Linking adaptation processes to team performance in high-tempo, high-stakes teamwork : a large-scale gaming perspective

Abstract

Through four interrelated studies, this dissertation examines behavioral adaptations within teams in response to planned-for and unplanned-for contingencies in extreme task environments, whether precipitated by changes within the team itself, or through a team's operational experience. This dissertation is unique in its focus on highly detailed, naturally occurring data collected longitudinally from thousands of teams. The data are taken from the Multi-player Online Battle Arena game, League of Legends (LoL). The Input-Mediator-Outcome Team Effectiveness Model provides the organizing framework for this dissertation. It casts team performance in terms of the relationship between inputs (critical team members, team familiarity, and role familiarity), mediators (such as lost member criticality) and outcomes (match win/loss, team effectiveness, and team efficiency), leading to different levels of team development.

The third study explores the impact of one input (role familiarity) on a multi-dimensional measure of team performance as output (performance effectiveness and efficiency). Role familiarity refers to the experience of an individual in executing a defined pattern of expectations and behaviors. This study hypothesizes that the importance of role familiarity is mediated by the nature and extent of team members' experience working together in defined roles. ANOVA and visualization techniques are used to explore match-level data in order to address the proposed research questions.

Finally, the fourth study examines the effect of team familiarity, role familiarity, and CTM on team performance as mediated by adaptive behaviors in executing teamwork processes through a fully tested integrated team effectiveness framework. Path Analysis is the analytical method used to test the models. The interrelated studies demonstrate that generalizations of this modeling approach can be applied to other domains where the quantification of individual and team-level workflow, role familiarity, and team familiarity are important to understanding performance.

The first study investigates the effect of losing a "critical" team member (CTM) on the performance of teams. A CTM is any individual whose presence or absence has a substantial impact on a team's performance. In this study, data from LoL gameplay from randomly sampled, ranked matches are used to examine team processes and performance outcomes when the CTM is present or absent. Statistical analysis is used to explore the effects on team performance. Initial results indicate that the presence or absence of a CTM has a significant impact on team processes and performance outcomes. This research illustrates the feasibility of exploring online gaming data for new insights into team performance, leading to a larger study on team effectiveness.

The second study evaluates the effect of two inputs (team familiarity and CTM) on team effectiveness. Team familiarity refers to team members' shared experience working with each other. Statistical data modeling techniques are used to explore these relationships. Results from this study are used to motivate further work on exploring possible mediators involved in this relationship, as discussed in the descriptions of the following two studies.