In the context of external shocks, socio-economic coherence of an industrial region reflects its ability to function successfully. Many researchers examine economic space, focusing on interaction between entities (including infrastructure) while ignoring territorial boundaries. However, it is necessary to consider a region’s endogenous core, whose historically connected elements generate evolutionary changes under the influence of external factors. This study develops tools to assess regional infrastructure coherence, taking into account the endogenous determinants of its socio-economic development. The research methodology includes: a comparison of absolute and relative territorial characteristics and infrastructure development parameters; statistical, economic and mathematical methods for determining and evaluating the resulting indicators; an expert assessment of the infrastructure potential; a matrix method for identifying the depth of infrastructure gaps. An analysis of Sverdlovsk oblast and neighbouring regions revealed infrastructure gaps of the first level of depth (insignificant, significant, stably significant), violating the integrity of the regional core, as well as gaps of the second level of depth (forming, potentially forming), requiring serious transformations of the core elements. The con ducted research determined the infrastructure coherence characteristics of the regional core. Thus, the most favourable situation is in Sverdlovsk oblast, whose core has strong integrity. The most unfavourable situation is observed in Perm Krai and Khanty- Mansi Autonomous Okrug. Perm Krai’s core is characterised by minor gaps of the first level of depth and potential second level gaps. In Khanty-Mansi Autonomous Okrug, significant first level gaps are already established, while second level gaps are still forming. This situation occurred due to the industrial specificity of these regions, as well as the discrepancy between high economic activity (increasing the demand for transport services) and infrastructure development. Further research will focus on the ways to improve the regional connectivity at the intra- and inter-regional levels.

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While the problem of digital transformation of the economy requires digital maturity of com-panies, the level, readiness and capabilities of individual industries, sectors and enterprises for such a transformation differ. The events of 2020 and emerging social and economic restrictions have increased the relevance of digital transformation, leading to the transition to new services, platforms, business mod-els, as well as to the development of digital systems. We believe that the regional potential for acceler-ated digitalisation is not fully realised in the current and projected periods. The study aims to substantiate and develop a new approach to assessing the readiness of regional transport systems for digital transfor-mation and identifying regions in which the potential of digital development is not fully exploited. Several approaches were used in the research, such as the index method, statistical methods (including standard deviation), the principal component method for selecting and evaluating indicators to create a composite index, etc. The study utilised data from the Federal State Statistics Service and its territorial departments, the Ministry of Digital Development of the Russian Federation, the Unified Interdepartmental Statistical Information System (EMISS), departmental statistics (JSC Russian Railways, the Federal Air Transport Agency (Rosaviatsia), Federal Road Transport Agency (Rosavtodor), etc.) for 2020. In particular, the proposed methodological approach was tested in the industrially developed regions of the Russian Federation. At the first stage of the assessment, industrialised regions were divided into 5 groups according to the read-iness of transport systems for digital transformation (extremely low, low, moderate, high, extremely high). The group with the lowest values of indicators included Vologda, Volgograd, and Irkutsk oblasts. A low level of readiness was recorded in Novgorod, Kaluga and Omsk oblasts and Krasnoyarsk krai. The largest group of regions with a moderate readiness index included seven regions: Vladimir, Yaroslavl, Leningrad, Rostov, Samara oblasts, Perm krai and the Republic of Bashkortostan. Lipetsk, Murmansk and Chelyabinsk oblasts are characterised by high readiness, while Nizhny Novgorod, Sverdlovsk and Moscow oblasts have an ex-tremely high level of readiness. At the second stage, the regions were distributed according to the devia-tion of the level of digitalisation from the level of readiness of the transport system for digital transforma-tion. As a result, the study revealed the potential of digital development of transport systems in industri-alised regions. The obtained findings can be used by state and local authorities to establish directions for national, regional and municipal policies to accelerate the digital transformation of the transport system and improve the efficiency of industry regulation.