Market Insights Mobility Travel & Tourism

Package Holidays - Indonesia

Indonesia

By 2024, the projected revenue in the Package Holidays market of Indonesia is expected to reach €2.94bn.
Moreover, the market is expected to grow annually at a rate of 6.97%, resulting in a projected market volume of €3.85bn by 2028.
The number of users is also expected to increase, reaching 19.07m users by 2028.
User penetration, which is currently at 6.2% in 2024, is expected to rise to 6.6% by 2028.
The average revenue per user (ARPU) is expected to be €168.50.
Additionally, in the Package Holidays market of Indonesia, 71% of the total revenue will come from online sales by 2028.
It's worth noting that in a global comparison, China is projected to generate the most revenue, reaching €54,720m in 2024.
Indonesia's package holiday market is thriving due to its diverse culture, stunning landscapes, and affordable prices.

Key regions: United Kingdom, India, Indonesia, Germany, Malaysia

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Analyst Opinion

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

Customer preferences: Indonesian customers are increasingly drawn to the convenience and affordability of package holidays, which often include flights, accommodations, and activities all in one bundled price. This all-inclusive approach appeals to travelers looking for a hassle-free vacation experience without the need to plan every detail themselves.

Trends in the market: One notable trend in the Indonesian Package Holidays market is the rise of domestic tourism. As more Indonesians explore their own country, there is a growing demand for package holidays to domestic destinations. This trend is driven by factors such as improved infrastructure, rising disposable incomes, and a desire to discover the diverse attractions Indonesia has to offer.

Local special circumstances: Indonesia's archipelagic nature presents a unique opportunity for package holiday providers to offer a wide range of destinations to travelers. From the pristine beaches of Bali to the cultural richness of Yogyakarta, Indonesia has something for every type of traveler. This diversity allows for a variety of package options catering to different interests and preferences.

Underlying macroeconomic factors: The growing middle class in Indonesia is playing a significant role in the development of the Package Holidays market. With more disposable income, an increasing number of Indonesians are able to afford travel packages that were previously considered luxury items. Additionally, the government's efforts to promote tourism and improve infrastructure have boosted the overall tourism industry, benefiting the package holidays sector as well.

Methodology

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.