Vacation Rentals - Singapore

  • Singapore
  • Singapore is expected to witness a significant growth in the Vacation Rentals market.
  • By 2024, it is projected that the revenue in this market will reach €345.70m.
  • Furthermore, there is an expected annual growth rate of 3.94%, resulting in a projected market volume of €419.30m by 2029.
  • The number of users in the Vacation Rentals market is also expected to increase to 1.65m users by 2029.
  • It is worth noting that the user penetration rate is expected to increase from 23.6% in 2024 to 26.6% by 2029.
  • Moreover, the average revenue per user (ARPU) is expected to be €242.10.
  • In the Vacation Rentals market, it is projected that 90% of the total revenue will be generated through online sales by 2029.
  • It is also interesting to note that in global comparison, United States is expected to generate the most revenue in this market, with a projected revenue of €18,800m in 2024.
  • Singapore's Vacation Rentals market is seeing an uptick in demand for luxury properties with private pools and sea views.

Key regions: India, Vietnam, Saudi Arabia, Singapore, Germany

 
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Comparaison de régions
 
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Analyst Opinion

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

Customer preferences:
Customers in Singapore are increasingly looking for unique and personalized vacation experiences, driving the demand for vacation rentals over traditional accommodation options. The flexibility, affordability, and local immersion offered by vacation rentals are appealing to travelers seeking a more authentic experience.

Trends in the market:
One notable trend in the Singapore Vacation Rentals market is the rise of short-term rental platforms and online booking services, making it easier for property owners to list their spaces and for travelers to find and book accommodations. Additionally, the increasing popularity of staycations among locals has boosted the demand for vacation rentals within the country.

Local special circumstances:
Singapore's limited land space and strict regulations on property ownership have led to a growing trend of property owners renting out their spaces as vacation rentals to generate additional income. The diverse range of vacation rental options available in Singapore, from luxury condos to heritage shophouses, caters to the varied preferences of travelers.

Underlying macroeconomic factors:
Singapore's strong economy and status as a global business hub have attracted a steady flow of business and leisure travelers, contributing to the demand for vacation rentals. Additionally, the government's efforts to promote tourism and hospitality have further fueled the growth of the Vacation Rentals market in the country.

Methodology

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.

Vue d’ensemble

  • Revenue
  • Sales Channels
  • Analyst Opinion
  • Users
  • User Demographics
  • Global Comparison
  • Methodology
  • Key Market Indicators
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