Shared Mobility - LATAM

  • LATAM
  • Revenue in the Shared Mobility market is projected to reach US$91,470.00m in 2024.
  • Revenue is expected to show an annual growth rate (CAGR 2024-2029) of 2.86%, resulting in a projected market volume of US$105,300.00m by 2029.
  • The market's largest market is the Flights market with a projected market volume of US$40,240.00m in 2024.
  • In the Public Transportation market, the number of users is expected to amount to 415.70m users by 2029.
  • User penetration is 77.4% in 2024 and is expected to hit 82.7% by 2029.
  • The average revenue per user (ARPU) is expected to amount to US$185.90.
  • In the Shared Mobility market, 63% of total revenue will be generated through online sales by 2029.
  • In global comparison, most revenue will be generated in China (US$365bn in 2024).

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

 
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Analyst Opinion

Shared Mobility services in LATAM have been experiencing significant growth and development in recent years, reflecting the global trend towards more sustainable and convenient transportation options.

Customer preferences:
Customers in LATAM are increasingly looking for cost-effective and efficient transportation solutions, leading to a rise in demand for Shared Mobility services. The convenience of accessing transportation on-demand through mobile applications has also contributed to the popularity of ride-sharing and bike-sharing services in the region.

Trends in the market:
In Brazil, ride-sharing services have seen a surge in adoption, particularly in major cities like Sao Paulo and Rio de Janeiro. This trend can be attributed to the high urban population density and traffic congestion in these areas, making shared rides a more attractive option for commuters. Additionally, the growing middle-class population in countries like Mexico and Colombia has fueled the demand for affordable transportation alternatives, leading to the expansion of Shared Mobility services in these markets.

Local special circumstances:
One interesting development in the Shared Mobility market in LATAM is the emergence of electric scooter-sharing services in cities like Buenos Aires and Santiago. The compact size and eco-friendly nature of electric scooters make them a popular choice for short-distance trips in urban areas with limited parking space. This trend highlights the adaptability of Shared Mobility services to local infrastructure and environmental concerns in different countries across the region.

Underlying macroeconomic factors:
The economic growth and increasing smartphone penetration in LATAM have played a significant role in the expansion of Shared Mobility services. As more people gain access to mobile technology, the ease of booking shared rides or scooters through apps has become more widespread, driving the adoption of these services. Additionally, the rising awareness of environmental issues and the need for sustainable transportation options have further propelled the growth of Shared Mobility in 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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