earticle

영어

After the 4th industrial revolution, smart logistics has become a hot issue, and scholars in logistics, engineering, transportation, and management are all being led by these changes. There have been an increasing number of studies on smart logistics in recent years, but the research fields of smart logistics are extensive, and it is not easy to distinguish the correlation between research directions and industries. Furthermore, smart logistics is a complex issue, and research on research trends is lacking. Therefore, to fill this research gap, this study aims to identify smart logistics research trends based on text mining and network analysis techniques using various software such as R, UCINET, and Power BI under the background of big data. Using these big data techniques, it is possible to grasp and analyze smart logistics research trends more objectively and generally. In addition, it is expected to be a good reference for future research.