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The implications of behavioural economics for pricing in a world of offer optimisation

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  • Octavian Oancea

Abstract

The impact of the COVID-19 on the industry has highlighted once again the need to create new ways of addressing consumers that would be less reliant on historic data, and more adjusted to recent observations of consumer behaviour, real time experiments and competitive context. This article addresses the implications of consumer behavioural economics in the design of offers and the way airlines will have to rethink the way they price in a New Distribution Capability (NDC) world, as defined by IATA. In a pandemic impacted era, this investment will show its fruits not only after, but also during the recovery phase, where travel behaviour is exceptionally different, capacity fluctuates and the competitive landscape is equally difficult to predict. We will discuss what challenges a pricing department is facing in this new world of offers, as well as how to overcome them in order to provide relevant and personalised offers to each consumer and price them according to the value that these offers bring. In the COVID-19 context as well as post-pandemic, airlines will need to not only respond quicker with capacity adjustments, but also to better understand human behaviour relative to a purchase decision and address each consumer with an optimised offer in real-time, as they request it. Some of the questions for which new artificial intelligence experimentation techniques and behavioural economics models will require significant development are: What drives a person to choose or not to choose a certain offer? How many choices should they see? What trip purpose segment do they belong to? What is their willingness to pay? What attributes of an offer are people considering and what value do they associate to these offers?

Suggested Citation

  • Octavian Oancea, 2021. "The implications of behavioural economics for pricing in a world of offer optimisation," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 20(6), pages 626-633, December.
    • Handle: RePEc:pal:jorapm:v:20:y:2021:i:6:d:10.1057_s41272-021-00348-5
    DOI: 10.1057/s41272-021-00348-5
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    References listed on IDEAS

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    1. Park, Jeong-Yeol & Jang, SooCheong (Shawn), 2013. "Confused by too many choices? Choice overload in tourism," Tourism Management, Elsevier, vol. 35(C), pages 1-12.
    2. Octavian Oancea, 2020. "Optimizing airline fare structures," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(4), pages 230-233, August.
    3. Adam Bockelie & Peter Belobaba, 2017. "Incorporating ancillary services in airline passenger choice models," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 16(6), pages 553-568, December.
    4. Octavian Oancea, 0. "Optimizing airline fare structures," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 0, pages 1-4.
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    Cited by:

    1. 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.
    2. Michal Sznajder & Richard Ratliff & Cuneyd Kaya, 2023. "A heuristic for incorporating ancillaries into air choice models with personalization (Part 1: estimating preferences using hedonic regression)," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 22(2), pages 122-139, April.
    3. Michal Sznajder & Richard Ratliff & Cuneyd Kaya, 2023. "A heuristic for incorporating ancillaries into air choice models with personalization (part 2: integrated multinomial logit and hedonic regression models)," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 22(2), pages 140-151, April.

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