Ride-hailing - Central & Western Europe

The Ride-hailing market in Central & Western Europe is experiencing significant growth and development. Customer preferences, trends in the market, local special circumstances, and underlying macroeconomic factors are all contributing to this positive trajectory. Customer preferences in Central & Western Europe are driving the growth of the Ride-hailing market. With the rise of smartphone usage and the convenience of on-demand transportation, consumers are increasingly opting for ride-hailing services over traditional taxis. The ability to easily book a ride, track its progress, and pay electronically is appealing to customers in this region. Additionally, the availability of various vehicle types and the option to share rides with others are also factors that are attracting customers to ride-hailing services. Trends in the market are also playing a role in the development of the Ride-hailing market in Central & Western Europe. One notable trend is the increasing popularity of electric and hybrid vehicles among ride-hailing companies. This trend is driven by both environmental concerns and government regulations promoting sustainable transportation options. As a result, ride-hailing companies are expanding their fleets to include more electric and hybrid vehicles, which not only aligns with customer preferences but also positions them as leaders in the push for sustainable transportation. Local special circumstances in Central & Western Europe are also contributing to the growth of the Ride-hailing market. One such circumstance is the presence of strong public transportation systems in many cities. While public transportation is widely used in this region, ride-hailing services provide a convenient and efficient alternative for shorter trips or during off-peak hours when public transportation may be less frequent. Additionally, the increasing urbanization and congestion in major cities are driving the demand for ride-hailing services as a way to navigate through traffic and reach destinations more quickly. Underlying macroeconomic factors are also influencing the development of the Ride-hailing market in Central & Western Europe. The region has a strong and stable economy, which provides a favorable environment for ride-hailing companies to operate and expand. Furthermore, the high smartphone penetration rate and widespread internet connectivity in this region make it easier for customers to access and use ride-hailing services. These factors, combined with the growing popularity of cashless transactions, create a conducive environment for the growth of the Ride-hailing market. In conclusion, the Ride-hailing market in Central & Western Europe is experiencing growth and development due to customer preferences, trends in the market, local special circumstances, and underlying macroeconomic factors. As ride-hailing services continue to evolve and adapt to the needs of customers in this region, the market is expected to further expand and thrive.

Data coverage:

The data encompasses B2C enterprises. Figures are based on bookings and revenues of ride-hailing 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.