Vacation Rentals - Sweden

Sweden

Highlights

Sweden is projected to witness a revenue of US$580.60m in the Vacation Rentals market by 2024.
The market is expected to grow annually at a rate of 2.64% between 2024 and 2029, leading to a projected market volume of US$661.40m by 2029.
The number of users in the Vacation Rentals market is estimated to reach 2.84m users in Sweden by 2029, with a user penetration rate of 23.6% in 2024, expected to rise to 25.9% by 2029.
The average revenue per user (ARPU) is expected to be US$230.80.
Online sales are projected to contribute 79% of the total revenue in the Vacation Rentals market by 2029 in Sweden.
Comparing globally, United States is expected to generate the highest revenue of US$20bn by 2024.
Sweden's Vacation Rentals market is highly competitive, with a focus on sustainable and eco-friendly properties.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

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

Customer preferences: Travelers in Sweden are increasingly seeking unique and authentic experiences, driving the demand for vacation rentals over traditional accommodation options. The flexibility, privacy, and local charm offered by vacation rentals appeal to a wide range of travelers, from families to solo adventurers.

Trends in the market: One notable trend in the Swedish vacation rental market is the rise of sustainable and eco-friendly properties. Travelers are becoming more environmentally conscious, leading to a growing preference for eco-friendly accommodations. Additionally, the integration of technology, such as online booking platforms and smart home features, has streamlined the booking process and enhanced the overall guest experience.

Local special circumstances: Sweden's diverse landscape, including picturesque countryside, coastal regions, and vibrant cities, offers a wide variety of vacation rental options to travelers. From cozy cabins in the woods to modern apartments in urban centers, the market caters to different preferences and budgets. The Swedish "allemansrätten" (freedom to roam) allows travelers to enjoy nature and access public land, contributing to the popularity of outdoor-oriented vacation rentals.

Underlying macroeconomic factors: The stable economy and high standard of living in Sweden have increased disposable income levels, enabling more individuals to travel and explore domestic destinations. The government's support for tourism initiatives and sustainable practices has further boosted the vacation rental market. Additionally, Sweden's well-developed infrastructure and efficient public transportation system make it easy for travelers to access various vacation rental locations across the country.

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.