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.

中文翻译：

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超越模型的思考：四个中欧国家的飞行倾向


本文提出了一种基于多线性回归分析的新型增强型飞行倾向模型，用于分析四个中欧国家的航空运输市场潜力。使用了 2009 年至 2019 年来自 31 个欧洲国家的 Eurostat 数据库数据，强调数据的同质性和稳健性。为了评估回归模型的质量，总共考虑了七个变量对飞行倾向的影响——GDP、各州的地理特征（3 个变量）、旅游规模、工作年龄经济活动人群的影响和教育。多元回归分析结果显示所检查状态下的理论值和实际值之间存在差异。在所有四种研究的状态中，回归模型预测的理论值都高于实际数字。在捷克共和国和斯洛伐克，这些差异比其他两个国家要大得多。这可能表明来自捷克共和国和斯洛伐克的一部分航空乘客选择其他国家/地区的机场进行旅行。本文讨论了上述差异的原因和后果。拟议的增强型飞行倾向方法可以帮助决策者评估从中欧四个国家到国外机场的“航空旅客泄漏”规模。它可以作为为航空运输政策的设计和/或审查提供信息的工具之一。然而，尽管该模型在统计上强大且可靠，但它仍然是一个“粗糙的工具”，航空运输规划者应与其他数据结合使用。