Vacation Rentals - Australia & Oceania

Australia & Oceania

Highlights

Australia & Oceania is expected to experience significant growth in the Vacation Rentals market.
By 2024, the projected revenue is estimated to reach US$1.86bn.
The market volume is also expected to grow, with a projected revenue of US$2.27bn by 2029, showing a CAGR of 4.06%.
The number of users is expected to reach 9.85m users by 2029, with a user penetration of 21.5%, which is lower than the 19.1% in 2024.
The average revenue per user (ARPU) is expected to be US$223.50.
In terms of sales channels, 90% of the total revenue is expected to be generated through online sales by 2029.
It is interesting to note that United States is expected to generate the most revenue in the Vacation Rentals market, with a projected revenue of US$20bn in 2024, in comparison to in Australia & Oceania.
Australia's Vacation Rentals market is experiencing a rise in popularity, driven by an increase in domestic travel due to international travel restrictions.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Vacation Rentals market in Australia & Oceania has been experiencing significant growth in recent years, driven by various factors influencing the travel and tourism industry in the region.

Customer preferences: Travelers in Australia & Oceania are increasingly seeking unique and personalized accommodation options, leading to a growing preference for vacation rentals over traditional hotels. The flexibility, space, and amenities offered by vacation rentals appeal to a wide range of travelers, including families, groups of friends, and solo travelers.

Trends in the market: In Australia, coastal regions such as the Gold Coast and Sunshine Coast are popular destinations for vacation rentals, with beachfront properties in high demand. Additionally, the rise of eco-tourism has led to an increase in bookings for sustainable and eco-friendly vacation rentals in destinations like Byron Bay and the Great Barrier Reef.

Local special circumstances: One of the unique aspects of the Vacation Rentals market in Australia & Oceania is the abundance of luxury properties available for short-term rental. From exclusive beach houses to secluded mountain retreats, travelers can find a wide range of high-end vacation rentals in the region. This caters to the affluent segment of the market looking for premium accommodation options.

Underlying macroeconomic factors: The strong performance of the tourism industry in Australia & Oceania, driven by factors such as a robust economy, increased international and domestic travel, and government initiatives to promote tourism, has contributed to the growth of the Vacation Rentals market. Additionally, the region's diverse landscapes, including beaches, rainforests, and wineries, attract a steady flow of tourists seeking unique experiences, further fueling the demand for vacation rentals.

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.