Bike-sharing - EU-27 | Statista Market Forecast

The Bike-sharing market in EU-27 is expected to see a significant boost in revenue in the upcoming years.
It is projected to reach US$353.60m by 2024 with an annual growth rate of 3.69%, leading to a projected market volume of US$423.70m by 2029.
Moreover, the number of users is expected to increase to 18.81m users by 2029.
The user penetration rate is projected to be 3.8% in 2024 and 4.2% by 2029.
The average revenue per user (ARPU) is expected to be US$20.96.
It is worth noting that 96% of the total revenue generated in this market will be through online sales by 2029.
In terms of global comparison, China is expected to generate the most revenue with US$6bn in 2024.
In EU-27, bike-sharing programs are becoming increasingly popular in urban areas as a sustainable mode of transportation.

Definition:

The Bike-sharing market includes short-term bike-sharing services. In bike-sharing services, bicycles are generally owned by a bike-sharing provider and are independently reserved by customers around the clock. Customers are required to open an account with the bike-sharing provider and can then reserve bicycles. This is usually done with a smartphone app, but there are also service providers that allow reservations to be made via the provider's website, by telephone, or at a terminal.

The two most frequently used bike-sharing varieties are the following: station-based (e.g., Stadtrad and Citi Bike New York) and free-floating (such as nextbike and ofo). With station-based bike-sharing, a bicycle is retrieved from a bike-sharing station and returned to either the same station or dropped off at another station. With free-floating bike-sharing, it is possible to find bicycles everywhere within the service provider's business zone and leave the bicycle anywhere in accordance with traffic regulations. Peer-to-peer bike-sharing is not included in the market definition of this market. Moped-sharing services are not available in all countries; thus, only a limited number of countries and regions can be selected.

Additional Information:

The main performance indicators of the Bike-sharing market are revenues, average revenue per user (ARPU), user numbers and user penetration rates. Additionally, online and offline sales channel shares display the distribution of online and offline bookings. The ARPU refers to the average revenue one user generates per year while the revenue represents the total booking volume. Revenues are generated through both online and offline sales channels and include exclusively B2C revenues and users for the mentioned market. User numbers show only those individuals who have made a reservation, independent of the number of travelers on the booking. Each user is only counted once per year.

The booking volume includes all booked rides made by users from the selected region, regardless of where the ride took place.

For further information on the data displayed, refer to the info button right next to each box.

Free-floating bike-sharing reservations
Stationary bike-sharing reservations
Services such as nextbik, ofo, Mobike, and LimeBike

Peer-to-peer bike-sharing reservations
Free bike-sharing services, such as Aarhus City Bikes
Multi-day bike rental offers
Discounts for customers with long-term subscriptions and other types of discounts
Electric scooter service providers

The Bike-sharing market in EU-27 has been experiencing significant growth in recent years, driven by changing customer preferences, emerging trends, and local special circumstances.

Customer preferences: Customers in the EU-27 are increasingly looking for convenient and sustainable transportation options. Bike-sharing provides an affordable and flexible solution for short-distance travel, allowing users to easily access bikes in urban areas. The convenience of bike-sharing services, such as the ability to locate and unlock bikes through mobile apps, has made them popular among tech-savvy customers. Additionally, the growing awareness of the environmental benefits of cycling has also contributed to the increasing demand for bike-sharing services.

Trends in the market: One of the key trends in the Bike-sharing market in the EU-27 is the expansion of dockless bike-sharing systems. Unlike traditional dock-based systems, dockless bike-sharing allows users to pick up and drop off bikes anywhere within a designated service area. This flexibility has made dockless bike-sharing more popular among customers, as it eliminates the need to find docking stations and provides greater convenience. Another trend in the market is the integration of electric bikes (e-bikes) into bike-sharing fleets. E-bikes offer an alternative to traditional bicycles, allowing customers to cover longer distances with less effort. The increasing availability of e-bikes in bike-sharing systems has attracted a wider range of customers, including those who may not have considered cycling as a viable transportation option before.

Local special circumstances: The Bike-sharing market in the EU-27 is influenced by various local special circumstances. For example, the presence of well-developed cycling infrastructure in certain countries, such as the Netherlands and Denmark, has created a favorable environment for bike-sharing services. These countries have a long-standing culture of cycling, which has made bike-sharing an integral part of their transportation systems. Furthermore, the high population density and congested urban areas in many EU-27 countries have created a demand for alternative transportation options. Bike-sharing provides a convenient and efficient solution for short-distance travel, allowing users to avoid traffic congestion and reduce their commuting time.

Underlying macroeconomic factors: The growth of the Bike-sharing market in the EU-27 is also influenced by underlying macroeconomic factors. The increasing focus on sustainability and environmental conservation has led to government initiatives and policies that promote cycling as a means of transportation. For example, some EU-27 countries offer subsidies or tax incentives for bike-sharing operators to encourage the adoption of this eco-friendly mode of transportation. Additionally, the rise of the sharing economy and the increasing popularity of mobility-as-a-service (MaaS) platforms have also contributed to the growth of the Bike-sharing market. MaaS platforms integrate various transportation services, including bike-sharing, into a single app, providing customers with a seamless and convenient way to access different modes of transportation. In conclusion, the Bike-sharing market in the EU-27 is experiencing significant growth due to changing customer preferences, emerging trends, local special circumstances, and underlying macroeconomic factors. The demand for convenient and sustainable transportation options, the expansion of dockless bike-sharing systems, the integration of e-bikes, and the presence of cycling-friendly infrastructure and government initiatives all contribute to the development of this market.

Data coverage:

The data encompasses B2C enterprises. Figures are based on bookings, revenues, and online shares of bike-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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