Despite noticeable research interest, the labor-intensive Readymade Garments (RMG) industry has rarely been studied from the perspective of workers’ productivity. Additionally, previous studies already generalized that rewards and organizational commitment lead to employee productivity. However, extant research focused on the RMG industry of Bangladesh, which consists of a different socio-cultural, economic, and political environment, as well as profusion dependency on unskilled labor with an abundance supply of it, hardly considered job satisfaction as a factor that may affect the dynamics of compensations or rewards, commitment, and employee productivity. To address this research gap, this study analyzes the spillover effect of compensation, organizational commitment, and job satisfaction on work productivity in Bangladesh’s readymade garments (RMG) industry. Besides, it delves into the analysis of job satisfaction as a mediator among these relationships. We examined the proposed model by analysing cross-sectional survey data from 475 respondents using the partial least squares-structural equation model in Smart PLS 4.0. The findings show that higher compensation and organizational commitment levels lead to higher levels of job satisfaction, leading to greater productivity. This research also discovered that job satisfaction is a mediator between compensation and productivity and commitment and productivity, respectively. Results further show that increased organizational commitment and competitive wages are the two keyways to boost job satisfaction and productivity in the RMG industry. Relying on the findings, this study outlines pathways for organizational policymakers to improve employee productivity in the labor-intensive industry in developing countries.

This study examined the factors influencing the organizational satisfaction of employees in public institutions. In the case of public institutions that must provide stable public services on behalf of the government, the organizational satisfaction of employees will be more important. In this regard, this study includes the perception of HRM and trust between employees as affecting factors, and the perception of HRM consisted of sub-components such as fairness of evaluation and excellence of education and training. Moreover, this study considered trust between employees as a mediator. In more specific, online surveys were conducted with 705 employees of public institutions in Korea, and the Structural Equation Model (SEM) was performed. The results indicated that the perception of HRM affected organizational satisfaction directly or indirectly. In addition, trust between employees mediated between all sub-components of perception of HRM and organizational satisfaction. Particularly, trust between employees has been verified to increase the influence of the perception HRM. Meanwhile, in the case of Korea, there are more public institutions than other countries, and many other countries are showing high interest in Korea’s public institution operation system. In this respect, dealing with Korean public institutions as examples provides important international implications.

This study investigates the impact of artificial intelligence (AI) integration on preventing employee burnout through a human-centered, multimodal approach. Given the increasing prevalence of AI in workplace settings, this research seeks to understand how various dimensions of AI integration—such as the intensity of integration, employee training, personalization of AI tools, and the frequency of AI feedback—affect employee burnout. A quantitative approach was employed, involving a survey of 320 participants from high-stress sectors such as healthcare and IT. The findings reveal that the benefits of AI in reducing burnout are substantial yet highly dependent on the implementation strategy. Effective AI integration that includes comprehensive training, high personalization, and regular, constructive feedback correlates with lower levels of burnout. These results suggest that the mere introduction of AI technologies is insufficient for reducing burnout; instead, a holistic strategy that includes thorough employee training, tailored personalization, and continuous feedback is crucial for leveraging AI’s potential to alleviate workplace stress. This study provides valuable insights for organizational leaders and policymakers aiming to develop informed AI deployment strategies that prioritize employee well-being.

Objective: This study synthesizes current evidence on the role of Artificial Intelligence (AI) and, where relevant, Open Science (OS) practices in enhancing Human Resource Management (HRM) performance. It focuses on recruitment processes, ethical considerations, and employee participation. Methodology: A systematic literature review was conducted in Scopus covering the period 2019–2024, following PRISMA guidelines. The initial search yielded 1486 records. After de-duplication and screening using Rayyan, 66 studies (≈ 4.4%) met the inclusion criteria, which targeted peer-reviewed works addressing AI-supported HR decision-making. A combined content and bibliometric analysis was performed in R (Bibliometrix) to identify thematic patterns and conceptual structures. Results: Analysis revealed four thematic clusters: 1) Implementation and employee participation emphasizing human-in-the-loop approaches and effective change management; 2) ethical challenges including algorithmic bias, transparency gaps, and data privacy risks; 3) data-driven decision-making delivering higher accuracy, fewer errors, and personalized recruitment and performance assessment; 4) operational efficiency enabling faster workflows and reduced administrative workloads. AI tools consistently improved selection quality, while OS practices promoted transparency and knowledge sharing. Implications: The successful adoption of AI in HRM requires employee engagement, strong ethical safeguards, and transparent data governance. Future research should address the long-term cultural, organizational, and well-being impacts of AI integration, as well as its sustainability.

This research explores the impact of employee green behavior on green transformational leadership (GTL) and green human resource management (GHRM), and their subsequent effects on sustainable performance within organizations. Utilizing a sample of 482 environmental quality promotion departments across Thailand, the study employs stratified random sampling to ensure representative data collection. Analysis was conducted using SPSS software, applying Ordinary Least Squares (OLS) regression to test the hypothesized relationships between the variables. The findings reveal a positive and significant influence of employee green behavior on both GTL and GHRM. Additionally, both GTL and GHRM are found to positively correlate with sustainable performance, indicating that enhanced leadership and management practices in the environmental domain can lead to better sustainability outcomes. This research utilizes the Ability-Motivation-Opportunity (AMO) theory as its theoretical framework, illustrating how organizations can leverage strategic HRM practices to promote environmental consciousness and action among employees, thereby enhancing their long-term sustainability success. Implications of this study underscore the importance of integrating green practices into leadership and HRM strategies, advocating for targeted training programs and energy conservation measures to boost environmental awareness and performance in the workplace. This contributes to the literature on sustainable performance by providing empirical evidence of the pathways through which green HRM and transformational leadership foster a sustainable organizational environment.

The research aims to explore the role of Electronic Human Resources Management on employee performance through employee engagement. The present research’s population included all Jordanian Service and Public Administration Commission employees. The data was collection through a questionnaire that was administered for the study Population. 262 questionnaires collected from employees working in Service and Public Administration Commission in Jordan valid for statistics. The analysis of the data was undertaken through the use of SEM (structural equation modelling). The results showed that E-HRM has a direct impact on employee performance and employee engagement. Consequently, the indication from the results was that a significant role in mediation within the effect that E-HRM had upon employee performance been played by employee engagement. The conclusion reached was that transformation of the public sector through implementation of technological HRM methods fosters employee engagement, with that being a key driver for the alignment of employee behaviors for the achievement of high levels of employee performance.