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Location, location and professionalization: a multilevel hedonic analysis of Airbnb listing prices and revenue

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  • Robbin Deboosere
  • Danielle Jane Kerrigan
  • David Wachsmuth
  • Ahmed El-Geneidy

Abstract

Hedonic modelling techniques have frequently been used to examine real estate valuation, and they have recently started to be applied to short-term rental valuation. Relying on a web-scraped data set of all Airbnb transactions in New York City (NYC) between August 2014 and September 2016, this paper presents the first hedonic regression model of Airbnb to take into account neighbourhood effects and to predict both average price per night and revenue generated by each listing. The model demonstrates that locational factors – above all, transit accessibility to jobs – and neighbourhood variation have a large impact on both price per night and monthly revenue, and further reveals how professionalization of the short-term rental market is driving more revenue to a narrower segment of hosts. Further, the findings suggest that Airbnb hosts earn a significant premium by converting long-term housing in accessible residential neighbourhoods into de facto Airbnb hotels. This premium incentivizes landlords and hosts with properties in accessible neighbourhoods to replace long-term tenants with short-term guests, forcing those in search of housing to less accessible neighbourhoods.

Suggested Citation

  • Robbin Deboosere & Danielle Jane Kerrigan & David Wachsmuth & Ahmed El-Geneidy, 2019. "Location, location and professionalization: a multilevel hedonic analysis of Airbnb listing prices and revenue," Regional Studies, Regional Science, Taylor & Francis Journals, vol. 6(1), pages 143-156, January.
    • Handle: RePEc:taf:rsrsxx:v:6:y:2019:i:1:p:143-156
    DOI: 10.1080/21681376.2019.1592699
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    Cited by:

    1. Bouzouina, Louafi & Baraklianos, Ioannis & Bonnel, Patrick & Aissaoui, Hind, 2021. "Renters vs owners: The impact of accessibility on residential location choice. Evidence from Lyon urban area, France (1999–2013)," Transport Policy, Elsevier, vol. 109(C), pages 72-84.
    2. Ricardo Teruel-Gutierrez & Mariluz Maté-Sánchez-Val, 2021. "The impact of Instagram on Airbnb’s listing prices in the city of Barcelona," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 67(3), pages 737-763, December.
    3. Jelke R. Bosma, 2022. "Platformed professionalization: Labor, assets, and earning a livelihood through Airbnb," Environment and Planning A, , vol. 54(4), pages 595-610, June.
    4. Csaba Sidor & Branislav Kršák & Ľubomír Štrba & Michal Cehlár & Samer Khouri & Michal Stričík & Jaroslav Dugas & Ján Gajdoš & Barbora Bolechová, 2019. "Can Location-Based Social Media and Online Reservation Services Tell More about Local Accommodation Industries than Open Governmental Data?," Sustainability, MDPI, vol. 11(21), pages 1-21, October.
    5. Yifei Jiang & Honglei Zhang & Xianting Cao & Ge Wei & Yang Yang, 2023. "How to better incorporate geographic variation in Airbnb price modeling?," Tourism Economics, , vol. 29(5), pages 1181-1203, August.
    6. Lan-fei Gao & Hui Li, 2024. "Overcoming the pitfalls of economies-of-scale in shared accommodation: How can effective multi-listing management enhance the sustainability of homestay businesses?," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-14, December.
    7. Gyódi, Kristóf, 2021. "Airbnb and hotels during COVID-19: different strategies to survive," MPRA Paper 109333, University Library of Munich, Germany.
    8. Abrate, Graziano & Sainaghi, Ruggero & Mauri, Aurelio G., 2022. "Dynamic pricing in Airbnb: Individual versus professional hosts," Journal of Business Research, Elsevier, vol. 141(C), pages 191-199.
    9. Chunfang Zhao & Yingliang Wu & Yunfeng Chen & Guohua Chen, 2023. "Multiscale Effects of Hedonic Attributes on Airbnb Listing Prices Based on MGWR: A Case Study of Beijing, China," Sustainability, MDPI, vol. 15(2), pages 1-21, January.
    10. Türk, Umut & Östh, John & Kourtit, Karima & Nijkamp, Peter, 2021. "The path of least resistance explaining tourist mobility patterns in destination areas using Airbnb data," Journal of Transport Geography, Elsevier, vol. 94(C).
    11. María Barrero-Rescalvo & Ibán Díaz-Parra, 2024. "Short-term rentals’ supply-side structure and the struggle for rent appropriation: Insights from Andalusia, Spain," Environment and Planning A, , vol. 56(2), pages 508-524, March.
    12. Agustin Cocola-Gant & Angela Hof & Christian Smigiel & Ismael Yrigoy, 2021. "Short-term rentals as a new urban frontier – evidence from European cities," Environment and Planning A, , vol. 53(7), pages 1601-1608, October.
    13. Shijie Sun & Shengyue Zhang & Xingjian Wang, 2021. "Characteristics and influencing factors of Airbnb spatial distribution in China’s rapid urbanization process: A case study of Nanjing," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-19, March.
    14. Martí Cors-Iglesias & María Belén Gómez-Martín & Xosé Antón Armesto-López, 2020. "Peer-to-Peer Accommodation in Rural Areas of Catalonia: Defining Typologies of Rural Municipalities," Sustainability, MDPI, vol. 12(15), pages 1-15, July.
    15. Sainaghi, Ruggero & Chica-Olmo, Jorge, 2022. "The effects of location before and during COVID-19," Annals of Tourism Research, Elsevier, vol. 96(C).
    16. Emeka Ndaguba & Cina Van Zyl, 2023. "Professionalizing Sharing Platforms for Sustainable Growth in the Hospitality Sector: Insights Gained through Hierarchical Linear Modeling," Sustainability, MDPI, vol. 15(10), pages 1-24, May.

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