁道科学研究院集团有限公司 铁道技术研修学院,北京 100081
交通运输
铁路科技人才胜任力词典胜任力模型胜任力培养
Railway Science and Technology TalentsCompetency DictionaryCompetency ModelCompetency Development
《铁道运输与经济》 2024 (006)
153-160 / 8
中国铁道科学研究院集团有限公司科研项目(2022YJ343)
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