Vacation Rentals - Uzbekistan

Uzbekistan

Highlights

By 2024, the Vacation Rentals market in Uzbekistan is expected to generate a revenue of US$48.70m.
According to forecasts, this figure will grow annually at a rate of 8.60% (CAGR 2024-2029), eventually reaching a market volume of US$73.58m by 2029.
Additionally, the number of users in this market is expected to increase to 2.63m users by 2029, with a user penetration of 4.5% in 2024 and an expected increase to 6.9% in 2029.
The average revenue per user (ARPU) is expected to be US$30.26.
Furthermore, 88% of the total revenue generated in the Vacation Rentals market in Uzbekistan will be through online sales by 2029.
It is worth mentioning that in global comparison, United States will generate the most revenue in this market, with a projected revenue of US$20bn in 2024.
Despite being a relatively new market, vacation rentals in Uzbekistan are gaining popularity among tourists seeking an authentic cultural experience.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

Amidst the rich cultural tapestry and historical wonders of Uzbekistan, the Vacation Rentals market is experiencing a notable surge in popularity.

Customer preferences: Travelers in Uzbekistan are increasingly leaning towards vacation rentals due to the desire for more authentic and immersive travel experiences. The opportunity to stay in local neighborhoods and interact with residents provides a unique perspective that traditional hotels often lack.

Trends in the market: One of the prominent trends in the Uzbekistan Vacation Rentals market is the growing number of local hosts offering unique accommodations. From traditional guesthouses in historic cities like Samarkand to yurts in the scenic countryside, travelers have a wide range of options to choose from. This diversity caters to different preferences and budgets, contributing to the overall growth of the market.

Local special circumstances: Uzbekistan's rich cultural heritage and architectural marvels play a significant role in driving the demand for vacation rentals. Travelers are drawn to the opportunity to stay in traditional Uzbek homes, allowing them to immerse themselves in the local culture and lifestyle. Additionally, the warm hospitality of Uzbek hosts adds a personal touch to the accommodation experience, making visitors feel welcomed and valued.

Underlying macroeconomic factors: The increasing focus on tourism development in Uzbekistan, coupled with government initiatives to promote the sector, has created a favorable environment for the Vacation Rentals market. The growing infrastructure, improved connectivity, and simplified visa procedures have made the country more accessible to international travelers, boosting the demand for alternative accommodation options like vacation rentals. Additionally, the rising disposable incomes and changing travel preferences among domestic tourists have further fueled the expansion of the market.

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.