Perceptions of high involvement work practices and burnout: investigating the mediating role of procedural justice and role overload and the moderating role of colleague support

Purpose
The purpose of this paper is to investigate the impact of employees’ perceptions of high involvement work practices (HIWPs) on burnout (emotional exhaustion and depersonalisation) via the mediating role of role overload and procedural justice. Further, perceived colleague support was hypothesised to moderate the effects of role overload and procedural justice on these outcomes.

Design/Methodology
The study was conducted on a random sample of unionised registered nurses (RNs) working in the Canadian public health care sector, stratified by mission and size of the institution to ensure representativeness. Of the 6546 nurses solicited, 2174 returned a completed questionnaire, resulting in a response rate of 33.2%. To test our hypotheses we conducted structural equation modelling (SEM) in Mplus version 6.0 (Muthen and Muthen, 1998 – 2010) with Maximum Likelihood (ML) estimation.

Results
The results showed that procedural justice and role overload fully mediated the influence of HIWPs on burnout. Moreover, colleague support moderated the effects of procedural justice and role overload on emotional exhaustion but not depersonalisation.

Limitations
The study used a cross-sectional research design and is conducted among one occupational group (i.e. nurses).

Research/Practical Implications
The findings question the dark side of HRM in the health care context. They also contribute to the lack of theoretical and empirical work dedicated to understanding the ‘black box’ problem (Castanheira and Chambel, 2010).

Originality/Value
The study employs a well-known theoretical perspective from the occupational health psychology literature to the HR field in order to contribute to the lack of theorising in the HR-well-being link.

Optimization of Controller Parameters for Energy Saving

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his paper considers a problem of identification for a high dimensional nonlinear non-parametric system when only a limited data set is available. The algorithms are proposed for this purpose which exploit the relationship between the input variables and the output and further the inter-dependence of input variables so that the importance of the input variables can be established. A key to these algorithms is the non-parametric two stage input selection algorithm.