Key regions: China, Germany, Thailand, Saudi Arabia, India
The E-Scooter-sharing market in France has been experiencing significant growth in recent years.
Customer preferences: Customers in France are increasingly opting for e-scooter-sharing services due to their convenience and affordability. E-scooters provide a quick and efficient mode of transportation, especially for short distances within crowded urban areas. They are particularly popular among young adults and tourists who are looking for a fun and eco-friendly way to navigate the city. Additionally, the ease of use and availability of e-scooter-sharing apps make it convenient for customers to locate and rent e-scooters whenever they need them.
Trends in the market: One of the key trends in the e-scooter-sharing market in France is the rapid expansion of service providers. Several international and domestic companies have entered the market, leading to increased competition and a wider range of options for customers. This has resulted in lower prices and improved service quality as companies strive to attract and retain customers. Another trend in the market is the integration of e-scooter-sharing services with existing transportation systems. Many cities in France have introduced e-scooter-sharing as a part of their public transportation network, allowing customers to seamlessly switch between different modes of transport. This integration not only enhances the overall transportation experience but also promotes sustainability and reduces congestion in urban areas.
Local special circumstances: France has a well-developed infrastructure and a high population density in major cities, making it an ideal market for e-scooter-sharing services. The compact nature of urban areas in France makes e-scooters a convenient and efficient mode of transportation, especially for short trips. Additionally, the French government has been supportive of sustainable transportation initiatives, including e-scooter-sharing, by implementing regulations and infrastructure improvements to accommodate these services.
Underlying macroeconomic factors: The growth of the e-scooter-sharing market in France can also be attributed to several macroeconomic factors. The rising concern for environmental sustainability has led to an increased demand for eco-friendly transportation options. E-scooters, being electric vehicles, align with this trend and have gained popularity as a greener alternative to traditional modes of transport. Furthermore, the increasing urbanization and congestion in major cities have created a need for efficient and flexible transportation solutions. E-scooter-sharing services address this need by providing a convenient and flexible mode of transportation that can easily navigate through traffic and crowded areas. In conclusion, the e-scooter-sharing market in France is experiencing significant growth due to customer preferences for convenience and affordability, the expansion of service providers, integration with existing transportation systems, local infrastructure and government support, and underlying macroeconomic factors such as environmental sustainability and urbanization. As the market continues to evolve, it is expected to further contribute to the transformation of urban mobility in France.
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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