Package Holidays - Southern Europe

  • Southern Europe
  • Southern Europe is expected to see a rise in revenue within the Package Holidays market, as it is projected to reach US$30.10bn in 2024.
  • Moreover, this market is anticipated to show an annual growth rate (CAGR 2024-2029) of 2.56%, resulting in a projected market volume of US$34.15bn by 2029.
  • Furthermore, it is expected that the number of users in this market will amount to 40.17m users by 2029, with a user penetration of 15.1% in 2024 and an expected increase to 17.0% by 2029.
  • The average revenue per user (ARPU) is expected to be US$0.84k.
  • Additionally, it is projected that 78% of the total revenue in this market will be generated through online sales by 2029.
  • Finally, it is worth mentioning that, in a global comparison, the highest revenue in this market is expected to be generated China, projected to reach US$49,250m in 2024.
  • Spain's package holiday market is seeing a shift towards sustainable tourism, with an emphasis on eco-friendly accommodations and activities.

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

 
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Analyst Opinion

The Package Holidays market in Southern Europe has been experiencing significant growth and evolution in recent years.

Customer preferences:
Travelers in Southern Europe are increasingly looking for convenience and hassle-free experiences when planning their holidays. Package holidays offer a one-stop solution that includes flights, accommodation, and sometimes even meals and activities, catering to the preferences of customers who seek a seamless vacation experience.

Trends in the market:
In countries like Spain and Italy, popular destinations for package holidays in Southern Europe, there has been a noticeable shift towards more personalized and experiential travel packages. Travelers are looking for unique experiences that allow them to immerse themselves in the local culture and lifestyle, leading to the development of specialized packages that focus on activities such as culinary tours, wellness retreats, and eco-friendly stays.

Local special circumstances:
Countries in Southern Europe benefit from a diverse range of attractions including beautiful coastlines, rich historical heritage, and vibrant cities, making them appealing destinations for package holidays. The Mediterranean climate and the region's renowned hospitality further contribute to the popularity of package holidays in Southern Europe.

Underlying macroeconomic factors:
The economic stability and improved infrastructure in Southern European countries have made them more accessible to tourists, driving the growth of the package holidays market. Additionally, the rise of online booking platforms and travel agencies has made it easier for travelers to compare and choose from a wide range of package deals, further fueling the market expansion.

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
  • Key Market Indicators
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