Key regions: China, Germany, Thailand, Saudi Arabia, India
The E-Scooter-sharing market in Southern Europe has experienced significant growth in recent years, driven by changing customer preferences, emerging trends in the market, and local special circumstances.
Customer preferences: Customers in Southern Europe are increasingly looking for convenient and eco-friendly transportation options. E-Scooter-sharing services provide a flexible and sustainable alternative to traditional modes of transportation, such as cars or public transportation. The ease of use and affordability of E-Scooter-sharing services appeal to a wide range of customers, including commuters, tourists, and students. Additionally, the younger generation, who are more environmentally conscious, are particularly attracted to the concept of E-Scooter-sharing.
Trends in the market: One of the key trends in the E-Scooter-sharing market in Southern Europe is the expansion of services to smaller cities and towns. While initially concentrated in major urban centers, E-Scooter-sharing companies are now realizing the potential in smaller markets. This trend is driven by the increasing popularity of E-Scooters and the desire to provide transportation options in areas where public transportation may be limited. Another trend in the market is the integration of E-Scooter-sharing services with existing transportation infrastructure. Many cities in Southern Europe have implemented bike lanes and dedicated parking spaces for E-Scooters, making it easier for customers to access and use the services. This integration not only improves the user experience but also encourages more people to adopt E-Scooter-sharing as a viable mode of transportation.
Local special circumstances: Southern Europe has a favorable climate for E-Scooter-sharing, with mild winters and long summers. This weather condition allows for year-round usage of E-Scooters, unlike in regions with harsher climates. The compact nature of many cities in Southern Europe also makes E-Scooter-sharing a convenient option for short trips, as customers can easily navigate through narrow streets and congested areas.
Underlying macroeconomic factors: The growing E-Scooter-sharing market in Southern Europe is also influenced by several underlying macroeconomic factors. The region has seen an increase in urbanization, with more people moving to cities for work and study. This urbanization trend creates a larger customer base for E-Scooter-sharing services. Additionally, Southern Europe has experienced economic growth in recent years, leading to increased disposable income and a higher willingness to spend on convenient and sustainable transportation options. In conclusion, the E-Scooter-sharing market in Southern Europe is developing rapidly due to changing customer preferences, emerging market trends, local special circumstances, and underlying macroeconomic factors. The convenience, affordability, and eco-friendliness of E-Scooter-sharing services make them an attractive option for customers in the region. As the market continues to grow, we can expect to see further expansion into smaller cities, increased integration with existing transportation infrastructure, and continued adoption by a wide range of customers.
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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