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Optimal demand for operating lease of aircraft

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  • Oum, Tae Hoon
  • Zhang, Anming
  • Zhang, Yimin

Abstract

Operating lease of the aircraft gives the airlines flexibility in capacity management. However, airlines pay a risk premium to the leasing companies for bearing part of the risks. Therefore, the airlines face a trade-off between flexibility of capacity and higher costs. This paper develops a model for the airlines to determine their optimal mix of leased and owned capacity, taking into consideration that the demand for air transportation is uncertain and cyclical. Empirical results based on the model suggested that the optimal demand by 23 major airlines in the world would range between 40% and 60% of their total fleet, for the reasonable range of premiums of operating lease. For the leasing companies, this indicates huge potential of the market given strong forecast for the growth of air transportation in the next decade.

Suggested Citation

  • Oum, Tae Hoon & Zhang, Anming & Zhang, Yimin, 2000. "Optimal demand for operating lease of aircraft," Transportation Research Part B: Methodological, Elsevier, vol. 34(1), pages 17-29, January.
    • Handle: RePEc:eee:transb:v:34:y:2000:i:1:p:17-29
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    Cited by:

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    2. Gianmaria Martini & Davide Scotti, 2009. "Potere di mercato e distribuzione dei profitti nella filiera del trasporto aereo," Working Papers 0906, Department of Management, Information and Production Engineering, University of Bergamo.
    3. Chen, Wei-Ting & Wu, Cheng-Lung, 2023. "Aircraft acquisition optimization under demand and cost fluctuations: Before and after leasing standard changes," Journal of Air Transport Management, Elsevier, vol. 112(C).
    4. Lee, Chyn-Hwa & Hooy, Chee-Wooi, 2012. "Determinants of systematic financial risk exposures of airlines in North America, Europe and Asia," Journal of Air Transport Management, Elsevier, vol. 24(C), pages 31-35.
    5. Bazargan, Massoud & Hartman, Joseph, 2012. "Aircraft replacement strategy: Model and analysis," Journal of Air Transport Management, Elsevier, vol. 25(C), pages 26-29.
    6. Dožić, Slavica & Kalić, Milica, 2015. "Three-stage airline fleet planning model," Journal of Air Transport Management, Elsevier, vol. 46(C), pages 30-39.
    7. Bourjade, Sylvain & Huc, Regis & Muller-Vibes, Catherine, 2017. "Leasing and profitability: Empirical evidence from the airline industry," Transportation Research Part A: Policy and Practice, Elsevier, vol. 97(C), pages 30-46.
    8. Sa, Constantijn A.A. & Santos, Bruno F. & Clarke, John-Paul B., 2020. "Portfolio-based airline fleet planning under stochastic demand," Omega, Elsevier, vol. 97(C).
    9. Geursen, Izaak L. & Santos, Bruno F. & Yorke-Smith, Neil, 2023. "Fleet planning under demand and fuel price uncertainty using actor–critic reinforcement learning," Journal of Air Transport Management, Elsevier, vol. 109(C).
    10. Czerny, Achim I. & Cowan, Simon & Zhang, Anming, 2017. "How to mix per-flight and per-passenger based airport charges: The oligopoly case," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 483-500.
    11. Jing Zhou, 2023. "Airline capacity distribution under financial budget and resource consideration," Journal of Combinatorial Optimization, Springer, vol. 45(5), pages 1-29, July.
    12. Hu, Qiwei & Zhang, Anming, 2015. "Real option analysis of aircraft acquisition: A case study," Journal of Air Transport Management, Elsevier, vol. 46(C), pages 19-29.
    13. Chen, Wei-Ting & Huang, Kuancheng & Ardiansyah, Muhammad Nashir, 2018. "A mathematical programming model for aircraft leasing decisions," Journal of Air Transport Management, Elsevier, vol. 69(C), pages 15-25.
    14. Singh, Jagroop & Sharma, Somesh Kumar & Srivastava, Rajnish, 2019. "What drives Indian Airlines operational expense: An econometric model," Journal of Air Transport Management, Elsevier, vol. 77(C), pages 32-38.

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