Key regions: Germany, Europe, India, Indonesia, United States
The Moped-sharing market in Southern Asia is experiencing significant growth and development.
Customer preferences: Customers in Southern Asia are increasingly turning to moped-sharing services as a convenient and cost-effective mode of transportation. The high population density and congestion in many cities in the region make mopeds an attractive option for short-distance travel. Additionally, the relatively low cost of moped-sharing compared to owning a personal vehicle or using other modes of transportation is appealing to price-conscious customers.
Trends in the market: One major trend in the moped-sharing market in Southern Asia is the rapid expansion of service providers. Both local startups and international companies are entering the market to capitalize on the growing demand. This has led to increased competition and innovation, with companies offering features such as mobile app-based booking, flexible pricing plans, and improved customer support. Another trend is the integration of electric mopeds into the sharing market. With a focus on sustainability and reducing carbon emissions, many moped-sharing companies are introducing electric mopeds as a cleaner alternative to traditional gasoline-powered vehicles. This trend is driven by both customer demand for eco-friendly transportation options and government initiatives promoting the adoption of electric vehicles.
Local special circumstances: Southern Asia is home to several densely populated cities with limited parking infrastructure and congested roads. This creates a favorable environment for moped-sharing services, as they provide a convenient solution for short-distance travel without the need for parking space. Additionally, the warm climate in the region makes riding a moped an attractive option for many customers.
Underlying macroeconomic factors: The growing middle class in Southern Asia is a key driver of the moped-sharing market. As disposable incomes rise, more people are able to afford transportation services beyond traditional modes like public transit. Moped-sharing offers a flexible and affordable alternative to car ownership, particularly for short trips or last-mile connectivity. Furthermore, urbanization and the increasing number of people moving to cities in Southern Asia contribute to the growth of the moped-sharing market. As cities become more crowded and congested, there is a greater need for efficient and convenient transportation options. Moped-sharing services fulfill this need by providing a quick and flexible mode of transportation that can navigate through traffic and reach destinations faster than other alternatives. In conclusion, the moped-sharing market in Southern Asia is thriving due to customer preferences for convenient and cost-effective transportation, the expansion of service providers, the integration of electric mopeds, local special circumstances such as limited parking infrastructure, and underlying macroeconomic factors like the growing middle class and urbanization. This market is expected to continue growing as more people in the region recognize the benefits of moped-sharing and as companies innovate to meet customer demands.
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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