Key regions: China, Germany, Thailand, Saudi Arabia, India
The E-Scooter-sharing market in India is experiencing significant growth and development.
Customer preferences: Customers in India are increasingly opting for E-Scooter-sharing services due to their convenience, affordability, and environmental benefits. E-Scooters provide a cost-effective and efficient mode of transportation, especially for short distances in congested urban areas. Additionally, the growing awareness about environmental sustainability has made E-Scooter-sharing services an attractive option for eco-conscious consumers.
Trends in the market: One of the key trends in the E-Scooter-sharing market in India is the rapid expansion of service providers. Several companies have entered the market, offering a variety of E-Scooter-sharing options to cater to different customer needs. This increased competition has led to improved services, better pricing, and enhanced customer experience. Another trend in the market is the integration of technology. E-Scooter-sharing companies in India are leveraging mobile applications and GPS tracking to provide users with a seamless experience. Customers can easily locate and unlock E-Scooters using their smartphones, making the process convenient and user-friendly.
Local special circumstances: India's urban population is growing rapidly, leading to increased congestion and pollution in cities. The government and local authorities are actively promoting sustainable transportation solutions to address these challenges. E-Scooter-sharing services align with the government's initiatives to reduce pollution and promote clean mobility options. Furthermore, India has a large young population, which is more inclined towards adopting new technologies and embracing innovative transportation solutions. This demographic factor has contributed to the growing popularity of E-Scooter-sharing services among the younger generation.
Underlying macroeconomic factors: India's economic growth and rising disposable incomes have played a significant role in the development of the E-Scooter-sharing market. As people's purchasing power increases, they are more willing to spend on convenient and sustainable transportation options. Additionally, the government's push for electric mobility and the availability of subsidies for electric vehicles have created a favorable environment for the E-Scooter-sharing market to thrive. The government's focus on reducing dependence on fossil fuels and promoting electric vehicles has encouraged the adoption of E-Scooter-sharing services. In conclusion, the E-Scooter-sharing market in India is witnessing rapid growth due to customer preferences for convenience and sustainability. The market is characterized by the expansion of service providers and the integration of technology. Local special circumstances, such as urban congestion and the young population, further contribute to the market's development. Additionally, underlying macroeconomic factors, including economic growth and government initiatives, have created a conducive environment for the E-Scooter-sharing market to flourish in India.
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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