Package Holidays - Southeast Asia

Southeast Asia

Highlights

It is projected that the revenue in the Package Holidays market, for Southeast Asia, will reach US$12.34bn by 2024.
The revenue is expected to show an annual growth rate (CAGR 2024-2029) of 6.08%, leading to a projected market volume of US$16.58bn by 2029.
By 2029, the number of users in the Package Holidays market is expected to amount to 57.76m users.
In 2024, the user penetration is 6.6% and it is expected to increase to 8.0% by 2029.
The average revenue per user (ARPU) is expected to be US$270.40.
It is projected that 76% of the total revenue in the Package Holidays market will be generated through online sales by 2029.
When compared globally, China is expected to generate the most revenue in the Package Holidays market by 2024, with a projected revenue of US$49bn.
The package holiday market in Thailand is experiencing a shift towards sustainable tourism, with a growing number of travelers seeking eco-friendly and culturally immersive experiences.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Package Holidays market in Southeast Asia is experiencing steady growth and development due to changing customer preferences, emerging trends, and local special circumstances in the region.

Customer preferences: Customers in Southeast Asia are increasingly seeking convenience and hassle-free travel experiences, which has led to a rise in demand for package holidays. Travelers appreciate the all-inclusive nature of package holidays, which often include accommodations, transportation, meals, and activities, providing them with a seamless vacation experience.

Trends in the market: In Thailand, the Package Holidays market is seeing a surge in popularity due to the country's diverse attractions, including pristine beaches, vibrant cities, and rich cultural heritage. Tour operators are offering specialized packages catering to different interests, such as wellness retreats, adventure tours, and cultural experiences, to meet the evolving demands of travelers.

Local special circumstances: Indonesia, with its vast archipelago and diverse landscapes, is witnessing a growing trend of eco-friendly and sustainable package holidays. Travelers are increasingly conscious of their environmental impact and are opting for tours that promote conservation efforts, support local communities, and minimize carbon footprints. This shift towards sustainable tourism is shaping the Package Holidays market in the country.

Underlying macroeconomic factors: The economic growth and rising disposable incomes in countries like Vietnam are driving the expansion of the Package Holidays market. As more people in the region enter the middle-class segment, there is a greater appetite for travel and exploration, leading to an increased demand for package holidays. Additionally, government initiatives to promote tourism and improve infrastructure are further fueling the growth of the market in Southeast Asia.

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.