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Abstract

Marine accidents would not only cause considerable loss of human life and property, but also seriously affect the safety of navigation environments. Effective security management could guarantee the prevention of marine accidents. By analysing the systematic patterns of Changjiang Maritime Safety Administration (MSA) of the People’s Republic of China, this study constructed a suitable navigation security assessment model for evaluating security management performance. Our dataset was derived from the official website of Changjiang MSA, which is composed of seven MSA branches, in terms of Chongqing, Yichang, Yueyang, Wuhan, Huangshi, Anqing and Wuhu, respectively. The main research data component was focussed on marine accidents that have occurred in the Changjiang River, covering six varieties of marine accident without explicit input (WEI) variables. Data envelopment analysis (DEA) is a mathematical method for measuring the relative efficiencies of peer decision-making units (DMUs) with multiple inputs and outputs. A DEA-WEI model was implemented and applied to the evaluation in this study. According to the evaluation, we identified collision and foundering-based accidents to be the two most common varieties of marine accidents in the Changjiang River. We also observed higher safety performance in the MSAs controlling the upper and middle reaches of the Changjiang River, especially the Chongqing and Yueyang MSAs, than in those controlling the lower reaches. Therefore, Chongqing and Yueyang could be adopted as references for improving the overall security management performance in the Changjiang River area.

Item Type:	Article
Authors/Creators:	Gan, G-Y and Lee, H-S and Chung, C-C and Chen, S-L
Keywords:	security management, Changjiang MSA, without explicit input (WEI), undesirable output
Journal or Publication Title:	Journal of Marine Science and Technology
Publisher:	National Taiwan Ocean University
ISSN:	1023-2796
DOI / ID Number:	https://doi.org/10.6119/JMST-016-1207-1
Copyright Information:	Copyright 2017 Journal of Marine Science and Technology
Related URLs:	Google Scholar: Chen, S-L UTAS Profile: Chen, S-L
Item Statistics:	View statistics for this item

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