Shared Mobility - Central & Western Europe

  • Central & Western Europe
  • By 2024, the revenue in the Shared Mobility market in Central & Western Europe is expected to reach US$217,200.00m.
  • It is projected to show an annual growth rate (CAGR 2024-2029) of 2.55%, resulting in a projected market volume of US$246,300.00m by 2029.
  • The largest market in this market is Flights, which is expected to have a projected market volume of US$87,740.00m in 2024.
  • By 2029, the number of users in the Public Transportation market is expected to amount to 229.70m users.
  • In 2024, user penetration is projected to be 95.0% and is expected to increase to 95.0% by 2029.
  • The average revenue per user (ARPU) is expected to be US$664.00.
  • By 2029, it is expected that 64% of total revenue in the Shared Mobility market in Central & Western Europe will be generated through online sales.
  • In comparison to other countries, China is projected to generate the most revenue in the Shared Mobility market with US$365bn in 2024.
  • In Germany, the trend towards electric scooters and bike-sharing services is rapidly growing within the shared mobility market.

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

 
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Analyst Opinion

The Shared Mobility market in Central & Western Europe is experiencing a significant shift in consumer preferences and market trends, driven by various factors influencing the industry.

Customer preferences:
Consumers in Central & Western Europe are increasingly opting for shared mobility services due to the convenience, cost-effectiveness, and environmental benefits they offer. The flexibility of choosing between different modes of transportation such as ride-hailing, car-sharing, and bike-sharing aligns well with the diverse mobility needs of urban dwellers in this region.

Trends in the market:
In countries like Germany and France, there is a growing trend towards integrating shared mobility services with public transportation systems, creating seamless multi-modal experiences for users. This integration not only enhances the overall efficiency of urban transportation but also encourages more people to shift away from private car ownership.

Local special circumstances:
Cities like Amsterdam and Copenhagen are known for their strong cycling culture, which has led to the proliferation of bike-sharing services in these regions. The flat terrain, well-developed cycling infrastructure, and environmentally conscious population make these cities ideal markets for bike-sharing operators. Additionally, the presence of strict regulations and policies promoting sustainable transportation practices further drives the adoption of shared mobility services in Central & Western Europe.

Underlying macroeconomic factors:
The Shared Mobility market in Central & Western Europe is also influenced by macroeconomic factors such as increasing urbanization, rising concerns over air pollution, and changing attitudes towards car ownership. As more people move to urban centers and seek alternative transportation solutions, shared mobility services are poised to play a crucial role in shaping the future of transportation in the region. Additionally, the emphasis on reducing carbon emissions and promoting sustainable urban development aligns with the goals of shared mobility providers, further fueling the growth of the market in Central & Western Europe.

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
  • Global Comparison
  • Methodology
  • Key Market Indicators
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