Abstract
In the last years, the amount of data and the possibilities of its analysis have risen rapidly. Leading retail businesses are able to work with complex sources of data, embrace intelligence tools and generate better outcomes. Tourism industry is becoming smarter; however, because of its fragmented nature and small size of tourism businesses, it lags behind the other industries. Today’s destination management organizations (DMOs) are struggling with several challenges and have difficulties in adapting to new market conditions. Within the smart tourism concept, the big data analytics is seemed to be a promising tool for overcoming the challenges. Therefore, the aim of the paper is to find out the possibilities of overcoming challenges of today’s DMOs based on the analysis of current state and best practices of big data analytics in tourism destinations. The analysis is based on multiple case studies, with the main focus on Central Europe. The paper presents a conceptual view on big data analytics and concludes that the application of big data analytics allows DMOs to better define destination boundaries, understand the needs of today’s tourists, effectively manage destination stakeholders and be more competitive and sustainable.
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The research was supported by the research project VEGA 1/0809/17 Reengineering of destination management organizations and good destination governance conformed to principles of sustainable development.
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Gajdošík, T. (2019). Big Data Analytics in Smart Tourism Destinations. A New Tool for Destination Management Organizations?. In: Katsoni, V., Segarra-Oña, M. (eds) Smart Tourism as a Driver for Culture and Sustainability. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-03910-3_2
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