The rapid advancement of the industrial revolution and digital transformation has reshaped organizational systems, particularly in Human Resource Management (HRM), by introducing artificial intelligence (AI) as a tool for efficiency, effectiveness, and innovation. However, the challenge lies in ensuring that AI-based HRM practices align with sustainable development goals (SDGs). This study aims to explore how Digital Business graduates and undergraduate students, representing Generation Z as the future workforce, perceive the role of AI in HRM and its contribution to achieving specific SDGs, namely: SDG 4 (Quality Education), SDG 8 (Decent Work and Economic Growth), SDG 9 (Industry, Innovation and Infrastructure), and SDG 11 (Sustainable Cities and Communities). Using an exploratory qualitative approach, two focus group discussions were conducted with 40 participants consisting of students and graduates who have completed internships or worked in industries applying AI in HRM. The findings highlight that participants perceive AI as enhancing recruitment, training, performance evaluation, and data-driven decision-making. However, challenges such as data security, digital literacy gaps, and organizational culture resistance remain significant. The contribution of this study lies in emphasizing the perspective of Gen Z, who not only experience but also drive digital transformation in HRM. Their insights reveal the potential of AI to accelerate SDG achievements while underscoring the need for competency development in technology literacy and data analysis. Practical implications are directed to higher education institutions for curriculum adjustments and to organizations for fostering adaptive, innovative, and sustainable HR practices in the digital era.

This study aimed to validate the digital transformation model in human resource management of the Civil Registration Organization of Iran. The research method was mixed (qualitative–quantitative) and employed a descriptive–analytical approach. In the qualitative phase, by applying grounded theory and conducting interviews with experts, the main and subcategories of digital transformation were extracted, followed by open, axial, and selective coding. Then, based on the qualitative findings, a questionnaire was designed and implemented in the quantitative phase with a sample of 380 managers and specialists. The data were analyzed using structural equation modeling (PLS-SEM) and validity and reliability tests. The reliability of the questionnaire was confirmed with Cronbach’s alpha above 0.7 and composite reliability above 0.8. Convergent validity was verified with AVE greater than 0.5, and discriminant validity was confirmed with HTMT less than 0.9. The findings indicated that digital transformation in human resource management is a multidimensional process influenced by causal conditions (β = 0.34), intervening conditions (β = 0.49), and contextual conditions (β = 0.56). Strategies such as organizational culture development, human resource empowerment, smart network development, and continuous monitoring were identified as key drivers. The outcomes of this transformation emerged at three levels — individual, organizational, and social — including enhanced employee performance, increased organizational agility, and improved social capital. The modeling results showed that all hypotheses were statistically significant (t > 1.96). Additionally, the coefficient of determination (R² = 0.20) and the global goodness-of-fit index (GOF = 0.411) indicated an acceptable model fit. Ultimately, the proposed model can serve as a comprehensive framework for digital human resource management in the Civil Registration Organization and similar organizations.

Purpose The purpose of this paper is to show how psychological safety and collective leadership help human resource (HR) systems turn into everyday behaviour and better team performance. Many HR initiatives look good on paper but do not change what people actually do. Drawing on recent research and field experience, the paper focuses on concrete interactions between leaders and team members, and proposes a simple framework, mini-cases and a short checklist that HR leaders and line managers can use to start small, experiment and adjust within their own organisations. Design/methodology/approach This paper is based on a review of recent research on psychological safety, collective leadership and human resource management (HRM) micro-foundations, combined with observations from leadership development and team training projects in various organisations. Rather than presenting a formal empirical study, the approach integrates evidence with practical experience to highlight the everyday interactions that shape behaviour. The paper organises these insights into a simple framework and illustrates them with short mini-cases and a quick diagnostic that HR leaders and line managers can apply immediately. Findings Across the research and practice reviewed, two patterns stood out. Firstly, psychological safety and collective leadership consistently acted as the behavioural link between HR intentions and what actually happened in teams. HR systems alone did not shift behaviour unless day-to-day interactions supported speaking up, shared influence and basic relational coordination. Secondly, these behaviours were not abstract ideals but small, repeatable actions by both leaders and team members. When these actions accumulated, teams showed clearer decision-making, faster learning after setbacks and more reliable collaboration, regardless of hierarchy. Research limitations/implications Because this paper integrates research with field observations rather than reporting a single empirical study, the conclusions should be read as indicative rather than definitive. The examples draw mainly on knowledge-intensive and team-based settings, so some elements may need adaptation in other contexts. Even so, the review highlights clear behavioural mechanisms that can inform future empirical work on HRM micro-foundations. For practitioners, the implication is that improving psychological safety and collective leadership does not require large programmes; small, observable actions can be tested and refined within existing HR and management routines. Practical implications For HR leaders and line managers, the main implication is that psychological safety and collective leadership can be reinforced through small, routine adjustments rather than major structural changes. Simple behaviours – such as clarifying the purpose of a discussion, asking for alternative views and openly acknowledging uncertainty – help teams speak up and share influence. These actions make existing HR systems more effective by improving how people coordinate, decide and learn together. Starting with a few repeatable practices, testing them in real meetings and adjusting based on team feedback can produce visible improvements within weeks. Social implications Improving psychological safety and collective leadership has broader implications beyond organisational performance. When everyday interactions become more open and respectful, people experience fewer interpersonal risks at work, which supports wellbeing and reduces avoidable conflict. Teams become more inclusive because diverse members have more opportunities to speak and influence decisions. These conditions can also strengthen trust between managers and employees, especially in settings with strong hierarchy. Although the practices described in this paper are small in scale, they can contribute to healthier and more participatory work environments, which has benefits for both individuals and communities. Originality/value The paper brings together psychological safety, collective leadership and HRM micro-foundations in a way that is easy for practitioners to use. Rather than proposing a new theory, it highlights concrete behaviours that help HR systems work as intended in everyday team settings. By combining insights from research with observations from development programmes, the paper offers a practical lens for understanding how small interactions shape collaboration and decision-making. The simple framework, mini-cases and diagnostic are designed to help HR leaders and line managers test ideas quickly and adapt them to their own context.

In India rural and semi-urban financial system, co-operative banks are vital, especially in regions such as Odisha where they provide low-income individuals, small enterprises, and farmers with vital loans. These banks, however, confront a number of difficulties, including unstable finances, ineffective governance, technology constraints, and disgruntled customers. This study uses factor analysis, a multivariate statistical technique, to assess the major factors influencing the performance of co-operative banks in Odisha. To find out how 200 respondents – including co-operative bank customers and staff – perceived banking services, governance, financial stability, and technology adoption, a primary survey was carried out. The appropriateness of factor analysis was validated by the Bartlett’s test of sphericity (p < 0.05) and the Kaiser-Meyer-Olkin (KMO) test (0.812). Five key elements were identified through Principal Component Analysis (PCA): (1) risk management and financial stability; (2) governance and regulatory compliance; (3) digital banking and technological adoption; (4) customer satisfaction and service quality; and (5) operational efficiency and human resource management. Together, these variables accounted for 77.7% of the variance, demonstrating their significant impact on the operation of co-operative banks. The results emphasise how urgently governance frameworks must be strengthened, financial risk management must be improved, and digital transformation must be accelerated to increase banking efficiency. To increase client trust and retention, the report also emphasises the significance of customer-centric strategies, such as expedited loan processing and grievance redressal procedures. These insights can be used by regulators, policymakers, and bank management to create focused actions that would increase the competitiveness and sustainability of Odisha’s co-operative banks.

Beyond aversion – principles of appropriate algorithmic decision-making in human resource management

Abstract Continuous training constitutes a central component of the strategic and operational management of Human Resources. It aims to produce, maintain, and develop individual and collective skills within organizations, thereby directly contributing to performance and competitiveness. For training to be effective, it must not be an end in itself but rather a strategic tool aligned with the company’s objectives. This requires integrating evaluation mechanisms and tools from the design phase to ensure the relevance, usefulness, and effectiveness of training programs in relation to the expected outcomes. At the national level, Morocco, as an emerging country, must raise the overall level of education and training of its population—an essential condition for improving the competitiveness of Moroccan enterprises. Continuous training enhances adaptation to labor market transformations, strengthens employee employability, and improves productivity. To maximize its impact, training must be considered a strategic investment and integrated into the company’s overall strategy. An effective training policy requires strategic thinking in human resource management and skills development, grounded in and aligned with the organization’s strategy.However, in Moroccan SMEs, this strategic approach remains limited: material investments are generally prioritized at the expense of continuous training. This research aims to examine existing training practices within Moroccan SMEs in a strategic approach.

Linking green entrepreneurial leadership with green innovative behaviour through green human resource management, organisational learning culture, and environmental dynamism

The contribution of green human resource management to promoting the use of artificial intelligence in Arab universities

A multilevel moderated mediation model of developmental human resource management practices in the hotel industry

Sustainable human resource management: a dynamic valuation approach

A comprehensive study of green human resource management practices in relation to employee performance and organisation citizenship behaviour among IT professionals in Gurgaon.

In the age of digital revolution, organizations increasingly use artificial intelligence (AI) and machine learning (ML) to improve their data-driven decision-making, especially in human resource management. This paper makes a comparative evaluation of AI-driven data warehousing systems and ML methods for forecasting employee turnover and maximizing employee performance. The study compares top data warehousing platforms like Redshift, BigQuery, Snowflake, and Databricks and their coupling with ML models with regard to prominent workforce features. Qualitative findings from HR managers were also examined, in order to evaluate the real-world effect of these technologies on the productivity of the workforce and employment strategies. Research shows that AI-based data warehousing integrated with competent machine learning models drastically enhances attrition prediction accuracy, performance tracking, and strategic workforce planning. This research identifies the strategic advantages of combining AI-driven data warehousing with HR analytics, offering organizations actionable findings to choose the best AI-enabled solutions. The findings contribute to extending knowledge on efficient data strategies in lessening attrition as well as improving employee performance, aiding organizations in their pursuit of strategic human capital objectives.

Low-skilled migrant workers make up a significant portion of the workforce in many countries, yet their well-being remains underexplored in mainstream human resource literature, particularly in relation to stress and coping mechanisms. This study examines how low-skilled migrant workers navigate stress while working and living overseas, identifying key stressors and coping strategies. Focussing on Bangladeshi male migrant workers in Malaysia, a country shaped by migration, the study responds to calls for a more inclusive perspective in human resource management research. Drawing on 44 semi-structured interviews, our findings indicate that low-skilled migrants predominantly rely on support-seeking strategies, particularly from family, peers, and faith. This is followed by problem-solving and accommodation strategies. Additionally, religion emerges to be a key personal resource in their coping efforts. These insights offer implications for human resource management practices and government policies aimed at enhancing the well-being of foreign semi-skilled and unskilled workers.

Weekly maintenance scheduling is an important activity in maintaining the reliability of operating facilities, especially in the Power Plant area in the oil and gas industry sector. This study aims to optimize the maintenance planning and scheduling process by utilizing the text mining approach through Latent Dirichlet Allocation (LDA) modeling to manage and group maintenance data, and integrate it with the Linear Programming (LP) model as the basis for the preparation of an optimal Work Order (WO) Scheduler. The LDA model is used to categorize work based on Fixed Reference Activities (FRA), resulting in a more structured classification of maintenance activities. The output of this category is then an input for the LP model that compiles labor allocation, duration, and work priorities according to the available weekly time limits. Sensitivity analysis was carried out on the parameters of the number of labor, work priority, and length of time horizon with variations of ±10%, ±20%, and ±30%. The results show an increase in the WO completion rate, a reduction in the backlog, and a more accurate understanding of labor utilization. The model has proven to be sensitive to changes in workforce capacity so that human resource management is the dominant factor in the successful implementation of schedulers.

This study explains how human resource management (HRM) practices function in Nepal and why adoption differs across sectors. It uses an explanatory qualitative design based entirely on desk research. A structured framework guided source selection, thematic coding across core HR domains, and an explanatory synthesis that links observed practices to contextual factors such as regulation, resources, leadership capability, and culture. Results show a dual trajectory. Private and joint-venture firms more often practice strategic HR planning, merit-based hiring, targeted training, and merit-linked appraisal. Public enterprises and smaller firms frequently retain administrative routines, weak planning, and formality-driven evaluations. Public bodies should insulate HR from political influence, introduce transparent succession planning, link appraisals to development and promotion, and fund regular upskilling. Private firms should deepen data-enabled talent systems and flexible job design. The paper clearly separates what is established in prior research from what is newly inferred for Nepal, using an issue-based, explanatory lens to connect sector, policy, and culture with HRM outcomes, thereby improving transparency and utility for managers and policymakers.

Human Resources (HR) technology solutions encompass software and hardware tools designed to automate HR processes, gather, process, and analyze data, utilize it for strategic decision-making, and execute HR professionals' tasks while prioritizing security and privacy considerations. As with numerous other domains, Digital Transformation and emerging technologies have commenced integration into HR processes. These technologies are utilized by HR professionals and various stakeholders involved in HR operations. This study evaluates the utilization of Artificial Intelligence (AI), Virtual Reality (VR), Augmented Reality (VR), and the Metaverse within HR management, focusing on current trends and potential opportunities. A survey was conducted to gauge HR professionals' perceptions and critiques regarding these technologies. Participants were the HR department officers, academicians who specialized in HR and staff who had courses at diverse levels about HR. This study revealed that a substantial majority of participants view integrating AI, VR, AR, and Metaverse technologies in HR processes as beneficial, particularly in enhancing training, recruitment, and performance management. In particular, ethical concerns and data security risks emerged as dominant challenges. The two-way nature of technological adoption in HR, with both positive and negative aspects, was revealed. The research contributes to the growing body of knowledge by offering statistically significant insights into how demographic factors influence perceptions of emerging technologies in HR contexts.

ABSTRACT Background The Health Extension Program (HEP) is Ethiopia’s flagship program introduced in 2003 to ensure equitable access to primary healthcare services. Recently, inefficiency in the time use patterns of staff of the HEP, including absenteeism and non-productive engagements, has been reported as a major challenge. Objective This qualitative study explored what factors influenced their time use and efficiency. Methods This is a qualitative study that was conducted in rural health posts (HPs) across Ethiopia in three rounds over a period of 12 months (17 May 2023 to 16 May 2024). Qualitative data were collected through key informant interviews (KIIs), in-depth interviews (IDIs), and focus group discussions (FGDs) involving HEWs and other staffs of health posts, their supervisors, Kebele leaders, Women’s Development Army (WDA), teachers, and other community members. A total of 52 KIIs, 31 IDIs, and 28 FGDs were conducted in three rounds. Data were analyzed using ATLAS.ti 7.1.18 software. Results HEWs commonly spent their time on productive non health or non-HEP activities such as those related to community-based health insurance, agricultural and rural development and education sectors, and other political assignments. It was also noted that HEWs could be available in their workplace, but might not be productive. Factors for the inefficiencies across HPs often pertained to environmental and demographic features, community trust and engagement, local administration; human resource development and management practices, multisectoral collaboration; and underlying causes of absenteeism including motivation. Conclusion Inefficiencies are common among HEWs. Strategies need to be devised focusing on the identified modifiable factors such as improving accountability and performance management practices, introducing incentive mechanisms to keep HEWs motivated, improving accessibility to transportation services, and security conditions, workforce to population size ratio; and capacity building.

The current study aimed to identify the impact of human capital in organizational performance in Jordanian five-star hotels. The descriptive analytical approach was used, and a questionnaire was applied consisting of three parts: the first is the demographic information of the study sample, the second is the human resources management scale consisting of (20) paragraphs, and the third is the organizational performance scale consisting of (15) paragraphs. Its validity and reliability were confirmed. The study population consisted of (6189) employees in five-star hotels in Amman, the sample consisted of (362) employees in five-star hotels in Amman were selecting by stratified sampling due to hotel variable by get back percent (94.3 %) whenevre (384) questionnaires was collecting by E-Link, and delay (22) by percent (5.7 %). After collecting the data and conducting the appropriate statistical processing, the study concluded that there is a statistically significant at level (α ≤ 0.05) effect of human capital in its dimensions (knowledge, skill, experience, and training) on organizational performance with its dimensions (Internal process, Customer satisfaction, learning and development) in Jordanian five-star hotels. Training had the highest effect, then experience, then skill, and finally knowledge. The study proposed a set of recommendations, most notably the need for five-star hotel management to focus on training their human resources and involve them in developing training programs. The need to prioritize organizational performance in five-star hotels, given its significant importance in achieving positive results across hotel services as a whole, and continuously assess the level of human resources to ensure the best customer service at all times.

This research analyzes the implementation of the Regent of Cirebon Regulation Number 66 of 2021 concerning the Talent Management System for Civil Servants (Aparatur Sipil Negara, ASN) within the Cirebon Regency Government. The policy aims to create a professional, accountable, and competitive bureaucracy through the systematic development of human resources based on merit principles. However, in practice, several challenges emerge, including inadequate understanding of talent management concepts, uneven competence mapping, and limited digital integration in the implementation process. This study applies a qualitative descriptive approach, focusing on the analysis of policy implementation according to the model proposed by Edward III (1980), which emphasizes four key variables: communication, resources, disposition, and bureaucratic structure. Data were collected through interviews with officials from the Regional Civil Service and Human Resource Development Agency (BKPSDM), document analysis, and field observation. The research also employed secondary data from official government reports, performance evaluations, and local regulations related to human resource management. The findings show that the implementation of talent management in Cirebon Regency has been initiated structurally through the issuance of regulatory instruments and the formation of a task force. However, at the operational level, the process has not been fully optimal. The main constraints include limited understanding of talent management among civil servants, absence of standardized performance evaluation systems, and weak inter-departmental coordination in identifying and developing potential talents. In addition, technological support systems such as the digital database and information integration between agencies remain inadequate. The study concludes that successful implementation of talent management requires not only regulatory support but also organizational commitment, leadership, and systematic competence development. The Cirebon Regency Government is advised to strengthen institutional capacity, improve human resource planning, and integrate information systems to support evidence-based and meritocratic personnel management.

This inaugural critical reviews special issue marks a deliberate step in renewing what Human Relations has always stood for: a broad, rigorous, and human-centered conversation about work and organizing. Our aim with this special issue is therefore twofold: to take stock and to set direction. By curating critical, integrative reviews on select but timely topics, we map the evolution of debates, clarify where concepts and methods need to realign, and chart agendas that advance our understanding of the human side of organizational life. The four articles featured in this inaugural issue exemplify the intellectual breadth and critical depth that define Human Relations . Each engages a core tension of contemporary organizing; how multilevel systems interact in strategic human resource management; how colonial legacies shape Indigenous experiences of work; how precarity redefines the meaning and politics of labor; and how algorithmic technologies transform the inequalities embedded in hiring and organizational life. Read collectively, these contributions illuminate the diversity of themes, methods, and theoretical traditions that animate our journal, while also revealing a shared pursuit: understanding what it means to be human in the evolving relations of work, organization, and society.