Abstract
It is determined that the cluster approach is a necessary tool for creating the spatial development of the world's tourist regions, and the focus on the formation of competitive advantages of tourist clusters will lead to the production of creative innovative tourism products. The study examines the competitiveness index according to a set of indicators, which are grouped into four subindexes – environmental friendliness, public policy and the creation of favorable conditions, infrastructure, natural and cultural resources. A cluster analysis of the factors that create the regional potential of clusters in the tourism industry of the European space has been carried out. The features of the competitive environment in the tourism services market and its impact on the competitiveness of economic entities of the tourism industry are considered. The number and composition of tourism clusters in the EU member states is demonstrated. With the help of cluster analysis and audit, more competitive tourist clusters of the European space have been identified. A correlation analysis was carried out between the general competitiveness index of the EU member states in the field of travel and tourism and its subindexes. The results of this analysis confirm the existence of a direct relationship between these components. In order to characterize tourist clusters and determine the degree of development of their tourism potential, the process of combining clusters by the Ward method and the K-means method was used, which made it possible to determine various levels of competitiveness of the travel and tourism sector. The forecasting tool is applied by the method of extrapolation of market trends and indicators. The forecast efficiency of the development of the regional potential of tourist clusters is calculated using the growth rates of the final product. As the main indicators of forecasting, such indicators as the growth rate of national income, the rate of dynamics of visits to tourist sites and recreation in the country, the parameter of the degree of labor intensity, labor productivity growth, the parameter of the degree of capital intensity, the growth of capital return are selected.
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