Jon Ivar Håvold1. 1. Alesund University College, N-6025 Alesund, Norway. jh@hials.no
Abstract
PROBLEM: Although there has been considerable interest in safety culture and safety climate in many industries, little attention has been given to safety culture in one of the world's riskiest industries, shipping. METHOD: Using both self developed items and items from published research on safety culture, safety climate, and quality and management style, a 40-item safety culture questionnaire was developed. The questionnaire was distributed in a self-administered form to sailors onboard 20 vessels and to officers attending a seminar in Manila. A total of 349 questionnaires were collected (total response rate, 60%). RESULTS, DISCUSSION AND IMPACT ON INDUSTRY: Principal component analysis (PCA) revealed 11 factors when the Kaiser eigenvalue rule was used and four factors when the scree test criterion was used. The factor structure in the material confirmed structures found in other industries. The relative importance of the factors from the factor analysis on "level of safety" measures was tested by canonical correlation analysis and regression analysis. The results confirmed previous research and showed that the most important factors were influential across industries. To determine weather differences existed between nationalities, occupations, and vessels the factors from the PCA was subjected to Multiple Discriminant Analysis. Significant differences between occupations, nations, and vessels were found on one or more of the factors from the PCA.
PROBLEM: Although there has been considerable interest in safety culture and safety climate in many industries, little attention has been given to safety culture in one of the world's riskiest industries, shipping. METHOD: Using both self developed items and items from published research on safety culture, safety climate, and quality and management style, a 40-item safety culture questionnaire was developed. The questionnaire was distributed in a self-administered form to sailors onboard 20 vessels and to officers attending a seminar in Manila. A total of 349 questionnaires were collected (total response rate, 60%). RESULTS, DISCUSSION AND IMPACT ON INDUSTRY: Principal component analysis (PCA) revealed 11 factors when the Kaiser eigenvalue rule was used and four factors when the scree test criterion was used. The factor structure in the material confirmed structures found in other industries. The relative importance of the factors from the factor analysis on "level of safety" measures was tested by canonical correlation analysis and regression analysis. The results confirmed previous research and showed that the most important factors were influential across industries. To determine weather differences existed between nationalities, occupations, and vessels the factors from the PCA was subjected to Multiple Discriminant Analysis. Significant differences between occupations, nations, and vessels were found on one or more of the factors from the PCA.
Authors: Albert P C Chan; Francis K W Wong; Carol K H Hon; Tracy N Y Choi Journal: Int J Environ Res Public Health Date: 2018-11-08 Impact factor: 3.390