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.
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Notes: Data was converted from local currencies using average exchange rates of the respective year.
Most recent update: Jul 2024
Source: Statista Market Insights
Most recent update: Jul 2024
Source: Statista Market Insights
Most recent update: Jul 2024
Source: Statista Market Insights
The E-Scooter-sharing market in EU-27 has experienced significant growth in recent years, driven by changing customer preferences, emerging trends in the market, and local special circumstances.
Customer preferences: Customers in the EU-27 have shown a growing preference for convenient and eco-friendly transportation options. E-Scooter-sharing services provide a flexible and sustainable alternative to traditional modes of transportation, such as cars or public transport. The ease of use, affordability, and ability to avoid traffic congestion make e-scooters an attractive option for short-distance travel in urban areas.
Trends in the market: One of the key trends in the EU-27 E-Scooter-sharing market is the increasing number of market players. Several companies have entered the market, offering their own e-scooter-sharing services to meet the growing demand. This competition has led to innovation in terms of technology, pricing models, and service quality, benefiting the customers. Another trend in the market is the integration of e-scooter-sharing services into existing transportation networks. Many cities in the EU-27 have embraced e-scooters as a part of their sustainable mobility strategies, integrating them with public transportation systems. This integration allows customers to seamlessly switch between different modes of transport, enhancing the overall convenience and accessibility of e-scooter-sharing services.
Local special circumstances: The EU-27 consists of diverse countries with varying urban landscapes, regulations, and infrastructure. These local special circumstances have influenced the development of the E-Scooter-sharing market in different ways. For example, cities with well-developed cycling infrastructure and a strong cycling culture have seen a higher adoption rate of e-scooters. On the other hand, cities with limited infrastructure and stricter regulations have faced challenges in the implementation and operation of e-scooter-sharing services.
Underlying macroeconomic factors: The growth of the E-Scooter-sharing market in the EU-27 can also be attributed to underlying macroeconomic factors. The increasing urbanization, rising population density, and the need for sustainable transportation solutions have created a favorable environment for the development of e-scooter-sharing services. Additionally, advancements in technology and the availability of affordable e-scooter models have made it easier for companies to enter the market and expand their operations. In conclusion, the E-Scooter-sharing market in the EU-27 is developing rapidly due to changing customer preferences, emerging market trends, local special circumstances, and underlying macroeconomic factors. The convenience, affordability, and eco-friendliness of e-scooters have made them a popular choice for short-distance travel in urban areas. As the market continues to evolve, it is expected that further innovations and integration with existing transportation networks will drive its growth.
Most recent update: Jul 2024
Source: Statista Market Insights
Most recent update: Jul 2024
Source: Statista Market Insights
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.Notes: Based on data from IMF, World Bank, UN and Eurostat
Most recent update: Sep 2024
Source: Statista Market Insights