Key regions: South America, Europe, China, Saudi Arabia, Malaysia
The Ride-hailing market in BRICS countries has been experiencing significant growth in recent years. Customer preferences, trends in the market, local special circumstances, and underlying macroeconomic factors have all contributed to the development of this industry.
Customer preferences: Customers in BRICS countries are increasingly turning to ride-hailing services due to their convenience and affordability. The ability to request a ride with just a few taps on a smartphone has revolutionized the transportation industry. Additionally, ride-hailing services often offer competitive pricing compared to traditional taxis, making them an attractive option for cost-conscious consumers.
Trends in the market: One of the key trends in the ride-hailing market in BRICS countries is the emergence of local players. While global ride-hailing giants have a presence in these countries, local companies have gained significant market share by tailoring their services to meet the unique needs of the local population. These local players often have a better understanding of the local transportation infrastructure and cultural nuances, giving them a competitive advantage. Another trend in the market is the expansion of ride-hailing services beyond major cities. Initially, ride-hailing services were primarily available in urban areas with high population densities. However, as these services have gained popularity, they have expanded their operations to smaller cities and even rural areas. This expansion has helped to further increase the customer base and drive growth in the industry.
Local special circumstances: Each BRICS country has its own set of local special circumstances that have influenced the development of the ride-hailing market. For example, in Brazil, the high crime rate and lack of reliable public transportation have made ride-hailing services a popular choice for safety-conscious consumers. In Russia, the harsh winters and limited public transportation options have also contributed to the growth of the ride-hailing industry.
Underlying macroeconomic factors: Several underlying macroeconomic factors have played a role in the development of the ride-hailing market in BRICS countries. Rapid urbanization and population growth have increased the demand for transportation services, creating a favorable environment for ride-hailing companies. Additionally, the growing middle class in these countries has led to an increase in disposable income, allowing more people to afford ride-hailing services. In conclusion, the ride-hailing market in BRICS countries is experiencing significant growth due to customer preferences, trends in the market, local special circumstances, and underlying macroeconomic factors. The convenience and affordability of ride-hailing services, coupled with the expansion of these services to smaller cities and rural areas, have contributed to the industry's success. Local players have also gained market share by tailoring their services to meet the unique needs of the local population. The underlying macroeconomic factors, such as rapid urbanization and a growing middle class, have further fueled the growth of the ride-hailing market in BRICS countries.
Data coverage:
The data encompasses B2C enterprises. Figures are based on bookings and revenues of ride-hailing 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.
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