Тип публикации: научное издание
Год издания: 2021
Идентификатор DOI: 10.1007/978-3-030-56433-9_82
Ключевые слова: changing business needs, clusters of professional competencies, innovative development, labor market, labor resources, region, sector of the economy, zone of accelerated development
Аннотация: The relevance of identifying accelerated development zones in the region’s economy to reduce the gaps between the supply and demand parameters in the labor markets is explained by the need to determine the lists of professional competencies and professions for which there is currently no generated demand from business. To reduce thПоказать полностьюe level of uncertainty in solving the problem, it is advisable to localize the area of the search for the expected changes in the demand for professional competencies of labor resources in those areas of the economy where organizational, technological, marketing and other types of innovations will be introduced. The aim of the study is to develop an algorithm for identifying areas of accelerated development in the region. Based on the content analysis of scientific publications on the study of the structure of the regional economy, the authors divided the concepts of “economy sector” and “accelerated development zone”. Characteristics are identified that allow identifying accelerated development zones by spatial distribution in the region, belonging to the type of economic activity, technological efficiency and investment activity. Based on multicriteria selection, the article proposes an algorithm for identifying areas of accelerated development in sectors of the region’s economy, the staffing needs of which will be reoriented to new professional competencies. On the example of the Krasnoyarsk Territory, the proposed algorithm was tested, accelerated development zones were established for macro-regions and types of economic activity, quantitative characteristics of labor resources were determined for which changes in business needs with respect to professional competencies are most likely. © 2021, Springer Nature Switzerland AG.
Журнал: Studies in Systems, Decision and Control
Выпуск журнала: Vol. 314
Номера страниц: 777-787
ISSN журнала: 21984182
Издатель: Springer Science and Business Media Deutschland GmbH