Статьи

Relevance. Ensuring equal access to resources is crucial for social development, especially in rural areas. Women in these regions face distinct challenges due to traditional lifestyles and cultural norms, impacting their access to education, healthcare, and economic opportunities. Addressing these challenges is vital for the overall development of rural communities. Research objective. This study aims to develop methodological approaches to assessing women’s access to resources in rural areas of Kazakhstan. Data and methods. Based on the investigation of methodological approaches, multinomial logistic regression analysis was proposed to assess the impact of regional differences on gender gaps in access to various resources. The study is based on qualitative data collected from May to June 2023 from a sociological survey conducted among women aged 18-60 in rural settlements of Kazakhstan. A total of 600 respondents were interviewed, and 542 of the respondents had completed questionnaires. This methodology enables the collection, analysis, and processing of primary data, aiding in the assessment of gender disparities in resource access. Results. The proposed methodology facilitated a thorough analysis of qualitative data, offering insights into the problem of gender disparities. Most respondents rated their access to social and economic resources as average, suggesting that while there are available resources, they might not fully meet rural women’s needs or expectations in terms of level or quality. Conclusions. Regions like Akmola, Atyrau, Mangystau, North Kazakhstan, Turkestan, and Zhambyl show significant disparities in resource access, indicating regional inequalities. Addressing this gap necessitates collaborative efforts between government and businesses to enhance resource availability and broaden opportunities for rural women.

Relevance. Uneven spatial development is a common challenge for all countries, driven by both subjective and objective factors. The issue lies not in regional disparities themselves but in their growing intensity. Amid crises and economic turbulence, it is crucial to have tools to assess the risks of increasing spatial unevenness and widening socio-economic disparities between regions. Research Objective. This study aims to develop and test a tool for estimating the risks of uneven spatial development in Russia’s macroregions and the growing differentiation of regions by socio-economic level, using the Urals-Siberian macroregion as a case study. Data and Methods. A two-stage approach is proposed to evaluate spatial development in terms of uniformity and regional differentiation by socio-economic level and growth rate. In the first stage, the probability of a socio-economic decline is estimated based on key indicators (risk factors) and their dynamic indices. In the second stage, the probability of an increasing variation coefficient within a macroregion, reflecting rising disparities in socio-economic development, is analyzed. A multifactor risk model is used for analysis. The study relies on data from the Federal State Statistics Service (Rosstat) covering the period from 2000 to 2022. Results. Applying this approach to the Urals-Siberian macroregion revealed persistent spatial unevenness throughout the study period, primarily due to the specialization of regions, which stabilizes their relative positions. However, during crises, spatial disparities tend to widen as regions demonstrate varying adaptive capacities and resilience - some not only recover but also improve their positions. Conclusion. The proposed tool assesses risks linked to uneven development and growing regional disparities, offering insights for sustainable macroregional strategies. The findings emphasize the need to consider regions’ specificities and adaptive capacities in spatial development policies.

Легенду о татарском хане и дочери царя Армении, произведшей на свет чудовище, которое в результате крещения превратилось в прекрасного младенца, что побудило хана принять христианство, включили в свое повествование многие европейские хронисты и историки. Эта легенда легла в основу известного английского рыцарского романа «Царь Тарса». Сюжет легенды слагается в основном из одних и тех же элементов. Однако в отдельных хрониках и летописях, а также в названном романе меняются их соотношение и комбинация, а порой имеют место выпадение одной из сюжетных линий или замена одного персонажа другим. Зачастую происходит приращение к сюжету, например, таких элементов, как взятие Иерусалима татарским ханом, изгнание сарацин из Иерусалима, взятие Алеппо, Дамаска и других городов объединенными войсками татар, царей Армении и Грузии. Что касается армянского следа этой легенды в европейской историко-литературной традиции, то между сюжетами первой ветви «Давида Сасунского» и циркулирующими на Западе легендами об истории дочери армянского царя, которую выдают замуж за иноверца, обнаруживаются явные параллели. В данной статье выявляются эти параллели, а также следы сходства с древнерусскими сказаниями.

He study aims to revisit the relationship between aviation pollution, tourism, and economic development through the lens of the Environmental Kuznets Curve (EKC), particularly at the regional level, using New Zealand as a case study. We are the first to estimate aviation pollution at regional airports in New Zealand and use them as proxy for the regional pollution in an EKC setting. Our findings provide evidence of an EKC at New Zealand regions, indicating that tourism and economic development contribute to the long-term regional environment improvement. This highlights the necessity for environment policy to be tailored at a regional level, rather than solely at the national scale. Additionally, our research introduces a novel approach to EKC studies by incorporating new pollution estimations, which enhances the understanding of regional environmental dynamics. Among others, we discovered that that the sustainable tourism policy has, and will, work well in New Zealand. This study underscores the importance of considering regional factors in environmental policymaking and offers insights that could inform future strategies for balancing economic growth with environmental sustainability.

The growing economic prominence of BRICS nations (Brazil, Russia, India, China, and South Africa) has attracted considerable attention to the macroeconomic dynamics driving their development. As these economies grow rapidly and become more integrated into global markets, it becomes increasingly difficult to balance economic growth, trade liberalization, and sustainable fiscal policies. Government size, a key factor in fiscal management, tends to increase with national income (as suggested by Wagner’s Law) and in response to trade openness (as outlined by the Compensation Hypothesis). Understanding these dynamics is crucial due to the unique fiscal pressures and global competitiveness faced by BRICS countries. This study investigates the validity of Wagner’s law and the Compensation Hypothesis in the context of BRICS. Using a panel nonlinear autoregressive distributed lag model on annual panel data from 1999 to 2023, our findings confirm Wagner’s law, showing a positive relationship between economic growth and government size. Additionally, the results support the Compensation Hypothesis, indicating that trade openness enhances government size. This study underscores the potential trade-offs between promoting economic growth and trade liberalization, as these strategies may inadvertently expand the government sector and affect fiscal stability. As BRICS economies continue to integrate into global markets, this research contributes to the discussion on Wagner’s law and trade openness, offering new insights into sustainable fiscal policies, government expenditure optimization, and the pursuit of global competitiveness and economic growth within the BRICS framework.

Megumi Saigo derived generalized fractional operators, involving Gauss hypergeometric function, having four special cases: Riemann-Liouville, Weyl, Erdely-Kober left and right sided fractional operators. Mridula Garg and Lata Chanchalani established q-analogues of Saigo fractional integral operators. Building upon this base, the current article aims to generalize Saigo integral operators as well their q-analogues. In addition, we obtain some new results involving extended Saigo integral operators and their q-extensions.

Innovation processes are strongly in uenced by changes in economic, political, technological and other external factors. For instance, economic instability and political uncertainty can both stimulate and limit innovative activity in organisations. Transmodern innovation is a concept that involves scienti c and technological advancements that may remain unutilised until favourable changes occur in technological or economic conditions. The purpose of this study is to develop a conceptual model for transmodern innovation that takes into account the dynamics of innovation, including the intensity, economic prerequisites, external changes and degree of innovation adaptation. This model will help organisations to better understand and respond to the complexities of the innovation process. The resulting model is a comprehensive tool for analysing changes in innovation activity and the external environment over di erent time phases, including the initial state (t0), the transition to new conditions (t1) and the nal state (tx). In this model, the ‘Final stage of tx’ block represents the nal stage, which allows us to draw conclusions about the success of adaptation and innovation development. This is the basis for formulating strategic conclusions and recommendations for future development.

This article analyses the sustainability of the agro-industrial complex (AIC) in the Eurasian Economic Union (EAEU) countries with an emphasis on food security. The study covers challenges and threats to food security in Russia, Belarus, Armenia, Kazakhstan, and Kyrgyzstan, given the difficult geopolitical situation. The article examines data from the national statistical services of the EAEU countries, as well as international sources such as the FAO and the World Bank. Correlation and cluster analysis approaches are applied to assess the impact of socioeconomic indicators on the sustainability of the AIC. Significant correlations between indicators of food security and such factors as the volume of agricultural production, investments in the agricultural sector, the level of technological development, and government support are revealed. On average, for the period from 2015 to 2022, the added value of agriculture amounted to 8.2% of GDP, and the food production index was 104.1. The results of the cluster analysis showed that the EAEU countries can be grouped by levels of agricultural development and food security. Thus, K-means and GMM identified three clusters in which Russia found itself both in a separate cluster and in combination with other countries. Agglomerative and spectral clustering also showed similar results, distinguishing three main groups of countries. The average silhouette coefficient for agglomerative and spectral clustering was 0.41, which indicates a better clustering quality compared to K-means and GMM (0.38). It is confirmed that integration and coordination of efforts within the EAEU, as well as diversification of agricultural production and increased investment in innovation, determine the state of sustainability of the agro-industrial complex.

The contemporary information landscape is characterised by a huge amount of data available for analysis using a variety of research tools and methods. Considering the limitations of using individual models and methods, it is worth employing an approach that combines functional and logical autoregression methods to conduct a more accurate analysis of trends and topics in the information space. Considering this context, this work aims to develop an algorithm to identify and analyse topics that would be relevant in the future using autoregression methods. The process begins with the quantification and normalisation of data, which significantly affect the quality of analysis. The main focus of this study is to implement the autoregression method to analyse long-term trends and predict future developments in the selected data. The proposed algorithm evaluates the forecast of these future developments and analyses graphical trends, thus conducting a more detailed study and modelling of future data dynamics. The regression coefficient is used as a quality criterion. The algorithm concludes with a polynomial function to help identify topics that will be relevant in the future. Overall, the proposed algorithm can be considered an effective tool for analysing and predicting future trends based on the analysis of historical data, thus contributing to the identification of prospects for technological development.

This article discusses the relevance of mapping as a lean technology employed in the higher education institution in the conditions of digital transformation. The authors emphasize that modern challenges require optimization of business processes, which can be achieved by using lean production methods. In the course of the research a mapping tool was used to analyze and optimize the tracking of student attendance in the structural divisions of the university. This work aims to improve control over student attendance, including several major tasks: assessment of existing lean production tools, application of mapping in attendance tracking, optimization of the current control measures, and development of recommendations for further improvement based on the PDCA cycle. According to the results, mapping and the PDCA cycle proved their efficiency in terms of improving the quality of education in the digital environment.

In recent years artificial intelligence (AI) has become an indispensable tool in digital marketing that is able to simplify human performance and expand business opportunities. This research considers the current AI (artificial intelligence) architectures in digital marketing, reflects on their impact on the activities of companies, and develops a range of optimization recommendations. The authors identify the most important tasks in evaluating existing solutions and their efficiency, as well as assess the possibilities of switching to AI technologies in business. Specific attention is also devoted to the examples of the neural networks implementation in marketing. As a result, the main components of the AI support architecture are identified, together with the further development prospects, with due consideration of current trends and ethical aspects. This research employs the practical achievements of marketing specialists and suggests a range of step-by-step strategies to optimize the business processes.

The healthcare industry makes one of the main components of the productive forces of the state. Therefore, the well-being and welfare of the entire society in the future depend on its thriving development. Despite significant accumulated knowledge in medicine, there are still some white spots that are difficult to analyze and predict. The use of artificial intelligence and neural networks in healthcare can significantly expand the analytical apparatus and radically change the existing approaches to scientific research. This article discusses the results of the practical application of artificial intelligence and artificial neural networks in healthcare. The research aims to demonstrate the prospects and advantages of using these information technologies in medicine; identify problems in the implementation of AI technologies in medical practice and offer possible solutions to some of them. The authors provide a comprehensive literature review on the issues of artificial intelligence and neural networks, consider successful examples of the AI use in pharmacology, forecasting, and research of various types of diseases, including cardiovascular system, dermatology, and oncology. A significant part of the research is devoted to ethical and legal concerns, as well as problems associated with the practical use of artificial intelligence. As a result of the research, the authors suggest the models of the IT architecture of a medical information system and data flows, based on the TOGAF standard.