Thinking beyond models: The propensity to fly of four Central European countries

Abstract

This paper proposes a new enhanced propensity to fly model based on multilinear regression analysis, which is used to analyse the air transport market potential in four central European countries. Eurostat database data from 31 European states in years 2009–2019 were used with an emphasis on data homogeneity and robustness. To evaluate the quality of the regression model, the influence of seven variables was considered in total on propensity to fly – GDP, geographical characteristics of states (3 variables), magnitude of tourism, the effect of economically active people of working age, and education. The multi-regression analysis findings show differences between the theoretical and actual values in the examined states. In all four investigated states, the theoretical values predicted by the regression model are higher than the actual numbers. In the Czech Republic and Slovakia, these differences are substantially larger than in the other two countries. This may indicate that a proportion of air passengers from the Czech Republic and Slovakia choose airports in other countries for their travel. The article discusses the causes and consequences of the mentioned differences. The proposed enhanced propensity to fly method can help decision-makers assess the scale of ‘air passenger leakage’ from the four countries of the Central Europe to airports abroad. It could serve as one of the tools to inform the design and/or review of air transport policies. However, while the model is statistically strong and reliable, it remains a ‘crude tool’ and should be used in conjunction with other data by air transport planners.