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Forecasting of the Volume of the SPA and Wellness Tourism Receipts in the South-West Bulgaria

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The present paper regards the application of some forecasting methods in regards to the SPA and Wellness tourism in South-West Bulgaria such as: the linear trend forecasting, the double exponential forecasting (the Holt’s method), the ARIMA method, the naïve method and the indexed naïve method. Specially designed model for estimation of the weight coefficient needed for determining the size of the sector of the SPA and Wellness tourism in the time series of the available data and in the forecast values is being presented. Future and past predictions have been achieved based on statistical records of a time series of 18-year periods. The present paper regards also several major problems in the application of the univariate forecasting methods for the purpose of the long-run forecasting of the volume of the tourism receives and especially the ones in the sub sector of the SPA and Wellness tourism in SouthWest Bulgaria. These problems include as: (i) the problem of finding of a suitable general indicator; (ii) Determining the time series pattern, or the so-called “forecast profile” and selecting and using of suitable forecasting techniques; (iii) Calculating of short-run and long-run forecasts; (iv) comparing of the results of the forecast techniques on the basis of the errors in the forecasts;(v) Estimating the size of the SPA and Wellness tourism in South-West Bulgaria in certain terms, so that the forecast(s) of the above-mentioned general indicator could be particularized especially for regarded sub sector and region. The results from the different forecasting methods and techniques are being presented and conclusions are drawn on the reliability of the achieved forecasts.

Suggested Citation

  • Dimitrov, Preslav & Daleva, Diana & Stoyanova, Milena, 2017. "Forecasting of the Volume of the SPA and Wellness Tourism Receipts in the South-West Bulgaria," Journal of Tourism, Sustainability and Well-being, Cinturs - Research Centre for Tourism, Sustainability and Well-being, University of Algarve, vol. 5(2), pages 83-99.
    • Handle: RePEc:ris:jspord:0933
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    1. Taylor, James W., 2003. "Exponential smoothing with a damped multiplicative trend," International Journal of Forecasting, Elsevier, vol. 19(4), pages 715-725.
    2. Tashman, Leonard J. & Kruk, Joshua M., 1996. "The use of protocols to select exponential smoothing procedures: A reconsideration of forecasting competitions," International Journal of Forecasting, Elsevier, vol. 12(2), pages 235-253, June.
    3. Everette S. Gardner, Jr. & Ed. Mckenzie, 1985. "Forecasting Trends in Time Series," Management Science, INFORMS, vol. 31(10), pages 1237-1246, October.
    4. Filipova, Milena, 2010. "Peculiarities of project planning in tourism," Perspectives of Innovations, Economics and Business (PIEB), Prague Development Center (PRADEC), vol. 4(1), pages 1-3, February.
    5. Milena Filipova, 2010. "Peculiarities Of Project Planning In Tourism," Perspectives of Innovation in Economics and Business (PIEB), Prague Development Center, vol. 4(1), pages 57-59, February.
    6. Williams, Dan W. & Miller, Don, 1999. "Level-adjusted exponential smoothing for modeling planned discontinuities1," International Journal of Forecasting, Elsevier, vol. 15(3), pages 273-289, July.
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    Cited by:

    1. Avgustin Milanov, 2020. "Forecasting Of Some Key Indicators Of The Rfi And Rfp Processes Of The Bulgarian Mobile Telecommunication Operators," Economics & Law, Faculty of Economics, SOUTH-WEST UNIVERSITY "NEOFIT RILSKI", BLAGOEVGRAD, vol. 2(2), pages 62-70.

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    More about this item

    Keywords

    SPA and Wellness Tourism; Exponential Forecasting; Economic Cycles; SouthWest Bulgaria;
    All these keywords.

    JEL classification:

    • Z32 - Other Special Topics - - Tourism Economics - - - Tourism and Development
    • Z33 - Other Special Topics - - Tourism Economics - - - Marketing and Finance

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