Vacation Rentals - Montenegro

Montenegro

Highlights

Montenegro's Vacation Rentals market is projected to reach a revenue of US$7.87m in 2024.
The revenue is predicted to grow annually at a rate of 2.23% between 2024 and 2029, resulting in a projected market volume of US$8.79m by 2029.
By 2029, the number of users in the Vacation Rentals market is expected to amount to 87.17k users, with a user penetration of 14.0%, up from 12.4% in 2024.
The average revenue per user (ARPU) is expected to be US$101.00.
It is projected that 69% of the total revenue in the Vacation Rentals market will be generated through online sales by 2029.
In comparison to other countries, United States will generate the most revenue, reaching US$20bn in 2024.
Vacation rentals in Montenegro are becoming increasingly popular among tourists due to the country's stunning coastal scenery and rich cultural heritage.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Vacation Rentals market in Montenegro is experiencing significant growth and development in recent years.

Customer preferences: Travelers in Montenegro are increasingly seeking unique and authentic experiences, driving the demand for vacation rentals that offer a more personalized and local stay. Tourists are looking for accommodations that provide a sense of immersion in the destination's culture and lifestyle, leading to a rise in bookings for vacation rental properties.

Trends in the market: One noticeable trend in the Montenegrin vacation rental market is the increasing popularity of properties in coastal areas, particularly along the Adriatic Sea. The stunning beaches and picturesque coastal towns attract a large number of tourists looking for beachfront villas and apartments. Additionally, the demand for eco-friendly and sustainable accommodations is on the rise, with travelers showing a preference for properties that prioritize environmental conservation.

Local special circumstances: Montenegro's unique geographical features, including its diverse landscapes ranging from mountains to beaches, offer a wide variety of vacation rental options for travelers. The country's rich history and cultural heritage also contribute to the appeal of vacation rentals in traditional stone houses or historic buildings. Furthermore, Montenegro's status as an emerging tourist destination in Europe has led to an influx of international visitors seeking alternative accommodation options beyond traditional hotels.

Underlying macroeconomic factors: The growth of the vacation rental market in Montenegro can be attributed to several macroeconomic factors, such as increasing disposable income levels among tourists, improved infrastructure and connectivity, and government initiatives to promote tourism. The country's stable economic environment and favorable investment climate have also encouraged property owners to enter the vacation rental market, further expanding the accommodation options available to travelers.

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.