Shared Mobility - Malaysia

Malaysia

The Shared Mobility market sector in Malaysia is set to experience substantial growth in revenue, with a projected revenue of €5,818.00m in 2024.
It is predicted that the market volume will reach €6,727.00m by 2028, with an annual growth rate of 3.70%.
The largest market within Shared Mobility market is Flights, which is expected to generate a market volume of €3,230.00m in 2024.
The Public Transportation users are expected to be 13,100.00k users by 2028.
The user penetration rate is projected to increase from 56.4% in 2024 to 56.9% by 2028.
The average revenue per user (ARPU) is expected to be €297.70.
Furthermore, by 2028, 72% of the total revenue within the Shared Mobility market sector will be generated through online sales.
In comparison to other countries, China is expected to generate the highest revenue of €376bn in 2024.
In Malaysia, the shared mobility market is gaining traction with the rise of ride-hailing services like Grab and the introduction of electric scooter sharing programs.

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

Mercado

Región

Comparación de regiones

Moneda

Analyst Opinion

The Shared Mobility market in Malaysia has been experiencing significant growth and development in recent years.

Customer preferences: Customers in Malaysia are increasingly looking for convenient and cost-effective transportation options, which has led to a rise in demand for shared mobility services. The younger population, in particular, is more inclined towards using shared mobility services due to their flexibility and ease of use.

Trends in the market: One of the key trends in the Shared Mobility market in Malaysia is the increasing popularity of ride-hailing services. Companies offering ride-hailing services have been expanding their operations in the country, providing customers with a convenient way to get around urban areas. Additionally, the introduction of bike-sharing and e-scooter services has also gained traction among Malaysians looking for alternative modes of transportation.

Local special circumstances: Malaysia's growing urban population and increasing traffic congestion in major cities have contributed to the rise of shared mobility services in the country. The government's initiatives to promote sustainable transportation and reduce carbon emissions have also played a significant role in shaping the Shared Mobility market in Malaysia.

Underlying macroeconomic factors: The growing economy and rising disposable income levels in Malaysia have made shared mobility services more accessible to a larger segment of the population. Additionally, advancements in technology and the widespread use of smartphones have made it easier for customers to access and use shared mobility services, further driving the market growth in the country.

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.