Key regions: China, Germany, Thailand, Saudi Arabia, India
The E-Scooter-sharing market in Ukraine is experiencing significant growth and development. Customer preferences for convenient and eco-friendly transportation options, along with the increasing popularity of shared mobility services, are driving this trend. Additionally, local special circumstances and underlying macroeconomic factors are contributing to the expansion of the E-Scooter-sharing market in Ukraine. Customer preferences in Ukraine are shifting towards more sustainable and efficient transportation options. E-Scooter-sharing services provide a convenient and environmentally friendly alternative to traditional modes of transportation. With the growing concern for air pollution and congestion in urban areas, customers are increasingly opting for E-Scooter-sharing as a means of transportation. The ease of use and flexibility offered by E-Scooter-sharing services also appeal to customers who value convenience and flexibility in their daily commute. The E-Scooter-sharing market in Ukraine is also benefiting from global and regional trends in the shared mobility sector. Worldwide, the popularity of shared mobility services, such as bike-sharing and car-sharing, has been on the rise. This trend has influenced the growth of E-Scooter-sharing in Ukraine, as customers are becoming more familiar and comfortable with the concept of shared transportation. The success of E-Scooter-sharing in other countries has also sparked interest and investment in the Ukrainian market. Local special circumstances in Ukraine further contribute to the development of the E-Scooter-sharing market. The country has a large urban population, with many residents living in densely populated cities. This creates a high demand for efficient and convenient transportation options. E-Scooter-sharing services provide a solution to the last-mile connectivity problem, allowing users to easily navigate through congested urban areas and reach their final destinations. The compact size and maneuverability of e-scooters make them particularly suitable for navigating crowded streets and narrow lanes in Ukrainian cities. Underlying macroeconomic factors also play a role in the growth of the E-Scooter-sharing market in Ukraine. The country has experienced steady economic growth in recent years, leading to an increase in disposable income and purchasing power among the population. This enables more people to afford and access E-Scooter-sharing services. Additionally, the government has been supportive of sustainable transportation initiatives and has implemented policies and regulations to encourage the adoption of electric vehicles and shared mobility services. In conclusion, the E-Scooter-sharing market in Ukraine is developing rapidly due to customer preferences for convenient and eco-friendly transportation options, global and regional trends in shared mobility, local special circumstances, and underlying macroeconomic factors. As the market continues to grow, it is expected to contribute to the overall transformation of urban transportation in Ukraine, providing a sustainable and efficient solution for commuters and reducing the reliance on private vehicles.
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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