The microdynamics of team diversity and collaboration networks

Abstract

Current team diversity research is largely equivocal regarding the direct effects of intrateam differences on team processes and performance. In response, scholars encourage a more complex and multi-level approach to understanding this phenomenon. In this dissertation, I contribute to this effort by theorizing an emergent network approach to team diversity—that is, a dynamic, relational and structural approach to interpersonal differences. Given the historical and current emphasis on collective-level theories and measures of diversity in the team literature, I argue that this perspective will provide a more detailed account of the perceptions and behaviors associated with differences within teams. Through this paradigm, I ask two interrelated research questions. First, how does the structure of team diversity impact dyadic task-related collaboration over time within the team? Second, how does the heterogeneity of dyadic collaboration affect team performance? These questions are tested with a combination of archival and laboratory data using stochastic actor-oriented models (SAOMs), which enables the prediction of network evolution over time.