Social networks, Teams in the workplace
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.
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Doctor of Philosophy (Ph.D.)
College of Sciences
Psychology; Industrial and Organizational Psychology
Length of Campus-only Access
Doctoral Dissertation (Open Access)
Dissertations, Academic -- Sciences, Sciences -- Dissertations, Academic
Murase, Toshio, "Measuring Multilevel Constructs Theoretical And Methodological Features Of Team Behavioral Process Under Compilational Models" (2011). Electronic Theses and Dissertations, 2004-2019. 1783.