Author
Listed:
- Tifang Li
(College of Naval Architecture and Shipping, Guangdong Ocean University, Zhanjiang 524088, China
These authors contributed equally to this work.)
- Zihao Weng
(College of Naval Architecture and Shipping, Guangdong Ocean University, Zhanjiang 524088, China
These authors contributed equally to this work.)
- Jin Yan
(College of Naval Architecture and Shipping, Guangdong Ocean University, Zhanjiang 524088, China
Guangdong Provincial Key Laboratory of Intelligent Equipment for South China Sea Marine Ranching, Zhanjiang 524088, China)
- Lijun Wang
(College of Naval Architecture and Shipping, Guangdong Ocean University, Zhanjiang 524088, China
Guangdong Provincial Key Laboratory of Intelligent Equipment for South China Sea Marine Ranching, Zhanjiang 524088, China)
- Ronghui Li
(College of Naval Architecture and Shipping, Guangdong Ocean University, Zhanjiang 524088, China
Guangdong Provincial Key Laboratory of Intelligent Equipment for South China Sea Marine Ranching, Zhanjiang 524088, China)
- Wei Wang
(College of Naval Architecture and Shipping, Guangdong Ocean University, Zhanjiang 524088, China
Guangdong Provincial Key Laboratory of Intelligent Equipment for South China Sea Marine Ranching, Zhanjiang 524088, China)
Abstract
Identifying and optimizing core factor configurations for anchorage operational safety under typhoon scenarios is critical to enhancing anchorage operational resilience and sustainable port development. This study develops a complementary hybrid SEM–fsQCA framework: key factors are identified via literature review and expert interviews; SEM quantifies factor correlations and contribution weights and corrects expert-evaluated anchorage capacity; six core factors are extracted, three typhoon types (heavy-rainfall, strong-wind, complex-track) are defined, and a coupled anchorage–typhoon case dataset is constructed. Subsequently, fsQCA performs necessary condition analysis and identifies causal configurations driving safety effectiveness. Based on these configurations, we establish a dynamic three-tier risk classification framework for refined anchorage management. Validated using 36 coupled cases (12 anchorages × 3 typhoon types) from Huizhou Port, a core hub in the Guangdong–Hong Kong–Macao Greater Bay Area, this framework enables adaptive vessel traffic scheduling throughout the entire typhoon cycle through dynamic tiered management. The proposed “identification-intervention-feedback” closed-loop governance model delivers theoretical rigor and operational implementation ability for coastal port typhoon risk mitigation.
Suggested Citation
Tifang Li & Zihao Weng & Jin Yan & Lijun Wang & Ronghui Li & Wei Wang, 2026.
"Optimizing Anchorage Safety Under Typhoons: Key Factor Identification and Dynamic Tiered Management via SEM–fsQCA Hybrid Modeling,"
Sustainability, MDPI, vol. 18(10), pages 1-26, May.
Handle:
RePEc:gam:jsusta:v:18:y:2026:i:10:p:5068-:d:1945486
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