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Global Transportation Analytics Market to reach USD 30.68 billion by the end of 2029.

Global Transportation Analytics Market Size study & Forecast, by Type (Descriptive, Predictive, Prescriptive), by Deployment (On-premises, Cloud, Hybrid), by Application (Traffic Management, Logistics Management, Planning & Maintenance, Others) and Regional Analysis, 2022-2029

Product Code: ICTICTS-51479405
Publish Date: 10-04-2023
Page: 200

Global Transportation Analytics Market is valued at approximately USD 9.62 billion in 2021 and is anticipated to grow with a healthy growth rate of more than 15.6% over the forecast period 2022-2029. Transportation Analytics deals with the large amount of data that is generated and present in distribution operations. Moreover, organizations can use this data as a guide to get data-based business insights. Additionally, transportation analytics offers useful metrics at every point in the delivery process. It not only helps to identify the company’s weakest and strongest areas, but it also produces reliable deliverables that the company can share with clients. Furthermore, Big data analytics are also widely applied in supply chain management to assess operational risks, enhance communication, secure confidential information, and increase supply chain accessibility. The increasing adoption of Advanced Traffic Management Systems (ATMs) and growing usage of AI and ML technologies are key factors driving the market growth.

Over the years the adoption of artificial intelligence and machine learning technology has significantly increased. For instance – as per Statista – as of 2021, the global artificial intelligence market was valued at USD 34.87 billion, and as per projections, the market is expected to grow to USD 1591 billion by 2030. Also, favorable government initiatives for the development of smart cities and rising expansion of logistics & transportation industry would create a lucrative growth prospectus for the market over the forecast period. However, data security and privacy concerns associated with Transportation Analytics solutions stifle market growth throughout the forecast period of 2022-2029.

The key regions considered for the Global Transportation Analytics Market study include Asia Pacific, North America, Europe, Latin America, and Rest of the World. North America dominated the market in terms of revenue, owing to the presence of leading market players as well as increasing adoption of transportation analytics solutions from leading logistics and transportation companies in the region. Whereas Asia Pacific is expected to grow with the highest CAGR during the forecast period, owing to factors such as rising investment in smart cities and smart transportation as well as growing expansion of logistics and transportation industry in the region.

Major market players included in this report are:
IBM Corporation
Cubic Corporation
Sisense Inc.
Oracle Corporation
Inrix Corporation
Cellint Corporation
Alteryx Inc.
Hitachi Ltd.
SmartDrive Systems Inc.
Omnitracs LLC

Recent Developments in the Market:
 In September 2021, Ontario, Canada based Geotab, one of the leaders in IoT and connected transportation, through its Geotab Intelligent Transportation Systems (ITS) line of business announced the launch of a new transportation analytics platform.

Global Transportation Analytics 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 Type, Deployment, Application, 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 Type

By Deployment

By Application
Traffic Management
Logistics Management
Planning & Maintenance

By Region:
North America
Asia Pacific
South Korea
Latin America
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. Transportation Analytics Market, by Region, 2019-2029 (USD Billion)
1.2.2. Transportation Analytics Market, by Type, 2019-2029 (USD Billion)
1.2.3. Transportation Analytics Market, by Deployment, 2019-2029 (USD Billion)
1.2.4. Transportation Analytics Market, by Application, 2019-2029 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Transportation Analytics 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 Transportation Analytics Market Dynamics
3.1. Transportation Analytics Market Impact Analysis (2019-2029)
3.1.1. Market Drivers Increasing adoption of Advanced Traffic Management System (ATMs) Growing usage of AI and ML technologies
3.1.2. Market Challenges Data security and privacy concerns
3.1.3. Market Opportunities Favourable government initiatives for the development of smart cities Rising expansion of logistics & transportation industry
Chapter 4. Global Transportation Analytics 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. Top investment opportunity
4.5. Top winning strategies
4.6. Industry Experts Prospective
4.7. Analyst Recommendation & Conclusion
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 Transportation Analytics Market, by Type
6.1. Market Snapshot
6.2. Global Transportation Analytics Market by Type, Performance – Potential Analysis
6.3. Global Transportation Analytics Market Estimates & Forecasts by Type 2019-2029 (USD Billion)
6.4. Transportation Analytics Market, Sub Segment Analysis
6.4.1. Descriptive
6.4.2. Predictive
6.4.3. Prescriptive
Chapter 7. Global Transportation Analytics Market, by Deployment
7.1. Market Snapshot
7.2. Global Transportation Analytics Market by Deployment, Performance – Potential Analysis
7.3. Global Transportation Analytics Market Estimates & Forecasts by Deployment 2019-2029 (USD Billion)
7.4. Transportation Analytics Market, Sub Segment Analysis
7.4.1. On-premises
7.4.2. Cloud
7.4.3. Hybrid
Chapter 8. Global Transportation Analytics Market, by Application
8.1. Market Snapshot
8.2. Global Transportation Analytics Market by Application, Performance – Potential Analysis
8.3. Global Transportation Analytics Market Estimates & Forecasts by Application 2019-2029 (USD Billion)
8.4. Transportation Analytics Market, Sub Segment Analysis
8.4.1. Traffic Management
8.4.2. Logistics Management
8.4.3. Planning & Maintenance
8.4.4. Others
Chapter 9. Global Transportation Analytics Market, Regional Analysis
9.1. Transportation Analytics Market, Regional Market Snapshot
9.2. North America Transportation Analytics Market
9.2.1. U.S. Transportation Analytics Market Type breakdown estimates & forecasts, 2019-2029 Deployment breakdown estimates & forecasts, 2019-2029 Application breakdown estimates & forecasts, 2019-2029
9.2.2. Canada Transportation Analytics Market
9.3. Europe Transportation Analytics Market Snapshot
9.3.1. U.K. Transportation Analytics Market
9.3.2. Germany Transportation Analytics Market
9.3.3. France Transportation Analytics Market
9.3.4. Spain Transportation Analytics Market
9.3.5. Italy Transportation Analytics Market
9.3.6. Rest of Europe Transportation Analytics Market
9.4. Asia-Pacific Transportation Analytics Market Snapshot
9.4.1. China Transportation Analytics Market
9.4.2. India Transportation Analytics Market
9.4.3. Japan Transportation Analytics Market
9.4.4. Australia Transportation Analytics Market
9.4.5. South Korea Transportation Analytics Market
9.4.6. Rest of Asia Pacific Transportation Analytics Market
9.5. Latin America Transportation Analytics Market Snapshot
9.5.1. Brazil Transportation Analytics Market
9.5.2. Mexico Transportation Analytics Market
9.5.3. Rest of Latin America Transportation Analytics Market
9.6. Rest of The World Transportation Analytics Market

Chapter 10. Competitive Intelligence
10.1. Top Market Strategies
10.2. Company Profiles
10.2.1. IBM Corporation Key Information Overview Financial (Subject to Data Availability) Product Summary Recent Developments
10.2.2. Cubic Corporation
10.2.3. Sisense Inc.
10.2.4. Oracle Corporation
10.2.5. Inrix Corporation
10.2.6. Cellint Corporation
10.2.7. Alteryx Inc.
10.2.8. Hitachi Ltd.
10.2.9. SmartDrive Systems Inc.
10.2.10. Omnitracs LLC
Chapter 11. Research Process
11.1. Research Process
11.1.1. Data Mining
11.1.2. Analysis
11.1.3. Market Estimation
11.1.4. Validation
11.1.5. Publishing
11.2. Research Attributes
11.3. 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.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
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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