In the evolving economic landscape, Industry 4.0 emphasizes strategic planning and operational progress for large enterprises. This transformation relies on smart robotization technologies like AGVs (Automated Guided Vehicles) and AMRs (Autonomous Mobile Robots) for reducing transportation time, thereby reducing energy costs per unit of production, increasing energy efficiency, as well as replacing combustible-fuel-powered tools with electric ones. A number of concerns arise with their introduction into the production cycle. This research aims to provide a methodical basis for averting substantial mistakes when executing projects centered around the incorporation of AGVs/AMRs into in-house logistics systems. The FMEA method and empirical analysis were employed to achieve a more accurate risk assessment. APIS and MS Excel softwares were chosen. We investigated the potential hazards related to the incorporation of mobile robotic solutions and identified both external and internal threats. To streamline and improve project efficiency, a risk management algorithm for high-tech projects is presented in the paper. Integrating FMEA into projects implementing robotic technologies can lead to significant enhancements in risk reduction, and therefore cost savings, efficiency, safety, and quality, while fostering a culture of collaboration and problem solving. The research contributes to the literature by introducing an AMR planning and control framework to guide managers in the decision-making process, thereby supporting them to achieve optimal performance. Finally, we propose an agenda for future research within the field of interest.

A “silver economy” can drive economic growth. The key condition is effective demand, determined by the number of financially secure members of the elderly population. The aim of this study is to assess the conditions of the Russian “silver economy”, identify the constraints on its growth, and develop recommendations for their elimination to achieve Sustainable Development Goals. We applied multivariate statistical analysis methods. The absolute and structural numbers of elderly people in Russia were found to not differ much from those in the developed countries of Europe. Their financial support exhibits several important features. A state pension plays a key role in financing the needs of Russian pensioners. Income from labor occupies the second position. Asset-based reallocations are negligible. Public programs will improve the standard of living of current pensioners. For future pensioners, it is important to increase the income received from asset-based reallocations. Russian pensioners were found to have had a negative experience of participation in the funded pension system. It is necessary to stimulate the voluntary participation of future pensioners in the funded pension system and to change the regulation of the investment activities of pension managers. In general, the formation of conditions favorable to the “silver economy” may turn it into a driver of sustainable development in Russia.

Global institutional changes (GICs), having influenced energy prices, led to a steady upward trend in carbon prices on the EU ETS. The aim of the article is to assess the changes in the relationship between carbon prices and energy prices under GICs. The Bai–Perron tests for structural breaks identified two dates as the breakpoint, 21 April 2016 and 21 September 2020. We test the hypothesis that powerful external factors (GIC) are changing the trend pattern of the carbon price time series. New pricing rules of the carbon price are being formed after the breakpoint. We use daily observations from 4 January 2010 to 1 September 2022. We use GARCH models with multiple stationary time series to discover a relationship energy price with the carbon price before and after the break points. We found that three models for two breakpoints better describe the relationship between carbon prices and energy prices than two models for one breakpoint, much less one model for the entire period. We find that the carbon price depends on energy prices, especially on the price of oil, in a statistically significant way, but the gas price is not statistically significant after 21 September 2020.

China and Russia have different interests in the Arctic but are forced to look for possible ways of cooperation in energy projects in the current external conditions. This changes the priorities of both countries and, accordingly, transforms the risks. Objectives of the research: to build an algorithm for identifying anthropogenic environmental risks in the context of two major players economic activities in the Arctic region: the Russian Federation and China. In the paper, we formulated an algorithm of environmental risk identification. We identified environmental hazards from the main parameter—the type of economic activity for the extraction of energy resources, premises, and factors for the occurrence of environmental hazards and compiled criteria for risk selection. Methods used: complex analysis (mixed method research): empirical and comparative methods, methods of expert assessments, the method of inductive statistics (inferential statistics) to compare the perception of risk at the level of different groups. Results: the algorithm has been formed for determining risks in the changed external conditions. Major anthropogenic environmental risks are identified from the perspective of the main players in the Arctic—Russia and China, which can help to make the necessary decisions on time and partially prevent environmental degradation. This makes it possible to identify the risks associated with conducting economic activities for the extraction of energy resources in the Arctic region. Therefore, this study contributes to a more accurate identification of anthropogenic environmental risks in the Arctic region.