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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.

Due to government policies, accreditation demands, competition, digital India reforms and National Education Policy (NEP) 2020, the need for electronic human resource management (e-HRM) has increased considerably in the Indian higher education (HE) sector, but the literature has revealed that the adoption of e-HRM practices in Indian HE institutions (HEIs) is still in its embryonic stage; therefore, the purpose of the current qualitative study is to explore the challenges and facilitators of e-HRM adoption in the Indian HE sector through interpretative phenomenological analysis (IPA).

The present study incorporates IPA, to capture the personal lived experiences of the HR executives employed in the Indian HEIs. Using purposive sampling, semi-structured interviews were conducted with the HR executives employed in Indian universities and institutions to know the perspectives on the adoption of e-HRM practices in Indian HEIs.

The study identified two superordinate themes, namely, challenges and facilitators of e-HRM adoption in the Indian HE sector. The superordinate theme “challenges” comprises eight sub-themes. Further, the theme “facilitators” consists of six subthemes.

The study has implications for the stakeholders of the HE sector, i.e. HR practitioners, top executives of the HE sector, government and HE regulators and other stakeholders of the HE sector.

This study has given deep insights into the challenges and facilitators in the adoption of e-HRM practices in the Indian HE sector, and to the best of the authors’ knowledge, no study till date has filled this knowledge gap through qualitative exploration using IPA.

The advancement in science and technology has led to the existence and continuous growth of various physical machines and now computer programs which are supposed to perform once thought unbelievable multi-tasks for humans.

Many firms, governments, industries and syndicates are switching to automated process for achieving maximum output and having minimum cost and errors in the manufacturing and various other processes, hence the role of human involvement is getting decreased. With the Industry 4.0 standards being opted, industry gurus have been forecasting the limiting power of human labour and interaction and fears exist complete replacement of human beings from the working environment by robots and automated machines.

Artificial intelligence has aggressively overtaken almost all fields of businesses and human resource (HR) hasn't been either immune to that. Robotics is an important factor as well.

Technology implementation has its own benefits and negative impacts which is creating fears among various professionals with regards to their complete replacement by machines.

The following paper looks deeply into various researches performed by scholars to have a thorough knowledge of present-day status of human–machine collaboration and the challenges organizations are facing. It will help in understanding the current scenario of HR with modern technologies.

The purpose of this study is to add to the currently limited research on individual level people analytics (PA) adoption by focusing on a vital resource in the implementation of PA, namely the technology used for PA. We draw on the unified theory of acceptance and use of technology (UTAUT) to examine antecedents of the use of technology for PA.

This study uses latent profile analysis to examine how different antecedents of PA (technology) adoption jointly act among 279 users of a specific PA technology.

This study identifies four user profiles, that we labeled the skeptic diplomats, the optimistic strugglers, the optimists, and the enthusiasts. These profiles relate to differences in user satisfaction and the frequency and versatility of PA technology use. This study demonstrates that performance benefits, social influence, required effort, and facilitating conditions jointly affect the use of PA technology, but that the latter two might be the most influential factors.

This study offers recommendations to practitioners and organizations on which actions by managers and the organization can be taken to support the use of PA technology.

Compared to previous research, we take a different approach by applying latent profile analysis to examine the combined effect of antecedents on user behavior and user satisfaction. In addition to a different analytical approach, we also extend existing research on individual PA adoption by focusing on actual behaviors and behavioral intention.

The aim of this study is to examine in detail the impact of technological advancements on the workforce within the tourism industry. Specifically, it seeks to understand the effects of information and communication technologies (ICT), social media, the internet and websites, mobile technologies and other technological developments on workforce dynamics, skill requirements and job descriptions. The research intends to analyze how technological innovations are transforming the workforce and how these transformations are influencing practices within the industry.

This study employs a comprehensive literature review to understand the impact of technological innovations on the workforce in the tourism industry. The research aims to conduct an in-depth examination of empirical data obtained from extensive databases in the fields of technology and tourism and detail the effects of technological advancements on the workforce. Additionally, it includes a general assessment of trends and transformation processes within the sector by synthesizing findings from existing literature on the relationship between technology and workforce.

The results of the research reveal that technological innovations have fundamentally transformed workforce dynamics and job descriptions. Developments in information technology have led to the automation of routine tasks and the creation of high-skilled new job roles. Social media has contributed to the emergence of new job roles and skill requirements, while the internet and websites have altered digital marketing strategies. Mobile technologies have increased the necessity for the workforce to develop mobile skills. Furthermore, big data and artificial intelligence applications have enhanced the workforce’s data management and analysis capabilities.

This study makes a significant contribution to understanding the impact of technological innovations on the workforce in the tourism industry. The findings emphasize how technological changes have altered skill requirements and job descriptions, highlighting the increased need for continuous education and skill development.

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.

The dynamic environment has necessitated searching for new ways for managing and grooming people for better performance. The purpose of this study is to explore ambidexterity in human resource management (HRM) for better management of paradoxical tensions and its effect on employee performance. Further, this research also addresses the black box in this relationship by evaluating the extraneous (managers’ ambidextrous orientation) and mediating (individual ambidexterity) variables in this relationship.

A quantitative research methodology has been used to explore the ambidexterity in HRM and its impact on employee performance. Around 470 banks have been contacted for data collection. The data have been thoroughly examined for reliability and validity. Further, it has also been checked for common method variance.

The findings revealed that individual ambidexterity mediates the relationship between ambidextrous HRM and employee performance. Further, managers’ ambidextrous orientation moderates the relationship between ambidextrous HRM and individual ambidexterity.

The present study makes an important contribution to the strategic HRM literature in general. The theoretical and practical implications have also been put forth for academic and practical fields. Lastly, the study contributes towards ambidexterity literature by examining it from an HRM perspective.

With the recent proliferation of AI, organisations are transforming not only their organisational design but also the input and output operational processes of the hiring process. The purpose of this paper is to explore the organisational and operational dimensions resulting from the deployment of AI during talent acquisition process.

The authors conducted semi-structured interviews and meetings with human resources (HRs) professionals, recruiters and AI hiring platform providers in Sweden. Using an inductive data analysis rooted in the principles of grounded theory, the study uncovered four aggregate dimensions critical to understanding the role of AI in talent acquisition.

With insights from algorithmic management and ambidexterity theory, the study presents a comprehensive theoretical framework that highlights four aggregate dimensions describing AI’s transformative role in talent recruitment. The results provide a cautionary perspective, advising against an excessive emphasis on operational performance driven solely by algorithmic management.

The study is limited in scope and subject to several constraints. Firstly, the sample size and diversity are restricted, as the findings are based on a limited number of semi-structured interviews and meetings with HRs professionals, recruiters, and AI hiring platform providers. Secondly, the rapid evolution of AI technologies means that the study’s findings may quickly become outdated as new advancements and applications emerge.

The results provide managers with actionable information that can lead to more precise and strategic management practices, ultimately contributing to improved organizational performance and outcomes. Plus, enhancing their ability to make informed decisions, optimize processes and address challenges effectively.

The results signal both positive and negative impacts on employment opportunities. On the positive side, AI can streamline recruitment processes, making it easier for qualified candidates to be identified and hired quickly. However, AI systems can also perpetuate existing biases present in the data they are trained on, leading to unfair hiring practices where certain groups are systematically disadvantaged.

By examining the balance between transactional efficiency and relational engagement, the research addresses a crucial trade-off that organizations face when implementing AI in recruitment. The originality lies in its critique of the prevailing emphasis on e-recruiting.

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.

Addressing workforce shortages in operations and supply chain management (OSCM) necessitates adaptive measures by both individuals and organizations, with a pivotal role played by Human Resources (HR). This impact pathway delves into how healthcare organizations can effectively manage workforce shortages, informed by HR practices. Through an in-depth understanding of healthcare organizations, the authors pinpoint challenges and concerns linked to workforce shortages. Pathways are proposed to stimulate future OSCM research and collaboration, leveraging innovative and creative methods from the HR field.

Data was collected from various representatives from healthcare organizations to explore how healthcare organizations for people with intellectual disabilities address the challenges stemming from contemporary workforce shortages.

Three pathways were outlined to address workforce shortages in healthcare supply chains, utilizing intellectual disability care as a representative example. These pathways comprise optimizing the potential of the current workforce, illustrating innovative HR practices for enhancing their performance, and proposing strategies for retaining these valuable workers.

Despite its potential, the HR domain remains relatively underdeveloped within OSCM research. The authors show how HR practices can potentially mitigate impending workforce shortages. While utilizing intellectual disability care as a representative example, this paper proposes that the impact pathways identified can be extended to various other healthcare settings.