Ride-hailing - Algeria | Statista Market Forecast

Algeria is projected to witness a substantial rise in revenue in the Ride-hailing market, which is expected to reach US$84.14m by 2024.
It is also expected to show an annual growth rate (CAGR 2024-2029) of 6.78%, resulting in a projected market volume of US$116.80m by 2029.
Furthermore, the number of users in this market is expected to amount to 8.93m users by 2029, with a user penetration rate of 15.0% in 2024 and 18.1% by 2029.
The average revenue per user (ARPU) is expected to amount to US$12.14, indicating that each user is likely to generate this much revenue.
By 2029, it is projected that 100% of total revenue will be generated through online sales.
Finally, it is worth noting that in global comparison, China is expected to generate the most revenue in this market, amounting to US$60bn in 2024.
Despite the emergence of new ride-hailing services, traditional taxis still dominate the Algerian market due to trust and familiarity with the service.

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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Platforms that let users book rides offered by drivers using their private vehicles (e.g., Uber)
Taxi companies that offer their services through an app (e.g., Free Now)
Platforms that offer shared rides (ride-pooling) with other passengers (e.g., Moia, Via)

Traditional taxi rides booked offline with taxi companies (via street-hailing or by telephone)

The Ride-hailing market in Algeria has been experiencing significant growth in recent years. Customer preferences, trends in the market, local special circumstances, and underlying macroeconomic factors have all contributed to this development. Customer preferences in Algeria have shifted towards convenience and affordability, which has led to the increased popularity of ride-hailing services. With the rise of smartphone usage and internet penetration in the country, consumers are increasingly looking for efficient and cost-effective transportation options. Ride-hailing platforms provide a convenient solution that allows users to book a ride with just a few taps on their smartphones, eliminating the need to wait for a taxi or navigate public transportation. Trends in the market have also played a role in the growth of the ride-hailing industry in Algeria. The emergence of local ride-hailing platforms has created competition in the market, leading to improved services and lower prices for consumers. These platforms have also introduced innovative features such as cashless payments and real-time tracking, further enhancing the customer experience. Local special circumstances have also contributed to the development of the ride-hailing market in Algeria. The country has a young and tech-savvy population, with a high percentage of smartphone users. This demographic is more likely to embrace new technologies and adopt ride-hailing services as a preferred mode of transportation. Additionally, the lack of a well-developed public transportation system in Algeria has created a demand for alternative transportation options, making ride-hailing services an attractive choice for many. Underlying macroeconomic factors have also played a role in the growth of the ride-hailing market in Algeria. The country has experienced economic growth in recent years, leading to an increase in disposable income and consumer spending. As a result, more people are able to afford ride-hailing services, contributing to the overall growth of the market. In conclusion, the ride-hailing market in Algeria has experienced significant growth due to customer preferences for convenience and affordability, trends in the market that have led to improved services and lower prices, local special circumstances such as a young and tech-savvy population, and underlying macroeconomic factors such as economic growth and increased consumer spending.

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.

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