Data analysis and forecasting of tourism development in Ukraine


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The article contains a thorough study of tourist flows in Ukraine during the last 18 years. The tendencies of the development of international tourism during the last 20 years and their influence on the development of tourism in Ukraine have been explored. Particular attention is paid to the analysis of inbound tourist flows. The negative dynamics of tourist arrivals in Ukraine led to the construction of a forecast model for the development of this component of tourism activity with the aim of an objective assessment of future tourist arrivals and the adoption of effective management decisions on improving the situation of tourism in Ukraine. Tourist destinations today are rigorously competing for consumer interest in tourism products. In view of this, tourist facilities operating in the tourist market place particular emphasis on the elements of tourism marketing (product, price, distribution, advertising, human capital, actual data, processes).
Modern forecasting systems and methods have been used to build a forecast of tourism development in Ukraine and, in particular, arrivals of foreign tourists to Ukraine. An analytical forecasting model was built by the system of CurveExpert in the form of a polynomial function, analytical forecasting models were built by the system of computer algebra Maple in the form of piecewise linear and piecewise polynomial functions. Numerical prediction models in the MathCAD system using different types of spline-interpolation and predictive functions have been constructed. A comparative analysis of the results of forecasting in different systems was carried out. The results of the comparative analysis give confidence in the development of inbound tourism in Ukraine.

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    • Figure 1. Tourist flows of Ukraine, 2000–2017
    • Figure 2. Building of forecast model by CurveExpert
    • Figure 3. High rank model – Gaussian Model and information about it
    • Figure 4. Visualization of forecasting models by Maple
    • Figure 5. Building the forecasting models by spline interpolation in MathCAD
    • Figure 6. Building the forecasting models by predict function in MathCAD
    • Figure A1. Creating the matrices of data in Maple
    • Figure A2. Function description of linear spline
    • Figure A3. Function description of quadratic spline
    • Figure A4. Function description of cubic spline
    • Figure A5. Creating the matrices of data in MathCAD
    • Table 1. International tourist arrivals, 1990–2017 (million)
    • Table 2. International tourism receipts, 1990–2017 (billion US dollars)
    • Table 3. TOP-30 country by indicators of tourist arrivals, 2000–2017
    • Table 4. Indicators of tourist arrivals in Ukraine, 2000–2017
    • Table 5. Comparative analysis of forecasting results