大数据背景下高校人力资源管理的作用、限制与提升路径研究
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孔文烁,袁博,孔祥通
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1. 山东体育学院,山东济南,250102;2. 曲阜远东职业技术学院,山东曲阜,273100
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摘要:随着大数据时代的到来,数据驱动决策已成为组织管理变革的核心趋势。高校作为知识密集型组织,其人力资源管理正面临前所未有的机遇与挑战。本文旨在系统探讨大数据技术在高校人力资源管理中的应用价值、现实困境及未来发展路径。文章首先阐释了大数据的内涵及其与高校人力资源管理的逻辑关联,进而从战略决策、人才引进、师资发展、绩效评价及服务效能五个维度,深入剖析了大数据的关键作用。随后,本文客观分析了当前实践中的数据壁垒、技术瓶颈、人才短缺、伦理风险及成本效益等主要限制因素。最后,针对性地提出了构建一体化数据平台、培育数据文化、创新人才队伍、健全伦理规范及实施渐进式开发等五位一体的提升路径,以期为推动我国高校人力资源管理的数字化、科学化与智能化转型,构建“数据驱动型”人力资源治理新模式提供理论参考与实践框架。
关健词:大数据;高校人力资源管理;数据驱动;作用;限制;提升路径 |
Research on the Role, Limitations, and Improvement Paths of University Human Resource Management in the Context of Big Data
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Wenshuo Kong,Bo Yuan,Xiangtong Kong
1.Shandong Institute of P.E. and Sports, Jinan, Shandong 250102, China;2.Qufu Far East Vocational and Technical College, Qufu, Shandong 273100, China
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Abstract:With the advent of the big data era, data-driven decision-making has become a core trend in organizational managementreform. As knowledge-intensive organizations, universities are facing unprecedented opportunities and challenges in theirhuman resource management (HRM). This paper aims to systematically explore the application value, practical difficulties, andfuture development paths of big data technology in university HRM. The article first explains the connotation of big data and itslogical connection with university HRM. Then, it deeply analyzes the key roles of big data from five dimensions: strategic decision-making, talent recruitment, faculty development, performance evaluation, and service efficiency. Subsequently, this paperobjectively analyzes the main limiting factors in current practice, including data silos, technical bottlenecks, talent shortages,ethical risks, and cost-effectiveness. Finally, it specifically proposes a five-in-one improvement path comprising building an integrateddata platform, cultivating a data culture, innovating the talent team, improving ethical norms, and implementing gradualdevelopment, with a view to providing a theoretical reference and practical framework for promoting the digital, scientific, andintelligent transformation of HRM in Chinese universities and building a new“ data-driven” human resource governance model.
Keywords : Big Data; University Human Resource Management; Data-Driven; Role; Limitations; Improvement Paths
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