A three-dimensional case is considered on the basis of a method developed for estimating the parameters of the aggregated production function used to calculate dynamic standards and build integral indicators of the performances of the functioning of socio-economic systems. The aggregated production function is determined by the quadratic convolution of the production functions of the results of the functioning of the elements of the subsystem and their correlation matrix. The parameters of the aggregated production function are determined from solving the problem of maximizing the likelihood function of a random variable – the residuals of production functions aggregated according to a similar rule. On the example of a project subsystem within the framework of the Kleiner’s spatial-temporal classification of socio-economic systems we obtained adjusted values of the parameters of a function that includes power-law multiplicative models of the relationship between the volume of gross domestic product by region for sections F (construction), G (wholesale and retail trade), K (financial activity) according to NACE 2 and the cost of fixed assets (total for section K, for sections F and G), the average annual number of employees (for sections F and G) and the average annual population (for section K), based on data for 2015–2020 (sections G, K) and 2018–2020 (section F) for the regions of the Central Federal District. The EFRA software package and Python’s project were used as tools. The results obtained can be used by regional authorities in assessing the functioning of the regions and the formation of appropriate standards in the short term.
The development of regional socio-economic and ecological systems requires informed decisions. In this, decision-making authorities can be helped by models of such systems, which include three interrelated subsystems: social, environmental and economic, which may include subsystems of a lower level. The object of the study is hierarchical socio-ecological-economic systems (SEES) with homogeneous performance characteristics at all levels of management. The subject of the study is the characteristics of the processes of influence of factors on the results of the functioning of a hierarchical SEES in order to develop control actions that provide a given level of target indicators. The purpose of the study is to model the functioning of socio-ecological and economic systems based on a multi-level optimization approach under conditions of uncertainty, with the help of which it is possible to find changes in factors that allow improving the goal indicators of the SEES functioning. Based on the constructed models of the state and functioning of complex systems for the regions of the Central Federal District and the Tula Region using statistical data for 2007-2020, a multilevel optimization approach to the management of socio-economic systems was applied, proposals aimed at ensuring the sustainable development of the Tula region in the ecological subsystem were substantiated.
Zhukov Roman Aleksandrovich -candidate of physics and mathematics sciences, Financial University under the Government of the Russian Federation (Tula Branch) (Tula).
The effective ensure of sustainable development of regions, including the Tula region, characterized by an unfavorable demographic situation, the presence of environmental problems and stagnation of industrial production, without the use of economic and mathematical apparatus and tools for data analysis and decision-making is difficult to implement. At the same time, most decisions are made on the basis of expert assessments, and this is typical for most Russian regions. The development and implementation of modern decision-making methods based on multi-criteria optimization will increase the validity of such decisions at various levels of management, and which can be applied not only in the Tula region, but also in other regions to solve their problems. The purpose of the study is to develop and test a method for optimizing the results of the functioning of socio-ecological-economic systems on the example of the regions of the Central Federal District and the district as a whole on the basis of the author's methodology within the framework of a multi-level optimization approach. The results of the study show that due to changes in values of factors included in the optimization model of the socio-ecological-economic systems functioning, which was developed on the basis of the author's methodology. It is possible to improve the target indicators of the development of the Tula region. The presented methodology can be used for other regions, which expands the scope of its application.
На основании проведенного опроса граждан Тульской области в 2019 г. с использованием прямого анкетирования оценен уровень цифровой грамотности населения. Обоснованы предложения, направленные на повышение уровня цифровизации населения Тульского региона и обеспечение граждан доступом к цифровым ресурсам. Сделан вывод об уровне цифровых компетенций и возможности сокращения цифрового дисбаланса между различными слоями населения Тульской области. Результаты могут быть использованы органами государственного управления для формирования региональных программ ликвидации цифрового неравенства и развития цифровой экономики в Тульской области. Based on the conducted survey of citizens of the Tula region in 2019, the level of digital literacy of the population was estimated using a direct questionnaire. The proposals aimed at increasing the level of digitalization of the population of the Tula region and providing citizens with access to digital resources are substantiated. The conclusion is made about the level of digital competencies and the possibility of reducing the digital imbalance between different segments of the population of the Tula region. The results can be used by public authorities to form regional programs for the elimination of digital inequality and the development of the digital economy in the Tula region.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.