Vacation Rentals - Worldwide

Worldwide

Highlights

The Vacation Rentals market is expected to generate a revenue of US$100.20bn in the world in 2024.
This is anticipated to experience a Compound Annual Growth Rate (CAGR) of 4.61% from 2024 to 2029, leading to an estimated market volume of US$125.60bn by 2029.
It is projected that the number of users in this market will increase to 1.07bn users by 2029.
The user penetration rate is expected to rise from 11.1% in 2024 to 13.3% by 2029.
The Average Revenue Per User (ARPU) is forecasted to be US$116.90.
By 2029, online sales are expected to account for 78% of the total revenue in the Vacation Rentals market.
In comparison to other countries, United States is expected to generate the highest revenue of US$20bn in 2024.
In the United States, vacation rental demand has shifted from urban areas to rural destinations due to the pandemic.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Vacation Rentals market has been experiencing significant growth and evolution in recent years.

Customer preferences: Travelers are increasingly seeking unique and personalized accommodation options, driving the demand for vacation rentals over traditional hotels. The flexibility, space, and amenities offered by vacation rentals cater to a wide range of preferences, from families looking for a home-like environment to solo travelers seeking local experiences.

Trends in the market: In the United States, the Vacation Rentals market is witnessing a trend towards urban rentals in major cities like New York and Los Angeles. This shift is fueled by the desire for authentic urban experiences and the convenience of staying in central locations. Additionally, the rise of eco-friendly and sustainable vacation rentals is gaining traction, aligning with the growing consciousness around responsible tourism.

Local special circumstances: In Europe, countries like Italy and Spain are known for their picturesque countryside villas and coastal cottages, attracting travelers looking for a relaxing retreat. These destinations offer a blend of natural beauty, cultural experiences, and gastronomic delights, making them popular choices for vacation rentals. Moreover, the regulatory environment for vacation rentals in Europe varies widely between countries, impacting the market dynamics in each region.

Underlying macroeconomic factors: The increasing popularity of vacation rentals can also be attributed to the rise of the sharing economy and online platforms that connect travelers directly with property owners. This direct booking model not only provides a seamless booking experience but also allows for more competitive pricing compared to traditional accommodation options. Furthermore, the impact of the COVID-19 pandemic has accelerated the shift towards vacation rentals, as travelers prioritize privacy, cleanliness, and social distancing measures in their accommodation choices.

Data coverage:

The data encompasses B2C enterprises. Figures are based on bookings, revenues, and sales channels of vacation rentals.

Modeling approach:

Market sizes are determined through a bottom-up approach, building on a specific rationale for each market. As a basis for evaluating markets, we use financial reports, the Global Consumer Survey, third-party studies and reports, data from industry associations (e.g., UNWTO), and price data of major players in respective markets. To estimate the number of users and bookings, we furthermore use data from the Statista Consumer Insigths Global survey. In addition, we use relevant key market indicators and data from country-specific associations, such as country-related GDP, demographic data (e.g., population), tourism spending, consumer spending, internet penetration, and device penetration. This data helps us estimate the market size for each country individually.

Forecasts:

In our forecasts, we apply diverse forecasting techniques. The selection of forecasting techniques is based on the behavior of the relevant market. For example, ARIMA, which allows time series forecasts, accounting for stationarity of data and enabling short-term estimates. Additionally, simple linear regression, Holt-Winters forecast, and exponential trend smoothing methods are applied. A k-means cluster analysis allows for the estimation of similar countries. The main drivers are tourism GDP per capita and respective price indices.

Additional notes:

The data is modeled using current exchange rates. The market is updated twice a year in case market dynamics change.