Master of Science (MS)
Please see currently inactive department below.
First Advisor's Name
Marc L. Resnick
First Advisor's Committee Title
Second Advisor's Name
Third Advisor's Name
Date of Defense
The purpose of this research was to develop a methodology that would evaluate employees’ personality traits, demographic characteristics, and workplace parameters to predict safety compliance along with the moderating effect of risk perception.
One hundred and twenty five employees of a manufacturing facility were given questionnaires to gather their demographic and perception information. Surveys were also used to measure their personality characteristics, and periodic observations were recorded to document employee’s safety compliance. A significant correlation was found between compliance and the worker's perception of management's commitment to safety (r = 0.27, p < 0.01), as well as with gender (r = -0.19, p < 0.05). Females showed a significantly higher average compliance (78%), than males (69%). These findings demonstrated the value of developing a model to predict safety behavior that would assist companies In maintaining a safe work environment, preventing accidents, ensuring compliance, and reducing associated costs.
Diaz, Yenny Farinas, "Predicting employee compliance with safety regulations, factoring risk perception" (2000). FIU Electronic Theses and Dissertations. 2731.
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