A novel functional model of a dynamic cognitive system, designed to simulate agent behavior in complex socio-informational environments is considered. The proposed approach integrates cognitive, emotional, motivational, and social components within a unified hierarchical architecture supported by multimodal data collection. Special emphasis is placed on the use of state-of-the-art machine learning techniques to optimize action-selection policies, enhance prediction accuracy, and improve adaptability to exogenous disturbances. The simulation results demonstrate the model’s relevance for scenario analysis, identifying the dynamics of recovery after information shocks, and revealing the internal structure of group behavior. The results obtained provide a basis for the practical application of the model in strategic management, education, rehabilitation, and social analytics.
Sustainability reporting is an important aspect of corporate social responsibility (CSR), enabling companies to demonstrate their commitment to issues beyond financial performance and profit. The purpose of this study is to analyse business development sustainability reporting and justify its use as an effective CSR tool. During the study, the theoretical foundations of corporate reporting were further developed by clarifying the thesaurus on accounting and reporting. The refinement of the terminology framework was complemented by the justification of updated classification criteria and types of corporate reporting in the context of sustainability requirements. The classification criteria and types of corporate reporting were justified by the following: (1) the type of indicators (financial or non-financial), (2) the standard of non-financial reporting, (3) the areas of disclosure (management, environmental, social or financial), and (4) the type of non-financial disclosure (sustainability information as part of the annual report or a separate sustainability report).
Purpose: to generalise and systematise contemporary scientific approaches to the analysis of competitive activity in boxing. Material and Methods. The study was based on the analysis and synthesis of modern scientific and methodological sources devoted to the investigation of boxers’ competitive activity. The literature search was conducted using scientometric databases (in particular Google Scholar), open-access scientific repositories, and specialised international journals, applying relevant search queries in both Ukrainian and English. Scientific articles, systematic reviews, and dissertation studies addressing technical-tactical, physiological, biomechanical, and psychophysiological aspects of competitive activity in boxing were included in the analysis. Comparative and structural-logical methods were used to systematise the selected sources and to identify the main research directions. Results. The analysis of scientific literature demonstrated that contemporary studies of competitive activity in boxing are characterised by a comprehensive and multidimensional approach. The key research areas include the identification of performance indicators, analysis of technical-tactical actions, determination of factors influencing victory, and the impact of athletes’ individual characteristics. It was established that the most informative indicators of performance are the number and accuracy of punches, the effectiveness of offensive and defensive actions, as well as the variability of technical-tactical decisions during a bout. The findings indicate that successful boxers demonstrate higher technical efficiency, greater attacking activity, and more rational tactical behaviour. At the same time, competitive activity indicators vary depending on athletes’ qualification level, sex, age, and weight category. Additionally, a growing body of research focuses on physiological, biomechanical, and psychophysiological aspects, expanding the understanding of the structure of competitive performance in boxing. Conclusions. The generalisation of modern scientific approaches allows competitive activity in boxing to be considered as a multifactorial system formed by the interaction of technical-tactical, functional, and psychophysiological components. Technical efficiency, punch accuracy, and activity volume are identified as the most significant determinants of performance. At the same time, current research trends highlight the need for integrating different analytical approaches, which provides a basis for improving the objectivity of performance assessment and optimising the training process in boxing.
Type of the article: Research Article AI is widely regarded by the IMF and the World Bank as a catalyst for growth. AI should be understood as a multidimensional socio-technical system embedded across institutions, industries, and society. Its economic contribution depends on which pillars of the national AI system expand (e.g., R&D capacity, infrastructure, governance, or social acceptance). For this reason, the seven pillars of AI development are measured by the AI Vibrancy subindices, which help avoid reliance on a single composite indicator that may conceal offsetting effects. This study examines how different pillars of the national AI ecosystem shape the architecture of the knowledge economy and its economic outcomes by estimating heterogeneous within-country associations between GDP per capita and seven AI ecosystem pillars, operationalized through AI Vibrancy subindices, using a balanced panel of 36 countries with complete data over the period 2020–2023. Fixed- and random-effects models are estimated using heteroskedasticity-robust and Driscoll-Kraay standard errors. The results indicate that, within countries over time, the R&D (β = –5.676, p < 0.001) and Infrastructure (β = –16.306, p < 0.001) subindices have strong and statistically significant negative associations with GDP per capita, while Public Opinion shows an adverse effect that is significant at the 5% level under heteroskedasticity-robust inference (β = –9.126, p = 0.040) and marginally significant under Driscoll-Kraay inference (p = 0.054). Responsible AI exhibits a marginally positive association (β = 5.773, p = 0.065) in the Driscoll-Kraay specification, whereas Economy, Education, and Policy & Government show no significant within-country effects.
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.
