Abstract
The article presents approaches to clustering of recreation and tourism facilities. The author sets the problem of sustainable development of rural areas which do not have agricultural specialization. Such territories include areas with the tourist and recreational potential. In these areas, agriculture is not developed due to its natural peculiarities, though they belong to rural areas. There, the standard of living is lower than in the areas with developed agricultural production. Rural areas with the tourist and recreational potential, as a rule, have land resources related to specially protected natural areas or are in close proximity to them which complicates the management process as applying generally accepted management methods to such specific areas does not give the desired effect. The author proposes to apply the elements of cluster policy in order to improve the efficiency of land management in such rural areas. The researcher analyzes Mostovsky district of Krasnodar Krai as the most striking example of a rural area with the tourist and recreational specialization. The creation of territorial tourist and recreational clusters was carried out in several steps. The property items were selected with the use of expert analysis. They are land plots for recreation and tourism facilities that meet the requirements. Three large groups of sites were created to simplify data processing. Further, the enlarged groups were divided into 12 sectors by the expert and graphical methods. This method is very approximate and does not give serious results. The author proposes to apply the mathematical methods for more accurate clustering. The author uses the Euclidean distance method and the “nested spheres method” resulting in the formation of three territorial tourism and recreation clusters of the district. The article describes the main directions of using the results of the suggested clustering methodology which will be the basis for making optimal management decisions to improve the land use efficiency in rural areas.
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