Shared Mobility - Oman

  • Oman
  • The projected revenue in Oman's Shared Mobility market is expected to reach US$689.50m by 2024, with an estimated annual growth rate (CAGR 2024-2029) of 3.48%.
  • This growth rate is expected to result in a market volume of US$818.30m by 2029.
  • The Flights market is projected to be the largest market, with an estimated market volume of US$299.50m in 2024.
  • By 2029, the number of users in the Public Transportation market is expected to reach 2.42m users.
  • The user penetration rate, which is 46.9% in 2024, is projected to increase to 50.8% by 2029.
  • The average revenue per user (ARPU) is expected to be US$311.70.
  • Furthermore, online sales are projected to generate 60% of the total revenue in the Shared Mobility market by 2029.
  • In comparison to other countries, China is expected to generate the most revenue, with an estimated revenue of US$365bn in 2024.
  • Shared mobility services are gaining popularity in Oman, with a growing number of residents opting for car-sharing and ride-hailing options.

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

 
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Analyst Opinion

The Shared Mobility market in Oman is experiencing a steady growth trajectory, driven by various factors unique to the region.

Customer preferences:
Customers in Oman are increasingly valuing convenience, affordability, and sustainability when it comes to transportation options. Shared mobility services such as ride-hailing, car-sharing, and bike-sharing are gaining popularity among the population as they offer flexible and cost-effective alternatives to traditional modes of transportation.

Trends in the market:
One of the key trends shaping the Shared Mobility market in Oman is the rise of technology-enabled platforms that connect users to different shared transportation options. These platforms provide users with easy access to on-demand services, real-time tracking, and cashless payment methods, enhancing the overall customer experience. Additionally, partnerships between shared mobility providers and local businesses are becoming more common, further expanding the reach and availability of these services.

Local special circumstances:
Oman's unique geographic and demographic characteristics play a significant role in shaping the Shared Mobility market. The country's growing urban population, particularly in major cities like Muscat, is driving the demand for efficient and sustainable transportation solutions. Moreover, the government's focus on reducing traffic congestion and carbon emissions is creating a conducive environment for the adoption of shared mobility services.

Underlying macroeconomic factors:
The economic stability and increasing disposable income levels in Oman are also contributing to the growth of the Shared Mobility market. As more people have the means to spend on transportation services, the demand for convenient and affordable shared mobility options is expected to rise. Additionally, government initiatives to improve infrastructure and promote smart city development are further fueling the expansion of the market.

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.

Overview

  • Revenue
  • Sales Channels
  • Analyst Opinion
  • Users
  • Global Comparison
  • Methodology
  • Key Market Indicators
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