Package Holidays - Dominican Republic

Dominican Republic

Highlights

The Dominican Republic is expected to experience a rise in revenue for the Package Holidays market, with projections indicating that it will reach US$260.30m by 2024.
This number is expected to increase at an annual growth rate of 6.77%, resulting in a market volume of US$361.20m by 2029.
As for the number of users, it is projected to amount to 869.60k users by 2029, with a user penetration of 6.1% in 2024, which is expected to hit 7.3% by 2029.
The average revenue per user (ARPU) is expected to be US$370.40.
It is also expected that 75% of the total revenue in this market will be generated through online sales by 2029.
It is interesting to note that in global comparison, China is expected to generate the most revenue in this market, with a projected revenue of US$49bn in 2024.
However, in the Dominican Republic is expected to have a significant share of the market as well.
The Dominican Republic's package holiday market is experiencing growth due to its beautiful beaches and all-inclusive resorts.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Package Holidays market in Dominican Republic has been experiencing a notable growth trajectory in recent years.

Customer preferences: Travelers in Dominican Republic are increasingly opting for package holidays due to the convenience and cost-effectiveness they offer. With busy lifestyles, customers appreciate the all-inclusive nature of package holidays that include accommodation, meals, and activities, allowing them to relax and enjoy their vacation without worrying about logistics.

Trends in the market: One of the prominent trends in the Package Holidays market in Dominican Republic is the rise of personalized and experiential packages. Travelers are seeking unique experiences that cater to their interests, such as eco-tourism, adventure sports, and cultural immersion. Tour operators are responding to this trend by offering specialized packages that provide authentic and memorable experiences for tourists.

Local special circumstances: The geographical diversity of Dominican Republic, with its stunning beaches, lush rainforests, and vibrant cities, presents a unique opportunity for the Package Holidays market. Tourists are drawn to the country's natural beauty and rich culture, making it a popular destination for package holidays. Additionally, the government's focus on promoting tourism and improving infrastructure has further boosted the growth of the market.

Underlying macroeconomic factors: The stable economic growth and increasing disposable income in Dominican Republic have played a significant role in driving the growth of the Package Holidays market. As more people have the financial means to travel, the demand for package holidays has increased. Additionally, the country's efforts to enhance its tourism sector through marketing campaigns and infrastructure development have attracted more international visitors, further fueling the growth of the market.

Data coverage:

The data encompasses B2C enterprises. Figures are based on bookings, revenues, and sales channels of package holidays.

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.