In the context of the implementation of the national project «Data Economy», the classic transactional model of digital platforms is showing signs of exhausting its extensive growth potential: user base growth is slowing, customer acquisition costs are rising, and bilateral network effects are stagnating. The relevance of this study is determined by the need to ensure technological sovereignty and sustainable growth of the platform sector of the economy. The goal of the study is to identify and systematize the coordination mechanisms that enable the transformation of transactional platforms into innovative ecosystems based on value co-creation. The object of the study is digital platforms and business ecosystems, and the subject is the mechanisms for participant coordination and value co-creation. The methodology combines a conceptual synthesis of theories of platform economics, ecosystem management, and service-dominant logic with a case study of the practices of the largest Russian B2C ecosystems based on open sources. The author proposes a platform evolution matrix reflecting the transition from directive management of closed resources to the orchestration of open architecture, and systematizes three groups of coordination mechanisms: institutional, architectural, and informational. Predictive and generative AI algorithms, combined with compositional network effects, are shown to form the core of an innovation ecosystem. A two-block metric system has been developed demonstrating the economic efficiency of the transition: service integration and cross-use of data reduces marginal user acquisition costs by 30-40% and increase the LTV/CAC ratio by 1.5-2 times. The practical significance lies in the development of a toolkit for platform orchestrators in developing institutional and technological rules that incentivize complementors to engage in collaborative innovation. Future research opportunities lie in adapting the matrix to the conditions of industrial B2B ecosystems and quantitatively verifying the proposed metrics.
The paper substantiates a conceptual approach to building a unified digital platform for state administration of preferential regimes (advanced development territories, special economic zones, the Vladivostok free port) in Russian regions. The relevance of the study stems from persistent information fragmentation among existing support systems and uneven outcomes across regimes: by the end of 2025 the aggregate effectiveness of Russian SEZs reached 94% (up from 90% a year earlier), while regional audit bodies show that individual advanced development territories fall well short of investment-agreement targets – residents of the Zarinsk and Novoaltaysk territories in the Altai Krai created only 82% and 54% of planned jobs, respectively, over seven years. This gap calls for continuous, rather than retrospective, digital verification at the level of a single resident. The study draws on platform-economy theory (multi-sided markets, network effects) and treats the regional administration system for preferential regimes as an institutional platform connecting public authorities, residents and development institutions. The paper systematises existing information systems supporting preferential regimes, proposes a five-layer conceptual architecture for a regional digital platform, and substantiates a methodology for applying machine-learning algorithms to early risk detection of inefficient tax-benefit use. Using verifiable official data, the study performs a set of calculations: target values for Altai Krai ADT residents are reverse-engineered from published completion rates (aggregate completion rate ≈69.3%); for the Novgorod SEZ, the lag between investment execution and job creation is estimated at ≈24 percentage points; and a four-year series (2022-2025) shows the aggregate federal SEZ effectiveness indicator fluctuating around one level (mean 92.5%, SD ≈1.6 p.p.) rather than trending upward. These calculations underpin an applied early-warning threshold indicator. The findings may be used by authorities to improve the management of preferential regimes.
This article examines current issues of integrating modern digital platforms and technologies, including artificial intelligence, into the public administration system. The prospects of using these technologies in the activities of customs authorities within the framework of the Development Strategy of the Customs service of the Russian Federation until 2030 are analyzed. The authors have undertaken a comprehensive research of the legal, technical, and ethical issues involved in the use of artificial intelligence algorithms and technologies. The theoretical and historical aspects of the development of these technologies are examined, with particular attention paid to the definition and nature of artificial intelligence. The main challenges associated with using these technologies in public administration are identified and discussed. Particular attention is paid to the openness and transparency of the use of artificial intelligence algorithms for understanding and monitoring management decisions. Risk levels for the application of these technologies are assessed. The legal and organizational issues of creating and applying new digital platforms and technologies to ensure high-quality customs administration, as well as creating favorable conditions for participants in foreign economic activity, are investigated. It is noted that building transparent and operational interaction between customs authorities and subjects of foreign trade activity helps to reduce costs and provides a cumulative socio-economic effect for the state and society. A promising area of transformation of the customs service is the implementation of the concept of «intelligent customs». Its implementation necessitates the formation of enhanced standards for information and cyber security, adapted to the specifics of the operation of modern digital platforms and artificial intelligence technologies. At the same time, the regulatory and legal support of these standards should ensure legal certainty and consistency of regulatory requirements in the field under consideration. Legislative regulation in this area should also consider ethical and appropriate considerations to prevent adverse consequences. Comprehensive collaboration between specialists and researchers from various fields in the development and subsequent technical and legal support for the effective operation of new artificial intelligence-based technologies and algorithms is advisable.
In the context of the transformation of the labor market caused by the digitalization of the economy and the spread of platform employment, the study of the gender aspects of the population's involvement in new forms of labor relations has both scientific and applied significance. The paper presents the results of an analysis of the gender structure of platform employment in the regions of the Central Federal District for the period of 2022-2024. The empirical basis of the study consists of data from the Federal State Statistics Service and the Unified Interdepartmental Information and Statistical System, which were aggregated into a panel structure for 18 regions of the Central Federal District. The methodological apparatus includes a descriptive analysis of the dynamics of the number of performers by gender groups, regression modeling to assess the impact of platform employment on the value of the gross regional product, as well as the calculation of the coefficients of determination with testing of the statistical significance of the constructed models using Fisher's F-test and Student's t-test. The study found that, against the backdrop of a general decrease in the number of employees in the platform segment by 33.1%, the rate of decline in the female contingent (41.5%) significantly exceeds the same indicator for men (25.2%). Regional analysis revealed a hyper-concentration of platform employment in Moscow and the Moscow Region, with deep interregional disparities. In some regions, the number of performers decreased by more than 80%, while other regions showed an increase, indicating the formation of new local centers of platform activity. Regression analysis confirmed the existence of a stable statistical relationship between the number of people employed on platforms and the value of the gross regional product for both gender groups (determination coefficients ranging from 0.56 to 0.93, with statistical significance of the models). At the same time, the models for the female group have a higher explanatory capacity with increasing dynamics (from 0.76 in 2022 to 0.93 in 2024), and the increase in the regression coefficients indicates an increase in the sensitivity of GRP to changes in the number of platform performers, especially in the female group. The practical significance of the work lies in substantiating the need for differentiated regional employment policies that take into account gender asymmetry and the vulnerability of the female population to structural shifts in the platform economy. The research results can be used in the development of professional retraining programs and the adaptation of platform employment mechanisms to the changing structure of the economy.
The relevance of the study is determined by the changing conditions for the growth of digital platforms: as the user base expands, simply increasing scale ceases to be a sufficient explanation for sustainable value creation. The aim of the work is to systematize the mechanisms of value creation by digital platforms as they develop and to formulate a conceptual framework for the transition from network scaling to ecosystem efficiency. To achieve this goal, studies of network effects and two sided markets, ecosystem architecture and complementarity, platform governance, market power, and institutional regulation are compared. The study is of a theoretical and analytical nature; systemic and comparative analysis and conceptual synthesis are applied. It has been shown that network effects retain their fundamental importance, but their relative role changes: in the early stages, they ensure the formation of a critical mass and accelerate growth, whereas as the platform becomes more complex, the quality of interdependencies, complementarity, and ecosystem architecture management become central. A conceptual framework for systematizing the mechanisms of value creation in digital platforms has been proposed, including four states of economic logic: network formation, scaling, ecosystem integration, and selective coordination. It has been shown that as the platform develops, not only the value creation mechanism changes, but also the associated limiting factor: from the need to form a sufficient set of participants to ensuring the quality of interdependencies and their coordinated management. The Russian specifics are interpreted as a set of institutional conditions that influence the speed and limitations of the transition between stages. The practical significance of the study lies in the possibility of using the proposed framework to analyze the development of digital platforms and refine approaches to assessing their maturity. The prospects for further research are related to the empirical validation of the proposed framework and the development of measurable indicators for the identified maturity dimensions based on data from Russian digital platforms.
