Identifying the Factors and Outcomes of Establishing Big Data Governance in Governmental Organizations Using a Mixed Methodology

Document Type : Research Paper


1 Ph.D. Candidate, Department of Public Administration, Faculty of Management and Economics, University of Sistan and Baluchestan, Zahedan, Iran.

2 Associate Prof., Department of Public Administration, Faculty of Management and Economics, University of Sistan and Baluchestan, Zahedan, Iran.

3 Prof., Department of Public Administration, Faculty of Management and Economics, University of Sistan and Baluchestan, Zahedan, Iran.


Objective: In the present study, an attempt has been made to examine and explain the factors and outcomes of establishing big data governance in governmental organizations.
Methods: A mixed-methods study was chosen as the design for this research and the two main types of analysis typically used were quantitative (deductive) and qualitative (inductive). In the qualitative stage, the method of thematic analysis, based on analysis, description, and composition of texts was discussed, and then in-depth interviews were conducted to extract and categorize the topics. The software used in the quality phase was Nvivo 12. Kappa-Cohen analysis and CVR coefficient were also applied to evaluate the validity and reliability of the qualitative part of the study. In the quantitative part, the fuzzy Delphi method was used to examine the verifiability of the factors and the outcomes of establishing big data governance. The statistical population of the present study in the qualitative stage included 12 organizational and academic experts while the quantitative stage included 21 affiliated experts.
Results: After analysing the texts and conducting the interview, 48 basic themes were identified. Then, by applying the opinions and modifications expressed by the experts, 36 final themes (24 factors and 12 outcomes) were grouped. To check the verifiability of the identified themes, the fuzzy Delphi method was employed in two stages. Examining the values of the fuzzy-deactivated mean of the first and second stages, the aforementioned preconditions and consequences were confirmed.
Conclusion: The performance of public organizations in making informed decisions, planning and strategic analysis, expanding good governance, and administrative transparency highly relies on the large amount of data they collect, process, and secure from within and outside the organizational environment. The issue has not received proper attention in Iranian public organizations and institutions. Accordingly, it is vital to establish big data governance in these organizations, which depends on recognizing the capacities and capabilities of the organization, drivers, and governance mechanisms and highlights the significance of the obtained results of establishing big data governance.


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