Vacation Rentals - Asia

Asia

Highlights

The Vacation Rentals market in Asia is projected to reach a revenue of US$28.55bn by 2024.
By 2029, the market volume is anticipated to reach US$35.89bn, exhibiting an annual growth rate of 4.68%.
The number of users in the Vacation Rentals market in Asia is also expected to increase significantly, amounting to 464.80m users by 2029.
The user penetration is predicted to rise from 7.9% in 2024 to 9.9% by 2029.
The average revenue per user (ARPU) is estimated to be US$79.85.
Additionally, 72% of the total revenue in the Vacation Rentals market in Asia is expected to be generated through online sales by 2029.
In comparison to other countries, United States is expected to generate the most revenue, with US$20bn in 2024.
In Japan's Vacation Rentals market, traditional ryokans are increasingly offering unique experiences such as private onsen and tea ceremonies to attract tourists.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Vacation Rentals market in Asia is experiencing a significant surge in popularity, driven by changing customer preferences and unique local circumstances.

Customer preferences: Travelers in Asia are increasingly seeking unique and personalized accommodation options that offer a more authentic and immersive experience during their vacations. This shift in preferences has led to a growing demand for vacation rentals over traditional hotels. Customers are drawn to the flexibility, privacy, and local charm that vacation rentals provide, allowing them to feel more at home while exploring new destinations.

Trends in the market: In Japan, the vacation rental market is booming due to the government's relaxation of regulations and the upcoming Tokyo Olympics. Travelers are opting for vacation rentals to experience the local culture and hospitality firsthand. The trend is similar in Thailand, where tourists are looking for alternative accommodation options beyond resorts and hotels, driving the growth of the vacation rental sector.

Local special circumstances: In Bali, Indonesia, the rise of digital nomads and remote workers has fueled the demand for long-term vacation rentals with reliable Wi-Fi and comfortable workspaces. Many properties in Bali cater specifically to this niche market, offering amenities that cater to the needs of remote workers. This unique local circumstance has positioned Bali as a desirable destination for those looking to combine work and leisure in a tropical setting.

Underlying macroeconomic factors: The economic growth in countries like China and India has resulted in a burgeoning middle class with increased disposable income, leading to a rise in domestic and international travel within Asia. As more people have the means to explore new destinations, the demand for vacation rentals is expected to continue growing. Additionally, the proliferation of online booking platforms and digital payment methods has made it easier for travelers to discover and book vacation rentals, contributing to the market's expansion.

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.