Strategizing Artificial Intelligence Transformation in Smart Ports: Lessons from Busan’s Resilient AI Governance Model
The global port and maritime industry is experiencing a new paradigm shift known as the artificial intelligence transformation (AX). Thus, domestic container-terminal companies should focus beyond mere automation to a paradigm shift in AI that encompasses operational strategy, organizational structu...
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| Format: | Article |
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MDPI AG
2025-06-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/13/7/1276 |
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| author | Jeong-min Lee Min-seop Sim Yul-seong Kim Ha-ram Lim Chang-hee Lee |
| author_facet | Jeong-min Lee Min-seop Sim Yul-seong Kim Ha-ram Lim Chang-hee Lee |
| author_sort | Jeong-min Lee |
| collection | DOAJ |
| description | The global port and maritime industry is experiencing a new paradigm shift known as the artificial intelligence transformation (AX). Thus, domestic container-terminal companies should focus beyond mere automation to a paradigm shift in AI that encompasses operational strategy, organizational structure, system, and human resource management. This study proposes a resilience-based AX strategy and implementation system that allows domestic container-terminal companies to proactively respond to the upcoming changes in the global supply chain, thus securing sustainable competitiveness. In particular, we aim to design an AI-based governance model to establish a trust-based logistics supply chain (trust value chain). As a research method, the core risk factors of AX processes were scientifically identified via text-mining and fault-tree analysis, and a step-by-step execution strategy was established by applying a backcasting technique based on scenario planning. Additionally, by integrating social control theory with new governance theory, we designed a flexible, adaptable, and resilience-oriented AI governance system. The results of this study suggest that the AI paradigm shift should be promoted by enhancing the risk resilience, trust, and recovery of organizations. By suggesting AX strategies and policy as well as institutional improvement directions that embed resilience to secure the sustainable competitiveness of AI-based smart ports in Korea, this study serves as a basis for establishing strategies for the domestic container-terminal industry and for constructing a global leading model. |
| format | Article |
| id | doaj-art-0f4faab70dfb418f971a79f4da9a0b7b |
| institution | Matheson Library |
| issn | 2077-1312 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj-art-0f4faab70dfb418f971a79f4da9a0b7b2025-07-25T13:26:57ZengMDPI AGJournal of Marine Science and Engineering2077-13122025-06-01137127610.3390/jmse13071276Strategizing Artificial Intelligence Transformation in Smart Ports: Lessons from Busan’s Resilient AI Governance ModelJeong-min Lee0Min-seop Sim1Yul-seong Kim2Ha-ram Lim3Chang-hee Lee4Department of Convergence Interdisciplinary Education of Maritime & Ocean Contents (Logistics System), National Korea Maritime and Ocean University, Busan 49112, Republic of KoreaDepartment of Convergence Interdisciplinary Education of Maritime & Ocean Contents (Logistics System), National Korea Maritime and Ocean University, Busan 49112, Republic of KoreaDepartment of Logistics, College of Engineering, National Korea Maritime and Ocean University, Busan 49112, Republic of KoreaDepartment of AI & Cyber Security, National Korea Maritime and Ocean University, Busan 49112, Republic of KoreaDivision of Navigation Convergence Studies, College of Maritime Sciences, National Korea Maritime and Ocean University, Busan 49112, Republic of KoreaThe global port and maritime industry is experiencing a new paradigm shift known as the artificial intelligence transformation (AX). Thus, domestic container-terminal companies should focus beyond mere automation to a paradigm shift in AI that encompasses operational strategy, organizational structure, system, and human resource management. This study proposes a resilience-based AX strategy and implementation system that allows domestic container-terminal companies to proactively respond to the upcoming changes in the global supply chain, thus securing sustainable competitiveness. In particular, we aim to design an AI-based governance model to establish a trust-based logistics supply chain (trust value chain). As a research method, the core risk factors of AX processes were scientifically identified via text-mining and fault-tree analysis, and a step-by-step execution strategy was established by applying a backcasting technique based on scenario planning. Additionally, by integrating social control theory with new governance theory, we designed a flexible, adaptable, and resilience-oriented AI governance system. The results of this study suggest that the AI paradigm shift should be promoted by enhancing the risk resilience, trust, and recovery of organizations. By suggesting AX strategies and policy as well as institutional improvement directions that embed resilience to secure the sustainable competitiveness of AI-based smart ports in Korea, this study serves as a basis for establishing strategies for the domestic container-terminal industry and for constructing a global leading model.https://www.mdpi.com/2077-1312/13/7/1276artificial-intelligence transformationresiliencetrust value chainbackcastingfault-tree analysissocial control theory |
| spellingShingle | Jeong-min Lee Min-seop Sim Yul-seong Kim Ha-ram Lim Chang-hee Lee Strategizing Artificial Intelligence Transformation in Smart Ports: Lessons from Busan’s Resilient AI Governance Model Journal of Marine Science and Engineering artificial-intelligence transformation resilience trust value chain backcasting fault-tree analysis social control theory |
| title | Strategizing Artificial Intelligence Transformation in Smart Ports: Lessons from Busan’s Resilient AI Governance Model |
| title_full | Strategizing Artificial Intelligence Transformation in Smart Ports: Lessons from Busan’s Resilient AI Governance Model |
| title_fullStr | Strategizing Artificial Intelligence Transformation in Smart Ports: Lessons from Busan’s Resilient AI Governance Model |
| title_full_unstemmed | Strategizing Artificial Intelligence Transformation in Smart Ports: Lessons from Busan’s Resilient AI Governance Model |
| title_short | Strategizing Artificial Intelligence Transformation in Smart Ports: Lessons from Busan’s Resilient AI Governance Model |
| title_sort | strategizing artificial intelligence transformation in smart ports lessons from busan s resilient ai governance model |
| topic | artificial-intelligence transformation resilience trust value chain backcasting fault-tree analysis social control theory |
| url | https://www.mdpi.com/2077-1312/13/7/1276 |
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