EVALUATING INBOUND TOURISM TRENDS THROUGH LINEAR REGRESSION ANALYSIS

Abstract

The dynamics of tourist flows and forecasts changes in demand using linear regression analysis have been considered in the paper. The period from 2011 to 2022 was taken as a basis. The analysis covers 18 countries that were selected both in terms of traditional popularity among tourists and in terms of growth in interest in lesser-known destinations. The R software environment and the tidyverse, dplyr, ggplot2 and gt libraries were used to process the data, which ensured efficient information processing, graphing and classification of countries by trends. The data was downloaded in CSV format, pre-processed and checked for missing values. Only records with non-zero values for the number of tourists were taken into account for the analysis. Additional variables were also created to classify countries by trends. The linear regression method allows determining the direction and intensity of changes in the number of tourists in each country. The slope coefficient shows the growth, stability or decline in tourist flows. Based on the quartile distribution, categories A, B, C and D were determined, reflecting the level of tourism development and the rate of its growth or decline. The results of the analysis show that due to the significant growth of various types of tourism in rapidly developing countries, most European countries are experiencing a decline in tourist flows, with the greatest losses observed in countries with high dependence on international tourism or geopolitical problems. At the same time, some countries, such as Ireland and Greece, are demonstrating positive trends, indicating successful practices in attracting tourists and opportunities for further research. The results obtained make it possible to identify promising regions for the development of tourism infrastructure and investment, optimise the use of natural resources and reduce the negative impact of tourism on the environment. The article demonstrates that the use of linear regression methods is an effective tool for forecasting demand, planning tourism and supporting the sustainable development of tourist regions, which is important for government agencies, businesses and tourism service operators.