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Bike-sharing - ASEAN

ASEAN

The projected revenue in the Bike-sharing market of ASEAN is expected to reach US$326.70m by 2024.
The revenue is anticipated to grow annually at a rate of 5.59% between 2024 and 2029, resulting in a market volume of US$428.90m by 2029.
By 2029, the number of users in the Bike-sharing market is projected to amount to 33.89m users.
The user penetration rate is expected to increase from 4.0% in 2024 to 4.7% by 2029.
The average revenue per user (ARPU) is estimated to be US$11.66.
It is predicted that 93% of the total revenue in the Bike-sharing market will be generated through online sales by 2029.
In comparison to other countries, China is expected to generate the highest revenue of US$5,515m in 2024.
In ASEAN, the bike-sharing market is growing rapidly with major players like oBike and ofo expanding their services in countries such as Singapore, Malaysia, and Thailand.

Key regions: South America, Malaysia, India, Indonesia, Saudi Arabia

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.

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Analyst Opinion

The Bike-sharing market in ASEAN has been experiencing significant growth in recent years.

Customer preferences: One of the main reasons for the growth of the Bike-sharing market in ASEAN is the increasing popularity of eco-friendly transportation options. With growing concerns about environmental sustainability, many consumers in the region are opting for greener modes of transportation, such as cycling. Bike-sharing services provide a convenient and affordable solution for individuals who want to reduce their carbon footprint and contribute to a cleaner environment.

Trends in the market: Another trend driving the growth of the Bike-sharing market in ASEAN is the increasing adoption of smartphone technology. Bike-sharing companies have leveraged the widespread use of smartphones to create user-friendly mobile applications that allow customers to easily locate and rent bikes. This technology-driven approach has made bike-sharing more accessible and convenient for consumers, leading to a surge in demand for these services.

Local special circumstances: The unique geography of ASEAN countries also plays a role in the development of the Bike-sharing market. Many cities in the region have high population densities and limited space for traditional transportation infrastructure. This makes bike-sharing a practical and efficient solution for short-distance travel within urban areas. Additionally, the warm climate in ASEAN countries makes cycling a desirable mode of transportation for many people, further contributing to the growth of the Bike-sharing market.

Underlying macroeconomic factors: The rapid urbanization and economic development in ASEAN countries have also contributed to the growth of the Bike-sharing market. As more people move to cities and disposable incomes increase, there is a higher demand for convenient and affordable transportation options. Bike-sharing services provide a cost-effective alternative to car ownership or public transportation, making them particularly attractive to urban dwellers in ASEAN countries. In conclusion, the Bike-sharing market in ASEAN is experiencing significant growth due to customer preferences for eco-friendly transportation options, the increasing adoption of smartphone technology, the unique geography of the region, and the underlying macroeconomic factors of rapid urbanization and economic development. As these trends continue, the Bike-sharing market in ASEAN is expected to further expand in the coming years.

Methodology

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.