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A Continuous-Time Yield Management Model with Multiple Prices and Reversible Price Changes


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  • Youyi Feng

    (Department of Information System, School of Computing, National University of Singapore, Republic of Singapore 119260)

  • Baichun Xiao

    (Department of Management, Long Island University, C.W. Post, Brookville, New York 11548)

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    This article studies a continuous-time yield management model in which reversible price changes are allowed. We assume that perishable assets are offered at a set of discrete price levels. Demand at each level is a Poisson process. To maximize the expected revenue, management controls the price dynamically as sales evolve. We show that a subset of these prices that form a concave envelope is potentially optimal. We formulate the problem into an intensity control model and derive the optimal solution in closed form. Properties of the optimal solution and their policy implementations are discussed. Numerical examples are provided.

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    Bibliographic Info

    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 46 (2000)
    Issue (Month): 5 (May)
    Pages: 644-657

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    Handle: RePEc:inm:ormnsc:v:46:y:2000:i:5:p:644-657

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    Keywords: yield management; optimal switching time; poisson demand; monotonicity;


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    Cited by:
    1. Berk, Emre & Gürler, Ülkü & YIldIrIm, Gonca, 2009. "On pricing of perishable assets with menu costs," International Journal of Production Economics, Elsevier, vol. 121(2), pages 678-699, October.
    2. Wang, Xiubin & Wang, Fenghuan, 2007. "Dynamic network yield management," Transportation Research Part B: Methodological, Elsevier, vol. 41(4), pages 410-425, May.
    3. Becher, Michael, 2009. "Simultaneous capacity and price control based on fuzzy controllers," International Journal of Production Economics, Elsevier, vol. 121(2), pages 365-382, October.
    4. Malgorzata Ogonowska & Dominique Torre, 2012. "Sustainable Tourism and the emergence of new Environmental Norms," Post-Print halshs-00726127, HAL.
    5. Chew, Ek Peng & Lee, Chulung & Liu, Rujing, 2009. "Joint inventory allocation and pricing decisions for perishable products," International Journal of Production Economics, Elsevier, vol. 120(1), pages 139-150, July.
    6. Cao, Ping & Li, Jianbin & Yan, Hong, 2012. "Optimal dynamic pricing of inventories with stochastic demand and discounted criterion," European Journal of Operational Research, Elsevier, vol. 217(3), pages 580-588.
    7. Pak, K. & Piersma, N., 2002. "Airline revenue management: an overview of OR techniques 1982-2001," Econometric Institute Research Papers EI 2002-03, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    8. Feng, Youyi & Xiao, Baichun, 2006. "Integration of pricing and capacity allocation for perishable products," European Journal of Operational Research, Elsevier, vol. 168(1), pages 17-34, January.
    9. Constantinos Maglaras & Joern Meissner, 2003. "Dynamic Pricing Strategies for Multi-Product Revenue Management Problems," Working Papers MRG/0002, Department of Management Science, Lancaster University, revised Nov 2005.
    10. Pak, K. & Piersma, N., 2002. "airline revenue management," ERIM Report Series Research in Management ERS-2002-12-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus Uni.
    11. Wang, Xiubin & Regan, Amelia, 2006. "Dynamic yield management when aircraft assignments are subject to swap," Transportation Research Part B: Methodological, Elsevier, vol. 40(7), pages 563-576, August.
    12. Sibdari, Soheil & Pyke, David F., 2014. "Dynamic pricing with uncertain production cost: An alternating-move approach," European Journal of Operational Research, Elsevier, vol. 236(1), pages 218-228.
    13. Ferreira, Kevin D. & Wu, Desheng Dash, 2011. "An integrated product planning model for pricing and bundle selection using Markov decision processes and data envelope analysis," International Journal of Production Economics, Elsevier, vol. 134(1), pages 95-107, November.


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