Shared Mobility - Peru

  • Peru
  • By the year 2024, the Shared Mobility market in Peru is anticipated to generate a revenue of US$4,817.00m.
  • Furthermore, the revenue is expected to exhibit an annual growth rate (CAGR 2024-2028) of 2.97%, eventually leading to a projected market volume of US$5,415.00m by 2028.
  • The largest market of this market in Peru is Flights, which is expected to reach a market volume of US$1,723.00m in 2024.
  • The number of users in the Public Transportation market is expected to reach 20.50m users by 2028.
  • User penetration in 2024 is 76.1% and is anticipated to rise to 76.2% by 2028.
  • The Average Revenue Per User (ARPU) is expected to be US$182.50.
  • In terms of online sales, 58% of the total revenue in the Shared Mobility market will be generated online by 2028.
  • It is worth noting that, in comparison to other countries, China is expected to generate the most revenue, with an estimated revenue of US$412bn in 2024.
  • Shared Mobility in Peru is gaining popularity due to the country's high traffic congestion and a growing demand for sustainable transportation options.

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

 
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Analyst Opinion

The Shared Mobility market in Peru is experiencing significant growth and development, reflecting a global trend towards alternative transportation options.

Customer preferences:
Customers in Peru are increasingly valuing flexibility and convenience when it comes to transportation. Shared Mobility services offer a cost-effective and efficient way to navigate the often congested urban areas in the country. The younger demographic, in particular, is driving the demand for shared mobility solutions as they seek more sustainable and convenient transportation options.

Trends in the market:
One notable trend in the Shared Mobility market in Peru is the increasing popularity of ride-hailing services. Companies offering ride-hailing apps have seen a surge in users as more people opt for on-demand transportation. Additionally, the electric scooter and bike-sharing services are gaining traction in major cities as a convenient and eco-friendly way to travel short distances.

Local special circumstances:
Peru's unique geography and urban landscape play a significant role in shaping the Shared Mobility market in the country. The presence of hilly terrains in cities like Lima makes it challenging for traditional transportation modes to navigate, creating a demand for more flexible and agile mobility solutions. Additionally, the growing middle class in Peru is driving the adoption of shared mobility services as people seek affordable and efficient ways to commute.

Underlying macroeconomic factors:
The growing economy in Peru is contributing to the expansion of the Shared Mobility market. As disposable incomes rise and urbanization continues, more people are looking for convenient and cost-effective transportation options. Additionally, government initiatives to improve infrastructure and promote sustainable transportation are further fueling the growth of shared mobility services 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.

Overview

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