Key regions: Germany, Indonesia, South America, India, Europe
The Moped-sharing market has been rapidly growing in recent years. This mode of transportation offers a convenient and cost-effective solution for short-distance travel, especially in congested urban areas.
Customer preferences: Customers are increasingly opting for moped-sharing services due to their affordability and flexibility. Mopeds are a popular choice for short commutes, as they are faster than bicycles and more maneuverable in traffic compared to cars. Additionally, the ease of access and availability of moped-sharing services through mobile applications have made them a convenient option for customers.
Trends in the market: One of the key trends in the moped-sharing market is the expansion of services to new cities and regions. As the demand for convenient and sustainable transportation options continues to rise, moped-sharing companies are expanding their operations to cater to a larger customer base. This trend is driven by the success and positive reception of moped-sharing services in existing markets, as well as the potential for growth in untapped markets. Another trend in the market is the integration of electric mopeds. With a growing emphasis on environmental sustainability, moped-sharing companies are increasingly incorporating electric mopeds into their fleets. Electric mopeds offer a cleaner and quieter alternative to traditional gasoline-powered mopeds, aligning with the preferences of environmentally conscious customers. This trend also benefits from the increasing availability and affordability of electric vehicles.
Local special circumstances: The development of the moped-sharing market in each country is influenced by local factors and circumstances. For example, in densely populated cities with limited parking spaces, moped-sharing services provide a practical solution for last-mile transportation. In tourist destinations, moped-sharing services cater to the needs of visitors who want to explore the city at their own pace. Additionally, in countries with high gasoline prices, moped-sharing services offer a cost-effective alternative to owning a private vehicle.
Underlying macroeconomic factors: Several macroeconomic factors contribute to the growth of the moped-sharing market. Urbanization and population growth have led to increased congestion and longer commutes, creating a demand for efficient and affordable transportation options. Additionally, rising fuel prices and environmental concerns have prompted individuals to seek alternative modes of transportation. The increasing penetration of smartphones and the widespread availability of mobile applications have also facilitated the growth of moped-sharing services by providing a platform for easy access and booking. In conclusion, the Moped-sharing market is experiencing significant growth due to customer preferences for affordable and flexible transportation options. The expansion of services to new cities, the integration of electric mopeds, and local special circumstances all contribute to the development of the market. Underlying macroeconomic factors such as urbanization, population growth, rising fuel prices, and smartphone penetration further drive the growth of 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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