The Saint Petersburg University of Economics (UNECON, SPbSUE, Saint Petersburg State University of Economics; Russian: СПбГЭУ, Санкт-Петербургский государственный экономический университет) is a public university located in Saint Petersburg, Russia. It was formed in 2012 by merging Saint Petersburg State University of Economics and Finance, Saint Petersburg State University of Engineering and Economics, and Saint Petersburg State University of Service and Economics. The university consists of 7 faculties, 45 departments, has 1 branch and includes the College of Business and Technology.
The article examines the features of the digital transformation of state social organizations in the Russian Federation. It is shown that digitalization in modern conditions acts not only as a technological process, but also as a factor in changing the logic of management, mechanisms of interaction with the population and approaches to assessing the effectiveness of public institutions. The author identifies key areas of digitalization, systematizes organizational, resource and managerial constraints that prevent the expected effects from being achieved. The author’s methodology for assessing the digital maturity of social sector organizations has been developed in four blocks: digital strategy and organizational culture, resources (labor, financial information), processes, and customer orientation.
The article examines the impact of network effects of digital platforms on the spatial differentiation of the regional economy. The relevance of the study is driven by the growing importance of platform-based business models that reshape the distribution of demand and economic activity. The aim of the research is to identify the mechanisms through which network effects contribute to regional disparities. The methodological framework is based on the theory of platform economics and regional development, as well as comparative analysis and economic-mathematical modeling. The paper proposes a model linking regional demand to the number of users, business participants, and algorithmic amplification. The empirical analysis is based on data from major platforms such as Wildberries and Ozon. The results show that platform development leads to the concentration of users, businesses, and infrastructure in economically advanced regions. It is concluded that network effects act as a significant factor in reinforcing spatial inequality and influencing regional competitiveness.
This paper presents a competency profiling system combining traditional pedagogical frameworks (T-Shaped Skills, 4C model, Bloom’s Taxonomy) with predictive analytics to support adaptive educational pathways in engineering education. The system was validated through a mixed-methods study involving 1,459 students from three Russian universities, complemented by Delphi expert assessments from 20 faculty members and 20 industry employers (Kendall’s $\mathrm{W}=0.78; \mathrm{p}{\lt}0.001$). Skill demand forecasting through 2035 was performed using an ensemble of ARIMA, Prophet, and XGBoost models (ensemble MAPE $= 6.9 \%; R^{2}=0.93$). Gap analysis identified critical competency deficits in programming (37.9%), process evaluation (32.2%), and solutions development (30.4%). Scenario-based forecasting indicates that the demand index for programming and AI skills may reach 245% of the 2024 baseline by 2035. We propose a conceptual architecture for an AI-Enhanced Adaptive Tutor built on LLM/RAG with a Dual Knowledge Base and an Ethics-by-Design framework ensuring transparency, contestability, fairness, and inclusivity.
This article examines the requirements for customs-related support of import shipments under conditions of sanctions. It identifies risk factors concerning shipment timelines, costs, and documentation. A procedure for evaluating the documentation associated with a completed shipment is formulated; the causes of discrepancies are categorized; and an analysis is provided of the measures taken by the service provider to address the root causes of these discrepancies.
Процессы диджитализации и медиатизации трансформируют медиапространство, изменяя методы создания и распространения контента, а также инфлюенсинга. Возникает необходимость введения новых терминов, обозначающих акторов медиасреды. Несмотря на рост количества публикаций по указанной проблематике, исследований, осмысляющих теоретическое наполнение и особенности использования понятий «инфлюенсер» и «виртуальный инфлюенсер» в условиях медиапространства недостаточно, что затрудняет их теоретическое разграничение и эмпирическое использование. Данная работа предлагает научно обоснованные дефиниции новых медиапонятий и их сравнительный анализ по онтологическим, коммуникативным и функциональным критериям. Исследование проводилось на основе анализа теоретических источников по теме, контент-анализа и лексико-семантического анализа 250 текстовых источников, опубликованных в средствах массовой информации и сетевых аналитических ресурсах (статьи, аналитические интервью, обзоры, аналитические комментарии) в период с января по июль 2025 г., описывающих деятельность инфлюенсеров и виртуальных инфлюенсеров. В ходе анализа были выявлены причины терминологической полисемии и влияние цифровизации на возникновение новых номинаций субъектов, в частности – цифровых персонажей, представляющих бренды. Особое внимание уделено феномену онтологического сближения человека и его цифрового двойника, отраженному в языке и практике терминоупотребления. В результате исследования сформулированы дефиниции понятий «инфлюенсер» и «виртуальный инфлюенсер», а также сопоставлены их конститутивные признаки. Обоснована необходимость дальнейшей систематизации понятийного аппарата и определены направления для будущих исследований в сфере виртуального инфлюенсинга и цифровых коммуникаций.
