Shared Mobility - Saudi Arabia

Saudi Arabia

Saudi Arabia is expected to experience significant growth in the Shared Mobility market, with projected revenue of €12,710.00m in 2024.
This is expected to rise at an annual growth rate of 3.44%, reaching a projected market volume of €14,550.00m by 2028.
The largest market in Saudi Arabia is Flights, with a projected market volume of €8,389.00m in 2024.
By 2028, the number of users in Ride-hailing is expected to increase to 13,790.00k users.
The user penetration rate in this market is expected to rise from 55.3% in 2024 to 55.6% by 2028.
The average revenue per user (ARPU) is expected to be €613.40.
In Saudi Arabia, 82% of the total revenue in the Shared Mobility market will be generated through online sales by 2028.
In comparison to other countries, China is expected to generate the most revenue in the Shared Mobility market, with a projected revenue of €376bn in 2024.
Shared mobility is gaining popularity in Saudi Arabia as the government pushes for sustainable transportation solutions.

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

Marché

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Comparaison de régions

Monnaie

Analyst Opinion

The Shared Mobility market in Saudi Arabia is witnessing significant growth and development in recent years.

Customer preferences: Customers in Saudi Arabia are increasingly looking for convenient, cost-effective, and environmentally friendly transportation options. Shared Mobility services such as ride-hailing, car-sharing, and bike-sharing are becoming popular choices among consumers who value flexibility and ease of access to transportation.

Trends in the market: One of the key trends in the Shared Mobility market in Saudi Arabia is the growing adoption of ride-hailing services. With the rise of smartphone usage and the convenience of booking a ride with just a few taps, more consumers are opting for ride-hailing platforms to navigate the cities. Additionally, car-sharing services are also gaining traction, especially in urban areas where individuals prefer to access a vehicle only when needed, rather than owning one.

Local special circumstances: Saudi Arabia's Vision 2030 initiative, aimed at diversifying the economy and reducing dependence on oil, is driving innovation and investment in the transportation sector. The government's support for smart mobility solutions and sustainable transportation options is creating a conducive environment for the growth of the Shared Mobility market in the country.

Underlying macroeconomic factors: The increasing urbanization rate in Saudi Arabia, coupled with a young and tech-savvy population, is fueling the demand for Shared Mobility services. Moreover, the government's efforts to improve public transportation infrastructure and reduce traffic congestion are encouraging more people to opt for shared modes of transportation. Overall, the combination of changing consumer preferences, government initiatives, and technological advancements is shaping the Shared Mobility market landscape in Saudi Arabia.

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.