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Key regions: South America, Malaysia, India, Indonesia, Saudi Arabia
The Bike-sharing market in Central Asia has been experiencing significant growth in recent years, driven by changing customer preferences, emerging trends in the market, local special circumstances, and underlying macroeconomic factors. Customer preferences in the Bike-sharing market in Central Asia have shifted towards more sustainable and convenient transportation options. With growing concerns about environmental issues and increasing traffic congestion in urban areas, customers are increasingly opting for bike-sharing services as a greener and more efficient mode of transportation. Additionally, the younger generation is showing a preference for bike-sharing due to its affordability and flexibility, as it allows them to easily navigate through crowded cities and avoid the hassle of finding parking spaces. Trends in the market are also contributing to the growth of the Bike-sharing market in Central Asia. One major trend is the rise of dockless bike-sharing systems, which allow users to pick up and drop off bikes anywhere within a designated service area, without the need for docking stations. This trend has gained popularity due to its convenience and flexibility, as it eliminates the need for users to locate and return bikes to specific stations. Another trend is the integration of bike-sharing services with mobile applications, allowing users to easily locate and unlock bikes using their smartphones. This technology-driven trend has made bike-sharing more accessible and user-friendly, attracting a larger customer base. Local special circumstances in Central Asia have also contributed to the development of the Bike-sharing market. The region's cities are experiencing rapid urbanization, with a growing population and increasing demand for transportation solutions. Inefficient public transportation systems and limited parking spaces have further fueled the demand for bike-sharing services as a viable alternative. Additionally, Central Asia is known for its scenic landscapes and tourist attractions, making bike-sharing an attractive option for both locals and tourists who want to explore the region's natural beauty. Underlying macroeconomic factors have played a role in the growth of the Bike-sharing market in Central Asia. Economic development and rising disposable incomes have made bike-sharing more affordable and accessible to a larger segment of the population. Furthermore, government initiatives promoting sustainable transportation and reducing carbon emissions have created a favorable regulatory environment for bike-sharing companies to operate and expand their services. In conclusion, the Bike-sharing market in Central Asia is experiencing significant growth due to changing customer preferences, emerging trends in the market, local special circumstances, and underlying macroeconomic factors. As the region continues to urbanize and prioritize sustainable transportation solutions, the Bike-sharing market is expected to further expand and evolve to meet the growing demand.
Data coverage:
The data encompasses B2C enterprises. Figures are based on bookings, revenues, and online shares of bike-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)