Artificial Intelligence in Port Logistics: A Bibliometric Analysis of Technological Integration and Research Dynamics

Abstract : The paper explores the transformation of port logistics operations with artificial intelligence (AI) during the port transformation into a smart port. The research integrates capabilities-based resource analysis and dynamic capabilities with sociotechnical implementations of technologies and resilience approaches of complex systems under disruptions. The system applies robustdata infrastructures (AIS/IoT streams and data quality and interoperability) to propel analytical and AI modules (forecasting and optimization and anomaly detection) that become effective once integrated with sufficient governance systems and trained personnel and operational processes to transform planning and safety and sustainability operations. It applies Scopus bibliometric research to analyze 123 articles using a systematic approach with both a search protocol and a document screening and duplication verification. It incorporates annual behavior and distribution of author and country performance analysis with science mapping techniques that explore keyword relation and co-citation and bibliographic coupling and conceptual structuring tools that construct thematic maps and multiple correspondence analysis with community detection while applying explicit thresholding and robust tests. The research connects AI applications to smart port domains through specific data-to-impact pathways while providing a method for bibliometric analysis that enables future updates. The research presents a step-by-step approach for data readiness followed by predictive and optimization implementation and organizational integration. The paper supports public policy through recommendations for data sharing standards and complete environmental benefit assessments. The research proposes a future study plan whichcombines field-based testing with multiple port assessments to enhance both cause-effect understanding and research applicability. Keywords: Artificial Intelligence, Bibliometric, Port, Logistics, Classification JEL:O33 Paper type:Theoretical Research

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-10-08
DOI
https://doi.org/10.5281/zenodo.17290869
Primary Topic
Nitric Oxide and Endothelin Effects
Type
article
Field-Weighted Citation Impact
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article

Artificial Intelligence in Port Logistics: A Bibliometric Analysis of Technological Integration and Research Dynamics

Zenodo (CERN European Organization for Nuclear Research)
Nitric Oxide and Endothelin Effects
article

Artificial Intelligence in Port Logistics: A Bibliometric Analysis of Technological Integration and Research Dynamics

article en

Abstract

Abstract : The paper explores the transformation of port logistics operations with artificial intelligence (AI) during the port transformation into a smart port. The research integrates capabilities-based resource analysis and dynamic capabilities with sociotechnical implementations of technologies and resilience approaches of complex systems under disruptions. The system applies robustdata infrastructures (AIS/IoT streams and data quality and interoperability) to propel analytical and AI modules (forecasting and optimization and anomaly detection) that become effective once integrated with sufficient governance systems and trained personnel and operational processes to transform planning and safety and sustainability operations. It applies Scopus bibliometric research to analyze 123 articles using a systematic approach with both a search protocol and a document screening and duplication verification. It incorporates annual behavior and distribution of author and country performance analysis with science mapping techniques that explore keyword relation and co-citation and bibliographic coupling and conceptual structuring tools that construct thematic maps and multiple correspondence analysis with community detection while applying explicit thresholding and robust tests. The research connects AI applications to smart port domains through specific data-to-impact pathways while providing a method for bibliometric analysis that enables future updates. The research presents a step-by-step approach for data readiness followed by predictive and optimization implementation and organizational integration. The paper supports public policy through recommendations for data sharing standards and complete environmental benefit assessments. The research proposes a future study plan whichcombines field-based testing with multiple port assessments to enhance both cause-effect understanding and research applicability. Keywords: Artificial Intelligence, Bibliometric, Port, Logistics, Classification JEL:O33 Paper type:Theoretical Research

Zenodo (CERN European Organization for Nuclear Research)
Digital Science (United States) (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 41%
Nitric Oxide and Endothelin Effects
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