Designing a Participatory Governance Model in Order to Reduce Corruption with a Mixed Approach (Case study: Ahvaz Governor's Office)

Document Type : Research Paper

Authors

1 PhD Student, Department of Management, Sirjan Branch, Islamic Azad University, Sirjan, Iran

2 Assistant Professor, Department of Management, Sirjan Branch, Islamic Azad University, Sirjan, Iran

3 Assistant Professor, Department of Management, Payame Noor University, Tehran, Iran

Abstract

The aim of this study was to design a participatory governance model in order to reduce corruption. Accordingly, the present study is practical-fundamental in terms of purpose, mixed (qualitative-quantitative) in terms of data type, cross-sectional in terms of data collection time, and a survey research in terms of data collection method. The statistical population of the present research in the qualitative section includes 20 experts, specialists and elites working in both the provincial government and the office of governor. Also in the quantitative part, the statistical population of this study includes all experts working in the organizations of the provincial office and office of governor from which 335 individuals were selected as a sample using cluster random sampling method. The analysis in the qualitative part was conducted through the methods of literature review and the interview. In the inferential and quantitative sections, one-sample t-test and SPSS-v21 software were used in order to answer the research questions. The results showed that the model of participatory governance to reduce corruption in Iran includes the dimensions of the central phenomenon: participatory governance, causal conditions: institutional development of participatory governance, consequences and results: reduction of corruption, Contextual background (governing context): participatory culture, interfering conditions: strengthening the administrative system and strategies: reforming the organizational structure along with 30 components. Finally, the results showed that the proposed model has a good validity.
 

Keywords

References

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History

  • Receive Date: 09 December 2021
  • Revise Date: 08 March 2022
  • Accept Date: 08 March 2022

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