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.
Notes: Data was converted from local currencies using average exchange rates of the respective year.
Most recent update: Jul 2024
Source: Statista Market Insights
Most recent update: Jul 2024
Source: Statista Market Insights
Most recent update: Mar 2023
Source: Statista Market Insights
Most recent update: Jul 2024
Source: Statista Market Insights
The Bike-sharing market in Netherlands has been experiencing significant growth in recent years.
Customer preferences: One of the main reasons for the growth in the Bike-sharing market in Netherlands is the increasing popularity of sustainable transportation options. Customers are becoming more conscious of the environmental impact of traditional modes of transport and are seeking greener alternatives. Bike-sharing provides a convenient and eco-friendly way for people to travel short distances, especially in urban areas where traffic congestion can be a major issue. Additionally, the rise of health and wellness trends has also contributed to the demand for bike-sharing services, as people are increasingly incorporating exercise into their daily routines.
Trends in the market: The Bike-sharing market in Netherlands has seen a surge in the number of players entering the market. This has led to increased competition and innovation, with companies offering different types of bikes, pricing models, and additional services to attract customers. The market has also witnessed the introduction of electric bikes, which provide an easier and more efficient way of commuting. Furthermore, bike-sharing apps have become popular, allowing users to easily locate and unlock bikes using their smartphones.
Local special circumstances: The Netherlands is known for its extensive cycling infrastructure, making it an ideal market for bike-sharing services. The country has a well-developed network of bike lanes and dedicated cycling paths, making it safe and convenient for people to ride bikes. Additionally, the flat terrain of the Netherlands makes cycling a relatively easy mode of transportation, further encouraging the use of bike-sharing services.
Underlying macroeconomic factors: The Bike-sharing market in Netherlands has also been influenced by macroeconomic factors. The country has a strong economy and a high standard of living, which allows people to afford the convenience and flexibility of bike-sharing services. Furthermore, the government has implemented policies to promote cycling as a sustainable mode of transport, including providing subsidies for bike-sharing companies and investing in cycling infrastructure. These factors have created a favorable environment for the growth of the Bike-sharing market in Netherlands.
Most recent update: Jul 2024
Source: Statista Market Insights
Most recent update: Mar 2024
Sources: Statista Market Insights, Statista Consumer Insights Global
Most recent update: Jul 2024
Source: Statista Market Insights
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.Notes: Based on data from IMF, World Bank, UN and Eurostat
Most recent update: Sep 2024
Source: Statista Market Insights