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Ride-hailing - Indonesia

Indonesia

Indonesia is expected to witness a significant growth in the Ride-hailing market, with projected revenue reaching €3.25bn by 2024.
The market is further estimated to grow at an annual growth rate (CAGR 2024-2029) of 6.00%, resulting in a market volume of €4.35bn by 2029.
It is projected that the number of users in the Ride-hailing market will amount to 111.90m users by 2029, with a user penetration of 38.5%, up from 31.6% in 2024.
Additionally, the average revenue per user (ARPU) is expected to reach €36.84.
The Ride-hailing market is an online-only market.
In global comparison, China is expected to generate the most revenue in the market, with projected revenue of €55,230m in 2024.
Indonesia's Ride-hailing market is dominated by Gojek and Grab, with increasing competition from newcomers like Blue Bird and Tada.

Key regions: South America, Europe, China, Saudi Arabia, Malaysia

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Analyst Opinion

The Ride-hailing market in Indonesia has experienced significant growth in recent years, driven by changing customer preferences and the rise of digital technology.

Customer preferences: In Indonesia, customers are increasingly turning to ride-hailing services as a convenient and affordable mode of transportation. The ease of booking a ride through a mobile app and the ability to track the driver's location in real-time have made ride-hailing a popular choice among commuters. Additionally, the availability of various vehicle options, such as motorcycles and cars, caters to the diverse needs and preferences of customers.

Trends in the market: One of the key trends in the Indonesian ride-hailing market is the increasing competition among ride-hailing companies. Both local and international players have entered the market, offering attractive incentives and promotions to attract customers. This intense competition has led to price wars and aggressive marketing strategies, benefiting consumers with lower fares and better service quality. Another trend in the market is the expansion of ride-hailing services beyond major cities. Initially, ride-hailing services were primarily available in urban areas, but they have now expanded to smaller cities and even rural areas. This expansion has been facilitated by the growing penetration of smartphones and internet connectivity in these regions, making ride-hailing accessible to a wider population.

Local special circumstances: Indonesia's unique geography and infrastructure challenges have also contributed to the growth of the ride-hailing market. With its archipelago of more than 17,000 islands, Indonesia has limited public transportation options, especially in remote areas. Ride-hailing services have filled this gap by providing reliable transportation services to areas where traditional public transportation is scarce.

Underlying macroeconomic factors: The growing middle class and increasing urbanization in Indonesia have played a significant role in the development of the ride-hailing market. As more people move to cities and experience rising incomes, the demand for convenient and affordable transportation options has increased. Additionally, the rapid adoption of smartphones and internet connectivity has enabled the widespread use of ride-hailing services. In conclusion, the ride-hailing market in Indonesia is experiencing rapid growth due to changing customer preferences, increasing competition, expansion to new regions, unique geographical circumstances, and underlying macroeconomic factors. As the market continues to evolve, ride-hailing companies will need to adapt and innovate to meet the evolving needs of Indonesian consumers.

Methodology

Data coverage:

The data encompasses B2C enterprises. Figures are based on bookings and revenues of ride-hailing 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.