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Marine piracy prediction and prevention: Policy implications


Jin, M and Shi, W and Lin, K-C and Li, KX, Marine piracy prediction and prevention: Policy implications, Marine Policy, 108 Article 103528. ISSN 0308-597X (2019) [Refereed Article]

Copyright Statement

2019 Elsevier Ltd. All rights reserved.

DOI: doi:10.1016/j.marpol.2019.103528


Marine piracy has traditionally been a serious threat to marine security, highlighting the great significance of piracy risk assessment and prevention to the marine industry and global economy. This study uses data on piracy attacks between 1994 and 2017 to estimate the probability of a vessel being attacked by pirates and the success rate of piracy attacks. The results of the employed binary logistic regression model show that small vessels and open registry vessels are more likely to be targeted by pirates. Further, the probability of successful boarding by pirates is higher for a vessel at berth or anchor, at night, in territorial waters and port areas, and in South America, the South China Sea, and the Strait of Malacca. Moreover, the rate of successful boarding will decreases from 99.42% to 86.71% if crews take passive measures and decreases further to 9.39% if crews take active measures. These results can not only be used by stakeholders to estimate the likelihood of piracy incidents, but can also provide information on how and the extent to which the identified factors influence piracy, helping marine stakeholders take appropriate anti-piracy measures. Moreover, these results can also be used for crew training and education to counter pirates as well as to help insurance companies set a premium rate for the different risk levels calculated by the model.

Item Details

Item Type:Refereed Article
Keywords:piracy risk, piracy prediction, piracy prevention, shipping safety, policy
Research Division:Commerce, Management, Tourism and Services
Research Group:Other commerce, management, tourism and services
Research Field:Other commerce, management, tourism and services not elsewhere classified
Objective Division:Economic Framework
Objective Group:Microeconomics
Objective Field:Industry policy
UTAS Author:Shi, W (Dr Wenming Shi)
ID Code:133004
Year Published:2019
Web of Science® Times Cited:3
Deposited By:Maritime and Logistics Management
Deposited On:2019-05-31
Last Modified:2020-04-29

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