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Benchmarking of Airbnb listings: How competitive is the sharing economy sector of European cities?

Author

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  • Bozana Zekan

    (MODUL University Vienna, Austria)

  • Irem Önder

    (MODUL University Vienna, Austria)

  • Ulrich Gunter

    (MODUL University Vienna, Austria)

Abstract

Airbnb is arguably the world’s most popular accommodation sharing platform. Its impact on demand and supply within the tourism and hospitality industry is nowadays unquestionable. The present study delves into inspecting the efficiency of Airbnb listings of European cities, as, in spite of the success of Airbnb as a whole, it cannot be presupposed that all listings are equally successful. More specifically, data envelopment analysis (DEA) is employed in this first comprehensive benchmarking attempt within the domain of the sharing economy to date. This article also makes a contribution to robustness by introducing an interactivity note to the base model, thus, inspecting the results for corroboration/discrepancies and going beyond the static analyses that are common in DEA modeling. Ultimately, this is done with the goal of highlighting opportunities for inefficient Airbnb listings to properly utilize their inputs and therefore become more competitive.

Suggested Citation

  • Bozana Zekan & Irem Önder & Ulrich Gunter, 2019. "Benchmarking of Airbnb listings: How competitive is the sharing economy sector of European cities?," Tourism Economics, , vol. 25(7), pages 1029-1046, November.
    • Handle: RePEc:sae:toueco:v:25:y:2019:i:7:p:1029-1046
    DOI: 10.1177/1354816618814349
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Juan L Eugenio-Martin & José M Cazorla-Artiles & Christian González-Martel, 2019. "On the determinants of Airbnb location and its spatial distribution," Tourism Economics, , vol. 25(8), pages 1224-1244, December.
    2. Bozana Zekan & Ulrich Gunter, 2022. "Zooming into Airbnb listings of European cities: Further investigation of the sector’s competitiveness," Tourism Economics, , vol. 28(3), pages 772-794, May.
    3. Schmücker Dirk & Reif Julian, 2023. "Geht Tourismus alle an? Teilnahme der deutschen Gemeinden am Übernachtungstourismus," Zeitschrift für Tourismuswissenschaft, De Gruyter, vol. 15(1), pages 4-26, March.
    4. Francesco Angelini & Paolo Figini & Veronica Leoni, 2024. "High tide, low price? Flooding alerts and hotel prices in Venice," Tourism Economics, , vol. 30(4), pages 876-899, June.
    5. Wei Guo & Jing Wang & Yue Kang, 2024. "Internet use and inverted U-shaped employment polarization in tourism occupations," Tourism Economics, , vol. 30(2), pages 457-476, March.
    6. Reif, Julian, 2022. "Hot or not? Räumliche Analyse von Airbnb-Listings in Deutschland, Berlin, Hamburg, München und Köln," Working Paper Series 3, Deutsches Institut für Tourismusforschung, Fachhochschule Westküste.
    7. 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.
    8. Yoo Ri Kim & Anyu Liu & Allan M Williams, 2022. "Competitiveness in the visitor economy: A systematic literature review," Tourism Economics, , vol. 28(3), pages 817-842, May.
    9. 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.
    10. Yuting Chen & Rong Zhang & Bin Liu, 2021. "Fixed, flexible, and dynamics pricing decisions of Airbnb mode with social learning," Tourism Economics, , vol. 27(5), pages 893-914, August.
    11. Martin Thomas Falk & Yang Yang, 2021. "Hotels benefit from stricter regulations on short-term rentals in European cities," Tourism Economics, , vol. 27(7), pages 1526-1539, November.

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