DIGITAL TECHNOLOGIES IN THE ORGANIZATION OF TOURIST TRIPS
Abstract
Relevance of the research is determined by the rapid digital transformation of the tourism industry, which reshapes management structures, stakeholder interaction, and the organization of travel. The introduction of geoinformation systems, online platforms, mobile applications, and artificial intelligence establishes preconditions for shifting from traditional administrative models toward integrated, data-driven governance based on predictive analytics. However, ongoing digitalization remains fragmented, hindering the efficient use of natural, cultural, and logistical resources. The purpose of the article is to clarify the theoretical and practical foundations for applying digital technologies in organizing tourist trips and to develop approaches for improving the efficiency of route planning, resource management, and transport services in the context of tourism’s digital transformation. Research methodology is based on a system-analytic approach combining methods of geoinformation analysis, comparative evaluation, and structural-functional generalization. Research results. Current trends in tourism digitalization have been examined, and a correlation between the level of technological integration and service quality has been established. The use of GIS tools, big-data analytics, and mobile platforms has been shown to enable dynamic route formation, optimization of transport flows, and higher personalization of tourist experiences. It has been demonstrated that an effective digital ecosystem requires data interoperability, open APIs, cognitive analytics, and automated monitoring of service quality. It has been established that digitalization acts as a key driver of improved service quality, managerial transparency, and competitiveness of destinations. Major barriers were identified-fragmented legislation, technical incompatibility of systems, and insufficient coordination between public and private sectors. The necessity of transitioning toward data-driven governance and predictive analytics in tourism management has been substantiated.
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