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This chapter discusses how the real options theory can be useful for understanding the adoption of human resources management (HRM) practices. The authors review how the real options theory has provided insights into the processes through which firms manage uncertainties involved in the adoption of HRM practices. The authors offer propositions for future HRM research from the real options perspective. The authors contend that analyzing HRM practice adoptions through the lens of real options theory can enhance our understanding of the mechanisms through which firms choose which HRM practices to adopt and how they adjust the timing, scale, and methods of investment in these practices. Specifically, the authors suggest that differences in information relevant to valuation of HRM options are the source of distinct choices of HRM options across firms. Finally, the authors propose advancing knowledge on HRM practice adoptions by using a portfolio of options approach, as well as considering factors like competitors, path dependence, and switching options.

The main goal of any organization is to achieve the best quality of work through employees, and managers play a very important role in this field. Managers and leaders of organizations often face with paradoxes that make decision-making difficult. The purpose of this paper is to develop a competency model for human resource managers considering the importance of the role of paradoxes for organizations.

The research methodology is of a mixed type and with an approach based on paradox theory and using theme analysis and fuzzy Delphi, it seeks to provide a model of paradoxical managers’ competence. The statistical sample included 11 experts working in the information and communication technology industry, who were selected using the snowball and judgmental sampling method.

The results of this research show that the competency model of human resource managers has three managerial, organizational and individual levels and has 15 themes including strategic partner, organizational knowledge, awareness of the industry environment, awareness of the external environment, paradoxical thinking, managerial knowledge, relationship management, resource management , leadership, human resources analyzer, information technology (IT) knowledge, personality traits, development, multitasking and cognitive competence. The most important theme identified is paradoxical thinking and familiarity with IT knowledge, and it is suggested that human resource managers working in this field should preferably study technical and engineering fields at the undergraduate level and shift to human resource management fields at the graduate level.

The distinguishing feature of this paper is the presentation of a competency model based on paradox theory. Paradoxes are part of organizational life. Therefore, there should be a paradoxical view in all organizational analysis.

This paper tries to retrospect the mounting application of machine learning (ML) and artificial intelligence (AI) in the human resource management area. The document applies bibliometric analysis and uses relational techniques to explore dimensions of documents in the field. The results highlight publication trends, most impactful authors, countries and institutes in the research area. The science mapping along with co-citation and bibliometric coupling analysis revealed major developments in the field. The thematic mapping and trend analysis highlighted the past and emerging trends towards significant and impactful research in the areas of robotics, big data, AI and data analytics. This paper sets the base for future researchers by coordinating and combining various past researches to help in understanding the evolution of ML and AI in human resource management and expansion of knowledgebase.

Applying resource-based view and the configurational approach theory, this study seeks to understand the moderating role of age and gender between human resource practices and employee competencies relationship.

43 food processing firms of India participated in the study. Applying multilevel approach, the responses of 295 human resource managers and 3,557 employees were used for the analysis.

The human resource practices–employee competencies relationship was stronger in the case of young employees. Furthermore, the relationship was better in case of male employees over female employees. The results urge for greater attention toward age and gender diversity issues while tailoring human resource practices for enhancing employee skills. This article contributes the human resource management literature by exploring the role of age and gender, which has been used as the control variables as the moderating variables for governing the human resource practices–employee competencies relationship.

Special focus can be placed on extensive custom in-house training and development activities. Proper division of work can be done for new employees and experienced employees depending upon their learning capabilities. The firms can do so by either implementing formal or informal organizational structures to achieve full gains. Firms should focus largely on narrowing the development practices adopted for diverse age groups of workforce population. The four practices proposed by the Organization for Economic Cooperation and Development (2006) for ensuring effectiveness of development practices and its impact on old age employee effectiveness and attitude should be put in practice.

The originality of this study lies in its exploration of the intricate interplay among age, gender and human resource practices in shaping employee competencies. By understanding how these factors interact within the human resource practices–employee competencies framework, this research offers a unique perspective on the evolving workforce dynamics. It goes beyond the conventional human resource management strategies to uncover nuanced insights, shedding light on tailored approaches that consider the specific needs and aspirations of diverse employees. This innovative perspective contributes to a more inclusive, efficient and adaptable work environment, enriching both the academic understanding of human resources and the practical implementation of strategies for contemporary organizations.

Artificial intelligence (AI) can enhance human resource resiliency (HRR) by providing the insights and resources needed to adapt to unexpected changes and disruptions. Therefore, the present research attempts to develop a framework for future researchers to gain insights into the actions of AI to enable HRR.

The present study used a systematic literature review, bibliometric analysis, and network analysis followed by content analysis. In doing so, we reviewed the literature to explore the present state of research in AI and HRR. A total of 98 articles were included, extracted from the Scopus database in the selected field of research.

The authors found that AI or AI-associated techniques help deliver various HRR-oriented outcomes, such as enhancing employee competency, performance management and risk management; enhancing leadership competencies and employee well-being measures; and developing effective compensation and reward management.

The present research has certain implications, such as increasing the HR team's proficiency, addressing the problem of job loss and how to fix it, improving working conditions and improving decision-making in HR.

The present research explores the role of AI in HRR following the COVID-19 pandemic, which has not been explored extensively.

Organizational scholars studying compensation often place an emphasis on certain employee groups (e.g., executives). Missing from this discussion is research on the compensation systems for low-wage jobs. In this review, the authors argue that workers in low-wage jobs represent a unique employment group in their understanding of rent allocation in organizations. The authors address the design of compensation strategies in organizations that lead to different outcomes for workers in low-wage jobs versus other workers. Drawing on and integrating human resource management (HRM), inequality, and worker literatures with compensation literature, the authors describe and explain compensation systems for low-wage work. The authors start by examining workers in low-wage work to identify aspects of these workers’ jobs and lives that can influence their health, performance, and other organizationally relevant outcomes. Next, the authors explore the compensation systems common for this type of work, building on the compensation literature, by identifying the low-wage work compensation designs, proposing the likely explanations for why organizations craft these designs, and describing the worker and organizational outcomes of these designs. The authors conclude with suggestions for future research in this growing field and explore how organizations may benefit by rethinking their approach to compensation for low-wage work. In sum, the authors hope that this review will be a foundational work for those interested in investigating organizational compensation issues at the intersection of inequality and worker and organizational outcomes.

Talent management is conducted to maximize an organization's overall performance and efficiency which helps to serve as a competitive advantage. Human resource management is a concept which includes human-related activities, but talent management is a strategy which helps to get new talent, develop their skill sets and provide better employee engagement and experience to retain the top potential employees in an organization. Improvement in recruiting and retention of a workforce results from a well-executed talent acquisition approach. In the 21st century, employee retention has become a primary concern for the organizations specially with work from home and hybrid models.

The workforce for tomorrow is going to be very different from what it has been. Technology is transforming the way people work within organizations. The workplace is rapidly evolving in terms of people and processes and is going through a lot of technological changes. The terminologies such as automation, artificial intelligence, augmented reality and block chain technologies are slowly becoming part of the workplace and everyday activities of the organization.

The challenges are many and especially post-pandemic organizations are going through some major changes such as a mindset shift of employees to take up more remote working opportunities, building virtual teams, increase in the gig economy workers (contractual workers) and a diverse workforce which makes it even more challenging for the organization to manage and retain talent.

This systematic literature review aims to explore the adoption, global acceptance and implementation of human resources (HR) analytics (HRA) by reviewing literature on the subject. HRA adoption can assist HR professionals in managing complex procedures and making strategic human resource management (SHRM) decisions more effectively. The study also aims to identify the applications of analytics in various disciplines of management.

The review is conducted using a domain-based structured literature review (SLR), emphasizing the diffusion of innovative thinking and the adoption process of HRA among early adopters. The philosophical stances are analyzed with the combination of research onion model and PRISMA protocol. Secondary data are gathered from published journals, books, case studies, conference proceedings, web pages and media stories as the primary source of information.

The study finds that skilled professionals and management assistance can significantly impact adoption intentions, enabling professionals to deal with analytics. The examples and analytical models provided by early adopters allow managers to manage complex processes and make SHRM decisions.

The study suggests that the lack of use of quantitative techniques is a key limitation and should be considered in future studies. Despite the rise in the number of research papers on HRA, its application in the workplace remains limited.

This research can assist managers in implementing HRA and help resolve complex and inefficient processes, making SHRM decisions.

This study adds to the existing body of knowledge on how HRA can aid a company's efficacy and performance and can be considered one of the first to link adoption and HRA.

This study examines the impact of perceived human resource management practices on talent turnover intention, with work engagement mediating and self-efficacy moderating the relationship. It examines how employees' perceptions of pay satisfaction, empowerment, participation and communication are related to their turnover intentions.

A total of 283 valid questionnaires from UAE government employees were used for data analysis. Partial least squares structural equation modeling (PLS-SEM) was used to examine the proposed hypothesis.

The results reveal that employees' perceptions of pay satisfaction, empowerment, participation and communication are significant contributors to work engagement. The findings further demonstrate that work engagement significantly negatively affects talent turnover intention and acts as a mediator between employees' perceptions of individual human resource management practices and talent turnover intention. However, the results contradict the hypothesis that self-efficacy moderates the association between work engagement and talent turnover intention.

This study focuses on the impact of perceived human resource management practices on talent turnover intention, an area that has received limited attention in literature. By focusing on perceived human resource management practices, this study illuminates employees' subjective experiences and how they perceive human resource management practices intended to reduce talent turnover intention. The inclusion of the mediating effect of work engagement offers a more profound understanding of how employees' perceptions of human resource management practices influence their turnover intentions. This comprehensive approach to understanding the interplay between these variables provides valuable insights for organizations seeking to improve their human resource management practices and talent turnover intention.

The aim of this study is to review the literature on how intellectual capital (IC) contributes to the decarbonization efforts of firms. It explores how carbon accounting can measure the components of IC in decarbonization efforts to balance profitability with environmental and social goals, particularly in promoting decent work and economic growth (Sustainable Development Goal [SDG] 8 and its targets [2, 5, 6, 8]). Moreover, it emphasises the importance of multi-stakeholder partnerships for sharing knowledge, expertise, technology, and financial resources (SDG17-Target 17.G) to meet SDG8.

As a consolidated methodological approach, a systematic literature review (SLR) was used in this study to fill the existing research gaps in sustainability accounting. To consolidate and clarify scholarly research on IC towards decarbonization, 149 English articles published in the Scopus database and Google Scholar between 1990 and 2024 were reviewed.

The results highlight that the current research does not sufficiently cover the intersection of carbon accounting and IC in the analysis of decarbonization practices. Stakeholders and regulatory bodies are increasingly pressuring firms to implement development-focused policies in line with SDG8 and its targets, requiring the integration of IC and its measures in decarbonization processes, supported by SDG17-Target 17.G. This integration is useful for creating business models that balance profitability and social and environmental responsibilities.

The integration of social dimension to design sustainable business models for emission reduction and provide a decent work environment by focusing on SDG17-Target 17.G has rarely been investigated in terms of theory and practice. Through carbon accounting, IC can be a key source of SDG8-Targets 8.[2, 5, 6, 8] and SDG17-Target 17.G. Historically, these major issues are not easily aligned with accounting research or decarbonization processes.