Structure of port cargo turnover as a factor of industry and spatial development of regions

• Dmitry V. Martynov

  Dmitry V. Martynov. Vladivostok State University. Vladivostok. Russia

• Красько Андрей Александрович

  Andrey A. Krasko. Vladivostok State University. Vladivostok. Russia

The article is devoted to the development and testing of a method for assessing the impact of port cargo traffic structure on the socio-economic development of Russian regions taking into account the requests of key stakeholders – regional authorities and society. The study covers 23 Russian regions with 55 seaports in operation and relies on data from 2015 to 2023. Gradient boosting and Shapley methods are
used for analysis, which allow identifying nonlinear dependencies and synergistic effects between types of transshipped goods and employment indicators, contributions of related industries to gross regional product, as well as land use levels. Seaports are considered crucial elements of production-logistics systems that indirectly influence energy sectors, information and communication fields, manufacturing industry, transportation and storage, as well as trade. The results obtained by the authors demonstrate that the cargo turnover structure is a significant factor shaping the socio-economic development of regions, related industries, and their spatial evolution. In regions with low port activity, this effect is local and fragmented. In regions with medium-level activity, clear dependence of specific industries on certain types of freight flows is identified. In larger port regions, an integrated logistics system emerges where different types of cargo enhance the multiplicative effect of port infrastructure. The developed methodology allows classifying cargo types based on their indirect influence and can be applied for strategic territorial management considering port specialization, improving efficiency of regional planning, and enhancing sustainability of socioeconomic systems.
Keywords: sea ports, cargo traffic structure, regional development, GRP, budget revenues, cluster analysis.