Clustering of the regions of the Russian Federation according to socio-economic indicators of the development of the tourism industry

In the current changing conditions, segmentation of tourist territories in Russia can help identify potential breakthrough markets. Timely identification of new trends from a huge amount of data plays an important role in business processes and decision-making. Data mining methods help to overcome this lack of knowledge. The purpose of the study is to divide the regions of the Russian Federation into categories based on the available official statistical data . To achieve this goal, two interrelated tasks were supposed to be solved. - Clustering of Russian regions based on available statistical data on their development in the field of tourism - Construction of a model interpreting the results obtained to explain the partitioning into clusters. Such a model will help to form the main development goals for lagging regions to pull them up to the level of the “locomotives” of the industry. These tasks were solved using data mining methods. The individual groups of regions described in the study can help decision makers better understand the tourism sector in the region from the point of view of its profitability and, accordingly, adopt appropriate strategies for the development of regions depending on its current state. Further research suggests the formation of a general model of digital transformation of the tourism sector, depending on the specifics of the region.