Data analysis and forecasting of tourism development in Ukraine

• Main Authors: Andrii Roskladka, Nataliia Roskladka, Oleksandr Dluhopolskyi, Ganna Kharlamova, Mehmet Kiziloglu
• Format: Article
• Language: English
• Published: LLC "CPC "Business Perspectives" 2018-12-01
• Series: Innovative Marketing
• Subjects: data analysis; forecasting; tourism; tourism development in Ukraine; tourism management; tourist flows
• Online Access: https://businessperspectives.org/images/pdf/applications/publishing/templates/article/assets/11317/IM_2018_04_Roskladka.pdf
• ISSN: 1814-2427; 1816-6326

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.