Chechen State University

Abstract. The relevance of this study is determined by the need to overcome structural imbalances in regional economies dependent on federal funding and to find effective mechanisms for transitioning from a budgetary redistribution model to a market-oriented production development model. The objective of the study is to identify paths and prospects for diversifying the Chechen Republic's economy based on a quantitative assessment of the sectoral structure and identifying priority areas for expanding the region's production base in the period 2022-2025. Research methods include a systemic and statistical analysis of gross regional product, employment, and investment indicators, calculation of the diversification coefficient using the Herfindahl-Hirschman formula and the structural coefficient of industries, as well as a matrix ranking of economic activities. The results showed that the formally high diversification coefficient (Kdv ≈ 0.886) is achieved primarily through budget-dependent sectors, while the share of manufacturing, information technology, and tourism in GRP remains critically low. The share of federal transfers exceeded 80% of budget revenues throughout the entire period. The practical significance of the study lies in the substantiation of four priority areas for diversification: the agro-industrial complex, the tourism and recreation sector, production-oriented small and medium-sized enterprises, and the digital economy. Their implementation will ensure a gradual increase in the financial self-sufficiency of the Chechen Republic.

This article addresses a problem that at first glance seems obvious, but upon closer examination reveals unexpected depth: how exactly should the changing behavior of digital consumers influence the design of e-commerce interfaces? The authors analyze the “Messy Middle” model of the nonlinear consumer journey, explore the phenomenon of attention deficit in the digital environment, and trace the consequences of the mobile shift for the mobile-first principle. The paper identifies and describes trends changing the face of the market: social commerce, subscription consumption models, and ecosystem competition. Particular attention is paid to Russian specifics–in particular, the fact that marketplaces account for over 70% of online orders in the country. The novelty of the paper lies in its attempt to establish a system of connections between behavioral shifts and specific, verifiable design requirements for user interfaces.

In an era of increasing competition and declining profitability in the construction industry, competent management of all stages of a project’s lifecycle is becoming a key condition for a company’s survival. Digital technologies are no longer just a fashionable trend; they have become an effective means of minimizing human losses both on construction sites and in the offices of engineering organizations. Real-world examples from major developers are studied, demonstrating reductions in construction periods of up to 20% and a reduction in construction supervision costs of up to 30%. This is achieved by integrating a facility’s information model with a scheduling and network planning system (the so-called 4D system). Particular emphasis is placed on the complexity of the “last mile”–the process of transferring clearly structured information from contractors to the operating party to create a company’s “digital asset.” The article also proposes a method for the phased implementation of Russian engineering software, which can replace the products of foreign developers that have left the market, while ensuring the continuity of management throughout the entire lifecycle. This algorithm ensures that accumulated data is not lost or disrupted, adapting it to new software solutions. Particular attention is paid to the fact that the effective use of digital tools requires not only a technical foundation but also a change in the data culture. Project managers must shift from reactive management methods to proactive ones, using predictive analytics to prevent problems before they arise. For example, a 4D system not only allows for visualization of construction progress but also identifies potential schedule conflicts, which directly impacts risk reduction and increased process transparency. Case studies show that companies that have successfully implemented such approaches not only save resources but also improve the quality of projects. Timely data transfer to operational services helps avoid costly downtime and errors during the commissioning of engineering systems. Thus, digitalization is becoming more than just another report, but a real lever for improving efficiency and competitiveness in today’s construction market. In conclusion, it is emphasized that the transition to domestic software is not only a necessity due to geopolitical changes, but also an opportunity to revise outdated processes and implement more flexible and reliable technological chains, which ultimately leads to a stronger business in the long term.

This article presents the conceptual development and psychometric substantiation of a scale for measuring university faculty readiness to integrate neural network technologies into the educational process without conducting its own empirical research. Based on an analysis of Russian studies on digital competence and innovation readiness, the key components of the construct are identified and their operationalization as subscales is proposed. The scale’s potential as a tool for monitoring faculty readiness for the neural network-based transformation of higher education is demonstrated.

The article discusses the theoretical and applied aspects of enterprise cost optimization using modern information technologies and data analytics methods. The relevance of the research is due to the need to increase the operational efficiency of a business in conditions of economic instability and fierce competition, when traditional methods of cost management based on budgeting and regulatory accounting cease to produce the necessary results. Based on the synthesis of the provisions of financial management, management accounting and information technology, the key areas of application of data analytics to identify and reduce inefficient costs are analyzed. The methods of descriptive, diagnostic, predictive and prescriptive analytics in the context of cost management are considered. Special attention is paid to the practical aspects of implementing information systems for monitoring and cost optimization, including the selection of software solutions, data preparation and staff training.