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From travel agents to OTAs: How the evolution of consumer booking behavior has affected revenue management

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  • Timothy Webb

    (Virginia Polytechnic Institute
    Delaware North Companies)

Abstract

Travel booking behavior has changed substantially over the past two decades. The traditional approach of utilizing travel agents and booking ahead has evolved into a fast-paced, last-minute booking environment. This evolution has had substantial effects on revenue management (RM) in the areas of forecasting, pricing and online travel agency inventory allocations. These changes have made understanding the consumer booking process a necessary requirement for success. This article reviews the relevant literature on this historical shift and the effects it has had on RM.

Suggested Citation

  • 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.
    • Handle: RePEc:pal:jorapm:v:15:y:2016:i:3:d:10.1057_rpm.2016.16
    DOI: 10.1057/rpm.2016.16
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    References listed on IDEAS

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    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. Xuanming Su, 2007. "Intertemporal Pricing with Strategic Customer Behavior," Management Science, INFORMS, vol. 53(5), pages 726-741, May.
    3. Kinshuk Jerath & Serguei Netessine & Senthil K. Veeraraghavan, 2010. "Revenue Management with Strategic Customers: Last-Minute Selling and Opaque Selling," Management Science, INFORMS, vol. 56(3), pages 430-448, March.
    4. 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.
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    Citations

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    Cited by:

    1. Zvi Schwartz & Timothy Webb & Jean-Pierre I van der Rest & Larissa Koupriouchina, 2021. "Enhancing the accuracy of revenue management system forecasts: The impact of machine and human learning on the effectiveness of hotel occupancy forecast combinations across multiple forecasting horizo," Tourism Economics, , vol. 27(2), pages 273-291, March.
    2. Carmen Berne-Manero & Maria Gómez-Campillo & Mercedes Marzo-Navarro & Marta Pedraja-Iglesias, 2018. "Reviewing the Online Tourism Value Chain," Administrative Sciences, MDPI, vol. 8(3), pages 1-18, August.
    3. Slak Valek, Nataša, 2015. "Tourism expenditure according to mode of transportation: A comparative study between 2009 and 2012," MPRA Paper 77406, University Library of Munich, Germany, revised 07 Oct 2015.
    4. Alderighi, Marco & Nava, Consuelo R. & Calabrese, Matteo & Christille, Jean-Marc & Salvemini, Chiara B., 2022. "Consumer perception of price fairness and dynamic pricing: Evidence from Booking.com," Journal of Business Research, Elsevier, vol. 145(C), pages 769-783.
    5. Seung Hyun Lee & Cynthia S. Deale & Jaeyong Lee, 2022. "Does it pay to book direct?: Customers’ perceptions of online channel distributors, price, and loyalty membership on brand dimensions," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(6), pages 657-667, December.
    6. 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).
    7. Miriam Scaglione & Coin Johnson & Pascale Favre, 2019. "As time goes by: last minute momentum booking and the planned vacation process," Information Technology & Tourism, Springer, vol. 21(1), pages 9-22, March.
    8. Kwanglim Seo, 2019. "Same-day discounting’s effect on consumers’ evaluations of a hotel," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 18(2), pages 107-111, April.
    9. Martin Falk & Markku Vieru, 2019. "Myth of early booking gains," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 18(1), pages 52-64, February.

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