Asia Pacific Journal of Human Resources最新文献

Digital human resource management (HRM) is a crucial component of organizational digital transformation. However, it is unclear whether and how digital HRM will impact employee cognitive and behavioral reactions during this process. In recognition of the effect of digital HRM, this study deployed HR attribution theory and conducted a two-stage survey involving 137 senior managers and 1157 employees from 150 companies undergoing digital transformation to explore the mechanisms and boundary conditions of digital HRM on employee reactions to change. This study also provides new insights for managers seeking to motivate employee supportive behaviors toward organizational digital transformation.

This study investigates whether employee environmental passion (EEP) mediates the effect of a green workplace environment (GWE) and sustainable human resource management (SHRM) on employee green engagement (EGE). The hypothesized research model was assessed by integrating the principles of the theory of planned behavior (TPB) and social exchange theory (SET). Primary data were collected through a web-based survey from employees of large-scale energy sector corporations in Malaysia, where sustainability efforts are predominantly driven by governmental regulations rather than voluntary organizational initiatives. Purposive sampling was used to collect responses. Data from 364 participants were analyzed using PLS-SEM. Findings suggest a positive relation between GWE, SHRM, and EGE. Notably, findings report that EEP mediates the effects of GWE and SHRM on EGE. The study provides practical implications for the Malaysian energy sector, which is undergoing a state-led transition toward sustainability under frameworks such as MyRER. Since energy sector employees play a critical role in endorsing environmentally friendly practices, organizations should revise their employment policies to promote pro-environmental behaviors. Moreover, hiring managers and employees with strong environmental passion may further enhance green engagement. Managers should, among other activities, implement SHRM practices aligned with national sustainability directives while tapping into individual values for resource preservation and environmental protection. This study contributes to a growing research area on EGE by characterizing effective green work initiatives, such as greening the workplace and green practices. It further provides empirical evidence on how GWE and SHRM effects on EGE are transmitted through EEP, highlighting the unique context of Malaysia's government-led sustainability agenda. The study quantifies the advantages of greening practices for employees' pro-environmental behaviors by integrating the TPB and SET theories.

Green Human Resource Management (GHRM) is increasingly acknowledged as a crucial strategy for enhancing organisational environmental performance. Despite growing empirical evidence regarding the antecedents and outcomes of GHRM, limited efforts have been made to quantitatively synthesise the existing findings to advance the literature. Additionally, it is not clear which specific GHRM practices are more effective in predicting different favourable employee outcomes. To address the gaps, we conducted a comprehensive meta-analysis of 172 studies (N = 54,963) from 166 articles. Our results indicate that overall GHRM is positively related to various employee attitudinal and behavioural outcomes and organisational outcomes. Further analysis using MASEM (meta-analytic structural equation modelling) reveals that overall GHRM impacts both employee in-role and extra-role green behaviours through employee green values. Moreover, the result of relative weight analysis shows that specific GHRM practices, such as green performance management, and employee empowerment and involvement, are particularly effective at promoting employee in-role green behaviours. Green performance management and green reward and compensation are more important for fostering employee extra-role green behaviours.

Artificial intelligence (AI) technologies have been increasingly adopted in service industries and are playing a crucial role in affecting service innovation. Drawing on the perspective of information exchange, our research investigates the impact of AI usage on employee service innovation behavior and the underlying mechanism. We conducted a qualitative study, an experimental study, and a field survey to test our hypothesized model. The findings indicate that AI usage at work reduces the information exchange between employees and customers, which, in turn, negatively affects employee service innovation behavior. However, job autonomy can mitigate the negative effects of AI usage on employee-customer information exchange and service innovation behavior. Our research contributes to the literature on AI usage and service innovation and provides practical insights for using AI effectively in work settings.

The influence of technological changes on work has long been debated, but labor's impact on technology, especially in rapid-industrializing economies, deserves more research. This study explores labor's influence on automation in China, based on long-term investigations of eight automotive suppliers. Each of these factories, following the 2010 strikes, established enterprise unions that engage in regular collective bargaining, making them among the country's most active grassroots trade unions. As is typical in the industry, management in all these factories has been actively pursuing automation. However, their automation processes have diverged widely. By comparing these processes, this study identifies two key labor impacts on technology: the first arises from the productive characteristics of labor, and the second from workers' collective action. Both types influence the form and pace of technology adoption in China. The former, based on labor costs, skills, and other productive attributes, structurally constrains automation choices. Action-based union effects, which are prominent in some Western unions, remain limited and primarily defensive and may weaken further as the march of automation continues.

Given the profound influence of organizations on societal well-being and their role in environmental stewardship, there is a growing trend for organizations to proactively integrate corporate social responsibility (CSR) into human resource management (HRM) practices to align with societal expectations and sustainable development goals. However, the consequences of proactive CSR from an employee perspective are not well understood. Drawing on attribution theory, this study investigates whether employees' different attributions of perceived proactive CSR have a positive or negative impact on their attitudes and subsequent behaviors in a Chinese context. The findings of a time-lagged field survey involving 430 employees and 131 leaders reveal that when employees attribute perceived proactive CSR to substantive motives, their organizational identifications are more likely to increase, leading to their taking charge. Conversely, when employees attribute perceived proactive CSR to symbolic motives, they are more likely to experience an increase in organizational stigma, resulting in job withdrawal.

As algorithmic management (AM) becomes an increasingly prominent feature of the digital workplace, understanding its implications for human resource management (HRM) is both timely and critical. This study investigates how AM, as an emerging HRM practice, contributes to team resilience (TR)—a key strategic goal for HR professionals seeking to foster adaptability and sustainability in uncertain environments. Drawing on social cognitive theory, we develop and test a model in which AM reduces managerial objectification (MO) and facilitates informal leadership emergence, ultimately enhancing TR. Based on a multi-wave field survey of enterprise managers in China, our findings reveal a dual-path mechanism: AM improves TR both cognitively, by reshaping managerial perceptions of employees, and behaviorally, by triggering bottom-up leadership processes. A sequential mediation pathway—AM → MO → informal leadership → TR—is also supported. This study contributes to HRM research by demonstrating how algorithmic systems can be designed and leveraged to promote resilient, self-organizing teams. Practical implications are offered for HR practitioners aiming to implement AM in ways that empower both managers and employees.