Shared Mobility - Chile

  • Chile
  • By 2024, the Shared Mobility market in Chile is anticipated to reach a revenue of US$4,443.00m .
  • Additionally, it is expected to exhibit an annual growth rate of 4.68% resulting in a projected market volume of US$5,585.00m by 2029.
  • The largest market in the market is Flights, with a projected market volume of US$2,131.00m by 2024.
  • In the case of Public Transportation, the number of users is expected to be around 12.38m users by 2029.
  • The user penetration rate is expected to increase from 74.9% in 2024 to 83.1% by 2029.
  • Furthermore, the average revenue per user (ARPU) is projected to be US$301.70 .
  • It is expected that by 2029, 69% of the overall revenue in the Shared Mobility market will be generated via online sales.
  • As compared to other countries, China is expected to generate the highest revenue of US$365bn by 2024.
  • Chile's shared mobility market is growing rapidly, with a focus on electric scooters and bikes in major cities like Santiago.

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

 
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Analyst Opinion

Chile has seen a significant rise in the Shared Mobility market in recent years, with various services like ride-hailing, bike-sharing, and car-sharing gaining popularity among consumers.

Customer preferences:
Customers in Chile are increasingly opting for Shared Mobility services due to the convenience, cost-effectiveness, and flexibility they offer. With growing urbanization and traffic congestion in major cities like Santiago, people are looking for alternative transportation options that are efficient and sustainable.

Trends in the market:
One of the key trends in the Shared Mobility market in Chile is the integration of technology. Companies are investing in app-based platforms, GPS tracking, and digital payment systems to enhance the user experience and streamline operations. Additionally, there is a growing trend towards electric vehicles in Shared Mobility services to promote environmental sustainability.

Local special circumstances:
Chile's unique geography and topography play a significant role in shaping the Shared Mobility market. The country's long and narrow shape, with major urban centers located far apart, creates a demand for flexible transportation solutions that can bridge the gap between different regions. This has led to the expansion of Shared Mobility services beyond metropolitan areas into suburban and rural areas.

Underlying macroeconomic factors:
The growth of the Shared Mobility market in Chile is also influenced by macroeconomic factors such as income levels, employment rates, and government regulations. As disposable incomes rise and more people enter the workforce, there is a greater demand for affordable and convenient transportation options. Moreover, government initiatives to reduce traffic congestion and curb emissions are driving the adoption of Shared Mobility services as part of a sustainable transportation 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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