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A stochastic dynamic pricing model for the multiclass problems in the airline industry

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  • Otero, Daniel F.
  • Akhavan-Tabatabaei, Raha

Abstract

In the airline industry, deciding the ticket price for each flight directly affects the number of people that in the future will try to buy a ticket. Depending on the willingness-to-pay of the customers the flight might take off with empty seats or seats sold at a lower price. Therefore, based on the behavior of the customers, a price must be fixed for each type of product in each period. We propose a stochastic dynamic pricing model to solve this problem, applying phase type distributions and renewal processes to model the inter-arrival time between two customers that book a ticket and the probability that a customer buys a ticket. We test this model in a real-world case where as a result the revenue is increased on average by 31 percent.

Suggested Citation

  • Otero, Daniel F. & Akhavan-Tabatabaei, Raha, 2015. "A stochastic dynamic pricing model for the multiclass problems in the airline industry," European Journal of Operational Research, Elsevier, vol. 242(1), pages 188-200.
    • Handle: RePEc:eee:ejores:v:242:y:2015:i:1:p:188-200
    DOI: 10.1016/j.ejor.2014.09.038
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    References listed on IDEAS

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    1. Ernst, Ricardo & Kamrad, Bardia, 2006. "Estimating demand by using sales information: inaccuracies encountered," European Journal of Operational Research, Elsevier, vol. 174(2), pages 675-688, October.
    2. Constantinos Maglaras & Joern Meissner, 2006. "Dynamic Pricing Strategies for Multiproduct Revenue Management Problems," Manufacturing & Service Operations Management, INFORMS, vol. 8(2), pages 136-148, July.
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    Cited by:

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    2. Li, Tingting & Xie, Jinxing & Lu, Shengmin & Tang, Jiafu, 2016. "Duopoly game of callable products in airline revenue management," European Journal of Operational Research, Elsevier, vol. 254(3), pages 925-934.
    3. Gökgür, Burak & Karabatı, Selçuk, 2019. "Dynamic and targeted bundle pricing of two independently valued products," European Journal of Operational Research, Elsevier, vol. 279(1), pages 184-198.
    4. Otero, Daniel F. & Escallón, Mariana & López, Cristina & Akhavan-Tabatabaei, Raha, 2019. "Optimal timing of airline promotions under dilution," European Journal of Operational Research, Elsevier, vol. 277(3), pages 981-995.
    5. Yu, Shunan & Yang, Zhongzhen & Zhang, Wei, 2019. "Differential pricing strategies of air freight transport carriers in the spot market," Journal of Air Transport Management, Elsevier, vol. 75(C), pages 9-15.
    6. Moreno-Izquierdo, L. & Ramón-Rodríguez, A. & Perles Ribes, J., 2015. "The impact of the internet on the pricing strategies of the European low cost airlines," European Journal of Operational Research, Elsevier, vol. 246(2), pages 651-660.
    7. Michael D. Wittman & Peter P. Belobaba, 2018. "Customized dynamic pricing of airline fare products," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 17(2), pages 78-90, April.
    8. Dinçer, Hasan & Hacıoğlu, Ümit & Yüksel, Serhat, 2017. "Balanced scorecard based performance measurement of European airlines using a hybrid multicriteria decision making approach under the fuzzy environment," Journal of Air Transport Management, Elsevier, vol. 63(C), pages 17-33.
    9. Song, Boqian & Li, Michael Z.F. & Zhuang, Weifen, 2021. "Dynamic channel control and pricing of a single perishable product on multiple distribution channels," European Journal of Operational Research, Elsevier, vol. 288(2), pages 539-551.

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