Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.trip.2019.100007
DC FieldValue
dc.titleAntecedents of flight delays in the Australian domestic aviation market
dc.contributor.authorMohammadian, I.
dc.contributor.authorAbbasi, B.
dc.contributor.authorAbareshi, A.
dc.contributor.authorGoh, M.
dc.date.accessioned2021-12-16T07:49:01Z
dc.date.available2021-12-16T07:49:01Z
dc.date.issued2019
dc.identifier.citationMohammadian, I., Abbasi, B., Abareshi, A., Goh, M. (2019). Antecedents of flight delays in the Australian domestic aviation market. Transportation Research Interdisciplinary Perspectives 1 : 100007. ScholarBank@NUS Repository. https://doi.org/10.1016/j.trip.2019.100007
dc.identifier.issn25901982
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/210769
dc.description.abstractFlight delays are widespread and growing around the world. Using public domain data of the airlines in Australia's domestic aviation market, this study investigates the antecedents of flight delays, and how airline operations contribute to such an important issue in the aviation industry. Applying the Hausman-Taylor regression method, the estimations suggest that the variables of the airline capacity decision are meaningful determinants of flight delays. Our findings inform that more frequent flights and larger aircraft are associated with more flight delays. A higher level of route congestion leads to more flight delays, especially for the low-cost carriers. Jet fuel price is identified as a driver, leading to more flight delays for the legacy airlines compared to the low-cost carriers. Keen competition between the airlines actually helps to improve the flight service quality, through fewer flight delays. © 2019 The Authors
dc.publisherElsevier Ltd
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.sourceScopus OA2019
dc.subjectAustralia
dc.subjectAviation
dc.subjectEconometrics
dc.subjectFlight delays
dc.subjectHausman-Taylor regression
dc.typeArticle
dc.contributor.departmentANALYTICS AND OPERATIONS
dc.description.doi10.1016/j.trip.2019.100007
dc.description.sourcetitleTransportation Research Interdisciplinary Perspectives
dc.description.volume1
dc.description.page100007
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