Key regions: China, Germany, Thailand, Saudi Arabia, India
The E-Scooter-sharing market in United States is experiencing significant growth and development.
Customer preferences: Customers in the United States are increasingly opting for E-Scooter-sharing services due to their convenience and affordability. With the rise of urbanization and traffic congestion in major cities, people are looking for alternative modes of transportation that are efficient and cost-effective. E-Scooter-sharing provides a solution by offering a convenient and eco-friendly way to travel short distances. 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 States is the rapid expansion of service providers. Numerous companies have entered the market, competing to capture a share of the growing demand. This has led to an increase in the number of E-Scooters available for rent, making them more accessible to a larger population. Additionally, there is a trend towards the integration of E-Scooter-sharing services with existing transportation infrastructure, such as public transit systems. This integration allows for seamless multimodal transportation options and enhances the overall user experience.
Local special circumstances: The United States has a unique set of circumstances that contribute to the development of the E-Scooter-sharing market. Firstly, the country has a well-developed urban infrastructure, with many cities designed for car-centric transportation. This presents an opportunity for E-Scooter-sharing companies to fill the gap in the market and provide alternative transportation options. Secondly, the United States has a large population of tech-savvy individuals who are early adopters of new technologies. This tech-savvy population has embraced E-Scooter-sharing as a convenient and innovative mode of transportation.
Underlying macroeconomic factors: Several macroeconomic factors contribute to the growth of the E-Scooter-sharing market in the United States. Firstly, the increasing cost of car ownership, including fuel and parking expenses, has made people more willing to explore alternative transportation options. E-Scooter-sharing provides a cost-effective alternative that does not require the same level of financial commitment. Secondly, the focus on sustainability and reducing carbon emissions has gained traction in the United States. E-Scooter-sharing aligns with these goals by offering a green transportation option. Lastly, the sharing economy has gained popularity in recent years, with people embracing the idea of sharing resources rather than owning them outright. E-Scooter-sharing fits into this sharing economy model, allowing individuals to access transportation on-demand without the need for ownership. In conclusion, the E-Scooter-sharing market in the United States is experiencing significant growth and development due to customer preferences for convenience and affordability, the trend of rapid expansion of service providers, local circumstances such as well-developed urban infrastructure and a tech-savvy population, and underlying macroeconomic factors such as the increasing cost of car ownership, sustainability goals, and the popularity of the sharing economy.
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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