The article examined the integration of the digital economy and public debt management, as well as the formation of new financial models. Innovative areas of Public Debt Management based on Artificial Intelligence, big data, Blockchain and fintech technologies were analyzed. Scientific conclusions were developed based on international experience and macroeconomic indicators of Uzbekistan.

This article examines the specific aspects of econometric modeling in the dynamic and complex conditions of the modern economy. The paper highlights contemporary trends such as the integration of big data, machine learning, and artificial intelligence, which play a crucial role in forecasting the impacts of inflation, unemployment, climate change, and pandemics. The methodology employs a systematic literature review, drawing on scientific articles from the Scopus, Web of Science, and ResearchGate databases over the last five years (2020-2025). The results indicate that ML-hybrid models enhance forecast accuracy (with reductions in RMSE and MAE), although the adverse effects of climate change and data uncertainty pose significant challenges. The conclusions and recommendations propose increasing the robustness of models in policy formulation, strengthening interdisciplinary collaboration, and implementing ethical standards, thereby contributing to sustainable development and economic recovery.

This study provides a comparative analysis of innovative development models that have played an important role in the global economy in the 21st century. The article takes an in-depth look at the innovation systems of the United States, the European Union, the Scandinavian countries, South Korea, Singapore, Japan, and Germany. Five main models - open innovation, Triple Helix, cluster innovation, public governance, and corporate strategies - are analyzed based on statistical data for 2024. The results of the study show that each model has its own advantages and is adapted to the institutional environment and economic characteristics of countries. Hybrid models and the integration of sustainable development goals have become the main trends in modern innovation strategies. The recommendations presented for Uzbekistan determine the ways to develop the national innovation ecosystem.

The study paper provides a detailed examination of how digital marketing methods affect the economic efficiency of commercial banks, specifically within the changing environment of the banking sector. The study examines the relationship between higher digital marketing spending, increased investment in staff development, and their impact on the net income of banks using 18 years of financial data from ATIB "Mortgage Bank" in Uzbekistan. The study uses advanced statistical analysis to create Vector Autoregressive (VAR) and Autoregressive Distributed Lag (ARDL) models to predict and assess the impact of marketing initiatives in the banking industry. The results highlight a strong correlation between increased digital marketing initiatives, greater staff commitment, and higher financial success of commercial banks. The VAR and ARDL econometric equations, generated from time series data, offer a strong foundation for comprehending the dynamic relationship between marketing tactics and economic results in the banking sector. This research adds to the overall discussion on the effectiveness of digital marketing, providing significant data for financial institutions looking to improve their economic efficiency by strategically investing in marketing and human resources.

In this research work, autoregressive distribution lag (ARDL) models have been developed that assess the long-term and short-term influence of factors influencing the sustainable socio-economic development of the region on the volume of GRP per capita. Based on the developed models, the priority levels of factors were determined.

These findings underscore the need for context-specific corporate governance models to optimize overall financial performance and mitigate risk. This research contributes to the understanding of how multiple governance models affect bank stability globally and provides information for policy makers and bank executives aiming to improve governance frameworks. These findings underscore the need for context-specific ways of corporate governance to optimize economic performance and mitigate risk. This research contributes to the expert knowledge of the ways in which different governance models affect the global stability of financial institutions and provides information for policymakers and bank executives aiming to improve governance frameworks.

This article describes the application of digital transformation in industry, and the main issues in the organization of digital transformation processes in enterprises. The purpose of this study is to identify the main problems and opportunities in the organization of digital transformation processes in the industry based on statistical analysis methods. While writing the article, scientific and practical methods were used, such as the method of comparison, analysis, and synthesis, and statistical data for monitoring the main expenses of enterprises for the development of the digital environment. The main problems of digital transformation were analyzed, and several problems and obstacles of digital transformation were studied. Also, the article describes foreign experiences of the digital transformation process, its role in the economy, advantages and disadvantages, and solutions.

This article examines the transformative role of neural networks in econometrics and financial decision-making, emphasizing their influence on personal finance, automation, healthcare, transportation, and human-computer interaction. Neural networks, inspired by the structure of the human brain, have the potential to revolutionize these sectors by enhancing efficiency, accuracy, and decision-making capabilities. In personal finance, they can optimize budgeting, savings, and expenditure management through automated models such as the McCulloch-Pitts neuron. In healthcare, neural networks improve diagnostic capabilities and enable predictive treatment. The article also highlights the applications of neural networks in econometrics to analyze financial patterns, detect fraud, and manage risks more effectively. However, it also addresses the ethical concerns related to data privacy, security, and biases in algorithmic decision-making, stressing the importance of responsible development. Ultimately, it concludes that, despite the challenges, the benefits of integrating neural networks into econometric models and financial systems are substantial and indispensable for modern advancements.

In this article, mathematical models are compiled based on the dynamics of electricity supply volumes in the Republic of Uzbekistan for 2010-2023, as well as for the period from 2010 to 2017 and beyond. The forecast indicators for the period from 2024 to 2030 have been determined. The dynamics of the growth of electricity supply volumes during the study period is also analyzed.

This study explores how Islamic finance can be effectively introduced in non-Islamic economies, with a focus on Uzbekistan’s legal and economic environment. Through examining global models such as dual banking, hybrid systems, regulatory sandboxes, and institutional frameworks couple with case studies from the UK, Malaysia, Bahrain, Singapore, and Nigeria, the research highlights how diverse jurisdictions have adapted to Shariah-compliant finance. Using a qualitative methodology, it emphasizes the need for regulatory innovation and alignment with Islamic principles. The study offers policy recommendations to support inclusive, ethical, and sustainable financial development, positioning Islamic finance as a strategic tool for economic diversification in Uzbekistan.

In this article, based on the dynamics of electricity production and gross domestic product in the Republic of Uzbekistan, mathematical models were constructed for the period 2010-2023 and further until 2017. Forecast indicators for the period from 2024 to 2030 were determined. An econometric analysis of the impact of electricity production on GDP for the period under study was also conducted.

This article presents a scientific analysis of the integration of artificial intelligence technologies into assessment systems in higher education. It examines the challenges of traditional assessment, such as subjectivity, rigidity, and dependence on the human factor. The potential of artificial intelligence tools to automate assessment, increase transparency and accuracy, and analyze student performance in real time is substantiated. The article also provides proposals for developing assessment models based on advanced international practices.

The article analyzes the essence of the management system, its main functions and impact on production efficiency from a theoretical and practical point of view. The study examines the formation of management functions and their impact on the activities of the enterprise based on classical schools of management and modern approaches. Also, based on practical examples and modern models, the influence of these functions on the indicators of production productivity, resource efficiency, product quality and competitiveness are substantiated.

The rapid growth of on-demand food delivery services has posed significant challenges in logistics optimization. This study focuses on a formerly leading food delivery company in Uzbekistan, which faced difficulties in meeting customer expectations due to high demand and inefficiencies in courier allocation. The research applied Discrete Event Simulation (DES) theory to analyze courier utilization, waiting times, and delivery performance. The model incorporated district-based clustering, queueing theory, stochastic simulation modeling, model validation and performance evaluation to evaluate various operational scenarios. Findings reveal that integrated models reduce delivery times by 1.6 times, enhance throughput, and provide actionable strategies for urban delivery optimization. The results contribute to both academic literature and managerial practice in emerging markets.

This article analyzes the future scenarios of regional socio-economic development in the context of forming an innovation economy, grounded in scientific evidence. The introduction outlines contemporary trends (digital transformation, artificial intelligence, green technologies, and climate change), while the literature review is based on several scholarly research works from prestigious journals over the past five years, encompassing the evolution of RIS (regional innovation systems), empirical models, and policy recommendations. The methodology relies on systematic literature review (SLR) and scenario planning. The results delineate three scenarios: optimistic (2–5% growth through digital integration), pessimistic (inequality and stagnation), and mixed (transformative adaptation). The conclusion proposes strengthening RIS and investing in green innovations

The rapid development of the tourism industry is generating deep structural changes in the management of tourism infrastructure in Uzbekistan. This article provides a systematic analysis of the key components of tourism infrastructure, its development trends, and interactions with major economic factors. The study comparatively examines statistical data from 2016-2024 on the expansion of hotel capacity, improvements in transport and logistics systems, growth in investment flows, formation of regional tourism clusters, and service quality enhancements. Moreover, the impact of infrastructure development on tourism demand, the impulse of state policies and reforms on the sector, as well as pandemic-related disruptions and post-pandemic recovery dynamics, are assessed using econometric models. The findings contribute to the development of practical recommendations aimed at modernizing tourism infrastructure, increasing international tourist inflows, improving regional infrastructure efficiency, and ensuring sustainable economic growth.

This article provides a comprehensive analysis of the theoretical, methodological, and institutional aspects of implementing a mass property valuation system in the Republic of Uzbekistan. The study substantiates the limitations of traditional cadastral valuation methods in an economy based on market mechanisms and reveals the necessity of introducing a transparent and automated mass valuation system aligned with international best practices. The paper presents a comparative analysis of individual and mass valuation approaches, highlighting their role in tax base formation and functional differences. The advantages of using GIS technologies, mathematical and statistical models, large-scale data (Big Data), and multiplicative valuation models in the mass valuation process are demonstrated. In addition, ongoing reforms, the regulatory and legal framework, institutional structures, and step-by-step implementation mechanisms of the valuation system are analyzed. The research findings contribute to fair and economically justified property tax assessment, stabilization of budget revenues, and increased transparency in the real estate market.

Maqolada O‘zbekistonda mehnat bozorining hozirgi holati va rivojlanish istiqbollari, shuningdek, aholini ish bilan ta’minlash xizmatlari, kasbiy tayyorlash va qayta tayyorlash, yoshlarni ish bilan ta’minlash, ishsizlarga nafaqa to‘lash va boshqa yo‘nalishlardagi tendensiyalar tahlil qilingan. Ishda mehnat bozorini makroiqtisodiy tartibga solish modellari va instrumentlari, shuningdek ayrim xorijiy mamlakatlarda faol mehnat bozori choralarini qo‘llash tajribasi ko‘rib chiqilgan. Xorijiy manbalar sharhi asosida faol makroiqtisodiy siyosatning bandlikka ta’siri yoritilgan.

This article analyzes foreign legal approaches to regulating tour and excursion activities and defines the role of tourist police within the system of ensuring tourist safety. The paper examines institutional models for interaction between law enforcement agencies and tourism management bodies, as well as mechanisms for monitoring the activities of tour guides. Based on a comparative legal analysis of regulatory acts, this paper identifies the primary models for tourist police participation in regulating tour and excursion activities and applying administrative enforcement measures. It is concluded that while tourist police generally do not directly license guides, they play an important role in maintaining public order, identifying illegal activities, and protecting the rights of tourists.

Furthermore, the paper demonstrates that the current accounting system of Uzbekistan represents a hybrid model combining elements of different international frameworks. It is argued that the transition to international standards should not be viewed as a one-dimensional reform but rather as a complex transformation incorporating economic, strategic, and social factors. Based on this approach, the study develops theoretical and practical recommendations aimed at improving the national accounting system, including alignment with key trading partners, strengthening regional integration, and incorporating Islamic finance principles.

This article examines the issues of improving the accounting of financial investments from the perspective of national and international standards. In particular, it analyzes the content, scope of application, and practical aspects of the National Accounting Standard No. 12 “Accounting for Financial Investments,” adopted in the Republic of Uzbekistan in 2024. The study explores the differences between traditional approaches to the measurement and classification of financial investments and modern models applied in international practice. Specifically, it provides a theoretical analysis of business model-based classification, fair value measurement, and the expected credit loss (ECL) model within the framework of IFRS 9 “Financial Instruments”. Furthermore, the article develops theoretical and practical recommendations aimed at enhancing accounting practices and improving the quality of financial reporting in the context of ongoing accounting reforms.

Vocational interest theory has long been dominated by Holland’s RIASEC model. Although its simplicity, interpretability, and practical usefulness remain influential, its broad-band categories are increasingly unable to capture finer-grained differences in contemporary occupational structures and non-Western cultural contexts. This article proposes the WBCI six-dimensional hierarchical model, composed of six first-order dimensions and twelve second-order factors, to reflect the Chinese cultural context and occupational ecology. The model highlights functionally important distinctions that are often compressed in traditional classifications, such as influential interaction versus supportive interaction, technical construction versus normative execution, and business expansion versus transactional allocation. This purely conceptual article systematically clarifies the theoretical gaps addressed by WBCI, its construct boundaries, its comparative relationship with existing models, and its future validation path. WBCI provides a theoretically clearer, more culturally embedded, and more operational framework for vocational assessment, career counseling, major selection, and occupational matching.

This article is devoted to consideration of the prospects for the development of small business and private entrepreneurship in our country, the directions for reducing poverty based on the development of entrepreneurship through foreign models. Moreover, the article provides a comparative analysis of the scientific and theoretical views of foreign and local scholars. The problems related to the development of small business and private entrepreneurship have been revealed, and conclusions and proposals for solving these problems have been developed.

The paper examines economic mechanisms of water quota allocation under conditions of increasing water scarcity. Water quota allocation is considered as a key instrument for water distribution, closely linked to tariff regulation, water markets, and water rights. The study explores fixed, adaptive, seasonal, and market-based quota models. A comparative analysis of practices in Australia, Spain, and Chile is conducted, alongside an assessment of challenges related to the allocation of water withdrawal limits in Central Asia. The study concludes that the most sustainable approaches are hybrid models combining state regulation of environmentally acceptable quotas with economic mechanisms for their efficient redistribution among water users.