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The purpose of this study is to explore the mechanism of digitalized transformation in organizations’ human resource management (HRM). This study summarizes three basic factors driving the digital transformation process in China: level of perception, level of application and speed of transformation.

This study analyzes the strategic transformation process of HRM in Haier, Hisense and Chambroad to explore the human resource digital transformation mechanism in Chinese enterprises.

The results of this study show that three HR value chain models can be constructed based on how well HRM deals with business: the efficiency-oriented HRM value chain, quasi-business-oriented HRM value chain and business-oriented HRM value chain. The basic factors – level of perception, level of application and speed of transformation – are observed in the entire HRM digital transformation process.

This study provides theoretical and empirical insights for enterprises to explore the value of digital technology in HRM and facilitate the digital transformation of HRM.

HR analytics is a process for systematic computational analysis of data or statistics. It discovers, interprets and communicates significant patterns in data to enable evidence-based HR research and uses analytical insights to help organizations achieve their strategic objectives. However, its adoption and utilization among HR professionals remain a subject of concern. This study aims to determine the reasons that facilitate or inhibit the acceptance of HR analytics among HR professionals in the banking, financial services and insurance (BFSI) sector.

A sample of 387 HR professionals in BFSI firms across India was collected through non-probabilistic purposive sampling. Structural equation modeling was applied to analyze the association between predetermined variables. In addition, the predictive relevance of “Data Availability” was analyzed using hierarchical regression.

The results revealed that data availability, hedonic motivation and performance expectancy positively influenced behavioral intention (BI). In contrast, effort expectancy, social influence and habit had an insignificant effect on BI. Also, facilitating conditions (FCs), habit, BI achieved a variance of 60% in HR analytics use. The use behavior of HR analytics was significantly influenced by FCs and BIs.

This study focuses on insights into the elements that influence HR analytics adoption, revealing additional light on success drivers and grey areas for failed adoption.

This research adds to the body of knowledge by identifying factors that hinder the adoption of HR analytics in Indian organizations and signifies the relevance of easy accessibility and availability of data for technology adoption.

Our proposed machine learning model contributes to improving the quality of Hire by providing a more nuanced and comprehensive analysis of candidate attributes. Instead of focusing solely on obvious factors, such as qualifications and experience, our model also considers various dimensions of fit, including person-job fit and person-organization fit. By integrating these dimensions of fit into the model, we can better predict a candidate’s potential contribution to the organization, hence enhancing the Quality of Hire.

Within the scope of the investigation, the competencies of the personnel working in the IT department of one in the largest state banks of the country were used. The entire data collection includes information on 1,850 individual employees as well as 13 different characteristics. For analysis, Python’s “keras” and “seaborn” modules were used. The Gower coefficient was used to determine the distance between different records.

The K-NN method resulted in the formation of five clusters, represented as a scatter plot. The axis illustrates the cohesion that exists between things (employees) that are similar to one another and the separateness that exists between things that have their own individual identities. This shows that the clustering process is effective in improving both the degree of similarity within each cluster and the degree of dissimilarity between clusters.

Employee competencies were evaluated within the scope of the investigation. Additionally, other criteria requested from the employee were not included in the application.

This study will be beneficial for academics, professionals, and researchers in their attempts to overcome the ongoing obstacles and challenges related to the securing the proper talent for an organization. In addition to creating a mechanism to use big data in the form of structured and unstructured data from multiple sources and deriving insights using ML algorithms, it contributes to the debates on the quality of hire in an entire organization. This is done in addition to developing a mechanism for using big data in the form of structured and unstructured data from multiple sources.

The main goal of the article is to determine the mediating role of HRM outcomes in the relationships between staffing the organization and company performance results and to establish whether there are any identifiable regularity in this scope in the pre-pandemic and pandemic period in the HQs and foreign subsidiaries of MNCs.

The empirical research included 200 MNCs headquartered in Central Europe. To capture the actual relations between the variables under study the raw data in the variables were adjusted with the efficiency index (EI). The Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to verify the research hypotheses and assess the mediating effects.

The research findings show that, with the exception of the HQs in the pandemic period, when staffing had a negative effect on the company performance results in quality, in other cases it had a positive effect on results in HRM, finance, innovativeness and quality, both in the pre-pandemic and pandemic period, although this effect was not always statistically significant. Furthermore, the company's performance results in HRM mediate positively the relationships between staffing and the other three categories of company performance results, regardless of the organizational level (HQs' or subsidiaries') and time period under consideration. Additionally, during the pandemic, the company's performance results in HRM mediate the relationships between staffing and the other company's performance results stronger than in the pre-pandemic time.

In addition to confirming the results of some other studies, the article also provides new knowledge. It determines the mediating role of HRM outcomes in the relationship between staffing and company performance results in finance, innovativeness and quality. Moreover, it identifies certain regularities in the four studied contexts, which is a novelty in this type of research. It also uses an innovative approach to including employee KPIs as the efficiency index in analyzing the relationships between the variables under study.

Upon the premises of social exchange theory (SET), this study aimed at hypothesizing and examining a serial mediation model that investigated the underlying mechanism through which a high-performance work system (HPWS) affects individuals’ future time perspective (FTP).

The hypothesized relationships were examined using responses collected from 275 employees from 15 local private banks and 40 established branches through a proportionate stratified sampling technique. The statistical package for social sciences (SPSS) PROCESS macro 3.0 and analysis of moment’s structure (AMOS) 24.0 were employed for data analysis purposes.

The study revealed that HPWS is indirectly related to the individuals’ FTP through workplace social courage (WSC) and employee well-being (EWB) sequentially. Prescriptions for theoretical and managerial implications were discussed, and future research viewpoints with limitations were acknowledged.

This study illuminated the underlying mechanism and theoretical logic linking HPWS and individuals’ FTP by proposing the serial mediating effect of WSC and EWB.

This study aims to identify the enablers of human resource (HR) digitalization and HR analytics. This paper also aims to build a relationship map using interpretive structural modeling.

A systematic literature review is used to identify the key enablers of HR digitalization and HR analytics. Ten expert opinions have been taken from the key officials of IT firms located in New Delhi North Central Region.

This study is focused on the enablers of HR analytics. It is found that change management (CM) in the organization is the key enabler of implementing HR digitalization and analytics in an organization. However, other elements like learning culture, training and development, E-learning management and HR transformation (HRT) play a vital role in implementing HR analytics. It is also found that implementing artificial intelligence for HR practices is the ultimate goal for every organization.

Management teams in IT firms should focus on the continuous learning process in the organization. The CM should be expedited for digitalization and adoption of HR analytics. Managers must go through the ramification of HRT, which possesses diligence in HR analytics and artificial intelligence.

This study explicitly talks about the enablers of HR digitalization and HR analytics. It also explores the relationship between the enablers. This study also describes the driving and dependence power of all the enablers.

The continued relevance of technologies in halal industries requires managers to understand the factors contributing to such technologies’ acceptance. The technology acceptance model (TAM) is dominant in the literature that predicts user acceptance and behaviour towards technology. Despite the model’s significance, there has yet to be a systematic review of studies featuring halal sectors that use TAM. The purpose of this study is to systematically review the existing literature on TAM in halal industries to understand the research trends as well as TAM modifications and research opportunities in halal industries.

Guided by the preferred reporting items for systematic review and meta-analysis protocol, a framework-based review using the theories, contexts, characteristics and methods (TCCM) framework was conducted. The Scopus and Web of Science databases were used to retrieve English journal articles that investigated TAM in the context of halal markets. In total, 44 eligible articles were reviewed in terms of the developments and extensions of TAM in their studies across the halal industries.

The first study related to the use of TAM in the context of halal industries was published in 2014. The most prominent halal industry in the review, which used TAM, was Islamic finance. Indonesia was the leading economy in halal studies using TAM. Perceived usefulness was found to be a more significant factor than perceived ease of use for technology acceptance in TAM studies on halal industries. The significance of religiosity on TAM was inconsistent. Most research was done using quantitative surveys with consumers as the target sample.

The studies in this review are based on the Scopus and Web of Science databases, which may be perceived as a study limitation. This study also only considered English journal articles and research in which the focus was on the use of TAM in halal industries rather than general industries with Muslim consumers.

Halal industries will continue to rely on technology for the provision of goods and services. With the rise of emerging technological innovations, this review will provide managers with an appreciation of technology acceptance across different contexts. Researchers can use the results of this review to guide future studies and contribute toward the development of this research area.

This review contributes to the Islamic marketing literature by being the first to comprehensively review the TAM model in the context of halal industries using the TCCM framework-based review approach. A research agenda is proposed to advance research on technology acceptance and TAM in halal industries.

The purpose of this paper is to research the impact of digitalization on employees' future competencies and the conditional role of human resource development (HRD) in the relationship between independent and dependent variables.

Empirical research covered 1209 enterprises from all of Slovakia, Poland and the Czech Republic. The research was conducted from 2019 to 2021. Using structural equation modeling (SEM), a theoretical model was tested and verified.

Confirmatory factor analysis has shown a good fit for the tested model. The purpose and character of our data showed a good alignment with the SEM partial least squares method, as the goal is to predict a construct. The model showed that employee-oriented digitalization positively affected the employees' future competencies, with no impact of customer-oriented digitalization treated as a control variable. Also, the moderating role of HRD has not been shown to be significant for the “digitalization – competencies” relationship.

Previous studies on the development of personnel competencies treated these competencies as antecedents of digital transformation and examined the formal role of HRD in building the competencies. The novelty of this study lies in exploring the pattern of interactions among the impact of an environment built by innovative technologies and HRD on the competencies of the future. Also, the research embedded in the environment of Poland, the Czech Republic and Slovakia has contributed to the complex understanding of the transition to digitalization, as this region has often been omitted in the field of human resource management (HRM) research focused on exploring digital transformation.

Considering the significant increase in researchers’ interest in human resource management (HRM) in the public sector domain, this study aims to focus on producing a scale of HRM practices customized for the context of public organizations.

Experts and semantic analysis were performed for the scale development (qualitative stage), and exploratory and confirmatory factor analysis through structural equation modeling was conducted for the scale validation (quantitative stage).

The public HRM practices scale (public HRMPS) is composed of 19 items, distributed along four factors/dimensions, named training, development and education; relationship; work conditions; and competency and performance appraisal. The scale showed evidence of internal and construct validity (convergent, divergent, criterion-related and discriminant), as well as reliability and content validity.

The public HRMPS can be applied in relational studies to test structural models of prediction, mediation and moderation to evaluate relationships with organizational behavior variables, such as leader-members exchange, engagement at work, life quality at work and well-being at work, among others.

The public HRMPS may also serve as a useful diagnostic tool for the decision-making process made by public managers so they can promote a strategic, evidence-based HRM. Furthermore, the transforming role of strategic HRM can be operationalized by adopting practices gathered in the public HRMPS, advancing toward new HRM strategies to promote healthier and more productive work environments.

Healthier and more productive environments translate into real impacts for society, the first beneficiary of public services with more quality, efficiency and accountability.

The public HRMPS is the first attempt to produce an operationally valid and reliable measure to evaluate strategic HRM practices, responding to calls in the literature concerning the need for an integrated, comprehensive and customized HRM practices scale for the public service context.

In the literature, evidence is to be found of the positive effect of high-performance work systems (HPWSs) on innovation in firms. However, innovation is enabled by not only human resources but also digital technology, and scholars have called for further investigation into the interplay between digital technology and HRM systems. Drawing on signalling theory and HPWSs research, the purpose of this study is to explore the moderating role of digital technologies in the relationship between HPWSs and innovation in the firm and consider employee participation as an additional conditioning factor.

This study uses data from the European Company Suvery 2019 administered in a sample of more than 20,000 European establishments and applies logistic regression with a three-way interaction.

HPWSs underpin product and process innovation. Moreover, this study shows that in firms with low levels of employee participation, digital technology enhances the effect of HPWSs on innovation, while in firms with high levels of employee participation, this effect is reduced.

This study enriches the scholarly discussion about the link between HPWSs and innovation in the firm, by investigating in theoretical and empirical terms the moderating effect of digital technology, underlining that either positive or negative synergistic effects are possible. By adding employee participation to the analysis, the authors cast light on an important boundary condition for understanding when the synergic effects become more prominent. This intends to respond to recent calls from scholars and practitioners for more insight into the precise nature of the synergies between HPWSs and digital technology on innovation in the firm, with important implications for management.