Home – Home – Jornals – Region: Economics and Sociology 2024 number 2

Defining economic specializations at the level of administrative-territorial units in Russia’s major urban agglomerations is a pressing concern for regional scientific research. This stems not only from the concentrated socioeconomic activities and ongoing economic transformations within these areas but also from the need to pinpoint the types of economic activities (specializations) that will foster further growth and development. However, limited access to statistical data complicates research efforts focused on determining specializations at the municipal district level. To address this challenge and calculate the specialization coefficient, we utilize the “number of business entities belonging to legal entities" indicator per type of economic activity, sourced from the SPARK-Interfax information group’s regional breakdown of Russian Federation constituent entities. The St. Petersburg agglomeration includes 18 districts of St. Petersburg and 7 districts of Leningrad Oblast (Vsevolozhsky, Kirovsky, Tosnensky, Gatchinsky, Volosovsky, Lomonosovsky, and Sosnovoborsky urban districts), each with administrative centers located within ninety minutes of driving distance from the core’s central point (Palace Square, St. Petersburg). Specialization coefficient calculations were conducted for each district of the St. Petersburg agglomeration, revealing distinct specializing types of economic activity. To facilitate analysis, the districts were conventionally grouped based on historical and geographical administrative-territorial principles, resulting in four categories: the historical center, the middle zone, the suburban zone, and the peripheral zone. This grouping allowed for an examination of specializations aligned with spatial and functional patterns typical of urban agglomeration development. The findings from this research hold practical implications for regional and local government bodies in formulating spatial development strategies and documents. They can also be helpful to business entities seeking optimal organization (enterprise) locations.