Destination-level challenges and opportunities of data-driven smart tourism in Hungary

Abstract

This study examines the data maturity of Hungarian tourism destinations in the context of smart tourism and data-driven decision-making. Data-driven operations enable destinations to use resources more efficiently, enhance competitiveness, and respond proactively to changing market conditions; however, the level of data utilization varies significantly across destinations. The research is based on a nationwide quota-based questionnaire survey covering 100 domestic tourism destinations that register at least 50,000 guest nights annually, ensuring proportional representation in terms of visitor traffic characteristics and geographical distribution. The analysis explores the extent to which destinations use data in strategic planning and tourism development, the types of indicators they rely on, and the prevalence of advanced practices such as real-time analytics and big data solutions. The results show that 59% of destinations incorporate data into the strategy-making process, yet only 12% follow a fully data-driven approach aligned with strategic needs. Quantitative indicators dominate, while qualitative metrics related to visitor satisfaction, community well-being, and sustainability remain underutilized. Real-time data use is rare, big data applications are still at an early stage, and data-sharing practices are inconsistent. The study highlights the need to strengthen digital competencies, institutional cooperation, and analytical capacities in order to support the development of sustainable and competitive smart tourism ecosystems.