2782-6333 2 16 2025 1-109

RAR RUS 7-24 Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russian Federation Dergachev Maxim 0009-0009-6448-9486 Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russian Federation Beketov Salbek W-8013-2019 57203897426 0000-0002-9703-5079 Peter the Great St. Petersburg Polytechnic University, Russian Federation Gintciak Aleksei gintsyak_am@spbstu.ru COMPARISON OF TOOLS AND METHODS OF FORMING AN IT PROJECT TEAM IN THE CONTEXT OF CASCADING AND FLEXIBLE PROJECT DEVELOPMENT In the context of digital transformation, the formation of well-balanced project teams has become one of the critical factors for the successful implementation of IT projects. The aim of this study is to identify and compare tools that take into account the specifics of both waterfall and agile project management methodologies. The object of the study is the process of selecting and allocating specialists within IT project teams. The research methodology included a critical review of scientific publications, comparative analysis of team formation models and tools, and their systematization according to their applicability to Agile and Waterfall approaches. The analysis identified five key models (fuzzy cognitive, regression, system analysis, grading and experience-based algorithm, skill trees) and six main tools (expert evaluation, game theory, system analysis, single- and multi-criteria optimization, simulation modeling). The comparison showed that most approaches focus on single criteria optimization, while the use of multi-criteria methods for Waterfall projects remains limited. The results revealed a methodological gap between agile and waterfall practices, particularly in terms of communication and dynamic factors. The study concludes that the development of multi-criteria optimization tools for Waterfall projects is necessary to enhance team stability and predictability. The findings may be useful for project managers, HR specialists, and scholars in the field of project team management. 10.48554/SDEE.2025.2.1 519.8 IT-projects optimisation methods team formation waterfall methodology agile methodology https://sustainable.spbstu.ru/article/2025.16.1/ 2_1.pdf

RAR RUS 25-47 Peter the Great St.Petersburg Polytechnic University, Saint-Petersburg, Russia Tereshko Ekaterina

Polytechnicheskaya 29

Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russian Federation Severyukhina Anastasia ANALYSIS OF MARKET RISKS IN THE DEVELOPMENT OF AN AIRLINE'S RISK MANAGEMENT SYSTEM This article is devoted to the analysis of market risks for the development of an effective risk management system in an airline to increase its resilience to crisis situations, as well as minimize the impact of risks on its operations. The study is based on the hypothesis that the effectiveness of implementing a risk management system in the airline directly depends on the quality of the analysis of key production processes. The purpose of the study is to analyze market risks as part of the development of an effective risk management system in the air company to increase its resilience to crisis situations, as well as minimize the impact of risks on its activities. The methodological basis of the study was qualitative and quantitative methods, which assume: 1) construction of the airline's basic production process; 2) formation of the airline's risk register; 3) construction of the airline's risk heat map; 4) formation of an ontological scheme of the stakeholders register for risk management. As a result of the research, key aspects for the development of risk management in airlines have been identified. The integration of risk management systems with quality and safety management systems, digitalization will help to improve the quality of risk analysis, improve decision-making processes in airlines, and adapt to new market requirements.  10.48554/SDEE.2025.2.2 656.7 risk management passenger transportation airlines production process risk register register of stakeholders https://sustainable.spbstu.ru/article/2025.16.2/ 2_2.pdf

RAR RUS 48-65 St. Petersburg Electrotechnical University “LETI”, Saint-Petersburg, Russian Federation Mavrin Daniil 57144577800 St Petersburg Electrotechnical University “LETI”, St. Petersburg, Russia Brusakova Irina MODULAR ARCHITECTURE OF A HEALTHCARE ANALYTICS PLATFORM WITH DE-IDENTIFIED DATA PROCESSING The digitalization of healthcare has led to a rapid increase in data volume alongside growing demands for privacy and regulatory compliance. In this context, many healthcare organizations face difficulties integrating fragmented information systems while maintaining full control over sensitive data. This paper proposes a conceptual framework for a modular analytics platform designed to support predictive decision-making in medical institutions without direct access to identifiable patient information. The study focuses on the digital transfor mation of healthcare management processes using de-identified institutional data. The methodology combines systems analysis with architectural modeling, resulting in a set of structured diagrams that describe the platform’s deployment logic, component interaction, and business model. The proposed architecture supports both cloud-based and on-premises deployment options, allowing institutions to choose between flexibility and full data sovereignty. The platform includes modules for integration and visualization, along with secure API-based data exchange mechanisms. architectural and BPMN diagrams are presented to illustrate the platform structure and subscription-based financial model. The results demonstrate the feasibility of implementing the proposed architecture in healthcare environments constrained by legal, technical, and organizational factors. The concept provides a foundation for future prototyping and pilot deployment in healthcare systems aiming to achieve secure, scalable analytics. 10.48554/SDEE.2025.2.3 004 analytics platform modular architecture digital healthcare de-identified data predictive analytics information security https://sustainable.spbstu.ru/article/2025.16.3/ 2_3.pdf

RAR RUS 66-83 Peter the Great St.Petersburg Polytechnic University, Saint-Petersburg, Russia Gutman Svetlana Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russian Federation Egorova Maya Department of Sustainable Development of PJSC "SPB Exchange", Moscow, Russian Federation Novikova Ekaterina THE GREENIUM EFFECT IN THE CORPORATE BOND MARKET OF EU COUNTRIES The article examined the effect of the green premium (greenium) on the corporate bond market of the European Union countries. The relevance of the work is due to the need for empirical evidence of the existence of this award in the context of heterogeneous methodological approaches to its assessment and the increasing role of sustainable financing in the context of the transition to a low-carbon economy. The aim of the work is to identify and quantify the effect for corporate bonds issued by Germany, Spain and the Netherlands, taking into account national macroeconomic specifics and industry specifics of issuers. The research methodology includes the formation of a sample of pairs of comparable instruments, a comparative analysis of profitability and liquidity, an assessment of correlation dependencies and the construction of regression models taking into account macroeconomic indicators and market indicators. The results show that the most significant and statistically significant decrease in yields was found for Spanish issuers, while the effect was statistically less significant for German and Dutch bonds. Regression analysis confirmed the significant impact on profitability of traditional macroeconomic factors, including the inflation rate and the risk-free rate. There was also a statistically significant negative impact of inflation and a positive impact of the risk-free rate on the yield of Spanish green bonds, and the sensitivity to inflation turned out to be significantly higher. The quality of the constructed models was high, as evidenced by the coefficients of determination (R2) at the level of 0.82 for classic Spanish bonds and 0.86 for green bonds of Germany and the Netherlands. The results obtained emphasize the importance of taking into account national specificities when developing investment strategies and shaping public policy for the transition to sustainable development. The practical significance lies in the possibility of using the research results for a deeper analysis and development of a methodology for assessing sustainable financial instruments.  10.48554/SDEE.2025.2.4 330.3 sustainable development green bonds greenium corporate bonds https://sustainable.spbstu.ru/article/2025.16.4/ 2_4.pdf

RAR RUS 84-109 Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russian Federation Sharikov Nikita LLC Gazpromneft Information Technology Operator, St. Petersburg, Russian Federation Poliakova Polina Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russian Federation Kudryavtsev Arsenii CLUSTER ANALYSIS OF THE ECONOMIC DEVELOPMENT OF THE PROVINCES OF THAILAND The article addresses the issue of spatial differentiation in the socio-economic development of Thailand’s provinces in the context of the national “Thailand 4.0” strategy. The research problem arises from the limited empirical evaluation of regional heterogeneity that integrates demographic, sectoral, and institutional dimensions. The objective is to identify structural patterns of provincial development and to propose a typology that may serve as a basis for differentiated regional policy. The study relies on provincial-level indicators for 2010 2021, including per capita gross regional product, labor migration, industrial investment, land use, and inbound tourism. The Williamson coefficient was applied to quantify inequality, revealing its growth over the past decade. Clustering was performed using k-means, hierarchical agglomerative methods, and DBSCAN in Python with scikit-learn. The k-means algorithm with three and four clusters produced the most robust results, isolating Bangkok as a distinct cluster. Three persistent groupings were identified: industrial centers in the central region, agricultural provinces of the northern and northeastern areas, and tourism-driven provinces in the south. The analysis also revealed β-convergence processes in several transitional provinces, suggesting gradual alignment of development trajectories. Policy recommendations emphasize modernization of agriculture, innovation support for industrial centers, and infrastructure projects in tourism-intensive provinces. The findings confirm the persistence of spatial polarization and highlight the utility of cluster analysis as a tool for refining Thailand’s regional development strategy.  10.48554/SDEE.2025.2.5 332.135 cluster analysis regional economic development spatial differentiation socio-economic factors provinces of Thailand https://sustainable.spbstu.ru/article/2025.16.5/ 2_5.pdf