Mediation role of management commitment on improving fraud prevention in primary healthcare: Empirical evidence from Indonesia

  • 860 Views
  • 309 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

Fraud in primary healthcare (PHC) is an important and relevant topic to study because of its impact on the state in terms of financial losses and a decrease in the quality of PHC. This study is also relevant because previous studies that formulate a model and measure fraud prevention comprehensively are still limited. It aims to examine the mediating role of management commitment on the effect of apparatus competence and internal control system on fraud prevention. The sample comprises 78 PHCs and 234 senior managers as respondents in Aceh Province, Indonesia. Data for this study were collected using questionnaires from March to July 2021. Structural equation modeling was used to examine a causal relationship between the variables. The result shows that apparatus competence and internal control system positively affect management commitment and fraud prevention with p-value 0.000 (p > 0.01). Likewise, management commitment has a positive effect on fraud prevention with p-value 0.000 (p > 0.01). The findings show that management commitment mediates the relationship between the internal control system and fraud prevention. At the same time, the apparatus competence does not directly affect fraud prevention. The practical significance of this study is the importance of implementing an effective internal control system and high management commitment as a mediating variable for fraud prevention.

Acknowledgments
The authors are very thankful to the University of Muhammadiyah Aceh, which has supported this study, and all those who have contributed to this investigation.

view full abstract hide full abstract
    • Figure 1. Structural results of the proposed model
    • Table 1. Sampling technique
    • Table 2. Operationalization of research variables
    • Table 3. Demographic profile of respondents
    • Table 4. Confirmatory factor analysis
    • Table 5. Path coefficient analysis of the structural equations
    • Table 6. Mediating effect analysis
    • Conceptualization
      Surna Lastri, Heru Fahlevi, Yossi Diantimala, Ridwan
    • Data curation
      Surna Lastri, Heru Fahlevi, Yossi Diantimala
    • Formal Analysis
      Surna Lastri, Yossi Diantimala
    • Funding acquisition
      Surna Lastri
    • Investigation
      Surna Lastri, Ridwan
    • Methodology
      Surna Lastri, Heru Fahlevi, Yossi Diantimala, Ridwan
    • Project administration
      Surna Lastri
    • Resources
      Surna Lastri, Heru Fahlevi
    • Software
      Surna Lastri, Heru Fahlevi, Yossi Diantimala
    • Supervision
      Surna Lastri, Heru Fahlevi, Yossi Diantimala, Ridwan
    • Validation
      Surna Lastri
    • Visualization
      Surna Lastri, Yossi Diantimala
    • Writing – original draft
      Surna Lastri
    • Writing – review & editing
      Surna Lastri, Heru Fahlevi, Yossi Diantimala