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Scheduled block time setting and on-time performance of U.S. and Chinese airlines—A comparative analysis

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  • Wang, Yanjun
  • Zhou, Ying
  • Hansen, Mark
  • Chin, Christopher

Abstract

Scheduled block time (SBT) is the duration between scheduled departure time and scheduled arrival time of a given flight. SBTs have a significant impact on airline operations and performance, and airlines consider various factors in setting them. Recent studies have proposed several models for understanding U.S. airlines’ SBT-setting behavior and have examined the contribution of SBT-setting to airline on-time performance (OTP). How airlines in different countries and regions set their SBTs and to what degree differences in SBT-setting behavior explain observed differences in OTP is still unknown. Here we develop econometric models of SBTs based on historical distributions of actual block time to reveal the differences in SBT-setting behavior between major airlines in China and the U.S. We find that Chinese airlines focus on the left tail of the distributions while the U.S. airlines consider the left tail, middle, and inner right tail. They also have different ways of accounting for taxi-out time in setting SBTs, with the U.S. focusing on historical time distributions while in China taxi-out time is based on airport category. We then perform counterfactual analysis by using one nation’s model to predict the other nation’s SBTs and the resulting difference in OTP. Results indicate that the OTP of Chinese airlines would match those of the U.S. if they followed U.S. practices in setting SBTs, while U.S. airlines would have slightly worse OTP than Chinese carriers if they set SBTs according to Chinese methods. Our findings highlight the difference in SBT-setting behavior of major airlines in China and U.S. and its contribution to OTP. The model and methods presented here may also be applied to study and compare SBT setting and its impact on OTP in other parts of the world.

Suggested Citation

  • Wang, Yanjun & Zhou, Ying & Hansen, Mark & Chin, Christopher, 2019. "Scheduled block time setting and on-time performance of U.S. and Chinese airlines—A comparative analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 825-843.
    • Handle: RePEc:eee:transa:v:130:y:2019:i:c:p:825-843
    DOI: 10.1016/j.tra.2019.09.043
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    References listed on IDEAS

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    1. Liu, Yi & Hansen, Mark & Zou, Bo, 2013. "Aircraft gauge differences between the US and Europe and their operational implications," Journal of Air Transport Management, Elsevier, vol. 29(C), pages 1-10.
    2. Barbot, Cristina & Costa, Ã lvaro & Sochirca, Elena, 2008. "Airlines performance in the new market context: A comparative productivity and efficiency analysis," Journal of Air Transport Management, Elsevier, vol. 14(5), pages 270-274.
    3. Vinayak Deshpande & Mazhar Arıkan, 2012. "The Impact of Airline Flight Schedules on Flight Delays," Manufacturing & Service Operations Management, INFORMS, vol. 14(3), pages 423-440, July.
    4. Hao, Lu & Hansen, Mark, 2014. "Block time reliability and scheduled block time setting," Transportation Research Part B: Methodological, Elsevier, vol. 69(C), pages 98-111.
    5. Kang, Lei & Hansen, Mark, 2017. "Behavioral analysis of airline scheduled block time adjustment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 56-68.
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    Cited by:

    1. 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).
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    3. Abdelghany, Ahmed & Guzhva, Vitaly S. & Abdelghany, Khaled, 2023. "The limitation of machine-learning based models in predicting airline flight block time," Journal of Air Transport Management, Elsevier, vol. 107(C).
    4. 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.
    5. Abdelghany, Ahmed & Abdelghany, Khaled & Guzhva, Vitaly S., 2024. "Schedule-level optimization of flight block times for improved airline schedule planning: A data-driven approach," Journal of Air Transport Management, Elsevier, vol. 115(C).
    6. 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).
    7. Eufrásio, Ana Beatriz R. & Eller, Rogéria A.G. & Oliveira, Alessandro V.M., 2021. "Are on-time performance statistics worthless? An empirical study of the flight scheduling strategies of Brazilian airlines," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    8. Wang, Chunzheng & Hu, Minghua & Yang, Lei & Zhao, Zheng, 2022. "Improving the spatial-temporal generalization of flight block time prediction: A development of stacking models," Journal of Air Transport Management, Elsevier, vol. 103(C).

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