Market Insights Mobility Shared Mobility

E-Scooter-sharing - Saudi Arabia

Saudi Arabia

The E-Scooter-sharing market in Saudi Arabia is expected to generate a revenue of €2,811.00k by 2024.
This revenue is projected to grow annually at a rate of 6.57% between 2024 and 2029, resulting in a market volume of €3,864.00k by 2029.
Moreover, the E-Scooter-sharing market in Saudi Arabia is expected to have 267.10k users users by 2029, with a projected user penetration of 0.5% in 2024 and 0.7% by 2029.
Additionally, the average revenue per user (ARPU) is expected to be €13.79.
Online sales will generate 100% of the total revenue in this market by 2029.
In comparison to other countries, United States is projected to have the highest revenue in the E-Scooter-sharing market, which is expected to reach €677,100k in 2024.
E-Scooter-sharing is gaining popularity in Saudi Arabia as the government pushes for sustainable transportation options.

Key regions: China, Germany, Thailand, Saudi Arabia, India

Marché

Région

Comparaison de régions

Monnaie

Analyst Opinion

The E-Scooter-sharing market in Saudi Arabia is experiencing significant growth and development.

Customer preferences: Customers in Saudi Arabia are increasingly turning to e-scooter sharing as a convenient and eco-friendly mode of transportation. The younger generation, in particular, is embracing this trend, as they value the flexibility and cost-effectiveness that e-scooters offer. Additionally, the ease of use and ability to navigate congested city streets make e-scooters an attractive option for both short commutes and leisurely rides.

Trends in the market: One of the key trends in the e-scooter-sharing market in Saudi Arabia is the rapid expansion of service providers. Several local and international companies have entered the market, offering a wide range of e-scooter options to cater to different customer preferences. This increased competition has led to improved service quality, lower prices, and expanded coverage areas, making e-scooter sharing more accessible to a larger population. Another trend in the market is the integration of technology. E-scooter-sharing companies are leveraging advanced mobile applications and GPS tracking systems to enhance the user experience. Customers can easily locate and unlock e-scooters through their smartphones, and the apps provide real-time information on available scooters, charging stations, and riding routes. This technological integration has not only improved convenience for users but also helped service providers optimize their operations and ensure efficient fleet management.

Local special circumstances: Saudi Arabia's Vision 2030 initiative, which aims to diversify the economy and reduce dependence on oil, has played a significant role in driving the growth of the e-scooter-sharing market. As part of this vision, the government has been actively promoting sustainable transportation solutions and investing in infrastructure development. The introduction of dedicated bike lanes and the integration of e-scooters into public transportation systems have created a favorable environment for the growth of the market. Moreover, the cultural shift towards more sustainable and environmentally friendly practices has also contributed to the popularity of e-scooter sharing. Saudi Arabia has been making efforts to reduce carbon emissions and combat air pollution, and e-scooters align with these goals. The government's support for sustainable transportation options has further encouraged the adoption of e-scooters among the population.

Underlying macroeconomic factors: The e-scooter-sharing market in Saudi Arabia is also influenced by macroeconomic factors. The country has a young and tech-savvy population, which is driving the demand for innovative mobility solutions. Additionally, the high urbanization rate and increasing traffic congestion in major cities have created a need for alternative modes of transportation. E-scooters offer a convenient and efficient solution to navigate through crowded streets, reducing travel time and easing the burden on existing transportation infrastructure. Furthermore, the growing tourism industry in Saudi Arabia has contributed to the demand for e-scooter sharing. Tourists are increasingly seeking sustainable and unique experiences, and e-scooters provide a fun and eco-friendly way to explore the country's attractions. The government's efforts to promote tourism and attract international visitors have created a favorable market for e-scooter-sharing companies. In conclusion, the e-scooter-sharing market in Saudi Arabia is experiencing significant growth due to customer preferences for convenience and sustainability, the rapid expansion of service providers, technological integration, government support for sustainable transportation, and underlying macroeconomic factors such as a young population and growing tourism industry. This market is expected to continue to evolve and thrive in the coming years.

Methodology

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.