IDEAS home Printed from https://ideas.repec.org/a/inm/orinte/v43y2013i1p21-36.html
   My bibliography  Save this article

Carlson Rezidor Hotel Group Maximizes Revenue Through Improved Demand Management and Price Optimization

Author

Listed:
  • Pelin Pekgün

    (JDA Software Group, Marietta, Georgia 30067; currently at Moore School of Business, University of South Carolina, Columbia, South Carolina 29208)

  • Ronald P. Menich

    (JDA Software Group, Marietta, Georgia 30067)

  • Suresh Acharya

    (JDA Software Group, Marietta, Georgia 30067)

  • Phillip G. Finch

    (JDA Software Group, Marietta, Georgia 30067)

  • Frederic Deschamps

    (Carlson Rezidor Hotel Group, Minnetonka, Minnesota 55305)

  • Kathleen Mallery

    (Carlson Rezidor Hotel Group, Minnetonka, Minnesota 55305)

  • Jim Van Sistine

    (Carlson Rezidor Hotel Group, Minnetonka, Minnesota 55305)

  • Kyle Christianson

    (Carlson Rezidor Hotel Group, Minnetonka, Minnesota 55305)

  • James Fuller

    (Carlson Rezidor Hotel Group, Omaha, Nebraska 68164)

Abstract

Under changing market conditions for the hospitality industry, the Carlson Rezidor Hotel Group (CRHG) collaborated with JDA Software Group to use operations research to drive higher revenue for its hoteliers and to stay ahead of the competition. This highly innovative revenue optimization project, Stay Night Automated Pricing (SNAP), started with enterprise demand forecasting across 600 US hotels in 2007. It was followed by a large-scale network optimization solution to dynamically optimize hotel room rates based on price elasticity of demand, competitor rates, availability of remaining inventory, demand forecasts, and business rules. All North American hotels were operational in SNAP by March 2011. Starting from the optimization prototyping results in 2008, CRHG consistently measured a 2–4 percent revenue improvement in compliant hotels over noncompliant ones. To date, compliant hotels have increased revenue by more than $16 million annually. After a successful deployment in the Americas, CRHG extended the partnership with JDA to globally roll out SNAP, with an initial focus on Europe, the Middle East, Africa, and the Asia Pacific region. CRHG anticipates that the worldwide incremental revenue from this solution will exceed $30 million annually.

Suggested Citation

  • 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.
    • Handle: RePEc:inm:orinte:v:43:y:2013:i:1:p:21-36
    DOI: 10.1287/inte.1120.0660
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/inte.1120.0660
    Download Restriction: no
    File URL: https://libkey.io/10.1287/inte.1120.0660?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
    ---><---

    References listed on IDEAS

    as
    1. Weatherford, Larry R. & Kimes, Sheryl E., 2003. "A comparison of forecasting methods for hotel revenue management," International Journal of Forecasting, Elsevier, vol. 19(3), pages 401-415.
    2. Dev Koushik & Jon A. Higbie & Craig Eister, 2012. "Retail Price Optimization at InterContinental Hotels Group," Interfaces, INFORMS, vol. 42(1), pages 45-57, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ivanov, Stanislav Hristov & Webster, Craig & Stoilova, Elitza & Slobodskoy, Daniel, 2020. "Biosecurity, crisis management, automation technologies, and economic performance of travel, tourism and hospitality companies – a conceptual framework," SocArXiv 2hx6f, Center for Open Science.
    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. Mihai Banciu & Andreas Hinterhuber & Fredrik Ødegaard, 2023. "Revenue management in sports, live entertainment and arts," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 22(3), pages 185-187, June.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Stefanus Jasin, 2014. "Reoptimization and Self-Adjusting Price Control for Network Revenue Management," Operations Research, INFORMS, vol. 62(5), pages 1168-1178, October.
    10. Arenoe, Bjorn & van der Rest, Jean-Pierre I. & Kattuman, Paul, 2015. "Game theoretic pricing models in hotel revenue management: An equilibrium choice-based conjoint analysis approach," Tourism Management, Elsevier, vol. 51(C), pages 96-102.
    11. Stanislav Hristov Ivanov & Craig Webster & Elitza Stoilova & Daniel Slobodskoy, 2022. "Biosecurity, crisis management, automation technologies and economic performance of travel, tourism and hospitality companies – A conceptual framework," Tourism Economics, , vol. 28(1), pages 3-26, February.
    12. Klein, Robert & Koch, Sebastian & Steinhardt, Claudius & Strauss, Arne K., 2020. "A review of revenue management: Recent generalizations and advances in industry applications," European Journal of Operational Research, Elsevier, vol. 284(2), pages 397-412.
    13. 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.

    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. 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.
    2. Yang, Xin & Pan, Bing & Evans, James A. & Lv, Benfu, 2015. "Forecasting Chinese tourist volume with search engine data," Tourism Management, Elsevier, vol. 46(C), pages 386-397.
    3. Doris Chenguang Wu & Shiteng Zhong & Richard T R Qiu & Ji Wu, 2022. "Are customer reviews just reviews? Hotel forecasting using sentiment analysis," Tourism Economics, , vol. 28(3), pages 795-816, May.
    4. 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.
    5. Hanyuan Zhang & Jiangping Lu, 2022. "Forecasting hotel room demand amid COVID-19," Tourism Economics, , vol. 28(1), pages 200-221, February.
    6. Binru Zhang & Yulian Pu & Yuanyuan Wang & Jueyou Li, 2019. "Forecasting Hotel Accommodation Demand Based on LSTM Model Incorporating Internet Search Index," Sustainability, MDPI, vol. 11(17), pages 1-14, August.
    7. 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.
    8. Guizzardi, Andrea & Pons, Flavio Maria Emanuele & Angelini, Giovanni & Ranieri, Ercolino, 2021. "Big data from dynamic pricing: A smart approach to tourism demand forecasting," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1049-1060.
    9. Valerio Lacagnina & Davide Provenzano, 2016. "An integrated fuzzy-stochastic model for revenue management," Tourism Economics, , vol. 22(4), pages 779-792, August.
    10. Haensel, Alwin & Koole, Ger, 2011. "Booking horizon forecasting with dynamic updating: A case study of hotel reservation data," International Journal of Forecasting, Elsevier, vol. 27(3), pages 942-960, July.
    11. Guizzardi, Andrea & Ballestra, Luca Vincenzo & D'Innocenzo, Enzo, 2022. "Hotel dynamic pricing, stochastic demand and covid-19," Annals of Tourism Research, Elsevier, vol. 97(C).
    12. 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.
    13. Stefanus Jasin, 2014. "Reoptimization and Self-Adjusting Price Control for Network Revenue Management," Operations Research, INFORMS, vol. 62(5), pages 1168-1178, October.
    14. Ikeda, Shunnosuke & Nishimura, Naoki & Sukegawa, Noriyoshi & Takano, Yuichi, 2023. "Prescriptive price optimization using optimal regression trees," Operations Research Perspectives, Elsevier, vol. 11(C).
    15. Ulrich Gunter, 2021. "Improving Hotel Room Demand Forecasts for Vienna across Hotel Classes and Forecast Horizons: Single Models and Combination Techniques Based on Encompassing Tests," Forecasting, MDPI, vol. 3(4), pages 1-36, November.
    16. Anna Maria Fiori & Ilaria Foroni, 2019. "Reservation Forecasting Models for Hospitality SMEs with a View to Enhance Their Economic Sustainability," Sustainability, MDPI, vol. 11(5), pages 1-24, February.
    17. Diego A. B. Marconatto & Gaspar A. Peixoto & Emidio G. Teixeira & Adelar Fochezatto, 2022. "Women on the Front Line: The Growth of SMEs during Crises," Sustainability, MDPI, vol. 14(16), pages 1-18, August.
    18. Timothy Webb, 2016. "From travel agents to OTAs: How the evolution of consumer booking behavior has affected revenue management," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 15(3), pages 276-282, July.
    19. Miguel Angel Ropero, 2019. "Pricing Policies in a Market With Asymmetric Information and Non-Bayesian Firms," Annals of Economics and Finance, Society for AEF, vol. 20(2), pages 541-563, November.
    20. Jin Qin & Xiqiong Li & Kang Yang & Guangming Xu, 2022. "Joint Optimization of Ticket Pricing Strategy and Train Stop Plan for High-Speed Railway: A Case Study," Mathematics, MDPI, vol. 10(10), pages 1-17, May.

    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:inm:orinte:v:43:y:2013:i:1:p:21-36. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.