Key regions: China, Germany, Thailand, Saudi Arabia, India
The E-Scooter-sharing market in Hungary has been experiencing significant growth in recent years.
Customer preferences: Customers in Hungary are increasingly turning to e-scooter sharing as a convenient and eco-friendly mode of transportation. The younger generation, in particular, is attracted to the flexibility and affordability that e-scooter sharing offers. With the rise of urbanization and the growing need for sustainable transportation options, e-scooter sharing has gained popularity among commuters and tourists alike.
Trends in the market: One of the key trends in the e-scooter sharing market in Hungary is the expansion of service providers. Several international and local companies have entered the market, leading to increased competition and a wider range of options for customers. This has resulted in lower prices and improved service quality as companies strive to differentiate themselves from their competitors. Another trend in the market is the integration of e-scooter sharing with other modes of transportation. Companies are partnering with public transportation operators to provide a seamless and integrated travel experience for customers. This not only enhances the convenience for users but also promotes the use of sustainable transportation options.
Local special circumstances: Hungary's well-developed infrastructure and compact cities make it an ideal market for e-scooter sharing. The country has a high population density in urban areas, which creates a strong demand for alternative transportation solutions. Additionally, Hungary has a favorable regulatory environment for e-scooter sharing, with clear guidelines and regulations in place to ensure the safety of riders and pedestrians.
Underlying macroeconomic factors: The growth of the e-scooter sharing market in Hungary is also influenced by underlying macroeconomic factors. The country has experienced steady economic growth in recent years, leading to increased disposable income and a higher standard of living. This has contributed to the willingness of customers to spend on convenient and sustainable transportation options. Furthermore, the government's focus on promoting sustainable mobility and reducing carbon emissions has created a favorable environment for the e-scooter sharing market. Hungary has set ambitious targets for reducing greenhouse gas emissions and improving air quality, which has encouraged individuals and businesses to adopt greener transportation alternatives. In conclusion, the e-scooter sharing market in Hungary is experiencing significant growth due to customer preferences for convenience and sustainability, the expansion of service providers, the integration with other modes of transportation, the favorable local circumstances, and the underlying macroeconomic factors. As the market continues to evolve, it is expected that e-scooter sharing will become an increasingly popular and mainstream mode of transportation in Hungary.
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.
Mon - Fri, 9am - 6pm (EST)
Mon - Fri, 9am - 5pm (SGT)
Mon - Fri, 10:00am - 6:00pm (JST)
Mon - Fri, 9:30am - 5pm (GMT)
Mon - Fri, 9am - 6pm (EST)
