Package Holidays - Denmark

  • Denmark
  • It is estimated that the revenue for Denmark's Package Holidays market will reach US$2.66bn by 2024.
  • Furthermore, the market is projected to grow annually at a rate of 1.39% between 2024 and 2029, resulting in a market volume of US$2.85bn by 2029.
  • The number of users in this market is expected to increase to 2.52m users by 2029.
  • It is worth noting that the user penetration rate is projected to rise from 38.0% in 2024 to 41.4% by 2029.
  • The average revenue per user (ARPU) is expected to be US$1.18k.
  • In terms of sales, it is estimated that 80% of the total revenue in the Package Holidays market will come from online sales by 2029.
  • When compared globally, China is expected to generate the most revenue in this market, with a projected revenue of US$49,250m in 2024.
  • Denmark's package holiday market shows a growing interest in sustainable and eco-friendly travel options.

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

 
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Analyst Opinion

Denmark, known for its picturesque landscapes and vibrant cities, has seen a notable development in the Package Holidays market.

Customer preferences:
Travelers in Denmark are increasingly seeking convenience and hassle-free experiences when planning their holidays. The demand for package holidays has risen as it offers a one-stop solution for flights, accommodation, and activities. Customers value the time-saving aspect and the ability to have their entire trip organized for them.

Trends in the market:
One prominent trend in the Danish Package Holidays market is the growing popularity of sustainable and eco-friendly travel options. Travelers are becoming more conscious of their environmental impact and are actively seeking packages that promote responsible tourism. This trend has led to the emergence of eco-friendly accommodations and carbon-neutral travel packages in the market.

Local special circumstances:
Denmark's strong emphasis on work-life balance and quality of life has influenced the Package Holidays market. With generous vacation policies and a culture that values relaxation and leisure time, Danes are inclined to invest in high-quality holiday experiences. This has led to a demand for premium package holidays that offer luxury accommodations, unique experiences, and personalized services.

Underlying macroeconomic factors:
The stable economy and high standard of living in Denmark have contributed to the growth of the Package Holidays market. With increasing disposable income levels, more Danes have the financial means to invest in travel experiences. Additionally, the strong Danish currency makes international travel more affordable, encouraging consumers to explore a wider range of package holiday options both domestically and abroad.

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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