Shared Mobility - Mauritius

  • Mauritius
  • The Shared Mobility market in Mauritius is expected to generate a revenue of US$119.30m in 2024, with an annual growth rate of 5.27% from 2024 to 2029.
  • This leads to a projected market volume of US$154.20m by 2029.
  • The largest market within this market is Flights, with a projected market volume of US$63.96m in 2024.
  • By 2029, the number of Public Transportation users is expected to increase to 585.90k users.
  • The user penetration rate is projected to reach 89.5% by 2029, with a rate of 77.8% in 2024.
  • The average revenue per user (ARPU) is expected to be US$117.70.
  • By 2029, 61% of the total revenue in the Shared Mobility market will be generated through online sales.
  • In comparison to other countries, China is expected to generate the most revenue with US$365bn in 2024.
  • Shared mobility in Mauritius is still in its infancy, with limited availability of ride-sharing and bike-sharing services in the country.

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

 
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Analyst Opinion

The Shared Mobility market in Mauritius is experiencing significant growth and evolution in response to changing consumer preferences and local special circumstances.

Customer preferences:
Customers in Mauritius are increasingly looking for convenient and cost-effective transportation options, which has fueled the demand for shared mobility services. With the rise of urbanization and traffic congestion in major cities, more people are opting for shared mobility solutions as a sustainable and efficient way to commute.

Trends in the market:
One notable trend in the Mauritian Shared Mobility market is the increasing popularity of ride-hailing services and bike-sharing platforms. These services offer flexibility and convenience to users, allowing them to travel around the island with ease. Additionally, the integration of technology such as mobile apps for booking and payment has made shared mobility services more accessible to a wider audience.

Local special circumstances:
Mauritius, known for its thriving tourism industry, has a diverse population with varying transportation needs. The presence of both locals and tourists on the island has created a unique market for shared mobility services. Tourists often seek convenient ways to explore the island, while locals rely on shared mobility for their daily commute. This dynamic has influenced the growth and development of shared mobility offerings in Mauritius.

Underlying macroeconomic factors:
The growth of the Shared Mobility market in Mauritius is also influenced by macroeconomic factors such as GDP per capita, disposable income levels, and government regulations. As the economy continues to develop and incomes rise, more people are able to afford shared mobility services. Additionally, government initiatives to promote sustainable transportation and reduce carbon emissions have further boosted the adoption of shared mobility solutions 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.

Overview

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