Abstract
The article presents an applied model for the digital transformation of domestic tourism in Ukraine. The proposed framework takes into account spatial characteristics, technological capabilities, and the organizational and economic conditions of the industry. The main objective of the study is to develop mechanisms for integrating intelligent technologies into programs for restoring the national tourism product. The methodological basis relies on geospatial mapping and integrated assessment of regional potential. In addition, matrix and scenario analysis, as well as structural modeling of digital infrastructure, were employed. The empirical basis includes official data from the State Agency for Tourism Development of Ukraine and analytical reports of the National Tourism Organization. Based on the obtained indicators, geospatial zoning was carried out. Territories capable of receiving domestic tourists in 2026 were identified, and regions with the highest level of integrated readiness were determined. A matrix for the priority implementation of intelligent technologies was developed, making it possible to forecast the organizational and economic consequences of digitalization. An architectural model of a national intelligent platform was proposed. The system integrates tools for personalized route planning, electronic booking, route safety verification, and geonavigation. An important component is the analysis of large data sets. The architecture also предусматривает interaction with government digital services. A conceptual model of an intelligent tourism destination was developed. It is based on Internet of Things networks, artificial intelligence algorithms, and virtual and augmented reality technologies. An organizational and economic mechanism for implementing digital innovations was proposed. The obtained results have practical value. Public authorities and local governments can apply the proposed solutions to accelerate the recovery of domestic tourism. Tourism enterprises and investors will be able to use the findings to increase the economic returns of territorial communities.
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