In this study, a network was mapped using the VOSviewer program for cluster analysis using the keyword network matrix for each period considered in the centrality analysis. To maintain the same analysis conditions for each period (2005–2009–2014, and 2015–2019), the resolution was set to 0.8, the minimum cluster size was set to 5 as a clustering analysis option, and the average number of keywords used for mapping was limited to approximately 200.
As shown in
Fig 6, the network map of the first period (2005–2009) revealed seven clusters. RFID, which exhibited high centrality, was located at the center of the network map and formed a cluster with Green logistics, Port logistics, Mobile, Simulation, and Monitoring. Communication-related technology fields such as Ubiquitous, Sensor network, Wibro (Wireless broadband) and Logistics were the next major clusters. In the aforementioned period, the government strongly emphasized fostering the ICT field. In particular, government expenditure in Ubiquitous and Wibro-related technologies increased, and this trend is believed to have significantly affected logistics R&D. In addition, other focus areas were a cluster representing the field of international and maritime logistics, including Container, Transportation, Terminal, ERP, and International logistics, and another cluster related to transport management systems such as Standard, Traceability, and Visibility. As depicted in the network map (
Fig. 7) of logistics R&D conducted between 2010 and 2014, seven clusters were obtained. Logistics and RFID, both of which exhibit high degree centrality and betweenness centrality, were located at the center of the network map, and each was clustered as an important research field. Specifically, Logistics formed an eco-friendly logistics-related cluster with keywords such as Green SCM, Risk management, and Eco-friendly, whereas RFID formed a logistics and communication cluster with Antenna, Computing, Mobile, and Network. In addition, cold-chain clusters, such as Cold chain, Substitution system, and Package, and smart logistics clusters, such as IoT, Big data, Cloud, and Data gathering, had newly emerged. This indicates that domestic logistics R&D was evolving from the existing conventional logistics field to a more advanced type of logistics. Furthermore, the network map for 2015–2019 revealed eight clusters, as shown in
Fig. 8. This network map is significantly different from that obtained for the logistics R&D conducted in the previous 10 years. Specifically, intelligent and digitizing technologies such as IoT, Big data, Platform, and AI emerged as key research areas in this period. First, clusters related to unmanned logistics, such as Robot, Unmanned aerial vehicle (UAV), and Autonomous, indicated the major research fields, while those related to logistics digitalization, such as Big Data, Simulation, and Process mining, were also present. In addition, clusters related to logistics intelligence such as AI and Cloud were located on one side. Moreover, logistics safety-related clusters, such as Security and Safety, and logistics standard-related clusters for systematization of logistics systems, such as International standard, Technical management, and System integration, had emerged. In particular, technology-related clusters, such as Platform and Export, were also being proposed to promote logistics sharing.