Vacation Rentals - Lithuania

Lithuania

Highlights

Lithuania is expected to witness a rise in the revenue of the Vacation Rentals market.
As per the projection, the revenue of the market is expected to reach US$89.75m in 2024 and show an annual growth rate (CAGR 2024-2029) of 3.01%.
This growth rate will ultimately result in a projected market volume of US$104.10m by 2029.
Furthermore, in the Vacation Rentals market, the number of users is estimated to reach 801.90k users by 2029.
The user penetration is expected to increase from 28.9% in 2024 to 31.1% by 2029.
It is noteworthy that the average revenue per user (ARPU) is expected to be US$115.50.
In terms of revenue generation through online sales, it is expected that 81% of total revenue will be generated through online sales by 2029.
It is also important to mention that in the global comparison, United States is projected to generate the most revenue in the Vacation Rentals market, which is expected to reach US$20bn in 2024.
The Vacation Rentals market in Lithuania is growing with an emphasis on unique and traditional accommodations in rural areas.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Vacation Rentals market in Lithuania has been experiencing a steady growth in recent years, reflecting the global trend of increasing popularity of alternative accommodations over traditional hotels.

Customer preferences: Travelers in Lithuania are increasingly seeking unique and authentic experiences, driving the demand for vacation rentals. Many tourists prefer the flexibility and privacy offered by vacation rental properties, allowing them to immerse themselves in the local culture and lifestyle. Additionally, the affordability of vacation rentals compared to hotels is appealing to budget-conscious travelers.

Trends in the market: One noticeable trend in the Lithuanian vacation rental market is the growing number of properties being listed on online platforms. Hosts are recognizing the opportunity to earn extra income by renting out their properties to tourists. This trend has led to a wider variety of vacation rental options available to travelers, catering to different preferences and budgets.

Local special circumstances: Lithuania's picturesque landscapes, charming historic towns, and vibrant cultural scene make it an attractive destination for tourists seeking a unique travel experience. The increasing number of international visitors to Lithuania has also contributed to the growth of the vacation rental market, as travelers look for accommodation options that offer a more personalized stay.

Underlying macroeconomic factors: The overall growth of the tourism industry in Lithuania, supported by initiatives to promote the country as a travel destination, has had a positive impact on the vacation rental market. Economic stability and rising disposable incomes have also made travel more accessible to a larger segment of the population, leading to an increase in domestic tourism and 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.