E-Scooter-sharing - South America

South America is expected to witness significant growth in the E-Scooter-sharing market.
By 2024, the projected revenue is estimated to reach US$78.24m, with an annual growth rate (CAGR 2024-2029) of 18.42%.
This growth is anticipated to result in a market volume of US$182.20m by 2029.
By 2029, the number of users in the E-Scooter-sharing market is expected to be 3.67m users with a user penetration rate of 0.9%.
The average revenue per user (ARPU) is expected to be US$26.78.
It is projected that 100% of the total revenue in this market will be generated through online sales by 2029.
In comparison with other countries, United States is expected to generate the highest revenue (US$730m in 2024) in the global E-Scooter-sharing market.
In Argentina, E-Scooter-sharing companies are facing regulatory challenges due to safety concerns and lack of infrastructure.

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 South America has been experiencing significant growth in recent years. Customer preferences, trends in the market, local special circumstances, and underlying macroeconomic factors have all contributed to this development. Customer preferences in South America have played a crucial role in the growth of the E-Scooter-sharing market. With increasing urbanization and traffic congestion in many cities, customers are seeking alternative modes of transportation that are convenient, affordable, and environmentally friendly. E-Scooter-sharing services have emerged as a popular choice, providing a convenient and efficient way to navigate through crowded city streets. Trends in the market have also contributed to the growth of E-Scooter-sharing in South America. Many companies have entered the market, offering a variety of E-Scooter models and services to cater to different customer needs. This competition has led to innovations such as longer battery life, improved safety features, and user-friendly mobile applications, making E-Scooter-sharing even more attractive to customers. Local special circumstances in South America have further fueled the growth of the E-Scooter-sharing market. The region's favorable climate, with many cities experiencing mild temperatures year-round, makes E-Scooter riding a pleasant and enjoyable experience. Additionally, the relatively flat terrain in many South American cities makes it easier for customers to ride E-Scooters, further encouraging their adoption. Underlying macroeconomic factors have also played a role in the development of the E-Scooter-sharing market in South America. The region has seen steady economic growth in recent years, leading to increased disposable income and higher standards of living. This has made E-Scooter-sharing more affordable and accessible to a larger segment of the population, driving demand and market expansion. In conclusion, the E-Scooter-sharing market in South America has experienced significant growth due to customer preferences, market trends, local special circumstances, and underlying macroeconomic factors. As the market continues to evolve and mature, it is expected that E-Scooter-sharing will become an integral part of the urban transportation landscape in South America.

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.

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