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DC Field | Value | Language |
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dc.contributor.author | Sismanidou, Athina | - |
dc.contributor.author | Tarradellas Espuny, Joan | - |
dc.contributor.author | Suau Sánchez, Pere | - |
dc.contributor.other | Universitat Oberta de Catalunya. Estudis d'Economia i Empresa | - |
dc.contributor.other | Cranfield University | - |
dc.contributor.other | EADA Business School | - |
dc.date.accessioned | 2022-05-18T09:17:18Z | - |
dc.date.available | 2022-05-18T09:17:18Z | - |
dc.date.issued | 2021-12-20 | - |
dc.identifier.citation | Sismanidou, A., Tarradellas, J. & Suau-Sánchez, P. (2022). The uneven geography of US air traffic delays: Quantifying the impact of connecting passengers on delay propagation. Journal of Transport Geography, 98, 1-12. doi: 10.1016/j.jtrangeo.2021.103260 | - |
dc.identifier.issn | 0966-6923MIAR | - |
dc.identifier.uri | http://hdl.handle.net/10609/144208 | - |
dc.description.abstract | Sustained airport congestion periods translate into delays, especially in hub-and-spoke networks in which delay propagation is more evident. We examine the impact of connecting passenger arrival delays on network delay propagation by using passenger level data combined with flight delay data that allow us to analyse the correlation between delayed incoming flights and departure delays at the 21 U.S. airports with most delays, in July 2018. Results show that correlation between daily arrival delays and daily carrier induced departure delays are statistically significant only for flights carrying high proportions of connecting passengers. Correlation values are also higher for short-to-moderate arrival delays. In addition, a Neural Network model was trained for six major airports to build a delay prediction model and map the potential delay propagation. The results of the propagation scenarios suggest that the presence of a unique dominant carrier at an airport translates into a stronger correlation between arrival and carrier delays than that at airports where different carriers compete for connecting passengers. Furthermore, airline hubs located near the areas of the network with more traffic density, independently of the hub's volume of traffic, are more likely to propagate the delay than hubs located in the periphery. The results of this study can be relevant for airline, airport, and traffic control policies aimed at mitigating airport and network congestion. | en |
dc.format.mimetype | application/pdf | - |
dc.language.iso | eng | - |
dc.publisher | Journal of Transport Geography | - |
dc.relation.ispartof | Journal of Transport Geography, 2022, 98. | - |
dc.relation.ispartofseries | 98; | - |
dc.relation.uri | https://doi.org/10.1016/j.jtrangeo.2021.103260 | - |
dc.rights | CC BY-NC-ND 4.0 | - |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | - |
dc.subject | airport congestion | en |
dc.subject | congestió aeroportuària | ca |
dc.subject | congestión del aeropuerto | es |
dc.subject | network congestion | en |
dc.subject | congestión en la red | es |
dc.subject | congestió de la xarxa | ca |
dc.subject | flight delay propagation | en |
dc.subject | propagació del retard del vol | ca |
dc.subject | propagación de retraso de vuelo | es |
dc.subject | carrier delay | en |
dc.subject | retraso del transportista | es |
dc.subject | retard del transportista | ca |
dc.subject | delay prediction | en |
dc.subject | predicció de retard | ca |
dc.subject | predicción de retraso | es |
dc.subject | intra-airport delay | en |
dc.subject | retraso dentro del aeropuerto | es |
dc.subject | retard a l'interior de l'aeroport | ca |
dc.subject | machine learning algorithms | en |
dc.subject | algorismes d'aprenentatge automàtic | ca |
dc.subject | algoritmos de aprendizaje automático | es |
dc.subject.lcsh | machine learning | en |
dc.title | The uneven geography of US air traffic delays: Quantifying the impact of connecting passengers on delay propagation | - |
dc.type | info:eu-repo/semantics/article | - |
dc.subject.lemac | aprenentatge automàtic | ca |
dc.subject.lcshes | aprendizaje automático | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | - |
dc.identifier.doi | http://doi.org/10.1016/j.jtrangeo.2021.103260 | - |
dc.gir.id | AR/0000009339 | - |
dc.type.version | info:eu-repo/semantics/publishedVersion | - |
Appears in Collections: | Articles Articles cientÍfics |
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Sismanidou_1-s2.0-S0966692321003136-main.pdf | 2,93 MB | Adobe PDF | View/Open |
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