IDEAS home Printed from https://ideas.repec.org/a/pal/jorapm/v20y2021i1d10.1057_s41272-020-00259-x.html
   My bibliography  Save this article

Dynamic pricing with automated purchase-reservation algorithms

Author

Listed:
  • Kimitoshi Sato

    (Kanagawa University)

Abstract

We consider the problem of a firm that sells a perishable product such as airline tickets or hotel rooms with a dynamic pricing scheme in the presence of Internet bots. The bots automatically check for changes in the selling price every few seconds and hold the price for a short period by making a tentative reservation. Since the bots are not willing to buy the product, the bots’ reservation does not generate revenue for the firm. In addition, such a behavior would temporarily increase the price in conjunction with decreasing the inventory level. In this paper, we formulate a dynamic pricing model that accounts for tentative reservations made by bots, and derive an optimal pricing policy so as to maximize the total expected revenue. We show the monotone properties of the optimal price: (1) the optimal price decreases with inventory at any given timestep; (2) the optimal price decreases over time even if there is a temporary inventory decrease due to bot reservations. We demonstrate numerically that the optimal pricing policy is robust against the presence of bots, and further show that, as bot activity increases, the optimal price tends to decrease in the first portion of the sales interval.

Suggested Citation

  • Kimitoshi Sato, 2021. "Dynamic pricing with automated purchase-reservation algorithms," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(1), pages 33-41, February.
  • Handle: RePEc:pal:jorapm:v:20:y:2021:i:1:d:10.1057_s41272-020-00259-x
    DOI: 10.1057/s41272-020-00259-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41272-020-00259-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1057/s41272-020-00259-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mika Sumida & Huseyin Topaloglu, 2019. "An Approximation Algorithm for Capacity Allocation Over a Single Flight Leg with Fare-Locking," INFORMS Journal on Computing, INFORMS, vol. 31(1), pages 83-99, February.
    2. 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.
    3. Sato, Kimitoshi, 2019. "Price Trends and Dynamic Pricing in Perishable Product Market Consisting of Superior and Inferior Firms," European Journal of Operational Research, Elsevier, vol. 274(1), pages 214-226.
    4. Xiaowei Xu & Wallace J. Hopp, 2009. "Technical Note---Price Trends in a Dynamic Pricing Model with Heterogeneous Customers: A Martingale Perspective," Operations Research, INFORMS, vol. 57(5), pages 1298-1302, October.
    5. Yuri Levin & Jeff McGill & Mikhail Nediak, 2007. "Price Guarantees in Dynamic Pricing and Revenue Management," Operations Research, INFORMS, vol. 55(1), pages 75-97, February.
    6. Chen, Ming & Chen, Zhi-Long, 2019. "Uncertain about your travel plan? Lock it and decide later: Dynamic pricing with a fare-lock option," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 1-26.
    7. Zhan Pang & Oded Berman & Ming Hu, 2015. "Up Then Down: Bid-Price Trends in Revenue Management," Production and Operations Management, Production and Operations Management Society, vol. 24(7), pages 1135-1147, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sato, Kimitoshi, 2019. "Price Trends and Dynamic Pricing in Perishable Product Market Consisting of Superior and Inferior Firms," European Journal of Operational Research, Elsevier, vol. 274(1), pages 214-226.
    2. Chen, Ming & Chen, Zhi-Long, 2019. "Uncertain about your travel plan? Lock it and decide later: Dynamic pricing with a fare-lock option," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 1-26.
    3. Schlosser, Rainer, 2015. "Dynamic pricing and advertising of perishable products with inventory holding costs," Journal of Economic Dynamics and Control, Elsevier, vol. 57(C), pages 163-181.
    4. Ningyuan Chen & Guillermo Gallego, 2019. "Welfare Analysis of Dynamic Pricing," Management Science, INFORMS, vol. 65(1), pages 139-151, January.
    5. Yuri Levin & Jeff McGill & Mikhail Nediak, 2008. "Risk in Revenue Management and Dynamic Pricing," Operations Research, INFORMS, vol. 56(2), pages 326-343, April.
    6. Wanyang Dai, 2022. "Optimal policy computing for blockchain based smart contracts via federated learning," Operational Research, Springer, vol. 22(5), pages 5817-5844, November.
    7. Omar Besbes & Dan A. Iancu & Nikolaos Trichakis, 2018. "Dynamic Pricing Under Debt: Spiraling Distortions and Efficiency Losses," Management Science, INFORMS, vol. 64(10), pages 4572-4589, October.
    8. Yuri Levin & Mikhail Nediak & Andrei Bazhanov, 2014. "Quantity Premiums and Discounts in Dynamic Pricing," Operations Research, INFORMS, vol. 62(4), pages 846-863, August.
    9. Xing Hu & Zhixi Wan & Nagesh N. Murthy, 2019. "Dynamic Pricing of Limited Inventories with Product Returns," Manufacturing & Service Operations Management, INFORMS, vol. 21(3), pages 501-518, July.
    10. Yusen Xia & Jian Yang & Tingting Zhou, 2019. "Revenue management under randomly evolving economic conditions," Naval Research Logistics (NRL), John Wiley & Sons, vol. 66(1), pages 73-89, February.
    11. Chatwin, Richard E., 2000. "Optimal dynamic pricing of perishable products with stochastic demand and a finite set of prices," European Journal of Operational Research, Elsevier, vol. 125(1), pages 149-174, August.
    12. Schulte, Benedikt & Sachs, Anna-Lena, 2020. "The price-setting newsvendor with Poisson demand," European Journal of Operational Research, Elsevier, vol. 283(1), pages 125-137.
    13. Ali Hortaçsu & Olivia R. Natan & Hayden Parsley & Timothy Schwieg & Kevin R. Williams, 2021. "Organizational Structure and Pricing: Evidence from a Large U.S. Airline," NBER Working Papers 29508, National Bureau of Economic Research, Inc.
    14. Dasci, A. & Karakul, M., 2009. "Two-period dynamic versus fixed-ratio pricing in a capacity constrained duopoly," European Journal of Operational Research, Elsevier, vol. 197(3), pages 945-968, September.
    15. Aniruddha Dutta, 2019. "Capacity Allocation of Game Tickets Using Dynamic Pricing," Data, MDPI, vol. 4(4), pages 1-12, October.
    16. Namin, Aidin & Soysal, Gonca P. & Ratchford, Brian T., 2022. "Alleviating demand uncertainty for seasonal goods: An analysis of attribute-based markdown policy for fashion retailers," Journal of Business Research, Elsevier, vol. 145(C), pages 671-681.
    17. Yiwei Chen & Nikolaos Trichakis, 2021. "Technical Note—On Revenue Management with Strategic Customers Choosing When and What to Buy," Operations Research, INFORMS, vol. 69(1), pages 175-187, January.
    18. Davide Crapis & Bar Ifrach & Costis Maglaras & Marco Scarsini, 2017. "Monopoly Pricing in the Presence of Social Learning," Management Science, INFORMS, vol. 63(11), pages 3586-3608, November.
    19. Qi Chen & Qi Xu & Wenjie Wang, 2019. "Optimal Policies for the Pricing and Replenishment of Fashion Apparel considering the Effect of Fashion Level," Complexity, Hindawi, vol. 2019, pages 1-12, February.
    20. Adam J. Mersereau & Dan Zhang, 2012. "Markdown Pricing with Unknown Fraction of Strategic Customers," Manufacturing & Service Operations Management, INFORMS, vol. 14(3), pages 355-370, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:jorapm:v:20:y:2021:i:1:d:10.1057_s41272-020-00259-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.palgrave.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.