Digital Omnichannel marketing is viewed the answer to future marketing however, the concept is mired with problems related to the energy and carbon footprinting. Therefore, this study proposed energy efficient network of a complex topology of data access and marketting, where the nodes function as an objects with unique characteristics and create digital customer value network. It is believed that competition has transformed into a contest of online platforms in energy efficency as well in economic efficiency. It is emphasized that there is no alternative to multichannel interaction at the present stage of implementing digital business solutions. In this study, authors have developed omnichannel interaction algorithms based on mathematical models. The proposed approach supplements the digital twin model with economic indicators and methods. Results and analysis of multidimensional structures allows for omnichannel network digital interaction and improves the digital marketing approach. To consider the formation of a network configuration of customer service, developing the idea of digital interaction between participants in consumer value chains. The study conclude and recommend to expand the methodology of digital marketing involving alternative channels of interaction and energy efficency by including a mathematical apparatus for analyzing multidimensional structures (n-D structures).

Global climate change threatens the continued existence of mankind. The rate of warming in Russia, which is 2.5 times higher than the rate of growth of the global average temperature, can lead to huge environmental and financial losses. Thus, it is increasingly necessary to modernise and develop methods and tools for adaptive regulation of national climate policy to increase its efficiency at the regional and federal levels. To this end, the methods of content analysis, grouping, modelling, comparative and correlation analysis, as well as an information asymmetry approach were used in the research. The paper substantiates the necessity of a transition from autarky and directionality to the integration of regions and the federation based on adaptation and preventive measures. The periodic assessment of climate change and relevant contributing factors should be replaced by the continuous management and regional monitoring of climate risks. Stressing the importance of transparency and comparability of information on climate risks, the research distinguished anthropogenic risks, risks of reducing the quality of life and moral climate risks. In order to promote climate preservation, an organisational and economic mechanism for the implementation of climate policy was developed, whose main function is the regional environmental management. Assessment of the decoupling effect and ranking of the constituent entities of the Russian Federation in terms of the relationship between energy intensity and climate intensity proved the feasibility of using the proposed indicators to increase the efficiency of the organisational and economic mechanism. Regulatory and financial support for the mechanism can be provided by introducing a quota market, green certificates and bonds, insurance and risk hedging strategies based on a scenario approach and online-management models. The research results can be used for the digitalisation of national climate policy, as well as for the development of regional and municipal climate strategies, programmes, projects.

Since there is a lack of a strong CSR platform in the Iranian corporate environment, especially in the food and pharmaceutical industries, the proposed and existing strategies can be utilized to empower employees and the general public, improve executive processes, improve quality and customer satisfaction, and finally, organize financial and accounting reports. Hence, this study seeks to determine and evaluate strategies to improve the concepts and domain of corporate social responsibility (CSR) of food and pharmaceutical industries in Iran based on the requirements of sustainable development theory. This study analyzes the data of 22 companies active in the food and pharmaceutical industries listed on the Tehran Stock Exchange (TSE) over a period of six years (2014–2019). Eighty-three indicators were used to evaluate the performance of social responsibility based on economic, social and environmental dimensions. The Pareto approach has been used to determine the most important unmet current requirements. Then, using the Delphi method and content validity, appropriate strategies were determined. Finally, a correlation matrix was used to determine the most important and comprehensive strategies. Findings showed that 14 requirements in the field of corporate social responsibility are of great importance and with six strategies, the necessary measures to meet those requirements can be covered.

Aim. The presented study examines modern factors affecting the functioning of risk management, specify the requirements for information and services for retrieving and processing it to make effective management decisions aimed at minimizing or eliminating risks.Tasks. The authors specify the challenges of risk management in the context of economic instability to preserve existing positions and substantiate directions for development; determine the stages of further transformation of risk management corresponding to the strategic guidelines for the development of business structures and describe them with an emphasis on existing problems and the opportunities for solving them; investigate the nature of the increasing importance of information analysis within the framework of risk management and the necessity and possibility of attracting third-party organizations for this purpose; identify and describe changes taking place in risk management in the context of digital transformation, accompanied by changes in information analysis and the active promotion of related services by the IT sector.Methods. This study uses general scientific research methods (systems and logical approaches) and the methods of strategic and situational analysis to determine cause-and-effect relationships and describe the obtained results.Results. The authors propose an original concept substantiating the increasing importance of the joint work of business structures and their partners providing services for retrieving and processing information in the interests of risk management. Emphasis is placed on the need to protect commercial information and prevent its leakage. This concept makes allowance for current trends in the active development of the IT sector, the Internet economy, and economic security, including under economic sanctions. The proposed recommendations can serve as a basis for a comprehensive model that would make it possible to develop directions for improving the risk management system, substantiating the effective behavior of an entrepreneurial structure in the presence of economic and non-economic risks.Conclusions. The study proves that the development of a modern entrepreneurial structure increases the importance of the functioning risk management system. Factors that ensure the development of risk management and prevent it from functioning normally are identified. Based on this, recommendations for organizing effective management in this area of management activity are proposed.

Aim.The presented study aims to identify, systematize, and describe the specific features of public administration of business activity in the interests of creating and improving innovation climate, which ensures the acceleration of innovative development of the Russian economy under modern conditions.Tasks.The authors explore the essence of the current stage in the development of the innovative economy and the shift towards a post-industrial society in Russia; determine the nature of the influence of public administration tools and market self-regulation on the development of innovation climate; form and describe system units that determine the effectiveness of public administration of business activity and stimulation of its innovative activity; identify trends and specific aspects of management tasks in the field of the government’s influence on the level of innovation susceptibility of a wide range of economic entities.Methods.This study uses general scientific research methods (logical and systems approaches), expert assessments, and methods of strategic and situational analysis to establish cause-andeffect relationships, as well as generalization and description of the obtained results.Results.The proposals made by the authors substantiate the modernization of macro-, meso-, and sectoral policies in the field of innovation climate development based on improving business activity and stimulating interest in using innovation as a development tool. The ambiguity of the modern competition mechanism in the market of innovations and innovative products is observed due to the scale and direction of the business, which implies the transformation of the public administration system, especially in the field of antimonopoly regulation. Requirements to national policy in the field of science and education with regard to the search for an effective relationship between the development of fundamental and applied science to ensure the quality of economic growth and achieve economic and other types of security are clarified. The need to modernize development institutions and innovation infrastructure under modern conditions characterized by regionalization and the formation of economic block structures is confirmed.

This research considers an Artificial Intelligence (AI)-driven omnichannel logistics network for bioethanol supply from Russia to China. As a renewable, low-carbon transport fuel, bioethanol plays a critical role in energy diversification and decarbonization strategies for both Russia and China. However, its flammability and temperature sensitivity impose stringent requirements on transport infrastructure and supply chain management, making it a typical application scenario for exploring intelligent logistics models. The proposed model integrates information, transportation, and financial flows into a unified simulation framework designed to support flexible and sustainable cross-border (CB) logistics. Using a combination of machine learning, multi-objective evaluation, and reinforcement learning (RL), the system models and ranks alternative transportation routes under varying operational conditions. Results indicate that the mixed corridor through Kazakhstan and Kyrgyzstan achieves the best overall balance of cost, time, emissions, and customs reliability, outperforming single-country routes. The findings highlight the potential of AI-enhanced logistics systems in supporting low-carbon energy trade and CB infrastructure coordination.