Key regions: India, Thailand, Malaysia, China, South America
The E-Scooter-sharing market in Pakistan has been experiencing significant growth in recent years.
Customer preferences: Customers in Pakistan are increasingly opting for e-scooter sharing services due to their convenience and affordability. E-scooters provide a quick and efficient mode of transportation, especially in congested urban areas. Additionally, the low cost of renting an e-scooter compared to other modes of transportation, such as taxis or ride-sharing services, makes it an attractive option for many consumers.
Trends in the market: One of the key trends in the e-scooter sharing market in Pakistan is the expansion of services to smaller cities and towns. Initially, e-scooter sharing services were primarily available in major cities like Karachi and Lahore. However, due to the increasing demand and popularity of e-scooters, companies have started expanding their operations to smaller cities and towns. This trend is driven by the need for affordable and convenient transportation options in these areas. Another trend in the market is the introduction of electric scooters with enhanced features and capabilities. Companies are constantly innovating and improving their e-scooter models to cater to the evolving needs of customers. These new scooters offer longer battery life, better safety features, and improved performance, making them more appealing to consumers.
Local special circumstances: Pakistan's urban areas face significant traffic congestion and limited parking spaces, making e-scooter sharing an attractive alternative for short-distance travel. The compact size and maneuverability of e-scooters allow riders to navigate through congested roads and find parking spaces easily. This convenience factor has contributed to the growing popularity of e-scooter sharing services in Pakistan.
Underlying macroeconomic factors: The growth of the e-scooter sharing market in Pakistan can be attributed to several macroeconomic factors. Firstly, the increasing urbanization and population density in major cities have created a demand for efficient and affordable transportation options. E-scooter sharing services provide a solution to the transportation challenges faced by urban dwellers. Additionally, the rising awareness and concern about environmental sustainability have also played a role in the growth of the e-scooter sharing market. E-scooters are seen as a greener alternative to traditional modes of transportation, as they produce zero emissions. This aligns with the global trend towards sustainable transportation solutions. In conclusion, the e-scooter sharing market in Pakistan is experiencing significant growth due to customer preferences for convenience and affordability. The expansion of services to smaller cities, the introduction of enhanced e-scooter models, and the local special circumstances of traffic congestion and limited parking spaces have all contributed to this growth. Furthermore, underlying macroeconomic factors such as urbanization and environmental sustainability have also played a role in shaping the market.
Data coverage:
The data encompasses B2C enterprises. Figures are based on bookings and revenues of e-scooter-sharing 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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