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Optimal Multiperiod Pricing with Service Guarantees

Author

Listed:
  • Christian Borgs

    (Microsoft Research, New England Lab, Cambridge, Massachusetts 02142)

  • Ozan Candogan

    (Fuqua School of Business, Duke University, Durham, North Carolina 27708)

  • Jennifer Chayes

    (Microsoft Research, New England Lab, Cambridge, Massachusetts 02142)

  • Ilan Lobel

    (Stern School of Business, New York University, New York, New York 10012)

  • Hamid Nazerzadeh

    (Marshall School of Business, University of Southern California, Los Angeles, California 90089)

Abstract

We study the multiperiod pricing problem of a service firm with capacity levels that vary over time. Customers are heterogeneous in their arrival and departure periods as well as valuations, and are fully strategic with respect to their purchasing decisions. The firm's problem is to set a sequence of prices that maximizes its revenue while guaranteeing service to all paying customers. We provide a dynamic programming based algorithm that computes the optimal sequence of prices for this problem in polynomial time. We show that due to the presence of strategic customers, available service capacity at a time period may bind the price offered at another time period. This phenomenon leads the firm to utilize the same price in multiple periods, in effect limiting the number of different prices that the service firm utilizes in optimal price policies. Also, when customers become more strategic (patient for service), the firm offers higher prices. This may lead to the underutilization of capacity, lower revenues, and reduced customer welfare. We observe that the firm can combat this problem if it has an ability, beyond posted prices, to direct customers to different service periods. This paper was accepted by Dimitris Bertsimas, optimization.

Suggested Citation

  • Christian Borgs & Ozan Candogan & Jennifer Chayes & Ilan Lobel & Hamid Nazerzadeh, 2014. "Optimal Multiperiod Pricing with Service Guarantees," Management Science, INFORMS, vol. 60(7), pages 1792-1811, July.
    • Handle: RePEc:inm:ormnsc:v:60:y:2014:i:7:p:1792-1811
    DOI: 10.1287/mnsc.2013.1839
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    References listed on IDEAS

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    Cited by:

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    3. Yiwei Chen & Vivek F. Farias & Nikolaos Trichakis, 2019. "On the Efficacy of Static Prices for Revenue Management in the Face of Strategic Customers," Management Science, INFORMS, vol. 65(12), pages 5535-5555, December.
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    6. Jiang, Yuanchun & Liu, Yezheng & Shang, Jennifer & Yildirim, Pinar & Zhang, Qingfu, 2018. "Optimizing online recurring promotions for dual-channel retailers: Segmented markets with multiple objectives," European Journal of Operational Research, Elsevier, vol. 267(2), pages 612-627.
    7. Yanzhe (Murray) Lei & Stefanus Jasin, 2020. "Real-Time Dynamic Pricing for Revenue Management with Reusable Resources, Advance Reservation, and Deterministic Service Time Requirements," Operations Research, INFORMS, vol. 68(3), pages 676-685, May.
    8. Yiwei Chen & Vivek F. Farias, 2018. "Robust Dynamic Pricing with Strategic Customers," Mathematics of Operations Research, INFORMS, vol. 43(4), pages 1119-1142, November.
    9. Vibhanshu Abhishek & Mustafa Dogan & Alexandre Jacquillat, 2021. "Strategic Timing and Dynamic Pricing for Online Resource Allocation," Management Science, INFORMS, vol. 67(8), pages 4880-4907, August.
    10. Egan, Malcolm & Jakob, Michal, 2016. "Market mechanism design for profitable on-demand transport services," Transportation Research Part B: Methodological, Elsevier, vol. 89(C), pages 178-195.
    11. Andre P. Calmon & Florin D. Ciocan & Gonzalo Romero, 2021. "Revenue Management with Repeated Customer Interactions," Management Science, INFORMS, vol. 67(5), pages 2944-2963, May.
    12. Negin Golrezaei & Hamid Nazerzadeh & Ramandeep Randhawa, 2020. "Dynamic Pricing for Heterogeneous Time-Sensitive Customers," Manufacturing & Service Operations Management, INFORMS, vol. 22(3), pages 562-581, May.
    13. Hossein Jahandideh & Julie Ward Drew & Filippo Balestrieri & Kevin McCardle, 2020. "Individualized Pricing for a Cloud Provider Hosting Interactive Applications," Service Science, INFORMS, vol. 12(4), pages 130-147, December.
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    15. Yiwei Chen & Ming Hu, 2020. "Pricing and Matching with Forward-Looking Buyers and Sellers," Manufacturing & Service Operations Management, INFORMS, vol. 22(4), pages 717-734, July.
    16. Omar Besbes & Ilan Lobel, 2015. "Intertemporal Price Discrimination: Structure and Computation of Optimal Policies," Management Science, INFORMS, vol. 61(1), pages 92-110, January.
    17. Zubair Khalid & Ghulam Abbas & Muhammad Awais & Thamer Alquthami & Muhammad Babar Rasheed, 2020. "A Novel Load Scheduling Mechanism Using Artificial Neural Network Based Customer Profiles in Smart Grid," Energies, MDPI, vol. 13(5), pages 1-23, February.
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    19. Alex Gershkov & Benny Moldovanu & Philipp Strack, 2018. "Revenue-Maximizing Mechanisms with Strategic Customers and Unknown, Markovian Demand," Management Science, INFORMS, vol. 64(5), pages 2031-2046, May.

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