Key regions: Germany, Europe, India, Indonesia, United States
The Moped-sharing market in Georgia has been experiencing significant growth in recent years.
Customer preferences: Customers in Georgia are increasingly opting for moped-sharing services due to their convenience and affordability. Mopeds provide a flexible mode of transportation, allowing users to navigate through traffic and reach their destinations quickly. Additionally, the cost of renting a moped is relatively low compared to other transportation options, making it an attractive choice for budget-conscious individuals.
Trends in the market: One of the key trends in the moped-sharing market in Georgia is the rise of electric mopeds. With growing concerns about environmental sustainability, there is a growing demand for eco-friendly transportation options. Electric mopeds offer a cleaner and greener alternative to traditional gasoline-powered vehicles, making them popular among environmentally conscious customers. As a result, moped-sharing companies in Georgia are increasingly incorporating electric mopeds into their fleets to cater to this demand. Another trend in the market is the integration of technology. Moped-sharing companies are leveraging mobile applications and GPS tracking systems to streamline the rental process and enhance the overall user experience. Customers can easily locate and unlock available mopeds through their smartphones, eliminating the need for physical keys or manual paperwork. This technological integration has made moped-sharing more convenient and accessible, further driving its popularity in Georgia.
Local special circumstances: Georgia's urban areas, such as Tbilisi, experience high levels of traffic congestion, which can make commuting a challenging task. Moped-sharing services offer a practical solution for navigating through congested roads, allowing users to bypass traffic and reach their destinations faster. This unique local circumstance has contributed to the growth of the moped-sharing market in Georgia.
Underlying macroeconomic factors: Georgia's growing economy and increasing urbanization have played a significant role in the development of the moped-sharing market. As the country's GDP continues to rise, more individuals have disposable income to spend on transportation services. Additionally, the concentration of population in urban areas creates a higher demand for efficient and cost-effective transportation options, leading to the popularity of moped-sharing services. In conclusion, the moped-sharing market in Georgia is witnessing significant growth due to customer preferences for convenience and affordability. The rise of electric mopeds and the integration of technology are key trends in the market, catering to the demand for eco-friendly and user-friendly transportation options. The local special circumstance of traffic congestion in urban areas further drives the adoption of moped-sharing services. Overall, Georgia's growing economy and urbanization contribute to the development of the moped-sharing market in the country.
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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