Key regions: China, Germany, Thailand, Saudi Arabia, India
The E-Scooter-sharing market in United Arab Emirates is experiencing rapid growth and development due to several factors.
Customer preferences: Customers in the United Arab Emirates are increasingly turning to e-scooter-sharing as a convenient and eco-friendly mode of transportation. The compact size and maneuverability of e-scooters make them ideal for navigating the busy streets of cities like Dubai and Abu Dhabi. Additionally, the younger generation is particularly drawn to the concept of e-scooter-sharing, as it aligns with their desire for sustainable and tech-savvy transportation options.
Trends in the market: One of the key trends in the e-scooter-sharing market in the United Arab Emirates is the entry of major international players. Companies like Lime and Bird have expanded their operations to the region, bringing with them their expertise and established business models. This has led to increased competition and innovation in the market, with companies offering features like GPS tracking, mobile app integration, and improved battery life to attract customers. Another trend in the market is the integration of e-scooter-sharing with existing transportation systems. Local governments and transportation authorities have recognized the potential of e-scooters as a last-mile solution and have started to incorporate them into their overall transportation networks. This has led to the development of dedicated e-scooter lanes and parking areas, making it easier for customers to access and use e-scooters.
Local special circumstances: The United Arab Emirates has a high population density, especially in urban areas, which creates a demand for efficient and sustainable transportation options. E-scooter-sharing provides a solution to this demand by offering a cost-effective and convenient mode of transport for short distances. Additionally, the hot climate in the region makes walking or cycling less desirable, further driving the demand for e-scooters.
Underlying macroeconomic factors: The United Arab Emirates has a strong economy and a high disposable income among its residents. This enables people to afford the relatively higher rental fees associated with e-scooter-sharing services. Additionally, the government has been supportive of initiatives that promote sustainability and reduce carbon emissions. This has created a favorable regulatory environment for e-scooter-sharing companies to operate and expand in the country. In conclusion, the e-scooter-sharing market in the United Arab Emirates is experiencing significant growth due to customer preferences for convenient and eco-friendly transportation options. The entry of international players, integration with existing transportation systems, local special circumstances, and favorable macroeconomic factors have all contributed to the development of the market. As the market continues to evolve, it is expected that e-scooter-sharing will become an integral part of the transportation landscape in the United Arab Emirates.
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.
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