Predictors of satisfactory employee performance in the South African Department of Health
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DOIhttp://dx.doi.org/10.21511/ppm.15(2).2017.13
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Article InfoVolume 15 2017, Issue #2, pp. 140-147
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A study was conducted at the South African Department of Health (DOH) in order to assess the perception held by employees of the DOH at national and provincial levels about the suitability of the Performance Management System (PMS) tool that was being used in the DOH for the assessment and evaluation of the performance of employees working for the DOH at national and provincial level based on their Key Performance Areas (KPAs) and Key Performance Indicators (KPIs). The study was based on a stratified random sample of size n=120 employees of the DOH working at national and provincial levels. The study was quantitative, and used methods of data analyses such as frequency tables, cross-tab analysis and binary logistic regression analysis. The degree of productivity of employees at work was measured by using a composite index defined by Le Brasseur, Zannibbi & Zinger (2013). Results obtained from the study showed that about 74% of employees held a favorable view of the PMS tool that was used for the assessment and evaluation of employees. The percentage of respondents who viewed the PMS tool as unhelpful was about 26%. The study showed that the view held by employees working in the DOH about the relevance and objectivity of the PMS tool used for the assessment of employee performance in the DOH was significantly and adversely affected by the perception that the PMS policy was incapable of promoting the effectiveness of the DOH as an organization, the perception that the PMS policy was incapable of rewarding deserving employees, and the perception that there were not enough training opportunities in the PMS, in a decreasing order of strength.
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JEL Classification (Paper profile tab)I11, M54, C35
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References30
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Tables3
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Figures0
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- Table 1. General characteristics of respondents (n=120)
- Table 2. Results obtained from cross-tab analyses
- Table 3. Odds Ratios (OR) estimated from binary logistic regression analysis
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