Presenting a native model of organizational accountability with a public trust approach in Iranian government organizations

Document Type : Original Article

Authors

1 Ph.D. Student in Department of Managment, Ardabil Branch, Islamic Azad University, Ardabil, Iran

2 Assistant Professor Department of Managment, Ardabil Branch, Islamic Azad University, Ardabil, Iran

Abstract

Objective: The purpose of this study is to provide a local model of organizational accountability with a public trust approach for managers of Iranian government organizations.

Design / Methodology / Approach: In this research, the qualitative method of foundation data theory was used to present the native model. Then, CVI, CVR and CVI S-content validity indices were used to determine the validity of the themes and components of the model.

Research findings: The results of this study lead to the identification of 95 codes with 31 themes and categories in the form of six dimensions: causal factors (5 themes), intervention factors (5 themes), contextual factors (5 themes), main phenomena (6 themes), strategies (6 Themes) and consequences and results (4 themes).

Limitations and Implications: Although this study has provided a comprehensive and specific framework for the local model of organizational accountability of public sector managers based on the public trust approach, the importance and increasing the validity of these achievements requires field and experimental studies.

Practical implications: According to the findings, it can be said that the proposed indigenous model can increase its importance in the organizational accountability of government managers by emphasizing public trust.

Initiative or value of the article: The initiative and value of the present article is that it has been able to provide a comprehensive framework for designing a local model in government organizations that is based on the opinion of experts and such a model does not exist in the research background.

Keywords

Political Sociology of Iran
Volume 3, Issue 3 - Serial Number 11
November 2020
Pages 871-893

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