Shared Mobility - Myanmar

  • Myanmar
  • Myanmar's Shared Mobility market is expected to experience a significant boost in revenue, with projections showing a rise to €587.20m in 2024.
  • The market is also expected to grow annually by 5.75%, resulting in a projected market volume of €776.70m by 2029.
  • It is worth noting that the largest market in the Myanmar market is Flights, which is expected to reach a projected market volume of €210.80m by 2024.
  • In the Public Transportation market, the users are expected to amount to 21.28m users by 2029.
  • The user penetration in the Shared Mobility market of 56.1% in 2024 is projected increase to 64.4% by 2029.
  • The average revenue per user (ARPU) is expected to amount to €19.05.
  • It is also important to mention that online sales will account for 65% of total revenue in the Shared Mobility market by 2029.
  • In comparison to other countries, China is projected to generate the most revenue, with €335bn in 2024.
  • Shared mobility services in Myanmar are on the rise as the country's transportation infrastructure continues to develop.

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

 
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Analyst Opinion

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

Customer preferences:
Customers in Myanmar 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 solutions due to their flexibility and affordability compared to traditional transportation methods.

Trends in the market:
One of the key trends in the Shared Mobility market in Myanmar is the rapid adoption of ride-hailing services. Companies offering ride-hailing platforms have seen a surge in users as more people seek on-demand transportation options. Additionally, the introduction of motorbike taxi services has gained popularity in urban areas where traffic congestion is a major issue.

Local special circumstances:
Myanmar's unique geographical landscape and infrastructure challenges have played a significant role in shaping the Shared Mobility market in the country. With limited public transportation options and inadequate road infrastructure in certain regions, shared mobility services have filled a crucial gap in the transportation sector. Moreover, the increasing urbanization and population density in major cities like Yangon have further fueled the demand for shared mobility solutions.

Underlying macroeconomic factors:
The growing middle class and rising disposable income levels in Myanmar have contributed to the expansion of the Shared Mobility market. As more people have the purchasing power to afford transportation services, the demand for shared mobility options is expected to continue growing. Additionally, the government's efforts to improve regulations and infrastructure related to transportation have created a more conducive environment for shared mobility companies to operate and expand their services.

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.

Visión general

  • Revenue
  • Sales Channels
  • Analyst Opinion
  • Users
  • Global Comparison
  • Methodology
  • Key Market Indicators
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