Vacation Rentals - Bolivia

Bolivia

Highlights

In Bolivia, the projected revenue for the Vacation Rentals market in 2024 is US$97.47m.
The revenue is anticipated to grow annually at a rate of 5.60% from 2024 to 2029, resulting in a projected market volume of US$128.00m by 2029.
By 2029, the number of users in the Vacation Rentals market is expected to reach 1.96m users.
The user penetration rate is predicted to increase from 11.7% in 2024 to 14.6% by 2029.
The average revenue per user (ARPU) is expected to be US$66.05.
By 2029, 62% of the total revenue in the Vacation Rentals market is expected to be generated through online sales.
It is noteworthy that in global comparison, United States is expected to generate the most revenue in the Vacation Rentals market, with a projected revenue of US$20bn in 2024.
Bolivia's Vacation Rentals market is still in its infancy, but with the country's rich cultural heritage and natural attractions, it has great potential for growth.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Vacation Rentals market in Bolivia is showing promising signs of growth and development.

Customer preferences: Travelers in Bolivia are increasingly seeking unique and authentic experiences, leading to a rise in demand for vacation rentals over traditional hotel stays. Customers are looking for accommodations that offer a more personalized and local experience, allowing them to immerse themselves in the culture and lifestyle of the destination.

Trends in the market: One notable trend in the Bolivian vacation rentals market is the increasing popularity of eco-friendly and sustainable properties. Travelers are becoming more conscious of their environmental impact and are actively seeking accommodations that prioritize sustainability. This trend is driving property owners to invest in eco-friendly features and practices to attract environmentally conscious guests.

Local special circumstances: Bolivia's diverse geography and rich cultural heritage make it a unique destination for travelers. From the bustling markets of La Paz to the serene shores of Lake Titicaca, Bolivia offers a wide range of experiences for visitors. This diversity presents an opportunity for vacation rental owners to cater to different types of travelers, whether they are seeking adventure, relaxation, or cultural immersion.

Underlying macroeconomic factors: The growing tourism industry in Bolivia, supported by government initiatives to promote the country as a travel destination, is fueling the demand for vacation rentals. Additionally, the increasing connectivity and accessibility of remote regions in Bolivia are making it easier for travelers to explore the country, leading to a higher demand for accommodations beyond traditional hotels. As the tourism sector continues to expand, the vacation rentals market in Bolivia is expected to grow further in the coming years.

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.