Reaping what you sow: A multilevel investigation of allocation from a pool of workers to teams.

Organizations commonly face the task of allocating workers to mutually exclusive teams from finite worker pools-a process called seeding. The approach an organization takes to seeding affects within-team and between-team distributions of performance or other outcomes. Substantial prior research explains the effects of combinations on team performance, but little is known about between-team combinations. I extend prior theory to a higher level of analysis, elaborating on the nature and function of between-team combinations on organization-level performance. I use a simulation method to identify seeding approaches that can maximize organizational outcomes in various contexts. Results uncover conditions under which the seeding approach is irrelevant to outcomes, instances where random assignment outperforms intentional seeding, and instances where particular approaches produce the most favorable outcomes. I discuss the implications of multilevel combinations for theory and practice. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Collective turnover response over time to a unit-level shock.

This work provides a theoretical explanation for the mechanisms that can drive collective turnover in response to a unit-level shock by applying event systems theory to collective turnover. Specifically, we recognize the importance of modeling a disruption phase following a shock, the social mechanisms that influence the collective turnover response, and boundary conditions on the impact of the shock on the collective turnover response. We examine collective turnover following 239 general manager departures in a large U.S. retailer from 2012 to 2014 to observe how a unit-relevant shock affects the collective turnover response across time. In doing so, we identify and explain a potential delay before the disruption phase and the cumulative abnormal voluntary turnover that occurs in the disruption phase following a unit-level shock. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Individualized pay-for-performance arrangements: Peer reactions and consequences.

We contribute to understanding the previously unrecognized consequences of individualized employment arrangements on the relationship between pay and performance. Increases in the application of pay-for-performance (PFP) idiosyncratic deals (PFP i-deals) raise questions about how individualized PFP arrangements affect the performance of peers who do not receive such customized deals. As pay systems become more individualized, understanding the economic ramifications of how PFP i-deals affect peer performance is essential for understanding the total unit effects of implementing PFP i-deals. To examine these peer effects, we explored peer responses to PFP i-deals and identified boundary conditions on broad theoretical assumptions underlying the conclusion that PFP increases unit performance. We tested our predictions by applying multilevel random-coefficient discontinuous growth models to a sample of 451 peers nested in 117 business units of a for-profit health-care organization. Immediately after PFP i-deal implementation in the unit, the performance level of peers was negatively affected. Additionally, peer performance trends after PFP i-deal implementation were lower than they were before the PFP i-deal implementation. Our study also identified contextual factors that influence peer responses to PFP i-deal implementation. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

A theoretical assessment of dismissal rates and unit performance, with empirical evidence.

Unit-level dismissal rates have rarely been studied, but utility analysis suggests that increasing dismissal rates can improve performance by increasing the contribution of a unit's workers. This proposition comports with other theory around dismissals but contradicts substantial empirical evidence. We extend the staffing utility framework, taking a multilevel perspective and attending to both within- and between-unit effects of dismissal rate practices. We test our theory in monthly observations from 1,047 retail locations over almost 3 years. Our results explain how between-unit associations between workforce contribution and unit performance can mask the within-unit benefit of increasing dismissal rates. This insight reconciles theory with prior evidence, although some researchers have interpreted them to be at odds. A better understanding of the complex causes and consequences of dismissal rates has the potential to open new avenues of research and inform practice in ways that promote unit effectiveness. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Improving the measurement of group-level constructs by optimizing between-group differentiation.

The ability to detect differences between groups partially impacts how useful a group-level variable will be for subsequent analyses. Direct consensus and referent-shift consensus group-level constructs are often measured by aggregating group member responses to multi-item scales. We show that current measurement validation practice for these group-level constructs may not be optimized with respect to differentiating groups. More specifically, a 10-year review of multilevel articles in top journals reveals that multilevel measurement validation primarily relies on procedures designed for individual-level constructs. These procedures likely miss important information about how well each specific scale item differentiates between groups. We propose that group-level measurement validation be augmented with information about each scale item's ability to differentiate groups. Using previously published datasets, we demonstrate how ICC(1) estimates for each item of a scale provide unique information and can produce group-level scales with higher ICC(1) values that enhance predictive validity. We recommend that researchers supplement conventional measurement validation information with information about item-level ICC(1) values when developing or modifying scales to assess group-level constructs. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

A conceptual and empirical analysis of the cognitive ability-voluntary turnover relationship.

Despite much research into cognitive ability as a selection tool and a separate large literature on the causes of voluntary turnover, little theoretical or empirical work connects the two. We propose that voluntary turnover is also a potentially key outcome of cognitive ability. Incorporating ideas from the person-environment fit literature and those regarding push and pull influences on turnover, we posit a theoretical connection between cognitive ability and voluntary turnover that addresses both why and how voluntary turnover is related to cognitive ability. Integrating data from 3 different sources, our empirical analyses support the theoretical perspective that the relationship between cognitive ability and voluntary turnover depends on the cognitive demands of the job. When the cognitive demands of a job are high, our findings support the hypothesized curvilinear relationship between cognitive ability and voluntary turnover, such that employees of higher and lower cognitive ability are more likely than medium cognitive ability employees to leave voluntarily. With regard to jobs with low cognitive demands, our data are more consistent with a negative linear relationship between cognitive ability and voluntary turnover, such that higher cognitive ability employees are less likely to leave voluntarily. We also examine the role of job satisfaction, finding that job satisfaction is more strongly linked to voluntary turnover in jobs with high cognitive demands.