Ride-hailing - Lebanon

The Ride-hailing market in Lebanon has experienced significant growth in recent years, driven by changing customer preferences and local special circumstances.

Customer preferences: Lebanese customers have shown a growing preference for ride-hailing services due to their convenience and reliability. With the rise of smartphone usage in the country, people are increasingly relying on ride-hailing apps to book their transportation. The ability to track the driver's location, estimated time of arrival, and cashless payment options have made ride-hailing a popular choice for many Lebanese consumers. Additionally, the availability of various vehicle options, including economy, luxury, and shared rides, caters to the diverse needs and preferences of customers.

Trends in the market: One of the key trends in the ride-hailing market in Lebanon is the increasing competition among different service providers. Several local and international companies have entered the market, offering their ride-hailing services to Lebanese customers. This competition has led to improved service quality, competitive pricing, and innovative features to attract and retain customers. Furthermore, ride-hailing companies are expanding their services beyond major cities, reaching more remote areas in Lebanon. This trend is driven by the growing demand for transportation options in these areas and the desire to tap into previously untapped markets.

Local special circumstances: Lebanon's challenging traffic conditions and limited public transportation infrastructure have created a favorable environment for the growth of the ride-hailing market. The country's congested roads and lack of reliable public transportation options have made ride-hailing an attractive alternative for many Lebanese residents. Furthermore, the safety and security concerns associated with traditional taxis have also contributed to the popularity of ride-hailing services. Lebanese customers appreciate the ability to track their ride and share their location with friends or family members for added safety.

Underlying macroeconomic factors: Lebanon's ride-hailing market has also been influenced by underlying macroeconomic factors. The country has experienced economic challenges in recent years, including high unemployment rates and inflation. This has led many individuals to seek alternative sources of income, such as becoming ride-hailing drivers. The flexibility and earning potential offered by ride-hailing platforms have attracted many Lebanese individuals to join the gig economy. Additionally, the availability of ride-hailing services has also contributed to job creation in the country. In conclusion, the ride-hailing market in Lebanon has grown rapidly due to changing customer preferences, local special circumstances, and underlying macroeconomic factors. The convenience, reliability, and safety offered by ride-hailing services have made them a popular choice for many Lebanese consumers. With increasing competition and expanding services, the ride-hailing market in Lebanon is expected to continue its growth trajectory in the coming years.

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.