Shared Mobility - Turkmenistan

  • Turkmenistan
  • Turkmenistan is expected to witness a significant growth in its Shared Mobility market.
  • According to projections, the revenue in this market is expected to reach US$405.10m by 2024, with an annual growth rate of 5.68% between 2024 and 2029.
  • This growth is expected to result in a projected market volume of US$533.90m by 2029.
  • The largest market in this market is Public Transportation, with a projected market volume of US$326.50m by 2024.
  • It is expected that the number of users in the Public Transportation market will reach 4.25m users by 2029.
  • The user penetration in this market is expected to increase from 82.1% in 2024 to 95.0% by 2029.
  • The average revenue per user (ARPU) is expected to be US$74.83.
  • It is projected that 33% of the total revenue in the Shared Mobility market will be generated through online sales by 2029.
  • In a global comparison, China is expected to generate the most revenue in this market, with a projected revenue of US$365bn in 2024.
  • Despite a lack of established shared mobility services in Turkmenistan, the government's push for modernization may lead to future growth in the market.

Key regions: United States, Saudi Arabia, Germany, Malaysia, India

 
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Analyst Opinion

The Shared Mobility market in Turkmenistan is witnessing a gradual but steady growth in recent years.

Customer preferences:
Customers in Turkmenistan are increasingly seeking convenient and cost-effective transportation options, leading to a rising interest in shared mobility services. The younger population, in particular, is inclined towards flexible and on-demand transportation solutions that shared mobility platforms offer.

Trends in the market:
One notable trend in the Shared Mobility market in Turkmenistan is the increasing availability and utilization of ride-hailing services. As urbanization continues and traffic congestion rises in major cities, more individuals are turning to ride-hailing apps for their daily commuting needs. Additionally, the integration of various shared mobility options such as car-sharing and bike-sharing services is also becoming more prevalent in the market.

Local special circumstances:
Turkmenistan's unique geographical and cultural landscape plays a significant role in shaping the Shared Mobility market in the country. The vast desert terrain and limited public transportation infrastructure in certain regions drive the demand for alternative mobility solutions. Moreover, the government's focus on modernizing the transportation sector and promoting sustainable practices is creating a conducive environment for shared mobility services to thrive.

Underlying macroeconomic factors:
The gradual opening up of Turkmenistan's economy and the increasing disposable income levels among the population are key macroeconomic factors influencing the Shared Mobility market. As individuals become more financially capable and tech-savvy, the adoption of shared mobility services is expected to rise further. Additionally, the government's efforts to attract foreign investment and improve the overall business environment are likely to fuel the growth of the shared mobility sector in Turkmenistan.

Methodology

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.

Overview

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