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Delay causality network in air transport systems

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  • Du, Wen-Bo
  • Zhang, Ming-Yuan
  • Zhang, Yu
  • Cao, Xian-Bin
  • Zhang, Jun

Abstract

To better understand the mechanism of flight delay propagation at the system-level, we built a delay causality network (DCN) based on the Granger causality test. Through topological analysis of DCNs, we found that only about a quarter of airports were involved in delay propagation during the peak travel period and large airports affected by many upstream airports impact fewer downstream airports. Furthermore, temporal analysis of DCNs indicates that the culprits of delay propagation in the air transport system are not a fixed set of airports; instead, they vary daily depending on the operational environment.

Suggested Citation

  • Du, Wen-Bo & Zhang, Ming-Yuan & Zhang, Yu & Cao, Xian-Bin & Zhang, Jun, 2018. "Delay causality network in air transport systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 466-476.
    • Handle: RePEc:eee:transe:v:118:y:2018:i:c:p:466-476
    DOI: 10.1016/j.tre.2018.08.014
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    1. Czerny, Achim I., 2010. "Airport congestion management under uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 44(3), pages 371-380, March.
    2. Chiou-Wei, Song Zan & Chen, Ching-Fu & Zhu, Zhen, 2008. "Economic growth and energy consumption revisited -- Evidence from linear and nonlinear Granger causality," Energy Economics, Elsevier, vol. 30(6), pages 3063-3076, November.
    3. Campanelli, Bruno & Fleurquin, Pablo & Arranz, Andrés & Etxebarria, Izaro & Ciruelos, Carla & Eguíluz, Víctor M. & Ramasco, José J., 2016. "Comparing the modeling of delay propagation in the US and European air traffic networks," Journal of Air Transport Management, Elsevier, vol. 56(PA), pages 12-18.
    4. Wang, Jiaoe & Mo, Huihui & Wang, Fahui, 2014. "Evolution of air transport network of China 1930–2012," Journal of Transport Geography, Elsevier, vol. 40(C), pages 145-158.
    5. Shan Lan & John-Paul Clarke & Cynthia Barnhart, 2006. "Planning for Robust Airline Operations: Optimizing Aircraft Routings and Flight Departure Times to Minimize Passenger Disruptions," Transportation Science, INFORMS, vol. 40(1), pages 15-28, February.
    6. Benjamin Wahl & Ulrike Feudel & Jaroslav Hlinka & Matthias Wächter & Joachim Peinke & Jan A. Freund, 2017. "Conditional Granger causality of diffusion processes," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 90(10), pages 1-8, October.
    7. Meng, Lingyun & Zhou, Xuesong, 2011. "Robust single-track train dispatching model under a dynamic and stochastic environment: A scenario-based rolling horizon solution approach," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 1080-1102, August.
    8. AhmadBeygi, Shervin & Cohn, Amy & Guan, Yihan & Belobaba, Peter, 2008. "Analysis of the potential for delay propagation in passenger airline networks," Journal of Air Transport Management, Elsevier, vol. 14(5), pages 221-236.
    9. Du, Wen-Bo & Zhou, Xing-Lian & Lordan, Oriol & Wang, Zhen & Zhao, Chen & Zhu, Yan-Bo, 2016. "Analysis of the Chinese Airline Network as multi-layer networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 89(C), pages 108-116.
    10. Zhukova Olesia A. & Ivashkova N.I., 2017. "Marketing Strategies Of Low-Cost Airlines In Russia," Annals of marketing-mba, Department of Marketing, Marketing MBA (RSconsult), vol. 2, June.
    11. Cook, Andrew & Blom, Henk A.P. & Lillo, Fabrizio & Mantegna, Rosario Nunzio & Miccichè, Salvatore & Rivas, Damián & Vázquez, Rafael & Zanin, Massimiliano, 2015. "Applying complexity science to air traffic management," Journal of Air Transport Management, Elsevier, vol. 42(C), pages 149-158.
    12. Kafle, Nabin & Zou, Bo, 2016. "Modeling flight delay propagation: A new analytical-econometric approach," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 520-542.
    13. Britto, Rodrigo & Dresner, Martin & Voltes, Augusto, 2012. "The impact of flight delays on passenger demand and societal welfare," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(2), pages 460-469.
    14. Hao, Lu & Hansen, Mark & Zhang, Yu & Post, Joseph, 2014. "New York, New York: Two ways of estimating the delay impact of New York airports," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 245-260.
    15. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    16. Zou, Bo & Hansen, Mark, 2014. "Flight delay impact on airfare and flight frequency: A comprehensive assessment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 69(C), pages 54-74.
    17. Repko, Martijn G.J. & Santos, Bruno F., 2017. "Scenario tree airline fleet planning for demand uncertainty," Journal of Air Transport Management, Elsevier, vol. 65(C), pages 198-208.
    18. Ren, Pan & Li, Lishuai, 2018. "Characterizing air traffic networks via large-scale aircraft tracking data: A comparison between China and the US networks," Journal of Air Transport Management, Elsevier, vol. 67(C), pages 181-196.
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