ISSN: 2222-6990
Open access
A large body of research shows that human failures, the tendencies of which are expressed as safe behavioral potential in this study, are the main culprit of industrial accidents in oil and gas sectors, the antecedents of which might be the combinations or interactions of demographic and psychometric attributes of workers, and organizational safety culture. The purpose of study is to explore workers’ profile of safe behavioural potentials, and its corresponding remedies, from the perspective of human failure types that could be classified into human errors (unintentional actions) and violations (intentional actions). Human errors can be further categorized into slips, lapses, rule-based mistakes, knowledge-based mistakes; while violations consist of exceptional violations, situational violations, optimizing violations, and routine violations. Broadly speaking, local oil and gas construction industry is dominated by male workers. Result of demographic indicates most workers are aged above 25-year-old with presumably adequate safety knowledge and experience, probably that is the reason why majority of the workers showed the propensity to behave safely at work by agreeing to statements advocating committing fewer human failures. However, result also revealed of human failures simply could not be ignored because 5.0% - 34.2% respondents revealed their tendencies towards committing violations, and 6.5% - 13.1% of them indicated their proneness to human errors. Therefore, interventions to curb human failures are still of utmost importance. This study contributes to theoretical domains and practical applications in two ways, firstly, this study lays the foundation for future studies to explore distal and proximal determinants of a human failure with significant accident risks, skill and knowledge required to perform such behavior, its environmental constraints, and their relative importance in forming that failure. Secondly, it may also inspire the development of predictive and prescriptive tools for accident preventions, taking advantage of rapid advancement in Artificial Intelligence and Big Data technologies.
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