Shining with the Stars? Unearthing how group star proportion shapes non-star performance

Organizations grapple with how to position and manage star employees within and across workgroups. One critical question not yet well understood is how to optimize the influence of stars on non-stars and specifically whether to concentrate together or spread out stars across workgroups. Furthermore, we lack knowledge of who is more likely to benefit from stars. To that end, we develop a theoretical model that introduces a new unit-level concept—group star proportion (GSP)—to progress understanding of how the staffing of stars, within and across workgroups, influences non-star performance. Invoking theories of vicarious learning, we explicate why GSP has a curvilinear relationship with non-star performance. Specifically, GSP positively relates to non-star performance up to a point at which there are diminishing returns. In Study 1, we tested these predictions in a field dataset in a healthcare system. In Study 2, we replicated these findings in a commercial real estate firm and expanded understanding of how GSP may serve as a cross-level moderator of non-star performance and two critical individual differences germane to learning: non-star tenure and trait negative affect. Findings offer theoretical and practical insights into how stars might be of most benefit to their non-star peers.