37 datasets found
  1. Airbnb nights and experiences booked worldwide 2017-2024

    • statista.com
    • ai-chatbox.pro
    Updated Jun 26, 2025
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    Statista (2025). Airbnb nights and experiences booked worldwide 2017-2024 [Dataset]. https://www.statista.com/statistics/1193532/airbnb-nights-experiences-booked-worldwide/
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    Dataset updated
    Jun 26, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    Airbnb, a home sharing economy platform, gives users an alternative to traditional hotel accommodation by allowing them to rent accommodation from people who are willing to share their homes. The platform also allows consumers to book "experiences" in the regions they visit. In 2024, Airbnb reported over *** million booked nights and experiences. How much revenue does Airbnb make? In 2024, the total revenue of Airbnb worldwide increased by nearly ten percent over the previous year. This continued the upward trend which the company has experienced since recovering from the coronavirus (COVID-19) pandemic. ************* generated the highest share of Airbnb’s worldwide revenue in 2024, at **** billion U.S. dollars. How many people visit the Airbnb website? Airbnb ranked ***** among the most popular travel and tourism websites worldwide based on average monthly visits, behind *******************************. In 2024, airbnb.com saw its highest number of unique global visitors in March, at *** million. Meanwhile, Airbnb ranked fourth among leading travel apps globally, with over ** million downloads in 2024.

  2. s

    Airbnb Listings Per Region

    • searchlogistics.com
    Updated Mar 17, 2025
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    (2025). Airbnb Listings Per Region [Dataset]. https://www.searchlogistics.com/learn/statistics/airbnb-statistics/
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    Dataset updated
    Mar 17, 2025
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Listings per region on Airbnb declined from 2020 to 2021. Globally in 2021, there were a total of 12.7 million listings.

  3. b

    Airbnb Revenue and Usage Statistics (2025)

    • businessofapps.com
    Updated Aug 25, 2020
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    Business of Apps (2020). Airbnb Revenue and Usage Statistics (2025) [Dataset]. https://www.businessofapps.com/data/airbnb-statistics/
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    Dataset updated
    Aug 25, 2020
    Dataset authored and provided by
    Business of Apps
    License

    Attribution-NonCommercial-NoDerivs 4.0 (CC BY-NC-ND 4.0)https://creativecommons.org/licenses/by-nc-nd/4.0/
    License information was derived automatically

    Description

    In 2007, a cash-strapped Brian Chesky came up with a shrewd way to pay his $1,200 San Francisco apartment rent. He would offer “Air bed and breakfast”, which consisted of three airbeds,...

  4. s

    Airbnb Guest Demographic Statistics

    • searchlogistics.com
    Updated Mar 17, 2025
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    (2025). Airbnb Guest Demographic Statistics [Dataset]. https://www.searchlogistics.com/learn/statistics/airbnb-statistics/
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    Dataset updated
    Mar 17, 2025
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The majority of guests on Airbnb are women. Most Airbnb guests are aged 25 to 34.

  5. s

    Airbnb Corporate Statistics

    • searchlogistics.com
    Updated Mar 17, 2025
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    (2025). Airbnb Corporate Statistics [Dataset]. https://www.searchlogistics.com/learn/statistics/airbnb-statistics/
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    Dataset updated
    Mar 17, 2025
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Airbnb has a total of 6,132 employees that work for the company. 52.5% of Airbnb workers are male and 47.5% are female.

  6. Airbnb revenue 2017-2024

    • statista.com
    Updated Jun 26, 2025
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    Statista (2025). Airbnb revenue 2017-2024 [Dataset]. https://www.statista.com/statistics/1193134/airbnb-revenue-worldwide/
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    Dataset updated
    Jun 26, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    The total revenue of Airbnb reached **** billion U.S. dollars in 2024. This was an increase over the previous year's total of **** billion. The decrease in revenue in 2020 can be attributed to the coronavirus (COVID-19) pandemic, which caused travel disruption across the globe. When breaking down Airbnb revenue by region, ***************************************, brought in the most revenue in 2024. Where are Airbnb’s biggest markets? Airbnb is a home sharing economy platform that operates in many countries around the world. The company’s biggest market is in ************* where Airbnb’s gross booking value amounted to **** billion U.S. dollars. Meanwhile, Latin American travelers stayed more nights with Airbnb on average than those in the Asia Pacific region. How did COVID-19 impact Airbnb? The COVID-19 pandemic impacted the travel and tourism industry worldwide, with many countries initiating stay at home orders or travel bans to prevent the spread of the virus. In addition to a decrease in revenue in 2020, the company also experienced a reduction in the number of nights and experiences booked with Airbnb. Bookings fell to under *** million in 2020 due to these travel restrictions. In 2024, Airbnb reported over *** million booked nights and experiences, a significant increase over the previous year.

  7. s

    Airbnb Average Prices By Region

    • searchlogistics.com
    Updated Mar 17, 2025
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    (2025). Airbnb Average Prices By Region [Dataset]. https://www.searchlogistics.com/learn/statistics/airbnb-statistics/
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    Dataset updated
    Mar 17, 2025
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The current average price per night globally on Airbnb is $137 per night.

  8. Number of Airbnb users in the U.S. 2016-2022

    • statista.com
    Updated Jun 27, 2025
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    Statista (2025). Number of Airbnb users in the U.S. 2016-2022 [Dataset]. https://www.statista.com/statistics/346589/number-of-us-airbnb-users/
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    Dataset updated
    Jun 27, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    May 2018
    Area covered
    United States
    Description

    In 2017, the number of adults using Airbnb in the United States amounted to **** million, up from ** million the previous year. This figure is forecast to reach **** million by 2022. Why do people use Airbnb? The privately owned accommodation, rental and sharing website Airbnb has gained popularity all over the world. This is due to multiple factors including cheaper lodging alternatives, a more authentic experience, uniqueness of accommodation and more. A survey found that ** percent of U.S.-based & European Airbnb users were ‘very satisfied’ with their experience. On the other hand,**** percent stated that they were ‘somewhat dissatisfied’ or ‘not at all satisfied’ with using the accommodation sharing platform. Why don't people use Airbnb? Despite the large number of people who are satisfied with their Airbnb experience, there still remain those in Europe and the U.S. that do not want to use the company's services. The most common reason for people not to use Airbnb is privacy concerns, according to a 2017 survey – with ** percent of respondents expressing this fear.

  9. s

    Airbnb Gross Revenue By Country

    • searchlogistics.com
    Updated Mar 17, 2025
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    (2025). Airbnb Gross Revenue By Country [Dataset]. https://www.searchlogistics.com/learn/statistics/airbnb-statistics/
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    Dataset updated
    Mar 17, 2025
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    These are the Airbnb statistics on gross revenue by country.

  10. s

    Airbnb Commission Revenue By Region

    • searchlogistics.com
    Updated Mar 17, 2025
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    (2025). Airbnb Commission Revenue By Region [Dataset]. https://www.searchlogistics.com/learn/statistics/airbnb-statistics/
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    Dataset updated
    Mar 17, 2025
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This is the complete breakdown of how much revenue Airbnb makes in commission from listings in each region.

  11. Airbnb customer satisfaction in the U.S. and Europe 2015-2017

    • statista.com
    Updated Jul 11, 2025
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    Statista (2025). Airbnb customer satisfaction in the U.S. and Europe 2015-2017 [Dataset]. https://www.statista.com/statistics/799508/airbnb-customer-satisfaction-us-europe/
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    Dataset updated
    Jul 11, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    France, Europe, United States
    Description

    This statistic shows the the level of Airbnb customer satisfaction in the United States and Europe from 2015 to 2017. In 2017, ** percent of Airbnb users were 'very satisfied' with their experience.

  12. b

    Airbnb Overview

    • bullfincher.io
    Updated Aug 1, 2025
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    Bullfincher (2025). Airbnb Overview [Dataset]. https://bullfincher.io/companies/airbnb/overview
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    Dataset updated
    Aug 1, 2025
    Dataset authored and provided by
    Bullfincher
    License

    https://bullfincher.io/privacy-policyhttps://bullfincher.io/privacy-policy

    Description

    Airbnb, Inc., together with its subsidiaries, operates a platform that enables hosts to offer stays and experiences to guests worldwide. The company's marketplace model connects hosts and guests online or through mobile devices to book spaces and experiences. It primarily offers private rooms, primary homes, or vacation homes. The company was formerly known as AirBed & Breakfast, Inc. and changed its name to Airbnb, Inc. in November 2010. Airbnb, Inc. was founded in 2007 and is headquartered in San Francisco, California.

  13. New York City Airbnb Open Data

    • kaggle.com
    • marketplace.sshopencloud.eu
    zip
    Updated Aug 12, 2019
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    Dgomonov (2019). New York City Airbnb Open Data [Dataset]. https://www.kaggle.com/dgomonov/new-york-city-airbnb-open-data
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    zip(2562692 bytes)Available download formats
    Dataset updated
    Aug 12, 2019
    Authors
    Dgomonov
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    New York
    Description

    Context

    Since 2008, guests and hosts have used Airbnb to expand on traveling possibilities and present more unique, personalized way of experiencing the world. This dataset describes the listing activity and metrics in NYC, NY for 2019.

    Content

    This data file includes all needed information to find out more about hosts, geographical availability, necessary metrics to make predictions and draw conclusions.

    Acknowledgements

    This public dataset is part of Airbnb, and the original source can be found on this website.

    Inspiration

    • What can we learn about different hosts and areas?
    • What can we learn from predictions? (ex: locations, prices, reviews, etc)
    • Which hosts are the busiest and why?
    • Is there any noticeable difference of traffic among different areas and what could be the reason for it?
  14. Airbnb distribution of bookings 2019-2024, by region

    • statista.com
    Updated Jun 26, 2025
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    Statista (2025). Airbnb distribution of bookings 2019-2024, by region [Dataset]. https://www.statista.com/statistics/1193548/airbnb-regional-distribution-bookings-worldwide/
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    Dataset updated
    Jun 26, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    Airbnb, a home sharing economy platform, gives users an alternative to traditional hotel accommodation by allowing them to rent accommodation from people who are willing to share their homes. In addition, it allows consumers to book "experiences" in the regions they visit. In 2024, Europe, the Middle East, and Africa (EMEA) had the largest share of number of nights and experiences booked on the Airbnb platform at ** percent.

  15. V

    Vacation Rental Report

    • datainsightsmarket.com
    doc, pdf, ppt
    Updated Apr 21, 2025
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    Data Insights Market (2025). Vacation Rental Report [Dataset]. https://www.datainsightsmarket.com/reports/vacation-rental-1950342
    Explore at:
    pdf, ppt, docAvailable download formats
    Dataset updated
    Apr 21, 2025
    Dataset authored and provided by
    Data Insights Market
    License

    https://www.datainsightsmarket.com/privacy-policyhttps://www.datainsightsmarket.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The vacation rental market is experiencing robust growth, driven by increasing disposable incomes, a preference for unique travel experiences, and the rise of the sharing economy. The market's expansion is fueled by several key trends: the increasing popularity of alternative accommodations beyond traditional hotels, the growing adoption of online booking platforms, and the diversification of rental options, ranging from apartments and private homes to unique properties like villas and cabins. Technological advancements, such as improved search functionalities and mobile booking apps, are further enhancing accessibility and convenience for travelers. While factors like fluctuating travel restrictions and economic downturns can pose challenges, the market's inherent resilience and the continued demand for flexible and personalized travel experiences suggest a positive long-term outlook. The segmentation within the market indicates strong performance across various applications, including the travel industry and commercial sectors, with apartment and private home rentals holding significant market share. Major players like Airbnb, Booking Holdings, and Expedia are key contributors to market growth, constantly innovating to attract and retain customers. Geographic data indicates North America and Europe as major revenue generators, although Asia Pacific and other regions are showing significant growth potential. The forecast period (2025-2033) suggests continued expansion, driven by consistent demand and technological enhancements. Competition is fierce but opportunities abound for established players and new entrants alike who can effectively leverage technology and cater to evolving traveler preferences. The competitive landscape is dynamic, with established players like Airbnb and Booking Holdings continuously innovating their platforms and services to remain competitive. New entrants are also emerging, leveraging technological advancements and specialized offerings to carve out niche markets. However, regulatory challenges, particularly concerning licensing and taxation, represent a significant restraint for the industry. Maintaining sustainable practices and addressing environmental concerns are also becoming increasingly important. Despite these challenges, the long-term growth trajectory for the vacation rental market remains optimistic, propelled by persistent demand for unique and personalized travel experiences, and the ongoing evolution of technology within the hospitality sector. Data suggests that this market will experience significant growth across all regions, with some exhibiting faster growth rates than others. Understanding the nuances of regional demand and preferences will be crucial for success in this dynamic market.

  16. m

    Airbnb Inc - Change-To-Liabilities

    • macro-rankings.com
    csv, excel
    Updated Jul 24, 2025
    + more versions
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    macro-rankings (2025). Airbnb Inc - Change-To-Liabilities [Dataset]. https://www.macro-rankings.com/Markets/Stocks?Entity=ABNB.US&Item=Change-To-Liabilities
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    excel, csvAvailable download formats
    Dataset updated
    Jul 24, 2025
    Dataset authored and provided by
    macro-rankings
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    united states
    Description

    Change-To-Liabilities Time Series for Airbnb Inc. Airbnb, Inc., together with its subsidiaries, operates a platform that enables hosts to offer stays and experiences to guests worldwide. Its marketplace connects hosts and guests online or through mobile devices to book spaces and experiences. It also offers gift cards. The company was formerly known as AirBed & Breakfast, Inc. and changed its name to Airbnb, Inc. in November 2010. Airbnb, Inc. was founded in 2007 and is headquartered in San Francisco, California.

  17. Airbnb Price Determinants in Europe

    • kaggle.com
    Updated Feb 13, 2023
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    The Devastator (2023). Airbnb Price Determinants in Europe [Dataset]. https://www.kaggle.com/thedevastator/airbnb-price-determinants-in-europe/discussion
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 13, 2023
    Dataset provided by
    Kaggle
    Authors
    The Devastator
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    Europe
    Description

    Airbnb Price Determinants in Europe

    Characteristics and Effects

    By [source]

    About this dataset

    This dataset contains Airbnb rental data for European cities, including characteristics and their effects on price. The dataset includes several features such as the total price of the listing, room type, host status (superhost or not), amenities, and location information which can be used to analyze the factors that affect Airbnb prices. This data can help travelers find an accommodation that satisfies their needs without spending more than necessary. It can also provide business owners valuable insights on how to set competitive prices and optimize their listings for increased bookings. Furthermore, this data is useful for property investors who want to understand pricing trends in different cities across Europe and make informed decisions about investing in real estate

    More Datasets

    For more datasets, click here.

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    How to use the dataset

    This dataset contains Airbnb rental data for multiple European cities, including price, room type, host status, amenities and location information. This data can be used to better understand the factors that influence Airbnb rental prices in Europe.

    The columns of the dataset include: - realSum (total price of the listing) - room_type (type of room offered such as private/shared/entire home/apt)
    - room_shared (whether or not the room is shared) - person_capacity (maximum number of people allowed in the property)
    - host_is_superhost(whether or not the host is a superhost) (boolean value so either true or false)
    - multi (whether it’s for multiple rooms or not)
    - biz(whether it’s for business use or family use ) .
    dist(the distance from city center )
    metro dist (the distance from nearest metro station ) lng(longitude value ) lat(latitude value ) guest satisfaction overall () Cleanliness rating () Bedrooms () and Real sum -Total Price.

    First step would be to select features that are important and relevant to you according to your purpose. You can start by selecting the features like realSum ,room type ,host etc which will give you an understanding on how potential customers best fits your requirements i.e how many people will fit into a particular property when renting out a single bedroom versus renting out an entire home/apartment. After that review associated values; this could help you decide on pricing strategies such as offering discounts or raising prices according to needs and demands in different neighbourhoods depending on demand levels, availability and seasonality etc.. The next step would be to plot distance variables with respect to latitude & longitude which will indicate geographical locations where businesses could benefit from having higher occupancy rates by leveraging neighbourhood proximityi n order tackle seasonal variations . And lastly using correlation matrix between all other variables one can correlating parameters which display strong correlations thereby helping establish relationships across other variables relative towards each other as well as decide what set parameters should come into play when based upon one parameter . This dataset however does not provide dates

    Research Ideas

    • Price forecasting - Analyzing previous data about Airbnb listings, such as pricing, room type and amenities, could help predict potential rental prices in the future.

    • Business or tourist rental hotspots - By looking at each listing’s location in relation to business and tourism centers and correlating this with pricing can help determine areas where Airbnb rentals will be most profitable.

    • Customer sentiment analysis - Analyzing customer comments and satisfaction ratings to measure the effectiveness of a specific listing on their overall customer experience could be an useful tool for...

  18. f

    Table_1_Exploring Sources of Satisfaction and Dissatisfaction in Airbnb...

    • frontiersin.figshare.com
    docx
    Updated May 30, 2023
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    Kai Ding; Wei Chong Choo; Keng Yap Ng; Siew Imm Ng; Pu Song (2023). Table_1_Exploring Sources of Satisfaction and Dissatisfaction in Airbnb Accommodation Using Unsupervised and Supervised Topic Modeling.DOCX [Dataset]. http://doi.org/10.3389/fpsyg.2021.659481.s002
    Explore at:
    docxAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    Frontiers
    Authors
    Kai Ding; Wei Chong Choo; Keng Yap Ng; Siew Imm Ng; Pu Song
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This study aims to examine key attributes affecting Airbnb users' satisfaction and dissatisfaction through the analysis of online reviews. A corpus that comprises 59,766 Airbnb reviews form 27,980 listings located in 12 different cities is analyzed by using both Latent Dirichlet Allocation (LDA) and supervised LDA (sLDA) approach. Unlike previous LDA based Airbnb studies, this study examines positive and negative Airbnb reviews separately, and results reveal the heterogeneity of satisfaction and dissatisfaction attributes in Airbnb accommodation. In particular, the emergence of the topic “guest conflicts” in this study leads to a new direction in future sharing economy accommodation research, which is to study the interactions of different guests in a highly shared environment. The results of topic distribution analysis show that in different types of Airbnb properties, Airbnb users attach different importance to the same service attributes. The topic correlation analysis reveals that home like experience and help from the host are associated with Airbnb users' revisit intention. We determine attributes that have the strongest predictive power to Airbnb users' satisfaction and dissatisfaction through the sLDA analysis, which provides valuable managerial insights into priority setting when developing strategies to increase Airbnb users' satisfaction. Methodologically, this study contributes by illustrating how to employ novel approaches to transform social media data into useful knowledge about customer satisfaction, and the findings can provide valuable managerial implications for Airbnb practitioners.

  19. S

    Global Airbnb Business Model Market Growth Opportunities 2025-2032

    • statsndata.org
    excel, pdf
    Updated Jul 2025
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    Stats N Data (2025). Global Airbnb Business Model Market Growth Opportunities 2025-2032 [Dataset]. https://www.statsndata.org/report/airbnb-business-model-market-378572
    Explore at:
    pdf, excelAvailable download formats
    Dataset updated
    Jul 2025
    Dataset authored and provided by
    Stats N Data
    License

    https://www.statsndata.org/how-to-orderhttps://www.statsndata.org/how-to-order

    Area covered
    Global
    Description

    The Airbnb business model has revolutionized the hospitality and tourism industry by leveraging the power of the sharing economy. Established in 2008, Airbnb provides a platform for homeowners to monetize their extra space by renting it out to travelers seeking unique lodging experiences. This innovative approach no

  20. Number of Airbnb listings in selected European cities 2024

    • statista.com
    • ai-chatbox.pro
    Updated Jun 26, 2025
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    Statista (2025). Number of Airbnb listings in selected European cities 2024 [Dataset]. https://www.statista.com/statistics/815145/airbnb-listings-in-europe-by-city/
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    Dataset updated
    Jun 26, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Dec 2024
    Area covered
    Europe
    Description

    As of December, 2024, there were over ** thousand listings for room and apartment rentals in London on the Airbnb website, the highest of any other major European city. Airbnb listings were also high in Paris, Rome and Madrid. Paris accounted for around ** thousand listings, while Rome and Madrid had over ** and ** thousand, respectively. Controversy of Airbnb in Europe Airbnb has become an increasingly popular option for tourists looking for local accommodation. Visitors are attracted to using Airbnb properties instead of hotels and other traditional travel accommodation mainly due to cheaper prices, but also for the location, and to gain an authentic experience. However, the site is facing ongoing legal problems, with some destinations moving to ban or restrict rentals from the site because they worsen housing problems and undermining hotel regulations. Many European cities, including Amsterdam and Paris, have placed limits on the length of rentals, and others such as Barcelona have introduced strict regulations for hosts. The rise of Airbnb Airbnb is one of the most successful companies in the global sharing economy. The company was founded in San Francisco, California in 2008, after being conceived by two entrepreneurs looking for a way to offset their high rental costs. Airbnb was developed as an online platform for hosts to rent out their properties on a short-term basis. It now competes with other online travel booking websites, including Booking.com and Expedia.

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Close
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Statista (2025). Airbnb nights and experiences booked worldwide 2017-2024 [Dataset]. https://www.statista.com/statistics/1193532/airbnb-nights-experiences-booked-worldwide/
Organization logo

Airbnb nights and experiences booked worldwide 2017-2024

Explore at:
3 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jun 26, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
Worldwide
Description

Airbnb, a home sharing economy platform, gives users an alternative to traditional hotel accommodation by allowing them to rent accommodation from people who are willing to share their homes. The platform also allows consumers to book "experiences" in the regions they visit. In 2024, Airbnb reported over *** million booked nights and experiences. How much revenue does Airbnb make? In 2024, the total revenue of Airbnb worldwide increased by nearly ten percent over the previous year. This continued the upward trend which the company has experienced since recovering from the coronavirus (COVID-19) pandemic. ************* generated the highest share of Airbnb’s worldwide revenue in 2024, at **** billion U.S. dollars. How many people visit the Airbnb website? Airbnb ranked ***** among the most popular travel and tourism websites worldwide based on average monthly visits, behind *******************************. In 2024, airbnb.com saw its highest number of unique global visitors in March, at *** million. Meanwhile, Airbnb ranked fourth among leading travel apps globally, with over ** million downloads in 2024.

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