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Mon - Fri, 9am - 6pm (EST)
Key regions: South America, Malaysia, India, Indonesia, Saudi Arabia
The Bike-sharing market in China has experienced significant growth in recent years, driven by changing customer preferences, emerging trends, and unique local circumstances.
Customer preferences: Chinese consumers have increasingly embraced bike-sharing as a convenient and cost-effective mode of transportation. With the rise of urbanization and traffic congestion, many people are opting for bike-sharing as a way to navigate crowded cities and avoid the hassles of finding parking. Additionally, the younger generation, in particular, has shown a strong preference for bike-sharing due to its eco-friendly nature and the convenience of booking and unlocking bikes through mobile apps.
Trends in the market: One notable trend in the Chinese Bike-sharing market is the emergence of dockless bike-sharing systems. Unlike traditional docked systems, dockless bike-sharing allows users to locate and unlock bikes using GPS technology, making it more flexible and convenient. This trend has been fueled by advancements in mobile technology and the widespread adoption of smartphones among Chinese consumers. As a result, many bike-sharing companies have adopted this model, leading to a proliferation of brightly colored bikes on the streets of Chinese cities. Another trend in the market is the integration of bike-sharing with other forms of transportation. Many cities in China have implemented bike-sharing programs that are seamlessly connected with public transportation systems, allowing users to easily switch between bikes and buses or trains. This integration has been facilitated by the development of smart transportation infrastructure, such as bike lanes and bike parking facilities, which further encourage the use of bike-sharing as a viable mode of transportation.
Local special circumstances: China's dense population and rapid urbanization have created unique circumstances that have contributed to the growth of the Bike-sharing market. The country's large cities, such as Beijing and Shanghai, face severe traffic congestion and air pollution, making bike-sharing an attractive alternative to cars and public transportation. Additionally, the Chinese government has been supportive of bike-sharing initiatives, implementing policies and regulations that promote the development of the market.
Underlying macroeconomic factors: China's booming economy has played a significant role in the growth of the Bike-sharing market. As disposable incomes rise and the middle class expands, more people have the financial means to afford bike-sharing services. Furthermore, the Chinese government's focus on sustainable development and green transportation has created a favorable environment for the bike-sharing industry to thrive. Overall, the Bike-sharing market in China is driven by changing customer preferences, emerging trends, unique local circumstances, and underlying macroeconomic factors. As the market continues to evolve, it is expected to further transform the way people travel in Chinese cities, providing a sustainable and convenient transportation solution for urban dwellers.
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)