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Dynamic pricing – The next revolution in RM?

Author

Listed:
  • Thomas Fiig

    (Amadeus Airline IT)

  • Oriana Goyons

    (Amadeus Airline IT, Amadeus S.A.S.)

  • Robin Adelving

    (Amadeus Airline IT, Amadeus S.A.S.)

  • Barry Smith

    (Barry C Smith LLC)

Abstract

Existing revenue management systems (RMS) base their recommendations on historic observations and do not explicitly consider competition. This means that RMS recommendations often are not appropriate for real-time competitive situations. Dynamic pricing (DP) is an extension of RMS that dynamically calculates the optimal price, taking into account the airline’s strategy, customer-specific information and real-time alternative offerings. By optimizing the contribution within the shopping session, DP has a more current and detailed view of demand and can improve RMS performance. We investigated the performance of DP using two simulators, Altéa Benchmarking Engine and Passenger Origin Destination Simulator and demonstrate that DP can deliver substantial revenue benefits with no modification to existing revenue management (RM) processes. However, the deployment of DP into the airline distribution process will be a challenge, because it affects all shopping and downstream processes, such as ticketing, servicing, revenue accounting, RM and interline settlement, that rely on information from existing fare aggregators. Nevertheless, the potential benefits of DP are so compelling that we believe the effort to bring this technology into practice is warranted.

Suggested Citation

  • Thomas Fiig & Oriana Goyons & Robin Adelving & Barry Smith, 2016. "Dynamic pricing – The next revolution in RM?," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 15(5), pages 360-379, October.
    • Handle: RePEc:pal:jorapm:v:15:y:2016:i:5:d:10.1057_rpm.2016.28
    DOI: 10.1057/rpm.2016.28
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    References listed on IDEAS

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    1. Guillermo Gallego & Garrett van Ryzin, 1994. "Optimal Dynamic Pricing of Inventories with Stochastic Demand over Finite Horizons," Management Science, INFORMS, vol. 40(8), pages 999-1020, August.
    2. Kalyan Talluri & Garrett van Ryzin, 2004. "Revenue Management Under a General Discrete Choice Model of Consumer Behavior," Management Science, INFORMS, vol. 50(1), pages 15-33, January.
    3. Wen Zhao & Yu-Sheng Zheng, 2000. "Optimal Dynamic Pricing for Perishable Assets with Nonhomogeneous Demand," Management Science, INFORMS, vol. 46(3), pages 375-388, March.
    4. Guillermo Gallego & Woonghee Tim Huh & Wanmo Kang & Robert Phillips, 2006. "Price Competition with the Attraction Demand Model: Existence of Unique Equilibrium and Its Stability," Manufacturing & Service Operations Management, INFORMS, vol. 8(4), pages 359-375, June.
    5. Gustavo Vulcano & Garrett van Ryzin & Richard Ratliff, 2012. "Estimating Primary Demand for Substitutable Products from Sales Transaction Data," Operations Research, INFORMS, vol. 60(2), pages 313-334, April.
    6. Guillermo Gallego & Ming Hu, 2014. "Dynamic Pricing of Perishable Assets Under Competition," Management Science, INFORMS, vol. 60(5), pages 1241-1259, May.
    7. Barry C. Smith & Ross Darrow & John Elieson & Dirk Guenther & B. Venkateshwara Rao & Faker Zouaoui, 2007. "Travelocity Becomes a Travel Retailer," Interfaces, INFORMS, vol. 37(1), pages 68-81, February.
    8. William L. Cooper & Tito Homem-de-Mello & Anton J. Kleywegt, 2006. "Models of the Spiral-Down Effect in Revenue Management," Operations Research, INFORMS, vol. 54(5), pages 968-987, October.
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    Cited by:

    1. Jost Daft & Sascha Albers & Sebastian Stabenow, 2021. "From product-oriented flight providers to customer-centric retailers: a dynamic offering framework and implementation guidelines for airlines," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(6), pages 615-625, December.
    2. Michael D. Wittman & Peter P. Belobaba, 2019. "Dynamic pricing mechanisms for the airline industry: a definitional framework," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 18(2), pages 100-106, April.
    3. Stacey Mumbower & Susan Hotle & Laurie A. Garrow, 2023. "Highly debated but still unbundled: The evolution of U.S. airline ancillary products and pricing strategies," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 22(4), pages 276-293, August.
    4. Kevin K. Wang & Michael D. Wittman & Adam Bockelie, 2021. "Dynamic offer generation in airline revenue management," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(6), pages 654-668, December.
    5. Daniel Schubert & Christa Sys & Rosário Macário, 2022. "Customized airline offer management: a conceptual architecture," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(5), pages 553-563, October.
    6. Michael D. Wittman & Thomas Fiig & Peter P. Belobaba, 2018. "A dynamic pricing engine for multiple substitutable flights," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 17(6), pages 420-435, December.
    7. Kevin K. Wang & Michael D. Wittman & Thomas Fiig, 2023. "Dynamic offer creation for airline ancillaries using a Markov chain choice model," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 22(2), pages 103-121, April.
    8. Bazyli Szymański & Peter P. Belobaba & Alexander Papen, 2021. "Continuous pricing algorithms for airline RM: revenue gains and competitive impacts," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(6), pages 669-688, December.

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