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Forecast Of Using Neural Networks In The Tourism Sector


  • Miroslav Karahuta

    (University of Prešov)

  • Peter Gallo

    (University of Prešov)

  • Daniela Matušíková

    (University of Prešov)

  • Anna Šenková

    (University of Prešov)

  • Kristína Šambronská

    (Faculty of Management, Prešov University in Prešov)


The paper addresses the issue of management decision-making using artificial neural networks and their application in hotel management. Today, the development of tourism is of great importance and plays a very important role in the development of national economy. Balanced ranking and prediction model using financial and non-financial indicators with the application of artificial intelligence, allows us to reach a high level of effectivity and accuracy in evaluation of the financial and non-financial health of companies operating in this segment. This approach improves the manager’s ability to understand complex contexts and make better decisions for further development. It also brings new managerial and scientific point of view of an in-depth analysis of the performance of these facilities. It can help the development of tourism in terms of the application of modern management techniques built on scientific principles and thereby better integrate science and practice.

Suggested Citation

  • Miroslav Karahuta & Peter Gallo & Daniela Matušíková & Anna Šenková & Kristína Šambronská, 2017. "Forecast Of Using Neural Networks In The Tourism Sector," CBU International Conference Proceedings, ISE Research Institute, vol. 5(0), pages 218-223, September.
  • Handle: RePEc:aad:iseicj:v:5:y:2017:i:0:p:218-223
    DOI: 10.12955/cbup.v5.928

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    More about this item


    Prediction modelsfinancial health; neural networks; management; tourism;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • Z32 - Other Special Topics - - Tourism Economics - - - Tourism and Development


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