Reyhanoğlu, İzayReyhanoglu, IzayTengilimoğlu, DilaverTengilimoglu, DilaverBusinessAviation Management2024-07-052024-07-05202202149-165810.30798/makuiibf.1035167https://doi.org/10.30798/makuiibf.1035167https://hdl.handle.net/20.500.14411/1778This study, using the multi-vehicle approach, discusses the criteria affecting the transition from alternative transportation modes (car, train, bus) to air transportation between city pairs that neither have a hub status nor non-stop flights between them. If these criteria change, the demand for air transportation will increase. For this purpose, a survey was conducted in the provinces of Kayseri and Bursa, which are among the important trade, industry, and tourism centers in Turkey, in the course of three months between January and March, 2018. Logistic regression, the artificial neural network model, and clustering analyses were applied to the data compiled from questionnaires responded to by 501 individuals in Kayseri and 453 individuals in Bursa. According to the empirical findings, it was concluded that the most significant criteria in the transition to air transportation according to all three methods are the cost of travel/ticket price and non-stop flight. Additionally, it was observed that the Artificial Neural Networks (ANN) model made more accurate predictions compared to others. This study is important since it compares three different methods for the purpose of criteria determination concerning the choice of transportation modes.eninfo:eu-repo/semantics/openAccessAir Travel DemandTravel BehaviourAir Travel Demand Travel BehaviourLogistic RegressionArtificial Neural NetworksCluster AnalysisArticle9213491373WOS:0008700397000291162160