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Retail Price Optimization at InterContinental Hotels Group

Author

Listed:
  • Dev Koushik

    (Intercontinental Hotels Group, Atlanta, Georgia 30346)

  • Jon A. Higbie

    (Revenue Analytics, Atlanta, Georgia 30339)

  • Craig Eister

    (Intercontinental Hotels Group, Atlanta, Georgia 30346)

Abstract

PERFORM SM with price optimization is the first large-scale enterprise implementation of price optimization in the hospitality industry. The price optimization module determines optimal room rates based on occupancy, price elasticity, and competitive prices. The approach used is a major advancement over existing revenue management systems, which assume that demands by rate segments are independent of price and of each other. As of this writing, over 2,000 InterContinental Hotels Group (IHG) hotels use the price optimization module; all IHG properties will eventually use it. To date, price optimization has achieved $145 million in incremental revenue for IHG. At full rollout, we anticipate that this capability will generate approximately $400 million per year.

Suggested Citation

  • Dev Koushik & Jon A. Higbie & Craig Eister, 2012. "Retail Price Optimization at InterContinental Hotels Group," Interfaces, INFORMS, vol. 42(1), pages 45-57, February.
    • Handle: RePEc:inm:orinte:v:42:y:2012:i:1:p:45-57
    DOI: 10.1287/inte.1110.0620
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Qi (George) Chen & Stefanus Jasin & Izak Duenyas, 2016. "Real-Time Dynamic Pricing with Minimal and Flexible Price Adjustment," Management Science, INFORMS, vol. 62(8), pages 2437-2455, August.
    2. Maxime C. Cohen, & Georgia Perakis & Robert S. Pindyck, 2021. "A Simple Rule for Pricing with Limited Knowledge of Demand," Management Science, INFORMS, vol. 67(3), pages 1608-1621, March.
    3. Michael Murimi & Billy Wadongo & Tom Olielo, 2021. "Determinants of revenue management practices and their impacts on the financial performance of hotels in Kenya: a proposed theoretical framework," Future Business Journal, Springer, vol. 7(1), pages 1-7, December.
    4. Martin Petricek & Stepan Chalupa & David Melas, 2021. "Model of Price Optimization as a Part of Hotel Revenue Management—Stochastic Approach," Mathematics, MDPI, vol. 9(13), pages 1-16, July.
    5. Stefanus Jasin, 2014. "Reoptimization and Self-Adjusting Price Control for Network Revenue Management," Operations Research, INFORMS, vol. 62(5), pages 1168-1178, October.
    6. Pelin Pekgün & Ronald P. Menich & Suresh Acharya & Phillip G. Finch & Frederic Deschamps & Kathleen Mallery & Jim Van Sistine & Kyle Christianson & James Fuller, 2013. "Carlson Rezidor Hotel Group Maximizes Revenue Through Improved Demand Management and Price Optimization," Interfaces, INFORMS, vol. 43(1), pages 21-36, February.
    7. Andrei M. Bandalouski & Natalja G. Egorova & Mikhail Y. Kovalyov & Erwin Pesch & S. Armagan Tarim, 2021. "Dynamic pricing with demand disaggregation for hotel revenue management," Journal of Heuristics, Springer, vol. 27(5), pages 869-885, October.
    8. Övünç Yılmaz & Pelin Pekgün & Mark Ferguson, 2017. "Would You Like to Upgrade to a Premium Room? Evaluating the Benefit of Offering Standby Upgrades," Manufacturing & Service Operations Management, INFORMS, vol. 19(1), pages 1-18, February.
    9. Qi (George) Chen & Stefanus Jasin & Izak Duenyas, 2021. "Technical Note—Joint Learning and Optimization of Multi-Product Pricing with Finite Resource Capacity and Unknown Demand Parameters," Operations Research, INFORMS, vol. 69(2), pages 560-573, March.
    10. Joseph Jiaqi Xu & Peter S. Fader & Senthil Veeraraghavan, 2019. "Designing and Evaluating Dynamic Pricing Policies for Major League Baseball Tickets," Service Science, INFORMS, vol. 21(1), pages 121-138, January.
    11. 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.

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