IDEAS home Printed from https://ideas.repec.org/a/vrs/cjotou/v8y2019i2p85-102n2.html
   My bibliography  Save this article

Big Data: a Source of Mobility Behaviour and a Strategic Tool for Destination Management

Author

Listed:
  • Emmer Filip

    (Institute of Tourism, Faculty of Economics and Administration, Masaryk University, Brno, Czech Republic)

  • Holešinská Andrea

    (Institute of Tourism, Faculty of Economics and Administration, Masaryk University, Brno, Czech Republic)

Abstract

The abundant use of the Internet and mobile technologies while traveling leaves a digital footprint in the form of big data that can be tracked. Big data bring information about spatial visitor behaviour that is valuable for strategic destination management. Big data enrich not only scientific fields (e. g. management, marketing, or geography) with their knowledge, but also represent the invention of new tools for their actual processing. Generally, big data are considered as a strategic tool enhancing the competitiveness of a destination. The paper presents the basic characteristics of big data and reviews research focused on big data in tourism. Moreover, it identifies its potential for tourism from both the theoretical and methodological point of view. The final part deals with current trends in using the big data in tourism and its application in destination management. The future trends of big data in the context of destination management are implied as well.

Suggested Citation

  • Emmer Filip & Holešinská Andrea, 2019. "Big Data: a Source of Mobility Behaviour and a Strategic Tool for Destination Management," Czech Journal of Tourism, Sciendo, vol. 8(2), pages 85-102, December.
    • Handle: RePEc:vrs:cjotou:v:8:y:2019:i:2:p:85-102:n:2
    DOI: 10.2478/cjot-2019-0006
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/cjot-2019-0006
    Download Restriction: no
    File URL: https://libkey.io/10.2478/cjot-2019-0006?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Keywords

    tourism; big data; mobility behaviour; destination management;
    All these keywords.

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
    • Z32 - Other Special Topics - - Tourism Economics - - - Tourism and Development

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vrs:cjotou:v:8:y:2019:i:2:p:85-102:n:2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.