Shared Mobility - Morocco

  • Morocco
  • Morocco is expected to witness a surge in revenue for the Shared Mobility market, with a projection of €2,255.00m by 2024.
  • The market is estimated to grow annually by 3.68%, resulting in a projected market size of €2,701.00m by 2029.
  • Among the different Shared Mobility markets, Flights are expected to dominate the market, with an anticipated market volume of €724.40m by 2024.
  • By 2029, the number of users in the Public Transportation market is expected to reach 24.23m users.
  • The user penetration rate is projected to increase from 77.0% in 2024 to 83.7% by 2029.
  • The average revenue per user (ARPU) is expected to remain at €76.58.
  • Online sales are projected to contribute 57% to the total revenue of the Shared Mobility market by 2029.
  • In terms of revenue generation, China is expected to lead globally with a projected revenue of €335bn in 2024.
  • Morocco's shared mobility market is growing rapidly, with a focus on electric scooters and bike sharing services in major cities.

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

 
Marché
 
Région
 
Comparaison de régions
 
Monnaie
 

Analyst Opinion

Over the past few years, the Shared Mobility market in Morocco has been experiencing significant growth and evolution.

Customer preferences:
Customers in Morocco are increasingly leaning towards Shared Mobility services due to the convenience and cost-effectiveness they offer. With the rise of urbanization and traffic congestion in major cities like Casablanca and Marrakech, more people are opting for shared transportation options to navigate through the bustling streets.

Trends in the market:
One notable trend in the Shared Mobility market in Morocco is the increasing popularity of bike-sharing services. As the government pushes for sustainable and eco-friendly transportation solutions, bike-sharing companies have been gaining traction in the country. This trend aligns with global efforts to reduce carbon emissions and promote healthier modes of transportation.

Local special circumstances:
Morocco's unique geographical landscape, which includes both bustling cities and vast rural areas, presents a challenge and an opportunity for Shared Mobility providers. While urban areas offer a high demand for shared transportation services, rural areas may require tailored solutions to cater to the transportation needs of the population.

Underlying macroeconomic factors:
The growth of the Shared Mobility market in Morocco can also be attributed to macroeconomic factors such as the increasing disposable income of the middle class and the growing penetration of smartphones and internet connectivity. These factors have made it easier for people to access and utilize Shared Mobility services, driving the market forward.

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
  • User Demographics
  • Global Comparison
  • Methodology
  • Key Market Indicators
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