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The history of forecasting models in revenue management

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  • Larry Weatherford

    (College of Business, University of Wyoming, Dept.3275)

Abstract

Forecasting has been used in revenue management (RM) for nearly the last 60 years. This brief, historical article surveys over 80 articles from the recent period and traces the evolution of RM forecasting models. The natural breakdown of forecasting sub-categories that are covered within the airline industry include: origin–destination forecasting and whether to aggregate or disaggregate the data, user adjustment, hybrid forecasting in less-restricted fare environments, seasonality, forecast accuracy and choice-based forecasting. We also review RM forecasting in the hotel and other industries.

Suggested Citation

  • Larry Weatherford, 2016. "The history of forecasting models in revenue management," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 15(3), pages 212-221, July.
    • Handle: RePEc:pal:jorapm:v:15:y:2016:i:3:d:10.1057_rpm.2016.18
    DOI: 10.1057/rpm.2016.18
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    References listed on IDEAS

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    2. Jeffrey I. McGill & Garrett J. van Ryzin, 1999. "Revenue Management: Research Overview and Prospects," Transportation Science, INFORMS, vol. 33(2), pages 233-256, May.
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    8. 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.
    9. Barry C. Smith & John F. Leimkuhler & Ross M. Darrow, 1992. "Yield Management at American Airlines," Interfaces, INFORMS, vol. 22(1), pages 8-31, February.
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    Cited by:

    1. Larry Weatherford, 2018. "Simulation shows not to panic about bid price dysfunction close to departure," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 17(6), pages 403-419, December.
    2. Timothy Webb, 2022. "Forecasting at capacity: the bias of unconstrained forecasts in model evaluation," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(6), pages 645-656, December.
    3. Ian Yeoman, 2022. "The continuing evolution of revenue management science," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(1), pages 1-2, February.
    4. Ernst Ahlberg & Irina Mirkina & Alfred Olsson & Christian Söyland & Lars Carlsson, 2023. "On the selection of relevant historical demand data for revenue management applied to transportation," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 22(4), pages 266-275, August.
    5. Resul Aydemir & Mehmet Melih Değirmenci & Abdullah Bilgin, 2023. "Estimation of passenger sell-up rates in airline revenue management by considering the effect of fare class availability," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 22(6), pages 501-513, December.
    6. Rennie, Nicola & Cleophas, Catherine & Sykulski, Adam M. & Dost, Florian, 2021. "Identifying and responding to outlier demand in revenue management," European Journal of Operational Research, Elsevier, vol. 293(3), pages 1015-1030.
    7. Martin Petříček & Štěpán Chalupa & Věra Levičková, 2022. "Comparison of expected marginal revenue models in the hospitality industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(3), pages 299-305, June.
    8. Kavitha Balaiyan & R. K. Amit & Atul Kumar Malik & Xiaodong Luo & Amit Agarwal, 2019. "Joint forecasting for airline pricing and revenue management," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 18(6), pages 465-482, December.
    9. Muzaffer Buyruk & Ertan Güner, 2022. "Personalization in airline revenue management: an overview and future outlook," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(2), pages 129-139, April.
    10. 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.

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