Shared Mobility - Serbia

  • Serbia
  • According to projections, the revenue in Serbia's Shared Mobility market sector is expected to reach US$1,285.00m by 2025.
  • Furthermore, there is an anticipated annual growth rate (CAGR 2025-2029) of 4.19%, which will result in a predicted market volume of US$1,514.00m by 2029.
  • The largest market in Serbia's Shared Mobility market sector is Flights, which is projected to have a market volume of US$617.00m by 2025.
  • It is expected that by 2029, the number of users in the Public Transportation market will rise to 4.15m users.
  • The user penetration in Serbia's Shared Mobility market in 2025 is 95.0%, and it is expected to reach 95.0% by 2029.
  • The average revenue per user (ARPU) is expected to be US$159.60.
  • It is estimated that by 2029, 59% of the overall revenue in the Shared Mobility market will be generated through online sales.
  • When compared globally, China is predicted to generate the most revenue, amounting to US$382bn in 2025.
  • Shared mobility services, such as car-sharing and bike-sharing, are gaining popularity in Serbia as a cost-effective and convenient alternative to traditional modes of transportation.

Key regions: United States, Saudi Arabia, Germany, Malaysia, India

 
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Analyst Opinion

The Shared Mobility market in Serbia is showing promising signs of growth and development.

Customer preferences:
Customers in Serbia are increasingly valuing convenience, flexibility, and cost-effectiveness when it comes to transportation options. This has led to a rising demand for shared mobility services that offer on-demand access to vehicles without the hassle of ownership.

Trends in the market:
One of the key trends in the Shared Mobility market in Serbia is the expansion of ride-hailing services and car-sharing platforms. This trend is driven by the growing urban population seeking efficient and sustainable transportation solutions. Additionally, the integration of technology such as mobile applications for booking and payment has made shared mobility services more accessible to a wider audience.

Local special circumstances:
Serbia's urban centers, particularly Belgrade, are experiencing increasing traffic congestion and limited parking spaces, making shared mobility services an attractive alternative to traditional car ownership. The relatively lower car ownership rates compared to Western European countries also contribute to the growing popularity of shared mobility options among the Serbian population.

Underlying macroeconomic factors:
The improving economic conditions in Serbia, coupled with a rising middle class and changing consumer behavior, are creating a favorable environment for the expansion of the Shared Mobility market. Additionally, government initiatives to promote sustainable transportation solutions and reduce carbon emissions are further driving the adoption of shared mobility services in the country.

Methodology

Data coverage:

The data encompasses B2C enterprises. Figures are based on bookings, revenues, and online shares of car rentals, ride-hailing, taxi, car-sharing, bike-sharing, e-scooter-sharing, moped-sharing, trains, buses, public transportation, and flights.

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
  • User Demographics
  • Global Comparison
  • Methodology
  • Key Market Indicators
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