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An option-based revenue management procedure for strategic airline alliances


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  • Graf, M.
  • Kimms, A.
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    An airline has to decide whether to accept an incoming customer request for a seat in the airplane or to reject it in hope that another customer will request the seat later at a higher price. Capacity control, as one of the instruments of revenue management, gives a solution to this decision problem. In the presence of strategic alliances capacity control changes. For the case of two airlines in the alliance and a single flight leg we propose an option-based capacity control process. The determination of booking limits for capacity control is done with real options. A simulation model is introduced to evaluate the booking process of the partner airlines within the strategic alliance, considering the option-based procedure. In an iterative process the booking limits are improved with simulation-based optimization. The results of the option-based procedure will be compared with the results of the simulation-based optimization, the results of a first-come-first-served (FCFS) approach and ex post optimal solutions.

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    Bibliographic Info

    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 215 (2011)
    Issue (Month): 2 (December)
    Pages: 459-469

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    Handle: RePEc:eee:ejores:v:215:y:2011:i:2:p:459-469

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    Keywords: Revenue management Strategic alliances Capacity control Real options Simulation-based optimization Stochastic approximation;


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    Cited by:
    1. Çetiner, D. & Kimms, A., 2013. "Assessing fairness of selfish revenue sharing mechanisms for airline alliances," Omega, Elsevier, vol. 41(4), pages 641-652.
    2. Graf, M. & Kimms, A., 2013. "Transfer price optimization for option-based airline alliance revenue management," International Journal of Production Economics, Elsevier, vol. 145(1), pages 281-293.
    3. Gönsch, Jochen & Koch, Sebastian & Steinhardt, Claudius, 2014. "Revenue management with flexible products: The value of flexibility and its incorporation into DLP-based approaches," International Journal of Production Economics, Elsevier, vol. 153(C), pages 280-294.
    4. Grauberger, W. & Kimms, A., 2014. "Computing approximate Nash equilibria in general network revenue management games," European Journal of Operational Research, Elsevier, vol. 237(3), pages 1008-1020.
    5. Kimms, Alf & Çetiner, Demet, 2012. "Approximate nucleolus-based revenue sharing in airline alliances," European Journal of Operational Research, Elsevier, vol. 220(2), pages 510-521.


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