Inna Riepina

The article is devoted to the analysis of current problems, trends and opportunities for the grain trade market development in Ukraine in the context of ensuring anti-entropy. In recent years, Ukraine has established itself as one of the world's leading exporters of grain crops, such as wheat, corn and barley. The significant contribution of the agricultural sector to the country's economy emphasizes the importance of a detailed study of the factors affecting its development, which is extremely important for ensuring the competitiveness of our country in the geopolitical arena. The key challenges for grain trade remain infrastructure limitations. The problem of logistical leverage, including the insufficient development of ports, railway and road infrastructure and other obstacles. At the same time, the article emphasizes that climate change also poses a serious threat, causing instability of yields and increasing production costs; in particular, weather conditions are extremely unstable and difficult to predict. Also, an important aspect is that logistical problems, such as delays in transportation and storage of grain, limit the ability of Ukrainian exporters to compete in the market globalization. Let’s next step, these characteristics are complemented by geopolitical events that affect trade routes and export markets, creating additional instability. The article analyzes the dynamics of exports of major grain crops in the 2023/2024 marketing year. The article carefully examines the impact of world prices and trade conditions on the agricultural sector’s economic efficiency. Changes in global markets and product quality requirements require Ukrainian producers to adapt and implement the latest technologies to ensure competitiveness. Particular attention is paid to strategies aimed at increasing the efficiency of grain trade. Among the proposed areas are improving the infrastructure for storing and transporting grain, diversifying production to reduce risks associated with climate change and price fluctuations in international markets. An important aspect is the introduction of innovative technologies in grain production and processing, which will contribute to increasing the productivity and sustainability of the sector. Also, the issue of adaptation to global market changes is considered, where the demand for environmentally friendly products is growing, which is a problematic aspect for modern ecological conditions. In this context, the need to implement sustainable development practices is emphasized, including reducing greenhouse gas emissions and rational use of resources. Increasing the sustainability of the grain market through the creation of more flexible logistics systems and risk management mechanisms is key to ensuring long-term economic efficiency. In conclusion, the article offers strategic recommendations for the government and business on the grain trade market development in Ukraine. Given the importance of this sector for the country's economy, special emphasis is placed on the need for intersectoral cooperation, investment in scientific research, and infrastructure development, which will ensure the agricultural sector’s sustainable development and its integration into the global arena.

Purpose. Development and justification of an improved three-cluster GSI-model (Generation, Support, Implementation) ecosystem of innovative entrepreneurship in order to forecast its development under entropic conditions. Methodology. The study used a mixed approach, which includes an analysis of literary sources to identify key factors of innovative entrepreneurship, construction of a 20-factor parametric model and assessment of its modifications in the context of the three-cluster GSI-model, scenario analysis (optimistic, several realistic options and pessimistic) with forecasting changes for 2026–2030, taxonomic analysis to calculate the integral development coefficient di, as well as verification of results by extrapolation of trends and comparative analysis taking into account international experience. Findings. A three-cluster GSI-model (Generation, Support, Implementation) of the innovative entrepreneurship ecosystem has been developed. The scenario analysis (optimistic, realistic and pessimistic) conducted confirmed its effectiveness for the development of this ecosystem in Ukraine. Originality. The proposed three-cluster GSI-model of the innovative entrepreneurship ecosystem integrates the activities of universities, scientific institutions, businesses, investors and government bodies. Unlike traditional approaches, this model offers comprehensive assessment of the processes of generating, supporting and implementing innovations in conditions of uncertainty. Practical value. The introduction of the three-cluster GSI-model increases business innovation activity, strengthens the interaction of universities, research institutions, accelerators and venture funds with the authorities, accelerates the commercialization of innovations and increases the number of startups, which generally strengthens the competitiveness of the Ukrainian economy.

The object of research is the processes of formation, analysis, processing and analysis of information by business analysts of an enterprise in the conditions of changing digital environment. The problem being solved is the need to process a large amount of data to make high-quality management decisions and reduce economic costs. The relevance of the research is due to the trends in the development of the digital environment. The paper considers theoretical and applied aspects and stages of the development of business analytics under the influence of AI tools. The paper explores the fundamental principles of using AI tools in analytical processes of enterprises and assesses their effectiveness. The methodological apparatus is based on the use of a systems approach, methods of theoretical and economic and mathematical modulation. As a research result, it was determined that the AI implementation tools create a positive effect and reduce errors in forecasting (up to 90%) based on business analysis. Accordingly, a positive economic result was established, which proves the feasibility of improving business analytics. A significant increase in the efficiency of such business processes as logistics (by 20–30%), marketing and foreign economic activity of enterprises has been identified. Company management indicates a reduction in additional costs (up to 92%), which contributes to the choice of optimal development strategies. Key barriers to the development of AI have been identified, including the shortage of personnel and the ethics of using digital platforms. It is empirically presented that this is due to the use of only 16% of AI tools in enterprise management. For further effective implementation, a phased transformation of the management environment of enterprises is envisaged through the gradual introduction of digital tools on a permanent basis and the creation, as a result, of a common digital ecosystem of the enterprise in various areas of activity.

The article examines in detail the process of forming service-oriented business models in international trade in tourism services in a digital society, focusing on the need to integrate product, service and digital components to increase the adaptability and resilience of enterprises. The authors emphasize that traditional linear sales models and classical approaches to service do not provide sufficient efficiency due to the growing turbulence of markets, fragmentation of sales channels, exponential growth of data volumes and accelerated digitalization, which leads to an increase in the entropy of service processes and operational risks. Therefore, the integration of digital platforms, CRM systems, consumer behavior analytics and omnichannel solutions becomes a critical condition for ensuring the continuity of revenues and competitive advantage in global tourism markets. The article proposes a methodological framework that combines diversification of products, geography of presence and sales channels with service-oriented architecture and digital data management. To assess the level of disorder in multi-channel service processes, an entropy approach was used, which allows determining the optimal balance between standardization and flexibility of the business model, while maintaining the ability to innovate and adapt. The formalization of the service-oriented business model is presented in the form of a functional dependence between product and geographical diversification, multi-channel, service and digital architecture, as well as process entropy. Additionally, an integral sustainability indicator was introduced, which takes into account the impact of diversification, digital maturity and the level of entropy on the efficiency and stability of the business system. An important component of modern service business models is ESG compliance, which in international trade in tourist services becomes not only a regulatory requirement, but also a factor in reducing entropy, managing risks and increasing the trust of global partners. The implementation of ESG approaches in service-oriented models contributes to the structural streamlining of operational processes, increases transparency of data work, standardizes interaction with suppliers and minimizes social and environmental risks. The environmental component (E) forms requirements for the sustainability of resources in tourism products, energy efficiency of service platforms and reduction of the carbon footprint of travel; the social component (S) strengthens standards of safety, inclusivity and responsible attitude towards consumers; corporate governance (G) ensures data protection, compliance with international norms, transparency of recommendation algorithms and ethical use of digital analytics. The integration of ESG compliance into service-oriented business models contributes to the formation of predictable operational contours, reduction of regulatory and market entropy, and also increases the investment attractiveness of tourism enterprises operating in international markets. It also provides enterprises with the opportunity to transform global challenges (economic, social, environmental and geopolitical) into sources of structural development and service innovations, forming a financially, operationally and reputationally antifragile business architecture.

The article substantiates the conceptual and methodological foundations for the formation of a system for sustainable anti-crisis development of agribusiness based on the implementation of advanced resource circulation models. The current socio-economic environment, characterized by military shocks and logistics disruptions, necessitates a transition from traditional linear economic models to regenerative ones. The authors propose an original academic interpretation of "resource circulation in agribusiness" as a dynamic complex of systemic and innovation-oriented management models that ensure a continuous cycle of asset reproduction at all stages – from primary production to processing and distribution. The study develops an updated hierarchical taxonomy of resources, where human capital (Workforce) and information-technological resources are identified as dominant factors of resilience. It is proved that in the context of anti-crisis management, intellectual flexibility and digital maturity act as compensators for the lack of physical assets or capital. The research systematizes analytical tools for diagnosing resource potential, categorizing methods into visual-graphical, mathematical, logic-analytical, and indicator-based approaches, which allow for identifying "weak points" in the business structure during turbulent periods. Special attention is paid to industry-specific factors – climatic determinism, seasonality, and biological complexity – that adjust the effectiveness of management decisions. The authors substantiate that circular innovations serve not only as an environmental initiative but as a strategic foundation for transforming agricultural production and ensuring national food security. The proposed model of interaction between resource cycles and anti-crisis monitoring provides a platform for minimizing losses and achieving a synergy of economic, social, and environmental results of sustainable development. The findings contribute to the development of state policy mechanisms for supporting the innovative activity of agricultural producers in the post-war recovery period.

The article examines innovative leadership as a key driver in shaping and transforming business models of private medical institutions under the conditions of digitalization, socio-economic instability, and wartime challenges in Ukraine. The research emphasizes that the competitiveness and resilience of the healthcare sector increasingly depend on the ability of leaders to integrate innovation-oriented management approaches, technological modernization, and organizational security systems. The study analyzes the dynamics of the Ukrainian healthcare services market in 2023–2024, highlighting trends of gradual recovery, digital expansion, and the growing role of private clinics in ensuring the accessibility and quality of medical care. The paper substantiates that innovative leadership fosters strategic flexibility, patient trust, and internal cohesion within medical teams, enabling organizations to adapt to uncertainty and maintain service continuity. The conceptual model of innovative leadership proposed in the article unites five interrelated components – strategic, managerial, technological, sociocultural, and security dimensions – which together create a framework for sustainable business model transformation. Each component contributes to the systemic development of private healthcare institutions, enhancing their digital maturity, risk management capacity, and competitiveness. The findings demonstrate that innovation-oriented leadership is not only a management philosophy but also a mechanism for ensuring long-term stability, cybersecurity, and social responsibility in the private medical sector. The results may serve as a methodological foundation for improving healthcare management practices, leadership training, and strengthening the organizational security of medical institutions in the post-war recovery of Ukraine.

The object of research is crypto trading and blockchain technologies, including the development of trading bots and the implementation of automated risk management systems. AI includes the development of trading bots, the implementation of automated risk management systems, and the use of predictive analytics tools that optimize trading operations. This is important, as AI technology plays a crucial role in the rapid analysis of huge amounts of data to predict market prices and trading opportunities, thereby increasing the efficiency of investments. In addition, AI provides investors with real-time information and assists in risk management. However, there are objective difficulties, and crypto fraudsters study different scenarios and adapt to changing market conditions using AI. By using the methods of observation, generalization, systematization and comparison, the authors have achieved results in determining the significance of implementation. In particular, the integration of artificial intelligence and cryptocurrencies can be applied, which aims to use the capabilities of big data processing and continuous learning to create a more efficient trading environment and financial services. The results presented in this paper give grounds to assert that it is possible to implement in the real business and technological environment (exchanges, crypto-exchanges, cryptocurrency operations, IT infrastructure, big data, AI). The article proposes innovative models and applications of artificial intelligence for use in trading business operations, where the main tool for users is generative artificial intelligence and interfaces. This method makes it possible to define generative artificial intelligence and natural language interfaces as the main means for trading operations that will be carried out using cryptocurrencies. As a result, real-time cryptocurrency trading and investment strategies based on data and algorithms have become possible.

In today's environment, entropy management of logistics processes in agribusiness is becoming increasingly important due to the need for continuous development and changes in the external environment. Effective logistics management is critical for maintaining the sustainable development and competitiveness of agribusiness. This paper analyzes the role of stevedoring companies, which play a key role in ensuring the reliability and sustainability of supply chains. The paper also considers aspects related to the regulatory framework and the need to improve it to increase the flexibility and adaptability of stevedoring companies in crisis situations. The study was conducted using a systematic approach, which includes an analysis of economic and political conditions, as well as specific aspects of logistics processes in the agribusiness of Ukraine. The article focuses on the management of entropy processes and their impact on the efficiency of logistics operations. It highlights that the proper organization of logistics processes helps to minimize losses and increase the efficiency of supply, which is key for agribusiness in the context of constant development and change. It is shown that stevedoring companies, due to their ability to adapt to changes, have a significant impact on the efficiency of logistics operations and the economic performance of agribusiness. The study found that effective management of entropy processes is crucial for supporting the sustainable development of agribusiness in Ukraine. It emphasizes the need to harmonize Ukrainian legislation with international standards to improve the business environment and attract foreign investors. Thus, the study emphasizes the importance of entropy support for logistics processes in agribusiness and the role of stevedoring companies in ensuring the sustainability and competitiveness of this sector in the context of constant change and development.

Global food security is one of the most important and complex challenges of the modern world, directly impacting socio-economic stability, environmental balance, and the quality of life. With the growth of the world population, climate change, depletion of natural resources, and geopolitical instability, ensuring sustainable food systems hasbecome of strategic importance. This article is dedicated to the comparative analysis of modern concepts of global food security modeling, particularly approaches such as econometric models, ecosystem-based approaches, scenario forecasting, and the use of big data and artificial intelligence for assessing and predicting changes in food systems. The author explores current models that assess the impact of various factors on food security, including climate change, economic and social challenges, and environmental risks. The article discusses the key directions and issues in modern theories and models related to food security and highlights their strengths and weaknesses. Specifically, the need for integrating various approaches to create comprehensive models capable of adapting to global challenges and ensuring the sustainable development of food systems is identified. The author also analyzes the prospects for improving existing concepts, considering the latest technologies such as big data, geographic information systems, and artificial intelligence. Special attention is given to integrative models combining social, economic, and environmental aspects to achieve the United Nations Sustainable Development Goals in the field of food security. The findings of this research are of practical importance for the development of strategies and policies for global and regional food security.