ABSTRACT Employees' bridging social capital (EBSC), conceptualized as the collective bridging social capital that employees bring into the organization, has been recognized as a potential resource for fostering organizational resilience (i.e., the ability to survive and thrive when confronted with unexpected disruptions and challenges), especially for small and medium‐sized enterprises (SMEs) operating in a turbulent business environment. However, the questions of how and when EBSC relates to organizational resilience remain underexplored. Drawing on dynamic capabilities theory, we propose that knowledge sharing—a dynamic and emergent process where knowledge is introduced, exchanged, combined, and integrated within organizations—represents a key process through which EBSC may be associated with organizational resilience. We further propose that this mechanism is stronger in organizations that extensively implement high‐involvement work practices (HIWPs). Using data from 1131 participants (including top management team members, middle‐level managers, and entry‐level employees) across 175 SMEs in Nigeria, we find that the relationship between EBSC and knowledge sharing, as well as the indirect association between EBSC and organizational resilience via knowledge sharing, is stronger when HIWPs are high rather than low. These findings highlight the importance of HIWPs in leveraging EBSC to enhance organizational resilience, providing practical insights for SMEs seeking to harness EBSC for organizational advantages.

ABSTRACT Inclusion is a cornerstone of success for organizations and society, yet inclusion is not guaranteed. Building on inclusive leadership research and relational models theory, we argue that inclusion cannot manifest without systematic effort and planning by leaders. Unfortunately, few resources exist to help leaders plan and enact specific inclusion behaviors. To address this, we introduce the “Leader Success Bot,” an innovative conversational chatbot designed to help leaders develop daily inclusion action plans. Through our immersive longitudinal design and mixed methods data, we advance the taxonomy of inclusive leader behaviors and test the impact of inclusion planning on leaders and followers. We demonstrate how equality matching is an overlooked relational model that is a pivotal relational dynamic for inclusion. Across two studies, our quantitative and qualitative findings show that equitable exchanges by leaders can foster a deeper sense of belonging and community. As leaders interact with the chatbot, both leaders and followers are more likely to accomplish their goals. Additionally, followers' inclusion climate and psychological safety benefited, leading to a decrease in turnover intentions. Our findings underscore the potential of chatbots to support inclusive leadership training and development by providing leaders with a structured, scalable platform for continuous reflection and growth. This research advances theoretical understanding of relational inclusion dynamics and offers practical insights and a scalable tool for HR managers seeking to build more inclusive, psychologically safe cultures.

ABSTRACT While increasing evidence supports the workplace benefits of green human resource management (HRM) practices, this research explores how and when employees' experiences with these practices influence their green behaviors at home. Drawing on the work‐home resource model, this study examines the dual mechanisms of green job demands and resources while also exploring the moderating role of proactive vitality management. Study 1, a four‐wave time‐lagged survey, revealed that experienced green HRM practices were associated with both green job demands and green job resources. On the one hand, green job demands led to increased green job fatigue, which in turn reduced green behaviors at home. On the other hand, green job resources fostered green self‐efficacy, which subsequently enhanced green behaviors at home. Importantly, the negative indirect relationship between green HRM practices and green behaviors at home via green job demands and green job fatigue was stronger when employees' proactive vitality management was low, whereas the positive indirect relationship via green job resources and green self‐efficacy was stronger when proactive vitality management was high. Study 2, a four‐wave cross‐lagged survey, replicated the findings of Study 1 and further clarified the causal direction of these relationships. This research contributes to the literature on green HRM practices by uncovering their cross‐domain implications and highlighting both their benefits and costs.

ABSTRACT Reflecting a more balanced employer–employee relationship in which employees have latitude to shape aspects of their employment, idiosyncratic deals (i‐deals) are voluntary, personalized, nonstandard agreements that employees negotiate with their employers. In teams, i‐deals differentiation (i‐deals D ), the extent to which the degree of these arrangements varies across members, is a key form of HR differentiation. While research has largely emphasized its negative effects, we propose that the impact of i‐deals D on team effectiveness depends on the type of i‐deals. We focus on career, flexibility, and task i‐deals, the most common types of i‐deals that employees across different jobs can negotiate with their manager. Drawing on social comparison theory, we argue that career and flexibility i‐deals D relate positively to team relationship conflict, and in turn associate with lower customer‐related outcomes. In contrast, task i‐deals D relate negatively to team relationship conflict, and subsequently associate positively with customer‐related outcomes. We test our model in two samples: a field study with three‐source data collected from 59 stores of a national restaurant chain located in the United States (Study 1) and a field study with two‐source data collected from 108 teams from three service companies located in China (Study 2). Across both studies, flexibility i‐deals D and task i‐deals D had a negative and a positive association, respectively, with team customer‐related outcomes via team relationship conflict, while career i‐deals D was unrelated to our outcomes of interest. We advance the literatures on i‐deals and HR differentiation, and offer practical insights into the implementation of i‐deals D in teams.

ABSTRACT 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.

ABSTRACT The phrase “quiet quitting” has become a popular topic within the workplace and academia. However, the nomological network of quiet quitting is unclear. We contribute to quiet quitting research by incorporating organizational justice and job characteristics theories with a psychological contract and social exchange lens to illuminate antecedents and outcomes of quiet quitting. Prior to doing so, we address the conceptual and measurement challenges that threaten the knowledge accumulation of quiet quitting research. Using a qualitative study ( N = 42) and prior research, we disentangle quiet quitting from its antecedents and outcomes to define it as intentionally performing to the minimum requirements of the job . We then develop a measure of quiet quitting across a subject matter expert review ( N = 51), a naïve rater review ( N = 90), and an assessment of the measure's psychometric properties ( N = 198). Finally, we assess our conceptual model ( N = 540) and find that psychological contract fulfillment has a negative indirect effect on quiet quitting through job satisfaction. Furthermore, psychological contract breach increases quiet quitting through job satisfaction. We find that quiet quitting subsequently increases CWBs and decreases OCBs. Our findings point toward an optimistic outlook: by accurately communicating expectations regarding organizational justice and job characteristics, human resource managers may be able to limit the prevalence of quiet quitting and subsequent detrimental behaviors within their organizations.

ABSTRACT Bonuses are notoriously used to motivate workers. How effective are they at doing so, and might there be unintended consequences? We investigated the effectiveness of bonuses based on game profitability on the motivation of video game developers by examining specific bonus characteristics that align with advice derived from expectancy theory. We also investigated if bonuses encouraged or discouraged moral engagement and corner‐cutting behavior through their effects on work motivation as conceptualized through self‐determination theory. Company data on bonus characteristics coupled with surveys from 1024 game developers in a video game company indicated that the size of the last received bonus did not influence current work motivation. Uncertain probability of getting the next bonus installment was related to a lack of motivation, while more certain probability was related to higher intrinsic motivation. The probable size of the next bonus was related to lower external regulation and to higher intrinsic motivation, contrary to predictions from most motivation theories. Both probability certainty and bonus size probability were indirectly negatively associated with moral disengagement and corner‐cutting behaviors via decreasing amotivation and external regulation. Overall, results show that the bonus system in this company had limited effects on motivation and on discouraging deviant behaviors and point to how such systems can be improved using advice from theory.

ABSTRACT Existing research often highlights the negative consequences of algorithmic management (AM) for platform workers. By contrast, less is known about what, how, and when AM may produce both positive and negative outcomes. Drawing on attribution theory, this study examines the dual effects of core AM dimensions (i.e., algorithmic recommending, restricting, evaluating, and rewarding) on platform workers' perceptions of work overload and customer‐oriented service behavior. A two‐wave survey of 213 online platform workers in China reveals that algorithmic recommending and rewarding improve customer‐oriented service behavior and reduce work overload through AM commitment attributions. However, AM control attributions link algorithmic restricting, recommending, and evaluating (the latter two at low algorithmic transparency) to increased work overload. Algorithmic transparency moderates these effects, reducing the negative impacts of AM through AM control attributions. These findings contribute to a more nuanced understanding of the dual effects of core AM dimensions and provide practical insights for platforms seeking to enhance service quality while supporting worker well‐being.

ABSTRACT The field of strategic human resource (HR) management has shown an increasing focus on how employees perceive and react to their organization's HR practices. In this perspective, employees are not passive recipients of HR policies or mere observers of their managers' HR implementation strategies. Rather, their perceptions play a critical role in shaping organizational culture and fostering high‐performing workplaces. However, important questions remain regarding how line management roles shape not only employees' assessments of their work environment but also their perceptions of HR effectiveness. Drawing on cognitive appraisal theory, we argue that line managers' compliance‐ versus commitment‐focused orientations influence employee appraisals of threats and challenges in their jobs. These appraisals, in turn, shape how employees evaluate the effectiveness of their organization's HR practices (i.e., perceived HR effectiveness). Using qualitative data from focus groups and a multilevel quantitative research design, we find evidence supporting our hypotheses, showing that line managers' HR orientations significantly influence employees' cognitive appraisals and subsequent perceptions of HR effectiveness. We conclude by discussing the theoretical contributions and offering practical recommendations for improving the implementation of HR practices.