Hostname: page-component-586b7cd67f-t7czq Total loading time: 0 Render date: 2024-11-21T10:33:32.451Z Has data issue: false hasContentIssue false
  • English
  • Français

Social Network Analysis for Implementation of the Sendai Framework for Disaster Risk Reduction in Iran

Published online by Cambridge University Press:  17 August 2021

Homa Yousefi Khoshsabegheh Open the ORCID record for Homa Yousefi Khoshsabegheh [Opens in a new window] ,
Ali Ardalan ,
Amirhossein Takian ,
Leila Hedayatifar ,
Abbas Ostadtaghizadeh  and
Behnam Saeedi
Homa Yousefi Khoshsabegheh
Affiliation:
Department of Health in Emergencies and Disasters, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
Ali Ardalan*
Affiliation:
Department of Health in Emergencies and Disasters, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
Amirhossein Takian*
Affiliation:
Department of Global Health and Public Policy, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran Department of Management and Health Economics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran Health Equity Research Center (HERC), Tehran University of Medical Sciences, Tehran, Iran
Leila Hedayatifar
Affiliation:
New England Complex Systems Institute, Cambridge, MA, USA
Abbas Ostadtaghizadeh
Affiliation:
Department of Health in Emergencies and Disasters, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
Behnam Saeedi
Affiliation:
National Disaster Management Organization, Tehran, Iran
*
Corresponding authors: Ali Ardalan, Email: [email protected]. Amirhossein Takian, Email: [email protected]
Corresponding authors: Ali Ardalan, Email: [email protected]. Amirhossein Takian, Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Background:

Stakeholders are responsible for managing the risks of disasters. Hence, appropriate, collaborative, timely interactions of involved organizations, and having a collective view of these interactions, have an important influence on the operation of the whole system. This study was aimed at social network analysis (SNA) for the implementation of the Sendai framework for disaster risk reduction in Iran.

Methods:

SNA was used in this study. A review of literature on disaster risk management (DRM) plus snowball sampling technique identified a list of 85 stakeholders. Delphi method among purposefully selected experts was used to score the relationship between the stakeholders. Louvain method, along with the modularity optimization method, was applied to identify groups of stakeholders with greater interactions. Centrality measurements were used to define organizations with key-roles in the network.

Results:

The density of this network was 0.75, which showed that not all the stakeholders were connected. The National Disaster Management Organization and Civil Defense Organization showed higher influences considering their responsibilities. A total of 3 clusters of stakeholders with specific duties that mostly interact with each other and have some interaction with other groups were recognized.

Conclusion:

Understanding the pre-disaster interaction of the network and the strengths and weaknesses of the interactions among stakeholders could help improve DRM.

Keywords

social network analysisstakeholderdisaster risk managementdisaster risk reductionSendaiIran
Type
Original Research
Information
Disaster Medicine and Public Health Preparedness , Volume 16 , Issue 4 , August 2022 , pp. 1564 - 1572
Copyright
© Society for Disaster Medicine and Public Health, Inc. 2021

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Desai, B, Maskrey, A, Peduzzi, P, De Bono, A, Herold, C. Making development sustainable: The future of disaster risk management. Global assessment report on disaster risk reduction. Genève, Suisse: United Nations Office for Disaster Risk Reduction (UNISDR); 2015.Google Scholar
Safarpour, H, Khorasani-Zavareh, D. The fourth epidemiological transition: The need for worldwide focus on reducing morbidity and mortality rates of disasters and emergencies. Shiraz E-Med J. 2019;20(9):e86746.CrossRefGoogle Scholar
UNISDR U. Sendai framework for disaster risk reduction 2015–2030. Paper presented at 3rd United Nations World Conference on DRR; 2015.Google Scholar
Wallemacq, P, Guha-Sapir, D, McClean, D, CRED, UNISDR. The human cost of natural disasters: A global perspective. Centre for Research on Epidemiology of Disasters, Université catholique de Louvain Brussels; 2015.Google Scholar
Aboelela, SW, Merrill, JA, Carley, KM, Larson, EJ. Social network analysis to evaluate an interdisciplinary research center. J Res Adm. 2007;38(1):61-75.Google Scholar
Comfort, LK, Haase TWJPWm, policy. Communication, coherence, and collective action: The impact of Hurricane Katrina on communications infrastructure. PWMP. 2006;10(4):328-343.Google Scholar
Kapucu, N. Interorganizational coordination in dynamic context: Networks in emergency response management. Connections: Soc Networks. 2005;26(2):33-48.Google Scholar
Porter, MA, Onnela, J-P, Mucha, PJ. Communities in networks. Notices Amer. Math. Soc. 2009;56(9):1082-1097.Google Scholar
Prizzia, R. The role of coordination in disaster management. In: Pinkowski J, ed. Disaster Management Handbook. 1st ed. Taylor and Francis, UK: CRC Press, 2008:75-98.Google Scholar
Wyllie, J, Lucas, B, Carlson, J, Kitchens, B, Kozary, B, Zaki, M. An examination of not-for-profit stakeholder networks for relationship management: A small-scale analysis on social media. PLoS One. 2016;11(10):e0163914.CrossRefGoogle ScholarPubMed
Saqr, M, Fors, U, Tedre, M, Nouri, J. How social network analysis can be used to monitor online collaborative learning and guide an informed intervention. PLoS One. 2018;13(3):e0194777.Google ScholarPubMed
Hedayatifar, L, Hassanibesheli, F, Shirazi, A, Farahani, SV, Jafari, G. Pseudo paths towards minimum energy states in network dynamics. Physica A: Statistical Mechanics and its Applications. 2017;483:09-116.CrossRefGoogle Scholar
Marin, A, Wellman, B. Social network analysis: An introduction. In: Scott, J, Carrington, PJ, eds. The Sage Handbook of Social Network Analysis. Thousand Oaks, CA: Sage Publications; 2011:11-25.Google Scholar
Houghton, RJ, Baber, C, McMaster, R, et al. Command and control in emergency services operations: A social network analysis. Ergonomics. 2006;49(12-13):1204-1225.Google ScholarPubMed
Kapucu, N, Augustin, ME, Garayev, V. Interstate partnerships in emergency management: Emergency management assistance compact in response to catastrophic disasters. PAR. 2009;69(2):297-313.Google Scholar
Kleinberg JJCotA. The convergence of social and technological networks. 2008;51(11):66-72.Google Scholar
Mohammadfam, I, Bastani, S, Golmohamadi, R, Saei, A, Es-Haghi, M. Applying social network analysis to evaluate preparedness through coordination and trust in emergency management. Emergency Hazards. 2015;14(4):329-340.CrossRefGoogle Scholar
Steelman, TA, Nowell, B, Bayoumi, D, McCaffrey, S. Understanding information exchange during disaster response: Methodological insights from infocentric analysis. Administration & Society. 2014;46(6):707-743.CrossRefGoogle Scholar
Varda, DM, Forgette, R, Banks, D, Contractor, NJ. Social network methodology in the study of disasters: Issues and insights prompted by post-Katrina research. Popul. Res. Policy Rev. 2009;28(1):11-29.Google Scholar
Mohammadfam, I, Bastani, S, Esaghi, M, Golmohamadi, R, Saee, A. Evaluation of coordination of emergency response team through the social network analysis. Case study: Oil and gas refinery. Saf Health Work. 2015;6(1):30-34.CrossRefGoogle Scholar
Hedayatifar, L, Bar-Yam, Y, Morales, A. Social Fragmentation at Multiple Scales. J. R. Soc. Interface. 2018;Google Scholar
Butts, CT. Social network analysis: A methodological introduction. Asian J Soc Psychol. 2008;11(1):13-41.CrossRefGoogle Scholar
Kapucu, NJC. Interorganizational coordination in a dynamic context: Networks in emergency response management. Connections. 2005;26(2):33-48.Google Scholar
Safarpour, H, Fooladlou, S, Safi-Keykaleh, M, et al. Challenges and barriers of humanitarian aid management in 2017 Kermanshah earthquake: A qualitative study. BMC Public Health. 2020;20(1):563.CrossRefGoogle ScholarPubMed
Guion, LA, Diehl, DC, and McDonald, D. Triangulation: Establishing the validity of qualitative studies. EDIS. 2011(8):1-3. doi:10.32473/edis-fy394-2011.CrossRefGoogle Scholar
Reichardt, J, Bornholdt, S. Statistical mechanics of community detection. Phys Rev E. 2006;74(1):016110.CrossRefGoogle ScholarPubMed
Blondel, VD, Guillaume, J-L, Lambiotte, R, Lefebvre, E. experiment. Fast unfolding of communities in large networks. J Stat Mech Theory Exp. 2008;P10008:1-12.CrossRefGoogle Scholar
Favre, G, Brailly, J. (2012). The SAGE Handbook of Social Network Analysis. Scott, J, Carrington, PJ (Eds). Los-Angeles, London: SAGE publications; 2012.Google Scholar
Barabási, AL. Network science. Philos Trans A Math Phys Eng Sci. 2013;371(1987):20120375.Google ScholarPubMed
Bahadori, M, Khankeh, HR, Zaboli, R, Malmir, I. Coordination in disaster: A narrative review. IJMR. 2015;2(2):273-281.Google Scholar
Cheema, AR, Mehmood, AI, Imran, M. Learning from the past: Analysis of disaster management structures, policies, and institutions in Pakistan. Disaster Prev Manag. 2016;25 ( 4 ): 449-463.CrossRefGoogle Scholar
Varvasovszky, Z, Brugha, R. A stakeholder analysis. Health Policy Plan. 2000;15(3):338-345.Google ScholarPubMed
Newman, ME. Modularity and community structure in networks. Proc Natl Acad Sci U S A. 2006;103(23):8577-8582.CrossRefGoogle ScholarPubMed
Jackson, C. Using social network analysis to reveal unseen relationships in medieval Scotland. Jackson, C. (2017). Digit Scholarsh Humanit. 2017;32(2):336-343.Google Scholar
Wyllie, J, Lucas, B, Carlson, J, Kitchens, B, Kozary, B, Zaki, M. An examination of not-for-profit stakeholder networks for relationship management: A small-scale analysis on social media. PLOS One. 2016;11(10):e0163914.Google ScholarPubMed
Bavelas, A. A mathematical model for group structures. Appl Anthropol. 1948;7(3):16-30.Google Scholar
Denny, M. Social network analysis. ISSR: University of Massachusetts, Amherst; 2014.Google Scholar
Bavelas, A. Communication patterns in task-oriented groups. J Acoust Soc Am. 1950;22(6):725-730.CrossRefGoogle Scholar
Sabidussi, G. The centrality of a graph. Psychometrika. 1966;31(4):581-603.CrossRefGoogle ScholarPubMed
Supplementary material: File

Yousefi Khoshsabegheh et al. supplementary material

Table S1

Download Yousefi Khoshsabegheh et al. supplementary material(File)
File 45.4 KB