HRM Research Research Articles

Green human resource management in a family business setting: a fuzzy set approach

ABSTRACT Sustainability in family businesses as an entrepreneurial initiative is an emerging research field. The literature assumes that owners, managers, and employees in family businesses adopt homogeneous sustainability practices as a global construct mixing social and environmental issues. However, green human resource management (GHRM), considered as an innovative process, is focused on understanding how regular managers and employees become green-oriented and aim for business sustainability by applying green policies and practices. Based on previous green HRM research, this study proposes to apply a fuzzy set qualitative comparative analysis to identify the combinations of key practices observed in 513 family businesses in Quebec. This perspective helps to explain some of the boundary conditions and combinations of green HRM practices in family businesses based on more realistic insights by avoiding a merely linear analysis. We highlight four different pathways connecting green HRM system to economic performance. This study is the first to explore green HRM practices in family businesses. The paper concludes by discussing how the findings advance knowledge on sustainability in family business research.

Dealing with special supervisors: a typology of coping strategies toward accountability to customers in gig work

Numerous studies have explored the situations of gig workers in the ‘new’ gig economy. While the existing literature focuses on intermediary platforms’ algorithmic control over workers, this paper emphasizes the interpersonal and negotiable aspects of gig worker-customer interactions through an accountability perspective. We posit that algorithmic control and accountability to customers constitute two coordination mechanisms for platform HRM. The latter has gained significance as intermediary platforms adopt algorithmic management and empower customers as visible supervisors. Algorithm-mediated customer control assigns customers direct influence, thereby positioning them as prominent accountability sources and compelling gig workers to meet their expectations. Nevertheless, how gig workers navigate their behaviors under these conditions remains unknown. This study employs a typological approach to explore gig workers’ coping strategies in response to accountabilities, providing micro-level insights into the functionality and dysfunctionality of HRM with gig platforms. Drawing from a qualitative study in the Chinese online delivery industry, we integrate metaphors from cognitive research (i.e. intuitive psychologists and intuitive economists) with the metaphor derived from accountability theory (i.e. intuitive politicians) to develop a fourfold typology grounded in two dimensions (i.e. cognitive modes and economic motives). Our findings reveal both the inevitability and possibility of accountability to customers, identifying four coping strategies (i.e. obedient, ingratiatory, defensive, and cooperative behaviors). This paper offers novel insights into the fields of accountability and HRM research, along with practical implications.

Pedagogical implications of pragmatic HRM research.

This chapter examines the interplay between human resource management theory and human resource management practice. It advocates that effective human resource management practice and theory are intrinsically intertwined, and this indispensable link ought to be central to the pedagogy of management research methods. Through greater embeddedness of the institutional and societal context in research method teaching, students can develop as scholars who understand their roles as facilitators of dialogue between researchers and a significant part of their audience (practitioners). The chapter conceptualizes this perspective as a collaborative model in human resource management research, which then must hold centrality in the teaching of research methods in our university and college classrooms.

Singing the same environmental song: transmission of green HR signals from supervisors to subordinates through multilevel modeling

PurposeTo comprehend the influence of green HR practices (GHRM) on employee outcomes, strategic HRM researchers are gradually adopting an employee-centric approach, a subject that has sparked recent discussions among scholars in the field of green HR. These scholars have emphasized the need for studies that shed light on the reasons behind the differences in employees' perceptions of GHRM. To address this concern, we investigated (1) supervisors perceived GHRM (SUP-GHRM) and subordinates perceived GHRM (SUB-GHRM) as the fundamental source of variation in employee eco-friendly behavior and green performance, (2) the association between SUP-GHRM and SUB-GHRM, (3) the mediation role of SUB-GHRM toward green performance and eco-friendly behavior, and (4) the moderation of perceived HRM system strength (HRMSS) on supervisor-subordinate perceived GHRM.Design/methodology/approachApplying a survey approach, we collected data from 217 supervisors and 624 subordinates from Large-Scale Manufacturing Organizations in the Textile sector of Pakistan. Since the data is hierarchical, we applied the Hierarchical Linear Model (HLM) and bootstrapping techniques to examine the hypothesized relationship.FindingsThe results of HLM revealed that (1) the SUP-GHRM and SUB-GHRM were key in determining green performance and eco-friendly behavior, (2) the SUP-GHRM significantly influenced SUB-GHRM, (3) the SUP-GHRM indirectly affected the eco-friendly behavior and green performance through SUB-GHRM, (4) the HRM system’s strength positively moderated the association between the SUP-GHRM and SUB-GHRM.Practical implicationsThe corporations need to ensure that both supervisors and subordinates have a consistent understanding of GHRM practices and foster positive relationships between them. It is also important for companies to actively enhance supervisors' knowledge of GHRM and encourage them to effectively communicate the company’s GHRM practices to their subordinates. This is vital for improving employee job-related outcomes. Furthermore, corporations should emphasize developing a strong HRM system designed to create a climate where employees understand the behaviors and responses that are valued and recognized, leading them to perceive situations in line with their managers.Originality/valueThis study suggests SUP-GHRM and SUB-GHRM as critical factors that influence eco-friendly behavior and green performance, and HRMSS is key to aligning the perception gaps between subordinates and supervisors about what GHRM is in place in their organization, which is empirically analyzed in a developing country context.

Sustainable human resource management: a mixed-method analysis of the research field focusing on the visegrad countries

PurposeI aimed to analyze and synthesize the literature on sustainable HRM and its sub-concepts, such as green HRM and socially responsible HRM, with the focus on research conducted in the Visegrad Group (V4) countries. I posed the following research questions: (1) What are the main characteristics of sustainable HRM research in the worldwide literature? (2) What are the main characteristics of research conducted in the V4 countries? (3) Which future research directions are promising gaps to be filled by research conducted in V4 countries?Design/methodology/approachFor the purpose of this study, I applied bibliometric analysis, scientific network analysis and in-depth content analysis.FindingsThe results of the analyses of articles indexed in the Scopus database revealed that there is a growing trend in research on sustainable HRM. However, scarce research comes from the V4; scholars have conducted such studies only in Slovakia and Poland. There are five thematic clusters in the main sample, though the concept of green HRM has been explored the most. Although the keyword network analysis showed that the V4 articles focus mostly on sustainable HRM, the in-depth content analysis provided evidence that the V4 sample represented all concepts.Originality/valueThis is the first study to analyze the achievements of scientists from the V4 in this research field. It applies methodological rigor and a mixed-method approach. Moreover, it presents directions of research that go beyond the recommendations presented in the analyzed articles.

How HR managers develop ideas about HR reform: the role of inter-corporate knowledge exchange in Japan

Following a call for actor-centric research in HRM, we look at the modes how HR managers acquire HR knowledge. Our interview study with HR managers of large established companies in Japan finds a clear preference for direct inter-corporate knowledge exchanges instead of the engagement of outside consultants. Discussing our findings, we explain the reasons for this preference. ing from the case of Japan, we then propose with reference to institutional theory and isomorphism that the way HR knowledge is spread is linked to the nature of employment systems. In external labour markets, HR knowledge has been reported to be predominantly spread through business consultants, educational institutions, and career changes of HR professionals, resulting in normative isomorphism. We propose that in internal labour markets, like Japan’s, companies resort to direct inter-corporate knowledge exchange, which leads to mimetic isomorphism.

Bibliometric Methods in HRM: Contribution and Utility

This paper offers an overview of the usefulness of bibliographic analysis and conducts a retrospective review of the Human Resource Management Journal (HRMJ). The first part of the paper explains that bibliographic methods are not fully democratized in management and have just started their modest ascent in HRM. In the second part, the paper provides a retrospective review (1990–2022) of HRMJ articles (n = 855), which constitutes one of the two general objectives of bibliometric analysis. The results revealed that bibliometrics analysis significantly contributes to the HRM body of knowledge, especially given that this methodology is barely used in HRM research. Conversely, the retrospective review has identified trends in performance analysis, such as co-authorship internationalization in HRMJ articles that were unclear until 2011. We also highlighted the existence of six major clusters: HRM and organizational behavior (cluster 1), HR practices and policies (cluster 2), HRM as a strategy (cluster 3), HRM and performance (cluster 4), international HRM (cluster 5), and HRM roles and contingencies (cluster 6). Insights into potential trajectories for HRMJ scope are provided.

조직 운영 방식이 알고리즘 HRM 도입과 활용에 미치는 영향

The increasing use of advanced technologies in human resource management, such as
 big data driven decision making, HR analytics, and AI-enhanced selection processes, is a
 notable trend. Algorithmic HRM refers to the application of advanced algorithms to automate
 tasks within human resource management or to facilitate data-driven decision making. This
 study seeks to investigate the differences in the adoption and utilization of algorithmic
 HRM among organizations based on organizational management orientations. In particular,
 this study posits that companies may vary in their perception of usefulness and ease of use
 for algorithm HRM depending on two distinct management orientations: control structure
 and external orientation. Based on the empirical analysis of 329 companies, our findings
 indicate that organizations with a control structure orientation, compared to those valuing
 flexibility structure, were more likely to adopt and utilize algorithmic HRM. Similarly, our
 results show that companies prioritizing the integration of internal resources, rather than
 relying on external environments, tend to be more engaged with algorithmic HRM. Based
 on these findings, the study discusses theoretical and practical implications and suggests
 future directions for algorithm HRM research.

Sustainable HRM the next hotspot for management research? A study using topic modelling

Purpose Sustainable human resource management (SuHRM), which aims to achieve positive environmental, social and economic outcomes at the same time, has gained prominence across industries. However, the challenges of implementing SuHRM across industries are largely under-studied. The purpose of this study is to identify the grey areas in the field of SuHRM by using an unsupervised learning algorithm on the abstracts of 607 papers published in prominent journals from 1995 to 2023. Most of the articles have been published post-2018. Design/methodology/approach The analysis of the data (abstracts of the selected articles) has been done using topic modelling via latent Dirichlet algorithm (LDA). Findings The output from topic modelling-LDA reveals nine primary focus areas of SuHRM research – the link between SuHRM and employee well-being; job satisfaction; challenges of implementing SuHRM; exploring new horizons in SuHRM; reaping the benefits of using SuHRM as a strategic tool; green HRM practices; link between SuHRM and organisational performance; link between corporate social responsible and HRM. Research limitations/implications The insights gained from this study along with the discussions on each topic will be extremely beneficial for researchers, academicians, journal editors and practitioners to channelise their research focus. No other study has used a smart algorithm to identify the research clusters of SuHRM. Originality/value By utilizing topic modeling techniques, the study offers a novel approach to analyzing and understanding trends and patterns in HRM research related to sustainability. The significance of the paper would be in its potential to shed light on emerging areas of interest and provide valuable implications for future research and practice in Sustainable HRM.

High-performance work systems and individual performance: a longitudinal study of the differential roles of happiness and health well-being.

As a part of the growing strand of employee-centered HRM research, employee well-being is suggested to be a key mechanism that may help to explain the relationship between HRM and performance. To investigate how an employee's well-being mediates the HRM-performance relationship, we distinguish between two types of well-being identified in prior work, happiness well-being and health well-being, and present arguments for differences in their effects on individual performance. Building on Job Demands-Resources (JDR) theory, we propose that happiness well-being positively mediates the relationship between perceived High-Performance Work Systems (HPWS) and individual task performance, while health well-being negatively mediates this focal relationship. Thus, happiness well-being fits the "mutual gains" perspective. In contrast, health well-being fits the "conflicting outcomes" perspective, and thus may be harmed by the HPWS to enhance the performance. We find partial support for our arguments in an analysis of longitudinal survey data of 420 participants spanning a total of four waves of data collection.

Retrospection of merger and acquisition research in HRM: science mapping and thematic clustering

Retrospection of merger and acquisition research in HRM: science mapping and thematic clustering

The Relationship between Hybrid HRM and Artificial Intelligence Exploratory Research at Zain Company for Communication - Iraq

The Relationship between Hybrid HRM and Artificial Intelligence Exploratory Research at Zain Company for Communication - Iraq

Editorial: Scholar‐stakeholder collaboration for rigorous and relevant HRM research—Possible contributions and key requirements of collaborative studies in HRM

AbstractHuman Resource Management research is striving to develop rigorous and actionable knowledge for today’s social and environmental global challenges. For years, academic‐stakeholder collaborative knowledge creation processes have been considered as potentially rewarding ways to achieve this objective. However, applications of collaborative HRM research are still relatively sparse, as HR scholars tend to engage with more traditional processes of knowledge creation. The aim of this editorial is to foster more widespread conduct of collaborative HRM research in the future. Drawing on Habermas, whose ideas on human knowledge are considered to be at the core of the epistemology of collaborative management research, we first highlight three avenues for collaborative HRM research that addresses our technical, practical and emancipatory knowledge‐constitutive interests. For each of them, we highlight key theoretical assumptions and risks. Thereafter, we describe two key requirements for rigour and relevance in the context of any collaborative HRM study. Finally, we present the papers included in this special section and discuss their implications for HRM research.

The dark side of AI-enabled HRM on employees based on AI algorithmic features

PurposeAI is an emerging tool in HRM practices that has drawn increasing attention from HRM researchers and HRM practitioners. While there is little doubt that AI-enabled HRM exerts positive effects, it also triggers negative influences. Gaining a better understanding of the dark side of AI-enabled HRM holds great significance for managerial implementation and for enriching related theoretical research.Design/methodology/approachIn this study, the authors conducted a systematic review of the published literature in the field of AI-enabled HRM. The systematic literature review enabled the authors to critically analyze, synthesize and profile existing research on the covered topics using transparent and easily reproducible procedures.FindingsIn this study, the authors used AI algorithmic features (comprehensiveness, instantaneity and opacity) as the main focus to elaborate on the negative effects of AI-enabled HRM. Drawing from inconsistent literature, the authors distinguished between two concepts of AI algorithmic comprehensiveness: comprehensive analysis and comprehensive data collection. The authors also differentiated instantaneity into instantaneous intervention and instantaneous interaction. Opacity was also delineated: hard-to-understand and hard-to-observe. For each algorithmic feature, this study connected organizational behavior theory to AI-enabled HRM research and elaborated on the potential theoretical mechanism of AI-enabled HRM's negative effects on employees.Originality/valueBuilding upon the identified secondary dimensions of AI algorithmic features, the authors elaborate on the potential theoretical mechanism behind the negative effects of AI-enabled HRM on employees. This elaboration establishes a robust theoretical foundation for advancing research in AI-enable HRM. Furthermore, the authors discuss future research directions.

Redefining concepts to build theory: A repertoire for conceptual innovation

Defining and redefining theoretical concepts is an essential part of HRM research, but its role in the theorizing process is still poorly understood. While concept redefinition practices are often dismissed as a scholarly malpractice (‘concept proliferation’) by methodologists, we argue that concept redefinition enhances the health of a literature if one makes a theoretical contribution. To learn what this entails, we first explore the various philosophical motivations for why and how concept definitions are reformulated, changed, and improved. This culminates in a general framework and a vocabulary of ten different opportunities for making theoretical contributions via conceptual redefinition, using the concept of charisma as an illustrative case. From our analysis we induce that concept redefinition is both inevitable and necessary as a form of theory development and conceptual maintenance in many fields of inquiry. We discuss the implications of our framework as being a methodological ‘repertoire’ that, we hope, spurs both useful and novel concept redefinitions that help maintain a healthy HRM literature.

Digital Workforce: From the Generational to the Strategic Approach in HRM Research and Practice

Digital Workforce: From the Generational to the Strategic Approach in HRM Research and Practice

Scholar-Stakeholder Collaborative HRM Research – Taking Stock and Moving Forward

Scholar-Stakeholder Collaborative HRM Research – Taking Stock and Moving Forward

Human resource management in the age of generative artificial intelligence: Perspectives and research directions on ChatGPT

AbstractChatGPT and its variants that use generative artificial intelligence (AI) models have rapidly become a focal point in academic and media discussions about their potential benefits and drawbacks across various sectors of the economy, democracy, society, and environment. It remains unclear whether these technologies result in job displacement or creation, or if they merely shift human labour by generating new, potentially trivial or practically irrelevant, information and decisions. According to the CEO of ChatGPT, the potential impact of this new family of AI technology could be as big as “the printing press”, with significant implications for employment, stakeholder relationships, business models, and academic research, and its full consequences are largely undiscovered and uncertain. The introduction of more advanced and potent generative AI tools in the AI market, following the launch of ChatGPT, has ramped up the “AI arms race”, creating continuing uncertainty for workers, expanding their business applications, while heightening risks related to well‐being, bias, misinformation, context insensitivity, privacy issues, ethical dilemmas, and security. Given these developments, this perspectives editorial offers a collection of perspectives and research pathways to extend HRM scholarship in the realm of generative AI. In doing so, the discussion synthesizes the literature on AI and generative AI, connecting it to various aspects of HRM processes, practices, relationships, and outcomes, thereby contributing to shaping the future of HRM research.

Human Resource Management and Artificial Intelligence: A Bibliometric Exploration

The concept of artificial intelligence, a driving force behind human resource management, has recently gained popularity in the academic community. This study explores the intellectual structure of this field using the Scopus database in the subject area of business, management and accounting. Bibliographic analysis, a recent and rigorous method for delving into scientific data, is used in this investigation. The approach used is a structured and transparent process divided into four steps: (1) search criteria; (2) selection of database and documents; (3) selection of software and data pre-processing; and (4) analysis of findings. We employ bibliometric mapping to observe their numerous linkages and performance evaluation to learn about their structure. A total of 67 articles were collected from the Scopus database between 2015 and 2022 using certain keywords (artificial intelligence, expert systems, big data analytics, and human resource management) and some specific filters (subject–business, management and accounting; language-English; document–article, review articles and source-journals). Ten research clusters were identified: Cluster 1: multi-agent system; Cluster 2: decision support system; Cluster 3: internet of things; Cluster 4: active learning; Cluster 5: decision tree; Cluster 6: optimisation; Cluster 7: software design; Cluster 8: data mining; Cluster 9: cloud computing; Cluster 10: human-robot interaction. The findings could be helpful for researchers and practitioners in the HRM field to extend their knowledge and understanding of AI and HRM research. This study can provide notable guidance and future directions for quite a few firms in expanding the use of AI in HRM.
 Keywords: Artificial intelligence, human resource management, bibliometric analysis

AI-Augmented HRM: Literature review and a proposed multilevel framework for future research

The research using artificial intelligence (AI) applications in HRM functional areas has gained much traction and a steep surge over the last three years. The extant literature observes that contemporary AI applications have augmented HR functionalities. AI-Augmented HRM HRM(AI) has assumed strategic importance for achieving HRM domain-level outcomes and organisational outcomes for a sustainable competitive advantage. Moreover, there is increasing evidence of literature reviews pertaining to the use of AI applications in different management disciplines (i.e., marketing, supply chain, accounting, hospitality, and education). There is a considerable gap in existing studies regarding a focused, systematic literature review on HRM(AI), specifically for a multilevel framework that can offer research scholars a platform to conduct potential future research. To address this gap, the authors present a systematic literature review (SLR) of 56 articles published in 35 peer-reviewed academic journals from October 1990 to December 2021. The purpose is to analyse the context (i.e., chronological distribution, geographic spread, sector-wise distribution, theories, and methods used) and the theoretical content (key themes) of HRM(AI) research and identify gaps to present a robust multilevel framework for future research. Based upon this SLR, the authors identify noticeable research gaps, mainly stemming from - unequal distribution of previous HRM(AI) research in terms of the smaller number of sector/country-specific studies, absence of sound theoretical base/frameworks, more research on routine HR functions(i.e. recruitment and selection) and significantly less empirical research. We also found minimal research evidence that links HRM(AI) and organisational-level outcomes. To overcome this gap, we propose a multilevel framework that offers a platform for future researchers to draw linkage among diverse variables starting from the contextual level to HRM and organisational level outcomes that eventually enhance operational and financial organisational performance.