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Predictors and Mediators of Work Commitment at a Selected South African Government Department: A SMART PLS Approach

Author

Listed:
  • Molefe Jonathan Maleka

    (Office of the DVC: TLT, Tshwane University of Technology, eMalahleni Campus, eMalahleni 1043, South Africa)

  • Fhatuwani Rampfumedzi

    (Tshwane School for Business and Society, Tshwane University of Technology, Tshwane 0001, South Africa)

Abstract

Government managers should understand the determinants of work commitment, a people analytics metric. This study focuses on training, involvement, clarity of organisational goals, and performance feedback. According to Social Exchange Theory (SET), these predictors are salient, and the literature review suggests that there is little or no existing literature related to the South African government department. This study was conducted to expand the body of knowledge of SET, using a quantitative approach and a cross-sectional case study design within the South African government department. Subsequently, 260 respondents were selected, who completed a validated closed-ended questionnaire. The data were analysed in SMART PLS 4, using structural equation modelling for analysis. The key findings determined that training predicted involvement most strongly (β = 0.377, t = 6.171, p < 0.05), and involvement mediated the relationship between training and clarity on organisational goals (β = 0.096, t = 2.716, p < 0.05). Moreover, it found that clarity on organisational goals was a significant predictor of work commitment (β = 0.257, t = 3.638, p < 0.05). The priority–performance map analysis (IPMA) ranked priority highest but performance lowest, revealing insights into the organisation’s aims. The managerial implication is that the government department must strengthen the clarity of organisational goals across all levels.

Suggested Citation

  • Molefe Jonathan Maleka & Fhatuwani Rampfumedzi, 2025. "Predictors and Mediators of Work Commitment at a Selected South African Government Department: A SMART PLS Approach," Administrative Sciences, MDPI, vol. 16(1), pages 1-18, December.
  • Handle: RePEc:gam:jadmsc:v:16:y:2025:i:1:p:21-:d:1830105
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