Measuring and Evaluating Convergence Processes Across a Series of Group Discussions

Sarah M. Staggs (), Joseph A. Bonito () and Jennifer N. Ervin ()
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Sarah M. Staggs: Arizona State University
Joseph A. Bonito: University of Arizona
Jennifer N. Ervin: University of Pittsburgh

Group Decision and Negotiation, 2018, vol. 27, issue 5, No 2, 715-733

Abstract: Abstract As groups develop, members’ knowledge and expectations regarding the task and the group tend to converge. Such convergence allows members to anticipate and coordinate their own and others’ actions, facilitating productive group work. Using zero-history laboratory groups, this study analyzes the presence and trajectory of cognitive convergence as groups worked on a series of three similar tasks. We focus on two types of convergence: anticipatory expectations for future work, and reflective assessments regarding previous group discussions. Results indicate immediate convergence for reflective cognitions but delayed convergence for anticipatory cognitions. Associations among the different types of convergence also vary at the group- and individual-levels of analysis. The discussion addresses measurement implications of both types of convergence in regard to emergence of group-like cognitive structures.

Keywords: Cognitive convergence; Longitudinal design; Latent group models; Structuration (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10726-018-9560-3

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