Vacation Rentals - Fiji

Fiji

Highlights

According to forecasts, the Vacation Rentals market in Fiji is expected to experience a significant increase in revenue.
Specifically, revenue is projected to reach US$5.86m by 2024 and grow at an annual rate of 5.62% until 2029, resulting in a market volume of US$7.70m.
In terms of user numbers, the market is expected to attract 122.70k users users by 2029, with user penetration increasing from 10.4% in 2024 to 12.5% by 2029.
The average revenue per user (ARPU) is expected to be US$59.80.
Furthermore, online sales are projected to account for 71% of total revenue by 2029.
It is worth noting that United States is expected to generate the most revenue globally, with an estimated revenue of US$20bn in 2024.
Fiji's Vacation Rentals market is characterized by luxurious villas, eco-friendly bungalows, and stunning oceanfront properties.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Vacation Rentals market in Fiji is experiencing a surge in popularity among tourists seeking unique and immersive travel experiences.

Customer preferences: Travelers in Fiji are increasingly looking for authentic and personalized vacation experiences, opting for vacation rentals over traditional hotels. This shift in preference can be attributed to the desire for a more local and cultural experience, as well as the flexibility and privacy that vacation rentals offer.

Trends in the market: One notable trend in the Vacation Rentals market in Fiji is the rise of eco-friendly and sustainable accommodations. With growing global awareness of environmental issues, travelers are actively seeking eco-conscious options, driving the demand for green vacation rentals in Fiji. Additionally, the market is seeing an increase in luxury vacation rentals catering to high-end travelers looking for exclusive and upscale accommodations.

Local special circumstances: Fiji's unique geography and rich cultural heritage make it a prime destination for vacation rentals. The country's stunning beaches, crystal-clear waters, and lush landscapes attract a diverse range of travelers, from honeymooners to adventure seekers. The warm hospitality of the Fijian people and the opportunity to immerse oneself in the local way of life further contribute to the appeal of vacation rentals in Fiji.

Underlying macroeconomic factors: The growth of the Vacation Rentals market in Fiji can also be attributed to the overall increase in tourism to the region. As Fiji continues to position itself as a top travel destination in the South Pacific, the demand for alternative accommodations such as vacation rentals is on the rise. Additionally, the government's efforts to promote tourism and improve infrastructure have created a favorable environment for the development of the vacation rental market in Fiji.

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.