Package Holidays - GCC

  • GCC
  • It is projected that by 2024, the Package Holidays market in the GCC will generate a revenue of US$2.09bn.
  • Moreover, the market is expected to grow annually by 3.73% until 2029, resulting in a market volume of US$2.51bn.
  • By 2029, the number of users is expected to reach 4.59m users in the Package Holidays market, with a user penetration of 6.2% in 2024 and an expected rise to 7.2% by 2029.
  • The ARPU is expected to be US$0.56k.
  • In this market, it is expected that 88% of the total revenue will be generated through online sales by 2029.
  • It is noteworthy that in global comparison, China is expected to generate the highest revenue in the Package Holidays market, with US$49,250m in 2024.
  • Despite the rise of independent travel, package holidays remain popular among families in the GCC due to their convenience and all-inclusive nature.

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

 
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Analyst Opinion

The Package Holidays market in GCC is experiencing a significant shift in consumer preferences, leading to notable trends and developments in the industry.

Customer preferences:
Customers in the GCC region are increasingly seeking convenience and hassle-free travel experiences, which has boosted the demand for package holidays. This trend is driven by the busy lifestyles of consumers who are looking for all-inclusive travel options that save time and offer value for money.

Trends in the market:
In the GCC, there is a growing preference for luxury package holidays that offer premium accommodation, exclusive experiences, and personalized services. Travelers in the region are willing to pay more for high-end packages that cater to their specific needs and preferences. Additionally, there is a rising interest in eco-friendly and sustainable travel options among consumers in the GCC, leading to an increase in demand for package holidays that focus on responsible tourism practices.

Local special circumstances:
The GCC countries have unique cultural and social norms that influence the package holidays market. For example, the concept of family is highly valued in the region, leading to a demand for family-friendly package holidays that cater to the needs of all age groups. Moreover, the popularity of shopping and dining experiences in the GCC has resulted in the emergence of themed package holidays that focus on retail therapy and gastronomic adventures.

Underlying macroeconomic factors:
The economic prosperity and high disposable incomes in the GCC countries have contributed to the growth of the package holidays market. As consumers in the region become more affluent, they are willing to spend more on travel experiences, including luxury package holidays. Additionally, the government initiatives to promote tourism and develop the hospitality sector have further boosted the demand for package holidays in the GCC.

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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