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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.

Over the last several years, it has been clear that HR departments rely heavily on their own pieces of technological infrastructure. For improved time management, efficiency in working, productivity, managing remuneration, assessing personnel, recruiting candidates via online methods, etc., technology is being used across all areas of human resources. All of this require technology, and in this qualitative study, the author has attempted to compile the technologies used across all of the verticals, as well as their impact on HR functioning and the ways in which the Human Resource Information System (HRIS) is used within the organization. HRIS have modified HR administrative work and improved the business, allowing HR to rise from the tiers of management, administration, and maintenance to the level of core business and strategy.

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)

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.

Smart HR 4.0 is a new concept characterized by adopting innovative technologies of Industry 4.0 (I4.0) in the HR domain. This study attempts to identify the key factors of Smart HR 4.0 to foster organizational innovation ambidexterity.

Based on review of literature and survey from expert opinions by using the Delphi method, 12 factors were found most suitable for this study. Further, the fuzzy-TISM technique was used to establish contextual relationships and develop a hierarchical model on the identified factors. Subsequently, the MICMAC analysis was applied to classify these factors according to their driving and dependence power.

This study framed a conceptual hierarchical model of Smart HR 4.0 and established contextual relationships among identified factors. Result shows that smart organic structure, industry–institute interface, IT-enabled system and ambidextrous leadership are important factors as they have the highest driving power. Further, knowledge management, learning culture and psychological empowerment are the linkage factors having both driving as well as dependency power in the whole system.

This study can guide the managers in smoothly implementing these practices to manage their human capital amidst digital disruption, ensuring innovation competitiveness of the firm. The structural hierarchical framework of Smart HR 4.0 may serve as a blueprint for HR professionals and business leaders to attain organizational innovation ambidexterity in the current wave of digital disruptions (Industry 4.0).

This study provides a holistic model of smart HR 4.0 integrating innovation ambidexterity in I4.0.

This study aims to explore the emergence of the human resource (HR) analyst role. The job posts on LinkedIn display the industry demand and skills required by the organizations. This study identifies the different knowledge, skills and abilities (KSA) required for an HR analyst role in different stages of professional growth (i.e. entry-level, middle-senior level and top-level) across different industries/sectors as applicable to the crisis.

A total of 80 job posts were extracted from LinkedIn. Details such as industry, job levels, qualifications, job experience, job functions, job descriptions (JDs) and job skills (JS) were collected. Further, 30 videos were extracted from YouTube and converted into text. Text analysis was conducted using NVivo software to analyze JDs, JS and job functions. Using NVivo, word frequency, word cloud, word tree and treemap were created to visualize the data. Finally, ten in-depth interviews were conducted with senior HRA managers based in India to understand the essential competencies required for the HR analyst role and the strategies to develop them.

The findings indicate that not only technical skills are needed, but business and communication skills are particularly important for all job levels during a crisis. The JD word cloud showed words, such as data, business, support and management, and the word tree depicted HR data and change agents as important words with many related sentences as branches. General JS included analytical, communication, problem-solving and management. Technical JS were the most widely used and included structure query language, system applications & products in data processing, human capital management, TABLEAU, management information system and PYTHON. Strategies to develop these competencies included case studies, live projects, internships on HR analytics (HRAs) assignments and mentoring by senior HRA professionals.

The sample used was small, as the study included 80 job posts available on LinkedIn restricted to India. The study was restricted to qualitative approach and text analytics was used. Survey methods and a quantitative approach can be used to collect data from HR recruiters, job holders and senior leaders to understand the role of HRAs in the job market and then these variables can be tested empirically.

Based on the McCartney et al.’s (2020) competency model for the HR Analyst role, this study has explored the KSA framework using data visualization techniques and used text analytics to analyze LinkedIn job posts for different levels, videos from YouTube and in-depth interviews. It also mapped the KSA for the HR analyst role to the various stages of crisis system management given by Mitroff (2005). The use of social media analytics, such as analyzing LinkedIn data and YouTube videos, are highlighted.

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 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.