Stars--employees with disproportionately high and prolonged (a) performance, (b) visibility, and (c) relevant social capital--have garnered attention in economics, sociology, and management. However, star research is often isolated within these research disciplines. Thus, 3 distinct star research streams are evolving, each disconnected from the others and each bringing siloed theoretical perspectives, terms, and assumptions. A conceptual review of these perspectives reveals a focus on the expost effects that stars exert in organizations with little explanation of who a star is and how one becomes a star. To synthesize the stars literature across these 3 disciplines, we apply psychological theories, specifically motivation theories, to create an integrative framework for stars research. Thus, we present a unified stars definition and extend theory on the making, managing, and mobility of stars. We extend research about how and why employees may be motivated to become stars, how best to manage stars and their relationships with colleagues, and how to motivate star retention. We then outline directions for future research.

This study builds from Context-Emergent Turnover (CET) theory to examine dynamic properties of turnover rates that include: (1) changing quality and quantity of the human capital resources that depart, (2) changing turnover dispersion (i.e., how distributed turnover events are over time), and (3) changing quality and quantity of replacement hires. We examine these properties using data drawn from retail employees nested within stores of a prominent U.S. retail chain over five quarters and show that the turnover rate (level) is conceptually and empirically distinct from turnover rate change, and that the two interact with each other to influence changes in unit performance. We also find that the relationship between turnover rate change and change in unit performance is moderated by both the quality of those who leave as well as turnover dispersion. Overall, we contribute to turnover rate, staffing, and human capital resource literatures by testing core CET theory propositions to show when, why, and how turnover rate change and replacement hires, as part of a holistic human capital resource system, influence unit performance. ABSTRACTThis study builds from Context-Emergent Turnover (CET) theory to examine dynamic properties of turnover rates that include: (1) changing quality and quantity of the human capital resources that depart, (2) changing turnover dispersion (i.e., how distributed turnover events are over time), and (3) changing quality and quantity of replacement hires. We examine these properties using data drawn from retail employees nested within stores of a prominent U.S. retail chain over five quarters and show that the turnover rate (level) is conceptually and empirically distinct from turnover rate change, and that the two interact with each other to influence changes in unit performance. We also find that the relationship between turnover rate change and change in unit performance is moderated by both the quality of those who leave as well as turnover dispersion.Overall, we contribute to turnover rate, staffing, and human capital resource literatures by testing core CET theory propositions to show when, why, and how turnover rate change and replacement hires, as part of a holistic human capital resource system, influence unit performance.Collective turnover is a phenomena of considerable practical importance and scholarly interest. Three recent meta-analyses (Hancock, Allen, Bosco, McDaniel, & Pierce, 2013;Heavey, Holwerda, & Hausknecht, 2013; Park & Shaw, 2013) report a negative turnover rateunit performance relationship. While this research has provided many insights, most of the primary studies examine static turnover rates, treat each employee departure identically, and ignore replacements. Examining turnover in isolation is necessarily limited because real-world turnover is not isolated but rather embedded within broader dynamic systems. Indeed, Price (1977: 118) postulated that, ". . . it may be that it is not the absolute amount of turnover which is significant for effectiveness, but whether ...

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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.