Zh. T. Konurbayeva

The study focuses on the development and evaluation of predictive models for forecasting labour demand in the metallurgical industry of the East Kazakhstan Region, with particular emphasis on the impact of production volume and labour productivity. The methodological framework combines classical econometric approaches with modern machine learning techniques, which makes it possible to capture nonlinear dependencies and more accurately assess labour market dynamics. The research is based on regional statistical data for the period 2015–2023. Several modeling approaches were tested, including linear regression, a parametric specification, and a hybrid machine learning model that integrates decision trees with local linear regression. Model performance was validated using the Mean Absolute Error (MAE), followed by forecasting labour demand for 2024–2028. Results demonstrate that the hybrid model outperforms the alternatives by achieving the lowest prediction error and producing the most plausible projection of moderate employment growth. The parametric model, although less precise, offers a high level of interpretability and is well suited for strategic analysis, while the linear regression model has limited effectiveness under nonlinear conditions. The practical value of the research lies in the possibility of embedding the developed models into decision support systems for government bodies and industrial enterprises, enabling early assessment of the impact of technological changes and production dynamics on employment. The outcomes may contribute to shaping balanced human resource policies, aligning educational programs with labour market needs, and conducting scenario analyses. Furthermore, the findings establish a foundation for extending the methodology to other industries and incorporating additional variables related to digitalization and innovation activity.

The integration of artificial intelligence (AI) and information technology (IT) is transforming business operations while increasing energy demand. A scalable and nonintrusive method for assessing the adoption of energy-conscious IT governance without direct measurements of energy use is lacking. To address this gap, a machine learning framework is developed and validated that infers the presence of energy-conscious IT governance from five indicators of digital maturity and AI adoption. Enterprise survey data were used to train five classification algorithms—support vector machine, logistic regression, decision tree, neural network, and k-nearest neighbors—to identify organizations implementing energy-efficient IT/AI management. All models achieved strong predictive performance, with SVM achieving 90% test accuracy and an F1 score of 89.8%. The findings demonstrate that an enterprise’s technological profile can serve as a reliable proxy for assessing sustainable IT/AI practices, enabling rapid assessment, benchmarking, and targeted support for green digital transformation. This approach offers significant implications for policy design, ESG reporting, and managerial decision-making in energy-conscious governance, supporting the alignment of digital innovation with environmental objectives.

Professional certification of engineers plays a crucial role in verifying competencies and ensuring the safety and quality of engineering outputs. However, most existing certification systems assign fixed validity periods (e.g., 3–5 years) without considering individual engineer characteristics or the intensity of technological progress in specific fields. This study examines the key factors influencing the optimal validity period of engineering certifications and proposes it as a measurable indicator to support safety in engineering practice. A new model is introduced that integrates expert judgment, fuzzy set theory, and bibliometric analysis of Q1/Q2 Scopus-indexed publications. The model incorporates three main factors: competence level, professional experience, and the technological intensity of the discipline. A case study from the engineering certification system of Kazakhstan demonstrates the model’s practical applicability. Certification bodies, policymakers, and engineering organizations can use these findings to establish more flexible certification validity periods, thereby ensuring timely reassessment of competencies and reducing safety risks. For example, for mechanical engineers, the optimal validity period is 3 years rather than the statutory 5 years; in other words, the model recommends a 40% reduction in certification validity. This reduction reflects the combined effects of competency level, professional experience, and technology intensity on certification renewal schedules. Overall, the proposed factorial approach supports a more personalized and safety-oriented certification process and offers insights into improving national qualification systems.

This study examines the development of the digital economy and society in the Republic of Kazakhstan by combining international benchmarking with a context-specific national framework. It highlights the limitations of existing global indices such as DESI, NRI, and EGDI in capturing the structural and institutional dimensions of digital transformation in emerging economies. To address this gap, the study introduces a novel composite metric, the Index of Digital Economy Development (IDED), which integrates five sub-indices: infrastructure, usage, human capital, economic digitization, and transformation effectiveness. The methodology involves comparative index analysis, the construction of the IDED, and statistical validation through a public opinion survey and regression modeling. Key findings indicate that cybersecurity is a critical yet under-represented component of digital development, showing strong empirical correlations with DESI scores in benchmark countries. The results also highlight Kazakhstan’s strengths in digital public services and internet access, contrasted with weaknesses in business digitization and innovation. The proposed IDED offers a more comprehensive and policy-relevant tool for assessing digital progress in transitional economies. This study contributes to the literature by proposing a replicable index structure and providing empirical evidence for the inclusion of cybersecurity in national digital economy assessments. The aim of the study is to assess Kazakhstan’s digital economy development by addressing limitations in global measurement frameworks. Methodologically, it combines comparative index analysis, the construction of a national composite index (IDED), and statistical validation using a regional survey and regression analysis. The findings reveal both strengths and gaps in Kazakhstan’s digital landscape, particularly in cybersecurity and SME digitalization. The IDED introduces an innovative, context-sensitive framework that enhances the measurement of digital transformation in transitional economies.

Engineering education serves as a cornerstone of a region's economic potential, and its continuous improvement is essential for driving rapid and positive economic transformations. The strategic objectives of universities should be focused on ensuring that graduates leave their institutions with confidence in their future and the ability to swiftly adapt to the industrial environment. However, according to data from the Ministry of Labor and Social Protection of the Republic of Kazakhstan, a significant number of engineering graduates are compelled to undergo retraining after completing their studies. Addressing this issue necessitates the development and implementation of a unified managerial approach. Such an approach would enable universities to prepare engineering personnel in alignment with contemporary economic trends, labor market demands, and the requirements of key stakeholders. The article demonstrates that the development of educational programs must prioritize the cultivation of universal competencies (soft skills). Soft skills are essential for engineers, enabling teamwork in interdisciplinary fields and adaptation to fast-changing technology. An online survey of employers in the East Kazakhstan Region helped identify the most significant soft skills, assess their current level, and forecast future competencies. The study confirmed that soft skills development greatly improves graduates' readiness to adapt to the evolving labor market and technology. The survey results provided a basis for recommendations to improve the educational process in universities. Partial implementation of these recommendations will enable the preparation of qualified engineering personnel tailored to the needs of the regional labor market.

Research objective. The purpose of this study is to analyze the economic aspects of integrating technical and vocational education standards into the system of higher and postgraduate education, as well as to identify prospects and problems related to the training of engineering personnel. The research is aimed at determining the impact of such standards on improving the competencies and professional training of graduates in accordance with the requirements of the modern labor market.Research methodology. The methodological basis of the study is economic, statistical and comparative analysis. To obtain data, quantitative and qualitative methods were used, including document analysis, statistical methods and comparative case studies, allowing us to consider the experience of implementing educational standards in different countries, on the basis of which an assessment of the effectiveness of educational standards and their impact on the professional training of engineering personnel was carried out.Originality / research value. The study presents an original approach to the analysis of the economic aspects of implementing technical and vocational education standards into higher and postgraduate education systems. The contribution of the research is to identify promising areas and possible risks associated with the integration of such standards, which is especially important in the context of digitalization and technological development. The value of the work lies in the possibility of using its results to develop recommendations for improving the training of engineering personnel in Kazakhstan and other developing countries.Research findings. The study showed that the integration of technical and vocational education standards helps to improve the level of qualification of engineering personnel, their readiness to solve modern problems in the manufacturing and construction industries. It was also found that digitalization and technological equipment of universities help to attract additional funding and improve the material and technical base for training specialists.

Мақалада цифрлық жетілу ұғымы және оны бағалаудың әдістемелік негіздері қарастырылады. Цифрлық жетілу – бұл компанияның заманауи технологияларды енгізу және пайдалану арқылы бизнес-процестерді оңтайландыруға, инновациялық шешімдерді қолдануға және нарықтық жағдайларға икемделуге қабілеттілік деңгейін сипаттайтын маңызды көрсеткіш. Мақалада цифрлық жетілудің әртүрлі деңгейлерін сипаттау үшін қолданылатын негізгі тәсілдер мен көрсеткіштер жүйеленген. Мысалы, ODMM (Open Digital Maturity Model), Digital Maturity Index (DMI), Digital Maturity Model (DMM), сондай-ақ International Institute for Management Development (IMD) және Cisco әзірлеген Digitization Piano модельдері талданады. Бұл модельдер ұйымның цифрлық жетілуін бағалау үшін қолданылатын негізгі категориялар мен өлшемдерге негізделген. Бағалау салаларына стратегия мен көшбасшылық, цифрлық мәдениет, IT-мүмкіндіктер, клиентке бағдарлану, инновациялар, процестер мен құрылымдық өзгерістер кіреді. Әр модельдің ерекшеліктері, оның қолдану аясы мен кәсіпорынның дамуына қосатын үлесі көрсетілген.Мақалада цифрлық жетілуді бағалаудың әдістемелік құралдары кәсіпорындарға жаңа цифрлық технологияларды енгізу арқылы процестерді оңтайландыру, шығындарды азайту және клиенттердің қанағаттану деңгейін арттыруға бағытталған ұсыныстар әзірлеу үшін қолданылады. Зерттеу нәтижелері цифрлық трансформация процесінде ұйымдарға олардың күшті және әлсіз жақтарын анықтап, даму жол картасын құруға көмектеседі. Кілтті сөздер: цифрлық жетілу, цифрландыру, жетілу модельдері, цифрлық трансформация, бизнес-процестер, цифрлық технологиялар.

Настоящее исследование посвящено изучению состояния современного инженерного образования. В статье представлен анализ моделей инженерного образования, определяющих концептуальную основу развития инженерного дела передовых стран мира. Определена необходимость трансформации отечественной модели инженерного образования в долгосрочной перспективе с учетом мирового опыта и трендов отрасли. Цифровая трансформация существенно меняет ландшафт инженерной деятельности. Инженеры должны быть адаптируемыми, устойчивыми и владеть новейшими цифровыми технологиями, чтобы не только быть успешными, но и сохранять конкурентоспособность в динамичной среде современного мира. Принятие этих изменений может привести к созданию более эффективных, инновационных и устойчивых инженерных практик, отвечающих меняющимся требованиям современного мира. В рамках анализа вторичных источников определены потенциальные вызовы и тренды в области инженерного образования как на глобальном, так и на локальном уровне. Результаты исследования показали растущую необходимость в согласованных усилиях представителей академических кругов, университетов, государства и бизнеса по совершенствованию национальной модели инженерного образования. Цифровые технологии выступают инструментом на пути к предоставлению равных возможностей по развитию необходимого «портфеля навыков» для обучающихся. Ключевые слова: инженерное образование, компетенции, цифровизация, hard skills, soft skills.

Высокие темпы социально-экономического развития регионов Казахстана невозможны без высокого уровня эффективности управления в вузах. Обучение инженеров в региональных вузах должно соответствовать отраслевой специфике конкретных областей и фокусироваться на разработке компетенций, необходимых для решения конкретных проблем и внедрения технологий, актуальных для производств. Анализ показал, что регионы имеют разную специализацию своих экономик. Такие различия в региональном развитии являются ключевым фактором, который необходимо учитывать при организации инженерной подготовки. Высокий спрос на конкретные инженерные навыки из-за особенностей отраслевой структуры экономики региона ведет к необходимости уделять внимание развитию специализированных навыков при подготовке инженерных кадров. В случае, если у региональных различий есть экологический или социальный аспект, обучение инженеров должно поддерживать принципы устойчивого развития, специфичные для конкретного региона. Тем самым, учет региональных особенностей в инженерной подготовке позволит обеспечить более эффективное соответствие компетенций выпускников вузов требованиям местного рынка труда, что, несомненно, будет способствовать устойчивому и сбалансированному развитию экономики регионов Казахстана. В целом можно сказать, что качественная подготовка инженерных кадров, ориентированная на соблюдение принципов и целей устойчивого развития, будет способствовать достижению более сбалансированного и эффективного развития экономики регионов и страны. Ключевые слова: инженерные кадры, устойчивость экономики региона, сбалансированность регионального развития, региональные вузы, экономика промышленности, экологическая политика.