The Human Element in Shipping

Barnett, Michael L.; Pekcan, Claire

doi:10.1002/9781118476406.emoe033

Cited by 13 publications

(9 citation statements)

References 7 publications

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“…Modern shipping companies face a number of problems that need conceptual solutions. Human resources are at the heart of shipping companies' potential, and they are a source of potential risks (Barnett and Pekcan 2017;Ilina, Miloradov and Kovaltchuk 2019). Modern scientists highlight a number of issues associated with human factor (Livingstone, Cahoon, and Fei 2014), namely:…”

Section: Relevance Of the Research Topicmentioning

confidence: 99%

Crewing of Sea Vessels Taking into Account Project Risks and Technical Condition of Ship Equipment

Zakharchenko

Bedrii²,

Bileha

et al. 2020

J. Rev. Global Econ.

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Motivation: One of the main concepts in project management is the concept of "team" in the project, and in project management-the human resources management of the project, which includes the processes of planning, forming and creating a team, its development and support activities, transformation or disbandment of the team. Despite the great attention paid to the formation of project management teams, existing studies do not fully highlight the specifics and features of crew operations. Criteria for the quantitative optimization of the ship's crew should be consistent with the main objectives of the project. Novelty: The research paper proposes an approach that allows optimizing the quantitative composition of the crew of a ship by more accurately assessing the level of project risks and costs associated with the maintenance of ship equipment. The practical application of this approach will optimize the quantitative composition of the ship's crew, which will both satisfy the needs of managing the technical equipment and minimize the risks and costs of the shipowner. Methodology and Methods: Risk management tools were used to achieve the objective and test the hypotheses suggested in the research, namely: methodology for estimating the net present value of the project; the method of estimating internal rate of return for the project; the method of estimating the return on investment in the project; the method of estimation for the period of return on investment costs in the project; the method of estimating the discounted payback period for the project, as well as the tools of simulation modelling (Monte Carlo simulation method). The method of identification and grouping in the process of classification of project risks in the sphere of marine transportation, methods of systematization, grouping and logical generalization were also applied for systematization of information, drawing conclusions and making scientific suggestions in the research.

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Section: Relevance Of the Research Topicmentioning

confidence: 99%

Crewing of Sea Vessels Taking into Account Project Risks and Technical Condition of Ship Equipment

Zakharchenko

Bedrii²,

Bileha

et al. 2020

J. Rev. Global Econ.

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“…e Bayesian Network, namely the reliability network, is an extension of the Bayes method. It was proposed by Judea Pearl in 1986 and is a type of inference-based [17-20, 23, 24, 26, 27] Perceptual errors [17-20, 24, 27] Violations Routine violations [18,20,21,23,25,28] Exceptional violations [18,20,21,24,25,29] Quality and experience of crew…”

Section: Bayesian Networkmentioning

confidence: 99%

“…Post adaptability of crew [19,22,[30][31][32] Situation awareness [18,27] Psychological factor [20,22,24,27,30,33,34] Physiological factor [22,24,27,28,30,33] Technical factor [20,22,25,29,30,33] Experience [19,20,31] Ship factor…”

Section: Bayesian Networkmentioning

confidence: 99%

“…Completeness of maritime management laws and regulations [20,30,31,33] Equipment completeness of maritime monitoring system [25-27, 30, 31] Adequacy of the supervision and management [20,24,30,32] Supervise violations or not [18,20] Internal management network based on probability uncertainty, and variability. It is suitable for expressing and analyzing various uncertainties and probabilistic events.…”

Section: External Supervisionmentioning

confidence: 99%

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Safety Risk Analysis of Unmanned Ships in Inland Rivers Based on a Fuzzy Bayesian Network

Zhang

Yang

et al. 2019

Journal of Advanced Transportation

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Risk factor identification is the basis for risk assessment. To quantify the safety risks of unmanned vessels in inland rivers, through analysis of previous studies, the safety risk impact factor framework of unmanned vessels in inland rivers is established based on three aspects: the ship aspect, the environmental aspect, and the management and control aspect. Relying on Yangtze River, a fuzzy Bayesian network of the sailing safety risk of unmanned ships in inland rivers is constructed. The proposed safety risk model has considered different operational and environmental factors that affect shipping operations. Based on the fuzzy set theory, historical data, and expert judgments and on previous works are used to estimate the base value (prior values) of various risk factors. The case study assessed the safety risk probabilities of unmanned vessels in Yangtze River. By running uncertainty and sensitivity analyses of the model, a significant change in the likelihood of the occurrence of safety risk is identified, and suggests a dominant factor in risk causation. The research results can provide effective information for analyzing the current safety status for navigation systems of unmanned ships in inland rivers. The estimated safety risk provides early warning to take appropriate preventive and mitigative measures to enhance the overall safety of shipping operations.

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“…For the second, it is accepted that, under physical or work‐induced pressures, the projection of events and outcomes in time may not develop as anticipated, since human reasoning is not constantly updated for interpreting and realizing how things would evolve. This reduced situational awareness affects the appropriate management of any course deviation or close encounter, as well as making accurate judgments and actions to prevent hazards (Barnett & Pekcan, ). Because of such discounted predictability and the dynamically changing environmental conditions, the resulting response alternatives and navigation strategies may not be optimal in the entire time interval in which the system operates.…”

Section: Determining the Navigation System's Automatic Interventionmentioning

confidence: 99%

Fuzzy logic system interference in ship accidents

Psarros

2018

Hum Ftrs & Erg Mfg Svc

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Poor lookout, lack of situation awareness, and delayed response have been continuously recognized as contributory causes of navigation accidents (i.e., collisions and groundings). It is claimed that such negative behavioral characteristics can be corrected when the navigation system is equipped with the automation capability to intervene upon their detection. Building on the results of my previous work, this study sets the starting line in exploring this technological innovation under a conceptual framework, where it is attempted to employ simple, quantifiable, and measurable ways to assess the deck officer's (navigator's) complex aspect of mental task reliability. To deal with this challenge, the navigator's behavior when performing navigation tasks is described by the Markov method and the uncertainty, ambiguity, and weakness in perceiving accurately the environment and traffic conditions is determined by fuzzy logic. The proposed concept is demonstrated through its practical application in collision and grounding accidents, where it is argued that further research is required for its validation. K E Y W O R D Sautomation, cognitive/mental performance reliability, fuzzy logic, human factors, maritime accidents, Markov method

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The Human Element in Shipping

Cited by 13 publications

References 7 publications

Crewing of Sea Vessels Taking into Account Project Risks and Technical Condition of Ship Equipment

Crewing of Sea Vessels Taking into Account Project Risks and Technical Condition of Ship Equipment

Safety Risk Analysis of Unmanned Ships in Inland Rivers Based on a Fuzzy Bayesian Network

Fuzzy logic system interference in ship accidents

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