احمد سامی

Purpose: The current research was conducted with the aim of validating the structural model of open data governance in line with the health of the administrative system in e-government in government organizations. Method: This research, with a practical purpose, was based on a descriptive survey implementation method. The statistical population of the research included the managers of the country's tax affairs organization and several university professors, all of whom (18 person) were selected as a statistical sample. The data collection tool in this research was a researcher-made questionnaire, and confirmatory factor analysis, structural equation modeling, and Smart PLS software were used for data analysis. Findings: The results of the research show that the structural model of open data governance in the direction of administrative health in e-government at governmental organizations includes six components: platforms (with the dimensions of intra-organizational platforms and external platforms), strategies (with the dimensions of common strategies—internal and external—, intra-organizational strategies, and extra-organizational strategies), intervening conditions (with common dimensions—internal and external), causal category (with dimensions of internal-external organizational factors, individual and social factors), central category, and consequences (with common dimensions—internal and external). Conclusion: Intra-organizational and extra-organizational platforms have a positive and significant effect on common strategies. The strategies of this research have a positive and significant effect on the results. The impact of intervening conditions on the central category is positive and significant. The effect of the causal category of this research, including individual factors and social factors, on the central category, is negative and significant because the regression coefficient has become negative. The impact of the central category on strategies has become negative, but this impact is not significant.