Development of information technology of correlation analysis of tourist demand

Authors

DOI:

https://doi.org/10.15587/2312-8372.2018.147613

Keywords:

information technology modeling unit, tourist demand, correlation analysis, programming language R

Abstract

The object of research is the process of automating information technology of the correlation analysis of tourist demand on the basis of a cognitive-statistical approach. One of the most problematic places is determination of the factors affecting tourism demand, so it is necessary to develop information technology of correlation analysis, which will allow to determine the factors that most affect tourism demand.

The paper substantiates the improvement of the method of correlation analysis of tourist demand is the calculation of the multiple correlation coefficient of tourist demand, a distinctive feature of which is to take into account both qualitative and quantitative parameters. The following factors are chosen for the analysis of tourist demand:

  • the average wage per person in the tourism industry;
  • tourism expenses;
  • the number of collective accommodation facilities;
  • the number of subjects of tourist activity;
  • the number of recreation;
  • release in basic prices and release by types of economic activity;
  • capital investment by region;
  • transport connection;
  • ecological situation;
  • infrastructure (subjective indicator).

A block of information technology for modeling and analysis is developed for the study of tourist demand which determines the correlation dependence between the factors influencing tourist demand. Information technology is developed in the R programming language, by the Shiny package, which enables the creation of interactive web applications and the simplicity of the developed technology for the average user.

The following factors affecting tourist demand are identified:

  • the number of collective accommodation facilities;
  • the number of subjects of tourist activity;
  • the number of recreation;
  • level of infrastructure based on subjective expertise.

As a result, based on the correlation analysis, a model of the process of formation of tourist demand on the basis of the cognitive-statistical method is built.

Thanks to this, it is possible to further develop the methodological foundations of the strategic planning of the development of subjects at the macro and micro levels, to develop regulatory, economic and socio-political mechanisms for the flexible development of tourism enterprises in certain regions based on qualitatively new principles.

Author Biography

Khrystyna Lipyanina, Ternopil National Economic University, 11, Lvivska str., Ternopil, Ukraine, 46009

Lecturer

Department of Economic Cybernetics and Informatics

References

  1. UNWTO Turism Highlights. Available at: https://www.e-unwto.org/doi/pdf/10.18111/9789284419876
  2. Derzhavna sluzhba statystyky Ukrainy. Available at: http://www.ukrstat.gov.ua/
  3. Dritsakis, N., Athanasiadis, S. (2008). An Econometric Model of Tourist Demand. Journal of Hospitality & Leisure Marketing, 7 (2), 39–49. doi: http://doi.org/10.1300/j150v07n02_03
  4. Garin-Munoz, T., Amaral, T. P. (2000). An econometric model for international tourism flows to Spain. Applied Economics Letters, 7 (8), 525–529. doi: http://doi.org/10.1080/13504850050033319
  5. Botti, L., Peypoch, N., Randriamboarison, R., Solonandrasana, B. (2007). An Econometric Model of Tourisn Demand in France. Tourismos: an International Multidisciplinary Journal of Tourism, 2 (1), 115–126.
  6. Witt, S. F., Martin, C. A. (1987). Econometric Models for Forecasting International Tourism Demand. Journal of Travel Research, 25 (3), 23–30. doi: http://doi.org/10.1177/004728758702500306
  7. Yang, Y., Wong, K. K. F. (2012). A Spatial Econometric Approach to Model Spillover Effects in Tourism Flows. Journal of Travel Research, 51 (6), 768–778. doi: http://doi.org/10.1177/0047287512437855
  8. Kalchenko, O. M. (2013). Otsinka vplyvu faktoriv rozvytku pidpryiemstv turystychnoi sfery. Naukovyi visnyk Chernihivskoho derzhavnoho instytutu ekonomiky i upravlinnia. Seriia: Ekonomika, 3, 94–101.
  9. Balashova, R., Ivchenko, L. (2011). Metodychni zasady analizu ta prohnozuvannia rynku turystychnykh posluh v Ukraini z vykorystanniam matematychnoho modeliuvannia. Ekonomika, 3 (110), 3–9.
  10. Beidyk, O. O., Novosad, N. O. (2012). Faktornyi analiz formuvannia potokiv viznoho turyzmu Ukrainy. Ukrainskyi heohrafichnyi zhurnal, 1, 44–49.
  11. Barna, M. Y., Myronov, Y. B. (2017). Econometric modelling of tourist flows dynamics. Scientific bulletin of Polissia, 1 (4 (12)), 165–170. doi: http://doi.org/10.25140/2410-9576-2017-1-4(12)-165-170
  12. Morokhovych, V. S. (2017). Ekonomiko-matematychne modeliuvannia turystychnykh potokiv zakarpatskoi oblasti. Naukovyi visnyk Uzhhorodskoho universytetu, 1, 143–146.
  13. Kuvaieva, V. I., Lipyanina, Kh. V., Boltonkov, V. O. (2018). Processing expert information in the context of collective assessment of a tourist infrastructure. Innovative Technologies and Scientific Solutions for Industries, 5 (3 (5)), 35–43. doi: http://doi.org/10.30837/2522-9818.2018.5.035

Published

2018-05-31

How to Cite

Lipyanina, K. (2018). Development of information technology of correlation analysis of tourist demand. Technology Audit and Production Reserves, 6(2(44), 16–21. https://doi.org/10.15587/2312-8372.2018.147613

Issue

Section

Information Technologies: Original Research