Knowledge that Transforms

Compensation plays a pivotal role in shaping employee behavior, motivation, and well‐being. Although extant research has explored various dimensions of compensation, questions about how important pay is to employees and concerns (on the part of employers and/or employees) about the unintended negative (in addition to intended positive) consequences of pay and pay for performance (PFP) decisions remain. For employers, these include claims that PFP can provoke undesirable employee behaviors and undermine employee intrinsic motivation and creativity, and that PFP‐related organizational change is difficult to implement successfully. For employees, concerns include claims that PFP programs negatively affect employee health, well‐being, and financial security. We address and evaluate these concerns in light of theory and evidence and emphasize the need to examine not only the potential negative but also the potential positive consequences of pay and PFP decisions. The strength of PFP effects is greater to the degree that pay is important to employees. Further, in the global context, where much of the world has lower income and higher poverty rates than in the higher productivity economies (e.g., the United States, Europe), we often study pay's importance and thus PFP's impact may be greater.

The purpose of this article is primarily to evaluate whether machine learning (a form of artificial intelligence) can meet scientific, professional, and legal principles of personnel selection based on the rapidly accumulating research literature in Human Resource Management (HRM). It does so by addressing a series of questions in terms of what is known in the current research literature on these principles and related topics and by proposing a research agenda for what else needs to be studied. The review shows that there is enough current scientific evidence on the value of ML to support its use. ML tools are able to meet the basic principles of personnel selection and better meet many other very important principles. In addition, ML for personnel selection decisions is not a “black box” and can be understood and explained. It does not increase the legal risks from hiring, although it may require some additional steps in a few jurisdictions. There are uses of ML in selection that most organizations should be considering. Customized procedures will require good data, but generic vendor products may also serve some needs. Additional expertise may be required of HRM professionals, but not necessarily at a high level that would require new staffing or consultant expense. The availability of large language models (LLMs) may render unproctored remote assessments vulnerable to cheating, and all narrative candidate information provided in the future susceptible to AI‐generated text, resulting in more questions than research answers at this stage. The article ends with practical and theoretical implications for the use of ML in selection.

This study examines the impact of executive pay cuts on executive turnover. While previous research has largely focused on the drivers of pay increases of top management team (TMT) members or the effects of their relative pay standing on executive behavior, the prevalence and consequences of pay cuts have received limited attention. Drawing on temporal comparison theory, I argue that executive pay cuts are positively associated with executive turnover. I then propose that the impact of pay cuts on executive turnover depends on contextual cues that influence how executives interpret these cuts. Specifically, I argue that the effect is stronger for salary cuts than for pay‐for‐performance (PFP) cuts. I also argue that the impact of a pay cut is stronger when an executive is paid below the TMT pay level and when few other TMT members experience similar cuts. I test these predictions on a large longitudinal sample of U.S. firms and find empirical support. These results highlight the importance of temporal comparisons in executive pay evaluation processes.

Most research on family demands has been conducted at the individual level, showing that they can negatively influence employees' abilities to manage the work‐family interface. We challenge this existing paradigm by arguing that at the team level, family demands diversity (i.e., differences among members of the same team with respect to their family demands) can enable the entire team to better manage the work‐family interface. Drawing on the categorization‐elaboration model and social exchange theory, we found that family demands diversity was indirectly and positively related to team effort through team backup behavior and team work‐to‐family conflict, and these effects were stronger when team family identity was low and supervisor family support was high. We discuss the theoretical implications of our findings and the practical implications for HR policies and practices.

Leveraging theories from the friendship, contact, and collective action literatures we examine the effects of a unique learning function of cross‐race friendships—discrimination awareness—on workplace allyship. Using field and experimental designs, we found that this function of cross‐race friendships creates a sense of moral outrage that motivates Whites to engage in and support allyship at work. This function predicted allyship behaviors and was resilient to ally risk, which reflects organizational sanctions for voicing concerns about racism. Robustness tests showed that other forms of interracial contact (positive/negative contact; residential, family, and work group diversity) had little effect on allyship and the effects of this friendship function held when we controlled for them. This function also contributed explanatory power beyond individual differences in race‐related ideologies and personality traits, such as social dominance orientation and beliefs in the malleability of prejudice. The relationship lens offered here brings new theoretical traction to the field of allyship and illustrates the potential of cross‐race friendships as sources of learning and agents for organizational change.

Frontline service workers are crucial to service delivery and have been a long‐standing focus of research, with scholars and practitioners alike maintaining an interest in their effective management. As technology increasingly transforms this context, the way in which managers in service organizations communicate with frontline workers has also evolved, with a notable increase in the use of enterprise social media (ESM). This study investigates the idea that it is not just ‘what’ management says (service‐oriented messaging) but ‘the way’ they say it (via ESM) that matters. Drawing on interviews with 36 informants and guided by signaling theory, this study explores how ESM influences customer‐focused signaling via management communication and HR implementation in the frontline service context, fostering conditions for a service climate. Findings reveal that ESM's affordances can potentially enhance service climate by strengthening HR system strength, promoting voice, and fostering informal leadership. However, risks such as manager role ambiguity, perceptions of mixed messaging, and over‐surveillance are also identified. This study highlights the double‐edged implications of ESM in its shaping of service‐oriented signaling and emphasizes the importance of the signaling environment in realizing its benefits while mitigating its risks.

As more organizations move to remote hiring assessments, important questions emerge as to the effects on scores, racioethnic, and gender subgroup differences, and candidate reactions. We compare scores of candidates assessed remotely under proctored conditions ( N = 902) versus onsite ( N = 891) in an actual selection context in the same organization, in the same time period, and on the same cognitive ability tests, case exercises, and structured interviews. Controlling for job, there were no differences for cognitive ability tests or case exercises in the remote environment, but higher scores for structured interviews, leading to a slightly higher total score for all assessments combined and a 5% increase in the overall passing rate. Within groups, Hispanic or Latino candidates performed better on the remote cognitive ability test compared with Hispanic or Latino candidates onsite, while Asian candidates performed better remotely for the case exercise. All subgroups performed better on the remote structured interview compared with their onsite counterparts. No between‐group differences emerged by racioethnicity, but women outperformed men on the remote cognitive ability test compared to onsite. Candidate fairness reactions did not differ by test environment for any assessments or subgroups. We conclude that: (1) remote proctored assessments will not create lower overall passing rates (i.e., fewer candidates for hire); (2) differences in remote assessment scores may depend on the type of assessment, with the greatest positive differences for structured interviews; (3) remote assessments do not disadvantage racioethnic minority candidates or candidates overall; and (4) remote assessments do not reduce candidate fairness reactions.

Existing human resource (HR) theory highlights that differences in perceptions of HR practices between leaders and subordinates have a critical impact on employee outcomes. We extend such literature by drawing on frame‐of‐reference theory to develop and test a model examining how different patterns of (dis)agreement in leader and subordinate employee HR attributions affect employee well‐being. Specifically, we conceptualize that leaders and subordinates form (dis)similar frames of reference based upon employee well‐being HR attribution, which impacts employee well‐being through organization‐based self‐esteem (OBSE) in different ways. Using polynomial regression and response surface modeling, our results confirm our hypotheses to show that leader–subordinate agreement on employee well‐being HR attribution positively impacts OBSE, with a stronger effect when such attribution agreement is high rather than low. Furthermore, when subordinates have a higher level of employee well‐being HR attribution compared with the leader, there is a more pronounced positive impact on OBSE, which, in turn, enhances employee well‐being. We discuss the theoretical and practical implications of our study to the HR literature.

In this research, we aim to further our understanding of supervisors' enactment of psychosocial risk management and their own psychological responses to supporting employees through stressful work situations. Informed by event system theorizing and the special case of affective events, we examined 342 employee critical events of a stressful nature through the eyes of the supervisor. Thematic analysis revealed 16 supervisor actions that were aggregated into nine supervisor action themes that supervisors evaluated for stressfulness and effectiveness. Clustering stressfulness and effectiveness scores revealed the emergence of three supervisor groups: favorable, unfavorable, and challenge. Multinomial logistic regressions demonstrated that both organizational and supervisor psychosocial risk management capabilities reduced the odds of supervisors developing unfavorable psychological responses in relation to their supervisor action, whereas supervisors with time pressure and psychological distress had increased odds. In addition, supervisors experiencing psychological distress had a twofold likelihood of experiencing their chosen action as both stressful and effective, calling into question the potential for future benefits to arise from what might be otherwise considered a challenge experience. Overall, our findings demonstrate that pre‐existing features of the supervisor's own psychosocial work environment shape their psychological responses to having enacted psychosocial risk management, irrespective of the type of supervisor action.

Drawing on the organizational identification perspective, this paper proposes that employee‐friendly workplace practices can positively impact employees' innovation productivity through their identification with the organization. Using a sample of 2642 firm‐year observations from public firms in the United States, a positive relationship was found between employee‐friendly workplace practices and employee innovation productivity, which was mediated by identification with the organization. The results also showed that the employee professional human capital dampened the relationship between employee‐friendly workplace practices and employee innovation productivity. Finally, the mediated relationship between employee‐friendly workplace practices and employees' innovation productivity through organizational identification was moderated by employees' professional human capital, such as when employees are credentialed knowledge workers.