Key regions: China, Germany, Thailand, Saudi Arabia, India
The E-Scooter-sharing market in Southern Asia is experiencing significant growth and development, driven by various factors such as customer preferences, trends in the market, local special circumstances, and underlying macroeconomic factors. Customer preferences in Southern Asia play a crucial role in the growth of the E-Scooter-sharing market. With increasing urbanization and congestion in cities, customers are looking for convenient and eco-friendly transportation options. E-Scooter-sharing provides a solution by offering a flexible and affordable mode of transportation that can easily navigate through crowded streets. Additionally, the younger generation in Southern Asia is more inclined towards adopting new technologies and embracing sustainable practices, making E-Scooter-sharing a popular choice among this demographic. Trends in the market also contribute to the development of the E-Scooter-sharing industry in Southern Asia. One major trend is the rise of ride-sharing platforms that integrate E-Scooter-sharing services into their existing applications. This allows users to access multiple modes of transportation through a single platform, providing convenience and seamless connectivity. Furthermore, advancements in technology, such as improved battery life and enhanced safety features, are making E-Scooter-sharing more attractive and reliable for customers. Local special circumstances in Southern Asia further drive the growth of the E-Scooter-sharing market. For example, many cities in the region have limited parking spaces and face challenges in terms of traffic congestion. E-Scooter-sharing offers a solution by providing a compact and easily accessible mode of transportation that can be parked in designated areas or even on sidewalks. Additionally, Southern Asia experiences high population density in urban areas, making E-Scooter-sharing a practical and efficient option for short-distance travel. Underlying macroeconomic factors also contribute to the development of the E-Scooter-sharing market in Southern Asia. The region is witnessing rapid economic growth, leading to an increase in disposable income and purchasing power. This allows more individuals to afford E-Scooter-sharing services and contributes to the overall demand. Furthermore, governments in Southern Asia are increasingly focusing on sustainable transportation solutions and are implementing policies and regulations to support the growth of the E-Scooter-sharing industry. In conclusion, the E-Scooter-sharing market in Southern Asia is experiencing significant growth and development due to customer preferences, market trends, local special circumstances, and underlying macroeconomic factors. As more individuals seek convenient and eco-friendly transportation options, the E-Scooter-sharing industry is poised to continue its expansion in the 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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