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List pricing versus dynamic pricing: Impact on the revenue risk

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  • Koenig, Matthias
  • Meissner, Joern

Abstract

We consider the problem of a firm selling multiple products that consume a single resource over a finite time period. The amount of the resource is exogenously fixed. We analyze the difference between a dynamic pricing policy and a list-price capacity control policy. The dynamic pricing policy adjusts prices steadily resolving the underlying problem every time step, whereas the list pricing policy sets static prices once but controls the capacity by allowing or preventing product sales. As steady price changes are often costly or unachievable in practice, we investigate the question of how much riskier it is to apply a list pricing policy rather than a dynamic pricing policy. We conduct several numerical experiments and compare expected revenue, standard deviation, and conditional-value-at-risk between the pricing policies. The differences between the policies show that list pricing can be a useful strategy when dynamic pricing is costly or impractical.

Suggested Citation

  • Koenig, Matthias & Meissner, Joern, 2010. "List pricing versus dynamic pricing: Impact on the revenue risk," European Journal of Operational Research, Elsevier, vol. 204(3), pages 505-512, August.
  • Handle: RePEc:eee:ejores:v:204:y:2010:i:3:p:505-512
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    References listed on IDEAS

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    1. William L. Cooper, 2002. "Asymptotic Behavior of an Allocation Policy for Revenue Management," Operations Research, INFORMS, vol. 50(4), pages 720-727, August.
    2. Levy, Daniel & Bergen, Mark & Dutta, Shantanu & Venable, Robert, 1997. "The Magnitude of Menu Costs: Direct Evidence from Large U.S. Supermarket Chains," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 112(3), pages 791-824.
    3. Andrew E. B. Lim & J. George Shanthikumar, 2007. "Relative Entropy, Exponential Utility, and Robust Dynamic Pricing," Operations Research, INFORMS, vol. 55(2), pages 198-214, April.
    4. Guillermo Gallego & Garrett van Ryzin, 1997. "A Multiproduct Dynamic Pricing Problem and Its Applications to Network Yield Management," Operations Research, INFORMS, vol. 45(1), pages 24-41, February.
    5. Guillermo Gallego & Garrett van Ryzin, 1994. "Optimal Dynamic Pricing of Inventories with Stochastic Demand over Finite Horizons," Management Science, INFORMS, vol. 40(8), pages 999-1020, August.
    6. Bergen, Mark & Ritson, Mark & Dutta, Shantanu & Levy, Daniel & Zbaracki, Mark, 2003. "Shattering the Myth of Costless Price Changes," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 21(6), pages 663-669.
    7. Mark J. Zbaracki & Mark Ritson & Daniel Levy & Shantanu Dutta & Mark Bergen, 2004. "Managerial and Customer Costs of Price Adjustment: Direct Evidence from Industrial Markets," The Review of Economics and Statistics, MIT Press, vol. 86(2), pages 514-533, May.
    8. Tak C. Lee & Marvin Hersh, 1993. "A Model for Dynamic Airline Seat Inventory Control with Multiple Seat Bookings," Transportation Science, INFORMS, vol. 27(3), pages 252-265, August.
    9. Daniel Levy & Shantanu Dutta & Mark Bergen & Robert Venable, 1998. "Price adjustment at multiproduct retailers," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 19(2), pages 81-120.
    10. Yuri Levin & Jeff McGill & Mikhail Nediak, 2008. "Risk in Revenue Management and Dynamic Pricing," Operations Research, INFORMS, vol. 56(2), pages 326-343, April.
    11. Luciano, Elisa & Peccati, Lorenzo & Cifarelli, Donato M., 2003. "VaR as a risk measure for multiperiod static inventory models," International Journal of Production Economics, Elsevier, vol. 81(1), pages 375-384, January.
    12. Netessine, Serguei, 2006. "Dynamic pricing of inventory/capacity with infrequent price changes," European Journal of Operational Research, Elsevier, vol. 174(1), pages 553-580, October.
    13. C. Barz & K. Waldmann, 2007. "Risk-sensitive capacity control in revenue management," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 65(3), pages 565-579, June.
    14. Youyi Feng & Baichun Xiao, 1999. "Maximizing Revenues of Perishable Assets with a Risk Factor," Operations Research, INFORMS, vol. 47(2), pages 337-341, April.
    15. Constantinos Maglaras & Joern Meissner, 2006. "Dynamic Pricing Strategies for Multiproduct Revenue Management Problems," Manufacturing & Service Operations Management, INFORMS, vol. 8(2), pages 136-148, July.
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    Cited by:

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    2. Koenig, Matthias & Meissner, Joern, 2015. "Value-at-risk optimal policies for revenue management problems," International Journal of Production Economics, Elsevier, vol. 166(C), pages 11-19.
    3. Marla, Lavanya & Rikun, Alexander & Stauffer, Gautier & Pratsini, Eleni, 2020. "Robust modeling and planning: Insights from three industrial applications," Operations Research Perspectives, Elsevier, vol. 7(C).
    4. Bernardo Bertoldi & Chiara Giachino & Alberto Pastore, 2016. "Strategic pricing management in the omnichannel era," MERCATI & COMPETITIVIT?, FrancoAngeli Editore, vol. 2016(4), pages 131-152.
    5. Sato, Kimitoshi & Sawaki, Katsushige, 2013. "A continuous-time dynamic pricing model knowing the competitor’s pricing strategy," European Journal of Operational Research, Elsevier, vol. 229(1), pages 223-229.
    6. Jochen Gönsch & Michael Hassler & Rouven Schur, 2018. "Optimizing conditional value-at-risk in dynamic pricing," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(3), pages 711-750, July.
    7. Ming Chen & Zhi-Long Chen, 2018. "Robust Dynamic Pricing with Two Substitutable Products," Manufacturing & Service Operations Management, INFORMS, vol. 20(2), pages 249-268, May.
    8. Kuo, Chia-Wei & Huang, Kwei-Long, 2012. "Dynamic pricing of limited inventories for multi-generation products," European Journal of Operational Research, Elsevier, vol. 217(2), pages 394-403.
    9. Catherine Cleophas & Daniel Kadatz & Sebastian Vock, 2017. "Resilient revenue management: a literature survey of recent theoretical advances," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 16(5), pages 483-498, October.
    10. Franz Wirl, 2010. "Optimal Pricing of Nondurables when Demand is Dynamic and Stochastic," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 17(2), pages 187-206.
    11. R. Schlosser, 2021. "Scalable relaxation techniques to solve stochastic dynamic multi-product pricing problems with substitution effects," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(1), pages 54-65, February.
    12. Basu, Sanjay, 2011. "Comparing simulation models for market risk stress testing," European Journal of Operational Research, Elsevier, vol. 213(1), pages 329-339, August.
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    14. Sun, Shuxiao & Zheng, Xiaona & Sun, Luping, 2020. "Multi-period pricing in the presence of competition and social influence," International Journal of Production Economics, Elsevier, vol. 227(C).
    15. Gönsch, Jochen, 2017. "A survey on risk-averse and robust revenue management," European Journal of Operational Research, Elsevier, vol. 263(2), pages 337-348.

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    More about this item

    Keywords

    Revenue management Pricing Risk analysis Dynamic programming Capacity control;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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