Search results

The disruptive human resource management (HRM) technologies are now considered a significant facilitator to change and benefit the entire HRM landscape. This view needs to be further verified by reviewing the knowledge on the subject in the empirical research landscape. Thus, the study's objectives were to find (1) the current knowledge and (2) the areas where empirical research is lacking in disruptive HRM technologies.

The article is a literature review that was followed by the systematic literature review and the preferred reporting items for systematic reviews and meta-analyses (PRISMA). The review considered 45 articles published during the 2008–2021 period extracted from the Scopus database, and bibliometric analysis was performed to achieve the research objectives.

The results found that scholarly attention has been given to electronic HRM (E-HRM) rather than the disruptive HRM technologies. The areas investigated include the determinants of intention, adoptions and use of E-HRM and the outcomes of E-HRM adoptions and use. These outcomes can be further divided into general outcomes and HRM outcomes.

The findings reveal gaps in E-HRM research and disruptive HRM technologies remain untapped in the empirical research landscape. Hence, the study findings provide some implications for future research and applications.

The study found empirically proven determinants of E-HRM intention, adoptions and use and E-HRM adoptions and use outcomes. These were found in the studies conducted during the 2008–2021 period.

顛覆性人力資源管理技術被認為是一個可改變、並幫助整個人力資源管理格局的重要誘導者; 這個看法、需透過檢核在實證研究範疇裡就有關議題的資料、才能作進一步的核實。因此，本研究擬了解 (1): 我們目前對有關議題的認知，以及 (2): 就顛覆性人力資源管理所進行的實證研究有哪些不足之處。

本文是一個文獻探討。研究人員採用系統文獻綜述研究法，以及系統綜述和 meta分析的首選報告項目。研究涵蓋45篇於2008年至2021年期間發表的學術文章; 這些文章均取自 Scopus資料庫。研究人員進行文獻計量分析，以達到研究的目標。

研究結果顯示、被研究探索的是電子化人力資源管理 (E-HRM) ，而不是顛覆性人力資源管理技術。被研究的範疇包括使用電子化人力資源管理的決定因素，以及使用後的結果。使用後的結果再細分為一般性的結果、和與人力資源管理有關的結果。

研究結果顯示、在實證研究的範疇裡，電子化人力資源管理和顛覆性人力資源管理技術的研究均存在未被探索的研究缺口。因此，研究結果為今後的研究和有關的應用提供了啟示。

本研究發現並確認經實證證明的使用電子化人力資源管理的決定因素，以及使用後的結果。研究結果乃基於檢核於2008年至2021年期間進行的學術研究而得來的。

顛覆性人力資源管理技術、系統文獻綜述、系統綜述和meta分析的首選報告項目 (PRISMA)

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 investigate the mediating role of perceived organizational politics on the relationship between electronic human resource management (e-HRM) use and e-HRM macro-level consequences.

The paper uses a cross-sectional survey of HR professionals, line managers and information technology specialists. A purposive stratified sampling technique is employed. The analyses of data make use of regression and process macro in SPSS analysis.

The effect of e-HRM use on e-HRM macro-level consequences is partially mediated by perceived organizational politics.

Organizations can invest in e-HRM use alongside other HR practices such as, emotional intelligence training, to reduce the negative effects of perceived organizational politics and in the process enhance employee attitudes and performance.

The study enriches the scope through which the interaction between e-HRM use and perceived organizational politics is viewed. The study was conducted in Zimbabwe, demonstrating that the indirect effect of e-HRM use on e-HRM macro-level consequences is not limited to developed economies.

This study examines the adoption of information and communication technologies (ICT) for e-recruitment and its impacts on public value outcomes.

A survey was conducted with 213 public sector employees in the federal civil service using a questionnaire to test a conceptual model integrating the Technology Acceptance Model, Media Richness Theory and Public Value Theory using PLS-SEM analysis.

Results validate significant positive relationships between ICT adoption, social media use for e-recruitment and public value creation. Internet self-efficacy positively moderates public value outcomes.

While this study makes valuable contributions, avenues remain to further expand generalizability, strengthen validity and incorporate additional institutional factors in the framework.

The study provides insights to guide policies and interventions aimed at improving ICT adoption success and public value gains from e-government investments in developing countries.

The research makes key contributions by operationalizing and empirically assessing the public value impacts of e-government innovations and examining adoption issues in an understudied developing country context.

The current era of the fourth industrial revolution has attracted significant research on the use of digital technologies in improving construction project delivery. However, less emphasis has been placed on how these digital tools will influence the management of the construction workforce. To this end, using a review of existing works, this chapter explores the fourth industrial revolution and its associated technologies that can positively impact the management of the construction workforce when implemented. Also, the possible challenges that might truncate the successful deployment of digital technologies for effective workforce management were explored. The chapter submitted that implementing workforce management-specific digital platforms and other digital technologies designed for project delivery can aid effective workforce management within construction organisations. Technologies such as cloud computing, the Internet of Things, big data analytics, robotics and automation, and artificial intelligence, among others, offer significant benefits to the effective workforce management of construction organisations. However, several challenges, such as resistance to change due to fear of job loss, cost of investment in digital tools, organisational structure and culture, must be carefully considered as they might affect the successful use of digital tools and by extension, impact the success of workforce management in the organisations.

This book aimed to conceptualise a construction workforce management model suitable for effectively managing workers in construction organisations. To this end, this chapter presents the conceptualised model, which consists of seven workforce management practices with their respective measurement variables. Drawing from existing theories, models, and practices, the chapter concludes that a construction organisation that will attain its strategic objectives in the current fourth industrial revolution era must be willing to promote effective recruitment and selection, compensation and benefits, performance management and appraisal, employee involvement and empowerment, training and development, as well as improving workers emotional intelligence and handling external environment pressure. These practices can promote proactiveness, participation, and improved skills and can lead to effective commitment, better quality, and flexibility within the organisation.

This study investigates the psychological adoption of technology in relation to employees' mental beliefs about using technology in their workplace, because it is necessary to investigate the direct and indirect effects of information systems (IS) on employees' work-related results that underpin creativity and engagement.

Using a cross-sectional design, data were collected from 153 human resource (HR) employees who used human resource information systems (HRIS) in small- and medium-sized enterprises (SMEs) in Malaysia.

The results show that effective acceptance and adoption of an HRIS enables HR employees and management in SMEs to be creative, balanced and engaged. Facilitating conditions and task-technology fit positively affect the behavioral intention to accept and adopt an HRIS. Additionally, organizational citizenship behavior moderates the relationship between the behavioral intention to accept and adopt an HRIS and employee creativity.

This study significantly advances the fields of human resource management and IS by elucidating the factors influencing employees' adoption of technology. In an effort to address a research gap in existing research, it introduces a unified theory of acceptance and use of technology, which precedes the psychological adoption process by individuals. Furthermore, it offers both empirical and theoretical insights into the interplay between technology adoption factors and their subsequent impact on work-related outcomes.

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.

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.