Dinara Mussabalina

In response to increasing expectations for efficiency and quality in public administration, the modernization of medical–administrative processes in Kazakhstan’s public healthcare organizations is gaining strategic importance. This study aims to identify factors that influence managerial and economic efficiency in public healthcare institutions, with particular attention to patient and staff satisfaction as indicators of public service quality and institutional resilience. The research is based on a quantitative methodology involving two parallel surveys: one among patients who received medical care, and another among medical personnel using a continuous sample of key professional categories. This approach provides a comprehensive view of how public healthcare services are perceived by both service recipients and frontline providers. The findings indicate that patients generally rate professionalism, communication, hygiene, and the availability of basic services positively. At the same time, many respondents report dissatisfaction with the level of digitalization and access to electronic public services. Similarly, medical staff view working conditions as satisfactory but note insufficient digital tools and a need to strengthen digital competencies. These results point to the necessity of reengineering public healthcare processes, emphasizing digital transformation, improved service design, and greater alignment with user needs. The research highlights the importance of systematically integrating citizen and employee feedback into mechanisms of quality management and public service improvement. It also outlines directions for further research, particularly the development of an assessment model for digital maturity and managerial performance in public healthcare organizations. Key words: economy, quality management, reengineering, service quality, citizen satisfaction, digital transformation, managerial efficiency.

Objective – to examine innovative approaches to forming consumer loyalty in digital retail and to assess the effectiveness of neuromarketing tools in managing customer behavior under conditions of digital transformation. Methods – mixed research methodology combining quantitative survey methods, comparative analysis, customer segmentation, and experimental neurosensory monitoring. The empirical study included 150 respondents divided into individuals, corporate clients, and dealers, as well as an experimental group of 40 participants exposed to different neuromarketing stimuli. Results – significant differences in satisfaction levels among customer segments were identified. Corporate clients and dealers demonstrated higher satisfaction with payment flexibility, service quality, and reliability of interaction, while individual consumers showed greater sensitivity to service speed and personalization. Neuromarketing stimuli, including dynamic lighting, video displays, background music, and scent marketing, positively influenced emotional engagement, duration of store visits, and purchase intention. In addition, 2025 retail trends confirm the growing role of mobile commerce, personalized offers, and omnichannel loyalty ecosystems in Kazakhstan. Conclusions – effective loyalty formation in modern retail requires the integration of behavioral analytics, segmentation strategies, and sensory marketing tools. The practical significance of the study lies in the possibility of applying the results to improve customer experience management and strengthen the competitive position of retail companies in Kazakhstan.

The object of the study is energy sector companies in the Republic of Kazakhstan involved in the extraction, transportation, generation, transmission, and distribution of energy resources. The problem addressed is the insufficient understanding of the mechanism through which digitalization affects financial performance, since it remains unclear whether this effect is direct or transmitted through environmental performance indicators. The empirical basis of the study is a balanced quarterly panel dataset for 2015–2025, comprising 220 observations across five companies. Fixed-effects models, a dynamic lagged model, panel vector autoregressive models, and impulse response functions were used in the study. The results show that digitalization has a statistically significant negative effect on carbon intensity in the fixed-effects model (β = −0.2828; p < 0.01), whereas its direct effect on return on assets is not statistically confirmed (β = −0.0035; p > 0.10). Carbon intensity has a significant negative effect on financial performance in both the static fixed-effects model (β = −0.0118; p < 0.01) and the dynamic lagged model (β = −0.00213; p < 0.05). These findings provide indirect empirical support for a possible environmental transmission channel, in which digitalization is associated with a lower environmental burden that may subsequently contribute to financial performance. The study uses quarterly corporate data, a text-based digitalization indicator, and carbon intensity as a measure of environmental performance, allowing an indirect assessment of a possible environmental transmission mechanism. The results can be used by energy companies, regulators, and investors when developing digital transformation and decarbonization strategies and making ESG-related investment decisions

The digitalization of healthcare is becoming a crucial factor in improving the efficiency and accessibility of medical services worldwide. In Kazakhstan, the level of digital transformation remains uneven across regions. This research focuses on the East Kazakhstan Region, aiming to evaluate the impact of digitalization on healthcare services and identify the relationship between ICT integration and key demographic indicators. The research is based on statistical data from the Bureau of National Statistics of Kazakhstan, Ministry of Healthcare reports, and international sources covering the period 2020–2024. Methods applied include comparative and statistical analysis, trend modeling, and geographical contextualization with emphasis on regional healthcare infrastructure in Ust-Kamenogorsk. The research revealed a positive correlation between the increase in ICT specialists and improvements in mortality indicators, particularly maternal mortality. Results demonstrate a twofold increase in computer literacy among healthcare employees, significant growth in internet usage for professional tasks, and progressive but uneven adoption of ICT across healthcare institutions. Despite positive dynamics, challenges persist: insufficient funding for ICT, shortage of cybersecurity specialists, and limited training opportunities. The novelty of this research lies in its regional focus: it is the first systematic analysis of healthcare digitalization in the East Kazakhstan Region. The findings extend existing theoretical frameworks by incorporating regional heterogeneity and provide practical insights for policymakers to enhance digital healthcare strategies in Kazakhstan.

The object of the study is wheat yield forecasting based on the integration of climatic indicators, satellite vegetation indices, and machine learning algorithms. The problem to be solved is the limited accuracy of traditional crop yield forecasting methods, which fail to capture the complex nonlinear and multidimensional interactions among climatic, biophysical, and agronomic factors, thereby reducing their applicability for global food security tasks. The proposed approach is applied to a dataset comprising 345 observations from 2001–2023, combining vegetation indices (MODIS), climatic parameters (ERA5), and official statistics on yield and sown areas. The methodology included descriptive statistics, correlation analysis and forecasting models based on random forest, support vector machine and convolutional neural network. Model performance was assessed using coefficient of determination, root mean square error and mean absolute error. Random forest and support vector machine showed the highest accuracy (R2 = 0.85 with low errors), while convolutional neural network was less effective due to the limited dataset. The analysis confirmed the decisive role of vegetation indices, especially the normalized difference vegetation index, together with precipitation, temperature and sown area. The results address the identified research gap by demonstrating that the integration of climatic indicators and satellite vegetation indices significantly enhances the performance of machine learning models for wheat yield forecasting. In particular, the findings highlight the advantages of ensemble and support vector methods, which proved to be more robust and accurate under conditions of high climatic variability. The practical value lies in the potential use of these models in early warning and decision-support systems for farmers and state institutions, improving agrotechnical planning, resource allocation, and reducing food security risks, thereby contributing to global food security

The effectiveness and quality of the public administration system depend on the qualifications of civil servants and their professional competencies. The model of a professional, pragmatic state, adhering to the principle of "listening", "service", and "people first", requires the development of professional competencies and personal qualities of civil servants. The purpose of the article is to explore the possibilities of using a modern assessment center tool to identify and develop talented personnel in improving the public administration system. One of the most promising ways is a competence-based approach. The competence approach is an integrative tool for human resource management and allows you to synchronise various areas of work with the personnel reserve: selection and selection of candidates, motivation and development. To achieve the goal, the assessment of personnel assessment tools, including the advantages of the assessment centre, is given. The scientific article examines the essence of assessing the competence of capable civil servants in the public administration system of the Kazakhstan within the framework of the competence model developed jointly with the Presidential Administration and the Agency of the Republic of Kazakhstan for Civil Service Affairs, such as leadership, decision-making, proactivity, analysis and problem solving, as well as persuasiveness, its main tools. The possibilities of developing the assessment of personnel competencies are being studied.The research was guided by the methods of analysis, synthesis, observation, and comparison of scientific research. The idea of publishing the article arose as a result of the author's participation in competency assessment projects conducted under the leadership of the Academy of Public Administration under the President of the Republic of Kazakhstan. The results of the assessment were obtained as research materials.

Commuting’s impact on wellbeing is a growing focus in urban planning and public policy, reflecting its influence on daily life and health. Despite extensive research, quantitative analysis remains limited. This article conducts a bibliometric review of commuting and wellbeing literature from 1987 to 2024, using Scopus data (N=404). The analysis explores publication trends, key contributors, and thematic areas, identifying the United States, the United Kingdom, Australia, China, and Germany as primary research centers. Prominent journals include Journal of Transport and Health and Transportation Research Part A: Policy and Practice, with institutions such as Utrecht University and the University of Melbourne leading in research on commuting’s psychological and socioeconomic effects. Results indicate an increased focus on commuting’s health, inequality, and environmental impacts since 2020. It is anticipated future studies will explore technological innovations in commuting and their long-term impacts on diverse social groups, underscoring this field's ongoing evolution.

This study employed a comprehensive analytical approach to examine the relationships between investments in healthcare, education, and other economic sectors and their impact on poverty levels in Kazakhstan in urban and rural contexts, allowing for nuanced insights into the differential impacts of investments across these settings. The analysis was structured around evaluating correlations, regression modeling, and ANOVA tests to assess the significance of the observed relationships. Results revealed significant positive correlations between investments in healthcare and education and poverty reduction, with these investments demonstrating a powerful impact in urban areas. Investments in other economic sectors, such as agriculture, industry, and construction, also showed correlations with poverty levels, underscoring the importance of integrated investment strategies. However, regional disparities in investment impacts were evident, highlighting the need for tailored approaches to address the unique challenges and opportunities in specific areas of Kazakhstan. Notably, the study identified particular regions requiring more focused attention due to fluctuations in sectoral contributions to the Gross Regional Product (GRP), variations in investment levels, and the distinct challenges rural areas face. The findings support the hypotheses that investments in healthcare and education significantly affect poverty reduction, with implications for policymakers and regional development strategies.

In recent years, economic research has paid great attention to the development of the socio-cultural environment of the regions. In recent years, many countries have begun to invest more financial resources in the social and cultural problems of the country, including its regions. Identifying and considering the peculiarities of the regional socio-cultural environment will allow for the least painless integration into the global system and integration with other more developed countries. From the point of view of the theory of science, the purpose of this article is to reveal the essence of the concepts of "socio-cultural environment", the conditions and factors of its sustainable development, and to conduct a SWOT analysis to identify the strengths and weaknesses, advantages and disadvantages of the regions of the Republic of Kazakhstan from the prism of the socio-cultural environment of development. During the literature review, it was found that many research papers cover the problems of socio-cultural development of regions and countries in the areas of economics, management, social sphere, etc. In the course of the study, general scientific and special methods were used, and the course of the study was divided into four stages. The theoretical significance of this study is to generalize and expand the theory of the socio-cultural environment of the development of regions, and practical application can be reflected in use by government agencies of recommendations to improve the socio-cultural environment of the development of regions.