Key regions: India, Thailand, Malaysia, China, South America
The E-Scooter-sharing market in Switzerland has been experiencing significant growth in recent years, driven by changing customer preferences and local special circumstances.
Customer preferences: Customers in Switzerland have shown a growing preference for convenient and sustainable modes of transportation. E-Scooter-sharing services provide an alternative to traditional modes of transportation, such as cars or public transport, offering a flexible and eco-friendly solution for short-distance travel. The ease of use and affordability of E-Scooter-sharing services have made them popular among urban dwellers, who value convenience and cost-effectiveness.
Trends in the market: One of the key trends in the E-Scooter-sharing market in Switzerland is the increasing number of players entering the market. Both local and international companies have recognized the potential of the Swiss market and have launched their own E-Scooter-sharing services. This competition has led to an expansion of services and increased availability of E-Scooters in major cities across the country. Another trend in the market is the integration of E-Scooter-sharing services with existing transportation networks. Many cities in Switzerland have implemented bike lanes and infrastructure to accommodate E-Scooters, making it easier for users to navigate and access the service. This integration with existing transportation systems has further contributed to the popularity of E-Scooter-sharing services.
Local special circumstances: Switzerland's compact size and well-developed infrastructure make it an ideal market for E-Scooter-sharing services. The country's cities are known for their efficient public transportation systems, but E-Scooters offer a more flexible and convenient option for short trips within urban areas. Additionally, Switzerland's commitment to sustainability and environmental conservation aligns with the values of E-Scooter-sharing services, making them a popular choice among Swiss consumers.
Underlying macroeconomic factors: The growth of the E-Scooter-sharing market in Switzerland can also be attributed to underlying macroeconomic factors. The country has a strong economy and high disposable income, allowing consumers to afford the convenience and novelty of E-Scooter-sharing services. Furthermore, the Swiss government has implemented policies and regulations that support the development of sustainable transportation options, including E-Scooter-sharing. These factors create a favorable environment for the growth of the market. In conclusion, the E-Scooter-sharing market in Switzerland is experiencing significant growth due to changing customer preferences, local special circumstances, and underlying macroeconomic factors. The convenience, affordability, and sustainability of E-Scooter-sharing services have made them a popular choice among Swiss consumers, while the country's compact size and well-developed infrastructure provide an ideal market for these services. With increasing competition and integration with existing transportation networks, the E-Scooter-sharing market in Switzerland is expected to continue growing in the coming years.
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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