Market Insights Mobility Travel & Tourism

Package Holidays - Netherlands

Netherlands

By 2024, the Package Holidays market in the Netherlands is predicted to generate a revenue of €4.07bn.
Furthermore, the revenue is projected to experience an annual growth rate (CAGR 2024-2028) of 1.50%, resulting in an estimated market volume of €4.32bn by 2028.
During the same period, the number of users in this market is expected to reach 3.71m users.
In 2024, the user penetration rate is estimated to be 20.5% and is expected to increase to 20.8% by 2028.
The average revenue per user (ARPU) is expected to be €1.13k.
It is anticipated that 72% of the total revenue in the Package Holidays market will be generated through online sales by 2028.
Comparing globally, China is expected to generate the highest revenue of €55,510m in 2024 in this market.
Netherlands' package holiday market is seeing a shift towards sustainable and eco-friendly tourism options.

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

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Analyst Opinion

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

Customer preferences: Dutch consumers are increasingly valuing convenience and hassle-free travel experiences, which has led to a rise in the demand for package holidays. With busy lifestyles, customers are looking for all-inclusive options that provide them with a seamless vacation experience without the need to plan every detail themselves.

Trends in the market: One noticeable trend in the Netherlands is the shift towards sustainable and responsible tourism. Travelers are becoming more conscious of their environmental impact and are actively seeking package holidays that promote eco-friendly practices and support local communities. This trend has influenced tour operators to offer more sustainable options in response to the growing demand.

Local special circumstances: The geography of the Netherlands, with its flat landscape and extensive network of cycling routes, has also shaped the package holidays market. Cycling holidays have become particularly popular among both domestic and international tourists, allowing them to explore the country's picturesque countryside and charming towns at a leisurely pace. This unique selling point has attracted a niche market of cycling enthusiasts to the Netherlands.

Underlying macroeconomic factors: Furthermore, the stable economy and high disposable income levels in the Netherlands have contributed to the growth of the package holidays market. With more spending power, consumers are willing to invest in premium travel experiences, including luxury package holidays that offer exclusive amenities and personalized services. The strong purchasing power of Dutch travelers has created opportunities for tour operators to diversify their offerings and cater to different segments of the market.

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.