Key regions: China, Germany, Thailand, Saudi Arabia, India
The E-Scooter-sharing market in Europe is experiencing significant growth and development.
Customer preferences: Customers in Europe are increasingly choosing to use e-scooter-sharing services due to their convenience, affordability, and environmental benefits. E-scooters provide a flexible and efficient mode of transportation for short distances, allowing users to avoid traffic congestion and reduce their carbon footprint. Additionally, the user-friendly mobile applications and seamless payment systems offered by e-scooter-sharing companies make it easy for customers to access and use the service.
Trends in the market: One of the key trends in the European e-scooter-sharing market is the expansion of services to new cities and countries. E-scooter-sharing companies are rapidly expanding their operations across Europe, capitalizing on the growing demand for sustainable transportation options. This expansion is driven by the success and popularity of e-scooter-sharing services in existing markets, as well as the favorable regulatory environment in many European countries. Another trend in the market is the increasing competition among e-scooter-sharing companies. With the market becoming more saturated, companies are striving to differentiate themselves by offering unique features and services. This includes features such as longer battery life, improved safety measures, and enhanced user experiences through the integration of technology.
Local special circumstances: The development of the e-scooter-sharing market in Europe is influenced by local special circumstances in each country. For example, in densely populated cities with limited parking spaces and heavy traffic congestion, e-scooter-sharing services provide a practical and efficient alternative to traditional modes of transportation. In countries with a strong cycling culture, e-scooters are seen as a complementary mode of transport for shorter distances.
Underlying macroeconomic factors: Several macroeconomic factors contribute to the growth of the e-scooter-sharing market in Europe. Firstly, the increasing urbanization and population density in many European cities create a demand for innovative transportation solutions. E-scooter-sharing services offer a convenient and sustainable option for urban dwellers to navigate crowded streets. Furthermore, the focus on sustainability and reducing carbon emissions is a key driver for the growth of e-scooter-sharing in Europe. Governments and local authorities are actively promoting and supporting the adoption of electric vehicles, including e-scooters, as part of their efforts to combat climate change and improve air quality. In conclusion, the e-scooter-sharing market in Europe is experiencing significant growth due to customer preferences for convenience and sustainability. The market is characterized by the expansion of services to new cities, increasing competition among companies, and the influence of local special circumstances. The underlying macroeconomic factors, such as urbanization and the focus on sustainability, further contribute to the development of the market.
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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