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When Speaking Up Divides: Voice Modality Divergence, Behavioral Faultlines, and Team Performance

Submitted:

03 April 2026

Posted:

07 April 2026

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Abstract
Speaking up is widely regarded as a critical driver of team learning and performance, yet research typically examines promotive and prohibitive voice as separate predictors rather than as a collective behavioral system. We introduce Voice Modality Divergence (VMD), a team-level composition construct capturing the extent to which teams collectively differentiate and balance two distinct voice modalities: promotive voice oriented toward improvement and prohibitive voice oriented toward harm prevention. Drawing on ambidexterity, information integration, and team learning theories, we argue that VMD enhances team performance by enabling teams to integrate complementary improvement. At the same time, we theorize that the same voice landscape can generate a divisive social structure. We conceptualize Voice-Based Faultline Strength (VFS) as a behavioral segmentation that emerges when high levels of both promotive and prohibitive voice cluster within one subgroup while low levels of both cluster within another, creating rigid subgroup boundaries and fractured communication. Building on faultline and social categorization theories, we argue that stronger VFS directly undermines team performance by restricting cross-subgroup exchange, intensifying misattributions, and fragmenting psychological safety. Using data from intact work teams (N = 41 teams), results support both hypotheses: VMD is positively associated with team performance, whereas VFS is negatively associated with team performance, above and beyond average voice levels and team controls. This study advances the voice literature by shifting attention from the frequency of speaking up to the structural configuration of voice modalities within teams, highlighting that teams benefit from balanced voice patterns but suffer when voice becomes behaviorally segregated into subgroups.
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Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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