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Global Automotive 3PL Market to reach USD XX billion by 2028.

Global Automotive 3PL Market Size study, by Type (Finished Vehicle, Auto Component, Other types), by Service (Transportation, Warehousing, Distribution, and Inventory Management and Other Services) and Regional Forecasts 2022-2028

Product Code: ALTL-78608021
Publish Date: 10-05-2022
Page: 200

Global Automotive 3PL 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 2022-2028. Third-party logistics companies provide services such as inventory management, door-to-door delivery, product packaging and others to automobile and automobile component manufacturers and purchasers. Reduction in inventory and supply chain cost, growing sales of automobiles and strategic initiatives by market players are the factors fueling demand in the market. According to the International Organization of Motor Vehicle Manufacturers, commercial vehicle sales in Europe surged from 2.78 million units in 2018 to 2.83 million units in 2019. Also in Japan, commercial vehicle sales swelled from 880 thousand in 2018 to 894 thousand in 2019. Additionally, in October 2020, DSV partnered with Verity to deploy an autonomous drone system in its warehouses for inventory management. These drones can scan barcodes without the requirement of humans as well as capable of detecting empty or occupied pellet positions. Furthermore, growing number of warehouses and technological advancements are expected to further inject growth in the market during the forecast period. However, stringent regulations associated with shipping and high costs required for specialized equipment can hamper the growth in the near future.

The geographical regions considered for the global Automotive 3PL market analysis include Asia Pacific, North America, Europe, Latin America and Rest of the World. North America is deemed as a significant region in terms of revenue owing to the presence of prominent market players and enhanced shipping services. Whereas, Asia Pacific is expected to grow with a significant growth rate in coming years, due to the rapidly growing automotive sector and growing trans-regional trade corridors.

Major market players included in this report are:
DB Schenker
CEVA Logistics
Kuehne+Nagel
Expeditors International
XPO Logistics, Inc.
Deutsche Post AG
SINOTRANS Limited
C.H. Robinson Worldwide, Inc.
Ryder System, Inc.
Schnellecke group ag & co. Kg

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 eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available 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 Type:
Finished Vehicle
Auto Component
Other types
By Service:
Transportation
Warehousing, Distribution, and Inventory Management
Other Services
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

Furthermore, years considered for the study are as follows:

Historical year – 2018, 2019, 2020
Base year – 2021
Forecast period – 2022 to 2028

Target Audience of the Global Automotive 3PL Market in Market Study:

Key Consulting Companies & Advisors
Large, medium-sized, and small enterprises
Venture capitalists
Value-Added Resellers (VARs)
Third-party knowledge providers
Investment bankers
Investors

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2028 (USD Billion)
1.2.1. Automotive 3PL Market, by Region, 2020-2028 (USD Billion)
1.2.2. Automotive 3PL Market, by Type, 2020-2028 (USD Billion)
1.2.3. Automotive 3PL Market, by Service, 2020-2028 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Automotive 3PL 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 Automotive 3PL Market Dynamics
3.1. Automotive 3PL Market Impact Analysis (2020-2028)
3.1.1. Market Drivers
3.1.1.1. Reduction in inventory and supply chain cost
3.1.1.2. Growing sales of automobiles
3.1.2. Market Challenges
3.1.2.1. Stringent regulations associated with shipping
3.1.2.2. High cost required for specialized equipment
3.1.3. Market Opportunities
3.1.3.1. Growing number of warehouses
3.1.3.2. Technological advancements
Chapter 4. Global Automotive 3PL 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
4.1.6. Futuristic Approach to Porter’s 5 Force Model (2018-2028)
4.2. PEST Analysis
4.2.1. Political
4.2.2. Economical
4.2.3. Social
4.2.4. Technological
4.3. Investment Adoption Model
4.4. Analyst Recommendation & Conclusion
4.5. Top investment opportunity
4.6. Top winning strategies
Chapter 5. Risk Assessment: COVID-19 Impact
5.1.1. Assessment of the overall impact of COVID-19 on the industry
5.1.2. Pre COVID-19 and post COVID-19 market scenario
Chapter 6. Global Automotive 3PL Market, by Type
6.1. Market Snapshot
6.2. Global Automotive 3PL Market by Type, Performance – Potential Analysis
6.3. Global Automotive 3PL Market Estimates & Forecasts by Type, 2018-2028 (USD Billion)
6.4. Automotive 3PL Market, Sub Segment Analysis
6.4.1. Finished Vehicle
6.4.2. Auto Component
6.4.3. Other types
Chapter 7. Global Automotive 3PL Market, by Service
7.1. Market Snapshot
7.2. Global Automotive 3PL Market by Service, Performance – Potential Analysis
7.3. Global Automotive 3PL Market Estimates & Forecasts by Service, 2018-2028 (USD Billion)
7.4. Automotive 3PL Market, Sub Segment Analysis
7.4.1. Transportation
7.4.2. Warehousing, Distribution, and Inventory Management
7.4.3. Other Services
Chapter 8. Global Automotive 3PL Market, Regional Analysis
8.1. Automotive 3PL Market, Regional Market Snapshot
8.2. North America Automotive 3PL Market
8.2.1. U.S. Automotive 3PL Market
8.2.1.1. Type breakdown estimates & forecasts, 2018-2028
8.2.1.2. Service breakdown estimates & forecasts, 2018-2028
8.2.2. Canada Automotive 3PL Market
8.3. Europe Automotive 3PL Market Snapshot
8.3.1. U.K. Automotive 3PL Market
8.3.2. Germany Automotive 3PL Market
8.3.3. France Automotive 3PL Market
8.3.4. Spain Automotive 3PL Market
8.3.5. Italy Automotive 3PL Market
8.3.6. Rest of Europe Automotive 3PL Market
8.4. Asia-Pacific Automotive 3PL Market Snapshot
8.4.1. China Automotive 3PL Market
8.4.2. India Automotive 3PL Market
8.4.3. Japan Automotive 3PL Market
8.4.4. Australia Automotive 3PL Market
8.4.5. South Korea Automotive 3PL Market
8.4.6. Rest of Asia Pacific Automotive 3PL Market
8.5. Latin America Automotive 3PL Market Snapshot
8.5.1. Brazil Automotive 3PL Market
8.5.2. Mexico Automotive 3PL Market
8.6. Rest of The World Automotive 3PL Market

Chapter 9. Competitive Intelligence
9.1. Top Market Strategies
9.2. Company Profiles
9.2.1. DB Schenker
9.2.1.1. Key Information
9.2.1.2. Overview
9.2.1.3. Financial (Subject to Data Availability)
9.2.1.4. Product Summary
9.2.1.5. Recent Developments
9.2.2. CEVA Logistics
9.2.3. Kuehne+Nagel
9.2.4. Expeditors International
9.2.5. XPO Logistics, Inc.
9.2.6. Deutsche Post AG
9.2.7. SINOTRANS Limited
9.2.8. C.H. Robinson Worldwide, Inc.
9.2.9. Ryder System, Inc.
9.2.10. Schnellecke group ag & co. Kg
Chapter 10. Research Process
10.1. Research Process
10.1.1. Data Mining
10.1.2. Analysis
10.1.3. Market Estimation
10.1.4. Validation
10.1.5. Publishing
10.2. Research Attributes
10.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
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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:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
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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