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Choice-Based Dynamic Pricing for Vacation Rentals

Author

Listed:
  • Yaping Wang

    (Verizon, New York, New York 10007)

  • Kelly McGuire

    (ZS Associates, Washington District of Columbia 20814)

  • Jeremy Terbush

    (Simon Property Group, Indianapolis, Indiana 46204)

  • Michael Towns

    (RCI/Wyndham Destinations, Tuxedo Park, New York 10987)

  • Chris K. Anderson

    (SC Johnson College of Business, School of Administration, Cornell University, Ithaca, New York 14853)

Abstract

In this paper, we propose a new dynamic pricing approach for the vacation rental revenue management problem. The proposed approach is based on a conditional logistic regression that predicts the purchasing probability for rental units as a function of various factors, such as lead time, availability, property features, and market selling prices. In order to estimate the price sensitivity throughout the booking horizon, a rolling window technique is provided to smooth the impact over time and build a consistent estimation. We apply a nonlinear optimization algorithm to determine optimal prices to maximize the revenue, considering current demand, availability from both the rental company and its competitors, and the price sensitivity of the rental guest. A booking curve heuristic is used to align the booking pace with business targets and feed the adjustments back into the optimization routine. We illustrate the proposed approach by successfully applying it to the revenue management problem of Wyndham Destinations vacation rentals. Model performance is evaluated by pricing two regions within the Wyndham network for part of the 2018 vacation season, indicating revenue per unit growth of 3.5% and 5.2% (for the two regions) through model use.

Suggested Citation

  • Yaping Wang & Kelly McGuire & Jeremy Terbush & Michael Towns & Chris K. Anderson, 2021. "Choice-Based Dynamic Pricing for Vacation Rentals," Interfaces, INFORMS, vol. 51(6), pages 450-462, November.
    • Handle: RePEc:inm:orinte:v:51:y:2021:i:6:p:450-462
    DOI: 10.1287/inte.2021.1075
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    References listed on IDEAS

    as
    1. Chris K. Anderson & Xiaoqing (Kristine) Xie, 2016. "Dynamic pricing in hospitality: overview and opportunities," International Journal of Revenue Management, Inderscience Enterprises Ltd, vol. 9(2/3), pages 165-174.
    2. Guillermo Gallego & Richard Ratliff & Sergey Shebalov, 2015. "A General Attraction Model and Sales-Based Linear Program for Network Revenue Management Under Customer Choice," Operations Research, INFORMS, vol. 63(1), pages 212-232, February.
    3. Marcel L. Corstjens & David A. Gautschi, 1983. "Formal Choice Models in Marketing," Marketing Science, INFORMS, vol. 2(1), pages 19-56.
    4. Wedad Elmaghraby & P{i}nar Keskinocak, 2003. "Dynamic Pricing in the Presence of Inventory Considerations: Research Overview, Current Practices, and Future Directions," Management Science, INFORMS, vol. 49(10), pages 1287-1309, October.
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