Key regions: India, Thailand, Malaysia, China, South America
The E-Scooter-sharing market in China has witnessed significant growth in recent years, driven by changing customer preferences, emerging trends, and local special circumstances. Customer preferences in the E-Scooter-sharing market in China have shifted towards more sustainable and convenient transportation options. With increasing awareness about environmental issues, customers are opting for electric scooters as a greener alternative to traditional gasoline-powered vehicles. Additionally, the convenience and affordability of E-Scooter-sharing services have made them popular among urban dwellers, who are looking for flexible and cost-effective transportation solutions. Several trends have contributed to the growth of the E-Scooter-sharing market in China. Firstly, the rapid urbanization and population density in major cities have created a demand for compact and agile modes of transportation. E-Scooters provide a convenient solution for short-distance travel, especially in congested urban areas where parking is a challenge. Secondly, advancements in technology have made E-Scooter-sharing services more accessible and user-friendly. Mobile applications allow users to easily locate and unlock scooters, and integrated GPS systems ensure efficient fleet management. Moreover, the integration of smart features, such as digital payment options and real-time ride tracking, has enhanced the overall user experience. Local special circumstances in China have also played a significant role in the development of the E-Scooter-sharing market. The Chinese government has been actively promoting the use of electric vehicles as part of its efforts to reduce air pollution and carbon emissions. This has led to favorable policies and incentives for electric scooter manufacturers and operators. Additionally, the high population density in Chinese cities has created a large customer base for E-Scooter-sharing services, making it a lucrative market for both domestic and international players. Underlying macroeconomic factors have further fueled the growth of the E-Scooter-sharing market in China. The country's strong economic growth and rising disposable incomes have increased consumer spending power, enabling more people to afford E-Scooter-sharing services. Moreover, the Chinese government's focus on sustainable development and investment in clean energy technologies have created a supportive environment for the E-Scooter-sharing industry. In conclusion, the E-Scooter-sharing market in China is experiencing rapid growth due to changing customer preferences, emerging trends, local special circumstances, and underlying macroeconomic factors. As the demand for sustainable and convenient transportation solutions continues to rise, the E-Scooter-sharing market in China is expected to further expand in the coming years.
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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