Analyzing the Criteria Affecting Transition To Airplane by Comparing Different Methods

dc.contributor.author Reyhanoglu, Izay
dc.contributor.author Tengilimoglu, Dilaver
dc.contributor.other Business
dc.contributor.other Aviation Management
dc.contributor.other 05. School of Business
dc.contributor.other 13. School of Civil Aviation (4-Year)
dc.contributor.other 01. Atılım University
dc.date.accessioned 2024-07-05T15:17:43Z
dc.date.available 2024-07-05T15:17:43Z
dc.date.issued 2022
dc.description.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. en_US
dc.identifier.doi 10.30798/makuiibf.1035167
dc.identifier.issn 2149-1658
dc.identifier.uri https://doi.org/10.30798/makuiibf.1035167
dc.identifier.uri https://hdl.handle.net/20.500.14411/1778
dc.language.iso en en_US
dc.publisher Mehmet Akif Ersoy Univ en_US
dc.relation.ispartof Mehmet Akif Ersoy Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject Air Travel Demand en_US
dc.subject Travel Behaviour en_US
dc.subject Air Travel Demand Travel Behaviour en_US
dc.subject Logistic Regression en_US
dc.subject Artificial Neural Networks en_US
dc.subject Cluster Analysis en_US
dc.title Analyzing the Criteria Affecting Transition To Airplane by Comparing Different Methods en_US
dc.type Article en_US
dspace.entity.type Publication
gdc.author.institutional Reyhanoğlu, İzay
gdc.author.institutional Tengilimoğlu, Dilaver
gdc.bip.impulseclass C5
gdc.bip.influenceclass C5
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gdc.coar.access open access
gdc.coar.type text::journal::journal article
gdc.description.department Atılım University en_US
gdc.description.departmenttemp [Reyhanoglu, Izay] Atilim Univ, Sivil Havacilik Yuksekokulu, Havacilik Yonetimi Bolumu, Ankara, Turkey; [Tengilimoglu, Dilaver] Atilim Univ, Isletme Fak, Isletme Bolumu, Ankara, Turkey en_US
gdc.description.endpage 1373 en_US
gdc.description.issue 2 en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.startpage 1349 en_US
gdc.description.volume 9 en_US
gdc.identifier.openalex W4220774814
gdc.identifier.trdizinid 1162160
gdc.identifier.wos WOS:000870039700029
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gdc.oaire.keywords H1-99
gdc.oaire.keywords hava seyahat talebi
gdc.oaire.keywords Social Sciences
gdc.oaire.keywords air travel demand
gdc.oaire.keywords logistic regression analysis
gdc.oaire.keywords seyahat davranışı
gdc.oaire.keywords Social sciences (General)
gdc.oaire.keywords lojistik regresyon analizi
gdc.oaire.keywords travel bahaviour
gdc.oaire.keywords H
gdc.oaire.keywords yapay sinir ağları analizi
gdc.oaire.keywords neural network model
gdc.oaire.keywords kümeleme analizi
gdc.oaire.keywords cluster analysis
gdc.oaire.popularity 1.9413013E-9
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gdc.oaire.sciencefields 05 social sciences
gdc.oaire.sciencefields 0211 other engineering and technologies
gdc.oaire.sciencefields 02 engineering and technology
gdc.oaire.sciencefields 0502 economics and business
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