Key regions: Europe, Germany, India, United States, Malaysia
The Car-sharing market in Argentina is experiencing significant growth and development.
Customer preferences: Customers in Argentina are increasingly opting for car-sharing services due to the convenience and cost-effectiveness they offer. Car-sharing allows individuals to use a vehicle only when needed, eliminating the need for ownership and associated costs such as maintenance, insurance, and parking. This appeals to customers who are looking for flexible transportation options and want to avoid the hassles of owning a car.
Trends in the market: One of the key trends in the car-sharing market in Argentina is the rise of app-based platforms that connect car owners with individuals in need of a vehicle. These platforms provide a seamless and user-friendly experience, allowing customers to easily find and book a car for their desired duration. The availability of a wide range of vehicle options, from compact cars to SUVs, further enhances the appeal of car-sharing services. Another trend in the market is the increasing collaboration between car-sharing companies and traditional rental car companies. This partnership allows car-sharing companies to expand their fleet and reach, while rental car companies can tap into the growing demand for short-term rentals. This collaboration also enables car-sharing companies to offer a wider range of vehicle options to customers, catering to different needs and preferences.
Local special circumstances: Argentina's urban areas, particularly Buenos Aires, face challenges such as traffic congestion and limited parking space. Car-sharing services provide a solution to these issues by reducing the number of private vehicles on the road and promoting efficient use of existing parking infrastructure. This makes car-sharing an attractive option for individuals living in urban areas who want to avoid the hassle of driving and parking their own vehicles.
Underlying macroeconomic factors: The development of the car-sharing market in Argentina is also influenced by macroeconomic factors. The country has experienced economic fluctuations in recent years, with periods of recession and inflation. During economic downturns, individuals may be more inclined to opt for cost-effective transportation options like car-sharing, rather than investing in a personal vehicle. Additionally, the rise of the sharing economy globally has contributed to the growth of car-sharing in Argentina, as individuals are becoming more comfortable with the idea of sharing resources for economic and environmental benefits. In conclusion, the car-sharing market in Argentina is growing due to customer preferences for convenience and cost-effectiveness. The rise of app-based platforms and collaborations with traditional rental car companies are key trends in the market. Local special circumstances, such as traffic congestion and limited parking space, further drive the adoption of car-sharing services. Macroeconomic factors, including economic fluctuations and the rise of the sharing economy, also contribute to the development of the car-sharing market in Argentina.
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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