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Article detail · 2023 · article

A statistical analysis-based Bayesian Network model for assessment of mobbing acts on ships

ISSN0308-8839
YÖKSİS OpenAlex SJR Q1 JCR Q2 Top 10%
Year2023
Citations29OpenAlex
Percentile%97.5
FWCI8.841.00 = world average
Scopus (SJR)Q1
WoS (JCR)Q2

Data source split

  • YÖKSİSYÖKSİS article record
  • YÖKSİS venueMaritime Policy & Management
  • Catalog match (ISSN)Maritime Policy and Management
  • OpenAlexOpenAlex enrichment (abstract, citations, topics)

Abstract

OpenAlex English

Mobbing is a fundamental problem that disrupts the organization’s structure and negatively affects its employees’ safe work environment. The most critical issue in combating mobbing is increasing the awareness of victims, businesses and society about this problem. The importance of identifying this problem, which will adversely affect the professional life in the maritime profession, as in every professional group, is obvious. This study offers a statistical analysis-based dynamic Bayesian network to model seafarers’ mobbing acts in merchant ships. In this research, measures against mobbing in the maritime industry are also recommended after determining the most frequent mobbing elements in ships. It is observed that the seafarers who have just stepped into onboard are more exposed to mobbing; in contrast, mobbing attacks experienced by seafarers decrease with an increase in age. The most frequent mobbing behaviours are listed as: “I am continually given new tasks“, “My superiors restrict the opportunity for me to express myself” and ”Unfounded rumours about me is circulated in the ship”. The study reveals that while the maritime authorities such as PSC and the ITF have limited capabilities for solving mobbing related problems, the companies may have a crucial role to play in the process.

Topics

Citations

OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.

29citationsOpenAlex · cited_by_count (cache / database)

42 publications in the local catalog that cite this work (OpenAlex reference match; not the full global list).

  1. 2024 A holistic safety assessment for cargo holds and decks fire & explosion risks under fuzzy Bayesian network approachCitations 49 · OpenAlex
  2. 2024 A holistic safety assessment for cargo holds and decks fire & explosion risks under fuzzy Bayesian network approachCitations 49 · OpenAlex
  3. 2025 Improved Z-number based Bayesian network modelling to predict cyber-attack risk for maritime autonomous surface ship (MASS)Citations 32 · OpenAlex
  4. 2025 Improved Z-number based Bayesian network modelling to predict cyber-attack risk for maritime autonomous surface ship (MASS)Citations 32 · OpenAlex
  5. 2025 Improved Z-number based Bayesian network modelling to predict cyber-attack risk for maritime autonomous surface ship (MASS)Citations 31 · OpenAlex
  6. 2024 Predicting human reliability for emergency fire pump operational process on tanker ships utilising fuzzy Bayesian Network CREAM modellingCitations 25 · OpenAlex
  7. 2024 Predicting human reliability for emergency fire pump operational process on tanker ships utilising fuzzy Bayesian Network CREAM modellingCitations 25 · OpenAlex
  8. 2024 Predicting human reliability for emergency fire pump operational process on tanker ships utilising fuzzy Bayesian Network CREAM modellingCitations 25 · OpenAlex
  9. 2024 Predicting human reliability for emergency fire pump operational process on tanker ships utilising fuzzy Bayesian Network CREAM modellingCitations 25 · OpenAlex
  10. 2024 Investigating the influence of human errors in master-pilot information exchange on maritime accident risk during pilotageCitations 23 · OpenAlex

Authors

5
  1. ÖZKAN UĞURLU ORDU ÜNİVERSİTESİ 1
  2. ŞABAN EMRE KARTAL 2
  3. ORÇUN GÜNDOĞAN VAN YÜZÜNCÜ YIL ÜNİVERSİTESİ 3
  4. MUHAMMET AYDIN 4
  5. JIN WANG 5