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Detecting delay propagation in regional air transport systems using convergent cross mapping and complex network theory

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  • Guo, Zhen
  • Hao, Mengyan
  • Yu, Bin
  • Yao, Baozhen

Abstract

It has been widely recognized that delay propagation is a widespread phenomenon in air transport systems. Regional air transport systems are vulnerable to severe systemic delay propagation because of connected resources and shared airspace. This study presents a two-stage analytical framework to detect delay propagation in regional air transport systems, which is critical to support industrial applications in air transport operations. In the first stage, we propose a delay causality without the strong and independent causality (SIC) assumption to represent the delay propagation effect. A convergent cross mapping method is employed to obtain the delay causality. In the second stage, we build a delay causality graph based on the none SIC assumption (DCG-non-SIC). A complex network analysis of DCG-non-SIC is presented to enhance the understanding of delay propagation patterns. This study carries out a real-world case study and provides some interesting results. Robustness checks are conducted, which verifies that the results derived in the analytical framework are solid. The results show that there is extensive delay causality between airport pairs, and a transitive trait of delay causality is observed in regional air transport systems. In addition, the importance of airports in delay propagation is not exactly in line with the hub class or the airport size.

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  • Guo, Zhen & Hao, Mengyan & Yu, Bin & Yao, Baozhen, 2022. "Detecting delay propagation in regional air transport systems using convergent cross mapping and complex network theory," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
  • Handle: RePEc:eee:transe:v:157:y:2022:i:c:s1366554521003422
    DOI: 10.1016/j.tre.2021.102585
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    as
    1. Tan, Xinlong & Jia, Rongwen & Yan, Jia & Wang, Kun & Bian, Lei, 2021. "An Exploratory analysis of flight delay propagation in China," Journal of Air Transport Management, Elsevier, vol. 92(C).
    2. Wang, Chunan & Wang, Xiaoyu, 2019. "Airport congestion delays and airline networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 328-349.
    3. Duncan J. Watts & Steven H. Strogatz, 1998. "Collective dynamics of ‘small-world’ networks," Nature, Nature, vol. 393(6684), pages 440-442, June.
    4. Brueckner, Jan K. & Czerny, Achim I. & Gaggero, Alberto A., 2021. "Airline mitigation of propagated delays via schedule buffers: Theory and empirics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 150(C).
    5. Choi, Tsan-Ming & Feng, Lipan & Li, Rong, 2020. "Information disclosure structure in supply chains with rental service platforms in the blockchain technology era," International Journal of Production Economics, Elsevier, vol. 221(C).
    6. Gong, Qiang & Wang, Kun & Fan, Xingli & Fu, Xiaowen & Xiao, Yi-bin, 2018. "International trade drivers and freight network analysis - The case of the Chinese air cargo sector," Journal of Transport Geography, Elsevier, vol. 71(C), pages 253-262.
    7. 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.
    8. Belkoura, Seddik & Cook, Andrew & Peña, José Maria & Zanin, Massimiliano, 2016. "On the multi-dimensionality and sampling of air transport networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 94(C), pages 95-109.
    9. Van Nguyen, Truong & Zhang, Jie & Zhou, Li & Meng, Meng & He, Yong, 2020. "A data-driven optimization of large-scale dry port location using the hybrid approach of data mining and complex network theory," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 134(C).
    10. Lynn Wu & Bowen Lou & Lorin Hitt, 2019. "Data Analytics Supports Decentralized Innovation," Management Science, INFORMS, vol. 65(10), pages 4863-4877, October.
    11. Wu, Cheng-Lung & Law, Kristie, 2019. "Modelling the delay propagation effects of multiple resource connections in an airline network using a Bayesian network model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 62-77.
    12. 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.
    13. Kim, Myeonghyeon & Bae, Jiheon, 2021. "Modeling the flight departure delay using survival analysis in South Korea," Journal of Air Transport Management, Elsevier, vol. 91(C).
    14. Katie L. Cramer & Aaron O’Dea & Tara R. Clark & Jian-xin Zhao & Richard D. Norris, 2017. "Prehistorical and historical declines in Caribbean coral reef accretion rates driven by loss of parrotfish," Nature Communications, Nature, vol. 8(1), pages 1-8, April.
    15. Yu, Bin & Guo, Zhen & Asian, Sobhan & Wang, Huaizhu & Chen, Gang, 2019. "Flight delay prediction for commercial air transport: A deep learning approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 203-221.
    16. Wong, Allen & Tan, Sijian & Chandramouleeswaran, Keshav Ram & Tran, Huy T., 2020. "Data-driven analysis of resilience in airline networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).
    17. Sternberg, Alice & Carvalho, Diego & Murta, Leonardo & Soares, Jorge & Ogasawara, Eduardo, 2016. "An analysis of Brazilian flight delays based on frequent patterns," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 282-298.
    18. 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.
    19. Bombelli, Alessandro & Santos, Bruno F. & Tavasszy, Lóránt, 2020. "Analysis of the air cargo transport network using a complex network theory perspective," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    20. Li, Max Z. & Ryerson, Megan S. & Balakrishnan, Hamsa, 2019. "Topological data analysis for aviation applications," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 149-174.
    21. Jane Lee & Lavanya Marla & Alexandre Jacquillat, 2020. "Dynamic Disruption Management in Airline Networks Under Airport Operating Uncertainty," Transportation Science, INFORMS, vol. 54(4), pages 973-997, July.
    22. Lambelho, Miguel & Mitici, Mihaela & Pickup, Simon & Marsden, Alan, 2020. "Assessing strategic flight schedules at an airport using machine learning-based flight delay and cancellation predictions," Journal of Air Transport Management, Elsevier, vol. 82(C).
    23. Choi, Tsan-Ming, 2019. "Blockchain-technology-supported platforms for diamond authentication and certification in luxury supply chains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 17-29.
    24. 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.
    25. Li, Qiang & Jing, Ranzhe, 2021. "Characterization of delay propagation in the air traffic network," Journal of Air Transport Management, Elsevier, vol. 94(C).
    26. 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.
    27. Zhou, Yaoming & Wang, Junwei & Huang, George Q., 2019. "Efficiency and robustness of weighted air transport networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 14-26.
    28. 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.
    29. Voltes-Dorta, Augusto & Rodríguez-Déniz, Héctor & Suau-Sanchez, Pere, 2017. "Vulnerability of the European air transport network to major airport closures from the perspective of passenger delays: Ranking the most critical airports," Transportation Research Part A: Policy and Practice, Elsevier, vol. 96(C), pages 119-145.
    30. Choi, Tsan-Ming & Wen, Xin & Sun, Xuting & Chung, Sai-Ho, 2019. "The mean-variance approach for global supply chain risk analysis with air logistics in the blockchain technology era," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 178-191.
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