Labor potential and its attributes in the context of digital transformation and technological sovereignty in the Russian Arctic

One of the key challenges in achieving sustainable regional development is the effective utilization of labor potential within a territory. Major disparities in labor potential are observed across regions, driven by factors such as natural and climatic conditions, demographic trends, varying levels of industrial and transport infrastructure development, and government benefits. This issue is particularly pronounced in the Russian Arctic, a region of strategic importance to Russia. In the context of digital transformation, technological sovereignty, depopulation, and migration outflows, there exists a strong correlation between labor potential and workforce availability in these territories. The development of this macro-region necessitates a well-structured human resource strategy. This study aims to develop and test a methodology for forecasting labor potential levels in the context of digitalization and technological sovereignty, using data from regions within the Russian Arctic. The methodology comprises three stages: (1) identifying determinants and collecting relevant statistical data, (2) compiling a forecast data set based on dynamic series and calculating indices, and (3) utilizing a matrix framework to evaluate and rank territorial performance based on specified criteria. The study employs methods such as comparison, grouping, forecasting, visualization, and matrix techniques, as well as correlation and cluster analysis. Its scientific novelty lies in redefining the concept of "labor potential" within the framework of digitalization and technological sovereignty, and in creating a new typology of regions based on labor potential levels.