Shared Mobility - Indonesia

  • Indonesia
  • Indonesia is projected to see a significant increase in revenue in the Shared Mobility market, with a projected amount of US$19,220.00m by 2024.
  • The market is expected to maintain a steady annual growth rate (CAGR 2024-2029) of 4.90%, resulting in a forecasted market volume of US$24,410.00m by 2029.
  • The largest market in Indonesia's Shared Mobility market is Flights, which is expected to reach a market volume of US$7,317.00m in 2024.
  • By 2029, the number of users in the Public Transportation market is expected to amount to 152.30m users.
  • The user penetration is expected to increase from 52.0% in 2024 to 57.7% by 2029.
  • The average revenue per user (ARPU) is expected to remain stable at US$163.20.
  • It is projected that 64% of the total revenue in Indonesia's Shared Mobility market will be generated through online sales by 2029.
  • In comparison to other countries, China is expected to generate the most revenue in this market, with an estimated revenue of US$365bn in 2024.
  • Indonesia's shared mobility market is rapidly growing due to the increasing demand for affordable and convenient transportation options.

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

 
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Analyst Opinion

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

Customer preferences:
Consumers in Indonesia are increasingly seeking convenient and cost-effective transportation options, leading to a growing demand for shared mobility services. With a large population living in urban areas facing traffic congestion and limited parking spaces, many are turning to shared mobility solutions as a more efficient and sustainable alternative to traditional car ownership.

Trends in the market:
One of the key trends shaping the Shared Mobility market in Indonesia is the rise of ride-hailing services and bike-sharing platforms. Companies offering these services have been quick to adapt to local needs by providing affordable and accessible transportation options through user-friendly mobile applications. Additionally, the integration of electric scooters and motorcycles into the market is gaining popularity due to their environmental benefits and suitability for navigating congested city streets.

Local special circumstances:
Indonesia's archipelagic geography and diverse cultural landscape present both challenges and opportunities for shared mobility providers. The varying infrastructure development across different regions can impact the availability and accessibility of services. Moreover, the cultural preference for motorbikes as a primary mode of transportation in many parts of the country influences the type of shared mobility solutions that are most successful in different areas.

Underlying macroeconomic factors:
The growing middle class and increasing urbanization rates in Indonesia are driving the expansion of the Shared Mobility market. Rising disposable incomes and changing lifestyle preferences are fueling the demand for convenient transportation options. Furthermore, government initiatives to reduce traffic congestion and air pollution are encouraging the adoption of shared mobility services as part of a sustainable urban mobility strategy.

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
  • User Demographics
  • Global Comparison
  • Methodology
  • Key Market Indicators
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