How to identify key players that contribute to resilient performance: A social network analysis perspective

Abstract

Although resilience benefits from social interactions, there is a gap regarding the identification of key players that contribute to it. This study uses social network analysis (SNA) to identify those players based on the modeling of interactions associated with four abilities of resilient systems: monitor, anticipate, respond, and learn. Networks are developed for each ability, and a score is proposed for each player, combining five indicators theoretically connected to resilience: in-degree, closeness, and betweenness, which are derived from SNA, and availability and reliability, which are non-network attributes assessed through Likert-style questions. The proposal was implemented using data on 133 professionals from an intensive care unit. Five semi-structured interviews supported the interpretation of survey data and analysis of contextual factors. The ranking of key players varied across ability-based networks, and none of them excelled in all dimensions of the proposed score. The proposal bridges the gap between the role of individual players in work systems and system resilience. That occurs as the score, while being attributed to individual players, reflects their interactions with others. SNA is thus an effective analytical approach for dealing with the resilience engineering tension between individual performance and context.