Predicting career success: is the dark side of personality worth considering?

Dominik Paleczek, Sabine Bergner, Robert Rybnicek
2018 Journal of Managerial Psychology  
Purpose -The purpose of this paper is to clarify whether the dark side of personality adds information beyond the bright side when predicting career success. Design/methodology/approach -In total, 287 participants (150♀, M age ¼ 37.74 and SD age ¼ 10.38) completed questionnaires on the Dark Triad (narcissism, Machiavellianism and psychopathy) and the Big Five (emotional stability, extraversion, openness, agreeableness and conscientiousness). They also provided information on their objective
more » ... ary and leadership position) and subjective (job satisfaction and satisfaction with income) career success. Regression analyses were used to estimate the Dark Triad's incremental predictive value. Findings -The results show that the Dark Triad only provides incremental information beyond the Big Five when predicting salary (ΔR 2 ¼ 0.02*) and leadership position (ΔR 2 ¼ 0.04*). In contrast, the Dark Triad does not explain unique variance when predicting job satisfaction or satisfaction with income. Research limitations/implications -The exclusive use of self-rated success criteria may increase the risk of same-source biases. Thus, future studies should include ratings derived from multiple perspectives. Practical implications -Considering the Dark Triad in employee selection and development seems particularly promising in the context of competitive behaviour. Social implications -The results are discussed in light of the socioanalytic theory. This may help to better understand behaviour in organisational contexts. Originality/value -This study is the first that simultaneously investigates all three traits of the Dark Triad and the Big Five in combination with objective and subjective career success. In addition, it extends previous findings by answering the question of whether the Dark Triad offers incremental or redundant information to the Big Five when predicting success.
doi:10.1108/jmp-11-2017-0402 fatcat:fzcixx4zxjgrpfekqb3thsg7ne