Characterizing naval team readiness through social network analysis

Abstract

Characterizing a team's level of readiness in an efficient and objective way is important for organizations such as the military. Current methods to characterize real-time team interaction know limitations that may be addressed by social network analysis techniques. The purpose of the current field study was to investigate the usefulness of these techniques by applying them to two naval teams, one more experienced than the other. We observed how these teams responded during an actual training exercise to a comparable scenario and recorded their communication processes. The descriptive, non-inferential, results showed that, at the network level, the more experienced team displayed higher levels of information sharing and team member participation compared to the less experienced team. At the actor level, the team coordinator played a much more central role in the more experienced team, whereas in the less experienced team this role was taken up by various other team members.

Team Communication Patterns in Critical Situations

“…For all consecutive dyadic events with duplicate timestamp, events were separated by an offset of 1 ms in chronological order. Nondyadic events (directed at more than one receiver) were considered separately by giving the same offset of 1 ms (ms), in order of targeted recipients (as also used by Schraagen & Post, 2014). An offset of 1 ms was chosen to minimize the effect of the adaptation.…”

“…According to Woods and Hollnagel (2006), such adaptation of communication patterns might be generalizable across teams and domains. Multiple studies have applied social network analysis (SNA; see Wasserman & Faust, 1994) to teams in various domains (e.g., medical [Barth et al, 2015], military [Houghton et al, 2015; Schraagen & Post, 2014], and sports [Lusher et al, 2010]). Although SNA provides detailed measures of, amongst others, the centrality of actors in networks, it is limited in its ability to study how communication patterns develop over time.…”

Role network measures to assess healthcare team adaptation to complex situations: the case of venous thromboembolism prophylaxis

“…Team adaptation has been studied using multiple different methods including analysis of team performance in simulated environments (Burtscher et al 2011), team cognitive work analysis (Ashoori et al 2014;Pfautz and Pfautz 2009), and direct team observations utilizing questionnaires (Schraagen 2011). Social network analysis (SNA) is another method that can be used to measure team adaptation as the complexity of a situation changes (Baber et al 2013;Barth et al 2015;Houghton et al 2006;Schraagen and Post 2014). SNA, using social network metrics based on various data (e.g., survey, observation, interview) (Valente 2010;Wasserman and Faust 1994), provides a way to quantitatively evaluate team adaptation (Houghton et al 2006).…”

“…Within human factors and ergonomics, SNA has been used to understand organisational and team processes, such as information sharing and coordination. For example, SNA was used to study command and control operations within military and emergency services (Baber et al 2013;Houghton et al 2006;Houghton et al 2015;Roberts et al 2018); to evaluate and characterise naval team readiness (Schraagen and Post 2014); to explore changes in the transportation system from the introduction of Connected and Autonomous Vehicles (Banks et al 2018); to measure knowledge across a team and its effect on cohesion and performance (Espinosa and Clark 2014); to measure interruptions (McCurdie et al 2018) and influential team members (Fong et al 2017) in intensive care units; and to demonstrate a positive relationship between the number of nurse-to-nurse advice-seeking interactions about safe patient handling and frequency of patient-handling equipment use (Hurtado et al 2018). Euerby and Burns (2014) used SNA to measure information sharing in an online community comprised of university students, university faculty, community activists and members of local government, finding that human factors design changes to the website increased communication and connections between the website members.…”

“…Euerby and Burns (2014) used SNA to measure information sharing in an online community comprised of university students, university faculty, community activists and members of local government, finding that human factors design changes to the website increased communication and connections between the website members. Various methods were used in these studies to collect SNA data including survey (Espinosa and Clark 2014;Fong et al 2017;Hurtado et al 2018), observations (Houghton et al 2006;McCurdie et al 2018;Roberts et al 2018;Schraagen and Post 2014), cognitive work analysis (Houghton et al 2015), review of documents (Baber et al 2013), and website activity logs (Euerby and Burns 2014). Barth et al (2015) used SNA to examine team adaptation to varying levels of task complexity during paediatric cardiac surgeries.…”