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Predicting interference between work and home : a comparison of dispositional and situational antecedents

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Purpose - To examine the relative power of four dispositional, self-evaluation traits (adaptive and maladaptive perfectionism, generalized self-efficacy, and general self-esteem) versus three situational factors (organizational time demands, potential negative career consequences, and managerial support) in predicting work interference with home (WIH) and home interference with work (HIW). Methodology/Approach - A survey was conducted among 223 UK public sector employees. Hierarchical multiple regression analysis tested main effects of personality and situational characteristics on WIH and HIW. A usefulness analysis determined whether dispositional or situational variables had greater predictive power for the two dependent variables. Findings - Significant, negative main effects of adaptive perfectionism on HIW, and of self-esteem on WIH. Positive relationships were found between maladaptive perfectionism and both WIH and HIW. Situational factors were also significant predictors of WHI: organizational time demands were positively associated with WIH, while managerial support had a negative relationship with WIH. Dispositional variables accounted for 15% of variance in HIW, but only 4% of variance in WIH. Research limitations/implications - The cross-sectional design of the study does not permit firm conclusions regarding causality, and the results may be influenced by common method bias. Practical implications - Raising awareness of the role of personality in work-home interference may assist managers in providing more effective support to employees. The danger exists that policy-makers will dismiss HIW as an individual responsibility due to the influence of dispositional factors. Originality/Value - This study indicates that self-evaluation personality characteristics play a key role in predicting HIW, and are more important than traditionally investigated factors associated with the home and workplace environments.

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en

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application/pdf

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http://eprints.lse.ac.uk/892/1/BeauregardPredicting.pdf

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