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    Artificial intelligence in port environmental management: A strategic analysis
    (ORDU ÜNİVERSİTESİ, 2025) Önal, Esma; Toygar, Arda; Tehci, Ali
    Maritime activities play a crucial role in global trade. However, seaports cause various environmental problems, particularly pollution in coastal and urban areas. Artificial intelligence (AI) and its subfields, machine learning and deep learning have emerged as promising tools for addressing these problems, garnering increasing interest within the maritime sector. Nevertheless, existing studies in literature often focus on a limited scope and fail to incorporate environmental priorities in seaport operations. This study explored the potential of AI and its subfields to enhance resilience to environmental problems posed by operational activities in seaports. Ten port environmental priorities from the ESPO’s report were included as environmental indicators. The study was conducted in two phases. The first phase involved a systematic literature review of 117 sources from the Web of Science and Scopus databases. In line with the systematic analysis, the second phase was evaluated using a SWOT analysis. Thereafter, a series of strategic recommendations were formulated on the based on an analysis of both internal and external factors. The study provided twelve strategic recommendations for enhancing current practices. AI and its subfields has the potential to become a strategic tool for achieving seaport sustainability goals that align with environmental priorities.