Shared Mobility - Southeast Asia

  • Southeast Asia
  • Southeast Asia is a promising market for the Shared Mobility market, as revenue is projected to reach US$66,070.00m by 2024, with an expected annual growth rate of 4.41% from 2024 to 2029.
  • This growth is expected to result in a market volume of US$81,990.00m by 2029.
  • The largest market in this market is Flights, with a projected market volume of US$31,590.00m in 2024.
  • By 2029, the number of users in the Public Transportation market is expected to reach 413.30m users.
  • User penetration in this market is expected to increase from 56.7% in 2024 to 57.9% by 2029.
  • The average revenue per user (ARPU) is projected to be US$188.70.
  • Online sales are expected to generate 68% of the total revenue in the Shared Mobility market by 2029.
  • In comparison to other countries, China is expected to generate the most revenue, with a projected revenue of US$365bn in 2024.
  • In Southeast Asia, the shared mobility market is rapidly expanding with companies like Grab and Go-Jek dominating the scene in countries like Indonesia, Singapore, and Malaysia.

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

 
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Analyst Opinion

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

Customer preferences:
Customers in Southeast Asia are increasingly valuing convenience, affordability, and sustainability when it comes to transportation options. Shared mobility services such as ride-hailing, bike-sharing, and scooter-sharing are gaining popularity due to their flexibility and cost-effectiveness. Consumers are also showing a preference for seamless digital platforms that allow for easy booking and payment processes.

Trends in the market:
In countries like Indonesia, Thailand, and Vietnam, the Shared Mobility market is witnessing a surge in demand for motorbike taxis and ride-hailing services. These countries have dense urban populations and traffic congestion issues, making on-demand transportation services a practical choice for commuters. Additionally, the rise of e-scooter and bike-sharing services is catering to the growing trend of eco-friendly transportation solutions in cities like Singapore and Malaysia.

Local special circumstances:
Southeast Asia's diverse geography and regulatory environment play a significant role in shaping the Shared Mobility market. For instance, archipelagic countries like Indonesia face unique challenges in providing seamless transportation services across multiple islands. In contrast, Singapore's compact urban landscape and government support for sustainable mobility initiatives have created a conducive environment for shared transportation services to thrive.

Underlying macroeconomic factors:
Economic growth, urbanization, and a young tech-savvy population are key macroeconomic factors driving the Shared Mobility market in Southeast Asia. As disposable incomes rise and cities become more congested, consumers are turning to shared transportation options as a practical solution for their daily commuting needs. Moreover, the proliferation of smartphones and mobile internet connectivity has enabled the widespread adoption of shared mobility services across the region.

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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