A Digital Platform as a Tool for State Administration, Monitoring and Effectiveness Assessment of Preferential Regimes in Russian Regions

Abstract

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.