Data coverage:
The data encompasses B2C enterprises. Figures are based on the sales of bicycles and the respective average prices for bicycles.
Modeling approach:
Market sizes are determined through a Bottom-Up approach, building on specific predefined factors for each market. As a basis for evaluating markets, we use publications of industry associations, expert blogs, and data provided by governments and scientific institutions. In addition, we use relevant key market indicators and data from country-specific associations, such as GDP, population, and consumer spending per capita (based on current prices). 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, the ARIMA time series forecast and forecasts based on previous growth rates are well suited for forecasting the future demand for bicycles due to the brick and mortar nature of this market. The main drivers are GDP, consumer spending per capita, and population. The scenario analysis is based on a Monte Carlo simulation approach generating a range of possible outcomes by creating random variations in forecasted data points, based on assumptions about potential fluctuations in future values. By running numerous simulated scenarios, the model provides an estimated distribution of results, allowing for an analysis of likely ranges and confidence intervals around the forecast.
Additional notes:
The data is modeled using current exchange rates. The market is updated once a year. In some cases, the data is updated on an ad hoc basis (e.g., when new, relevant data has been released or significant changes within the market have an impact on the projected development).
