Digital Transformation in the Shipping Industry: A Network-Based Bibliometric Analysis
This paper presents a network-based bibliometric analysis of digital transformation in the shipping industry, a sector undergoing rapid change due to advancements in automation, artificial intelligence, blockchain, and Internet of Things. The study synthesizes existing knowledge to identify trends,...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-04-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/13/5/894 |
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| author | Luca Ferrarini Yannes Filippopoulos Zoran Lajic |
| author_facet | Luca Ferrarini Yannes Filippopoulos Zoran Lajic |
| author_sort | Luca Ferrarini |
| collection | DOAJ |
| description | This paper presents a network-based bibliometric analysis of digital transformation in the shipping industry, a sector undergoing rapid change due to advancements in automation, artificial intelligence, blockchain, and Internet of Things. The study synthesizes existing knowledge to identify trends, challenges, and opportunities for industry stakeholders and researchers. Unlike previous literature reviews, this work adopts a graph theory approach applied to a large dataset of scientific publications, without predefined technological or industrial sub-domains. Data were collected from EBSCO, ProQuest, and IEEE eXplore, then refined using OpenAlex to comprise 2293 scientific publications. The analysis includes descriptive statistics, co-authorship network analysis, co-citation network analysis, and thematic analysis. The findings reveal a significant increase in publications since 2005, with exponential growth after 2015. They also suggest a potential inflection point after 2024. A small percentage of authors and institutions account for a disproportionate share of publications, suggesting a skewed distribution of research efforts and encouraging funding agencies to broaden maritime research worldwide. The co-authorship network exhibits a heavy-tail distribution and interconnected communities, indicating extensive national and international collaborations. The co-citation analysis identifies key research areas such as fuel consumption optimization, safety and risk management, and smart port development. Thematic analysis highlights the growing importance of artificial intelligence and cybersecurity. |
| format | Article |
| id | doaj-art-8a1479e7edea4b269de3e60948f09e1e |
| institution | DOAJ |
| issn | 2077-1312 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj-art-8a1479e7edea4b269de3e60948f09e1e2025-08-20T03:14:31ZengMDPI AGJournal of Marine Science and Engineering2077-13122025-04-0113589410.3390/jmse13050894Digital Transformation in the Shipping Industry: A Network-Based Bibliometric AnalysisLuca Ferrarini0Yannes Filippopoulos1Zoran Lajic2Department of Information Technologies, University of Limassol, Limassol 3025, CyprusDepartment of Information Technologies, University of Limassol, Limassol 3025, CyprusAngelicoussis Group, Department of Energy Efficiency, 17674 Athens, GreeceThis paper presents a network-based bibliometric analysis of digital transformation in the shipping industry, a sector undergoing rapid change due to advancements in automation, artificial intelligence, blockchain, and Internet of Things. The study synthesizes existing knowledge to identify trends, challenges, and opportunities for industry stakeholders and researchers. Unlike previous literature reviews, this work adopts a graph theory approach applied to a large dataset of scientific publications, without predefined technological or industrial sub-domains. Data were collected from EBSCO, ProQuest, and IEEE eXplore, then refined using OpenAlex to comprise 2293 scientific publications. The analysis includes descriptive statistics, co-authorship network analysis, co-citation network analysis, and thematic analysis. The findings reveal a significant increase in publications since 2005, with exponential growth after 2015. They also suggest a potential inflection point after 2024. A small percentage of authors and institutions account for a disproportionate share of publications, suggesting a skewed distribution of research efforts and encouraging funding agencies to broaden maritime research worldwide. The co-authorship network exhibits a heavy-tail distribution and interconnected communities, indicating extensive national and international collaborations. The co-citation analysis identifies key research areas such as fuel consumption optimization, safety and risk management, and smart port development. Thematic analysis highlights the growing importance of artificial intelligence and cybersecurity.https://www.mdpi.com/2077-1312/13/5/894digital transformationshipping industrymaritime industrybibliometric analysisnetwork theory |
| spellingShingle | Luca Ferrarini Yannes Filippopoulos Zoran Lajic Digital Transformation in the Shipping Industry: A Network-Based Bibliometric Analysis Journal of Marine Science and Engineering digital transformation shipping industry maritime industry bibliometric analysis network theory |
| title | Digital Transformation in the Shipping Industry: A Network-Based Bibliometric Analysis |
| title_full | Digital Transformation in the Shipping Industry: A Network-Based Bibliometric Analysis |
| title_fullStr | Digital Transformation in the Shipping Industry: A Network-Based Bibliometric Analysis |
| title_full_unstemmed | Digital Transformation in the Shipping Industry: A Network-Based Bibliometric Analysis |
| title_short | Digital Transformation in the Shipping Industry: A Network-Based Bibliometric Analysis |
| title_sort | digital transformation in the shipping industry a network based bibliometric analysis |
| topic | digital transformation shipping industry maritime industry bibliometric analysis network theory |
| url | https://www.mdpi.com/2077-1312/13/5/894 |
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