Key regions: China, Germany, Thailand, Saudi Arabia, India
The E-Scooter-sharing market in Algeria is experiencing significant growth and development.
Customer preferences: Customers in Algeria are increasingly opting for E-Scooter-sharing services due to their convenience, affordability, and environmental benefits. The ease of renting and riding e-scooters appeals to a wide range of customers, including commuters, students, and tourists. Additionally, the availability of e-scooters in densely populated areas and near public transportation hubs makes them a popular choice for short-distance travel.
Trends in the market: One of the key trends in the E-Scooter-sharing market in Algeria is the rapid expansion of service providers. Several companies have entered the market, offering their e-scooter rental services in major cities across the country. This increased competition has led to improved service quality, lower prices, and a wider range of options for customers to choose from. Another trend is the integration of e-scooter-sharing services with existing transportation infrastructure. Many cities in Algeria are implementing dedicated e-scooter lanes and parking areas to accommodate the growing demand for these vehicles. This integration not only enhances the overall user experience but also promotes the use of e-scooters as a viable mode of transportation.
Local special circumstances: The development of the E-Scooter-sharing market in Algeria is also influenced by local special circumstances. Algeria has a relatively young population, with a significant percentage of the population being millennials and Gen Z. These younger generations are more open to adopting new technologies and are more likely to embrace alternative modes of transportation, such as e-scooters. Furthermore, the high population density in urban areas of Algeria creates a favorable environment for the growth of e-scooter-sharing services. The compact nature of cities and the limited availability of parking spaces make e-scooters an attractive option for short-distance travel, reducing traffic congestion and improving air quality.
Underlying macroeconomic factors: Several underlying macroeconomic factors contribute to the development of the E-Scooter-sharing market in Algeria. The country has been experiencing economic growth, which has led to an increase in disposable income and improved living standards. This economic stability allows individuals to afford the cost of renting e-scooters, contributing to the market's growth. Additionally, the government of Algeria has shown support for sustainable transportation solutions, including e-scooter-sharing services. This support is evident through the implementation of infrastructure improvements and regulations that promote the use of e-scooters as a means of reducing carbon emissions and improving urban mobility. In conclusion, the E-Scooter-sharing market in Algeria is growing due to customer preferences for convenience and affordability, the integration of e-scooters with existing transportation infrastructure, local special circumstances such as a young population and high population density, and underlying macroeconomic factors such as economic growth and government support for sustainable transportation solutions.
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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