Browsing by Author "McCourt, Michael"
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Item Better Together: Member Proactivity Is Better for Team Performance When Aligned with Conscientiousness(Academy of Management Discoveries, 2023-05-09) Emich, Kyle; Lu, Li; Ferguson, Amanda J.; Peterson, Randall; McCourt, Michael; Martin, Sean; McClean, Elizabeth; Woodruff, Col. ToddProactivity, the tendency to create change in the work environment, typically improves team performance. This relationship is far from perfect, however. We explore inconsistencies in the team proactivity literature to shed light on an important question – when is member proactivity beneficial or dysfunctional for teams? First, we consider the composition of member proactivity at the team level and whether a simple ‘more is better’ heuristic neglects a more complex relationship linking member proactivity to team coordination and performance. Second, we explore whether proactivity is better when aligned with another individual difference focused on the propensity to plan and coordinate with others (i.e., conscientiousness). In two studies, we compare traditional additive and configurational compositional approaches to these two attributes with a new attribute alignment approach, allowing us to examine the co-occurrence of proactivity and conscientiousness within some team members relative to others. First, we find that team member proactivity-conscientiousness alignment (P-C alignment) predicts the performance of MBA consulting teams better than the other team composition models we considered. Then, we replicate this finding in a laboratory simulation, finding that it occurs because P-C alignment improves team coordination. Our results demonstrate that member proactivity is most effective for the team when it aligns with conscientiousness.Item Team Composition Revisited: A Team Member Attribute Alignment Approach(Organizational Research Methods, 2021-10-18) Emich, Kyle J.; Lu, Li; Ferguson, Amanda; Peterson, Randall S.; McCourt, MichaelResearch methods for studying team composition tend to employ either a variable-centered or person-centered approach. The variable-centered approach allows scholars to consider how patterns of attributes between team members influence teams, while the person-centered approach allows scholars to consider how variation in multiple attributes within team members influences subgroup formation and its effects. Team composition theory, however, is becoming increasingly sophisticated, assuming variation on multiple attributes both within and between team members—for example, in predicting how a team functions differently when its most assertive members are also optimistic rather than pessimistic. To support this new theory, we propose an attribute alignment approach, which complements the variable-centered and person-centered approaches by modeling teams as matrices of their members and their members’ attributes. We first demonstrate how to calculate attribute alignment by determining the vector norm and vector angle between team members’ attributes. Then, we demonstrate how the alignment of team member personality attributes (neuroticism and agreeableness) affects team relationship conflict. Finally, we discuss the potential of using the attribute alignment approach to enrich broader team research.Item Team Composition Revisited: Expanding the Team Member Attribute Alignment Approach to Consider Patterns of More Than Two Attributes(Organizational Research Methods, 2023-05-03) Emich, Kyle J.; McCourt, Michael; Lu, Li; Ferguson, Amanda; Peterson, RandallThe attribute alignment approach to team composition allows researchers to assess variation in team member attributes, which occurs simultaneously within and across individual team members. This approach facilitates the development of theory testing the proposition that individual members are themselves complex systems comprised of multiple attributes and that the configuration of those attributes affects team-level processes and outcomes. Here, we expand this approach, originally developed for two attributes, by describing three ways researchers may capture the alignment of three or more team member attributes: (a) a geometric approach, (b) a physical approach accentuating ideal alignment, and (c) an algebraic approach accentuating the direction (as opposed to magnitude) of alignment. We also provide examples of the research questions each could answer and compare the methods empirically using a synthetic dataset assessing 100 teams of three to seven members across four attributes. Then, we provide a practical guide to selecting an appropriate method when considering team-member attribute patterns by answering several common questions regarding applying attribute alignment. Finally, we provide code (https://github.com/kjem514/Attribute-Alignment-Code) and apply this approach to a field data set in our appendices.