The Role of Demographic Processes in the Digital Transformation of Industrial Regions

Kursat Demiryurek (), Ludmila Glezman () and Irina Tsarenko ()
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Kursat Demiryurek: Ondokus Mayis University
Ludmila Glezman: Institute of Economics of the Ural Branch of the Russian Academy of Sciences
Irina Tsarenko: Institute of Economics of the Ural Branch of the Russian Academy of Sciences

A chapter in The Future of Industry, 2024, pp 347-358 from Springer

Abstract: Abstract The article identifies the current problems of the modern Russian labor market. To study them more closely and provide solutions, the paper proposes a methodological toolkit for assessing the use and impact of labor resources on the development of an industrial region in the conditions of digital transformation. The testing was carried out in the regions of the Volga Federal District of the Russian Federation (hereinafter the Volga Federal District), where a quarter of the country’s industrial production is concentrated. According to the testing results, the demographic factor was recognized as the most significant for the development and effective functioning of the labor market among numerous factors affecting the regional labor market amid digital transformation of industry. The analysis revealed the problems in the structure of available labor resources in the Volga Federal District, including the growing deficit of labor resources associated with the decline in the number of people below working age and the decline in the output of middle-level specialists (technical specialties). The results of the study confirm that the implemented set of state support measures is not fully efficient, so it is necessary to develop and introduce new tools and mechanisms that regulate the sustainable development of labor potential and meet the conditions of the transformational economy in the country’s industrial regions.

Keywords: Labour market; Labour resources; Demography; Digital transformation; Able-bodied population; Population reproduction; Workforce; Professional orientation (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnichp:978-3-031-66801-2_23

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DOI: 10.1007/978-3-031-66801-2_23

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