Keywords

Social networks, Teams in the workplace

Abstract

Since at least the 1950s, researchers interested in studying the dynamics of small groups have struggled with how best to measure interaction processes. Although team process measurement issues are not particularly unique in terms of content, measuring multilevel phenomena presents an interesting problem because structural aspects are integral components of emergence. The elemental content of multilevel phenomena is wholly unique and distinguishable from the elemental content of composite units, and emerges as individual behaviors compile to higher levels of analyses. Analogous to chemical structures, behavioral phenomena manifest at higher levels in different structural patterns as members connect to one another through dynamic interactions. Subsequently, multilevel phenomena are more appropriately characterized in terms of pattern in addition to the traditionally measured intensity. The vast majority of teams research conceptualizes and operationalizes multilevel phenomena based on compositional (i.e., additive) models. This approach impedes the further advancement of the science of team effectiveness by capturing content and intensity, but not structure. This dissertation argues that compilational models better capture content, intensity, and structure, and therefore represent a preferred alternative for conceptualizing and operationalizing team processes. This dissertation details measurement issues associated with compositional models in teams research, and provides concepts helpful for reconceptualizing team processes as compilational forms.

Notes

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Graduation Date

2011

Semester

Fall

Advisor

Dechurch, Leslie

Degree

Doctor of Philosophy (Ph.D.)

College

College of Sciences

Department

Psychology

Degree Program

Psychology; Industrial and Organizational Psychology Track

Format

application/pdf

Identifier

CFE0004145

URL

http://purl.fcla.edu/fcla/etd/CFE0004145

Language

English

Release Date

December 2011

Length of Campus-only Access

None

Access Status

Doctoral Dissertation (Open Access)

Subjects

Dissertations, Academic -- Sciences, Sciences -- Dissertations, Academic

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