An Analysis of Smart Logistics Trend using LDA Topic Modeling

This study aims to identify smart logistics trends and find actual and potential problems and issues in smart logistics by focusing on the cases of representative e-commerce companies in the United States, China, and Korea. To this end, 3,402 papers published between January 2001 and February 2024 were collected from Scopus, and word frequency, TF-IDF, and LDA topic modeling analyses were performed using Python 3. As a result of the study, five topics related to the current trends and issues in smart logistics were derived. They are “untact service for customer convenience”, “IoT-based technology”, “development of optimal logistics routes”, “technology used for last-mile delivery”, and “technology used for intelligent warehouses”. The practical contribution of this study is to provide smart logistics insights based on the cases of three representative e-commerce companies in the United States, China, and Korea to other companies so that they can implement new smart logistics systems or improve existing systems. In particular, it suggests future research directions such as improving the technology used in storage and internal logistics, optimizing the last-mile delivery method, and developing non-face-to-face services for consumer convenience. In this respect, this study fills the research gap in the literature and provides academic contributions.