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Due to the global labor market challenges, international companies react and adjust fast to these circumstances by implementing digital solutions into all business processes. Organizational ambidexterity is seen as the response of digital transformation and it can be divided into structural, contextual, and sequential dimensions. In this context, organizations representing the smart industry will need employees with specific competencies which let them meet technological challenges.

This chapter aims to clarify the state of opinion on expectations towards, and preparedness for, the impact of Industry 4.0 on human resources management and the implementation of various types of ambidexterity in these companies. We have conducted interviews with key HR informants from manufacturing companies operating in Germany and Poland. We have found that Industry 4.0 has a significant impact on HR practices. In both international companies, various digital solutions in employee recruitment, development, and performance, have been implemented. There have also been mature examples in both companies of structural, contextual, and sequential ambidexterity.

This paper explores the use of social media (SM) in Human Resource Management (HRM). Building on the configurational approach, the study investigates the existence of different configurations of social e-HRM, their consequences for the organizations and their predictors.

This empirical study draws on a survey administered to HR directors of 176 companies operating in Italy. Two-step cluster analysis, test for variance and logistic regressions were employed for data analysis.

Three social e-HRM configurations emerged – non-use, relational use and extended relational use – which distinguish different goals for using SM in HRM. The three configurations lead to similar outcomes for organizations, even if SM users, in general, enjoy greater success than non-users. Certain structural, strategic and HRM factors are systematically and variously associated with each configuration.

The study is based on cross-sectional research, and thus it is difficult to identify causal links between the variables. The study also relies on data collected in a specific national context, which limits the generalizability of the results.

The study suggests that different and equally effective social e-HRM configurations exist and that their presence is predicted by specific structural, strategic and HRM factors.

The study contributes to an emerging and still scarce literature on types, drivers and outcomes of SM use in HRM.

The purpose of this study is to examine the perceptions of the human resources (HR) function from millennials and postmillennials who are either just finishing college or already in the early stages of their careers. Previous works have often revealed negative stereotypes toward HR, and this study serves to discover whether these perceptions are changing. Further, the study aims to address the origins of and reasoning behind these new perceptions.

A two-study survey research design using a sample of 106 college of business students (Study 1) and an additional sample of 135 former business students who have graduated since 2011 (Study 2) is used.

The results demonstrate that perceptions of HR are changing and quite positive, with the majority of these perceptions originating from personal experiences. In fact, the vast majority of respondents not only felt positive about HR but also like and trust their HR representatives.

Results also suggest that there may be a disconnect between perceptions of the HR function and its actual purpose, suggesting that HR professionals need to better educate others about their important role as a strategic business partner.

The purpose of this paper is to critically study the implementation and contextualization of the human resource transformation (HRT) management model within the human resources (HR) function of a global industrial company group.

A qualitative case study that includes two data collections.

Implementation of the HRT model led to tensions and conflicting interpretations of the mission of the HR function, and a “tug of war” about the distribution of work both within HR and between HR and line management. Splitting the HR function into three legs made the HR function's learning cycles more difficult. The corporate group had a decentralized and diverse business culture, and contextualization of the HRT model to this setting highlighted the model's embeddedness in the American business culture of centralization and standardization. Implementation of the model also entailed a transition from an employee to an employer perspective within HR.

For an assessment of HR's total work other parts of the HRT model (Ulrich and Brockbank, 2005) need to be involved since HR professionals in the insourced or outsourced shared service center (SSC) and Center of Expertise (CoE) and the e-HR tools are equally important for executing the total HR's mission. Further studies of the problematic human resource business partner (HRBP) role are needed and also what the development of e-HR solutions means for the HR profession.

The authors argue for a continuous development of HR work, along with closer professional contact both with line managers (LMs) and within the HR function, for improved learning cycles and a need for contextualization when implementing management models.

The paper discusses the HRT model's impact on HR practitioners’ and LMs’ work practice.

This article shows the need for contextualization when implementing management models. The lack of such contextualization led to severe tensions, and the intentions of an efficient and respected HR function were not achieved. The study contributes an evaluation of the tensions between HRT as a normative and standardized model in business settings accustomed to variety and decentralized decision-making.

According to the significant growth of literature and continued adoption of people analytics in practice, it has been promised that people analytics will inform evidence-based decision-making and improve business outcomes. However, existing people analytics literature remains underdeveloped in understanding whether and how such promises have been realized. Accordingly, this study aims to investigate the current reality of people analytics and uncover the debates and challenges that are emerging as a result of its adoption.

This study conducts a systematic literature review of peer-reviewed articles focused on people analytics published in the Association of Business School (ABS) ranked journals between 2011 and 2021.

The review illustrates and critically evaluates several emerging debates and issues faced by people analytics, including inconsistency among the concept and definition of people analytics, people analytics ownership, ethical and privacy concerns of using people analytics, missing evidence of people analytics impact and readiness to perform people analytics.

This review presents a comprehensive research agenda demonstrating the need for collaboration between scholars and practitioners to successfully align the promise and the current reality of people analytics.

This systematic review is distinct from existing reviews in three ways. First, this review synthesizes and critically evaluates the significant growth of peer-reviewed articles focused on people analytics published in ABS ranked journals between 2011 and 2021. Second, the study adopts a thematic analysis and coding process to identify the emerging themes in the existing people analytics literature, ensuring the comprehensiveness of the review. Third, this study focused and expanded upon the debates and issues evolving within the emerging field of people analytics and offers an updated agenda for the future of people analytics research.

Studies of inter-organizational relationships have traditionally overlooked the human resource management (HRM) field, with most research focusing on collaborations in the technical domain. This study endeavors to explore the impact of organizational human resources (HR) collaborations on HR innovativeness, drawing on theories about organizational learning capabilities to explain this connection. By analyzing the synergies arising from inter-organizational HR collaborations, this study aims to seek to shed light on the potential for HRM to contribute to organizational performance and foster innovation.

The study is based on a quantitative survey conducted among 326 Dutch companies. The survey aims to find out whether these companies collaborate with other organizations on HR-related issues, the extent to which they renew their HRM function, and whether they apply organizational learning practices. The data collected for the survey are analyzed using Hayes PROCESS macro to investigate mediation effects.

As per the study, HR collaboration results in innovation. The research suggests that collaborating with HR across different organizations significantly contributes to HR innovation. This relationship can be explained by the inter-organizational learning practices that organizations adopt. Therefore, when organizations collaborate with each other, they learn from each other, which enhances their learning capabilities and ultimately leads to HR innovation.

This study delves into the extent to which organizations collaborate on HR-related issues, which is a relatively new field. Moreover, it contributes to the research on the connection between inter-organizational relationships and innovation by showing how much of it is explained by organizational learning.

The purpose of this paper is to examine whether employee outcomes of employee performance and job satisfaction mediate and enhance the effect of e-HRM usage on organizational performance.

Data were collected through a survey involving 35 organizations using e-HRM systems. A partially mixed sequential dominant status explanatory design was used for the study. A stratified convenience sampling technique was used for the quantitative phase of the study. A purposive sampling technique was employed for the qualitative phase. A structural equation modelling technique with the use of the process macro approach was used to analyse collected data.

There is a positive relationship between e-HRM usage and employee outcomes. Employee performance and job satisfaction mediate the effect of e-HRM usage on organizational performance. Employee performance and job satisfaction are contextual variables that characterize effective e-HRM configurations.

Organizations should invest in employee outcomes in order to maximize the potential of e-HRM. The e-HRM configurations characterized by a multiplicity of dimensions are more likely to add to organizational value creation. The deployment of e-HRM systems should be preceded by high levels of employee performance and job satisfaction, for organizational success.

The study contributes to a growing body of knowledge on dimensions, which characterize effective e-HRM configurations, yielding organizational success. Employee performance and job satisfaction should be added to the characteristics of effective e-HRM configurations.

The purpose of this paper is to examine the influence of the emotional intelligence (EI) of the person in charge of making human resource management (HRM) decisions on the adoption of high-performance human resource (HR) practices in small- and medium-sized enterprises (SMEs).

This study takes evidences from 157 HR decision makers in SMEs who autonomously make the decisions in the HR area and were responsible for the HR practices in their firm. The authors used multiple linear regression analysis to test the hypotheses.

Results show that both the EI and the different EI competencies of which it is comprised affect the adoption of various HR practices. Thus, the main theoretical contribution of this work stems from the incorporation of a psychological variable (EI) as an antecedent of HRM. Managers of the SME will find guidance about which emotional competencies are the most important for them to be more successful in their roles and for improving HRM.

First, the sample of firms the authors studied is limited to a specific geographic area in one country – Spain (Canary Islands) – that will necessarily limit generalisation of the results obtained to other populations of SMEs. Researchers should replicate the current model in other geographic areas. Second, and with regard the methodology, researchers could explore other tools to measure EI and emotional competencies. It would be interesting to measure this construct using qualitative analytical techniques, with 360 – or 180 – degree tools. Finally, the current study is cross-sectional in nature, which limits our ability to draw causal inferences from the data. This cross-sectional design prevents us, for example, from analysing EI’s influence on the continued development of high-performance HR practices over time. Future research using longitudinal methodologies to study these variables could provide additional advances in this area. This work makes important contributions to both the literature and the business world. With regard to the theoretical implications, results confirm that EI as a whole, as well as in terms of its specific emotional competencies, affects the decision making related to the adoption of high-performance HR practices, which is known to contribute to the organisational performance.

With regard its practical implications, SMEs’ owners-managers and HR practitioners may find our results and conclusions interesting. Indeed, recommendations in business management have often been accompanied by new approaches in HRM (Kent, 2005), as this study proposes. In particular, managers will find evidence of how a decision-maker’s higher EI propitiates the adoption of high-performance HR practices, thus being able to improve HRM in their SMEs. Moreover, managers will obtain guidance on which emotional competencies are the most important for adopting each HR practice, and so find greater success in their HRM roles. SMEs could organise programmes to develop the HR decision-maker’s emotional competencies, as large firms do for their executives.

Thus, the main theoretical contribution of this work stems from the incorporation of a psychological variable (EI) as an antecedent of HRM. Managers of the SME will find guidance about which emotional competencies are the most important for them to be more successful in their roles and for improving HRM.

This paper aims to study the extent of use of artificial intelligence (AI) in the modern organization; to comprehend the changing nature of future jobs in the context of application of AI; and to study the impact of AI on the economy of the country with special reference to the job market. Given the critical scenario of labor intensive Indian economy, the paper intends to show how AI shall affect rather coexist with human intelligence or labor.

The research on implementation of AI in different industries and its effect on job market are at a nascent stage. There is a dearth of literature. Hence, this study followed a qualitative approach to have a better understanding of the research questions as Bhattacherjee (2012) confirms that employing an interpretive paradigm (qualitative analysis as the analysis of data, e.g. data from interview transcripts) is the more productive way to study social order and that it is achieved through “subjective interpretation of participants involved, such as by interviewing different participants and reconciling differences among their responses using their own subjective perspectives”. Sample selection: The selection technique utilized is purposive sampling. The respondents in this research are the general managers and HRs from different companies. A total of 14 senior professionals from various sectors were approached for the interview out of which seven people gave their consent to take interview. Seven senior HR professionals, mainly general managers and HRs from various sectors viz. oil and gas sector, manufacturing, healthcare, construction, media, power and energy and retail were interviewed to understand how they are using AI in their respective fields. Inclusion Criteria: (1) Generally, the people covered under the research are from the decision-making level of their companies so they are in a position to give strategic perspective as well as day to day implication of implementation of AI. (2) Respondents have adequate knowledge of the respective industry to which they belong. (3) Respondents have reasonable industry of dealing with Human Resource Management and national economy as a whole assessment tool and its administration procedures. A narrative approach was adopted to have a better understanding of the research questions and comprehend their views regarding implementation of AI in their respective companies. A semi structured open ended interview was administered to steer the discussion around the research questions. The respondents were interviewed over the phone and each respondent shared their stories. Analysis of data: The narrations were then transcribed by online transcriber website otter.ai.com. The common keywords as prescribed by the website are as: AI, strategy, learning and implementation. The extracts of the discussions are noted in the next segment of the paper. As and when required this research also used secondary data from the journals, literature available in the websites to understand the implementation of AI globally.

A country where the government itself admits 90% of its workforce belongs to informal sector and conspicuously exits a multi-faceted stark digital divide (Huberman, 2001; DiMaggio et al., 2001; Guillen, 2006; Servon, 2002) wherein gap of digital divide is significant between the rural and urban India (Dasgupta et al., 2002; Nath, 2001; Singh, 2007; Mahajan, 2003; Dutta, 2003) talking of educating, applying and implementing AI seems to be “ a distant dream” but an “ambiguous ambition ”

Prior to implementation of AI that India has to ensure, the basic hygiene factors of informal sector labor force like social security, 2008, low wages and lack of legal protection, unpaid overtime and occupational health problems, poor bargaining power, working without leave under coercion, child care issues and health ailments(for which mere legislation or statutarization is just a formality executed than taking real action) to take the majority of Indian workforce to attain the motivational factor to acquire the knowledge and skill of AI and to implement it.

The AI and its adoption are still at their embryonic stage in Indian companies. With the adoption of such sophisticated technology, in one side, the organizations are dreaming of efficiency, higher productivity and better organizational performance whereas on the other side requirement of changing skill sets and decreasing manpower, creating fear among the mass, which results in hard resistance against the implementation process of AI. On the other hand, lack of expertise and high cost of adoption is also hindering AI to implement in the organizations. The adoption and implementation stage of AI vary from organization to organizations, as well as functions to functions. While the marketing departments of several organizations are using advanced level of AI, there, the HR departments are using AI at the very initial stage. But it is evident from the above discussions that adoption of AI in business functions is inevitable and only it is a matter of time. With the COVID-19 pandemic this has become the utmost necessity for many organizations, particularly who works across the globe. HR partners of the businesses are also adopting AI at a fast pace to do away with the mundane works and deliver efficient services to the stakeholders. It is understood from the discourse that the prerequisite for a successful implementation of AI across the industries throughout the country, needs a concerted effort from industries, academia and government.

The answer lies in Keynesian economics. The central tenet of which is government intervention rather investment to stabilize and progress the economy by way of spreading Internet connectivity, basic literacy and computer literacy, then only truly AI can be effective in a greater scale.

A study on application of artificial intelligence in the pandemic era from a wider perspective, this work is an empirical investigation into the benefits and limitations of artificial intelligence for human potential and labour -intensive pandemic ridden Indian economy.

This paper aims to specifically focus on the challenges that human resource management (HRM) leaders and departments in contemporary organisations face due to close interaction between artificial intelligence (AI) (primarily robots) and human workers especially at the team level. It further discusses important potential strategies, which can be useful to overcome these challenges based on a conceptual review of extant research.

The current paper undertakes a conceptual work where multiple streams of literature are integrated to present a rather holistic yet critical overview of the relationship between AI (particularly robots) and HRM in contemporary organisations.

We highlight that interaction and collaboration between human workers and robots is visible in a range of industries and organisational functions, where both are working as team members. This gives rise to unique challenges for HRM function in contemporary organisations where they need to address workers' fear of working with AI, especially in relation to future job loss and difficult dynamics associated with building trust between human workers and AI-enabled robots as team members. Along with these, human workers' task fulfilment expectations with their AI-enabled robot colleagues need to be carefully communicated and managed by HRM staff to maintain the collaborative spirit, as well as future performance evaluations of employees. The authors found that organisational support mechanisms such as facilitating environment, training opportunities and ensuring a viable technological competence level before organising human workers in teams with robots are important. Finally, we found that one of the toughest challenges for HRM relates to performance evaluation in teams where both humans and AI (including robots) work side by side. We referred to the lack of existing frameworks to guide HRM managers in this concern and stressed the possibility of taking insights from the computer gaming literature, where performance evaluation models have been developed to analyse humans and AI interactions while keeping the context and limitations of both in view.

Our paper is one of the few studies that go beyond a rather general or functional analysis of AI in the HRM context. It specifically focusses on the teamwork dimension, where human workers and AI-powered machines (robots) work together and offer insights and suggestions for such teams' smooth functioning.