State University of Management

Human health is determined not only by biological factors of a person's environment and social environment, but also by the attitude of values towards their health. The purpose of the study was to explore young Russians' ideas about their health, nutrition, quality of life, physical activity, and bad habits in order to find practical ways to increase their motivation towards a healthy lifestyle. Based on a focused interview at an online conference and an expert survey via email, the authors examine young people's ideas about a healthy lifestyle, health status. The findings underscore that young people's motivation is determined not only by personal perceptions, but also by the broader context of socialization, peer influence, and accessibility to health-promoting environments. The research concludes that young people have contradictory and not always accurate ideas about the main factors that affect their health, the means to maintain it and the importance of a healthy lifestyle. In order for young people to choose health, the family, the local community and the state must join forces to improve the spiritual, educational and cultural level of the individual, creating favorable conditions and motivating them. Therefore, the practical recommendations derived from this research emphasize the integration of healthy values into everyday social practices, creating conditions that foster consistent behavioral changes and a long-term commitment to health.

At the present stage, the achievement of the set strategic goals of ensuring Russia's economic independence and technological leadership is associated with the development and implementation of domestic information and cognitive technologies. The country's agro-industrial complex, which is undergoing a complex process of digital transformation with the expansion of the use of robotic technology and intelligent systems, plays a special role in solving the basic tasks of maintaining state sovereignty. The development of platform solutions in agricultural production faces serious limitations and constraints on the effective application of the "digital twin" concept, due to unresolved issues regarding the conceptual and institutional justification for their construction for organizational systems. In this regard, the aim of this study is to substantiate proposals for defining the concept of a digital model of an agricultural enterprise and the formation of a possible option for describing the economic system and basic business processes for conducting full-cycle smart agriculture. The application of content and logical analysis methods, and reengineering technology, allowed us to appropriately define a reference digital model of an enterprise in the agricultural sector and present a possible design for a digital model of the economic system of a smart agricultural enterprise. Definitions of the concepts of "digital model" and "digital twin" for organizational systems are proposed, clarifying existing definitions in terms of reflecting the variability of the description of the organization's business model when displaying the entities of "business architecture" and "business processes" as separate structural elements and the contour of subjective perception of information when making decisions. The structure of a digital model of an agricultural enterprise's economic system in a networked precision farming environment is substantiated, taking into account changes in the composition and role of production factors in a data economy. We demonstrate the need to reflect in this model elements and relationships that address the requirements of ensuring environmental neutrality and social responsibility in full-cycle agricultural production. We recommend using the information image of a digital twin of an agricultural enterprise to design the structure and fill the model of the economic system with data based on regulated forms of planning and reporting documentation when building a digital platform to support management decision-making. The digital twin ontology description scheme expands our understanding of the theoretical foundations of the methodology and tools for designing and developing information models of objects and processes for business systems.

This study analyzes the transformation of global production and consumption of agricultural products, followed by a systema-tization of the factors shaping a new global architecture of international trade in agricultural products. The need for this work arises from the fact that global agricultural markets are simultaneously experiencing pressure from technological innovation, environmen-tal requirements, and supply chain restructuring, which intensifies competition and increases risks for countries whose export specialization relies primarily on low-value-added goods. The goal of the study is to develop strategies for the development of the Russian agricultural industry based on the analyzed key trends. The study's hypothesis is that strengthening the competitivenessof the Russian agricultural sector is possible if two conditions are met: a transition from low-margin supplies to more highly processed products and the accelerated implementation of sustainable and digital solutions, which will reduce market access barriers and in-crease resilience to price and logistics shocks. This paper examines the evolution of agricultural production systems from industrial to digital, environmentally friendly ones. It also examines the trend of glocalization as an important factor in the transformation of agrifood systems, ensuring a balance between global trendsand local specifics. The article lists the factors determining the global architecture of international agricultural trade, analyzing scientific, technical, macroeconomic, consumer, and other factors. The authors note qualitative limitations, such as the high share of low-value-added products and the need to adapt to the transformation of the global agricultural market. Practical implications are described in the form of strategies aimed at transforming the Russian agro-industrial complex, from developing accessible financing and tax incentives for the adoption of sustainable technologies to im-plementing certification systems. The research methodology is based on a systems approach, examining the global agro-industrial complex as the object of study. The theoretical basis for the problem under consideration is presented through an analysis of scien-tific publications by both domestic and international scholars

Machine learning algorithms, which are also foundational to artificial intelligence, offer significant advantages in multi-criteria evaluation and decision-making. The pace of sustainable development in underground coal mining plays a crucial role in assessing the safety of coal mining enterprises. A neural network based on the error backpropagation (BP) method is a classic model in machine learning. In the proposed article, a neural network is applied to make decisions regarding the level of sustainable development and to assess operational safety in coal mining enterprises. Based on the analysis of the method for evaluating the sustainable development of coal enterprises, a system of evaluation indicators is established, and a multi-layer neural network is constructed using the error backpropagation algorithm. Grounded in the "human-machine-environment-management" system theory and taking these four elements and the system (the coal mine) as a whole as the research object, this work analyzes and studies the processes of assessing and continuously improving the safety level of a coal mine. The neural network-based evaluation model is used to analyze and study coal mine indicators, identify shortcomings in building the sustainable development system, and uncover a set of measures for its enhancement. This effectively contributes to safe production and ultimately aids in achieving the enterprise's overall development goals.

Purpose E-commerce consumers value both forward and reverse logistics services and triple-bottom-line sustainability (cost, CSR and environmental performance). Unfortunately, these aspects of e-commerce can be at odds with one another. Therefore, a major challenge for e-commerce retailers lies in balancing the importance of forward and reverse logistics services with concerns about triple-bottom-line sustainability. To help e-commerce retailers better understand this challenge, our study delves into US consumers' tradeoff preferences related to delivery, returns and sustainability performances. Design/methodology/approach Policy capturing is a method employed by researchers to assess how individual decision-makers use available information when making evaluative tradeoffs between factors. We employ a policy-capturing method with 364 participants. Findings We find different consumers' tradeoff preferences in different groups in the USA. We observed that environmental concerns are paramount for younger respondents, but cost is more important for older respondents. Also, delivery performance is regarded as more significant than returns performance. Research limitations/implications Our findings imply that the demographic background of consumers plays a role in their purchasing behaviors. E-commerce retailers need to consider the psychological attitudes and age of the consumers. Practical implications Environmental performance seems to matter more to younger respondents relative to their older counterparts, so e-commerce retailers will need to adjust their strategies accordingly. We see some examples of e-commerce retailers trying to use this shift in attitudes to their advantage. Originality/value While literature has demonstrated that triple-bottom-line sustainability and logistics service are key consumer considerations in e-commerce, it has not yet been established how consumers evaluate these disparate and sometimes orthogonal factors in tandem. Our research aims to fill this gap.