Vacation Rentals - Vietnam

Vietnam

Highlights

Vietnam is expected to experience a significant growth in the Vacation Rentals market as revenue is projected to reach US$370.40m by 2024.
This is a positive sign as revenue is expected to increase annually with a growth rate of 5.07%, resulting in a market volume projection of US$474.20m by 2029.
In terms of user base, the number of users is expected to increase to 11.80m users by 2029.
The user penetration rate is predicted to grow from 8.7% in 2024 to 11.5% by 2029.
As for the average revenue per user (ARPU), it is expected to remain steady at US$43.02.
Online sales are expected to generate 59% of the total revenue in the Vacation Rentals market by 2029.
It is interesting to note that in comparison to other countries, United States is projected to generate the most revenue in this market, with US$20bn in 2024.
Vietnam's Vacation Rentals market is on the rise as more tourists seek authentic experiences in traditional homestays and villas.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

Vietnam's Vacation Rentals market is experiencing significant growth and development, driven by various factors contributing to the increasing demand for alternative accommodations in the country.

Customer preferences: Travelers in Vietnam are increasingly seeking unique and personalized experiences, leading to a growing preference for vacation rentals over traditional hotels. The flexibility, authenticity, and affordability offered by vacation rentals appeal to a wide range of travelers, from budget-conscious backpackers to luxury-seeking tourists.

Trends in the market: One prominent trend in Vietnam's Vacation Rentals market is the rise of local hosts and property owners offering unique and culturally immersive accommodations. This trend not only caters to the demand for authentic experiences but also boosts the local economy by encouraging community-based tourism initiatives. Additionally, the market is witnessing a surge in digital platforms and online booking services, making it easier for travelers to discover and book vacation rentals across the country.

Local special circumstances: Vietnam's rich cultural heritage, diverse landscapes, and booming tourism industry contribute to the attractiveness of vacation rentals in the country. From charming homestays in rural villages to modern apartments in bustling cities, Vietnam offers a wide array of accommodation options that cater to different preferences and budgets. Moreover, the Vietnamese government's efforts to promote sustainable tourism practices and support the growth of the sharing economy have created a favorable environment for the Vacation Rentals market to thrive.

Underlying macroeconomic factors: The rapid economic growth, increasing disposable income, and expanding middle-class population in Vietnam are driving the demand for domestic and international travel. As more Vietnamese people embrace the travel culture and explore destinations within their own country, the Vacation Rentals market is poised to benefit from this growing trend. Additionally, the rise of digital technology and online platforms has made it easier for property owners to list their accommodations and for travelers to find and book vacation rentals, further fueling the market's growth.

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.