Paper
22 December 2021 Risk assessment of port infrastructure under public-private partnership: case of Ningbo Zhenhai Harbor District
Tingliu Xu, Yingjie Xiao, Qin Lin
Author Affiliations +
Proceedings Volume 12058, Fifth International Conference on Traffic Engineering and Transportation System (ICTETS 2021); 120580W (2021) https://doi.org/10.1117/12.2620253
Event: 5th International Conference on Traffic Engineering and Transportation System (ICTETS 2021), 2021, Chongqing, China
Abstract
This paper firstly identified the risk factors of the port infrastructure investment environment under the background of PPP (public-private partnership), and constructed the first-level index risk evaluation index system. The weight of the indicators was then determined using the Delphi method, and the indicators were graded according to questionnaires and generally accepted rules for ranking. Finally, taking the infrastructure project of Zhenhai Harbor District in Ningbo as the research object, the risk evaluation model of port infrastructure investment is established by the method of expert investigation and the fuzzy comprehensive evaluation. The results showed that the overall risk of the infrastructure project of Zhenhai Harbor District in Ningbo is moderate, and among all the first-class index risk factors, the operational risk and master/marine pilot’s risky behaviour are high risks, effective control should be given first; of all the secondary indicator risk factors, the division of rights and responsibilities between the two sides is the riskiest. Under the mode of public-private partnership, the risky factors in the process of port construction and operation should be monitored in real-time, and effective risk control measures should be taken.
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Tingliu Xu, Yingjie Xiao, and Qin Lin "Risk assessment of port infrastructure under public-private partnership: case of Ningbo Zhenhai Harbor District", Proc. SPIE 12058, Fifth International Conference on Traffic Engineering and Transportation System (ICTETS 2021), 120580W (22 December 2021); https://doi.org/10.1117/12.2620253
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KEYWORDS
Navigation systems

Collision avoidance

Data modeling

Fuzzy logic

Meteorology

Safety

Legal

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