An advanced risk analysis approach for container port safety evaluation

Alyami, Hani; Lee, Paul Tae–Woo; Yang, Zaili; Riahi, Ramin; Bonsall, Stephen; Wang, Jin

doi:10.1080/03088839.2014.960498

Cited by 91 publications

(91 citation statements)

References 40 publications

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“…The total magnitude of the influence of a combination of attributing factors is always greater than those of one factor [49]. Table 7 shows scenarios of combined variations for crashes on curves; situations that cause a high probability of fatal/incapacitating injury should be highlighted when driving.…”

Section: Sensitivity Analysismentioning

confidence: 99%

Analysis of Accident Severity for Curved Roadways Based on Bayesian Networks

Zhu

Zhang

et al. 2019

Sustainability

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Crashes that occur on curved roadways are often more severe than straight road accidents. Previously, most studies focused on the associations between curved sections and roadway geometric characteristics. In this study, significant factors such as driver behavior, roadway features, vehicle factors, and environmental characteristics are identified and involved in analyzing traffic accident severity. Bayesian network analysis was conducted to deal with data, to explore the associations between variables, and to make predictions using these relationships. The results indicated that factors including point of impact, site of location, accident side of road, alcohol/drugs condition, etc., are relatively critical in crashes on horizontal curves. Accident severity increases when crashes occur on bridges. The sensitivity of accident severity to vehicle use, traffic control, point of impact, and alcohol/drugs condition is relatively high. Moreover, a combination of negative factors will aggravate accident severities. The results also proposed some suggestions regarding the design of vehicles, as well as the construction and improvement of curved roadways.

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Section: Sensitivity Analysismentioning

confidence: 99%

Analysis of Accident Severity for Curved Roadways Based on Bayesian Networks

Zhu

Zhang

et al. 2019

Sustainability

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“…Since cargo will be loaded into containers, transported long distances, and then unloaded at the container terminal; keeping the cargo intact is a key requirement for all customers (UNCTAD, 1992;Murphy, Daley and Hall, 1997;Hsu, 2013). If a port has a bad reputation with cargo handling safety, potential clients will be driven away and the confidence of existing clients will be influenced (Alyami et al, 2014).…”

Section: Safetymentioning

confidence: 99%

Port sustainable services innovation: Ningbo port users’ expectation

Wang

Subramanian

Abdulrahman

et al. 2017

Sustainable Production and Consumption

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Port sustainable services innovation depends on understanding and matching customers' expectations with unique service offerings using advanced facilities. This study develops and validates a port sustainable services decision model to investigate customers' port services expectations based on the views of companies and freight services providers located in major cities nearby Ningbo port. Thus, the study will enable better understanding of the port's impact on sustainability of the economic and social prosperity of its immediate environment stakeholders by balancing three major aspects such as services, costs and facilities. The study employed a multi-criteria decision-making methodology Analytical Hierarchy Process (AHP) to analyze the model. The resultsshow that while different port users have different views and expectations, port infrastructure improvement, cargo safety, and reductions in port charges are critical to attract businesses. Port-dependent companies that were investigated also cite reduced paper work and optimized e-business as well as reduced transport congestion as key areas for improvements. This study provides port administrators with insights on how to effectively improve business attractiveness for greater sustainability and competitive advantages with rival ports within the same geographical proximity. In addition it also suggests how to design cost-effective ways of meeting and even surpassing users' expectations.

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“…, THEN SE is D1 with a belief degree of β 1 k, D2 with a belief degree of β 2 k, D3 with a belief degree of β 3 k and D4 with a belief degree of β 4 k.…”

Section: Analysis Of Security Risks Of Independent Components In Marimentioning

confidence: 99%

Quantitative maritime security assessment: a 2020 vision

Yang

2016

IMA J Management Math

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Maritime security assessment is moving toward a proactive risk-based regime. This opens the way for security analysts and managers to explore and exploit flexible and advanced risk modelling and decision making approaches in maritime transport. In this article, following a review of maritime security risk assessment, a generic quantitative security assessment methodology is developed. Novel mathematical models for security risk analysis and management are outlined and integrated together to demonstrate their use in the developed framework. Such approaches may be used to facilitate security risk modelling and decision making in situations where conventional quantitative risk analysis techniques cannot be appropriately applied. Finally, recommendations on further exploitation of advances in risk and uncertainty modelling technology are suggested with respect to maritime security risk quantification and management.

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An advanced risk analysis approach for container port safety evaluation

Cited by 91 publications

References 40 publications

Analysis of Accident Severity for Curved Roadways Based on Bayesian Networks

Analysis of Accident Severity for Curved Roadways Based on Bayesian Networks

Port sustainable services innovation: Ningbo port users’ expectation

Quantitative maritime security assessment: a 2020 vision

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