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Global New Energy Vehicle (NEV) Taxi Market to reach USD XXX Billion by the end of 2029.

Global New Energy Vehicle (NEV) Taxi Market Size study & Forecast, by Vehicle Type (Passenger Cars and Commercial Vehicles) by Type (Battery Electric Vehicles, Hybrid Vehicles, Plug-in Hybrid Electric Vehicles) and Regional Analysis, 2022-2029

Product Code: ALTST-61364678
Publish Date: 2-05-2023
Page: 200

Global New Energy Vehicle (NEV) Taxi Market is valued at approximately USD XX Billion in 2021 and is anticipated to grow with a healthy growth rate of more than XX% over the forecast period 2022-2029. NEV taxis are new energy vehicles, such as battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs), that is partially or entirely powered by electricity. Battery Electric Vehicles (BEVs), commonly known as EVs, are entirely electric vehicles with rechargeable batteries and no gasoline engine. BEVs are zero-emission vehicles since they produce no harmful exhaust emissions or air pollution hazards as typical gasoline-powered vehicles do. Plug-in Hybrid Electric Vehicles (PHEVs) are operated by both an engine and an electric motor. These can recharge their batteries through regenerative braking, just the same as regular hybrids. The NEV Taxi Market is expanding because of factors such as increasing electric vehicle demand and the rising adoption of Advanced Driver Assistance Systems (ADAS) are driving the market demand across the world.

According to the International Energy Agency (IEA), more than 2.1 million electric vehicles were sold in 2019, accounting for around 2.6% of total vehicle sales worldwide. Similarly, they accounted for around 1% of global automobile stock in 2019, marking a 40% increase over 2018. According to the road safety report provided by the World Health Organization in 2018, the global road death toll has reached 1.35 million. Furthermore, in response to growing worries about passenger safety, governments in emerging nations have imposed strict safety standards on automakers to build vehicles with ADAS functions. Also, to stimulate demand for NEV vehicles, governments in several countries are investing in charging infrastructure to offer customers with sufficient charging stations as well as tax incentives or perks for their smooth operation and to reduce rising air pollution which will provide lucrative growth opportunities for the market during the forecast period. However, inadequate internet connectivity hampers market growth during the forecast period of 2022-2029.

The key regions considered for the Global New Energy Vehicle (NEV) Taxi Market study includes Asia Pacific, North America, Europe, Latin America, and Rest of the World. Asia Pacific dominated the market in terms of revenue. The key emerging markets for automotive and technologically advanced automotive components include India, South Korea, and China. The rising incidence of traffic accidents, rising consumer disposable income, and rising vehicular pollution are important drivers of growth in this region. North America is expected to grow as the fastest growing region during the forecast period, owing to factors such as the government’s various development programs and the rise of key companies in this region.

Major market player included in this report are:
Tesla Inc., (California, United States)
BYD (Shenzhen, China)
Anhui Jianghuai Automobile Co Ltd (JAC) (Hefei, China)
Uber Technologies (California, United States)
Daimler AG (Stuttgart, Germany)
Beijing Automotive Industry Holding Co. Ltd. (BAIC) (Beijing, China)
Lyft Inc., (California, United States)
Baidu (Beijing, China)
Didi Chuxing (Beijing, China)
Amazon (Washington, United States)

Recent Developments in the Market:
Ø In May 2019, Chinese manufacturer BYD partnered with ENSA Servicios and Traservi to launch the first fleet of fully electric vehicles in Panama and Central America. These 3 companies also launched the first fast-charging station for electric vehicles in Colon Province, with the goal of laying a solid platform for boosting electric transportation throughout Panama.
Ø In November 2020, DiDi Chuxing launched the D1 electric vehicle for ride-sharing services. Didi built D1 with the assistance of the world’s largest EV manufacturer, BYD. The company intends to deploy its car in Changsha, Hunan province, to increase its share of the mobility market from 3% to 30% by 2030.

Global New Energy Vehicle (NEV) Taxi Market Report Scope:
Historical Data 2019-2020-2021
Base Year for Estimation 2021
Forecast period 2022-2029
Report Coverage Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
Segments Covered Vehicle Type, Type, Region
Regional Scope North America; Europe; Asia Pacific; Latin America; Rest of the World
Customization Scope Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:
By Vehicle Type:
Passenger Cars
Commercial Vehicles

By Type:
Battery Electric Vehicles
Hybrid Vehicles
Plug-in Hybrid Electric Vehicles

By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE
Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
Rest of the World

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2019-2029 (USD Billion)
1.2.1. New Energy Vehicle (NEV) Taxi Market, by Region, 2019-2029 (USD Billion)
1.2.2. New Energy Vehicle (NEV) Taxi Market, by Vehicle Type, 2019-2029 (USD Billion)
1.2.3. New Energy Vehicle (NEV) Taxi Market, by Type, 2019-2029 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global New Energy Vehicle (NEV) Taxi Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global New Energy Vehicle (NEV) Taxi Market Dynamics
3.1. New Energy Vehicle (NEV) Taxi Market Impact Analysis (2019-2029)
3.1.1. Market Drivers
3.1.1.1. Increasing electric vehicle demand
3.1.1.2. Rising Adoption of Advanced Driver Assistance System (ADAS)
3.1.2. Market Challenges
3.1.2.1. Inadequate internet connectivity
3.1.3. Market Opportunities
3.1.3.1. Rising pollution and fuel prices
3.1.3.2. Growing Government Initiatives and Investment

Chapter 4. Global New Energy Vehicle (NEV) Taxi Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Futuristic Approach to Porter’s 5 Force Model (2019-2029)
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.4. Investment Adoption Model
4.5. Analyst Recommendation & Conclusion
4.6. Top investment opportunity
4.7. Top winning strategies
Chapter 5. Risk Assessment: COVID-19 Impact
5.1. Assessment of the overall impact of COVID-19 on the industry
5.2. Pre COVID-19 and post COVID-19 Market scenario
Chapter 6. Global New Energy Vehicle (NEV) Taxi Market, by Vehicle Type
6.1. Market Snapshot
6.2. Global New Energy Vehicle (NEV) Taxi Market by Vehicle Type, Performance – Potential Analysis
6.3. Global New Energy Vehicle (NEV) Taxi Market Estimates & Forecasts by Vehicle Type 2019-2029 (USD Billion)
6.4. New Energy Vehicle (NEV) Taxi Market, Sub Segment Analysis
6.4.1. Passenger Cars
6.4.2. Commercial Vehicles
Chapter 7. Global New Energy Vehicle (NEV) Taxi Market, by Type
7.1. Market Snapshot
7.2. Global New Energy Vehicle (NEV) Taxi Market by Type, Performance – Potential Analysis
7.3. Global New Energy Vehicle (NEV) Taxi Market Estimates & Forecasts by Type 2019-2029 (USD Billion)
7.4. New Energy Vehicle (NEV) Taxi Market, Sub Segment Analysis
7.4.1. Battery Electric Vehicles
7.4.2. Hybrid Vehicles
7.4.3. Plug-in Hybrid Electric Vehicles
Global New Energy Vehicle (NEV) Taxi Market, Regional Analysis
7.5. New Energy Vehicle (NEV) Taxi Market, Regional Market Snapshot
7.6. North America New Energy Vehicle (NEV) Taxi Market
7.6.1. U.S. New Energy Vehicle (NEV) Taxi Market
7.6.1.1. Vehicle Typebreakdown estimates & forecasts, 2019-2029
7.6.1.2. Type breakdown estimates & forecasts, 2019-2029
7.6.2. Canada New Energy Vehicle (NEV) Taxi Market
7.7. Europe New Energy Vehicle (NEV) Taxi Market Snapshot
7.7.1. U.K. New Energy Vehicle (NEV) Taxi Market
7.7.2. Germany New Energy Vehicle (NEV) Taxi Market
7.7.3. France New Energy Vehicle (NEV) Taxi Market
7.7.4. Spain New Energy Vehicle (NEV) Taxi Market
7.7.5. Italy New Energy Vehicle (NEV) Taxi Market
7.7.6. Rest of Europe New Energy Vehicle (NEV) Taxi Market
7.8. Asia-Pacific New Energy Vehicle (NEV) Taxi Market Snapshot
7.8.1. China New Energy Vehicle (NEV) Taxi Market
7.8.2. India New Energy Vehicle (NEV) Taxi Market
7.8.3. Japan New Energy Vehicle (NEV) Taxi Market
7.8.4. Australia New Energy Vehicle (NEV) Taxi Market
7.8.5. South Korea New Energy Vehicle (NEV) Taxi Market
7.8.6. Rest of Asia Pacific New Energy Vehicle (NEV) Taxi Market
7.9. Latin America New Energy Vehicle (NEV) Taxi Market Snapshot
7.9.1. Brazil New Energy Vehicle (NEV) Taxi Market
7.9.2. Mexico New Energy Vehicle (NEV) Taxi Market
7.10. Rest of The World New Energy Vehicle (NEV) Taxi Market

Chapter 8. Competitive Intelligence
8.1. Top Market Strategies
8.2. Company Profiles
8.2.1. Tesla Inc., (California, United States)
8.2.1.1. Key Information
8.2.1.2. Overview
8.2.1.3. Financial (Subject to Data Availability)
8.2.1.4. Product Summary
8.2.1.5. Recent Developments
8.2.2. BYD (Shenzhen, China)
8.2.3. Anhui Jianghuai Automobile Co Ltd (JAC) (Hefei, China)
8.2.4. Uber Technologies (California, United States)
8.2.5. Daimler AG (Stuttgart, Germany)
8.2.6. Beijing Automotive Industry Holding Co. Ltd. (BAIC) (Beijing, China)
8.2.7. Lyft Inc., (California, United States)
8.2.8. Baidu (Beijing, China)
8.2.9. Didi Chuxing (Beijing, China)
8.2.10. Amazon (Washington, United States)
Chapter 9. Research Process
9.1. Research Process
9.1.1. Data Mining
9.1.2. Analysis
9.1.3. Market Estimation
9.1.4. Validation
9.1.5. Publishing
9.2. Research Attributes
9.3. Research Assumption

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Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
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Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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