Key regions: China, Germany, Thailand, Saudi Arabia, India
The E-Scooter-sharing market in Portugal has been experiencing significant growth in recent years.
Customer preferences: Customers in Portugal 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 urban areas. The younger generation, in particular, is attracted to the trendiness and tech-savvy nature of e-scooters.
Trends in the market: One of the key trends in the e-scooter-sharing market in Portugal is the increasing number of players entering the market. Several local and international companies have launched their e-scooter sharing services in major cities across the country. This has created a highly competitive landscape, with companies vying for market share through aggressive marketing strategies and competitive pricing. Another trend in the market is the integration of e-scooter sharing services with existing transportation networks. Many cities in Portugal have implemented initiatives to promote multi-modal transportation, and e-scooters are seen as a complement to public transportation systems. This integration allows users to easily combine different modes of transportation for their daily commute, enhancing overall mobility options.
Local special circumstances: Portugal's warm climate and tourist-friendly cities make it an ideal market for e-scooter sharing services. The country attracts a large number of tourists, who often prefer to explore cities on e-scooters rather than relying solely on public transportation or traditional car rentals. Additionally, Portugal's compact cities and well-maintained infrastructure make it conducive for e-scooter usage.
Underlying macroeconomic factors: The growth of the e-scooter-sharing market in Portugal can also be attributed to favorable macroeconomic factors. The country has experienced steady economic growth in recent years, leading to an increase in disposable income among the population. This has allowed more people to afford the cost of using e-scooter sharing services. Furthermore, the government's focus on sustainable transportation solutions and reducing carbon emissions has created a supportive regulatory environment for e-scooter sharing companies. The government has implemented policies to encourage the use of electric vehicles, including e-scooters, by providing incentives and infrastructure support. In conclusion, the e-scooter-sharing market in Portugal is thriving due to customer preferences for convenient and eco-friendly transportation options. The market is characterized by intense competition and integration with existing transportation networks. Portugal's warm climate, tourist-friendly cities, and favorable macroeconomic factors have contributed to the growth of this market.
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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