Vacation Rentals - Croatia

Croatia

Highlights

The Vacation Rentals market in Croatia is expected to see significant growth in the coming years, with revenue projected to reach US$63.18m by 2024.
Looking ahead, there is an anticipated annual growth rate of 4.34% between 2024 and 2029, which is expected to result in a market volume of US$78.12m by 2029.
In terms of user numbers, the Vacation Rentals market in Croatia is expected to have 864.80k users users by 2029.
The user penetration rate is projected to increase from 20.3% in 2024 to 22.3% in 2029.
The average revenue per user (ARPU) is expected to be US$77.86.
It is also expected that 79% of the total revenue for the Vacation Rentals market in Croatia will come from online sales by 2029.
In comparison 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.
Croatia's Vacation Rentals market is thriving due to its picturesque coastline, historic cities, and growing reputation as a top European destination.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Vacation Rentals market in Croatia has been experiencing a significant growth in recent years.

Customer preferences: Travelers are increasingly seeking unique and authentic experiences, leading to a rise in demand for vacation rentals over traditional hotels. This shift in preference is driven by a desire for more space, privacy, and flexibility during holidays.

Trends in the market: One notable trend in the Croatian vacation rental market is the increasing popularity of coastal properties. Croatia's stunning Adriatic coastline, with its crystal-clear waters and picturesque towns, attracts a large number of tourists looking for beachfront accommodations. As a result, seaside vacation rentals have been in high demand, especially during the peak summer season.

Local special circumstances: Croatia's membership in the European Union has positively impacted its tourism industry, making it more accessible to travelers from EU countries. The country's rich cultural heritage, Mediterranean climate, and diverse natural landscapes also contribute to its appeal as a vacation destination. Additionally, the presence of popular tourist destinations like Dubrovnik, Split, and Hvar has boosted the demand for vacation rentals in these areas.

Underlying macroeconomic factors: The overall growth of the Croatian economy and increasing disposable incomes have allowed more people to travel and explore the country. This economic stability has translated into higher spending on vacations, including accommodation options like vacation rentals. Furthermore, Croatia's efforts to improve its infrastructure and promote tourism have made it a more attractive destination for both domestic and international travelers, driving the growth of the vacation rental 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.