Shared Mobility - Ghana

  • Ghana
  • By 2024, the Shared Mobility market in Ghana is expected to generate a revenue of US$327.40m.
  • This revenue is projected to grow annually by a rate of 6.61%, resulting in a market volume of US$450.80m by 2029.
  • The largest market in the market is Public Transportation, with an expected market volume of US$163.00m in 2024.
  • The number of users in Public Transportation is expected to increase to 30.88m users by 2029.
  • The user penetration rate is expected to grow from 95.0% in 2024 to 95.0% by 2029.
  • The average revenue per user (ARPU) is projected to reach US$9.84.
  • By 2029, online sales are expected to account for 47% of the total revenue in the Shared Mobility market in Ghana.
  • When compared globally, China is projected to generate the most revenue in this market, amounting to US$365bn in 2024.
  • Shared mobility services are gaining popularity in Ghana due to increasing urbanization and the need for affordable transportation options.

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

 
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Analyst Opinion

The Shared Mobility market in Ghana is experiencing a significant growth trajectory driven by various factors.

Customer preferences:
Customers in Ghana are increasingly valuing convenience, affordability, and sustainability when it comes to transportation options. Shared Mobility services such as ride-hailing, bike-sharing, and carpooling are gaining popularity among urban dwellers looking for efficient and cost-effective ways to navigate the bustling cities.

Trends in the market:
One notable trend in the Shared Mobility market in Ghana is the rise of motorcycle taxis, also known as "okadas. " These two-wheeled vehicles provide a quick and flexible mode of transportation in congested urban areas, appealing to commuters looking to avoid traffic jams. Additionally, the integration of digital payment systems in Shared Mobility services is streamlining the booking and payment process, further enhancing the customer experience.

Local special circumstances:
Ghana's rapidly growing urban population and expanding middle class are driving the demand for Shared Mobility services. With increasing smartphone penetration and improved internet connectivity, more Ghanaians have access to on-demand transportation options at their fingertips. Moreover, the government's efforts to improve road infrastructure and enhance road safety are creating a conducive environment for the growth of the Shared Mobility market in the country.

Underlying macroeconomic factors:
The growing economy and rising disposable incomes in Ghana are fueling the demand for convenient transportation solutions. As more people move to urban areas in search of employment opportunities, the need for efficient and affordable mobility services continues to grow. Additionally, the competitive landscape of the Shared Mobility market in Ghana is attracting both local startups and international players, leading to innovation and service diversification to cater to the evolving needs of customers.

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.

Overview

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