IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2407.01555.html
   My bibliography  Save this paper

Unveiling Patterns in European Airbnb Prices: A Comprehensive Analytical Study Using Machine Learning Techniques

Author

Listed:
  • Trinath Sai Subhash Reddy Pittala
  • Uma Maheswara R Meleti
  • Hemanth Vasireddy

Abstract

In the burgeoning market of short-term rentals, understanding pricing dynamics is crucial for a range of stake-holders. This study delves into the factors influencing Airbnb pricing in major European cities, employing a comprehensive dataset sourced from Kaggle. We utilize advanced regression techniques, including linear, polynomial, and random forest models, to analyze a diverse array of determinants, such as location characteristics, property types, and host-related factors. Our findings reveal nuanced insights into the variables most significantly impacting pricing, highlighting the varying roles of geographical, structural, and host-specific attributes. This research not only sheds light on the complex pricing landscape of Airbnb accommodations in Europe but also offers valuable implications for hosts seeking to optimize pricing strategies and for travelers aiming to understand pricing trends. Furthermore, the study contributes to the broader discourse on pricing mechanisms in the shared economy, suggesting avenues for future research in this rapidly evolving sector.

Suggested Citation

  • 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.
    • Handle: RePEc:arx:papers:2407.01555
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2407.01555
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. V. Raul Perez-Sanchez & Leticia Serrano-Estrada & Pablo Marti & Raul-Tomas Mora-Garcia, 2018. "The What, Where, and Why of Airbnb Price Determinants," Sustainability, MDPI, vol. 10(12), pages 1-31, December.
    2. 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.
    3. 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.
    4. Insu Hong & Changsok Yoo, 2020. "Analyzing Spatial Variance of Airbnb Pricing Determinants Using Multiscale GWR Approach," Sustainability, MDPI, vol. 12(11), pages 1-18, June.
    5. 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.
    6. Baldwin Tong & Ulrich Gunter, 2022. "Hedonic pricing and the sharing economy: how profile characteristics affect Airbnb accommodation prices in Barcelona, Madrid, and Seville," Current Issues in Tourism, Taylor & Francis Journals, vol. 25(20), pages 3309-3328, October.
    7. Augusto Voltes-Dorta & Federico Inchausti-Sintes, 2021. "The spatial and quality dimensions of Airbnb markets," Tourism Economics, , vol. 27(4), pages 688-702, June.
    8. 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.
    9. Zhihua Zhang & Rachel J. C. Chen & Lee D. Han & Lu Yang, 2017. "Key Factors Affecting the Price of Airbnb Listings: A Geographically Weighted Approach," Sustainability, MDPI, vol. 9(9), pages 1-13, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. 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.
    3. Meijian Yang & Enjun Xia, 2021. "A Systematic Literature Review on Pricing Strategies in the Sharing Economy," Sustainability, MDPI, vol. 13(17), pages 1-28, August.
    4. Bobrovskaya, Ekaterina & Polbin, Andrey, 2022. "Determinants of short-term rental prices in the sharing economy: The case of Airbnb in Moscow," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 65, pages 5-28.
    5. Hongbo Tan & Tian Su & Xusheng Wu & Pengzhan Cheng & Tianxiang Zheng, 2024. "A Sustainable Rental Price Prediction Model Based on Multimodal Input and Deep Learning—Evidence from Airbnb," Sustainability, MDPI, vol. 16(15), pages 1-22, July.
    6. Nicola Camatti & Giacomo Tollo & Gianni Filograsso & Sara Ghilardi, 2024. "Predicting Airbnb pricing: a comparative analysis of artificial intelligence and traditional approaches," Computational Management Science, Springer, vol. 21(1), pages 1-25, June.
    7. Bobrovskaya, EV. & Polbin, A., 2023. "Econometric modeling of the demand for short-term rental housing: The case of Airbnb in Moscow," Journal of the New Economic Association, New Economic Association, vol. 59(2), pages 64-84.
    8. Augusto Voltes-Dorta & Federico Inchausti-Sintes, 2021. "The spatial and quality dimensions of Airbnb markets," Tourism Economics, , vol. 27(4), pages 688-702, June.
    9. Josep Lladós-Masllorens & Antoni Meseguer-Artola & Inma Rodríguez-Ardura, 2020. "Understanding Peer-to-Peer, Two-Sided Digital Marketplaces: Pricing Lessons from Airbnb in Barcelona," Sustainability, MDPI, vol. 12(13), pages 1-19, June.
    10. 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).
    11. Kisieliauskas Justinas, 2023. "Host-Related Factors Influencing Airbnb Prices in Rural Areas," Management Theory and Studies for Rural Business and Infrastructure Development, Sciendo, vol. 45(4), pages 379-389, December.
    12. 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.
    13. 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.
    14. 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.
    15. Meisam Ranjbari & Gustavo Morales-Alonso & Ruth Carrasco-Gallego, 2018. "Conceptualizing the Sharing Economy through Presenting a Comprehensive Framework," Sustainability, MDPI, vol. 10(7), pages 1-24, July.
    16. Zheng, Zuolong & Li, Ziying & Zhang, Xuwen & Liang, Sai & Law, Rob & Lei, Jiasu, 2023. "Substitution or complementary effects between hosts and neighbors’ information disclosure: Evidence from Airbnb," Journal of Business Research, Elsevier, vol. 161(C).
    17. Robert Jeyakumar Nathan & Vijay Victor & Melanie Tan & Maria Fekete-Farkas, 0. "Tourists’ use of Airbnb app for visiting a historical city," Information Technology & Tourism, Springer, vol. 0, pages 1-26.
    18. Marius-Ionuț Gordan & Valentina Constanța Tudor & Cosmin Alin Popescu & Tabita Cornelia Adamov & Elena Peț & Ioana Anda Milin & Tiberiu Iancu, 2024. "Hedonic Pricing Models in Rural Tourism: Analyzing Factors Influencing Accommodation Pricing in Romania Using Geographically Weighted Regression," Agriculture, MDPI, vol. 14(8), pages 1-22, July.
    19. Chaang-Iuan Ho & Tzong-Shyuan Chen & Chin-Pei Li, 2023. "Airbnb’s Negative Externalities from the Consumer’s Perspective: How the Effects Influence the Booking Intention of Potential Guests," Sustainability, MDPI, vol. 15(11), pages 1-28, May.
    20. 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).

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2407.01555. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.