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Host type and pricing on Airbnb: Seasonality and perceived market power

Author

Listed:
  • Georges Casamatta

    (LISA - Lieux, Identités, eSpaces, Activités - UPP - Université Pascal Paoli - CNRS - Centre National de la Recherche Scientifique, TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • Sauveur Giannoni

    (LISA - Lieux, Identités, eSpaces, Activités - UPP - Université Pascal Paoli - CNRS - Centre National de la Recherche Scientifique)

  • Daniel Brunstein

    (LISA - Lieux, Identités, eSpaces, Activités - UPP - Université Pascal Paoli - CNRS - Centre National de la Recherche Scientifique)

  • Johan Jouve

    (LISA - Lieux, Identités, eSpaces, Activités - UPP - Université Pascal Paoli - CNRS - Centre National de la Recherche Scientifique)

Abstract

The literature on short-term rental emphasises the heterogeneity of the hosts population. Some argue that professional and opportunistic hosts differ in terms of their pricing strategy. This study highlights how differences in market perception and information create a price differential between professional and non-professional players. Proposing an original and accurate definition of professional hosts, we rely on a large dataset of almost 9,000 properties and 73,000 observations to investigate the pricing behaviour of Airbnb sellers in Corsica (France). Using OLS and the double-machine learning methods, we demonstrate that a price differential exists between professional and opportunistic sellers. In addition, we assess the impact of seasonality in demand on the size and direction of this price differential. We find that professionals perceive a higher degree of market power than others during the peak season and it allows them to enhance their revenues.

Suggested Citation

  • Georges Casamatta & Sauveur Giannoni & Daniel Brunstein & Johan Jouve, 2022. "Host type and pricing on Airbnb: Seasonality and perceived market power," Post-Print hal-03250484, HAL.
    • Handle: RePEc:hal:journl:hal-03250484
    DOI: 10.1016/j.tourman.2021.104433
    Note: View the original document on HAL open archive server: https://hal.science/hal-03250484
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    Citations

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    Cited by:

    1. David Boto-García & Veronica Leoni, 2022. "The hedonic value of coastal amenities in peer-to-peer markets," DEA Working Papers 94, Universitat de les Illes Balears, Departament d'Economía Aplicada.
    2. Yoganathan, Vignesh & Osburg, Victoria-Sophie, 2024. "The mind in the machine: Estimating mind perception's effect on user satisfaction with voice-based conversational agents," Journal of Business Research, Elsevier, vol. 175(C).
    3. Trinath Sai Subhash Reddy Pittala & Uma Maheswara R Meleti & Hemanth Vasireddy, 2024. "Unveiling Patterns in European Airbnb Prices: A Comprehensive Analytical Study Using Machine Learning Techniques," Papers 2407.01555, arXiv.org.
    4. Feng, Nan & Xu, Nan & Feng, Haiyang & Li, Minqiang, 2022. "Turn on instant booking or not? Decisions of rival hosts," Annals of Tourism Research, Elsevier, vol. 96(C).
    5. Ngai, Eric W.T. & Wu, Yuanyuan, 2022. "Machine learning in marketing: A literature review, conceptual framework, and research agenda," Journal of Business Research, Elsevier, vol. 145(C), pages 35-48.
    6. Ru Jia & Shanshan Wang, 2021. "Investigating the Impact of Professional and Nonprofessional Hosts’ Pricing Behaviors on Accommodation-Sharing Market Outcome," Sustainability, MDPI, vol. 13(21), pages 1-16, November.

    More about this item

    Keywords

    Short-term rental; Pricing; Professionalism; Double machine learning; Seasonality; Market-power;
    All these keywords.

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