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EN
Many industries are confronted by plateauing safety performance as measured by the absence of negative events – particularly lower-consequence incidents or injuries. At the same time, these industries are sometimes surprised by large fatal accidents that seem to have no connection with their understanding of the risks they faced; or with how they were measuring safety. This article reviews the safety literature to examine how both these surprises and the asymptote are linked to the very structures and practices organizations have in place to manage safety. The article finds that safety practices associated with compliance, control and quantification could be partly responsible. These can create a sense of invulnerability through safety performance close to zero; organizational resources can get deflected into unproductive or counterproductive initiatives; obsolete practices for keeping human performance within a pre-specified bandwidth are sustained; and accountability relationships can encourage suppression of the ‘bad news’ necessary to learn and improve.
EN
Safety work behavior has continued to attract the interest of organizational researchers and practitioners especially in the health sector. The goal of the study was to investigate whether personality type A, accident optimism and fatalism could predict non-compliance with safety work behaviors among hospital nurses. One hundred and fifty-nine nursing staff sampled from three government-owned hospitals in a state in southeast Nigeria, participated in the study. Data were collected through Type A Behavior Scale (TABS), Accident Optimism, Fatalism and Compliance with Safety Behavior (CSB) Scales. Our results showed that personality type A, accident optimism and fatalism were all related to non-compliance with safety work behaviors. Personality type A individuals tend to comply less with safety work behaviors than personality type B individuals. In addition, optimistic and fatalistic views about accidents and existing safety rules also have implications for compliance with safety work behaviors.
EN
This paper presents a model that quantifies the causal relations among safety variables (latent variables) and workers’ safety behavior (indicator) using statistical data and hypotheses obtained from construction workers and existing literatures, respectively. The safety variables that affect workers’ safety behaviors are identified from existing studies and operationalized to measure their causal relations with the workers’ behaviors. The model identifies the directions and degrees of the effect of every latent variable on the other latent variables and the indicator. Survey questionnaires were administered to construction workers in South Korea. Exploratory and confirmatory factor analyses, Cronbach's α and structural equation modeling were performed to test the causal hypotheses using SPSS 18.0 and AMOS 18.0. This study provides the theoretical model that predicts construction workers’ safety behavior on construction sites using path diagram and analysis.
EN
One of the dimensions treated as part of a company's safety culture or climate is workers' attitudes towards risk and safety. In the present study these personal aspects are defined as workers' safety culture, which is understood as a way of acting focused on life and taking care of one's health. A questionnaire on safety culture was filled out by 200 employees of a metallurgical enterprise. Factor analysis was used to determine empirical scales of the questionnaire, whereas variance analysis was used to test hypotheses. The results confirmed the hypotheses that people who experienced accidents, dangerous situations, and-to a lesser extent-health problems had a lower level of safety culture. Nevertheless not all of the scales determined during factor analysis turned out to be significant as far as all kinds of those undesirable situations are concerned. Proposals for future studies are formulated in the conclusion.
EN
The scope of this study covers events resulting from improper functioning of machine control systems. An accident model providing a basis for formulating a checklist for accident analysis has been developed. Data about 700 accidents were collected. An analysis has proved that in the group of accidents caused by improper functioning of machine control systems, serious accidents happened much more frequently as compared to the group of accidents with no relation to the control system. The reasons for the majority of incidents caused by improper performance of safety functions consist in the errors made by designers. In view of that, incorrect behaviour of a worker should be treated as a normal event instead of a deviation causing an accident.
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