Vacation Rentals - Turkey

Turkey

Highlights

Turkey's Vacation Rentals market is expected to reach a revenue of US$1.39bn in 2024.
The revenue is projected to grow annually at a rate of 15.14% from 2024 to 2029, reaching a market volume of US$2.81bn by the end of 2029.
The number of users in the Vacation Rentals market is expected to increase to 22.07m users by 2029, with a user penetration rate of 17.1% in 2024, which is expected to rise to 24.9% by 2029.
The average revenue per user (ARPU) in Turkey is expected to be US$94.27.
The online sales are projected to contribute to 68% of the total revenue in the Vacation Rentals market in Turkey by 2029.
Compared 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.
Turkey is experiencing a rise in demand for vacation rentals due to its unique blend of culture, history, and natural beauty.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

Amidst the rich history and stunning landscapes of Turkey, the Vacation Rentals market is experiencing a significant surge in popularity.

Customer preferences: Travelers in Turkey are increasingly opting for vacation rentals over traditional hotels due to the desire for a more authentic and immersive travel experience. The flexibility, privacy, and often lower cost of vacation rentals are appealing to a wide range of visitors, from families to solo travelers.

Trends in the market: One notable trend in the Vacation Rentals market in Turkey is the growing popularity of unique and boutique accommodations. Travelers are seeking out properties that offer a sense of local charm and character, such as historic houses or traditional villas. This trend aligns with the overall global shift towards experiential travel and a desire for more personalized stays.

Local special circumstances: Turkey's diverse geography and cultural heritage provide a unique backdrop for the Vacation Rentals market. From the bustling streets of Istanbul to the tranquil beaches of the Mediterranean coast, there is a wide variety of destinations for travelers to explore. This diversity offers property owners the opportunity to cater to different preferences and attract a range of visitors.

Underlying macroeconomic factors: The development of the Vacation Rentals market in Turkey is also influenced by macroeconomic factors such as currency exchange rates and government regulations. Fluctuations in the Turkish Lira can impact the affordability of travel for international visitors, while changes in legislation related to short-term rentals can affect the ease of hosting properties. Despite these challenges, the market continues to grow as both domestic and international travelers recognize the value of vacation rentals in Turkey.

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.