Key regions: Germany, Europe, India, Indonesia, United States
The Moped-sharing market in Brazil has been experiencing significant growth in recent years.
Customer preferences: One of the main reasons for the growth of the Moped-sharing market in Brazil is the changing preferences of customers. With the increasing urbanization and traffic congestion in major cities like São Paulo and Rio de Janeiro, people are looking for more convenient and cost-effective transportation options. Moped-sharing provides a solution to this problem by offering a flexible and affordable mode of transportation for short-distance travel.
Trends in the market: The Moped-sharing market in Brazil is witnessing several trends that are driving its growth. Firstly, there is a growing trend of people opting for shared mobility solutions instead of owning a vehicle. This trend is fueled by factors such as rising vehicle ownership costs, limited parking space, and environmental concerns. Moped-sharing services provide a convenient and sustainable alternative to private vehicle ownership. Another trend in the market is the increasing adoption of electric mopeds. As the government and consumers become more conscious of environmental sustainability, there is a growing demand for electric vehicles. Electric mopeds offer a cleaner and greener mode of transportation, making them an attractive option for customers.
Local special circumstances: Brazil's unique geographical and demographic characteristics also contribute to the growth of the Moped-sharing market. The country has a large population, with a significant portion living in densely populated urban areas. This creates a high demand for efficient and affordable transportation options. Moped-sharing services cater to this demand by providing a convenient and cost-effective mode of transportation for short trips within the city.
Underlying macroeconomic factors: Several underlying macroeconomic factors have also played a role in the growth of the Moped-sharing market in Brazil. The country has experienced economic growth in recent years, leading to an increase in disposable income and consumer spending. This has made shared mobility services more accessible and affordable for a larger portion of the population. Furthermore, the government has been supportive of initiatives aimed at reducing traffic congestion and promoting sustainable transportation. This includes the implementation of bike lanes and the introduction of regulations to encourage the use of electric vehicles. These initiatives create a favorable environment for the growth of the Moped-sharing market. In conclusion, the Moped-sharing market in Brazil is growing due to changing customer preferences, trends in shared mobility, local special circumstances, and underlying macroeconomic factors. As urbanization and traffic congestion continue to increase, the demand for convenient and cost-effective transportation options is expected to drive further growth in the market.
Data coverage:
The data encompasses B2C enterprises. Figures are based on bookings and revenues of moped-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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