Public Administration Perspective

Performance Management System as a Tool To Prevent Administrative Corruption

Document Type : Research Article (with mixed approaches)

Author

Assistant Professor, Faculty of Governance, University of Tehran, Tehran, Iran.

Abstract

Purpose: Development and corruption are two related concepts; in fact, they are two sides of the same coin. This implies that achieving development is not possible without combating corruption. Given the crucial role of human resource management systems in preventing corruption, this study aims to model the optimal system for managing employee performance to prevent corruption in the public sector.
Design/ methodology/ approach: This research adopts an interpretive paradigm, applied for its purpose and descriptive in nature, employing interviews as the data collection method. The research method is based on interpretive-structural modeling. The statistical population comprises public sector managers, and snowball sampling is used for sampling.
Research Findings: The study identified ten components for designing an employee performance management model to prevent administrative corruption: transparency, accountability, procedural justice, interactional justice, justifiability, alignment, rule of law, continuous improvement, authenticity, and preventability. According to the results of the MICMAC analysis, none of the identified components are located in the autonomous region, indicating a strong interconnection among all model components. Nine components were identified in the linkage region: transparency, accountability, procedural justice, interactional justice, justifiability, alignment, rule of law, continuous improvement, and authenticity. These components are dynamic, meaning that changes in them can impact the entire system. Additionally, the preventability component is placed in the dependence region, indicating its high dependence on other components. Among other findings, the study delineated an interaction network of variables to determine the level and relationships of the identified components. According to this network, the rule of law and accountability dimensions are fundamental components of the model, as they influence all other components. These two components exhibit a two-way relationship with each other, implying mutual influence. Additionally, transparency and alignment rank next, also with a two-way relationship with the preceding components, indicating their significant influence on the model. Authenticity and justifiability are positioned in the third level of the model; authenticity affects continuous improvement and has an interactive relationship with justifiability. Continuous improvement, located in the fourth level, impacts two components in the fifth level: procedural justice and interactional justice. Procedural and interactional justice, besides influencing each other, affect the preventability component, the last level of the model. Preventability is the most dependent component, suggesting that procedural preventability in the employee performance management system relies on other model components.
Limitations & Consequences: Data collection through interviews introduces potential biases in the findings. Additionally, the scope of actors and the research problem prevented a comprehensive examination of the issue from all perspectives.
Practical Consequences: Public sector managers can use the findings of this applied research to design employee performance management systems that reduce corruption risk.
Innovation or value of the Article: Despite numerous efforts to combat corruption in Iran, effectiveness has been limited, as evidenced by Iran's low ranking in the Corruption Perceptions Index (CPI) in 2022. This study addresses the significant role of human resource systems in combating administrative corruption by identifying and modeling the components of an employee performance management system tailored for the public sector.
Paper Type: Original Article
 

Keywords

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Public Administration Perspective
Volume 15, Issue 1 - Serial Number 57
2024
Pages 36-61