2023
DOI: 10.5603/imh.2023.0003
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Bibliometric and systematic literature review on safety management in the shipping industry and further development in Indonesia

Abstract: This study aims to analyse safety management in the shipping industry and suggest further research. Safety management is a critical component in preventing accidents within the shipping industry. Unfortunately, ship accidents are relatively common. To improve safety management in the shipping industry, it is necessary to identify various problems and solutions from previous studies. This study uses comprehensive mapping, utilising bibliometric and systematic reviews, to analyse 669 articles within the Scopus d… Show more

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Cited by 5 publications
(5 citation statements)
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“…(3) derive fresh ideas for research; and (4) put their planned contributions to the area of study. There are bibliometric studies on different subjects in the maritime field such as maritime transport literature (Solak Fiskin & Güldem Cerit, 2019), maritime accidents (Cao et al, 2023;Yurt & Cenk, 2023), oil spill (Buber & Koseoglu, 2022a, 2022b, inspection analysis (Bicen & Celik, 2023), safety management (Rinaldy, 2023), seafarers' health research (Jiang et al, 2023), Automatic Identification System (Meyers et al, 2021). Table 1: The data collection process is illustrated in Figure 1.…”
Section: Methodsmentioning
confidence: 99%
“…(3) derive fresh ideas for research; and (4) put their planned contributions to the area of study. There are bibliometric studies on different subjects in the maritime field such as maritime transport literature (Solak Fiskin & Güldem Cerit, 2019), maritime accidents (Cao et al, 2023;Yurt & Cenk, 2023), oil spill (Buber & Koseoglu, 2022a, 2022b, inspection analysis (Bicen & Celik, 2023), safety management (Rinaldy, 2023), seafarers' health research (Jiang et al, 2023), Automatic Identification System (Meyers et al, 2021). Table 1: The data collection process is illustrated in Figure 1.…”
Section: Methodsmentioning
confidence: 99%
“…In this paper, a gray prediction model GM(1,n) that can comprehensively consider multiple related factors is used. It is a generalization of the model GM(1,1) in the case of multivariate, but it is not a simple combination of the model GM (1,1). N-element first-order differential equations are established and solved by linkage, so that the parameters in the multivariate gray prediction model can reflect the interrelationship between variables, and ultimately make the predicted value more in line with reality.…”
Section: Gray Predictive Modelmentioning
confidence: 99%
“…N-element first-order differential equations are established and solved by linkage, so that the parameters in the multivariate gray prediction model can reflect the interrelationship between variables, and ultimately make the predicted value more in line with reality. When N=1, the model degenerated into a model GM (1,1).The prediction principle of the model GM(1,n) is to accumulate a certain data sequence to generate a set of new data sequences with obvious trends, build a model to predict according to the growth trend of the new data sequence, and then use the accumulation method to perform reverse calculations, restore the original data sequence, and then obtain the prediction result. The comparison of prediction accuracy levels is shown in Table1.…”
Section: Gray Predictive Modelmentioning
confidence: 99%
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“…Rinaldy's article about shipping industry safety was very relevant [1]. The subject is delicate and critical because of the number of accidents and severe accidents among seafarers [2,3].…”
mentioning
confidence: 99%