Robotaxi Market by Application (Goods and Passenger), Level of Autonomy (L4 and L5), Vehicle (Car and Shuttle/Van), Service (Rental and Station Based), Propulsion (Electric and Fuel Cell), Component and Region - Global Forecast to 2030
The global robotaxi market size is projected to grow from 617 units in 2021 to 1,445,822 units by 2030, at a CAGR of 136.8%, during the forecast period 2021-2030.
Factors such as The rising concerns over road safety, emissions, and the increasing demand for ride-hailing services have led to the growth of the market. Autonomous vehicles also help in optimizing cost to the fleet operator. Newer business models like mobility as a service would provide another sustainable and profitable revenue stream in the future.
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COVID-19 Impact On the Robotaxi Market
The production and sales of new vehicles had come to a halt across the globe as the whole ecosystem had been disrupted in the initial outbreak of COVID 19. OEMs had to wait until lockdowns were lifted to resume production, which affected their businesses. Hence, vehicle manufacturers had to adjust the production volume. Also, component manufacturing was suspended, and small Tier II and Tier III manufacturers faced liquidity issues. The automotive industry is highly capital-intensive and relies on frequent financing to continue operations. Thus, the production suspension during the initial months of the outbreak and lower demand had an unprecedented impact on EV manufacturers in the initial months of the pandemic.
Due to the COVID-19 pandemic, many countries had imposed a complete lockdown of more than two months, which, in turn, has impacted vehicle production. Manufacturing units around the world were shut down, and vehicle sales have taken a huge hit. However, the majority of the automakers resumed vehicle production with limited production and necessary measures.
There were market disruptions in the initial phase of Covid-19 in the robotaxi market due to lockdowns, lower demand for ridesharing services etc. However, in the later period, the demand for robotaxis increased due to their own driving model. According to The Washington Post in May 2021, during the COVID-19 pandemic, over 5,000 drivers working at Lyft and Uber having independent contracts, accounted for approximately USD 80 million of the Economic Injury Disaster Loans. This showcases that these companies could not afford having large numbers of drivers, as demand for ridesharing/ride-hailing declined by 80% due to the pandemic. Thus, companies started emphasizing on including robotaxis in their fleets which is expected to significantly lower the operating costs, thereby, improving profit margins.
Market Dynamics:
Driver: Need for road safety and traffic control
According to the NHTSA, globally, approximately 94% car accidents occur due to human error every day. As stated by Waymo in 2020, approximately 1.4 million people die every year in road accidents around the world. As per the MIT Energy Initiative’s Mobility of the Future study in 2020, approximately 40,000 lives were lost in the US in 2019 due to road accidents. These behavioral errors can be reduced if technology takes charge of human activities such as driving. This is expected to lead to a reduction in owned vehicles on roads, decreasing the number of cars in cities worldwide. Thus, this is expected to ease traffic congestion and increase in efficiency in traffic control.
Restraint: High cost of R&D and complexity in adoption of robotaxis
Deploying a full-fledged robotaxi service requires high investments because components such as ultrasonic sensors, cameras, and LiDAR are expensive. The deployment and adoption of robotaxi fleets is complex and time consuming. As of June 2021, very few level 4 and level 5 autonomous vehicles are available for tests. Therefore, the deployment of robotaxi services in a comprehensive manner is difficult. The development of software for robotaxi’s is a complex process, and widespread application of level 5 autonomous vehicles is not only capital-intensive but is subject to regulatory compliance as well. A robotaxi is required to process large amounts of sensor data, which is almost 100 times higher than the most advanced vehicles available today. The complexity of software is increasing exponentially, with Diverse Deep Neural Networks (DNNs) functioning simultaneously, as part of a software stack.
To operate robotaxi’s in distinct conditions across the world, an intensive DNN training using large amount of data is required. This data is expected to grow exponentially due to the increasing number of robotaxi’s on roads. For instance, a robotaxi fleet of 50 vehicles driving for approximately six hours a day might produce approximately 1.6 petabytes data in a day. This volume of data is difficult to store and process, for vehicles to perform various functions in various conditions. Leading companies such as Google, Volkswagen, Volvo Cars, Nissan, Toyota, and General Motors have sufficient resources to tap into the robotaxi market. However, companies with limited resources are not capable of affording costly R&D processes.
Opportunity: Government support to drive the market
The race to deploy autonomous vehicles, especially in developed nations, has caught the attention of public policy makers in autonomous transportation and its potential impact. Governments of various countries have already loosened legal hindrances to undertake the testing of self-driving vehicles. The Ministry of Transport and Communications of Finland has gone a step ahead as it has prepared a legal structure for testing autonomous vehicles. Similarly, many other jurisdictions in countries such as Austria, France, Netherlands, UK, and the US are also following suit. For instance, in 2020, two new commercial programs were introduced by the California Public Utilities Commission (CPUC) which are expected to enable companies to test their robotaxi’s for commercial ride-hailing services.
Challenge:Navigation in crowded spaces expected to be challenging for robotaxis
Robotaxis are expected to wait for people to cross zebra crossings and move thereafter. However, in emerging countries, jaywalking is common practice with people passing by a zebra crossing randomly. This practice poses a major challenge for robotaxis in emerging countries. Crowded areas would also create a problem for these vehicles and would be a major challenge for implementing robotaxis. Technological advancements and strict implementation of regulations for pedestrians are expected to help resolve this issue. Some organizations are working to resolve the challenge with the help of real-time data. For instance, Mobileye crowdsources real-time road condition reports from vehicles equipped with intelligent fleet features and feeds the data for use in self-driving vehicles, making sure networked smart cars can navigate roads better.
A majority of robotaxis are expected to function initially on roads with marked lanes and vehicles moving in the same direction. Although the autonomous vehicle technology might correctly perform most of the time, it is expected to be challenging for the functioning of this technology in extreme conditions such as rain, snow, traffic signal failure, heavy traffic, and fog.
Electric propulsion is estimated to account for the largest market size during the forecast period
Rising emission concerns has led to the demand for fuel efficient vehicles. Robotaxis would not just offer robotic assistance but usher in an era of fuel efficiency and carbon-free emissions. The collaboration between Volvo and Uber is expected to introduce self-driving cars in the mid-size luxury segment by 2021—50% of which would be fully-electric cars. By 2030, two-third of the global population would reside in urban areas. Daimler is working with Bosch to develop self-driving electric cars in Germany that could be on the road by early 2020s. Full-electric robotaxis are already in demand due to stringency in worldwide government regulations for an emission-free environment. The joint venture between Volvo and Baidu for electric self-driving taxis in China is an example of an ecofriendly and advanced technical approach. Likewise, the partnership between BMW and Daimler has raked in investments worth USD 1.13 billion in autonomous electric cars.
Europe is expected to witness significant growth during the forecast period.
The European region is estimated to be dominated by countries such as Germany, France, Norway, and the Netherlands. Technological advancements and developed & supportive infrastructure have helped the fleet operators to test and deploy easily in this region. As per the European Commission, there are about 180 automobile facilities across the EU and the sector is the largest investor in R&D. Growing technological trends for autonomous vehicles will greatly impact the market. This will boost the overall demand for self-driving taxis in the region. Moreover, manufacturers such as NAVYA, Aptiv, EasyMile, Moia, and Daimler have their presence in the region.
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Key Market Players
The global The robotaxi market is dominated by global players such as Waymo (US), Cruise LLC (US), Baidu (China), AutoX (China), and Tesla (US). These companies develop new products, adopt expansion strategies, and undertake collaborations, partnerships, and mergers & acquisitions to gain traction in the high-growth robotaxi market.
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|
Report Metric |
Details |
|
Market size available for years |
2018–2030 |
|
Base year considered |
2020 |
|
Forecast period |
2021-2030 |
|
Forecast units |
Volume (Units) |
|
Segments covered |
Application, Level of Autonomy, Vehicle Type, Propulsion, Component, Service Type, and Region. |
|
Geographies covered |
North America, Asia Pacific, Europe, and Rest of the World. |
|
Companies Covered |
Waymo (US), Cruise Automation (US), Baidu (China), AutoX (China), and Tesla (US). |
This research report categorizes the robotaxi market based on Application, Level of Autonomy, Vehicle, Propulsion, Component, Service Type, and Region.
Based on Application Type:
- Goods Transportation
- Passenger Transportation
Based on Level of Autonomy:
- Level 4
- Level 5
Based on Vehicle Type:
- Car
- Shuttle/Van
Based on Propulsion:
- Electric
- Hybrid
- Fuel Cell
Based on Service Type:
- Car Rental
- Station Based
Based on Component Type:
- Camera
- Radar
- LiDAR
- Ultrasonic Sensors
Based on the region:
-
Asia Pacific
- China
- India
- Japan
- South Korea
- Singapore
-
North America
- US
- Canada
- Mexico
-
Europe
- France
- Germany
- Norway
- Spain
- UK
- The Netherlands
- Sweden
- Switzerland
-
Rest of the World
- UAE
- Russia
Recent Developments
- In May 2021, Argo AI unveiled the new LiDAR sensor which is capable of covering approximately 400 m down the road and thus, can be very useful in the autonomous driving technology.
- In May 2021, Baidu launched its first driverless, commercial robotaxi service in Beijing, China.
- In January 2021, AutoX revealed its driverless commercial taxi service, robotaxi, in Shenzhen, China. The service is expected to be available to the public in Shenzhen.
- In March 2020, The company introduced the 5th-generation Waymo Driver, a self-driving system.
- In March 2019, Waymo developed its own LiDAR. The company is now providing these sensors to companies for other than self-driving purposes—beginning with robotics, security, agricultural technology, and more—so that others can achieve their own technological breakthroughs. It announced that one of its 3D LiDAR sensors, Laser Bear Honeycomb, would be available to select partners.
- In November 2019, Tesla launched its EV Cybertruck with an approximately 3,500 pound payload capacity. It has a sturdy exoskeleton designed for superior strength and endurance.
- In March 2019, Waymo developed its own LiDAR. The company is now providing these sensors to companies for other than self-driving purposes—beginning with robotics, security, agricultural technology, and more—so that others can achieve their own technological breakthroughs. It announced that one of its 3D LiDAR sensors, Laser Bear Honeycomb, would be available to select partners.
Frequently Asked Questions (FAQ):
What is the current size of the global robotaxi market?
The global robotaxi market is estimated to be 617 units in 2021 and projected to reach 1,445,822 units by 2030, at a CAGR of 136.8%
Who are the winners in the global robotaxi market?
The global The robotaxi market is dominated by global players such as Waymo (US), Cruise LLC (US), Baidu (China), AutoX (China), and Tesla (US). These companies develop new products, adopt expansion strategies, and undertake collaborations, partnerships, and mergers & acquisitions to gain traction in the high-growth robotaxi market.
What is the Covid-19 impact on robotaxi manufacturers?
Most EV Manufacturers incurred losses due to sales reduction during the pandemic in the initial months. The sales recovered in the latter months as demand for robotaxis surged in the following months, however overall the companies suffered varying amount of losses.
What are the new market trends impacting the growth of the robotaxi market?
IoT and 5G network, 4D Lidar, Connected vehicles, AI and machine learning technology, cybersecurity and data privacy, etc. are some of the major trends affecting this market. .
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TABLE OF CONTENTS
1 INTRODUCTION (Page No. - 24)
1.1 OBJECTIVES OF THE STUDY
1.2 MARKET DEFINITION
1.2.1 INCLUSIONS & EXCLUSIONS
TABLE 1 INCLUSIONS & EXCLUSIONS FOR ROBOTAXI MARKET
1.3 MARKET SCOPE
1.3.1 MARKETS COVERED
FIGURE 1 MARKET SEGMENTATION
1.3.2 YEARS CONSIDERED FOR THE STUDY
1.4 PACKAGE SIZE
1.5 LIMITATIONS
1.6 STAKEHOLDERS
1.7 SUMMARY OF CHANGES
2 RESEARCH METHODOLOGY (Page No. - 31)
2.1 RESEARCH DATA
FIGURE 2 RESEARCH DESIGN
FIGURE 3 RESEARCH METHODOLOGY MODEL
2.1.1 SECONDARY DATA
2.1.1.1 List of key secondary sources
2.1.1.2 Key data from secondary sources
2.1.2 PRIMARY DATA
FIGURE 4 BREAKDOWN OF PRIMARY INTERVIEWS: BY COMPANY TYPE, DESIGNATION, & REGION
2.1.2.1 List of primary participants
2.2 MARKET ESTIMATION METHODOLOGY
FIGURE 5 RESEARCH METHODOLOGY: HYPOTHESIS BUILDING
2.3 MARKET SIZE ESTIMATION
2.3.1 BOTTOM-UP APPROACH
FIGURE 6 GLOBAL ROBOTAXI MARKET SIZE: BOTTOM-UP APPROACH
2.3.2 TOP-DOWN APPROACH
FIGURE 7 MARKET SIZE ESTIMATION METHODOLOGY FOR THE MARKET: TOP-DOWN APPROACH
FIGURE 8 MARKET: RESEARCH DESIGN & METHODOLOGY
FIGURE 9 MARKET: RESEARCH DESIGN & METHODOLOGY – DEMAND SIDE
FIGURE 10 RESEARCH APPROACH: MARKET
2.3.3 FACTOR ANALYSIS FOR MARKET SIZING: DEMAND AND SUPPLY SIDE
2.4 DATA TRIANGULATION
FIGURE 11 DATA TRIANGULATION
2.5 FACTOR ANALYSIS
2.6 RESEARCH ASSUMPTIONS
2.7 RESEARCH LIMITATIONS
3 EXECUTIVE SUMMARY (Page No. - 44)
FIGURE 12 ROBOTAXI MARKET: MARKET OVERVIEW
FIGURE 13 MARKET, BY REGION, 2021–2030
FIGURE 14 THE CAR SEGMENT IS ESTIMATED TO LEAD THE MARKET IN 2021
FIGURE 15 IMPACT OF COVID-19 ON THE MARKET, 2018–2030
FIGURE 16 REVENUE SHIFT IN THE MARKET
4 PREMIUM INSIGHTS (Page No. - 49)
4.1 ATTRACTIVE OPPORTUNITIES IN THE ROBOTAXI MARKET
FIGURE 17 GROWTH OF RIDE-HAILING SERVICES AND INCREASING FOCUS ON ROAD SAFETY EXPECTED TO BOOST THE MARKET
4.2 MARKET, BY REGION
FIGURE 18 ASIA PACIFIC ESTIMATED TO BE LARGEST MARKET IN 2021
4.3 MARKET, BY VEHICLE TYPE
FIGURE 19 CAR SEGMENT PROJECTED TO LEAD THE MARKET DURING THE FORECAST PERIOD
4.4 RMARKET, BY LEVEL OF AUTONOMY
FIGURE 20 LEVEL 4 SEGMENT PROJECTED TO DOMINATE THE MARKET DURING THE FORECAST PERIOD
4.5 MARKET, BY PROPULSION
FIGURE 21 ELECTRIC SEGMENT PROJECTED TO LEAD THE MARKET DURING THE FORECAST PERIOD
4.6 MARKET, BY SERVICE
FIGURE 22 CAR RENTAL SEGMENT TO LEAD THE MARKET DURING THE FORECAST PERIOD
4.7 MARKET, BY APPLICATION
FIGURE 23 PASSENGER TRANSPORT SEGMENT PROJECTED TO LEAD THE MARKET DURING THE FORECAST PERIOD
5 MARKET OVERVIEW (Page No. - 53)
5.1 INTRODUCTION
5.2 MARKET DYNAMICS
FIGURE 24 ROBOTAXI MARKET: MARKET DYNAMICS
5.2.1 DRIVERS
5.2.1.1 Robotaxis to reduce overall operating costs and increase profit margins for ride-sharing companies
TABLE 2 APPROXIMATE NUMBER OF DRIVERS EMPLOYED BY LEADING RIDE-HAILING SERVICE PROVIDERS
5.2.1.2 Need for enhanced road safety and traffic control
5.2.2 RESTRAINTS
5.2.2.1 Human jobs being jeopardized by machines expected to reduce wide acceptance
5.2.2.2 High R&D expenditure and complexity in the adoption of robotaxis
FIGURE 25 DATA FROM AN AUTONOMOUS VEHICLE
5.2.2.3 Cybersecurity threats might slow down market growth
5.2.3 OPPORTUNITIES
5.2.3.1 Government support to drive the market
5.2.3.2 Robotic assistance in the delivery of goods offer new opportunities for market growth
5.2.3.3 Rapid urbanization requiring the development of infrastructure in emerging countries
5.2.3.4 Increasing investments in lidar startups by automotive giants
5.2.4 CHALLENGES
5.2.4.1 Navigation in crowded spaces expected to be challenging for robotaxis
5.2.4.2 Gaining public and individual trust
5.2.4.3 Lack of required infrastructure in emerging countries
5.3 IMPACT OF MARKET DYNAMICS
5.4 FIVE ERAS OF VEHICLE SAFETY
FIGURE 26 FIVE ERAS OF VEHICLE SAFETY
5.5 SAE DEFINITION OF AUTONOMOUS VEHICLES
FIGURE 27 SOCIETY OF AUTOMOTIVE ENGINEERS AUTOMATION LEVELS
5.6 PORTER’S FIVE FORCES
TABLE 3 IMPACT OF PORTER’S FIVE FORCES ON THE ROBOTAXI MARKET
FIGURE 28 PORTER’S FIVE FORCES ANALYSIS: MARKET
5.6.1 THREAT OF SUBSTITUTES
5.6.2 THREAT OF NEW ENTRANTS
5.6.3 BARGAINING POWER OF BUYERS
5.6.4 BARGAINING POWER OF SUPPLIERS
5.6.5 RIVALRY BETWEEN EXISTING COMPETITORS
5.7 MARKET ECOSYSTEM
FIGURE 29 MARKET: ECOSYSTEM ANALYSIS
5.7.1 COMPONENT SUPPLIERS
5.7.2 SOFTWARE & PLATFORM PROVIDERS
5.7.3 AUTONOMOUS VEHICLE TECHNOLOGY PROVIDERS
5.7.4 AUTONOMOUS SHUTTLE MANUFACTURERS
TABLE 4 ROLE OF COMPANIES IN THE ROBOTAXI ECOSYSTEM
5.8 TECHNOLOGY ANALYSIS
5.8.1 IOT AND 5G IN ROBOTAXI MARKET
FIGURE 30 IOT DEVICES IN AUTONOMOUS VEHICLES
5.8.1.1 4D lidar
5.8.2 SENSORS AND THEIR IMPORTANCE IN AUTONOMOUS VEHICLES
FIGURE 31 SENSORS AND THEIR IMPORTANCE IN AUTONOMOUS VEHICLES
FIGURE 32 VISION SYSTEM OF A FULLY AUTONOMOUS VEHICLE
5.8.3 CONNECTED VEHICLES FOR AUTONOMOUS DRIVING
FIGURE 33 CONNECTED VEHICLES FOR AUTONOMOUS DRIVING
5.8.4 ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN THE MARKET
FIGURE 34 APPLICATIONS OF AI IN THE AUTOMOTIVE INDUSTRY
5.8.5 CYBERSECURITY AND DATA PRIVACY
5.9 PATENT ANALYSIS
5.9.1 INTRODUCTION
5.9.2 PATENTS FILED
FIGURE 35 PATENT APPLICATION TRENDS – LAST FIVE YEARS
5.9.2.1 Country-wise patent analysis
FIGURE 36 COUNTRY-WISE PATENT ANALYSIS
5.9.2.2 OEM-wise patent analysis
FIGURE 37 TOP PATENT APPLICANTS, 2010-2019
5.9.3 LIST OF SOME OF THE ONGOING AUTONOMOUS SHUTTLE PILOT PROJECTS IN THE EUROPEAN REGION
5.10 REGULATORY OVERVIEW
5.10.1 ENACTED LEGISLATIONS AND EXECUTIVE ORDERS IN THE US
FIGURE 38 ENACTED LEGISLATIONS AND EXECUTIVE ORDERS IN THE US
5.10.2 AUTONOMOUS VEHICLE TESTING AREA IN CHINA
FIGURE 39 AUTONOMOUS VEHICLE TESTING AREA IN CHINA
5.10.3 AUTONOMOUS VEHICLE TESTING AREA IN GERMANY
FIGURE 40 AUTONOMOUS VEHICLE TESTING AREA IN GERMANY
5.10.4 AUTONOMOUS VEHICLE TESTING AREA IN SINGAPORE
FIGURE 41 AUTONOMOUS VEHICLE TESTING AREA IN SINGAPORE
5.11 AVERAGE PRICING ANALYSIS
FIGURE 42 AVERAGE PRICES OF KEY COMPONENTS
TABLE 5 COMPANY-WISE APPROXIMATE COST OF ROBOTAXI & AUTONOMOUS SHUTTLE, 2020
5.12 VALUE CHAIN ANALYSIS
FIGURE 43 MAJOR VALUE ADDED TO DELIVERY SYSTEM DURING R&D AND MANUFACTURING PHASES
5.12.1 PLANNING AND REVISING FUNDS
5.12.2 R&D
5.12.3 MANUFACTURING
5.12.4 ASSEMBLY & INTEGRATION
5.12.5 DELIVERY/DISTRIBUTION
5.12.6 AFTERSALES SERVICES
5.13 CASE STUDY
5.13.1 NURO AUTONOMOUS VEHICLE PROVIDING COST-EFFECTIVE GROCERY DELIVERY SERVICES FOR KROGER
5.13.2 MCITY DRIVERLESS SHUTTLE PROJECT
5.14 MARKET, SCENARIOS (2021–2030)
FIGURE 44 MARKET– FUTURE TRENDS & SCENARIOS, 2021–2030 (UNITS)
5.14.1 MARKET – MOST LIKELY SCENARIO
TABLE 6 MARKET (MOST LIKELY), BY REGION, 2021–2030 (UNITS)
5.14.2 MARKET – OPTIMISTIC SCENARIO
TABLE 7 MARKET (OPTIMISTIC SCENARIO), BY REGION, 2021–2030 (UNITS)
5.14.3 MARKET – PESSIMISTIC SCENARIO
TABLE 8 MARKET (PESSIMISTIC), BY REGION, 2021–2030 (UNITS)
6 ROBOTAXI MARKET, BY VEHICLE TYPE (Page No. - 81)
6.1 INTRODUCTION
FIGURE 45 MARKET, BY VEHICLE TYPE, 2021 VS. 2030 (UNITS)
TABLE 9 MARKET, BY VEHICLE TYPE, 2018–2020 (UNITS)
TABLE 10 MARKET, BY VEHICLE TYPE, 2021–2030 (UNITS)
6.2 OPERATIONAL DATA
TABLE 11 FEW POPULAR AUTONOMOUS SHUTTLES FROM COMPANIES ACROSS THE WORLD
6.3 ASSUMPTIONS
TABLE 12 ASSUMPTIONS, BY VEHICLE TYPE
6.4 RESEARCH METHODOLOGY
6.5 CAR
6.5.1 DEVELOPMENTS IN RIDESHARING MARKET TO INCREASE THE DEMAND FOR ROBOTAXIS
TABLE 13 CAR: MARKET, BY REGION, 2018–2020 (UNITS)
TABLE 14 CAR: MARKET, BY REGION, 2021–2030 (UNITS)
6.6 VAN/SHUTTLE
6.6.1 RISING FOCUS ON PUBLIC TRANSPORT EXPECTED TO BOOST THE MARKET
TABLE 15 VAN/SHUTTLE: MARKET, BY REGION, 2018–2020 (UNITS)
TABLE 16 VAN/SHUTTLE: MARKET, BY REGION, 2021–2030 (UNITS)
FIGURE 46 KEY PRIMARY INSIGHTS
7 ROBOTAXI MARKET, BY APPLICATION TYPE (Page No. - 88)
7.1 INTRODUCTION
FIGURE 47 MARKET: BY APPLICATION TYPE, 2021 VS. 2030 (UNITS)
TABLE 17 MARKET, BY APPLICATION TYPE, 2018–2020 (UNITS)
TABLE 18 MARKET, BY APPLICATION TYPE, 2021–2030 (UNITS)
7.2 OPERATIONAL DATA
TABLE 19 FEW POPULAR ROBOTAXIS USED FOR PASSENGER TRANSPORTATION ACROSS THE WORLD
7.3 ASSUMPTIONS
TABLE 20 ASSUMPTIONS, BY APPLICATION TYPE
7.4 RESEARCH METHODOLOGY
7.5 GOODS TRANSPORTATION
7.5.1 RISING ECOMMERCE SERVICES AND UTILIZATION OF TRANSPORT CAPACITY EXPECTED TO DRIVE THE GOODS SEGMENT
TABLE 21 GOODS TRANSPORTATION: MARKET, BY REGION, 2021–2030 (UNITS)
7.6 PASSENGER TRANSPORTATION
7.6.1 GROWTH IN URBANIZATION IS EXPECTED TO BOOST THE PASSENGER SEGMENT
TABLE 22 PASSENGER TRANSPORTATION: MARKET, BY REGION, 2018–2020 (UNITS)
TABLE 23 PASSENGER TRANSPORTATION: MARKET, BY REGION, 2021–2030 (UNITS)
FIGURE 48 KEY PRIMARY INSIGHTS
8 ROBOTAXI MARKET, BY LEVEL OF AUTONOMY (LOA) (Page No. - 94)
8.1 INTRODUCTION
FIGURE 49 MARKET, BY LEVEL OF AUTONOMY, 2021 VS. 2030 (UNITS)
TABLE 24 MARKET, BY LEVEL OF AUTONOMY, 2018–2020 (UNITS)
TABLE 25 MARKET, BY LEVEL OF AUTONOMY, 2021–2030 (UNITS)
8.2 ASSUMPTIONS
TABLE 26 ASSUMPTIONS, BY LEVEL OF AUTONOMY
8.3 RESEARCH METHODOLOGY
8.4 LEVEL 4
8.4.1 LOWER RISK AND RAPID DEVELOPMENTS IN LEVEL 4 VEHICLES TO DRIVE THE MARKET
TABLE 27 LEVEL 4: MARKET, BY REGION, 2018–2020 (UNITS)
TABLE 28 LEVEL 4: MARKET, BY REGION, 2021–2030 (UNITS)
8.5 LEVEL 5
8.5.1 FUTURE TECHNICAL ADVANCEMENTS EXPECTED TO DRIVE THE LEVEL 5 MARKET
TABLE 29 LEVEL 5: MARKET, BY REGION, 2021–2030 (UNITS)
FIGURE 50 KEY PRIMARY INSIGHTS
9 ROBOTAXI MARKET, BY PROPULSION TYPE (Page No. - 100)
9.1 INTRODUCTION
FIGURE 51 MARKET, BY PROPULSION TYPE, 2021 VS. 2030 (UNITS)
TABLE 30 MARKET, BY PROPULSION TYPE, 2018–2020 (UNITS)
TABLE 31 MARKET, BY PROPULSION TYPE, 2021–2030 (UNITS)
9.2 OPERATIONAL DATA
TABLE 32 FEW POPULAR ELECTRIC AUTONOMOUS SHUTTLES OFFERED BY COMPANIES ACROSS THE WORLD
FIGURE 52 COMPARISON OF AMOUNT OF NATURAL GAS REQUIRED TO PROPEL ELECTRIC VEHICLE TO 300 MILES COMPARED TO FCEV TRAVELING 300 MILES
TABLE 33 SUMMARY OF FCEV ATTRIBUTES COMPARED TO THOSE OF ADVANCED ELECTRIC VEHICLE FOR 200 MILE AND 300 MILE RANGE
9.3 ASSUMPTIONS
TABLE 34 ASSUMPTIONS, BY PROPULSION
9.4 RESEARCH METHODOLOGY
9.5 ELECTRIC
9.5.1 HIGH FOCUS ON ELECTRIFICATION ACROSS THE GLOBE TO BOOST OVERALL DEMAND
TABLE 35 ELECTRIC: MARKET, BY REGION, 2018–2020 (UNITS)
TABLE 36 ELECTRIC: MARKET, BY REGION, 2021–2030 (UNITS)
9.6 FUEL CELL
TABLE 37 ZERO-EMISSION LIGHT-DUTY VEHICLES REFERENCE COMPARISON: BEV CHARGING VS. FCEV HYDROGEN FUELING
FIGURE 53 INITIAL INVESTMENT FOR VARIOUS FUEL INFRASTRUCTURE
FIGURE 54 COMPARISON OF BEV AND FCEV
9.6.1 FOCUS ON CURBING EMISSIONS EXPECTED TO BOOST THE FUEL CELL ROBOTAXI MARKET
TABLE 38 FUEL CELL: MARKET, BY REGION, 2021–2030 (UNITS)
FIGURE 55 KEY PRIMARY INSIGHTS
10 ROBOTAXI MARKET, BY SERVICE TYPE (Page No. - 109)
10.1 INTRODUCTION
FIGURE 56 MARKET, BY SERVICE TYPE, 2020 VS. 2030 (UNITS)
TABLE 39 MARKET, BY SERVICE TYPE, 2018–2020 (UNITS)
TABLE 40 MARKET, BY SERVICE TYPE, 2021–2030 (UNITS)
10.2 OPERATIONAL DATA
TABLE 41 SOME OF THE CAR RENTAL AND STATION-BASED AUTONOMOUS VEHICLE/ROBOTAXI PROVIDERS
10.3 ASSUMPTIONS
TABLE 42 ASSUMPTIONS, BY SERVICE TYPE
10.4 RESEARCH METHODOLOGY
10.5 CAR RENTAL
10.5.1 CONCERNS OVER TRAFFIC CONGESTION ARE DRIVING THE CAR RENTAL MARKET
TABLE 43 CAR RENTAL: MARKET, BY REGION, 2018–2020 (UNITS)
TABLE 44 CAR RENTAL: MARKET, BY REGION, 2021–2030 (UNITS)
10.6 STATION-BASED
10.6.1 FOCUS ON PUBLIC SAFETY EXPECTED TO BOOST THE STATION-BASED MARKET
TABLE 45 STATION-BASED: MARKET, BY REGION, 2018–2020 (UNITS)
TABLE 46 STATION-BASED: MARKET, BY REGION, 2021–2030 (UNITS)
FIGURE 57 KEY PRIMARY INSIGHTS
11 ROBOTAXI MARKET, BY COMPONENT TYPE (Page No. - 115)
11.1 INTRODUCTION
11.2 CAMERA
11.3 LIDAR
11.4 RADAR
11.5 ULTRASONIC SENSORS
12 ROBOTAXI MARKET, BY REGION (Page No. - 118)
12.1 INTRODUCTION
FIGURE 58 MARKET, BY REGION, 2021 VS. 2030
TABLE 47 MARKET, BY REGION, 2018–2020 (UNITS)
TABLE 48 MARKET, BY REGION, 2021–2030 (UNITS)
TABLE 49 MARKET, BY REGION, 2018–2020 (USD MILLION)
TABLE 50 MARKET, BY REGION, 2021–2030 (USD MILLION)
12.2 ASIA PACIFIC
FIGURE 59 ASIA PACIFIC: MARKET SNAPSHOT
TABLE 51 ASIA PACIFIC: MARKET, BY COUNTRY, 2018–2020 (UNITS)
TABLE 52 ASIA PACIFIC: MARKET, BY COUNTRY, 2021–2030 (UNITS)
12.2.1 CHINA
12.2.1.1 Technological advancements in autonomous driving expected to boost the market in China
TABLE 53 CHINA: MARKET, BY VEHICLE TYPE, 2018–2020 (UNITS)
TABLE 54 CHINA: MARKET, BY VEHICLE TYPE, 2021–2030 (UNITS)
12.2.2 INDIA
12.2.2.1 Government policies and infrastructure expected to lead to the growth of the market
TABLE 55 INDIA: MARKET, BY VEHICLE TYPE, 2021–2030 (UNITS)
12.2.3 JAPAN
12.2.3.1 Development of advanced EV technologies for the reduction of the carbon footprint expected to drive the market
TABLE 56 JAPAN: MARKET, BY VEHICLE TYPE, 2018–2020 (UNITS)
TABLE 57 JAPAN: MARKET, BY VEHICLE TYPE, 2021–2030 (UNITS)
12.2.4 SOUTH KOREA
12.2.4.1 Government initiatives towards the adoption of EVS to propel the market
TABLE 58 SOUTH KOREA: MARKET, BY VEHICLE TYPE, 2018–2020 (UNITS)
TABLE 59 SOUTH KOREA: MARKET, BY VEHICLE TYPE, 2021–2030 (UNITS)
12.2.5 SINGAPORE
12.2.5.1 Government initiatives towards the adoption of smarter transportation to drive the overall market
TABLE 60 SINGAPORE: MARKET, BY VEHICLE TYPE, 2021–2030 (UNITS)
12.3 EUROPE
FIGURE 60 EUROPE: MARKET SNAPSHOT
TABLE 61 EUROPE: MARKET, BY COUNTRY, 2018–2020 (UNITS)
TABLE 62 EUROPE: MARKET, BY COUNTRY, 2021–2030 (UNITS)
12.3.1 FRANCE
12.3.1.1 High demand for electric vehicles expected to drive the market
TABLE 63 FRANCE: MARKET, BY VEHICLE TYPE, 2018–2020 (UNITS)
TABLE 64 FRANCE: MARKET, BY VEHICLE TYPE, 2021–2030 (UNITS)
12.3.2 GERMANY
12.3.2.1 Innovations by German automakers in autonomous driving to drive the market
TABLE 65 GERMANY: MARKET, BY VEHICLE TYPE, 2018–2020 (UNITS)
TABLE 66 GERMANY: MARKET, BY VEHICLE TYPE, 2021–2030 (UNITS)
12.3.3 NORWAY
12.3.3.1 Government initiatives for zero-emissions in public transport to propel the market
TABLE 67 NORWAY: MARKET, BY VEHICLE TYPE, 2018–2020 (UNITS)
TABLE 68 NORWAY: MARKET, BY VEHICLE TYPE, 2021–2030 (UNITS)
12.3.4 SPAIN
12.3.4.1 Government initiatives for safer transportation is the key factor in overall growth
TABLE 69 SPAIN: MARKET, BY VEHICLE TYPE, 2021–2030 (UNITS)
12.3.5 SWEDEN
12.3.5.1 Increasing focus on AV technology is driving demand
TABLE 70 SWEDEN: MARKET, BY VEHICLE TYPE, 2021–2030 (UNITS)
12.3.6 NETHERLANDS
12.3.6.1 Increasing EV sales in the country expected to boost the market
TABLE 71 NETHERLANDS: MARKET, BY VEHICLE TYPE, 2021–2030 (UNITS)
12.3.7 UK
12.3.7.1 Good EV infrastructure to fuel the growth of the market
TABLE 72 UK: MARKET, BY VEHICLE TYPE, 2021–2030 (UNITS)
12.4 NORTH AMERICA
TABLE 73 NORTH AMERICA: MARKET, BY COUNTRY, 2018–2020 (UNITS)
TABLE 74 NORTH AMERICA: MARKET, BY COUNTRY, 2021–2030 (UNITS)
12.4.1 CANADA
12.4.1.1 Developments in EV infrastructure expected to propel growth
TABLE 75 CANADA: MARKET, BY VEHICLE TYPE, 2021–2030 (UNITS)
12.4.2 MEXICO
12.4.2.1 Rising awareness of low-emission and safe transport expected to drive the market
TABLE 76 MEXICO: MARKET, BY VEHICLE TYPE, 2021–2030 (UNITS)
12.4.3 US
12.4.3.1 Availability of infrastructure, regulations, and large-scale testing expected to boost the market
TABLE 77 US: MARKET, BY VEHICLE TYPE, 2018–2020 (UNITS)
TABLE 78 US: MARKET, BY VEHICLE TYPE, 2021–2030 (UNITS)
12.5 REST OF THE WORLD (ROW)
TABLE 79 ROW: MARKET, BY COUNTRY, 2018–2020 (UNITS)
TABLE 80 ROW: MARKET, BY COUNTRY, 2021–2030 (UNITS)
12.5.1 RUSSIA
12.5.1.1 Advancements in autonomous driving technology expected to lead to market growth
TABLE 81 RUSSIA: MARKET, BY VEHICLE TYPE, 2018–2020 (UNITS)
TABLE 82 RUSSIA: MARKET, BY VEHICLE TYPE, 2021–2030 (UNITS)
12.5.2 UAE
12.5.2.1 Increasing infrastructure for EV technology expected to lead to market growth
TABLE 83 UAE: MARKET, BY VEHICLE TYPE, 2021–2030 (UNITS)
13 COMPETITIVE LANDSCAPE (Page No. - 140)
13.1 OVERVIEW
TABLE 84 OVERVIEW OF STRATEGIES ADOPTED BY KEY PLAYERS IN THE ROBOTAXI MARKET
13.2 MARKET RANKING ANALYSIS
13.3 COMPANY EVALUATION QUADRANT
FIGURE 61 MARKET: COMPANY EVALUATION MATRIX, 2021
13.3.1 STAR
13.3.2 PERVASIVE
13.3.3 EMERGING LEADER
13.3.4 PARTICIPANT
TABLE 85 COMPANY APPLICATION FOOTPRINT (24 COMPANIES)
TABLE 86 COMPANY REGION FOOTPRINT (24 COMPANIES)
TABLE 87 OVERALL COMPANY FOOTPRINT (24 COMPANIES)
FIGURE 62 MARKET: COMPETITIVE LEADERSHIP MAPPING FOR TECHNOLOGY AND COMPONENT SUPPLIERS, 2021
13.4 COMPETITIVE SCENARIO AND TRENDS
13.4.1 PRODUCT LAUNCHES
TABLE 88 MARKET: PRODUCT LAUNCHES, 2018 - 2021
13.4.2 DEALS
TABLE 89 MARKET: DEALS, 2017 - 2020
13.4.3 OTHERS
14 COMPANY PROFILES (Page No. - 151)
14.1 KEY PLAYERS
(Business overview, Recent developments, MNM view, Key strengths/Right to win, Strategic choices made, and Weaknesses and competitive threats)*
14.1.1 WAYMO
TABLE 90 WAYMO: BUSINESS OVERVIEW
TABLE 91 WAYMO: PRODUCTS OFFERED
TABLE 92 WAYMO: NEW PRODUCT DEVELOPMENTS
TABLE 93 WAYMO: DEALS
TABLE 94 WAYMO: OTHERS
14.1.2 AUTOX
TABLE 95 AUTOX: BUSINESS OVERVIEW
TABLE 96 AUTOX: PRODUCTS OFFERED
TABLE 97 AUTOX: NEW PRODUCT DEVELOPMENTS
TABLE 98 AUTOX: DEALS
TABLE 99 AUTOX: OTHERS
14.1.3 CRUISE AUTOMATION
TABLE 100 CRUISE AUTOMATION: BUSINESS OVERVIEW
TABLE 101 CRUISE AUTOMATION: PRODUCTS OFFERED
TABLE 102 CRUISE AUTOMATION: NEW PRODUCT DEVELOPMENTS
TABLE 103 CRUISE AUTOMATION: DEALS
14.1.4 BAIDU
TABLE 104 BAIDU: BUSINESS OVERVIEW
FIGURE 63 BAIDU: COMPANY SNAPSHOT
TABLE 105 BAIDU: PRODUCTS OFFERED
TABLE 106 BAIDU: NEW PRODUCT DEVELOPMENTS
14.1.5 TESLA
TABLE 107 TESLA: BUSINESS OVERVIEW
FIGURE 64 TESLA: COMPANY SNAPSHOT
TABLE 108 TESLA: PRODUCTS OFFERED
TABLE 109 TESLA: NEW PRODUCT DEVELOPMENTS
TABLE 110 TESLA: DEALS
TABLE 111 TESLA: OTHERS
14.1.6 ARGO AI
TABLE 112 ARGO AI: BUSINESS OVERVIEW
TABLE 113 ARGO AI: PRODUCTS OFFERED
TABLE 114 ARGO AI: NEW PRODUCT DEVELOPMENTS
TABLE 115 ARGO AI: DEALS
14.1.7 PONY.AI
TABLE 116 PONY.AI: BUSINESS OVERVIEW
TABLE 117 PONY.AI: PRODUCTS OFFERED
TABLE 118 PONY.AI: NEW PRODUCT DEVELOPMENTS
TABLE 119 PONY.AI: DEALS
14.1.8 EASYMILE
TABLE 120 EASYMILE: BUSINESS OVERVIEW
TABLE 121 EASYMILE: PRODUCTS OFFERED
TABLE 122 EASYMILE: NEW PRODUCT DEVELOPMENTS
TABLE 123 EASYMILE: DEALS
TABLE 124 EASYMILE: OTHERS
14.1.9 DIDI CHUXING
TABLE 125 DIDI CHUXING: BUSINESS OVERVIEW
TABLE 126 DIDI CHUXING: PRODUCTS OFFERED
TABLE 127 DIDI CHUXING: NEW PRODUCT DEVELOPMENTS
TABLE 128 DIDI CHUXING: DEALS
14.1.10 NAVYA
TABLE 129 NAVYA: BUSINESS OVERVIEW
TABLE 130 NAVYA: PRODUCTS OFFERED
TABLE 131 NAVYA: DEALS
14.1.11 LOCAL MOTORS
TABLE 132 LOCAL MOTORS: BUSINESS OVERVIEW
TABLE 133 LOCAL MOTORS: PRODUCTS OFFERED
TABLE 134 LOCAL MOTORS: DEALS
14.1.12 2GETTHERE (ZF)
TABLE 135 2GETTHERE: BUSINESS OVERVIEW
TABLE 136 2GETTHERE: PRODUCTS OFFERED
TABLE 137 2GETTHERE: DEALS
14.2 OTHER KEY PLAYERS
14.2.1 NISSAN
TABLE 138 NISSAN: BUSINESS OVERVIEW
14.2.2 MOBILEYE (INTEL)
TABLE 139 MOBILEYE: BUSINESS OVERVIEW
14.2.3 NVIDIA
TABLE 140 NVIDIA: BUSINESS OVERVIEW
14.2.4 WOVEN PLANET (LYFT)
TABLE 141 WOVEN PLANET: BUSINESS OVERVIEW
14.2.5 APTIV
TABLE 142 APTIV: BUSINESS OVERVIEW
14.2.6 ZF FRIEDRICHSHAFEN
TABLE 143 ZF FRIEDRICHSHAFEN: BUSINESS OVERVIEW
14.2.7 DRIVE.AI (APPLE)
TABLE 144 DRIVE.AI: BUSINESS OVERVIEW
14.2.8 MAY MOBILITY
TABLE 145 MAY MOBILITY: BUSINESS OVERVIEW
14.2.9 OPTIMUS RIDE
TABLE 146 OPTIMUS RIDE: BUSINESS OVERVIEW
14.2.10 YANDEX
TABLE 147 YANDEX: BUSINESS OVERVIEW
14.2.11 AURORA INNOVATION
TABLE 148 AURORA: BUSINESS OVERVIEW
14.2.12 QUALCOMM
TABLE 149 QUALCOMM: BUSINESS OVERVIEW
14.2.13 LUMINAR
TABLE 150 LUMINAR: BUSINESS OVERVIEW
14.2.14 LEDDARTECH
TABLE 151 LEDDARTECH: BUSINESS OVERVIEW
14.2.15 ARBE ROBOTICS
TABLE 152 ARBE ROBOTICS: BUSINESS OVERVIEW
14.2.16 MOTIONAL
TABLE 153 MOTIONAL: BUSINESS OVERVIEW
14.2.17 ZOOX
TABLE 154 ZOOX: BUSINESS OVERVIEW
14.2.18 NURO
TABLE 155 NURO: BUSINESS OVERVIEW
14.2.19 WERIDE
TABLE 156 WERIDE: BUSINESS OVERVIEW
14.2.20 ROBOSENSE
TABLE 157 ROBOSENSE: BUSINESS OVERVIEW
14.2.21 INNOVIZ
TABLE 158 INNOVIZ: BUSINESS OVERVIEW
14.2.22 OCULII
TABLE 159 OCULII: BUSINESS OVERVIEW
*Details on Business overview, Recent developments, MNM view, Key strengths/Right to win, Strategic choices made, and Weaknesses and competitive threats might not be captured in case of unlisted companies.
15 RECOMMENDATIONS BY MARKETSANDMARKETS (Page No. - 185)
15.1 ASIA PACIFIC EXPECTED TO BE A MAJOR MARKET
15.2 GOODS TRANSPORT: KEY FOCUS AREA
15.3 GROWING PUBLIC TRANSPORT REQUIREMENTS
15.4 CONCLUSION
16 APPENDIX (Page No. - 187)
16.1 KEY INSIGHTS OF INDUSTRY EXPERTS
16.2 DISCUSSION GUIDE
16.3 KNOWLEDGE STORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL
16.4 AVAILABLE CUSTOMIZATIONS
16.5 RELATED REPORTS
16.6 AUTHOR DETAILS
The study involved 4 major activities in estimating the current size of the robotaxi market. Exhaustive secondary research was done to collect information on the market, the peer market, and the parent market. The next step was to validate these findings, assumptions, and sizing with the industry experts across value chains through primary research. The top-down approach was employed to estimate the complete market size. Thereafter, market breakdown and data triangulation were used in estimating the market size of segments and subsegments.
Secondary Research
In the secondary research process, various secondary sources such as company annual reports/presentations, press releases, industry association publications [for example, publications of automobile OEMs, American Automobile Association (AAA), country-level automotive associations and European Alternative Fuels Observatory (EAFO)], automobile magazines, articles, directories, technical handbooks, World Economic Outlook, trade websites, technical articles, and databases (for example, Marklines, and Factiva) have been used to identify and collect information useful for an extensive commercial study of the global robotaxi market.
Primary Research
Extensive primary research has been conducted after acquiring an understanding of the Robotaxi market scenario through secondary research. Several primary interviews have been conducted with market experts from both the demand-side [robotaxi operators (in terms of services, country-level government associations, and trade associations)] and supply-side (OEMs and component manufacturers) across 4 major regions, namely, North America, Europe, Asia Pacific, and the Rest of the World. Approximately 14% and 86% of primary interviews have been conducted from the demand- and supply-side, respectively. Primary data has been collected through questionnaires, emails, and telephonic interviews. In the canvassing of primaries, we have strived to cover various departments within organizations, such as sales, operations, and administration, to provide a holistic viewpoint in our report.
After interacting with industry experts, we have also conducted brief sessions with highly experienced independent consultants to reinforce the findings from our primaries. This, along with the in-house subject-matter experts’ opinions, has led us to the findings as described in the remainder of this report. Following is the breakdown of primary respondents
To know about the assumptions considered for the study, download the pdf brochure
Market Size Estimation
The bottom-up approach was used to estimate and validate the total size of the robotaxi market. These methods were also used extensively to estimate the size of various subsegments in the market. The research methodology used to estimate the market size includes the following:
- The key players in the industry and markets have been identified through extensive secondary research.
- The industry’s supply chain and market size, in terms of volume, have been determined through primary and secondary research processes.
- All percentage shares, splits, and breakdowns have been determined using secondary sources and verified through primary sources.
Data Triangulation
After arriving at the overall market size—using the market size estimation processes as explained above—the market was split into several segments and subsegments. To complete the overall market engineering process and arrive at the exact statistics of each market segment and subsegment, data triangulation, and market breakdown procedures were employed, wherever applicable. The data was triangulated by studying various factors and trends from both the demand and supply sides.
Report Objectives
- To segment and forecast the robotaxi market, in terms of volume (units)
- To define, describe, and forecast the market based on vehicle type, propulsion type, automation level, type of application, service type, and region
- To analyze the regional markets for growth trends, prospects, and their contribution to the overall market
- To segment and forecast the market, by application (passenger transportation and goods transportation)
- To segment and forecast the market, by service type (car rental and station-based)
- To segment and forecast the market, by propulsion (electric and fuel cell)
- To segment the market providing qualitative data on the basis of component (camera, LiDAR, radar, and ultra-sonic sensors)
- To segment and forecast the market, by level of autonomy (level 4 and level 5)
- To segment and forecast the market, by vehicle (car and van/shuttle)
- To forecast the market with respect to the key regions, namely, North America, Europe, Asia Pacific, and Rest of the World
- To provide detailed information regarding the major factors influencing the market growth (drivers, restraints, opportunities, and challenges)
- To strategically analyze markets with respect to individual growth trends, future prospects, and contribution to the total market
- To analyze opportunities for stakeholders and details of the competitive landscape for market leaders
- To strategically profile key players and comprehensively analyze their respective market share and core competencies
- To analyze recent developments, alliances, joint ventures, product innovations, and mergers & acquisitions in the market
Available Customizations
With the given market data, MarketsandMarkets offers customizations in accordance to the company’s specific needs.
- Robotaxi Market, by vehicle at country level (for countries not covered in the report)
- Robotaxi Market, by application at country level (for countries not covered in the report)
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Company Information
- Profiling of Additional Market Players (Up to 5)
Growth opportunities and latent adjacency in Robotaxi Market
What are Robotaxi Market newer business models like sustainable and profitable revenue streams in the future?