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The research examines the role of Smart HRM 4.0 in developing dynamic capabilities and its impact on human resources and organizational performance.

The authors used a grounded theory approach and conducted interviews of 39 senior HR managers from IT, ITeS, consulting, services and E-commerce companies through a semi-structured questionnaire. The authors analyzed the interview data with NVivo 8.0 to identify the themes related to the dynamic capabilities to Smart 4.0 HR practices.

The study provides a conceptual framework for organizational performance using dynamic capabilities built due to Smart HRM 4.0 practices. Organizations use Smart HRM 4.0 to develop dynamic capabilities: building learning and knowledge sharing capability and integration, reconfiguration capabilities. Further, the dynamic capabilities contribute to HR and organizational performance.

This study divulges the role of Smart HRM 4.0 practices in developing dynamic capabilities in Indian firms. The study provides an appealing insight into the structural link between Smart HRM 4.0 and dynamic capabilities, which are yet to be explored. This study extends the Smart HRM 4.0 and dynamic capabilities concepts for senior HR professionals and contributes to human resource management and organizational performance literature.

This paper aims to investigate the use of Industry 4.0 (I4.0) technology and its barriers in human resourcemanagement (HRM) for Smart HR 4.0 and its impact on HR performance.

The research has been conducted using the grounded theory approach. Semi-structured interviews were conducted with 122 senior HR officers of national and multi-national companies in India after the extensive literature review. NVivo 8.0 software was used for the analysis of the interview data.

I4.0 technology is used for HRM functions by HR professionals. It is revealed that Smart HR 4.0 that emerged from the I4.0 technology has leveraged the HR performance. It is also found that usage barriers, traditional barriers and risk barriers affect the use of I4.0 technology in HRM.

A model is developed using the grounded theory approach for HR managers to understand the impact of I4.0 on HRM. This study reveals the barriers affecting the use of I4.0 technology in HRM. It also provides the model for HR performance that emerged through the use of I4.0 technology in HR and Smart HR 4.0. The research delivered key insights for the HR professionals, marketers of HR technology and technology developers.

The purpose of this paper is to address the potential impacts of Industry 4.0 on human resource management (HRM) – with a particular focus on employment, job profile and qualification and skill requirements in the workforce – which can have implications for supply chain management (SCM). Consequently, exploratory relationships among Industry 4.0, HRM and SCM are presented based on a systematic review.

To explore Industry 4.0 literature and its impact on employment, the authors used a systematic literature review to identify, classify and analyze current knowledge, flagging trends and proposing recommendations for future research in this area. Using the Web of Science database, the authors utilized co-citation software to visualize the networks which emerged from recurrent terms and which were then used to develop the categories of analysis.

The authors can affirm that the literature in this field is in a transition process, from the early studies of German academics to the current development of new impacts worldwide. Industry 4.0 is the central theme of the literature analyzed and is accomplished through the development of employment, qualifications, skills and learning frameworks. The results reveal that most papers are conceptual, with quantitative studies still lacking. Developed countries have a leading role in terms of research production, while Latin America and Asia are far behind. Clustering reveals four dominant themes (educational changes, employment scenario, work infrastructure resources and work meaning and proposal). The first refers to labor changes around working conditions, the work environment and new skills which are required. The second main theme concerns the potentially unstable shift in the labor market has toward a high-level context. The third is about the technical interface of humans and machines, and finally, the fourth understands the German industry as a starting point for global industrial improvements and work proposal changes. Furthermore, socio-technical systems cover the implications of HRM for SCM in three different dimensions: qualification and education (human competences), collaboration and integration of SCM (organizational competences) and data and information management (technical competences).

An original research agenda for further development of the topic. Additionally, the implications of the findings for SCM practitioners are presented.

SCM managers can benefit from the results of this paper by developing adjusted polices for organizational and human aspects. Specially about training programs to improve technology skills and education programs for cyber-human new plataforms.

So far, Industry 4.0, HRM-related topics and implications for SCM have generally been considered separately. This paper elucidates the few important studies on the impacts of Industry 4.0 on human-related topics, such as the labor market, building a research framework using the main contributions highlighted in the literature. An original research agenda is presented, as well as potential implications for SCM.

Smart HR 4.0 is a new concept characterized by adopting innovative technologies of Industry 4.0 (I4.0) in the HR domain. This study attempts to identify the key factors of Smart HR 4.0 to foster organizational innovation ambidexterity.

Based on review of literature and survey from expert opinions by using the Delphi method, 12 factors were found most suitable for this study. Further, the fuzzy-TISM technique was used to establish contextual relationships and develop a hierarchical model on the identified factors. Subsequently, the MICMAC analysis was applied to classify these factors according to their driving and dependence power.

This study framed a conceptual hierarchical model of Smart HR 4.0 and established contextual relationships among identified factors. Result shows that smart organic structure, industry–institute interface, IT-enabled system and ambidextrous leadership are important factors as they have the highest driving power. Further, knowledge management, learning culture and psychological empowerment are the linkage factors having both driving as well as dependency power in the whole system.

This study can guide the managers in smoothly implementing these practices to manage their human capital amidst digital disruption, ensuring innovation competitiveness of the firm. The structural hierarchical framework of Smart HR 4.0 may serve as a blueprint for HR professionals and business leaders to attain organizational innovation ambidexterity in the current wave of digital disruptions (Industry 4.0).

This study provides a holistic model of smart HR 4.0 integrating innovation ambidexterity in I4.0.

The pace of transformation in the business landscape has made it mandatory for the human resource function within the organisation to evolve, adapt and adjust to the demands of the marketplace. This chapter focuses on HRM 4.0 and the change in employer branding strategies due to rapid increase in digitalisation, for example, through analytics and big data. A conceptual framework is provided that links HRM 4.0 with employer branding strategies.

This study aims to demystify the mediating mechanism behind the relationship between green human resource management (HRM) and an organization’s environmental performance with the support of resource-based view theory and social exchange theory. Specifically, this study investigates the sequential mediation of green work engagement and green innovation on the direct effect of green HRM on environmental performance.

This quantitative study collected data from 311 employees working in various Indian manufacturing firms using an online survey. Structural equation modeling was used to determine the model fit of the serial mediation model, and PROCESS macro was used to test the hypotheses.

The findings of the study revealed the following important results. First, green HRM positively affects an organization’s environmental performance. Second, green work engagement mediates the effect of green HRM on environmental performance. Third, green innovation mediates the effect of green HRM on environmental performance. Fourth, green work engagement and green innovation sequentially mediate the green HRM–environmental relationship.

This study offers the following practical implications. First, it improves the managerial comprehension of the processes in enhancing environmental performance. Second, it implies that managers need to implement green HRM in their organizations as they play a pivotal role in improving employees’ green work engagement, organizations’ green innovation and environmental performance.

The present study is one of the primary research works that examined the serial mediating effect of green work engagement and green innovation in the relationship between green HRM and environmental performance. This study enriches the existing literature on green HRM and environmental performance by uncovering the mediating mechanism of green work engagement and green innovation.

Green human resource management (HRM) plays a vital role in improving employees’ green behaviour. A research gap exists in the roles psychological green climate and employee green commitment have in the relationship between green HRM and employees’ green behaviour. Building on social exchange and social identity theories, this study aims to propose a model of the effects of green HRM on employees’ green behaviour through the serial mediation of psychological green climate and employee green commitment.

Data were collected from 297 full-time employees working in various manufacturing organizations in India using cross-sectional research design and self-reported measures. Structural equation modelling was used to examine the model fit of the serial mediation model, and PROCESS macro with a bias-corrected bootstrapping method was used to test the hypotheses.

The result of the study revealed that green HRM impacts employees’ green behaviour. Further, the findings showed that both psychological green climate and employee green commitment individually mediate the relationship between green HRM and employees’ green behaviour. The key outcome of this research is the partial serial mediation of psychological green climate and employee green commitment in the relationship between green HRM and employees’ green behaviour.

This is one of the primary studies that examined the serial mediating effect of psychological green climate and employee green commitment in the relationship between green HRM and employees’ green behaviour. This study contributes to the existing literature on green HRM and green behaviour by evincing the mediating mechanism of psychological green climate and employee green commitment.

This paper investigates effective human-robot collaboration (HRC) and presents implications for Human Resource Management (HRM). A brief review of current literature on HRM in the smart industry context showed that there is limited research on HRC in hybrid teams and even less on effective management of these teams. This book chapter addresses this issue by investigating factors affecting intention to collaborate with a robot by conducting a vignette study. We hypothesized that six technology acceptance factors, performance expectancy, trust, effort expectancy, social support, organizational support and computer anxiety would significantly affect a users' intention to collaborate with a robot. Furthermore, we hypothesized a moderating effect of a particular HR system, either productivity-based or collaborative. Using a sample of 96 participants, this study tested the effect of the aforementioned factors on a users' intention to collaborate with the robot. Findings show that performance expectancy, organizational support and computer anxiety significantly affect the intention to collaborate with a robot. A significant moderating effect of a particular HR system was not found. Our findings expand the current technology acceptance models in the context of HRC. HRM can support effective HRC by a combination of comprehensive training and education, empowerment and incentives supported by an appropriate HR system.

The study explores the factors affecting the use of smart human resource management 4.0 (SHRM 4.0) practices and its effect on dynamic capabilities and, consequently, on organizational performance.

The authors used socio-technical and dynamic capabilities theory to propose the notable research model. The authors explored the factors driving the use of SHRM 4.0 practices and their contribution to organizational performance through the development of dynamic capabilities. The authors collected data from 383 senior HR managers using a structured questionnaire, and PLS-SEM was used to analyze the data.

The results show that socio-technical factors such as top management support, HR readiness, competitive pressure, technology readiness and perceived usefulness influence the use of SHRM 4.0 practices, whereas security and privacy concerns negatively influence them. Furthermore, the authors also found the use of SHRM 4.0 practices influencing the dynamic capacities (build (learning), integration and reconfiguration) and, subsequently, its impact on organizational performance.

Its novelty lies in developing a model using dynamic capabilities and socio-technical theory to explore how SHRM 4.0 practices influence organizational performance through dynamic capabilities. This study extends the literature on SHRM 4.0 practices, HR technology use, HR and dynamic capabilities by contributing to socio-technical theory and dynamic capabilities and expanding the scope of these theories in the area of HRM. It provides crucial insights into HR and top managers to benchmark SHRM 4.0 practices for improved organizational performance.

The purpose of this article is to examine all the studies carried out within the scope of e-HRM and smart HRM, grouped according to the sub-functions of technical and HRM. The use of technology in HRM has started since the mid-1990s. However, this study focused on the articles published after 2014 in order to keep up to date. Any search strategy should allow for the completeness of the search to be evaluated. The terms “electronic-HRM”, “AI and HRM”, “Industry 4.0 and HRM”, “Society 5.0 and HRM”, “Human Resource Information Systems” and “Digital Technologies and HRM” “Human-robot interaction” has been questioned in IEEE Xplore, ALM digital library, Emerald Insight, SpringerLink, and Science Direct. The Web of Science and Scopus were also queried to double-check the findings and find other relevant articles in lesser-known libraries. Google Scholar was also used for forward and backward searches. These online databases have been chosen because they present the most important peer-reviewed full-text journals, conference proceedings, book chapters. Then, the references of each article were reviewed for additional articles on digital technologies and HRM. Each subsequent article is then reviewed for additional reference.

A total of 5,580 articles have been reviewed. Duplicate items have been removed. The titles and abstracts of 3,500 articles have been scanned to identify potential articles. The full-text evaluation of 2,554 was based on compliance with the inclusion criteria. In addition, 2,458 studies have been excluded. In total, 96 studies have been selected for data extraction. Additionally, questionnaires and reviews have been used to provide comprehensive research on e-HRM and smart HRM. The search terms used are expected to cover most, if not all, of the studies involving e-HRM and smart HRM.

The study carried out in this article is qualitative research. In the article, which methods are used and what has changed in e-HRM and smart HRM are examined. In particular, it has been thought about what can happen with the inclusion of human-machine interaction, AI, chatbots, industry 4.0 and information systems in HRM. Unlike previous studies, this review takes HRM from a broader perspective and groups it by topic, both by technical and HR functions. In addition, the reviewed articles provide brief information about the AI technologies used. In particular, criteria were taken into account according to the field, type and subject of the articles.

This study has the distinction of being the first in the literature in terms of examining all the studies carried out within the scope of e-HRM and smart HRM and grouped according to the sub-functions of technical and HRM in line with its purpose. The article focuses specifically on research published after 2014. It is expected to contribute to the literature in terms of collecting all studies in a single article. Other contributions of this article can be summarized in four main articles: 1) it presents a summary of previous research by grouping the studies on e-HRM and smart HRM according to the interests of researchers. 2) It saves time for the reader as it provides a brief explanation of the studies on the subject. 3) Instead of explaining in detail the general details analyzed in other articles, it offers a practical perspective by focusing on the type, subject and field of the article. 4) With the digitalization of HRM, new, up-to-date research and techniques are introduced.