Vol. 5 No. 06 (2025): Volume 05 Issue 06

This article examines the state and prospects of digitalization of the state pension system of modern Uzbekistan. The scale and speed of changes in all spheres of public relations caused by digital technologies are unprecedented. These changes also affect the processes of public administration, at the same time, there are differences in this area from the commercial sector, where such a phenomenon as "Digital Uzbekistan" has emerged and is developing. The task of the modern state is to create digital services and platforms focused on more prompt and high — quality satisfaction of the needs of citizens and businesses, i.e., in fact, to generate a new type of public goods in the form of digital state pension services. The article discusses the prospects for the development of such processes.

This article discusses business risk insurance, which is an important tool for protecting a business from potential financial losses and ensuring its stable development. The field of entrepreneurship is becoming more complex and risky, so company owners need to have reliable financial support in case of unforeseen circumstances.

In this article, you will learn what business risk insurance is, what types of business risk insurance exist, and what type of insurance to choose for your business.

In the rapidly evolving banking sector, understanding consumer sentiment is crucial for informed decision-making and enhancing customer experiences. This study investigates the efficacy of large language models (LLMs) for sentiment analysis of consumer feedback within the banking domain. We systematically evaluate five state-of-the-art LLMs—DistilBERT, BERT-base, RoBERTa-base, GPT-3.5, and GPT-4—on a domain-specific dataset of 10,000 consumer feedback entries collected from online banking forums and customer reviews. Each model is rigorously assessed in terms of accuracy, precision, recall, F1-score, and computational cost. Our findings reveal that GPT-4 delivers the highest accuracy and performance across all evaluation metrics but requires significant computational resources, making it less feasible for real-time deployment in cost-sensitive scenarios. In contrast, RoBERTa-base and BERT-base strike a balance between accuracy and resource efficiency, while DistilBERT emerges as the most cost-effective and computationally efficient solution. These results highlight the trade-offs between performance and practical deployment considerations in real-world banking environments. The study underscores the transformative potential of LLM-driven sentiment analysis in the financial sector, offering valuable insights for banks and financial institutions aiming to leverage AI for strategic decision-making and customer satisfaction improvements.

Intrapreneurship, the entrepreneurial activity within established organizations, has garnered significant attention for its role in fostering innovation, competitive advantage, and organizational renewal. This article provides a comprehensive review of the theoretical constructs underpinning intrapreneurship and a hypothetical bibliometric analysis of the academic literature. We explore the evolution of intrapreneurship as a concept, its key dimensions, and the various individual and organizational factors that influence its emergence and success. Through a hypothetical bibliometric mapping, we identify prominent research themes, influential scholars, key publications, and emerging trends in the field. The aim is to synthesize existing knowledge, highlight research gaps, and propose future directions for scholarly inquiry. Understanding intrapreneurship's theoretical foundations and its research trajectory is crucial for both academics and practitioners seeking to cultivate an entrepreneurial spirit within their organizations.