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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 Europe

Author

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  • Martina Zámková

    (Department of Mathematics, College of Polytechnics Jihlava, Tolstého 16, 58601 Jihlava, Czech Republic)

  • Stanislav Rojík

    (Department of Economic Studies, College of Polytechnics Jihlava, Tolstého 16, 58601 Jihlava, Czech Republic)

  • Martin Prokop

    (Department of Mathematics, College of Polytechnics Jihlava, Tolstého 16, 58601 Jihlava, Czech Republic)

  • Radek Stolín

    (Department of Mathematics, College of Polytechnics Jihlava, Tolstého 16, 58601 Jihlava, Czech Republic)

Abstract

This paper aims to analyze the causes of flight delays of a selected airline operating in Europe and identify potential risks and reasons for delays in air transport, which carry risk, especially in connection with passenger dissatisfaction and the resulting need to pay compensation for delayed flights, according to EU law, which brings significant financial costs for airlines. Data collected from the years 2013–2019 have been used for the purposes of this article, including data on the duration and causes of the delays and the characteristics of individual flights, such as the flight type, aircraft type, time of departure, aircraft capacity, and the load factor. Multidimensional statistics methods have been applied for data processing, namely tests of independence and correspondence analysis. Dependencies have been presented in graphical form using correspondence maps. The analysis shows that the total share of delayed flights of the company in question does not increase over the mentioned period of time. The analysis furthermore proved that higher capacity aircraft were rather prone to longer delays. The share of delayed charter flights declined slightly over the period under review, while the number of delays caused by airline operating reasons, aircraft clearance by supplier companies, technical maintenance and aircraft defects, operating procedures, and crew flight standards and airport restrictions is increasing. The analysis also shows that the delays propagated by the delays of the previous flights are becoming more frequent, with the exception of the year 2019. In the last pre-COVID year, air traffic control could boast about a positive trend regarding the number of produced delays over the years, contributing to greater air passenger satisfaction and airline service quality. Due to the gradual revival of air transport after the COVID pandemic lockdowns, the topic of flight delays, passenger customer satisfaction and financial costs for the resulting delays is once again an actual issue for air management and operation.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:22:p:14763-:d:967756
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    1. 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.
    2. Wesonga, Ronald, 2015. "Airport utility stochastic optimization models for air traffic flow management," European Journal of Operational Research, Elsevier, vol. 242(3), pages 999-1007.
    3. Wojciech Paprocki, 2021. "Virtual Airport Hub—A New Business Model to Reduce GHG Emissions in Continental Air Transport," Sustainability, MDPI, vol. 13(9), pages 1-19, April.
    4. Zhe Liang & Wanpracha Art Chaovalitwongse, 2009. "The Aircraft Maintenance Routing Problem," Springer Optimization and Its Applications, in: Wanpracha Chaovalitwongse & Kevin C. Furman & Panos M. Pardalos (ed.), Optimization and Logistics Challenges in the Enterprise, pages 327-348, Springer.
    5. Ioannis Simaiakis & Hamsa Balakrishnan, 2016. "A Queuing Model of the Airport Departure Process," Transportation Science, INFORMS, vol. 50(1), pages 94-109, February.
    6. 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.
    7. Ryerson, Megan S. & Hansen, Mark & Bonn, James, 2014. "Time to burn: Flight delay, terminal efficiency, and fuel consumption in the National Airspace System," Transportation Research Part A: Policy and Practice, Elsevier, vol. 69(C), pages 286-298.
    8. Silke J. Forbes & Mara Lederman & Trevor Tombe, 2015. "Quality Disclosure Programs and Internal Organizational Practices: Evidence from Airline Flight Delays," American Economic Journal: Microeconomics, American Economic Association, vol. 7(2), pages 1-26, May.
    9. Chaug-Ing Hsu & Ching-Cheng Chao & Nai-Wen Hsu, 2015. "Control strategies for departure process delays at airport passenger terminals," Transportation Planning and Technology, Taylor & Francis Journals, vol. 38(2), pages 214-237, March.
    10. Mazhar Arıkan & Vinayak Deshpande & Milind Sohoni, 2013. "Building Reliable Air-Travel Infrastructure Using Empirical Data and Stochastic Models of Airline Networks," Operations Research, INFORMS, vol. 61(1), pages 45-64, February.
    11. 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.
    12. Abdelghany, Ahmed & Abdelghany, Khaled & Narasimhan, Ram, 2006. "Scheduling baggage-handling facilities in congested airports," Journal of Air Transport Management, Elsevier, vol. 12(2), pages 76-81.
    13. 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.
    14. Huang, Edward & Mital, Pratik & Goetschalckx, Marc & Wu, Kan, 2016. "Optimal assignment of airport baggage unloading zones to outgoing flights," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 94(C), pages 110-122.
    15. Ivanov, Nikola & Netjasov, Fedja & Jovanović, Radosav & Starita, Stefano & Strauss, Arne, 2017. "Air Traffic Flow Management slot allocation to minimize propagated delay and improve airport slot adherence," Transportation Research Part A: Policy and Practice, Elsevier, vol. 95(C), pages 183-197.
    16. Gillen, David & Jacquillat, Alexandre & Odoni, Amedeo R., 2016. "Airport demand management: The operations research and economics perspectives and potential synergies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 495-513.
    17. Liu, Wenjing & Zhao, Qiuhong & Delahaye, Daniel, 2022. "Research on slot allocation for airport network in the presence of uncertainty," Journal of Air Transport Management, Elsevier, vol. 104(C).
    18. 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.
    19. Sai Ho Chung & Hoi Lam Ma & Hing Kai Chan, 2017. "Cascading Delay Risk of Airline Workforce Deployments with Crew Pairing and Schedule Optimization," Risk Analysis, John Wiley & Sons, vol. 37(8), pages 1443-1458, August.
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