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Airport and route classification by modelling flight delay propagation

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  • Kim, Myeonghyeon
  • Park, Sunwook

Abstract

Flight delay can be divided into the root and propagated delays for identification and analysis of airports/routes that have a great influence on actual flight delay using flight operations raw data (tower logs) for South Korean domestic flights. In addition, the presented concept of “generated delay†classifies airports as affecting other airport delays or affected by other airport delays. The generated delay refers to the delay time at a particular airport/route, and this delay thereafter actually propagates to other airports/routes. In this study, the generated and propagated delays were displayed on a two-dimensional graph, and the airports/routes were grouped according to delay characteristics. Group A represented airports with high generated and propagated delays, and group B represented airports that are highly affected by delays of preceding airports/routes. Group C represents airports where newly formed delays affect other airport delays, but these airports mitigate delays from other airports. Airports in group D have relatively low delays and propagation. Thus, we targeted airports belonging to groups A and C because of their delay propagation impact on other routes/airports, which must be reduced by decreasing the root delay from targeted routes/airports. Among the airports, Jeju international airport (CJU) had the highest average delay time and propagated flight delay time with similar averaged generated delay times. Among the routes, departure flights from various airports to CJU had significant propagation effects on the subsequent flights. CJU and related routes have a very large impact on domestic flight delays because South Korean domestic airline routes are concentrated on CJU. However, there has been no quantitative analysis, and it is meaningful that the quantitative analysis results were presented in this study. In addition, we suggest that other airports such as GMP (Gimpo), CJJ (Cheongju), WJU (Wonju), and KUV (Gunsan) have a significant impact on domestic flight delays.

Suggested Citation

  • Kim, Myeonghyeon & Park, Sunwook, 2021. "Airport and route classification by modelling flight delay propagation," Journal of Air Transport Management, Elsevier, vol. 93(C).
    • Handle: RePEc:eee:jaitra:v:93:y:2021:i:c:s0969699721000284
    DOI: 10.1016/j.jairtraman.2021.102045
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    References listed on IDEAS

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    Cited by:

    1. Brueckner, Jan K. & Czerny, Achim I. & Gaggero, Alberto A., 2022. "Airline delay propagation: A simple method for measuring its extent and determinants," Transportation Research Part B: Methodological, Elsevier, vol. 162(C), pages 55-71.
    2. Li, Chi & Mao, Jianfeng & Li, Lingyi & Wu, Jingxuan & Zhang, Lianmin & Zhu, Jianyu & Pan, Zibin, 2024. "Flight delay propagation modeling: Data, Methods, and Future opportunities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 185(C).
    3. Khan, Waqar Ahmed & Chung, Sai-Ho & Eltoukhy, Abdelrahman E.E. & Khurshid, Faisal, 2024. "A novel parallel series data-driven model for IATA-coded flight delays prediction and features analysis," Journal of Air Transport Management, Elsevier, vol. 114(C).
    4. Wang, Yanjun & Li, Max Z. & Gopalakrishnan, Karthik & Liu, Tongdan, 2022. "Timescales of delay propagation in airport networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    5. Kim, Myeonghyeon & Sohn, Jeongwoong, 2022. "Passenger, airline, and policy responses to the COVID-19 crisis: The case of South Korea," Journal of Air Transport Management, Elsevier, vol. 98(C).

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