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.
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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: Jul 2024
Source: Statista Market Insights
The Bike-sharing market in Asia has been experiencing significant growth in recent years, driven by changing customer preferences, emerging trends, and local special circumstances.
Customer preferences: Customers in Asia are increasingly looking for convenient and environmentally friendly transportation options. Bike-sharing provides a flexible and cost-effective alternative to traditional modes of transportation, allowing users to easily navigate congested city streets and avoid traffic jams. Additionally, the health benefits associated with cycling are becoming more widely recognized, further driving the demand for bike-sharing services.
Trends in the market: One of the key trends in the Bike-sharing market in Asia is the adoption of dockless bike-sharing systems. Unlike traditional docked systems, where bikes are picked up and returned to designated docking stations, dockless systems allow users to locate and unlock bikes using a smartphone app, and then park them anywhere within a designated area. This flexibility has made dockless bike-sharing extremely popular, particularly in densely populated cities where space is limited. Another trend in the market is the integration of bike-sharing with other forms of transportation. Many bike-sharing companies in Asia have partnered with ride-hailing services or public transportation providers to offer seamless travel experiences. This integration allows users to easily switch between different modes of transportation, increasing convenience and accessibility.
Local special circumstances: Asia is home to some of the world's largest cities, many of which face significant traffic congestion and air pollution issues. Bike-sharing has emerged as a solution to these challenges, offering a sustainable and efficient means of transportation. In addition, the relatively low cost of bike-sharing compared to owning a private vehicle makes it an attractive option for many people in Asia, particularly in countries with large urban populations and limited parking spaces.
Underlying macroeconomic factors: Rapid urbanization and population growth in Asia have contributed to the growth of the Bike-sharing market. As more people move to cities, the demand for convenient and affordable transportation options increases. Additionally, government initiatives to promote sustainable transportation and reduce carbon emissions have also played a role in driving the adoption of bike-sharing in Asia. These factors, combined with technological advancements and changing customer preferences, have created a favorable environment for the development of the Bike-sharing market in Asia.
Most recent update: Jul 2024
Source: Statista Market Insights
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