Package Holidays - South Africa

  • South Africa
  • South Africa is expected to witness a rise in Package Holidays market revenue, which is projected to reach €0.60bn by 2024.
  • Furthermore, the sector is anticipated to witness a Compound Annual Growth Rate (CAGR) of 6.19% from 2024 to 2029, thereby resulting in a market volume of €0.81bn by the end of 2029.
  • It is estimated that the number of users in the Package Holidays market will reach 3.24m users by 2029, with a user penetration of 4.3% in 2024, which is expected to increase to 5.1% by 2029.
  • The Average Revenue Per User (ARPU) is expected to be €229.80.
  • By 2029, approximately 74% of the total revenue in the Package Holidays market will be generated through online sales.
  • In terms of global comparison, China is expected to generate the highest revenue of €45,200m in 2024.
  • South Africa's package holiday market is seeing a rise in demand for sustainable and eco-friendly options.

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

 
Marché
 
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Comparaison de régions
 
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Analyst Opinion

The Package Holidays market in South Africa has been experiencing significant growth and development in recent years.

Customer preferences:
Customers in South Africa are increasingly seeking convenience and hassle-free travel experiences, which has led to a growing demand for package holidays. The all-inclusive nature of package holidays appeals to many travelers as it simplifies the planning process and offers a sense of security.

Trends in the market:
One notable trend in the South African package holidays market is the rise of domestic tourism. With an increasing focus on exploring local destinations, more South Africans are opting for package holidays within the country. This trend is driven by a desire to support local businesses and explore the diverse landscapes and cultures that South Africa has to offer.

Local special circumstances:
South Africa's unique blend of natural beauty, rich cultural heritage, and diverse attractions make it an attractive destination for both domestic and international travelers. The country's safari offerings, stunning coastlines, and vibrant cities contribute to the popularity of package holidays in the region. Additionally, the presence of well-established tour operators and travel agencies has made it easier for travelers to book package holidays tailored to their preferences.

Underlying macroeconomic factors:
The growth of the package holidays market in South Africa can also be attributed to the country's improving economic conditions and rising disposable income levels. As more South Africans have the financial means to travel, the demand for convenient and affordable holiday packages has increased. Additionally, government initiatives to promote tourism and infrastructure development have further boosted the tourism sector in South Africa.

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.

Vue d’ensemble

  • Revenue
  • Sales Channels
  • Analyst Opinion
  • Users
  • User Demographics
  • Global Comparison
  • Methodology
  • Key Market Indicators
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