Analyzing the Criteria Affecting Transition To Airplane by Comparing Different Methods

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Abstract

This 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.

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Keywords

Air Travel Demand, Travel Behaviour, Air Travel Demand Travel Behaviour, Logistic Regression, Artificial Neural Networks, Cluster Analysis, İşletme, Davranış Bilimleri, H1-99, hava seyahat talebi, Social Sciences, air travel demand, logistic regression analysis, seyahat davranışı, Social sciences (General), lojistik regresyon analizi, travel bahaviour, H, yapay sinir ağları analizi, neural network model, kümeleme analizi, cluster analysis

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05 social sciences, 0211 other engineering and technologies, 02 engineering and technology, 0502 economics and business

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Volume

9

Issue

2

Start Page

1349

End Page

1373

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