Applying social network analysis to evaluate preparedness through coordination and trust in emergency management

Abstract

The purpose of this paper is to examine the status of the preparedness within emergency response team (ERT) in a refinery. Preparedness was investigated through trust and coordination relationships. Social network analysis as a quantitative approach was utilized in this research. To do this, social network analysis (SNA) indicators including density, degree, reciprocity and transitivity were utilized as a whole network. These indicators were calculated at the levels of first-line, supportive and whole teams. The required data were collected through structured interviews and were analyzed using UCINET 6.0 social network analysis program. The results of this study indicate that first-line teams can play a critical role in ERT, which is related to a higher level of SNA indicators and consequently the preparedness between team members can be easily achieved. In addition, the findings for the supportive teams revealed that they had relatively a low level of cohesion. However, the results of whole networks among all of teams had low level of cohesion that is a key challenge for performance of ERT. According to statistical results, there is a high correlation (82%) between trust and coordination networks. The finding of SNA provides a main opportunity for managers and planners to detect preparedness challenges based on coordination and trust ties among response teams of emergency management. This research suggests that fundamental efforts along with evaluation of the effectiveness of programs are needed to improve the presented situations and in order to optimize preparedness between response teams.

Collaborative emergency preparedness and response to cross-institutional outbreaks of multidrug-resistant organisms: a scenario-based approach in two regions of the Netherlands

“…The data on collaboration between healthcare actors was analysed using social network analysis techniques. These techniques have been successfully applied in previous research on infectious disease control in the Netherlands (Kraaij-Dirkzwager, M.M., et al, Improving outbreak management through network analysis, in preparation) and Australia [20] and, in research on disaster management, these methods are applied frequently [13, 21, 22].…”

Critical Review of Social Network Analysis Applications in Complex Project Management

“…The determinants of the nodes' influence when using centrality measures in risk and coordination networks were different. For coordination networks, network Mohammadfam et al (2015) used out-degree centrality to identify those members who had a greater influence.…”

A scoping review on the current and potential use of social network analysis for evaluation purposes

“…Example 2: Finer et al 2010The nature of reproductive health policies in various states was explained by interstate influence (regional opinion leader influence and proximity influence) combined with other factors such as socio-economic status and governmental institutions. might be due to the difficulty of demonstrating the link between the internal network configuration and external network effects empirically (Albrecht et al, 2014;Cross et al, 2009;Friedman et al, 2007;Gold et al, 2008;Luke et al, 2010;Mohammadfam et al, 2015;Provan et al, 2005). Despite these difficulties, evaluators might be tempted to make bold statements about external network effects on the basis of network metrics which describe internal network processes.…”