Shared Mobility - South Africa

  • South Africa
  • South Africa's Shared Mobility market is projected to experience an increase in revenue, with an estimated value of €3,093.00m in 2024.
  • This projection is expected to show an annual growth rate (CAGR 2024-2029) of 3.96%, resulting in a projected market volume of €3,756.00m by 2029.
  • Flights represent the largest market in the market, with an estimated volume of €1,118.00m in 2024.
  • By 2029, the number of Public Transportation users is expected to amount to 28,530.00k users.
  • The user penetration rate is projected to be 44.0% in 2024 and is expected to hit 47.6% by 2029.
  • The average revenue per user (ARPU) is estimated to be €115.30.
  • By 2029, 61% of the total revenue in the Shared Mobility market is expected to be generated through online sales.
  • In global comparison, China is expected to generate the most revenue in the Shared Mobility market, with an estimated value of €338bn in 2024.
  • Shared mobility services are gaining popularity in South Africa as a cost-effective and convenient transportation option for urban residents.

Key regions: United States, Saudi Arabia, Germany, Malaysia, India

 
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Comparaison de régions
 
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Analyst Opinion

Shared Mobility in South Africa has been experiencing a significant rise in popularity in recent years.

Customer preferences:
Customers in South Africa are increasingly opting for shared mobility services due to the convenience and cost-effectiveness they offer. With the rise of urbanization and traffic congestion in major cities, people are looking for more efficient and sustainable transportation options. Shared mobility services provide a flexible and on-demand solution for commuters, especially in areas where public transportation may be limited.

Trends in the market:
One of the key trends in the Shared Mobility market in South Africa is the growing adoption of ride-hailing services. Companies offering ride-hailing services have seen a steady increase in users as more people choose to book rides through mobile apps for their daily commute or occasional travel needs. Additionally, the introduction of electric scooters and bicycles for short-distance trips has gained traction in urban areas, promoting eco-friendly transportation alternatives.

Local special circumstances:
South Africa's Shared Mobility market is unique due to its diverse demographic and geographic landscape. The country's major cities, such as Johannesburg, Cape Town, and Durban, have different transportation needs and infrastructures, leading to varied preferences for shared mobility services across regions. Additionally, safety and security concerns play a significant role in shaping customer behavior, with trust and reliability being crucial factors for the success of shared mobility providers.

Underlying macroeconomic factors:
The development of the Shared Mobility market in South Africa is also influenced by macroeconomic factors such as the overall economic growth, disposable income levels, and regulatory environment. As the economy continues to evolve, there is a growing middle class with higher purchasing power, making shared mobility services more accessible to a larger consumer base. Moreover, government initiatives promoting sustainable transportation and smart city development are driving the expansion of shared mobility options in the country.

Methodology

Data coverage:

The data encompasses B2C enterprises. Figures are based on bookings, revenues, and online shares of car rentals, ride-hailing, taxi, car-sharing, bike-sharing, e-scooter-sharing, moped-sharing, trains, buses, public transportation, and flights.

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, third-party studies and reports, federal statistical offices, industry associations, and price data. 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 demographic data, GDP, consumer spending, internet penetration, and device usage. 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, the S-curve function and exponential trend smoothing methods are applied.

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
  • Mode of Transportation
  • User Demographics
  • Global Comparison
  • Methodology
  • Key Market Indicators
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