Shared Mobility - APAC

  • APAC
  • Revenue in the Shared Mobility market is projected to reach US$643.90bn in 2024.
  • Revenue is expected to show an annual growth rate (CAGR 2024-2029) of 4.42%, resulting in a projected market volume of US$799.20bn by 2029.
  • The market's largest market is the Flights market with a projected market volume of US$247.00bn in 2024.
  • In the Public Transportation market, the number of users is expected to amount to 3,027.00m users by 2029.
  • User penetration is 64.1% in 2024 and is expected to hit 74.6% by 2029.
  • The average revenue per user (ARPU) is expected to amount to US$234.40.
  • In the Shared Mobility market, 70% of total revenue will be generated through online sales by 2029.
  • In global comparison, most revenue will be generated in China (US$365bn in 2024).

Key regions: United States, Saudi Arabia, Germany, Malaysia, India

 
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Analyst Opinion

The Shared Mobility market in APAC is witnessing significant growth and evolution driven by changing consumer preferences, technological advancements, and unique local circumstances.

Customer preferences:
Customers in APAC are increasingly looking for convenient and cost-effective transportation options. Shared Mobility services such as ride-hailing, bike-sharing, and car-sharing are gaining popularity due to their flexibility and affordability. With busy urban lifestyles and growing environmental concerns, consumers are opting for shared transportation solutions over traditional car ownership.

Trends in the market:
In countries like China, ride-hailing services have become an integral part of urban transportation, with a large number of users relying on platforms like Didi Chuxing for their daily commute. The bike-sharing trend is also on the rise in countries like India and Singapore, offering a sustainable and efficient way to navigate through traffic-congested cities. Additionally, car-sharing services are gaining traction in Japan and South Korea, especially among young urban dwellers looking to avoid the hassle and costs associated with owning a car.

Local special circumstances:
APAC countries exhibit unique characteristics that influence the Shared Mobility market. For instance, the rapid urbanization and population density in cities like Tokyo and Mumbai create a high demand for shared transportation services. Moreover, regulatory frameworks and infrastructure development play a crucial role in shaping the market landscape. In countries with supportive policies and well-established transportation networks, Shared Mobility services tend to thrive.

Underlying macroeconomic factors:
The Shared Mobility market in APAC is also influenced by macroeconomic factors such as GDP growth, disposable income levels, and technological innovation. As economies in the region continue to grow, more consumers have the purchasing power to access shared transportation services. Furthermore, advancements in mobile technology and digital payment systems have made it easier for customers to book and use Shared Mobility services, driving market expansion across APAC.

Methodology

Data coverage:

The data encompasses B2C enterprises. Figures are based on bookings, revenues, and online shares of car rentals, ride-hailing, taxi, car-sharing, bike-sharing, e-scooter-sharing, moped-sharing, trains, buses, public transportation, and flights.

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.

Overview

  • Revenue
  • Sales Channels
  • Analyst Opinion
  • Users
  • Global Comparison
  • Methodology
  • Key Market Indicators
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