Package Holidays - Thailand

Thailand

Highlights

It is projected that the Package Holidays market in Thailand will generate a revenue of US$1.30bn by 2024.
Moreover, it is expected that the revenue will experience an annual growth rate (CAGR 2024-2029) of 6.75%, leading to an anticipated market volume of US$1.80bn by 2029.
The number of users is also expected to increase in the Package Holidays market, with an estimation of 6.53m users users by 2029.
In 2024, the user penetration rate is projected to be 7.5% and it is expected to increase to 9.1% by 2029.
The average revenue per user (ARPU) is projected to be US$240.90.
Online sales are also expected to contribute a significant portion to the total revenue of the Package Holidays market, with an estimation of 80% by 2029.
It is worth mentioning that, in comparison to other countries, China is expected to generate the highest revenue in the Package Holidays market, with a projection of US$49bn in 2024.
Thailand's package holiday market continues to thrive, offering a diverse range of experiences from beach resorts to cultural tours.

Key regions:

Market definitionIn-Scope/Out-of-scopeMarket structureReportsMethodology

The Package Holidays market in Thailand has been experiencing significant growth and development in recent years.

Customer preferences: Travelers in Thailand are increasingly seeking convenience and hassle-free experiences when planning their vacations. The all-inclusive nature of package holidays, which typically include accommodation, meals, and activities, aligns well with the preferences of Thai tourists. Additionally, the peace of mind that comes with having everything organized by a single provider is becoming more appealing to travelers looking to relax and unwind during their holidays.

Trends in the market: One noticeable trend in the Package Holidays market in Thailand is the rise of personalized and experiential packages. Tour operators are now offering unique experiences tailored to the interests of different traveler segments, such as wellness retreats, cultural immersions, and eco-friendly adventures. This trend caters to the growing demand for authentic and memorable travel experiences among Thai tourists.

Local special circumstances: Thailand's diverse landscape and rich cultural heritage make it an attractive destination for both domestic and international tourists. The country's tropical beaches, historical sites, and vibrant cities provide a wide range of options for package holiday offerings. Moreover, the Thai government's efforts to promote tourism and improve infrastructure have further boosted the attractiveness of the Package Holidays market in the country.

Underlying macroeconomic factors: The stable economic growth in Thailand has contributed to the increasing disposable income of its residents, allowing more people to afford package holidays. Furthermore, the growing middle-class population in the country has led to a rise in domestic tourism, with many Thais opting for convenient and cost-effective package holiday options. Additionally, the strengthening of the Thai baht against other currencies has made international travel more affordable for Thai travelers, driving further growth in the Package Holidays 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.