Team Composition Revisited: A Team Member Attribute Alignment Approach

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Organizational Research Methods

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Research 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.

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This is the Accepted Manuscript version of Emich, K. J., Lu, L., Ferguson, A., Peterson, R. S., & McCourt, M. (2022). Team Composition Revisited: A Team Member Attribute Alignment Approach. Organizational Research Methods, 25(4), 642–672. https://doi.org/10.1177/10944281211042388. This article was original published in Organizational Research Methods. The version of record is available at https://doi.org/10.1177/10944281211042388. © The Author(s) 2021.

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Emich, K. J., Lu, L., Ferguson, A., Peterson, R. S., & McCourt, M. (2022). Team Composition Revisited: A Team Member Attribute Alignment Approach. Organizational Research Methods, 25(4), 642–672. https://doi.org/10.1177/10944281211042388

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