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 Taiwan has experienced significant growth in recent years, driven by changing customer preferences, market trends, local special circumstances, and underlying macroeconomic factors.
Customer preferences: Customers in Taiwan have shown a growing preference for convenient and environmentally friendly transportation options, leading to an increased demand for bike-sharing services. With the rise of urbanization and traffic congestion in major cities, people are seeking alternative modes of transportation that are efficient and cost-effective. Bike-sharing provides a solution by offering a convenient way to travel short distances while reducing carbon emissions.
Trends in the market: One of the key trends in the Bike-sharing market in Taiwan is the adoption of smart technology. Bike-sharing companies have introduced mobile apps and QR code systems that allow users to easily locate, unlock, and rent bikes. This technology-driven approach has made bike-sharing more accessible and user-friendly, attracting a larger customer base. Another trend in the market is the expansion of bike-sharing services beyond urban areas. Bike-sharing companies have recognized the potential in suburban and rural areas, where public transportation options may be limited. By expanding their service coverage, bike-sharing companies are able to reach a wider audience and tap into new markets.
Local special circumstances: Taiwan's compact size and well-developed infrastructure make it an ideal market for bike-sharing. The country's extensive network of bike lanes and bike-friendly policies have created a supportive environment for bike-sharing services. Additionally, Taiwan's population density and high smartphone penetration rate have contributed to the success of bike-sharing, as it is easy for users to locate and rent bikes using mobile apps.
Underlying macroeconomic factors: Taiwan's strong economy and high disposable income levels have played a role in the growth of the Bike-sharing market. As people have more disposable income, they are more willing to spend on convenient and sustainable transportation options. Additionally, the government's focus on promoting green initiatives and reducing carbon emissions has further encouraged the adoption of bike-sharing services. In conclusion, the Bike-sharing market in Taiwan has experienced significant growth due to changing customer preferences, market trends, local special circumstances, and underlying macroeconomic factors. The adoption of smart technology, expansion into suburban areas, and the country's supportive infrastructure have all contributed to the success of bike-sharing services. With Taiwan's strong economy and growing environmental awareness, the Bike-sharing market is expected to continue its upward trajectory in the coming years.
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