Shared Mobility - Tanzania

  • Tanzania
  • The Shared Mobility market in Tanzania is projected to experience a significant growth in revenue, with an expected reach of US$779.00m in 2024.
  • Furthermore, the market is expected to show an annual growth rate of 6.73% (CAGR 2024-2029), resulting in a projected market volume of US$1,079.00m by 2029.
  • The largest market in the Tanzanian Shared Mobility market is Flights, with a projected market volume of US$267.40m in 2024.
  • The number of users in the Public Transportation market is expected to amount to 35.80m users by 2029.
  • In 2024, the user penetration is projected to be 55.0%, which is expected to increase to 65.5% by 2029.
  • The average revenue per user (ARPU) is expected to be US$20.40.
  • By 2029, 57% of the total revenue in the Tanzanian Shared Mobility market will be generated through online sales.
  • It is worth noting that in a global comparison, China is expected to generate the most revenue, with an estimated revenue of US$365bn in 2024.
  • Shared mobility services, such as bike and taxi sharing, are gradually gaining popularity in Tanzania as urbanization and traffic congestion increase.

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

 
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Analyst Opinion

The Shared Mobility market in Tanzania is experiencing significant growth and development, driven by various factors influencing consumer behavior and market dynamics.

Customer preferences:
Customers in Tanzania are increasingly valuing convenience, cost-effectiveness, and sustainability when it comes to transportation options. Shared Mobility services such as ride-hailing, bike-sharing, and car-sharing are becoming popular choices among urban residents looking for efficient and affordable ways to commute.

Trends in the market:
One of the key trends shaping the Shared Mobility market in Tanzania is the rapid urbanization and population growth in major cities. As more people move to urban areas, there is a growing demand for flexible and on-demand transportation solutions, leading to the expansion of Shared Mobility services across the country. Additionally, technological advancements and the widespread use of smartphones have made it easier for consumers to access and use Shared Mobility platforms.

Local special circumstances:
Tanzania's unique geographical and infrastructural challenges, such as inadequate public transportation systems and traffic congestion in urban centers, have created opportunities for Shared Mobility providers to fill the gaps in the market. By offering convenient and reliable transportation options, these services are helping to address the mobility needs of Tanzanians, especially in densely populated areas.

Underlying macroeconomic factors:
The growing middle class and increasing disposable income levels in Tanzania are also contributing to the rise of Shared Mobility services. As more people have the financial means to afford transportation beyond traditional modes like owning a car, Shared Mobility presents a cost-effective alternative that aligns with changing consumer preferences. Moreover, government initiatives to improve transportation infrastructure and promote sustainable mobility are further supporting the growth of the Shared Mobility market in Tanzania.

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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