Key regions: India, Thailand, Malaysia, China, South America
The E-Scooter-sharing market in Poland has witnessed significant growth in recent years, driven by changing customer preferences, emerging trends, and local special circumstances. Customer preferences in Poland have shifted towards more sustainable and convenient modes of transportation, leading to an increased demand for e-scooter sharing services. Customers are increasingly looking for cost-effective and eco-friendly alternatives to traditional modes of transportation, such as cars or public transport. E-scooters offer a flexible and convenient solution for short-distance travel, allowing users to easily navigate through crowded urban areas and avoid traffic congestion. Additionally, the younger generation, in particular, is more open to adopting new technologies and embracing the sharing economy, making e-scooter sharing services an attractive option for them. Trends in the market indicate a growing number of e-scooter-sharing companies entering the Polish market, leading to increased competition and innovation. Companies are constantly improving their e-scooter models, incorporating advanced features such as longer battery life, better stability, and enhanced safety measures. Additionally, the integration of e-scooter sharing services with mobile applications has made it easier for customers to locate and rent e-scooters, further driving the market growth. Moreover, partnerships with local authorities and transportation companies have helped e-scooter sharing companies expand their reach and establish a strong presence in different cities across Poland. Local special circumstances, such as the infrastructure and urban layout, have also contributed to the development of the e-scooter-sharing market in Poland. Many Polish cities have well-developed cycling infrastructure, making it easier for e-scooters to navigate through the streets. The compact size and maneuverability of e-scooters make them ideal for short-distance travel in urban areas, where parking and traffic congestion are major challenges. Furthermore, the high population density in cities like Warsaw and Krakow provides a large customer base for e-scooter sharing companies, ensuring a steady demand for their services. Underlying macroeconomic factors, such as the growing urbanization and increasing disposable income, have also played a role in the development of the e-scooter-sharing market in Poland. As more people move to cities and rely on public transportation, the demand for alternative transportation options, like e-scooters, has increased. Additionally, the rising disposable income in Poland has made e-scooter sharing services more affordable and accessible to a larger segment of the population. Overall, the e-scooter-sharing market in Poland is witnessing significant growth due to changing customer preferences, emerging trends, local special circumstances, and underlying macroeconomic factors. The market is expected to continue expanding as more companies enter the market, technological advancements improve the user experience, and the demand for sustainable and convenient transportation options continues to rise.
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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