The relevance of the presented research lies in the existence of a number of signs that clearly indicate that the global economic crisis that began in 2020 has not yet ended. The purpose of the presented research is to isolate anti-Russian sanctions of the collective West as an independent indicator of the destabilization of the world economic system, indicating its state of crisis. The scientific novelty of the results obtained lies in the fact that the presented work shows that the ongoing sanctions pressure on Russia, considered as a pilot project for a possible subsequent sanctions war against China (including a possible forceful clash between China and Taiwan), indicates the absence of a global economic development of such solutions that would demonstrate that the effect from the implementation of technologies related to the vector of one’s own creation (primarily due to the introduction of technologies of the new (sixth) technological order) is higher than the effect from the implementation of technologies related to the vector of weakening the positions of competitors (up to the outbreak of local wars), which gives reason to consider the intensity of Western anti-Russian sanctions as one of the significant indicators of the course of the global economic crisis. The practical significance of the results obtained in this study lies in the possibility of their use in assessing the processes of the current economic crisis and predicting the prospects for overcoming it.

For a long time, geographically close countries were economically isolated from each other due to political factors, neglecting the obvious advantages of mutual cooperation. However, over the past two decades, the economic component has become the cornerstone of bilateral relations. Cooperation between Cambodia and Vietnam is developing dynamically and has a positive impact on the development of the economies of both countries. An increase in bilateral trade helps not only to meet the needs of the population and expand the sales market for products, but also to strengthen the export potential of Cambodia and Vietnam on the world market, what is more the latter at the expense of the former. There has also been an increase in intra-industry trade in recent years, indicating the beginning of vertical integration, taking into account identified comparative advantages. An important role is also played by Vietnam’s implementation of investment projects that fill empty niches, create the necessary infrastructure, make a significant contribution to socio-economic development, social security, stimulate the growth of budget revenues, and also create jobs in Cambodia. Vietnam has emerged as one of Cambodia’s most important trade and investment partners, increasing its presence in the neighboring market and playing an important role in the country’s development. Cambodia’s economy is booming, thanks in large part to developments in Vietnam’s (and, of course, China’s) sphere of influence. This confirms the theory of the benefits of flying “with a flock of geese.” Vietnam is historically and mentally inclined to help Cambodia through this influence, and apparently does not represent another model of relations. At the same time, there are also negative aspects of cooperation, such as inequality of trade and investment flows, Cambodia’s growing economic dependence on its neighbor, and weak integration. The study of the main aspects of Vietnam’s economic influence on Cambodia has become increasingly relevant in recent years. At the same time, the issue of Cambodian-Vietnamese trade and investment interaction has been poorly studied.

This article is devoted to the study of economic relations between Japan and the PRC in 2000–2020. The main indicators of bilateral trade, its structure, indicators of bilateral foreign direct investment between Japan and the PRC are presented and analyzed in the article. An assessment of the current state of Japanese-Chinese economic relations was given, factors affecting their development over the past 20 years were determined using the method of generalization of research materials, methods of comparative and correlation analysis of data, analytical method of information processing. The authors conclude that during the period under review, economic cooperation between Japan and China in trade and investments is expanding and strengthening, and their economic interdependence is increasing. The interest of Japanese corporations in carrying on business and opening branches in the PRC is indicated as the main factor of development. Political instability in bilateral Japanese-Chinese relations is indicated as a deterrent. The authors emphasize that in order to further increase the successful and stable development of economic partnership, the two states need to take specific steps for the purpose of political rapprochement and finding a compromise on controversial issues.

The article examines the trends in the production of the main types of agricultural products in the world based on the analysis of the OECD-FAO forecast for the next decade 2023–2032. According to this forecast, by 2032, world agricultural production in value terms will increase by 17%. The strengthening of the role of developing countries in the production of agricultural products is the main trend in the development of world agricultural production, which is based on population growth, the need to ensure food security in connection with the sanctions policy of Western countries, which led to a change in trade relations and disruption of logistics supply chains of products. According to the OECD-FAO forecast, the countries of the Asia-Pacific region, as well as the countries of Africa, will provide more than 70% growth in crop production. Developing countries will account for about 60% of livestock production by the end of the decade. The main growth factor will be an increase in crop yields and animal productivity based on the intensification of production and an increase in the level of scientific and technological support for the industry. The article also examines the main trends in the development of production and consumption of agricultural products in Russia for the next decade and determines the level of self-sufficiency in basic food products, which Russia will reach by 2032.

The article reviews the drivers and main goals of the Kunming-Montreal Global Biodiversity Framework (GBF), adopted by 196 countries during COP-15 in December 2022. The overarching aim of the GBF is to halt and reverse nature loss by 2030, in particular restore 30% of critical biodiversity areas. The targets should be translated into national-level policy concerning governments, global and national environment funds as well as private sector actors, including financial institutions. The GBF is analyzed in close connection with Paris agreement on climate change 2015 and Sustainable Development Goals. It is shown that a lot of GBF’s actions follow the example of those declared in the Paris agreement. The research is focused on the evaluation of the opportunities and challenges for the realization of GBF. The largest part of its stakeholders considers biodiversity as a unifying concept, that can help reduce the current political polarization that exist in relation to decarbonization in particular and to ESG principals as a whole. But difficulties and barriers also exist. One of them is the complicity of biodiversity impact, because it is not quite clear what to measure and how to measure. Probably the largest problem here is a lack of financial resources allocated to protection of ecological systems, especially in developing countries. So, the author comes to conclusion that despite approval of the aims of the GBF, practical actions taken by governments and business are scarce, and the conservation of biodiversity is seen as priority only in public discussions.

The relevance of the study lies in the fact that in modern conditions, artificial intelligence systems are increasingly used to support management decisions regarding the formation of an organization’s development strategy and other tasks. The purpose of the study is to forecast the profit of a credit institution using the Random Forest Regressor method to support management decision-making in a digital ecosystem. Among the methods in the presented work, the deep learning model "Random Forest" (RF — random forest), a multivariate regression model based on artificial intelligence, and the Graphviz program were used. Moreover, for the 7-factor DL model, the "Mean Absolute Error" (MAE) was 13.299, the "Root Mean Square Error" (MSE) reached 176.889, and the "Root Mean Square Error" (RMSE) amounted to 31289.71832. Moreover, in the 10-factor model, the above parameters had values respectively: 21.95, 20.532 and 421.563024. That is, judging by the value (MAE), the 7-factor model turned out to be more accurate. The scientific novelty lies in the fact that a machine learning model has been developed based on the "Deep Learning Random Forest" method, which provides support for management decisions, allowing one to obtain a reliable forecast of the bank’s net profit. The solution to this problem has important practical significance. Rospatent certificate for the computer software program No. 2023666284 dated July 28, 2023 was received. The hypothesis was put forward and proven that the use of the Random Forest DL artificial intelligence system makes it possible to obtain a forecast of the net profit of a credit institution. As a result of the study, conclusions were formulated. The processes of increasing digitalization are rapidly changing the financial world. An important role in modern conditions is played by the use of modern artificial intelligence systems to provide support for management decisions. The developed machine learning model based on the "Machine Learning Random Forest" method allows us to obtain a forecast of Sberbank’s net profit for the next year. Among the directions for further scientific research, it should be noted the identification of patterns and factors influencing the behavior of the resulting attribute — the net profit of a commercial bank.