Strategic Workforce Development of the Staffing in the Russian Federation

P. Popov
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引用次数: 0

Abstract

The article analyzes the current state of the electric power industry of the Russian Federation, identifies priority areas for its development in the context of the availability of modern technologies, such as artificial intelligence, digital twins, and a virtual reality system. The possibility of replacing human labor resources by electric power with artificial intelligence is considered in the context of the priority policy of using the best available technologies with minimal harm to the environment. The key directions of the strategic development of the labor resources of the electric power industry in Russia are studied, taking into account the specifics of the region, as well as the features of the development of the industry. The fundamental principles of the strategic development of labor resources are analyzed, taking into account the characteristics of the economic sector, and the possibility of applying the strategizing methodology proposed by Doctor of Economics, Professor, foreign member of the Russian Academy of Sciences V. L. Kvint is considered. The problematic aspects of labor efficiency in the electric power industry, including those related to cybersecurity threats in modern conditions, are highlighted, and practical cases of solving these problems by government agencies and various business entities are analyzed. Ways are proposed to overcome difficulties, taking into account the costs inherent in each of the options, in order to increase the performance of enterprises in the electric power industry and their further improvement.
俄罗斯联邦人力资源战略发展
文章分析了俄罗斯联邦电力行业的现状,在人工智能、数字孪生和虚拟现实系统等现代技术可用的背景下,确定了其发展的优先领域。在使用对环境危害最小的最佳可用技术的优先政策背景下,考虑了用人工智能取代电力人力资源的可能性。考虑到该地区的具体情况以及该行业发展的特点,研究了俄罗斯电力行业劳动力资源战略发展的关键方向。分析了劳动力资源战略开发的基本原则,考虑到经济部门的特点,并考虑了应用俄罗斯科学院外籍成员、经济学博士V.L.Kvint教授提出的战略制定方法的可能性。强调了电力行业劳动效率的问题方面,包括与现代条件下的网络安全威胁有关的问题,并分析了政府机构和各种商业实体解决这些问题的实际案例。提出了克服困难的方法,同时考虑到每种选择所固有的成本,以提高电力行业企业的绩效并进一步改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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131
审稿时长
12 weeks
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