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Key regions: South America, Malaysia, India, Indonesia, Saudi Arabia
The Bike-sharing market in Eastern Europe has been experiencing significant growth in recent years.
Customer preferences: One of the key customer preferences in the Bike-sharing market in Eastern Europe is the convenience and affordability of bike-sharing services. With increasing urbanization and traffic congestion in many cities in the region, customers are looking for alternative modes of transportation that can help them navigate through crowded streets quickly and at a lower cost. Bike-sharing services provide a flexible and cost-effective solution for short-distance travel, allowing customers to easily rent a bike and return it at their destination.
Trends in the market: One of the major trends in the Bike-sharing market in Eastern Europe is the adoption of dockless bike-sharing systems. Unlike traditional docked systems, dockless bike-sharing allows users to locate and unlock bikes using a mobile app, without the need for designated docking stations. This trend has gained popularity due to its convenience and flexibility, as users can pick up and drop off bikes anywhere within a designated service area. Dockless bike-sharing has also been facilitated by advancements in GPS technology and the widespread use of smartphones in the region. Another trend in the Bike-sharing market in Eastern Europe is the integration of electric bikes (e-bikes) into bike-sharing fleets. E-bikes provide an additional level of convenience and ease of use, as they require less physical effort to ride and can cover longer distances. The growing popularity of e-bikes can be attributed to their ability to attract a wider range of customers, including those who may not be physically fit or capable of riding traditional bicycles. E-bikes also align with the increasing focus on sustainability and eco-friendly transportation options in the region.
Local special circumstances: Eastern Europe has a unique set of circumstances that has contributed to the growth of the Bike-sharing market. Many cities in the region have limited parking spaces and congested roads, making bikes a more practical and efficient mode of transportation for short trips. Additionally, the relatively flat terrain in some Eastern European cities makes cycling an attractive option for commuting and leisure activities.
Underlying macroeconomic factors: The growth of the Bike-sharing market in Eastern Europe can also be attributed to favorable macroeconomic factors. The region has experienced steady economic growth in recent years, leading to an increase in disposable income and a higher standard of living. This has allowed more people to afford bike-sharing services and view them as a viable alternative to traditional transportation options. Furthermore, government initiatives promoting sustainable transportation and reducing carbon emissions have also played a role in the development of the Bike-sharing market in Eastern Europe. These initiatives have included the implementation of bike-friendly infrastructure, such as dedicated cycling lanes and bike parking facilities, which have made it easier and safer for people to use bike-sharing services.
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)