At the present time, an effective methodological toolkit has not been developed to manage economic processes in modern conditions in order to ensure the sustainable economic development of enterprises. On the basis of mathematical modeling, it has been proposed that such a tool could be created to provide a quantitative assessment of the main parameters in the creation of innovative products and activities of enterprises. Additionally, on the basis of this tool, decision makers could regulate these processes by introducing additional resources and buying risks. For this purpose, it is necessary to modernize the means of production, which requires a reassessment of the technical level of enterprises. It is possible to achieve these parameters through a certain technical policy of production modernization. In this aspect, the technical policy of enterprises should consider the fact that, depending on the complexity of innovative products put for development and production, the time lag between the start of production of such products and the moment when they enter the market with competitive advantage changes. This competitive advantage is determined by the design methods at a given cost. At the same time, the service models of enterprises are used as one of the most important tools to achieve the profitability of the enterprise, leading to its sustainable economic development. As a result of the proposed toolkit, a strategy for managing the processes of the sustainable economic development of enterprises could be developed based on the creation of an intelligent system using artificial intelligence and the use of large databases that create information support for decision makers to regulate these processes. This set of tools makes it possible to achieve the organization of sustainable economic development. To assess the technical, economic, and technological level of the enterprise, a complex integral indicator was obtained on the basis of mathematical modeling. It was proposed to confirm the obtained integral assessment by comparing the obtained calculated data with an expert assessment. The method of expert evaluation is used in the article. Expert assessments were obtained in science-intensive organizations in which the authors held managerial positions and were engaged in scientific projects. The obtained inputs were formulated based on the analysis of the reporting documentation provided by the organizations. The conducted research indicates the importance of the proposed practical recommendations and materials for solving the tasks set in this study.

Sustainable management in high-tech enterprises is a key aspect of successfully operating modern companies, especially under conditions of risk and uncertainty. This study reviews the field of sustainable management and interval analysis and identifies the main trends and challenges facing high-tech enterprises in the modern world. This study emphasizes the importance of applying interval analysis in making strategic decisions and developing sustainable business models that can adapt to variable environments. This paper presents empirical data, illustrating the practical application of interval analysis tools in the management in high-tech enterprises. It analyzes the effectiveness and potential of this approach to increase the levels of sustainability and competitiveness of organizations in constantly changing business environments. In general, this article is a valuable contribution to the development of sustainable management theory and practice for high-tech enterprises, enriching the existing knowledge in this area and offering new perspectives for research and practical application. Our research has been validated and is presented in the results section. The purpose of this study is to present current developments in methodologies and tools for risk measurement within the probabilistic paradigm of uncertainty, which are supposed to be used in relation to the economic evaluation of real investment projects. The methodological directions or approaches to risk measurement formed in this context are (1) based on quantile measures, within which the quantitative aspect of risk is modeled using quantile quantiles of the distribution of a random variable describing the possible (predicted) results of economic activity; (2) the Monte Carlo method, which is a tool for evaluating the indicators of economic efficiency and risk in justifying real investments, taking into account different distribution laws and mutual relations for the financial and economic parameters of the investment project, as well as its computational and instrumental elaboration.

This study analyzed the sustainable economic development of some organizations for the period of 2020–2022. The authors found that organizations’ sustainable development is influenced by technological superiority based on the creation and production of radical new products that can form new markets or be dominant in existing ones. This study examined effective management based on the application of digital technology and artificial intelligence for the creation and production of radically new products, which creates conditions for the advanced sustainable economic development of the organization. The main drivers of these processes are technological platforms, the formation of which requires significant amounts of different types of resources. To solve the issue of investment in the creation of radically new products in conditions of limited resources, the authors researched and developed tools for the effective use of investment in the creation of radically new products in order to ensure the formation of organizations of advanced, sustainable economic development. In the development of methodological tools for managing the creation and development of radically new products, a conceptual mathematical model for assessing the criteria of economic efficiency of projects is proposed. Thus, the proposed tools for managing the creation of radically new products and advanced sustainable economic development of organizations form the basis for technological superiority and sustainable economic development in modern economic conditions.

The modern system of higher education and research is undergoing deep institutional transformations, accompanied by changes in funding mechanisms, increased competition, the growing importance of project forms of scientific activity organization, and more complex requirements for performance. In the conditions of digital transformation and institutional instability, higher education faces the need to form sustainable smart management systems. The modern understanding of smart education goes beyond e-learning and includes the intellectualization of all levels of organization of educational and scientific activities. This requires the creation of new models capable of integrating the behavior of teachers and researchers in the context of digital, project, and institutional logics. Thus, the task of building intelligent models capable of reflecting the complex, multi-layered structure of interactions between researchers, organizations, forms of support, and the system of evaluation of scientific work becomes relevant. This article proposes an agent-based approach to modeling the process of formation of scientific knowledge, considered as a key element of the sustainable development of scientific and educational environment. The model reflects the interaction of agents—researchers with different characteristics: age, qualification level, scientific productivity, affiliation, and trajectory of professional development. The modeling results allow us to draw conclusions about the regularities of the reproduction of scientific potential, the factors of academic environment sustainability, and the effectiveness of institutional support mechanisms. The obtained results have both theoretical and applied significance. The model can be used to forecast the effectiveness of science policy, assess the risks and prospects of scientific teams, and justify incentive systems and the long-term design of the development of scientific organizations. The presented approach allows us to form a comprehensive view of the dynamics of scientific knowledge in the context of sustainable management in higher education.

This work was based on empirical studies of the credit register and loans issued, which have been compiled by all Russian banks since 2017, for the analysis of bank interest rates by a common factor and subject to the control of the characteristics of the loan. These dates identified bank-specific components in the management information system; also, the same data were used to measure the fragmentation of the accounting lending market in Russia. This paper illustrates the credit market in Russia during the COVID-19 pandemic by analyzing the management of loan rates with existing differences due to the heterogeneity of banks and borrowers in order to achieve a sustainable management system. The results show that the heterogeneity of banks’ decision-making when setting interest rates is high and increased at an early stage of the pandemic. Additionally, the results demonstrate that the banks tightened interest-free lending conditions during the pandemic for sustainable management goals.