Key regions: China, Germany, Thailand, Saudi Arabia, India
The E-Scooter-sharing market in Eastern Europe has been experiencing significant growth in recent years.
Customer preferences: Customers in Eastern Europe are increasingly opting for e-scooter-sharing services due to their convenience and affordability. E-scooters provide a flexible and eco-friendly mode of transportation, allowing users to easily navigate through congested city streets and avoid traffic. Additionally, the low cost of renting an e-scooter compared to other transportation options makes it an attractive choice for many customers in the region.
Trends in the market: One of the key trends in the e-scooter-sharing market in Eastern Europe is the expansion of services into smaller cities and towns. Initially, e-scooter-sharing services were primarily available in major metropolitan areas, but companies have recognized the potential demand in smaller markets and have started expanding their operations accordingly. This trend has been driven by the increasing popularity of e-scooters among residents in these areas, who are looking for convenient and efficient transportation options. Another trend in the market is the integration of e-scooter-sharing services with existing transportation infrastructure. Many cities in Eastern Europe have been investing in improving their public transportation systems, and e-scooter-sharing companies have been partnering with local authorities to integrate their services with these systems. This integration allows users to seamlessly switch between different modes of transportation, making their journeys more efficient and convenient.
Local special circumstances: Eastern Europe is known for its dense urban areas and historical city centers with narrow streets. This presents a unique challenge for e-scooter-sharing companies, as they need to ensure that their services are accessible and safe in these areas. To address this, companies have been working closely with local authorities to establish designated parking zones for e-scooters and implement regulations to prevent misuse and ensure the safety of both riders and pedestrians.
Underlying macroeconomic factors: The growth of the e-scooter-sharing market in Eastern Europe can be attributed to several underlying macroeconomic factors. Firstly, the region has experienced rapid urbanization in recent years, leading to increased demand for alternative transportation options. Additionally, the rising awareness of environmental issues and the need to reduce carbon emissions has encouraged more people to choose eco-friendly modes of transportation like e-scooters. Lastly, the relatively high smartphone penetration rate in Eastern Europe has made it easier for customers to access and use e-scooter-sharing apps, contributing to the market's growth. In conclusion, the e-scooter-sharing market in Eastern Europe is growing due to customer preferences for convenience and affordability, as well as the expansion of services into smaller cities and integration with existing transportation infrastructure. The unique local circumstances, such as dense urban areas and historical city centers, have prompted companies to work closely with local authorities to ensure the accessibility and safety of their services. The underlying macroeconomic factors of rapid urbanization, environmental awareness, and high smartphone penetration have also contributed to the market's development 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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