Vacation Rentals - Myanmar

Myanmar

Highlights

By 2024, it is projected that the Vacation Rentals market in Myanmar will generate a revenue of US$82.17m.
Moreover, it is expected to exhibit an annual growth rate (CAGR 2024-2029) of 7.71%, resulting in a projected market volume of US$119.10m by 2029.
In terms of user base, the market is expected to have 2.57m users users by 2029.
The user penetration rate which stood at 3.9% in 2024, is expected to increase and reach 4.5% by 2029.
Furthermore, the average revenue generated per user (ARPU) is anticipated to be US$38.46.
It is expected that 85% of the total revenue generated by the Vacation Rentals market will come from online sales by 2029.
In a global comparison, the highest revenue in this market will be generated United States, which is expected to reach US$20bn in 2024.
Myanmar's Vacation Rentals market is rapidly growing, driven by a rise in tourism and the country's unique cultural heritage.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

Myanmar, known for its rich cultural heritage and beautiful landscapes, has seen a significant growth in the Vacation Rentals market in recent years.

Customer preferences: Travelers in Myanmar are increasingly looking for unique and authentic experiences, driving the demand for vacation rentals over traditional hotel accommodations. Many tourists prefer the flexibility and privacy that vacation rentals offer, allowing them to immerse themselves in the local culture and lifestyle.

Trends in the market: One noticeable trend in the Vacation Rentals market in Myanmar is the rise of eco-friendly and sustainable accommodations. Travelers are becoming more conscious of their environmental impact, leading to a growing number of eco-friendly vacation rental options in the country. Additionally, with the increasing popularity of digital nomadism, there has been a surge in demand for long-term vacation rentals that cater to remote workers.

Local special circumstances: Myanmar's unique blend of traditional and modern influences has shaped the Vacation Rentals market in the country. Many vacation rentals in Myanmar showcase traditional architecture and design, providing guests with an authentic cultural experience. Furthermore, the warm hospitality of the local people has contributed to the growth of the vacation rental sector, with many visitors opting for homestays and guesthouses to interact closely with the locals.

Underlying macroeconomic factors: The growing tourism industry in Myanmar, coupled with improvements in infrastructure and connectivity, has played a crucial role in the development of the Vacation Rentals market. As the country opens up to more international visitors, the demand for alternative accommodations is expected to continue rising. Additionally, the government's efforts to promote tourism and attract foreign investment have created a favorable environment for the vacation rental sector to thrive.

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.