Abstract
We develop and test a holistic model of how team members’ swift judgments about a prospective team member impact their selection decisions and how accurate those judgments are in predicting the prospective member’s performance. Applying the social psychology literature on person perception to the organizational literature on team member selection, we argue that team members’ perceptions of the prospective member’s competence primarily shape their predictions about the prospective member’s task-related performance in the team, whereas perceptions of warmth primarily shape predictions about the prospective member’s interpersonal contextual performance in the team. We further propose that, although team members rely on both performance predictions when choosing a prospective member, predicted task-related performance receives more weight than predicted interpersonal contextual performance, and that the importance of predicted interpersonal contextual performance is elevated when team task interdependence is high. Importantly, we theorize that the predictions about task-related performance show good accuracy, whereas the predictions about interpersonal contextual performance do not, which makes the reliance on the latter erroneous. Across two studies utilizing prospective members’ actual task-related and interpersonal contextual performance (objective and peer-rated), as well as team members’ predictions about such performances, we found support for our predictions. Our research resolves several outstanding puzzles in the literature on person perception, integrates it into organizational research, and offers novel and actionable insights for selecting prospective team members.
Original language | English |
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Article number | 104206 |
Journal | Organizational Behavior and Human Decision Processes |
Volume | 173 |
DOIs | |
Publication status | Published - Nov 2022 |
Bibliographical note
Funding Information:We thank Marko Pitesa for providing us with extensive feedback on previous versions of this manuscript. We also thank Renee-Claire Belting and Alexandra Androulidaki for help with coding as well as Sheila Shukla and Claudia Heese with extensive help in running Study 2. Finally, we are grateful for the engagement and extremely constructive feedback provided by Associate Editor ChenBo Zhong and three annonymous reviewers throughout the review process.
Publisher Copyright:
© 2022 Elsevier Inc.