Car-sharing - Serbia

  • Serbia
  • The revenue in the Car-sharing market in Serbia is forecasted to reach US$2.76m by 2025.
  • Revenue is anticipated to demonstrate an annual growth rate (CAGR 2025-2029) of 5.74%, leading to a projected market volume of US$3.45m by 2029.
  • In Serbia's Car-sharing market, the number of users is estimated to reach 27.83k users by 2029.
  • User penetration is expected to be 0.3% in 2025 and 0.4% by 2029.
  • The average revenue per user (ARPU) is projected to be US$117.50.
  • In the Car-sharing market in Serbia, 100% of total revenue will be generated through online sales by 2029.
  • In global comparison, the United States is expected to generate the most revenue (US$3,036m in 2025).
  • Serbia's Car-sharing market is experiencing a surge in popularity, driven by urbanization and a growing preference for sustainable transportation solutions.

Key regions: Europe, Germany, India, United States, Malaysia

 
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Analyst Opinion

The Car-sharing market in Serbia has been experiencing significant growth and development in recent years.

Customer preferences:
Customers in Serbia are increasingly opting for car-sharing services due to the convenience and cost-effectiveness they offer. With the rise of urbanization and environmental awareness, more people are choosing shared mobility options over traditional car ownership. This shift in consumer behavior is driving the demand for car-sharing services in the country.

Trends in the market:
One prominent trend in the car-sharing market in Serbia is the expansion of service providers and the introduction of innovative technologies. Companies are investing in modernizing their fleets with electric vehicles and implementing user-friendly mobile applications for booking and managing rides. Additionally, partnerships with public transportation systems are becoming more common, providing customers with seamless multi-modal transportation options.

Local special circumstances:
Serbia's growing urban population and limited parking spaces in city centers are contributing to the popularity of car-sharing services. The convenience of being able to pick up and drop off a vehicle at multiple locations appeals to urban dwellers who may not need a car for their daily commute but require one for occasional trips. Moreover, the increasing focus on sustainability and reducing carbon emissions is driving the adoption of shared mobility solutions in the country.

Underlying macroeconomic factors:
The improving economic conditions in Serbia are also playing a role in the development of the car-sharing market. As disposable incomes rise and the middle class expands, more people have the financial means to choose alternative transportation options like car-sharing. Additionally, government initiatives to promote sustainable transportation and reduce traffic congestion are creating a favorable environment for the growth of the car-sharing industry.

Methodology

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.

Overview

  • Revenue
  • Sales Channels
  • Analyst Opinion
  • Users
  • Global Comparison
  • Methodology
  • Key Market Indicators
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