Car-sharing - Armenia

  • Armenia
  • Armenia is projected to reach a revenue of US$0.88m in the Car-sharing market by 2024.
  • The revenue is forecasted to grow annually at a rate of 7.10% between 2024 and 2029, leading to a market volume of US$1.24m by 2029.
  • By 2029, the number of users in the Car-sharing market in Armenia is expected to reach 7.99k users.
  • The user penetration is anticipated to be 0.2% in 2024 and 0.3% by 2029.
  • The average revenue per user (ARPU) is estimated to be US$145.60.
  • In Armenia, 100% of the total revenue in the Car-sharing market will come from online sales by 2029.
  • When compared globally, the United States is set to generate the highest revenue, amounting to US$2,986m in 2024.
  • Armenia's Car-sharing market is rapidly growing, driven by the capital city's congestion issues and the population's increasing preference for shared mobility solutions.

Key regions: Europe, Germany, India, United States, Malaysia

 
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Analyst Opinion

Armenia, a country known for its rich history and cultural heritage, has seen a notable development in the car-sharing market in recent years.

Customer preferences:
Customers in Armenia are increasingly opting for car-sharing services due to the convenience and cost-effectiveness they offer. With the rising urbanization and traffic congestion in major cities like Yerevan, consumers are looking for alternative transportation options that are flexible and efficient. Car-sharing provides them with the freedom to use a vehicle when needed without the hassle of ownership.

Trends in the market:
One noticeable trend in the car-sharing market in Armenia is the growing popularity of electric and eco-friendly vehicles. As the country focuses on sustainability and environmental conservation, more car-sharing companies are incorporating electric cars into their fleets to cater to the eco-conscious consumer segment. This trend aligns with global efforts towards reducing carbon emissions and promoting green transportation solutions.

Local special circumstances:
Armenia's unique geographical location and topography play a significant role in shaping the car-sharing market. The country's mountainous terrain and varying weather conditions make owning a car challenging for many residents. Car-sharing services provide a practical solution for individuals who may not need a vehicle daily but require access to one for specific purposes or occasions. Additionally, the tech-savvy population in Armenia has embraced digital platforms and mobile applications, making it easier for car-sharing companies to reach and engage with customers.

Underlying macroeconomic factors:
The economic landscape in Armenia, with a growing middle class and increasing disposable income, has contributed to the expansion of the car-sharing market. As more people enter the workforce and pursue urban lifestyles, the demand for convenient transportation options rises. Moreover, the government's initiatives to improve transportation infrastructure and reduce traffic congestion further support the growth of the car-sharing sector. Overall, the combination of changing consumer preferences, environmental awareness, special local circumstances, and macroeconomic factors has propelled the car-sharing market in Armenia towards a path of continuous development and innovation.

Methodology

Data coverage:

The data encompasses B2C enterprises. Figures are based on bookings, revenues, and online shares of car-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.

Overview

  • Revenue
  • Sales Channels
  • Analyst Opinion
  • Users
  • Global Comparison
  • Methodology
  • Key Market Indicators
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