Intelligent Maritime Shipping: A Bibliometric Analysis of Internet Technologies and Automated Port Infrastructure Applications
Amid the dual imperatives of global trade expansion and low-carbon transition, intelligent maritime shipping has emerged as a central driver for the innovation of international logistics systems, now entering a critical window period for the deep integration of Internet technologies and automated po...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Journal of Marine Science and Engineering |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2077-1312/13/5/979 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849327239832797184 |
|---|---|
| author | Yangqiong Zou Guangnian Xiao Qingjun Li Salvatore Antonio Biancardo |
| author_facet | Yangqiong Zou Guangnian Xiao Qingjun Li Salvatore Antonio Biancardo |
| author_sort | Yangqiong Zou |
| collection | DOAJ |
| description | Amid the dual imperatives of global trade expansion and low-carbon transition, intelligent maritime shipping has emerged as a central driver for the innovation of international logistics systems, now entering a critical window period for the deep integration of Internet technologies and automated port infrastructure. While existing research predominantly focuses on isolated applications of intelligent technologies, systematic evaluations of the synergistic effects of technological integration on maritime ecosystems, policy compatibility, and contributions to global carbon emission governance remain under-explored. Leveraging bibliometric analysis, this study systematically examines 488 publications from the Web of Science (WoS) Core Collection (2000–2024), yielding three pivotal findings: firstly, China dominates the research landscape, with a 38.5% contribution share, where Artificial Intelligence (AI), the Internet of Things (IoT), and port automation constitute the technological pillars. However, critical gaps persist in cross-system protocol standardization and climate-adaptive modeling, accounting for only 2.7% and 4.2% of the literature, respectively. Secondly, international collaboration networks exhibit pronounced “Islamization”, characterized by an inter-team collaboration rate of 17.3%, while the misalignment between rapid technological iteration and existing maritime regulations exacerbates industry risks. Thirdly, a dual-track pathway integrating Cyber–Physical System (CPS)-based digital twin ports and open-source vertical domain-specific large language models is proposed. Empirical evidence demonstrates its efficacy in reducing cargo-handling energy consumption by 15% and decision-making latency by 40%. This research proposes a novel tripartite framework, encompassing technological, institutional, and data sovereignty dimensions, to resolve critical challenges in integrating multi-source maritime data and managing cross-border governance. The model provides academically validated and industry-compatible strategies for advancing sustainable maritime intelligence. Subsequent investigations should expand data sources to include regional repositories and integrate interdisciplinary approaches, ensuring the adaptability of both technical systems and international policy coordination mechanisms across diverse maritime ecosystems. |
| format | Article |
| id | doaj-art-4cb410049b3444c19c3e52cc413f702c |
| institution | Kabale University |
| issn | 2077-1312 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj-art-4cb410049b3444c19c3e52cc413f702c2025-08-20T03:47:57ZengMDPI AGJournal of Marine Science and Engineering2077-13122025-05-0113597910.3390/jmse13050979Intelligent Maritime Shipping: A Bibliometric Analysis of Internet Technologies and Automated Port Infrastructure ApplicationsYangqiong Zou0Guangnian Xiao1Qingjun Li2Salvatore Antonio Biancardo3School of Economics & Management, Shanghai Maritime University, Shanghai 201306, ChinaSchool of Economics & Management, Shanghai Maritime University, Shanghai 201306, ChinaSchool of Economics & Management, Weifang University, Weifang 261061, ChinaSchool of Polytechnic & Basic Science, University of Naples Federico II, 80125 Naples, ItalyAmid the dual imperatives of global trade expansion and low-carbon transition, intelligent maritime shipping has emerged as a central driver for the innovation of international logistics systems, now entering a critical window period for the deep integration of Internet technologies and automated port infrastructure. While existing research predominantly focuses on isolated applications of intelligent technologies, systematic evaluations of the synergistic effects of technological integration on maritime ecosystems, policy compatibility, and contributions to global carbon emission governance remain under-explored. Leveraging bibliometric analysis, this study systematically examines 488 publications from the Web of Science (WoS) Core Collection (2000–2024), yielding three pivotal findings: firstly, China dominates the research landscape, with a 38.5% contribution share, where Artificial Intelligence (AI), the Internet of Things (IoT), and port automation constitute the technological pillars. However, critical gaps persist in cross-system protocol standardization and climate-adaptive modeling, accounting for only 2.7% and 4.2% of the literature, respectively. Secondly, international collaboration networks exhibit pronounced “Islamization”, characterized by an inter-team collaboration rate of 17.3%, while the misalignment between rapid technological iteration and existing maritime regulations exacerbates industry risks. Thirdly, a dual-track pathway integrating Cyber–Physical System (CPS)-based digital twin ports and open-source vertical domain-specific large language models is proposed. Empirical evidence demonstrates its efficacy in reducing cargo-handling energy consumption by 15% and decision-making latency by 40%. This research proposes a novel tripartite framework, encompassing technological, institutional, and data sovereignty dimensions, to resolve critical challenges in integrating multi-source maritime data and managing cross-border governance. The model provides academically validated and industry-compatible strategies for advancing sustainable maritime intelligence. Subsequent investigations should expand data sources to include regional repositories and integrate interdisciplinary approaches, ensuring the adaptability of both technical systems and international policy coordination mechanisms across diverse maritime ecosystems.https://www.mdpi.com/2077-1312/13/5/979intelligent maritime shippingbibliometric analysisInternetAI large modelport automation |
| spellingShingle | Yangqiong Zou Guangnian Xiao Qingjun Li Salvatore Antonio Biancardo Intelligent Maritime Shipping: A Bibliometric Analysis of Internet Technologies and Automated Port Infrastructure Applications Journal of Marine Science and Engineering intelligent maritime shipping bibliometric analysis Internet AI large model port automation |
| title | Intelligent Maritime Shipping: A Bibliometric Analysis of Internet Technologies and Automated Port Infrastructure Applications |
| title_full | Intelligent Maritime Shipping: A Bibliometric Analysis of Internet Technologies and Automated Port Infrastructure Applications |
| title_fullStr | Intelligent Maritime Shipping: A Bibliometric Analysis of Internet Technologies and Automated Port Infrastructure Applications |
| title_full_unstemmed | Intelligent Maritime Shipping: A Bibliometric Analysis of Internet Technologies and Automated Port Infrastructure Applications |
| title_short | Intelligent Maritime Shipping: A Bibliometric Analysis of Internet Technologies and Automated Port Infrastructure Applications |
| title_sort | intelligent maritime shipping a bibliometric analysis of internet technologies and automated port infrastructure applications |
| topic | intelligent maritime shipping bibliometric analysis Internet AI large model port automation |
| url | https://www.mdpi.com/2077-1312/13/5/979 |
| work_keys_str_mv | AT yangqiongzou intelligentmaritimeshippingabibliometricanalysisofinternettechnologiesandautomatedportinfrastructureapplications AT guangnianxiao intelligentmaritimeshippingabibliometricanalysisofinternettechnologiesandautomatedportinfrastructureapplications AT qingjunli intelligentmaritimeshippingabibliometricanalysisofinternettechnologiesandautomatedportinfrastructureapplications AT salvatoreantoniobiancardo intelligentmaritimeshippingabibliometricanalysisofinternettechnologiesandautomatedportinfrastructureapplications |