人力资源数字化对企业核心竞争力的重塑与优化
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张彪，郑铭颖，张湧滔，陈丽，陈毓慧
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广州工商学院，广东广州，510000
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摘要：在数字经济时代，企业置身于快速变化且竞争激烈的市场环境。人力资源数字化对企业提升效率、优化管理意义非凡，是增强核心竞争力的关键手段。研究表明，其通过重塑组织架构、人才管理和决策模式，优化流程、人才和成本来达成这一目的。企业要想实现人力资源数字化，需明确转型战略规划，引入人工智能、大数据等技术构建协同应用与员工自助服务平台，并且提高员工数字素养，组建多元化团队，营造创新文化。然而，企业也面临数据安全隐私保护、技术应用成本与难度等挑战。展望未来，人力资源数字化会朝着更智能、个性化的方向发展。由此可见，企业应积极适应变化，不断探寻新模式与新方法，这样才能在市场中保持领先，达成可持续发展。
关健词：人力资源数字化；核心竞争力；组织架构重塑；人才管理优化；数据驱动决策
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The Remodeling and Optimization of Enterprise Core Competitiveness by Human Resource Digitalization
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Biao Zhang,Mingying Zheng, Yongtao Zhang,Li Chen, Yuhui Chen
Guangzhou College of Technology and Business, Guangzhou, Guangdong，510000, China
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Abstract：In the era of digital economy, enterprises operate in a market environment characterized by rapid changes and fierce competition. Human resource digitalization is of great significance for enterprises to improve efficiency and optimize management, and it serves as a key means to enhance core competitiveness. Research shows that it achieves this goal by remodeling organizational structure, talent management and decision-making models, as well as optimizing processes, talent allocation and costs. For enterprises to realize human resource digitalization, they need to clarify the transformation strategic plan, introduce technologies such as artificial intelligence and big data to build collaborative application and employee self-service platforms, improve employees' digital literacy, form diversified teams, and cultivate an innovative culture. However, enterprises also face challenges such as data security and privacy protection, as well as the cost and difficulty of technology application. Looking ahead, human resource digitalization will develop in a more intelligent and personalized direction. It can be seen that enterprises should actively adapt to changes and continuously explore new models and methods to maintain a leading position in the market and achieve sustainable development.
Keywords : Human Resource Digitalization; Core Competitiveness; Organizational Structure Remodeling; Talent Management Optimization; Data-Driven Decision-Making
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