The impact of perceived effectiveness of performance management system on affective commitment: Employee participation as a moderator

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Palestinian companies nowadays realize the importance of performance management systems. This study examines the moderating effect of employee participation in the relationship between perceived effectiveness of performance management system and affective commitment of employees in Palestinian service companies. A questionnaire was designed using Google Docs and distributed randomly via e-mail among 174 employees working in Palestinian service companies. A structural equation modeling, using AMOS V26, was used to test the hypotheses. The findings showed that perceived effectiveness of performance management system has a significant positive impact on affective commitment (β = 0.77; p-value = 0.000). While the justice dimension of perceived effectiveness of performance management system has a significant positive impact on affective commitment (β = 0.52; p-value = 0.007), the accuracy dimension was found insignificant (β = 0.26; p-value = 0.178).
Regarding the moderating effect, neither the interaction between the perceived effectiveness of performance management system and employee participation (β = –0.031; p-value = 0.465) nor the justice dimension was significant (β = 0.103; p-value = 0.203). Nevertheless, the interaction between the accuracy dimension and employee participation was negative (β = –0.14; p-value = 0.034). This study yielded support for the importance of perceived effectiveness of performance management system. Employees who perceived the performance of management system to be effective have higher affective commitment. Therefore, managers, especially HR managers, in service companies should pay more attention to the perceived effectiveness of performance management system, especially its justice dimension, to gain the benefits of committed employees.

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    • Figure 1. Structural model 1
    • Figure 2. Structural model 2
    • Figure 3. Interaction model 1
    • Figure 4. Interactional model 2
    • Figure 5. Interaction graph
    • Table 1. Descriptive statistics of demographics
    • Table 2. Convergent validity and internal consistency reliability
    • Table 3. Goodness-of-fit indicators in the measurement model
    • Table 4. Goodness-of-fit indicators in the structural model
    • Table 5. Hypotheses testing
    • Conceptualization
      Emad Waladali
    • Data curation
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    • Formal Analysis
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    • Funding acquisition
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    • Investigation
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    • Methodology
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    • Project administration
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    • Resources
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    • Software
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    • Supervision
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    • Validation
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    • Visualization
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    • Writing – original draft
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    • Writing – review & editing
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