Definition:
The Ride-hailing market encompasses on-demand transportation services facilitated through mobile apps or online platforms. This market covers both private vehicle rides and taxi services, all booked exclusively online. It includes Transportation Network Companies (TNCs), such as Uber and Lyft, traditional taxis booked via apps, such as Free Now or Cabify, and ride-pooling services, such as Moia and Via. This market excludes peer-to-peer ride-sharing, focusing on professionally operated transport services booked digitally for efficient and convenient urban mobility. Rides of traditional taxi services hailed on the street or booked via telephone are not included in this market.
Additional Information:
The main performance indicators of the Ride-hailing market are revenues, average revenue per user (ARPU), user numbers and user penetration rates. Additionally, online and offline sales channel shares display the distribution of online and offline bookings. The ARPU refers to the average revenue one user generates per year while the revenue represents the total booking volume. Revenues are generated through both online and offline sales channels and include exclusively B2C revenues and users for the mentioned market. User numbers show only those individuals who have made a reservation, independent of the number of travelers on the booking. Each user is only counted once per year.
The booking volume includes all booked rides made by users from the selected region, regardless of where the ride took place.
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Notes: Data was converted from local currencies using average exchange rates of the respective year.
Most recent update: Jul 2024
Source: Statista Market Insights
Most recent update: Jul 2024
Source: Statista Market Insights
Most recent update: Jul 2024
Source: Statista Market Insights
Ride-hailing services have gained significant popularity in Guatemala in recent years. As more and more Guatemalans embrace the convenience and affordability of these services, the ride-hailing market in the country has experienced rapid growth.
Customer preferences: One of the main reasons for the growth of the ride-hailing market in Guatemala is the changing preferences of customers. Traditional taxi services in the country have long been plagued by issues such as unreliable service, high fares, and safety concerns. Ride-hailing platforms have addressed these concerns by offering a more convenient and reliable alternative. Customers can easily book a ride through a mobile app, track the driver's location, and make cashless payments. This level of convenience and transparency has resonated with Guatemalan customers, leading to a shift in their preferences towards ride-hailing services.
Trends in the market: The ride-hailing market in Guatemala has witnessed several key trends. Firstly, there has been a surge in the number of ride-hailing drivers in the country. Many individuals, including those who were previously unemployed or underemployed, have found ride-hailing to be a viable source of income. This has led to increased competition among drivers, resulting in shorter wait times for customers and lower fares. Additionally, ride-hailing companies in Guatemala have been expanding their services beyond just car rides. They have introduced options such as motorcycle taxis and delivery services, catering to a wider range of customer needs. This diversification of services has further contributed to the growth of the ride-hailing market in the country.
Local special circumstances: Guatemala has a large urban population, with many people residing in densely populated cities. The limited availability of parking spaces and the high cost of owning a car have made ride-hailing services an attractive option for many Guatemalans. Furthermore, the country has a relatively young population, with a high percentage of smartphone users. This has facilitated the adoption of ride-hailing apps and contributed to the growth of the market.
Underlying macroeconomic factors: The ride-hailing market in Guatemala has also been influenced by macroeconomic factors. The country has experienced steady economic growth in recent years, leading to an increase in disposable income for many Guatemalans. This has made ride-hailing services more affordable and accessible to a larger segment of the population. Furthermore, advancements in technology and the widespread availability of mobile internet have played a crucial role in the growth of the ride-hailing market. The ease of accessing ride-hailing apps and the seamless booking process have made these services more appealing to customers. In conclusion, the ride-hailing market in Guatemala has experienced significant growth due to changing customer preferences, key market trends, local special circumstances, and underlying macroeconomic factors. As ride-hailing services continue to evolve and expand their offerings, it is likely that the market will continue to thrive in the coming years.
Most recent update: Jul 2024
Source: Statista Market Insights
Most recent update: Jul 2024
Source: Statista Market Insights
Data coverage:
The data encompasses B2C enterprises. Figures are based on bookings and revenues of ride-hailing 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.Notes: Based on data from IMF, World Bank, UN and Eurostat
Most recent update: Sep 2024
Source: Statista Market Insights