Document Type : ORIGINAL RESEARCH ARTICLE

Authors

1 Department of Industrial Management, Faculty of Management, Tehran University, Iran. Researcher in Tehran Disaster Mitigation and Management Organization, Iran

2 Department of Health in Emergency and Disasters. Faculty of Health Management and Information. Iran University Medical of Science. Iran

3 Department of Health in Emergency and Disasters. Faculty of Health. Baghiyatallah University of Medical Sciences, Iran. President of Tehran Disaster Mitigation and Management Organization, Iran

4 Tehran Disaster Mitigation and Management Organization, Iran

Abstract

BACKGROUND AND OBJECTIVES: Crises of high uncertainty and complexity provoke discussion about new requirements of crisis management systems, which is of utmost importance in developing a cooperative environment and providing effective responses. This study aims to analyze the cooperative system of Tehran Municipality departments involved in crisis management of the COVID-19 pandemic, who are called actors afterward, and thereby presents the lessons learned through this pandemic.
METHODS: The Social network analysis has been applied in this research to analyze the collaboration system. Accordingly, the crisis management actions taken by Tehran Municipality is first explored and, 38 actors and 11 areas of knowledge are identified. The two-dimensional matrix of actors-actions and the cooperative system of the actors are then analyzed based on the indicators of degree and betweenness centrality in UCINET and NetDraw software to investigate the position of the actors' tacit knowledge power in the cooperative network.
FINDINGS: The actors’ cooperative system generally has high density and coherence; however, it seems that the position of some actors must be strengthened within the structure of the crisis management in Tehran Municipality. The results of degree centrality index identified 7 actors with higher degree centrality (20% of total actors), and 7 actors with lower degree centrality (20% of total actors). Moreover, the betweenness centrality of the network of actors is analyzed to find the highest and lowest betweenness power in the cooperative network. Afterward, a series of recommendations are proposed based on a designed systematic intervention. Moreover, a cooperative system of pandemic crisis management would be developed based on the key actors’ experiences and the lessons learned from failures.  
CONCLUSION: Existing knowledge presents a valuable prospect for policy-makers in urban crisis management to not only establish an organizational cooperative system but also capitalize on the insights gained and contemplate pragmatic collective measures to enhance urban resilience in the face of pandemic crises.

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