Extracting the knowledge of networks in solving the innovative military bottlenecks of the Islamic Republic of Iran during the era of holy defense

Document Type : Original Research Paper

Authors

1 PhD student of decision-making and public policy at Imam Hossein University

2 Assistant Professor of Imam Hossein University

Abstract

Nowadays, the need to address the role of networks has become increasingly important for the armed forces due to the limited resources on the one hand and the frequency of missions on the other hand. The network helps to give the right answer to the right people in war and in defense. Also, the network greatly reduces the fixed costs of war, including repairs and maintenance, readiness and support, as well as transportation costs. In this article, an attempt has been made to identify the role of networks in solving defense innovation bottlenecks in the eight years of holy defense. This research has worked in the scope of symbolic-interpretive research and inductive approach and based on the interview technique with targeted sampling and through snowballing in data collection. According to the type of data that often required the exploration of themes, the method of theme analysis was used. 17 people of science and technology experts, high-ranking officials of readiness and support, relevant ministers during the war and high-ranking commanders of holy defense have been interviewed in depth, and their tacit knowledge turned into explicit knowledge. In total, 173 primary themes, 22 basic themes and 7 central themes were extracted as the most key components. The final model shows the existence of three main network categories, including the organizational network (reviewing goals and policies supporting innovation and protecting innovation), national (focusing on the promotion of national social capital, innovative resource management, innovative human resource management) and international (soft management of knowledge and technology). in the international arena and the promotion of religious knowledge in the resistance front. Also, the model has specified the main functions of each of the networks.

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References

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