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Key regions: United States, Saudi Arabia, Germany, Malaysia, India
The Shared Mobility market in Kenya is experiencing a significant growth trajectory driven by several factors.
Customer preferences: Customers in Kenya are increasingly valuing convenience, affordability, and sustainability when it comes to transportation options. Shared mobility services such as ride-hailing, bike-sharing, and scooter-sharing are gaining popularity as they offer a cost-effective and efficient way to navigate the often congested urban areas in the country.
Trends in the market: One of the prominent trends in the Shared Mobility market in Kenya is the integration of technology. Companies offering shared mobility services are leveraging mobile apps for booking rides, making payments, and tracking vehicles in real-time. This technological advancement enhances the overall user experience and contributes to the growing adoption of shared mobility solutions. Moreover, the market is witnessing a rise in partnerships and collaborations between shared mobility providers and other stakeholders such as public transportation agencies and city governments. These partnerships aim to address transportation challenges, improve accessibility, and promote sustainable mobility solutions across different regions in Kenya.
Local special circumstances: Kenya's unique geographical landscape and urban infrastructure play a crucial role in shaping the Shared Mobility market in the country. With rapid urbanization and population growth in cities like Nairobi and Mombasa, there is a growing demand for efficient and reliable transportation options. Shared mobility services fill this gap by offering flexible and on-demand solutions that cater to the diverse needs of urban commuters. Furthermore, the presence of a young and tech-savvy population in Kenya contributes to the increasing adoption of shared mobility services. The convenience of booking a ride through a smartphone app and the flexibility to choose from various transportation modes resonate well with the preferences of the younger demographic in the country.
Underlying macroeconomic factors: The economic landscape in Kenya, characterized by a rising middle class and increasing disposable income, plays a significant role in driving the growth of the Shared Mobility market. As more people have access to smartphones and digital payment methods, the barriers to entry for shared mobility services are lowered, leading to a broader customer base and market expansion. Additionally, government initiatives aimed at promoting sustainable transportation and reducing traffic congestion further support the development of the Shared Mobility market in Kenya. By incentivizing shared mobility solutions and implementing regulatory frameworks to ensure safety and quality standards, the government creates an enabling environment for shared mobility providers to thrive and innovate in the market.
Data coverage:
The data encompasses B2C enterprises. Figures are based on bookings, revenues, and online shares of car rentals, ride-hailing, taxi, car-sharing, bike-sharing, e-scooter-sharing, moped-sharing, trains, buses, public transportation, and flights.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)