Vacation Rentals - Romania

Romania

Highlights

It is projected that the Vacation Rentals market in Romania will experience a rise in revenue, with an estimated value of US$200.40m by 2024.
This projected growth is expected to continue at an annual rate of 4.86%, resulting in a market volume of US$254.00m by 2029.
In terms of user base, the number of users is expected to increase to 3.45m users by 2029.
With a user penetration rate of 15.8% in 2024, it is expected to increase to 18.1% by 2029.
Moreover, the average revenue per user (ARPU) is estimated to reach US$64.54.
When it comes to online sales, it is expected that 87% of the total revenue in the Vacation Rentals market in Romania will be generated through online channels by 2029.
It is worth noting that in comparison to other countries, United States is expected to generate the most revenue in this market, with an estimated value of US$20bn in 2024.
Romania's Vacation Rentals market is experiencing a rise in popularity due to its affordable prices and picturesque countryside locations.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Vacation Rentals market in Romania is experiencing a significant growth trajectory, driven by various factors that cater to the evolving needs and preferences of travelers in the region.

Customer preferences: Travelers in Romania are increasingly seeking unique and authentic experiences, driving the demand for vacation rentals over traditional accommodation options. The desire for personalized stays, flexibility in booking, and a sense of living like a local are key factors influencing customers to choose vacation rentals.

Trends in the market: One notable trend in the Romanian Vacation Rentals market is the rise of digital platforms and online booking services, making it easier for travelers to discover and book vacation rental properties. Additionally, the market is witnessing a surge in the popularity of eco-friendly and sustainable accommodations, reflecting the growing global trend towards responsible tourism.

Local special circumstances: Romania's rich cultural heritage, diverse landscapes, and historical attractions make it a popular tourist destination, further fueling the demand for vacation rentals. The country's vibrant cities, charming rural areas, and picturesque seaside towns offer a wide range of options for travelers seeking unique and memorable experiences.

Underlying macroeconomic factors: The growing economy in Romania, coupled with increasing disposable incomes and a rising middle class, has led to a boost in domestic tourism and a higher demand for alternative accommodation options like vacation rentals. Additionally, the government's efforts to promote tourism and improve infrastructure have contributed to the overall development of the Vacation Rentals market in the country.

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.