Empathy as a Buffer: The Moderating Effect of Trait Empathy on Counterproductive Work Behavior
While much research has been dedicated to determining what may cause workers to engage in counterproductive behavior at work, fairly less attention has been paid to the factors which may influence individuals to refrain from enacting these behaviors. The current study was conducted to determine whether trait empathy may be one such factor and serve as a moderator of the relationship between work stressors and intentions to commit counterproductive work behavior (CWB). Using the theoretical framework of the stressor-emotion model of CWB it was hypothesized more specifically that empathy moderated the mediating effects of negative affect on relationships between stressors and CWB intentions; it was expected that this mediating process would be weaker for those who are more empathetic as compared to those who lower in empathy. 365 Full-time working adults were surveyed using Amazon's Mechanical TURK at two time points to examine this relationship. The moderating effects of the different facets of empathy on the work stressor-CWB relationship were also examined in regard the intention to commit CWB to see if one facet of empathy was more key in the buffering of CWB than the other. Results supported the stressor-emotion model of CWB finding that NA mediated the relationship between the work stressors workload and organizational injustice, and CWB intentions. Results also found that trait empathy significantly attenuated the indirect relationship between the stressors and CWB intentions with trait empathy's affective component found to be particularly influential in this process. Implications of these findings as well as directions for future research are discussed.
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Master of Science (M.S.)
College of Sciences
Industrial and Organizational Psychology
Length of Campus-only Access
Masters Thesis (Open Access)
Grinley, Amanda, "Empathy as a Buffer: The Moderating Effect of Trait Empathy on Counterproductive Work Behavior" (2021). Electronic Theses and Dissertations, 2020-. 687.