Methods and models for assessing the state of the region's human resources potential
Year: 2024
Type: article
Abstract: Relevance. One of the strategic goals of the development of the regional economy is to improve the socioeconomic condition of the region, which is based on human resources. The Forecast of the long-term socio-economic development of the Russian Federation for the period up to 2030 notes that economic growth will be possible due to certain factors, among which the human resource occupies an important place. Since in the modern arena of the world economy there is a struggle for the ability to introduce innovations, the use of intellectual capital, the knowledge economy needs to take the main place in the socio-economic development of society, given that human resources is one of the fundamental factors in achieving leading positions.The purpose is to conduct a comprehensive study of methods for assessing the human resources potential of the region.Objectives: to identify the features of approaches to the interpretation of the concept of "human potential", to study models for forecasting human potentialMethodology. The following methods were used in the research process: logical and statistical analysis, qualitative and quantitative analysis, as well as an expert approach.Results. Different approaches to the definition of human resources were considered, existing methods of assessing human resources were analyzed, the authors proposed a methodology for assessing human resources and studied the process of its formation.Conclusion. The proposed methodology allows us to determine the choice of preventive measures to build human resources and meet the indicators of the Forecast of social and economic development of the region. Also, this technique can be used to generate staffing requirements and admission control figures.
Authors: E. V. Kharchenko, V. S. Zhukova, E. A. Sysoeva, M. V. Vasilyeva
Institution: Financial University
Language: English
Subfield: Management, Monitoring, Policy and Law
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4405146672