Key regions: India, Thailand, Malaysia, China, South America
The E-Scooter-sharing market in LATAM has experienced significant growth in recent years, driven by customer preferences for convenient and eco-friendly transportation options.
Customer preferences: Customers in LATAM are increasingly seeking transportation options that are convenient, cost-effective, and environmentally friendly. E-Scooter-sharing services provide a solution to these preferences by offering a convenient mode of transportation that can be easily accessed and used for short trips within cities. Additionally, the affordability of e-scooter rentals compared to other modes of transportation, such as taxis or ride-hailing services, makes them an attractive option for many customers in the region.
Trends in the market: One of the key trends in the E-Scooter-sharing market in LATAM is the rapid expansion of service providers. Numerous companies have entered the market, competing to capture a share of the growing demand for e-scooter rentals. This has led to increased availability of e-scooters in major cities across the region, making them easily accessible to customers. Another trend in the market is the integration of e-scooter-sharing services with existing transportation infrastructure. Many cities in LATAM have implemented bike lanes and dedicated parking spaces for e-scooters, making it easier for customers to use and park the vehicles. This integration with existing infrastructure has contributed to the popularity of e-scooter-sharing services and their widespread adoption by customers.
Local special circumstances: LATAM has unique characteristics that contribute to the development of the E-Scooter-sharing market. The region has a high population density in many urban areas, which creates a demand for efficient and convenient transportation options. Additionally, the relatively warm climate in many parts of LATAM makes e-scooters an appealing choice for short trips, as customers can enjoy the outdoors while commuting.
Underlying macroeconomic factors: Several macroeconomic factors have also contributed to the growth of the E-Scooter-sharing market in LATAM. The region has experienced economic growth in recent years, leading to an increase in disposable income for many individuals. This has allowed more customers to afford e-scooter rentals and contribute to the market's expansion. Furthermore, concerns about air pollution and the environmental impact of traditional modes of transportation have driven the demand for eco-friendly alternatives. E-Scooter-sharing services provide a greener option for transportation, aligning with the growing awareness and emphasis on sustainability in the region. In conclusion, the E-Scooter-sharing market in LATAM is developing rapidly due to customer preferences for convenient and eco-friendly transportation options. The expansion of service providers, integration with existing infrastructure, and unique local circumstances have contributed to the market's growth. Additionally, underlying macroeconomic factors, such as economic growth and environmental concerns, have further fueled the demand for e-scooter rentals in the region.
Data coverage:
The data encompasses B2C enterprises. Figures are based on bookings and revenues of e-scooter-sharing services.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.
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