Key regions: South America, Europe, China, Saudi Arabia, Malaysia
The Ride-hailing market in Ethiopia is experiencing significant growth and development, driven by changing customer preferences and local special circumstances.
Customer preferences: In Ethiopia, customers are increasingly turning to ride-hailing services as a convenient and reliable mode of transportation. With the rise of smartphone usage and improved internet connectivity, customers are embracing the ease of booking rides through mobile applications. The ability to track the location of the driver and estimated time of arrival has also become an appealing feature for customers, ensuring a seamless and efficient experience.
Trends in the market: One of the key trends in the ride-hailing market in Ethiopia is the emergence of local players. These homegrown companies understand the unique needs and challenges of the Ethiopian market, and have tailored their services accordingly. This localization strategy has allowed them to gain a competitive edge over international ride-hailing giants. Another trend is the expansion of ride-hailing services beyond major cities. Initially concentrated in urban areas, ride-hailing companies are now expanding their operations to secondary cities and even rural areas. This expansion is driven by the growing demand for transportation options in these areas, as well as the potential for untapped market opportunities.
Local special circumstances: Ethiopia has a large and growing population, with a significant portion of the population residing in urban areas. The rapid urbanization and increasing middle class have created a demand for convenient and affordable transportation options. Ride-hailing services have filled this gap by providing a reliable alternative to traditional taxis, which often suffer from issues such as lack of availability and price haggling. Furthermore, the Ethiopian government has been supportive of the ride-hailing industry, recognizing its potential to improve transportation infrastructure and create employment opportunities. This support has included the development of regulations and policies that promote the growth of the sector, as well as partnerships between ride-hailing companies and local authorities.
Underlying macroeconomic factors: Ethiopia has been experiencing steady economic growth in recent years, which has contributed to the expansion of the ride-hailing market. The increasing disposable income and changing consumer behavior have created a favorable environment for the adoption of ride-hailing services. Additionally, the growing middle class and urbanization have led to an increase in the number of people commuting for work and leisure, further driving the demand for ride-hailing services. In conclusion, the ride-hailing market in Ethiopia is witnessing significant growth and development, fueled by changing customer preferences, local special circumstances, and underlying macroeconomic factors. As the market continues to evolve, it is expected to play a crucial role in improving transportation infrastructure and providing employment opportunities in the country.
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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