Package Holidays - Belgium

  • Belgium
  • Belgium is expected to generate a revenue of US$3.70bn in the Package Holidays market by 2024.
  • The revenue is expected to have an annual growth rate (CAGR 2024-2028) of 2.79%, resulting in a projected market volume of US$4.13bn by 2028.
  • The number of users in this market is expected to amount to 3.09m users by 2028, with a user penetration of 25.5% in 2024, which is expected to increase to 26.2% by 2028.
  • The average revenue per user (ARPU) is projected to be US$1.24k.
  • It is expected that 76% of total revenue will be generated through online sales by 2028.
  • In global comparison, China is expected to generate the most revenue in this market with a projected revenue of US$59,860m in 2024.
  • Belgians tend to opt for all-inclusive package holidays to sunny destinations such as Spain and Greece.

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

 
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Analyst Opinion

Belgium, known for its medieval towns, Renaissance architecture, and chocolate, also boasts a thriving Package Holidays market.

Customer preferences:
Belgian consumers are increasingly seeking convenience and hassle-free travel experiences, leading to a growing demand for package holidays. The all-inclusive nature of these packages, which often include flights, accommodation, and activities, appeals to customers looking for a seamless vacation experience without the need for extensive planning.

Trends in the market:
One prominent trend in the Package Holidays market in Belgium is the rising popularity of eco-friendly and sustainable travel options. Travelers are showing a preference for packages that prioritize environmental responsibility, such as eco-friendly accommodations and carbon offset programs. This trend aligns with the global shift towards sustainable tourism practices and reflects Belgian consumers' growing awareness of environmental issues.

Local special circumstances:
Belgium's central location in Europe makes it an attractive hub for international travel, further driving the demand for package holidays. The country's well-connected transportation network and proximity to other European destinations make it a convenient starting point for exploring the continent. Additionally, Belgium's diverse cultural offerings, including historic sites, culinary experiences, and vibrant festivals, contribute to the appeal of package holidays for both domestic and international tourists.

Underlying macroeconomic factors:
The stability of Belgium's economy and high standard of living have contributed to the growth of the Package Holidays market. With disposable incomes on the rise, Belgian consumers have more purchasing power to invest in leisure activities like travel. Additionally, the country's strong infrastructure and well-developed tourism industry support the accessibility and availability of package holiday options for a wide range of travelers.

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
  • User Demographics
  • Global Comparison
  • Methodology
  • Key Market Indicators
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