The Application of Artificial Intelligence Technology in Shipping: A Bibliometric Review

Abstract

Artificial intelligence (AI) technologies are increasingly being applied to the shipping industry to advance its development. In this study, 476 articles published in the Science Citation Index Expanded (SCI-EXPANDED) and the Social Sciences Citation Index (SSCI) of the Web of Science Core Collection from 2001 to 2022 were collected, and bibliometric methods were applied to conduct a systematic literature of the field of AI technology applications in the shipping industry. The review commences with an annual publication trend analysis, which shows that research in the field has been growing rapidly in recent years. This is followed by a statistical analysis of journals and a collaborative network analysis to identify the most productive journals, countries, institutions, and authors. The keyword “co-occurrence analysis” is then utilized to identify major research clusters, as well as hot research directions in the field, providing directions for future research in the field. Finally, based on the results of the keyword co-occurrence analysis and the content analysis of the papers published in recent years, the research gaps in AIS data applications, ship trajectory, and anomaly detection, as well as the possible future research directions, are discussed. The findings indicate that AIS data in the future research direction are mainly reflected in the analysis of ship behavior and AIS data repair. Ship trajectory in the future research direction is mainly reflected in the deep learning-based method research and the discussion of ship trajectory classification. Anomaly detection in the future research direction is mainly reflected in the application of deep learning technology in ship anomaly detection and improving the efficiency of ship anomaly detection. These insights offer guidance for researchers’ future investigations in this area. In addition, we discuss the implications of research in the field of shipping AI from both theoretical and practical perspectives. Overall, this review can help researchers understand the status and development trend of the application field of AI technology in shipping, correctly grasp the research direction and methodology, and promote the further development of the field.

Short Sea Shipping as a Sustainable Modal Alternative: Qualitative and Quantitative Perspectives

“…The Government of China has placed regulations reducing sulfur emissions related to vessels in ports on the Yangtze River that could be applied in a Hudson River scenario [38], where similar studies have focused on the use of environmentally friendly ships to reduce control sulfur emissions, and government policies driving their adoption will further add to the sustainable benefits of marine transportation [39]. Current research has also pointed to the use of artificial intelligence (AI) technology in shipping data processing and analysis to increase efficiency and economic benefits in shipping [40]. Yet, little empirical research has been conducted with shippers and receivers to understand better the perceived barriers and opportunities associated with a mode shift to SSS.…”

Constructing and implementing a green taxation system in China under the dual-carbon target

“…These taxes are levied on the purchase, sale, use, and road use of motor vehicles and ships. For instance, how to prevent the pollution from ships have become an important issue in China (Xiao et al, 2024a;Xu et al, 2024a;2024c). The Dutch government has introduced special taxes on motor vehicles in order to reduce the pollution of the environment by motor vehicle emissions.…”

Research Trends in Artificial Intelligence and Security—Bibliometric Analysis

“…The number of papers by country provides an insight into the activities of the research community around the world. China and the United States of America stand out as leaders in the number of papers [41], which is probably the result of their large population, wealth of resources, high investment in science and technology, and developed research infrastructure. Great Britain also has a significant amount of research, which may be the result of a rich scientific tradition, with renowned universities and institutions.…”