Package Holidays - EMEA

  • EMEA
  • Revenue in the Package Holidays market is projected to reach US$146.90bn in 2024.
  • Revenue is expected to show an annual growth rate (CAGR 2024-2029) of 3.24%, resulting in a projected market volume of US$172.30bn by 2029.
  • In the Package Holidays market, the number of users is expected to amount to 225.00m users by 2029.
  • User penetration is projected to be 7.8% in 2024 and 8.6% by 2029.
  • The average revenue per user (ARPU) is expected to amount to US$0.77k.
  • In the Package Holidays market, 81% of total revenue will be generated through online sales by 2029.
  • In global comparison, most revenue will be generated in China (US$49,250m in 2024).

Key regions: Singapore, India, Indonesia, Germany, Saudi Arabia

 
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Analyst Opinion

The Package Holidays market in EMEA is experiencing significant growth and development driven by changing customer preferences, emerging trends, local special circumstances, and underlying macroeconomic factors.

Customer preferences:
Customers in the EMEA region are increasingly seeking convenience and hassle-free travel experiences, leading to a rising demand for package holidays. The all-inclusive nature of package holidays, which typically include flights, accommodation, meals, and activities, appeals to travelers looking for a seamless vacation experience without the need to plan each aspect individually.

Trends in the market:
In the EMEA region, there is a noticeable trend towards personalized and experiential package holidays. Travelers are looking for unique experiences that cater to their specific interests and preferences, leading to the emergence of niche package holiday offerings such as wellness retreats, adventure tours, and cultural immersions. This trend is driven by a desire for authenticity and memorable experiences while on vacation.

Local special circumstances:
Each country in the EMEA region presents unique opportunities and challenges for the package holidays market. For example, popular tourist destinations like Spain and Greece benefit from a well-established tourism infrastructure and diverse attractions, making them attractive for package holiday providers. On the other hand, emerging markets in Eastern Europe offer untapped potential for growth but may require investment in infrastructure and marketing to attract international visitors.

Underlying macroeconomic factors:
The growth of the package holidays market in EMEA is also influenced by macroeconomic factors such as exchange rates, disposable income levels, and economic stability. Fluctuations in currency values can impact the affordability of international travel, while changes in disposable income affect consumers' willingness to spend on leisure activities like holidays. Economic stability and political factors can also influence consumer confidence and travel decisions, impacting the overall demand for package holidays in the region.

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.

Overview

  • Revenue
  • Sales Channels
  • Analyst Opinion
  • Users
  • Global Comparison
  • Methodology
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