E-Scooter-sharing - Russia | Statista Market Forecast

The E-Scooter-sharing market in Russia is anticipated to generate a revenue of US$25.12m by 2024, with an estimated annual growth rate (CAGR 2024-2029) of 5.38%.
This growth is expected to lead to a market volume of US$32.65m by 2029.
Additionally, the number of users in this market is projected to reach 2.71m users by 2029.
The user penetration rate is expected to increase from 1.7% in 2024 to 1.9% by 2029.
The average revenue per user (ARPU) is expected to be US$10.28.
Furthermore, it is projected that 100% of the total revenue in the E-Scooter-sharing market will be generated through online sales by 2029.
In comparison to other countries, United States is expected to generate the most revenue in this market, with a projected revenue of US$730m in 2024.
Despite a slow start due to regulatory hurdles, E-Scooter-sharing companies are gaining traction in Russia, particularly in Moscow and St. Petersburg.

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 Russia is experiencing significant growth and development.

Customer preferences: Customers in Russia are increasingly embracing E-Scooter-sharing services due to their convenience and affordability. E-Scooters provide a flexible and efficient mode of transportation, particularly for short distances within urban areas. With the growing concern for environmental sustainability, customers are also attracted to the eco-friendly nature of E-Scooters, as they produce zero emissions. Additionally, the ease of use and availability of E-Scooters through mobile applications make them an attractive option for customers seeking convenient and on-demand transportation solutions.

Trends in the market: One of the key trends in the E-Scooter-sharing market in Russia is the rapid expansion of service providers. Numerous companies have entered the market, offering their own fleet of E-Scooters and competing for market share. This has led to increased competition and innovation, with companies introducing new features such as longer battery life, improved safety measures, and enhanced user experience through mobile applications. Furthermore, partnerships with local businesses, such as cafes and shopping centers, have been established to provide customers with additional incentives and discounts, further driving the adoption of E-Scooter-sharing services.

Local special circumstances: Russia's urban centers, such as Moscow and St. Petersburg, are densely populated cities with heavy traffic congestion. This creates a strong demand for alternative modes of transportation that can navigate through crowded streets and provide a quicker means of travel. E-Scooters offer a solution to this problem by allowing users to easily maneuver through traffic and reach their destinations faster. Furthermore, Russia's relatively mild climate, particularly during the summer months, makes E-Scooter-sharing a popular choice for commuting and leisure activities.

Underlying macroeconomic factors: The growth of the E-Scooter-sharing market in Russia can be attributed to several macroeconomic factors. Firstly, the increasing urbanization in the country has led to a higher concentration of population in cities, resulting in a greater need for efficient transportation options. Secondly, the rising disposable income of the middle class has made E-Scooter-sharing services more accessible and affordable to a larger segment of the population. Lastly, government initiatives to promote sustainable transportation and reduce traffic congestion have created a favorable environment for the development of the E-Scooter-sharing market in Russia. These factors, combined with the convenience and environmental benefits of E-Scooters, have contributed to the rapid growth and adoption of E-Scooter-sharing services in the country.

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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