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The association between human leukocyte antigen (HLA) types and blood group alloimmunization remains unclear. Previous studies have predominantly focused on predicting immunization events in cancer immunotherapy, but not blood group antigens. In this study, we investigated whether HLA peptide binding could predict the immunogenicity of blood group antigens. We performed in silico binding analysis of Rh antigens and representative HLA class II alleles using NetMHCpan-4.1 and NetMHCIIpan-4.1 algorithms. The distribution of strong binding regions (hotspots) differed across HLA loci and ethnic groups. In particular, the RhD and RhCE antigens showed several distinct hotspots for the HLA-DRB, -DQA-DQB, and -DPA-DPB HLA class II peptides. A hotspot of RHD*01W.1 in HLA-DRB had a substitution in p.Val270Gly. The number of hotspots and core amino acids was different for each HLA locus, and the amino acid regions (exofacial, transmembrane, and intracellular region) differed among the hotspots. Our findings underscore the significance of immunogenicity between the Rh antigens and HLA-DR, suggesting the potential clinical utility of predicting antibody development in blood transfusions. This in silico approach offers novel insights into understanding and managing alloimmunization events, particularly in patients with multiple alloantibodies when blood transfusion is required.

Purpose Human resource analytics (HRA) is an HR activity that companies and academics increasingly pay attention to. Existing literature conceptualises HRA mostly from an objectivist perspective, which limits understanding of actual HRA activities in the complex organisational environment. This paper therefore draws on the practice-based approach, using a novel framework to conceptualise HRA-as-practice. Design/methodology/approach The authors conducted a systematic literature review of 100 academic and practitioner-oriented publications to analyse existing HRA literature in relation to practice theory, using the \"HRA-as-practice\" frame. Findings The authors identify the main practices involved in HRA, by whom and how these practices are enacted, and reveal three topics in nomological network of HRA-as-practice: HRA technology, HRA outcomes and HRA hindrances and facilitators, which the authors suggest might actualize enactment of HRA practices.Practical implicationsThe authors offer HR function and HR professionals a basic ground to evaluate HRA as a highly contextual activity that can potentially generate business value and increase HR impact when seen as a complex interaction between HRA practices, HRA practitioners and HRA praxis. The findings also help HR practitioners understand multiple factors that influence the practice of HRA. Originality/value This systematic review differs from the previous reviews in two ways. First, it analyses both academic and practitioner-oriented publications. Second, it provides a novel theoretical contribution by conceptualising HRA-as-practice and comprehensively compiling scattered topics and themes related to HRA.

Firms have recognized the opportunities presented by HR analytics; however, it is challenging for HR to convert their available data (sources) into meaningful strategical value. Moreover, research on the implementation and application of HR analytics is still in its infancy. Drawing on the socio-technical system perspective, we examine the implementation and application of HR analytics in firms. Based on a qualitative study with 17 HR analytics experts, we find that a shift to a more process-oriented perspective on HR analytics is needed. More precisely, besides the requirements for the analysis of data, the actual roles in the process of implementing and applying HR analytics need to be defined. In particular, this implies the interaction between the specialist department, the HR business partner and the HR analytics function. From a managerial perspective, we propose a process model for the future implementation and application of HR analytics.

This study aims to explore how and why human resource analytics, which involves using data analysis for HR-related decisions, is being adopted by Indian IT companies. It also seeks to understand the challenges faced in implementing these analytics and which analytical tools are commonly used. To achieve these goals, researchers collected and analyzed 478 responses from individuals working in the Indian IT industry. They used a software called AMOS version 21.0 to test their ideas. This software helps researchers understand relationships and patterns in data. The study found that certain factors, called “antecedents,” influence the adoption of HR analytics in IT organizations in India. It also revealed that problems with data, such as not having enough data or having data of low quality, were significant challenges in using HR analytics. Additionally, the research showed that many professionals in the Indian IT industry prefer using analytical tools like R and Power BI for HR analytics. The results of this study have important implications for businesses and HR professionals. By understanding the factors that influence the adoption of HR analytics, companies can make better decisions about how to implement these practices. Recognizing the challenges related to data quality and quantity can help organizations address these issues. Knowing which analytical tools are popular can guide companies in selecting the right tools for their HR analytics needs. Overall, this research provides valuable insights that can facilitate the adoption of HR analytics in various industries, not just in India. It’s important to note some limitations of this study. The research focused specifically on the Indian IT industry, so the findings may not apply equally to other sectors or regions. Additionally, the study used a specific software (AMOS version 21.0) and analyzed a specific number of responses (478), which could limit the generalizability of the results. Further research in different contexts and with larger samples may be needed to confirm these findings more broadly.

Purpose The purpose of this paper is to develop a multistakeholder scale for assessing an excellent human resource (HR) function to demonstrate the extent to which it is focused on creating value from the perspective of its key internal and external stakeholders. Design/methodology/approach At the first stage, an in-depth literature review was conducted to extract the best practices for an excellent HR function. Then, to test the validation of the developed framework, it was sent to HR academics and practitioners in different countries. The survey responses were analyzed using the methods of the structural equation modeling (SEM) and confirmatory factorial analysis. Findings This study proposes an excellent HR multistakeholder assessment scale consisting of ten criteria based on the perceptions of internal and external HR stakeholders. Research limitations/implications This study suggests a framework for assessing overall HR excellence based on the perceptions of key internal and external HR stakeholders. In addition, it is recommended that future researchers empirically test the developed scale across various industries and firm sizes. Practical implications HR managers, by using this framework, could continuously assess their HR excellence and compare their HR excellence with other companies’ HR excellence in the industry and then plan for continuous improvement in different HR areas to improve their stakeholders’ experiences. Originality/value This paper identifies the enablers and results of an excellent HR department and designs a multistakeholder feedback scale to better understand key internal and external HR stakeholders’ perceptions.

PurposeThis paper aims to identify the current research trends and set the future research agenda in the area of human resource (HR) analytics by an extensive review of the existing literature. The paper aims to capture state of the art and develop an exhaustive understanding of the theoretical foundations, concepts and recent developments in the area.Design/methodology/approachA portfolio of 125 articles collected from the Scopus database was systematically analyzed using a two-tier method. First, the evolution, current state of the literature and research clusters are identified using bibliometric techniques. Finally, using content analysis, the research clusters are studied to develop the future research agenda.FindingsBased on the bibliometric analysis, network analysis and content analysis techniques, this study provides a comprehensive review of the existing literature. The study also highlights future research themes by identifying knowledge gaps based on content analysis of research clusters.Research limitations/implicationsThe evolution and the current state of the HR analytics literature are presented. Some specific research questions are also provided to help future research.Originality/valueThis study enriches the literature of HR analytics by integrating bibliometric analysis and content analysis to develop a more systematic and exhaustive understanding of the research area. The findings of this study may assist fellow researchers in furthering their research in the identified research clusters.

Background: Two novel systemic inflammation indices, SII and SIRI, are associated with increased risk of cardiovascular diseases (CVD). However, SII and SIRI are prone to change over time and the association between changeable status and long-term outcome risk remains to be uncovered. This study aims to examine the association between the dynamic status of SII and SIRI and risk of CVD. Methods: This prospective study included a total of 45,809 subjects without MI, stroke and cancer prior to or in 2010 (baseline of this study). The dynamic status of SII and SIRI during 2006, 2008, and 2010 was assessed by dynamic trajectories (primary exposure), annual increase, and average value. The outcome was CVD incidence during 8.6 years' follow-up. Multiple Cox regression models were used to calculate the adjusted hazard ratios (HRs) and confidence intervals (95% CIs). Results: Four dynamic trajectories of SII and SIRI were identified as follows: low stable pattern, moderate stable pattern, increase pattern, and decrease pattern. For SII, compared with \"low stable pattern\", after controlling confounders and level of SII in 2006, adjusted HRs were 1.24 (95% CI = 1.02-1.51) for \"increase pattern\" and 1.11 (95% CI = 1.00-1.23) for \"moderate-stable pattern\" while the association was not significant for \"decrease pattern\". Additionally, the highest group of annual SII increase and average SII had respective HR of 1.20 (95% CI = 1.05-1.37) and 1.32 (95% CI = 1.13-1.55). The results were consistent for SIRI. \"Increase pattern\" and \"moderate stable pattern\" increased the risk of CVD by 38% (HR = 1.38, 95% CI = 1.17-1.63) and 12% (HR = 1.12, 95% CI = 1.01-1.25), while no significant association was found for \"decrease pattern\". The highest group of annual SIRI increase and average SIRI had respective HR of 1.25 (95% CI = 1.09-1.44) and 1.39 (95% CI = 1.19-1.63). Conclusion: Dynamic status of SII and SIRI was significantly associated with risk of CVD, which highlighted that we should focus on the dynamic change of SII and SIRI. Keywords: systemic inflammation, dynamic status, prospective study, cardiovascular diseases

Purpose – Prior research in the area of organizational change highlights the critical role played by HR practices during organizational change as it may require altering employee behavior to support the change direction. human resource (HR) function is considered to be well positioned to influence employee behavior by institutionalizing HR practices that support change. Further there is a significant body of literature that suggests that employee behavior is significantly influenced by the perceptions of HR practices during change. HR practices which create positive employee perceptions increase employee commitment to change. The purpose of this paper is to provide a conceptual framework that identifies critical HR practices that support organizational change and examines their impact on employee perception and commitment to change. Design/methodology/approach – First, an extensive literature review on organizational change at macro level has been done to identify critical practices desired from key organizational members during organizational change. Second, a case for importance of HR function as a key organizational member during change is presented. Further literature on effectiveness of HR practices adopted by HR professionals during organizational change is examined to find out the gap areas. Third, literature on employee perception and commitment to change is examined to find out possible linkages to HR practices during organizational change. Finally, eight propositions are presented to build an integrated conceptual framework identifying critical HR practices during organizational change and their impact on employee perception and commitment to change. Findings – The study suggests that HR practices undertaken in the area of culture, leadership, cross functional integration, training, communication and technology if introduced and implemented will positively influence employee perception reducing resistance and increasing commitment to change. Therefore assessing employee perception about critical HR practices at different stages of change initiation, implementation and consolidation can enable understanding about employee commitment to change. This would also help HR professionals understand how effective the HR practices implemented during change have been. Originality/value – This framework can be used by the researchers and practitioners to study, guide, frame and model empirical research into the area of studying critical HR practices during organizational change. So far literature provides a generic view of desired organizational practices during change. Moreover there are few studies available on employee perception about HR practices implemented during organizational change and its impact on employee commitment to change. The framework presented in this paper would help explore the effectiveness of specific HR practices implemented during change by evaluating its impact on employee perception and commitment to change.

PurposeThis paper aims to understand the role of perception of HR capability, HR service quality, along with HR inducements, which, in turn, provides satisfaction with HR practices and affects employee performance.Design/methodology/approachThe data of 155 managers have been collected through a questionnaire to understand the relationship among the studied constructs using partial least square structured equation modeling (PLS-SEM).FindingsThe results suggest that employers should attempt to create a positive perception by providing quality services in the HR domain, and quality services will certainly enhance employee performance.Originality/valueThis study is unique in terms of its contribution. This study has tried to link service quality and satisfaction to HR practices with employee performance. Further, it also shows that HR should be capable and have high HR inducements to provide the necessary and expected HR services, which leads to employee satisfaction with HR practices and employee performance.

This conceptual paper theorizes the emerging concept of personalized human resource management (HRM), which refers to HRM programs and practices that vary across individuals within an organization. As a subset of high-performance work practices (HPWPs), personalized HRM is implemented at the individual level and represents the next generation of HRM, which is characterized by the adoption of advanced HR analytics and artificial intelligence (AI) to provide tailored HR solutions. We argue that personalized HRM constitutes a unique source of sustained firm competitive advantage and offers additional beneficial performance effects on top of other HPWPs. Drawing on the theories of individual differences and person-organization fit, we explain why personalized HRM outperforms traditional standardized HRM in terms of productivity, favorable HR climate, flexibility, return on investment of HRM, and firm financial performance. We also suggest that business strategy is a moderator of the relationship between HRM and firm performance. Building on the AI job replacement theory, we further propose that the mechanical and analytical intelligence (intuitive and empathetic intelligence) required for personalized HRM tasks is positively (negatively) related to the adoption of AI. Lastly, we elaborate on the implications and explain how advanced HR analytics and AI can facilitate the transition toward personalized HRM.