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Marriott International Increases Revenue by Implementing a Group Pricing Optimizer

Author

Listed:
  • Sharon Hormby

    (Marriott International, Inc., Bethesda, Maryland 20817)

  • Julia Morrison

    (Marriott International, Inc., Bethesda, Maryland 20817)

  • Prashant Dave

    (Marriott International, Inc., Bethesda, Maryland 20817)

  • Michele Meyers

    (Marriott International, Inc., Bethesda, Maryland 20817)

  • Tim Tenca

    (Marriott International, Inc., Bethesda, Maryland 20817)

Abstract

Marriott International's Group Pricing Optimizer (GPO), a decision support system, provides guidance to Marriott personnel on pricing hotel rooms for group customers. GPO uses demand segmentation, price-elasticity modeling, and optimization techniques to recommend an optimal rate. In operation since late 2006, the system has improved Marriott's hotel profitability and enhanced the sales process for both sales managers and customers.

Suggested Citation

  • Sharon Hormby & Julia Morrison & Prashant Dave & Michele Meyers & Tim Tenca, 2010. "Marriott International Increases Revenue by Implementing a Group Pricing Optimizer," Interfaces, INFORMS, vol. 40(1), pages 47-57, February.
    • Handle: RePEc:inm:orinte:v:40:y:2010:i:1:p:47-57
    DOI: 10.1287/inte.1090.0482
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    Citations

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    Cited by:

    1. Huashuai Qu & Ilya O. Ryzhov & Michael C. Fu & Eric Bergerson & Megan Kurka & Ludek Kopacek, 2020. "Learning Demand Curves in B2B Pricing: A New Framework and Case Study," Production and Operations Management, Production and Operations Management Society, vol. 29(5), pages 1287-1306, May.
    2. Martin Petricek & Stepan Chalupa & Karel Chadt, 2020. "Identification of Consumer Behavior Based on Price Elasticity: A Case Study of the Prague Market of Accommodation Services," Sustainability, MDPI, vol. 12(22), pages 1-14, November.
    3. Aldric Vives & Marta Jacob & Eugeni Aguiló, 2019. "Online hotel demand model and own-price elasticities: An empirical application in a mature resort destination," Tourism Economics, , vol. 25(5), pages 670-694, August.
    4. Breffni M Noone, 2016. "Pricing for hotel revenue management: Evolution in an era of price transparency," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 15(3), pages 264-269, July.
    5. Larissa Koupriouchina & Jean-Pierre van der Rest & Zvi Schwartz, 2023. "Judgmental Adjustments of Algorithmic Hotel Occupancy Forecasts: Does User Override Frequency Impact Accuracy at Different Time Horizons?," Tourism Economics, , vol. 29(8), pages 2143-2164, December.
    6. Aldric Vives & Marta Jacob & Marga Payeras, 2018. "Revenue management and price optimization techniques in the hotel sector," Tourism Economics, , vol. 24(6), pages 720-752, September.
    7. Justin Beck & John Harvey & Kristina Kaylen & Corrado Sala & Melinda Urban & Peter Vermeulen & Norman Wilken & Wei Xie & Dan Iliescu & Pratik Mital, 2021. "Carnival Optimizes Revenue and Inventory Across Heterogenous Cruise Line Brands," Interfaces, INFORMS, vol. 51(1), pages 26-41, February.
    8. Ziad Alrawadieh & Zaid Alrawadieh & Gurel Cetin, 2021. "Digital transformation and revenue management: Evidence from the hotel industry," Tourism Economics, , vol. 27(2), pages 328-345, March.

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