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Big Data Analytics in Smart Tourism Destinations. A New Tool for Destination Management Organizations?

In: Smart Tourism as a Driver for Culture and Sustainability

Author

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  • Tomáš Gajdošík

    (Matej Bel University)

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.

Suggested Citation

  • Tomáš Gajdošík, 2019. "Big Data Analytics in Smart Tourism Destinations. A New Tool for Destination Management Organizations?," Springer Proceedings in Business and Economics, in: Vicky Katsoni & Marival Segarra-Oña (ed.), Smart Tourism as a Driver for Culture and Sustainability, chapter 0, pages 15-33, Springer.
    • Handle: RePEc:spr:prbchp:978-3-030-03910-3_2
    DOI: 10.1007/978-3-030-03910-3_2
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    More about this item

    Keywords

    Big data; Governance; Management; Tourism destination; Smart tourism;
    All these keywords.

    JEL classification:

    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism

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