Connectivity as a structural characteristic of the Russian spatial economic system: An application of complex network theory

This article examines the network architecture of the national economic system in order to develop and test an integrated approach to measuring regional connectivity. The relevance of the study is driven by the increasing role of domestic interregional linkages under conditions of geo-economic transformation, sanctions pressure, and the need to enhance the resilience of Russia’s spatial economic organization. The methodological framework combines spatial analysis, composite index construction, logarithmic rank-size distribution, cartographic visualization, and a network-based interpretation of regional structure. The empirical basis of the study covers data for 85 constituent entities of the Russian Federation. At the first stage, an index of economic connectivity is calculated by aggregating the production, market, transport-mobility, and network-innovation characteristics of regions. At the second stage, a matrix of interregional distances is constructed for administrative centers of the constituent entities of the Russian Federation. At the third stage, the two dimensions are combined into a composite index that makes it possible to evaluate a region’s position within the country’s spatial economic system. The findings show that the spatial organization of the Russian economy is characterized by a pronounced hierarchical structure and persistent center—periphery polarization. In comparison with the United States and China, the Russian model displays a higher degree of monocentricity, lower infrastructural redundancy, and a trunk-line organization of its eastern segment. The proposed index can be used as a public policy tool for diagnosing spatial disproportions, prioritizing infrastructure and logistics investment, and reducing vulnerability to sanctions. The scholarly contribution of the study lies in integrating the economic and spatial dimensions of connectivity into a single analytical model and in interpreting Russia’s regional structure as a multilayered hierarchical network.