E-Scooter-sharing - Lebanon | Statista Market Forecast

Lebanon is expected to witness a significant surge in revenue in the E-Scooter-sharing market, with projections indicating a rise to US$47.70k by 2024.
Furthermore, the market is anticipated to grow at an annual growth rate of 7.80% between 2024 and 2029, leading to a market volume of US$69.43k by 2029.
In terms of users, the market is expected to have 2.54k users users by 2029, with user penetration projected to increase from 0.0% in 2024 to 0.1% in 2029.
The average revenue per user (ARPU) is forecasted to be US$20.52.
It is expected that 100% of the total revenue in the E-Scooter-sharing market will be generated through online sales by 2029.
Notably, when compared globally, United States is anticipated to generate the highest revenue in the E-Scooter-sharing market, with a projected revenue of US$730m in 2024.
Despite the lack of proper infrastructure and regulations, E-Scooter-sharing is gaining popularity among young adults in Lebanon.

Definition:

The E-Scooter-sharing market comprises e-scooter-sharing services that provide short-term rentals of electric motorized scooters (stand-up scooters). In e-scooter-sharing, scooters are generally owned by an e-scooter-sharing provider and can be reserved independently by customers around the clock. Customers are required to open an account with the e-scooter-sharing provider and can then reserve the vehicles, typically with a smartphone app. Providers normally offer dockless services, so it is possible to find e-scooters everywhere within the provider’s business zone, e.g., on sidewalks, and to leave the scooters anywhere in accordance with traffic regulations. Moped-sharing services are not available in all countries; thus, only a limited number of countries and regions can be selected.

Additional Information:

The main performance indicators of the E-Scooter-sharing market are revenues, average revenue per user (ARPU), user numbers and user penetration rates. Additionally, online and offline sales channel shares display the distribution of online and offline bookings. The ARPU refers to the average revenue one user generates per year while the revenue represents the total booking volume. Revenues are generated through both online and offline sales channels and include exclusively B2C revenues and users for the mentioned market. User numbers show only those individuals who have made a reservation, independent of the number of travelers on the booking. Each user is only counted once per year.

The booking volume includes all booked rides made by users from the selected region, regardless of where the ride took place.

For further information on the data displayed, refer to the info button right next to each box.

Free-floating e-scooter-sharing services
Services such as Lime, Tier, Bird, and Movo

Private e-scooter usage
Multi-day e-scooter rentals
Peer-to-peer e-scooter reservations
Bike sharing and other forms of micro-mobility

The E-Scooter-sharing market in Lebanon is experiencing significant growth and development in recent years.

Customer preferences: Customers in Lebanon are increasingly opting for e-scooter-sharing services due to their convenience and affordability. E-scooters provide a convenient mode of transportation for short distances, especially in congested urban areas. They offer a faster and more flexible alternative to traditional modes of transportation like cars or public transportation. Additionally, e-scooters are environmentally friendly, which appeals to customers who are conscious about reducing their carbon footprint.

Trends in the market: One of the key trends in the e-scooter-sharing market in Lebanon is the increasing number of companies entering the market. This competition has led to a wider availability of e-scooters in different parts of the country, making it easier for customers to access them. Moreover, companies are constantly improving their services by introducing features like mobile apps for easy booking and payment, as well as implementing safety measures to ensure the well-being of riders.

Local special circumstances: The unique geography and infrastructure of Lebanon contribute to the development of the e-scooter-sharing market. Lebanon is known for its congested roads and limited parking spaces, making e-scooters an attractive alternative for short-distance travel. Additionally, the country has a relatively young population who are more open to adopting new technologies and embracing innovative transportation options.

Underlying macroeconomic factors: The growth of the e-scooter-sharing market in Lebanon can also be attributed to several macroeconomic factors. The country has witnessed a rise in urbanization, with more people moving to cities for better job opportunities and quality of life. This urbanization trend has increased the demand for efficient and convenient transportation solutions, leading to the popularity of e-scooter-sharing services. Furthermore, the government has shown support for sustainable transportation initiatives and has implemented policies to encourage the use of e-scooters as a means of reducing traffic congestion and air pollution.

Data coverage:

The data encompasses B2C enterprises. Figures are based on bookings and revenues of e-scooter-sharing services.

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.

This report presents a comprehensive analysis and additional information on the Mobility market, in a PDF format.