Explaining Implicit and Explicit Affective Linkages in IT Teams: Facial Recognition, Emotional Intelligence, and Affective Tone

<p>Over 80 percent of task work in organizations is performed by teams. Most teams operate in a more fluid, dynamic, and complex environment than in the past. As a result, a growing body of research is beginning to focus on how teams’ emotional well-being can benefit the effectiveness of workplace team efforts. These teams are required to be adaptive, to operate in ill-structured environments, and to rely on technology more than ever before. However, teams have become so ubiquitous that many organizations and managers take them for granted and assume they will be effective and productive. Because of the increased use of team work and the lack of sufficient organizational and managerial sufficient best practices for teams, more research is required. Team Emotional Intelligence (TEI) is a collective skill that has been shown to benefit team performance. However, measures for TEI are relatively new and have not been widely studied. Results show TEI is a viable skill that affects performance in IT teams. In technology-rich environments, the teams’ coordination can vary on levels of the expertise needed when TEI behaviors are employed. Cooperative norms play an important role in team interactions and influence TEI. Physiological measures of team emotional contagion and TEI, as well as psychometric measures of team affective tone results show causal affective linkages in the emotional convergence model. These results suggest that combined physiological and psychometric measures of team emotion behavior provide explanatory power for these linkages in teams during IS technology system use. These findings offer new insights into the emotional states of IS teams that may advance the understanding team behaviors for improved performance outcomes and contribute to the NeuroIS literature.</p>

Name thesis:degree_name

Doctor of Philosophy in Business Administration (PhD)

Level thesis:degree_level

Dissertation

Year dc:date.available

2014

Author dc:creator

• Dunaway, Mary M.

Advisor dc:contributor.advisor

• Davis, Fred D.

Contributors dc:contributor

• Cronan, Timothy P.
• Leger, Pierre-Majorique

• Applied sciences
• Psychology
• Emotional intelligence
• Facial recognition
• Information technology
• Information technology teams
• Neurois
• Applied Behavior Analysis
• Cognitive Psychology
• Technology and Innovation

Repository record dc:identifier

https://scholarworks.uark.edu/etd/2224

OAI identifier oai:identifier

oai:scholarworks.uark.edu:etd-3763