Key regions: China, Germany, Thailand, Saudi Arabia, India
The E-Scooter-sharing market in APAC is experiencing rapid growth and development due to several key factors.
Customer preferences: Customers in the APAC region are increasingly opting for E-Scooter-sharing services due to their convenience and affordability. E-Scooters provide a quick and efficient mode of transportation, especially for short distances in congested urban areas. Additionally, the environmentally-friendly nature of E-Scooters appeals to customers who are conscious about reducing their carbon footprint.
Trends in the market: One of the key trends in the E-Scooter-sharing market in APAC is the expansion of services to new cities and countries. As more customers embrace this mode of transportation, E-Scooter-sharing companies are rapidly expanding their operations to meet the growing demand. This trend is particularly evident in densely populated cities where traffic congestion is a major issue. Another trend in the market is the introduction of innovative features and technologies. E-Scooter-sharing companies are constantly striving to improve the user experience by incorporating features such as GPS tracking, mobile apps for easy booking and payment, and even smart locks. These advancements enhance the convenience and accessibility of E-Scooter-sharing services, further driving their popularity.
Local special circumstances: The E-Scooter-sharing market in APAC is influenced by several unique circumstances in different countries. For example, in countries like China and India, where two-wheeler vehicles are already widely used, the adoption of E-Scooter-sharing services has been relatively smooth. The familiarity with two-wheeler vehicles and the existing infrastructure for such vehicles have facilitated the growth of the E-Scooter-sharing market in these countries. On the other hand, in countries like Japan and South Korea, where public transportation is highly efficient and widely available, the adoption of E-Scooter-sharing services has been slower. However, as customers become more aware of the benefits of E-Scooter-sharing, such as flexibility and cost-effectiveness, the market is expected to grow in these countries as well.
Underlying macroeconomic factors: The growth of the E-Scooter-sharing market in APAC is also influenced by underlying macroeconomic factors. Rapid urbanization, increasing disposable incomes, and changing lifestyles are driving the demand for convenient and affordable transportation options. Additionally, government initiatives to promote sustainable transportation and reduce traffic congestion are also contributing to the growth of the E-Scooter-sharing market. In conclusion, the E-Scooter-sharing market in APAC is witnessing significant growth and development due to customer preferences for convenience and affordability, as well as the introduction of innovative features and technologies. Local special circumstances, such as existing two-wheeler vehicle usage and efficient public transportation, also play a role in shaping the market. Furthermore, underlying macroeconomic factors, such as rapid urbanization and government initiatives, are driving the demand for E-Scooter-sharing services in the APAC region.
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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