Vacation Rentals - Laos

Laos

Highlights

Laos is expected to witness a steady growth in the revenue of its Vacation Rentals market, with a projected revenue of US$32.19m by 2024.
This is expected to show an annual growth rate (CAGR 2024-2029) of 8.07%, resulting in a projected market volume of US$47.45m by 2029.
Additionally, the number of users in this market is expected to reach 671.10k users by 2029, with a user penetration of 6.2% in 2024 and an expected increase to 8.2% by 2029.
The average revenue per user (ARPU) is expected to be US$67.60.
Furthermore, it is projected that 65% of the total revenue in this market will be generated through online sales by 2029.
In comparison to other countries, United States is expected to generate the most revenue in the Vacation Rentals market, with a projected revenue of US$20bn in 2024.
Laos' Vacation Rentals market is growing steadily, offering unique and authentic experiences for travelers seeking to explore the country's rich cultural heritage.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Vacation Rentals market in Laos is experiencing a gradual but steady growth, influenced by various factors shaping the industry in the country.

Customer preferences: Travelers in Laos are increasingly seeking unique and authentic experiences, which has led to a rise in demand for vacation rentals over traditional hotel accommodations. The desire to immerse themselves in the local culture and lifestyle is driving tourists to opt for vacation rentals that offer a more personalized and intimate stay.

Trends in the market: One notable trend in the Vacation Rentals market in Laos is the increasing popularity of eco-friendly and sustainable properties. Travelers are showing a preference for accommodations that prioritize environmental conservation and support local communities. This trend aligns with global concerns about sustainability and responsible tourism practices.

Local special circumstances: Laos, known for its rich cultural heritage and stunning natural landscapes, offers a unique setting for vacation rentals. The country's serene environment and traditional architecture attract tourists looking for a peaceful retreat away from the hustle and bustle of city life. Vacation rental properties in Laos often reflect the local aesthetic and charm, providing guests with an authentic Lao experience.

Underlying macroeconomic factors: The growing tourism industry in Laos, supported by government initiatives to promote the country as a travel destination, is driving the expansion of the Vacation Rentals market. As more tourists discover the hidden gems of Laos, the demand for alternative accommodations such as vacation rentals is expected to continue rising. Additionally, the increasing connectivity and infrastructure development in the country are making it easier for travelers to explore different regions, further fueling the demand for vacation rental properties.

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.