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Original Research

The Job Demands-Resources model as predictor of work identity and work engagement: A comparative analysis

Roslyn De Braine, Gert Roodt

SA Journal of Industrial Psychology; Vol 37, No 2 (2011), 11 pages. doi: 10.4102/sajip.v37i2.889

Submitted: 20 January 2010
Published:  23 May 2011


Orientation: Research shows that engaged employees experience high levels of energy and strong identification with their work, hence this study’s focus on work identity and dedication.

Research purpose: This study explored possible differences in the Job Demands-Resources model (JD-R) as predictor of overall work engagement, dedication only and work-based identity, through comparative predictive analyses.

Motivation for the study: This study may shed light on the dedication component of work engagement. Currently no literature indicates that the JD-R model has been used to predict work-based identity.

Research design: A census-based survey was conducted amongst a target population of 23134 employees that yielded a sample of 2429 (a response rate of about 10.5%). The Job Demands- Resources scale (JDRS) was used to measure job demands and job resources. A work-based identity scale was developed for this study. Work engagement was studied with the Utrecht Work Engagement Scale (UWES). Factor and reliability analyses were conducted on the scales and general multiple regression models were used in the predictive analyses.

Main findings: The JD-R model yielded a greater amount of variance in dedication than in work engagement. It, however, yielded the greatest amount of variance in work-based identity, with job resources being its strongest predictor.

Practical/managerial implications: Identification and work engagement levels can be improved by managing job resources and demands.

Contribution/value-add: This study builds on the literature of the JD-R model by showing that it can be used to predict work-based identity.

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Author affiliations

Roslyn De Braine, University of Johannesburg, South Africa
Gert Roodt, University of Johannesburg, South Africa


employee engagement; identification; work identity; quantitative design; cross-sectional field survey; South African ICT sector company


Total abstract views: 5227
Total article views: 15916  


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ISSN: 0258-5200 (print) | ISSN: 2071-0763 (online)

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