Research Methodology on AI in Transportation Market
Introduction
This research methodology is an extensive and detailed description of the research approach and methodology for the market research report “AI in Transportation Market by Offering (Hardware, Software, and Services), Technology (Machine Learning, Computer Vision, NLP, and Others), Mode of Transport (Road, Rail, Air, Water, and Others), and Region – Forecast to 2030”, published by Market Research Future (MRFR). The research methodology explains in detail various processes, procedures, and approaches that were followed by researchers in order to generate accurate findings for the report.
The AI in Transportation Market is expected to report a strong growth rate during the forecast period (2023-2030). The study evaluates the current market size of the AI in Transportation Market from 2023 to 2030. AI-based technologies have revolutionized multiple aspects of transportation and are anticipated to experience significant growth in the Global AI in Transportation Market during the forecast period.
Research Design
The primary objective of this research report was to assess the current and estimated market outlook of the AI in Transportation Market over the forecast period of 2023 to 2030. In order to achieve this objective, the following research structures were designed and adopted.
In order to generate the primary data, both primary and secondary sources were used. The primary sources used in the research include industry experts from various AI in Transportation companies, telephonic interviews with CEOs, CFOs, and other sales and marketing executives; while the secondary sources include directories, industry journals, magazines, and a variety of databases.
Research Methodology
The research methodology followed for this project was based on both qualitative and quantitative methods. The first stage of the research approach included secondary research, market analysis and cross-validation of the data based on the secondary research findings. Secondary research provided a good understanding of the market, which helped to devise the primary research approach.
The primary research involved interactions with industry experts, such as C-level executives (CEO, CFO, sales, etc.), OEMs, vendors, and resellers. The primary research process was further divided into the following sub-processes:
• Exploratory research
This research methodology was used to get a better understanding of the AI in Transportation Market dynamics, competitive landscape and trends, and growth opportunities. The opinion of industry professionals was collected through various resources such as industry websites, white papers, journals, magazines, and company presentations.
• Descriptive research
This research methodology was used to determine the market size and market share of the AI in Transportation Market. Descriptive research also helped in segmentation of the market and identification of the opportunities.
• Causal research
This research methodology was used to establish the cause-effect relationship of the AI in Transportation market and to identify the areas of improvement for market players.
Data collection
The data gathered through both primary and secondary sources was collected and organized for analysis. Data was collected through industry experts, company executives, and opinion leaders in the form of quantitative data. The secondary sources used for data collection and validation included industry journals, directories, newspapers, and company annual reports.
Data analysis
The data collected was then analyzed in order to identify patterns and trends in the AI in Transportation market. The data was analyzed using various tools such as SWOT analysis, Porter’s Five Forces analysis, and S.P.A.C.E. Analysis. These tools helped in understanding the market scenario.
Model Build-Up
A regression model was built to calculate the market size, which formed the basis of the market estimations. The model was developed using the data collected from both primary and secondary sources. The model allowed for an estimation of the market size for various segments and sub-segments and to analyze the growth scenarios.
Conclusion
The research methodology detailed in the above report was designed to provide comprehensive coverage of the AI in Transportation Market. The research methodology employed a plethora of research activities to determine the current and future status of the market. In order to obtain accurate and reliable data, detailed primary and secondary research activities were conducted. The approach adopted ensured that the data gathered covered all aspects of the AI in Transportation market, thereby providing a comprehensive market estimate.
