Job and home characteristics associated with work-home interaction in the mining environment
Vermeulen, Elizabeth Maria
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The mining environment forms the bedrock of the South African economy. It is an environment in which people's lives are put at risk due to the nature of the work. Employees in the mining industry work with dangerous materials and use heavy machinery and equipment that can have negative consequences. Mine workers also experience high job demands that require much effort, and yet also experience a lack of resources to fulfil job requirements. Positive aspects of this environment include diverse social support systems, health care, skills development programmes and information systems. Mine workers can therefore experience negative and positive behaviour towards work which can influence their behaviour at home, and vice versa. However, there seems to be a lack of research investigating specific job and home characteristics associated with work-home interaction in the mining environment. The first objective of this study was to determine whether job and home characteristics play a role in negative or positive work-home interference (WHI) and in negative or positive homework interference (HWI). The second objective was to determine the predictors of each domain. The last objective was to determine the variance of WHI and HWI explained by both job and home characteristics in the mining environment. A cross-sectional survey design was used. Random samples (n = 320) were taken from employees of different Patterson grade levels working in various gold, platinum and phosphate mining houses in Gauteng, the Northwest and Limpopo provinces. A job characteristics questionnaire, home questionnaire and the 'Survey Work-Home Interaction - Nijmegen' (SWING) were administered. The factor structures were tested with structural equation modelling. Cronbach alpha coefficients were used to determine the reliability of the measuring instruments. The relationship between variables was determined with Pearson product-moment correlations and multiple regression analyses. The results indicated that significant predictors of Negative WHI were Pressure, Poor Working Conditions and a Lack of Instrumental Support and explained 34% of the variance. Autonomy was found to be the only predictor of Positive WHI, explaining 10% of the variance. Significant predictors of Negative HWI were Home Pressure and a Lack of Home Autonomy, which explained 9% of the variance. Finally, it was found that only Home Pressure predicted Positive HWI, accounting for 3% of the variance. Recommendations were made for the organisation and for future research.
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