AI Summary & Key Takeaways
AI InsightTheoretical and practical implications of the findings are discussed.
📌 3 Key Takeaways
Abstract
In the maritime industry, a person of lower class or rank is exposed to mobbing, which can easily be observed. In Turkey, instead of expressing mobbing in a specific word as "bullying in the workplace", replaced it as "emotional harassment", "psychological violence at work", "intimidation". The aim of the study is to determine the factors that affect the mobbing. Survey participants are 178 volunteers, almost all of the maritime university faculties and several private companies participated the survey. Data were collected in May 2018 in Turkey. Mobbing Scale (Leymann's LIPT-The Leymann Ivertory of Psychological For Social Sciences) was used. Mobbing scale has 5 factors: relationship, threat and harassment, business and career-related obstacles, private life, commitment to work. Statistical analysis were applied in SPSS (Statistical Package for Social Sciences v24). According to demographics, relationships between factors were assessed by correlation analysis. Multiple linear regression analysis was used to determine the factors affected the mobbing. 5 regression models were set up for each 5 factors. Bivariate correlations with Spearman’s rho coefficients between all factors are utilized. According to regression results, it is seen that variables affected mobbing significantly. Demographics are effective in determining mobbing. Theoretical and practical implications of the findings are discussed.