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Modeling the Customer Arrival Process and Comparing Decision Rules in Perishable Asset Revenue Management Situations

Author

Listed:
  • Lawrence R. Weatherford

    (University of Wyoming, Laramie, Wyoming 82071)

  • Samuel E. Bodily

    (University of Virginia, Charlottesville, Virginia 22906)

  • Phillip E. Pfeifer

    (University of Virginia, Charlottesville, Virginia 22906)

Abstract

A model for customer arrivals is presented that allows evaluation of different decision rules in perishable asset revenue management (PARM) situations. The model is used to derive probabilities necessary to operationalize the implementation of an optimal decision rule for PARM problems with diversion and two price classes. Heuristic approaches are compared to the proper closing out of price classes to see how much of an improvement can be made in expected contribution. The sensitivity of the difference in expected contribution between these rules is tested relative to changes in the model's input parameters. Managerial insights are presented.

Suggested Citation

  • Lawrence R. Weatherford & Samuel E. Bodily & Phillip E. Pfeifer, 1993. "Modeling the Customer Arrival Process and Comparing Decision Rules in Perishable Asset Revenue Management Situations," Transportation Science, INFORMS, vol. 27(3), pages 239-251, August.
    • Handle: RePEc:inm:ortrsc:v:27:y:1993:i:3:p:239-251
    DOI: 10.1287/trsc.27.3.239
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    Cited by:

    1. Lijian Chen & Tito Homem-de-Mello, 2010. "Re-solving stochastic programming models for airline revenue management," Annals of Operations Research, Springer, vol. 177(1), pages 91-114, June.
    2. Larry Weatherford, 2016. "The history of forecasting models in revenue management," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 15(3), pages 212-221, July.
    3. Wen Zhao & Yu-Sheng Zheng, 2001. "A Dynamic Model for Airline Seat Allocation with Passenger Diversion and No-Shows," Transportation Science, INFORMS, vol. 35(1), pages 80-98, February.
    4. Kalyan Talluri & Garrett van Ryzin, 1998. "An Analysis of Bid-Price Controls for Network Revenue Management," Management Science, INFORMS, vol. 44(11-Part-1), pages 1577-1593, November.
    5. Kyle Y. Lin, 2004. "A sequential dynamic pricing model and its applications," Naval Research Logistics (NRL), John Wiley & Sons, vol. 51(4), pages 501-521, June.
    6. Jeffrey I. McGill & Garrett J. van Ryzin, 1999. "Revenue Management: Research Overview and Prospects," Transportation Science, INFORMS, vol. 33(2), pages 233-256, May.
    7. de Boer, Sanne V. & Freling, Richard & Piersma, Nanda, 2002. "Mathematical programming for network revenue management revisited," European Journal of Operational Research, Elsevier, vol. 137(1), pages 72-92, February.
    8. Syed Asif Raza & Rafi Ashrafi & Ali Akgunduz, 2020. "A bibliometric analysis of revenue management in airline industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(6), pages 436-465, December.
    9. Richard E. Chatwin, 1998. "Multiperiod Airline Overbooking with a Single Fare Class," Operations Research, INFORMS, vol. 46(6), pages 805-819, December.
    10. You, Peng-Sheng, 2001. "Airline seat management with rejection-for-possible-upgrade decision," Transportation Research Part B: Methodological, Elsevier, vol. 35(5), pages 507-524, June.
    11. Syed A. M. Shihab & Peng Wei, 2022. "A deep reinforcement learning approach to seat inventory control for airline revenue management," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(2), pages 183-199, April.
    12. Qing Ding & Panos Kouvelis & Joseph M. Milner, 2006. "Dynamic Pricing Through Discounts for Optimizing Multiple-Class Demand Fulfillment," Operations Research, INFORMS, vol. 54(1), pages 169-183, February.
    13. Anton J. Kleywegt & Jason D. Papastavrou, 1998. "The Dynamic and Stochastic Knapsack Problem," Operations Research, INFORMS, vol. 46(1), pages 17-35, February.
    14. Rennie, Nicola & Cleophas, Catherine & Sykulski, Adam M. & Dost, Florian, 2021. "Identifying and responding to outlier demand in revenue management," European Journal of Operational Research, Elsevier, vol. 293(3), pages 1015-1030.
    15. Feng, Youyi & Xiao, Baichun, 2006. "A continuous-time seat control model for single-leg flights with no-shows and optimal overbooking upper bound," European Journal of Operational Research, Elsevier, vol. 174(2), pages 1298-1316, October.
    16. Kim, Sang-Won, 2015. "The impact of customer buying behavior on the optimal allocation decisions," International Journal of Production Economics, Elsevier, vol. 163(C), pages 71-88.
    17. Scott Carr & William Lovejoy, 2000. "The Inverse Newsvendor Problem: Choosing an Optimal Demand Portfolio for Capacitated Resources," Management Science, INFORMS, vol. 46(7), pages 912-927, July.
    18. Youyi Feng & Guillermo Gallego, 2000. "Perishable Asset Revenue Management with Markovian Time Dependent Demand Intensities," Management Science, INFORMS, vol. 46(7), pages 941-956, July.
    19. Valerio Lacagnina & Davide Provenzano, 2016. "An integrated fuzzy-stochastic model for revenue management," Tourism Economics, , vol. 22(4), pages 779-792, August.
    20. Dimitris Bertsimas & Sanne de Boer, 2005. "Simulation-Based Booking Limits for Airline Revenue Management," Operations Research, INFORMS, vol. 53(1), pages 90-106, February.

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