Understanding the root causes of maritime accidents has always been a complex task, but a recent systematic review of the Human Factors Analysis and Classification System (HFACS) offers a clearer path forward. Our view is that this research marks a necessary maturation of the field, moving beyond simple classification toward integrated, data-driven analysis, a shift that aligns with the kind of empirical rigor our readers expect. By synthesizing 65 unique studies from Web of Science and Scopus, the review confirms that HFACS is no longer a static checklist; it is being adapted with probabilistic, system-oriented, and data-driven methods to address the specific realities of maritime operations. This evolution is critical because human error is not a single variable, it is a cascade of organizational, operational, and environmental factors that demand a calibrated response.
The geographic concentration of this research in China and Türkiye is a telling signal. These nations, both with significant shipping and fishing industries, are investing in measurable frameworks to prevent accidents before they happen. This mirrors the kind of validated progress we have seen in other domains, such as the measured progress: Indonesia's extreme poverty reduction mirrors China's rapid gains we recently examined. In both cases, targeted, empirical approaches yield results that are replicable and scalable. The review's finding that the ten most-cited studies identify causal factors at multiple HFACS levels, and propose mitigation measures addressing both operational and organizational issues, demonstrates that the maritime sector is finally treating accidents as system failures, not isolated mistakes. This is a direct contrast to the one-dimensional safety narratives that have dominated for decades.
For practitioners and policymakers, the practical takeaway is clear: the future of maritime safety lies in combining established classification frameworks with real-time data and system-oriented models. The review shows that the most impactful studies are those that integrate HFACS with probabilistic risk models and longitudinal data, not those that merely label incidents. This is a call to move from retrospective reporting to predictive prevention. The citation-network analysis reveals that while the structures of Web of Science and Scopus differ, the influential authors and keywords are consistent, suggesting a converging consensus on what matters. As we consider the broader implications, it is worth asking how these adapted frameworks might be applied to other complex systems, such as the quantifying human factors in vessel loss-of-control risk models we have covered. The challenge now is to ensure that these academic insights translate into operational protocols, especially as autonomous vessels and AI-assisted navigation become more common. The open question remains: can the industry implement these integrated, evidence-based measures at a pace that matches the urgency of ocean stewardship?