Key regions: United States, Germany, South America, Indonesia, Malaysia
The Car-sharing market in Switzerland has experienced significant growth in recent years, driven by changing customer preferences and the emergence of new trends in the market. Customer preferences in Switzerland have shifted towards more sustainable and environmentally friendly transportation options, leading to an increased demand for car-sharing services. Additionally, the high cost of owning a car in Switzerland has made car-sharing an attractive alternative for many consumers. One of the key trends in the car-sharing market in Switzerland is the rise of electric car-sharing services. With the Swiss government's push towards reducing carbon emissions and promoting electric mobility, car-sharing companies have started to offer electric vehicles as part of their fleet. This trend has been further accelerated by the increasing availability of charging infrastructure across the country. Another trend in the market is the integration of car-sharing services with other modes of transportation. Many car-sharing companies in Switzerland have partnered with public transportation providers to offer integrated mobility solutions. This allows customers to seamlessly switch between different modes of transportation, such as trains, buses, and car-sharing, using a single app or card. This trend is driven by the growing demand for convenient and flexible transportation options. In addition to these customer preferences and market trends, there are also some local special circumstances that have contributed to the growth of the car-sharing market in Switzerland. The country's well-developed public transportation system, including an extensive network of trains and buses, has made it easier for car-sharing companies to operate and attract customers. Furthermore, Switzerland's compact size and high population density make it a favorable market for car-sharing, as it allows for efficient utilization of vehicles and reduces the need for long-distance travel. Underlying macroeconomic factors, such as the high cost of living and limited parking space in urban areas, have also played a role in the development of the car-sharing market in Switzerland. The cost of owning a car, including insurance, maintenance, and parking fees, can be prohibitively expensive in Switzerland. Car-sharing provides a more affordable alternative for individuals who do not need a car on a daily basis. Additionally, the limited availability of parking spaces in cities has made car-sharing a convenient option for residents who do not have access to private parking. Overall, the car-sharing market in Switzerland is driven by changing customer preferences, the integration of car-sharing with other modes of transportation, local special circumstances, and underlying macroeconomic factors. As these trends continue to evolve, the car-sharing market in Switzerland is expected to further expand and diversify in the coming years.
Data coverage:
The data encompasses B2C enterprises. Figures are based on bookings, revenues, and online shares of car-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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