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Improving the IATA delay data coding system for enhanced data analytics

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  • Wu, Cheng-Lung
  • Truong, Tiffany

Abstract

Aviation delays inconvenience travelers and result in financial losses for stakeholders. Without complex data pre-processing, delay data collected by the existing IATA delay coding system are inadequate to support advanced delay analytics, e.g. large-scale delay propagation tracing in an airline network. Consequently, we developed three new coding schemes aiming at improving the current IATA system. These schemes were tested with specific analysis tasks using simulated delay data and were benchmarked against the IATA system. It was found that a coding scheme with a well-designed reporting style can facilitate automated data analytics and data mining, and an improved grouping of delay codes can minimise potential confusion at the data entry and recording stages.

Suggested Citation

  • Wu, Cheng-Lung & Truong, Tiffany, 2014. "Improving the IATA delay data coding system for enhanced data analytics," Journal of Air Transport Management, Elsevier, vol. 40(C), pages 78-85.
  • Handle: RePEc:eee:jaitra:v:40:y:2014:i:c:p:78-85
    DOI: 10.1016/j.jairtraman.2014.06.001
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    References listed on IDEAS

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    1. 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.
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    4. 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.
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    Cited by:

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    2. Merkert, Rico & Bushell, James & Beck, Matthew J., 2020. "Collaboration as a service (CaaS) to fully integrate public transportation – Lessons from long distance travel to reimagine mobility as a service," Transportation Research Part A: Policy and Practice, Elsevier, vol. 131(C), pages 267-282.
    3. 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.
    4. Martina Zámková & Luboš Střelec & Martin Prokop & Radek Stolín, 2021. "Flight Delay Causes at Selected Visegrad Group International Airports," European Journal of Business Science and Technology, Mendel University in Brno, Faculty of Business and Economics, vol. 7(1), pages 91-108.
    5. Martina Zámková & Stanislav Rojík & Martin Prokop & Radek Stolín, 2022. "Factors Affecting the International Flight Delays and Their Impact on Airline Operation and Management and Passenger Compensations Fees in Air Transport Industry: Case Study of a Selected Airlines in ," Sustainability, MDPI, vol. 14(22), pages 1-16, November.
    6. Skorupski, Jacek & Wierzbińska, Magdalena, 2015. "A method to evaluate the time of waiting for a late passenger," Journal of Air Transport Management, Elsevier, vol. 47(C), pages 79-89.

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