The maritime economy, a cornerstone of global trade and economic development, is undergoing rapid transformation driven by technological advancements, sustainability challenges, and evolving regulatory frameworks. This study systematically organizes and analyses 827 scientific articles from the Web of Science, employing a hybrid methodology integrating Social Network Analysis (SNA), the Binary Space Partitioning (BSP) clustering algorithm, and large language models (LLMs) to identify key research themes and emerging trends. Through an iterative "human-in-the-loop" process, we refine the clustering process, resulting in six main clusters and 26 subclusters spanning topics such as governance and strategic management, forecasting and modelling, port operations, digital innovations, sustainability, and risk management. The results reveal a marked shift toward sustainability-oriented and technology-driven research, emphasizing the convergence of environmental responsibility, digital transformation, and operational resilience. The findings also highlight the growing role of autonomous technologies, big data analytics, and blockchain in reshaping maritime systems, while underscoring the need for adaptive governance frameworks and cross-sectoral collaboration. By offering a structured, data-driven overview of the maritime research ecosystem, this study contributes a novel methodological framework for bibliometric exploration and provides actionable insights for scholars, policymakers, and industry stakeholders seeking to advance innovation and sustainability in the maritime domain.
Cisic et al. (Thu,) studied this question.