Developing a Model to Analyze the Impact of Automation and Artificial Intelligence on Freight Transportation Using the Content Analysis Method

This research aimed to examine and develop a model to analyse the impact of automation and artificial intelligence on cargo transportation using the Content Analysis method in the year 1403 (2024). The statistical population of the study consisted of all experts in the field of artificial intelligence in cargo transportation. The sampling was purposive, and snowball sampling was conducted, resulting in seven interviews being collected. The validity and reliability of the interviews were confirmed by experts' opinions and the Holsti coefficient. Thematic analysis and identification of blocks, main contents, and sub contents were used to address the research objectives. In the analysis phase using MAXQDA2020 software, considering that the selected method for analysis was the theme, pervasive contents, organizing contents, and basic contents were taken into account by creating a confrontation between experts' opinions and the topics expressed in their group opinions. The results indicated the identification of six blocks: autonomous systems (with five main contents and 17 sub contents), data prediction, analysis, and optimization (with five main contents and 21 sub contents), progress in robotics (with five main contents and 14 sub contents), traffic planning (with five main contents and 19 sub contents), safety improvement (with four main contents and 10 sub contents), and environmental compatibility (with five main contents and 15 sub contents).