Shared Mobility - Southern Asia

  • Southern Asia
  • The Shared Mobility market in Southern Asia is expected to experience a significant growth in revenue, with a projection of US$59,240.00m by 2024.
  • The market is expected to maintain an annual growth rate of 6.94% from 2024 to 2029, resulting in a projected market volume of US$153,400.00m by 2029.
  • The market's largest market, Flights, is projected to have a market volume of US$59,240.00m in 2024.
  • In terms of the highest user count, the Public Transportation market is expected to reach 1,559.00m users by 2029.
  • The user penetration rate is expected to be 73.7% in 2024 and 85.3% by 2029.
  • The average revenue per user (ARPU) is projected to amount to US$120.70.
  • Moreover, it is expected that by 2029, 69% of the total revenue in the Shared Mobility market will be generated through online sales.
  • It is interesting to note that in comparison to other countries, China is expected to generate the most revenue with a projection of US$365bn in 2024.
  • In Southern Asia, the shared mobility market is rapidly growing, with ride-hailing services like Grab and Gojek dominating the space in countries such as Indonesia and Vietnam.

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

 
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Analyst Opinion

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

Customer preferences:
Customers in Southern Asia are increasingly valuing convenience, cost-effectiveness, and sustainability when it comes to transportation options. Shared mobility services such as ride-hailing, bike-sharing, and car-sharing are gaining popularity due to their flexibility and affordability compared to traditional modes of transportation.

Trends in the market:
In countries like India and Bangladesh, the Shared Mobility market is witnessing a surge in demand for motorcycle taxis and auto-rickshaws as convenient and efficient first and last-mile solutions. On the other hand, countries like Singapore and Malaysia are seeing a rise in electric scooter and bicycle-sharing services to promote eco-friendly transportation options in urban areas.

Local special circumstances:
Southern Asia's diverse geography, rapid urbanization, and infrastructural challenges are influencing the growth of the Shared Mobility market in unique ways. For instance, congested cities like Jakarta and Dhaka are embracing motorcycle ride-hailing services to navigate traffic jams, while tourist destinations like Bali are adopting shared car services to cater to the travel needs of visitors.

Underlying macroeconomic factors:
The increasing smartphone penetration, rising disposable incomes, and growing urban population in Southern Asia are creating a conducive environment for the expansion of Shared Mobility services. Moreover, government initiatives to promote sustainable transportation solutions and reduce carbon emissions are further driving the adoption of shared mobility options 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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