Overview and Scope
Carpooling, also known as shared mobility, is the most technologically advanced transportation system that enables users to book a short-distance ride as and when needed. The booking of the cars through online carpooling platforms and app-based carpooling helps reduce the number of vehicles on the road, reduce carbon emissions, and protect the environment.
Sizing and Forecast
The car pooling market size has grown rapidly in recent years. It will grow from $9.64 billion in 2023 to $11.15 billion in 2024 at a compound annual growth rate (CAGR) of 15.7%. The growth in the historic period can be attributed to oil crises impact, rise of environmental awareness, urbanization trends, early ride-sharing initiatives, rising congestion, corporate carpooling programs.
The car pooling market size is expected to see rapid growth in the next few years. It will grow to $17.62 billion in 2028 at a compound annual growth rate (CAGR) of 12.1%. The growth in the forecast period can be attributed to expansion of ride-sharing services, integration of autonomous vehicles, demand for sustainable mobility, corporate and workplace initiatives, regulatory support and policies. Major trends in the forecast period include micro-mobility integration, emergence of ride-sharing platforms, demand for sustainable transport, integration of ai and routing algorithms, corporate carpooling solutions.
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The car pooling market covered in this report is segmented –
1) By Type: Online Carpooling Platforms, App-based Carpooling
2) By Car Type: Economy, Executive, Luxury
3) By Application: Businesses, Individuals, Schools, Other Applications
Asia-Pacific was the largest region in the carpooling market in 2023. Western Europe was the second largest region in the global carpooling market share. The regions covered in the car pooling market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
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Major Driver Impacting Market Growth
Government initiatives to minimise carbon emissions are likely to drive the carpooling market. Major metropolitan cities have traffic congestion with an increase in vehicle density on the roads, increasing carbon emissions. For instance, cities such as New York, Seoul, and Shanghai are among the top 10 cities with the highest carbon footprint. In an attempt to curb emissions, governments and companies are encouraging car-pooling to commute in the cities. In the Paris agreement on climate change, countries have set determined targets for carbon footprint reduction by 2030. For instance, the Delhi government in India has introduced an odd-even scheme to control the traffic density and keep a check on carbon emissions in the city. Corporates such as Amazon and Infosys are also encouraging car-pooling to commute to workplaces to reduce congestion and air pollution. The initiatives to keep a check on carbon emissions thereby contribute to the growth of the carpooling market.
Key Industry Players
Major companies operating in the car pooling market report are Uber Technologies Inc., Didi Chuxing Technology Co. Ltd., Karos Inc., Lyft Inc., Grab Holdings Inc., Carma Inc., car2go Europe GmbH, Via Transportation Inc., Waze Carpool, BlaBlaCar Inc., Getaround Inc., Scoop Technologies Inc., Wunder Carpool Inc., Cambio CarSharing Inc., GoMore Aps, Ryde Inc., Liftshare Inc., Nuride Inc., SRide Carpool Services Private Limited, SnappCar BV, Hitch Technologies Inc., Ridejoy Inc., Carpoolworld Inc., Cowlines, JustShareIt Inc., Velocia Inc., Meru Carpool Inc., Zimride Inc., Splitting Fares Inc., ShareRing Inc., ANI Technologies Private Limited, Zify Tech Solutions Pvt. Ltd.
The car pooling market report table of contents includes:
1. Executive Summary
2. Car Pooling Market Characteristics
3. Car Pooling Market Trends And Strategies
4. Car Pooling Market – Macro Economic Scenario
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32. Global Car Pooling Market Competitive Benchmarking
33. Global Car Pooling Market Competitive Dashboard
34. Key Mergers And Acquisitions In The Car Pooling Market
35. Car Pooling Market Future Outlook and Potential Analysis
36. Appendix
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