Developing a Risks Identifying Model for the Army of Islamic Republic of Iran

Document Type : Original Article

Authors

1 Ph.D. Candidate, Department of Defense Management, Faculty of War, AJA University of Command and Staff, Tehran, Iran.

2 Associate Professor, Department of Strategic Management, Faculty of War, AJA University of Command and Staff, Tehran, Iran.

3 Associate Professor, Department of Futures Studies, Faculty of Social Sciences, AJA University of Command and Staff, Tehran, Iran.

4 Assistant Professor, Department of Information Technology Management, Faculty of Social Sciences, AJA University of Command and Staff, Tehran, Iran.

Abstract

This article presents a model of risk identification for the Army of Islamic Republic of Iran. The study can be described as applied in terms of nature of research, which utilizes a mixed-method approach within a descriptive-survey research design. The statistical population includes Army personal with relevant expertise and experience regarding the research topic of this study. The statistical sample, selected from a population of 124 individuals, consists of 93 participants chosen using a simple random stratified method.
 The results reveal that the risk identification model includes two primary dimensions: internal and external. The internal dimension is ranked first, followed by the external dimension, with consensus coefficients of 0.6483 and 0.6215, respectively. Within the internal dimension, the components of audit quality, administrative health, process, knowledge and skills, information technologies, databases, and human resources are ranked in the first to seventh priorities, with agreement coefficients ranging from 0.7433 to 0.5662. In the external dimension, the components of relationship power and influence, tax proceedings, and financial laws and regulations hold the first to third positions, with agreement coefficients of 0.6889, 0.6649, and 0.5311, respectively.

Keywords

References

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Journal of Defense Economics and Sustainable Development
Volume 9, Issue 34
December 2024
Pages 61-87

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